Lab experiments on shallow flows

2018 ◽  
Author(s):  
G. van Heijst ◽  
L. Kamp ◽  
M. Duran-Matute
Keyword(s):  
Shallow Flows ◽  
Lab Experiments

Attentional capture helps explain why moral and emotional content go viral

2019 ◽  
Author(s):  
William J. Brady ◽  
Ana P. Gantman ◽  
Jay Joseph Van Bavel
Keyword(s):  
Social Media ◽  
Attentional Capture ◽  
Emotional Content ◽  
Limited Attention ◽  
Psychological Process ◽  
Emotional Stimuli ◽  
Political Leaders ◽  
Lab Experiments ◽  
Perceptual Systems ◽  
Shed Light

Our social media newsfeeds are filled with a variety of content all battling for our limited attention. Across three studies, we investigated whether moral and emotional content captures our attention more than other content and if this may help explain why this content is more likely to go viral online. Using a combination of controlled lab experiments and nearly 50,000 political tweets, we found that moral and emotional content are prioritized in early visual attention more than neutral content, and that such attentional capture is associated with increased retweets during political conversations online. Furthermore, we found that the differences in attentional capture among moral and emotional stimuli could not be fully explained by differences in arousal. These studies suggest that attentional capture is one basic psychological process that helps explain the increased diffusion of moral and emotional content during political discourse on social media, and shed light on ways in which political leaders, disinformation profiteers, marketers, and activist organizations can spread moralized content by capitalizing on natural tendencies of our perceptual systems.

Predictability of fouling-potential of raw water for ultrafiltration membranes

2011 ◽  
Vol 11 (4) ◽  
pp. 481-489
Author(s):  
S. Krause ◽  
A. Obermayer
Keyword(s):  
Water Quality ◽  
Membrane Fouling ◽  
Large Scale ◽  
High Capacity ◽  
Raw Water ◽  
Ultrafiltration Membranes ◽  
Small Water ◽  
Lab Experiments ◽  
Flux Decline ◽  
Public Drinking Water

The public drinking water supply of southern Germany is characterized by a rather decentralized network. Due to the hydrogeological setting in these parts of Germany many of the small water works with an average capacity of 50 m3/h have to treat raw water extracted from karstic or cliffy aquifers. These raw waters tend to be contaminated with particles and pathogens acquired during snowmelt or after strong rainfalls. In the last decade ultrafiltration has become the technology of choice for the removal of the aforementioned contaminants. Flux decline caused by unanticipated membrane fouling is the main limitation for the application of ultrafiltration membranes. This paper describes how membrane fouling phenomena can be predicted by using a statistical approach based on data from large scale filtration systems in combination with field and lab experiments on raw water quality and membrane performance. The data defines water quality and respective fouling phenomena both in technical scale filtration plants and in lab experiments of eleven different raw waters. The method described here is more economically feasible for small water works when compared to typical pilot experiments that are used for high capacity water works.

scholarly journals Numerical Simulation of the Mechanical Behavior of Fiber-Reinforced Cement Composites Subjected Dynamic Loading

2021 ◽  
Vol 11 (3) ◽  
pp. 1112
Author(s):  
Nikita Belyakov ◽  
Olga Smirnova ◽  
Aleksandr Alekseev ◽  
Hongbo Tan
Keyword(s):  
Numerical Simulation ◽  
Reinforced Concrete ◽  
Dynamic Loading ◽  
Fiber Reinforced Concrete ◽  
Cement Composites ◽  
Fiber Reinforced ◽  
Lab Experiments ◽  
Reinforced Cement ◽  
Underground Workings ◽  
Concrete Damaged Plasticity

The problem of damage accumulation in fiber-reinforced concrete to structures supporting underground workings and tunnel linings against dynamic loading is insufficiently studied. The mechanical properties were determined and the mechanism of destruction of fiber-reinforced concrete with different reinforcement parameters is described. The parameters of the Concrete Damaged Plasticity model for fiber-reinforced concrete at different reinforcement properties are based on the results of lab experiments. Numerical simulation of the composite concrete was performed in the Simulia Abaqus software package (Dassault Systemes, Vélizy-Villacoublay, France). Modeling of tunnel lining based on fiber-reinforced concrete was performed under seismic loading.

scholarly journals Graph contextualized attention network for predicting synthetic lethality in human cancers

2021 ◽  
Author(s):  
Yahui Long ◽  
Min Wu ◽  
Yong Liu ◽  
Jie Zheng ◽  
Chee Keong Kwoh ◽  
...  
Keyword(s):  
Synthetic Lethality ◽  
Critical Role ◽  
Design Feature ◽  
Cost Effective ◽  
Attention Network ◽  
New Genes ◽  
Lab Experiments ◽  
Proposed Model ◽  
Multiple Feature ◽  
Wet Lab

Abstract Motivation Synthetic Lethality (SL) plays an increasingly critical role in the targeted anticancer therapeutics. In addition, identifying SL interactions can create opportunities to selectively kill cancer cells without harming normal cells. Given the high cost of wet-lab experiments, in silico prediction of SL interactions as an alternative can be a rapid and cost-effective way to guide the experimental screening of candidate SL pairs. Several matrix factorization-based methods have recently been proposed for human SL prediction. However, they are limited in capturing the dependencies of neighbors. In addition, it is also highly challenging to make accurate predictions for new genes without any known SL partners. Results In this work, we propose a novel graph contextualized attention network named GCATSL to learn gene representations for SL prediction. First, we leverage different data sources to construct multiple feature graphs for genes, which serve as the feature inputs for our GCATSL method. Second, for each feature graph, we design node-level attention mechanism to effectively capture the importance of local and global neighbors and learn local and global representations for the nodes, respectively. We further exploit multi-layer perceptron (MLP) to aggregate the original features with the local and global representations and then derive the feature-specific representations. Third, to derive the final representations, we design feature-level attention to integrate feature-specific representations by taking the importance of different feature graphs into account. Extensive experimental results on three datasets under different settings demonstrated that our GCATSL model outperforms 14 state-of-the-art methods consistently. In addition, case studies further validated the effectiveness of our proposed model in identifying novel SL pairs. Availability Python codes and dataset are freely available on GitHub (https://github.com/longyahui/GCATSL) and Zenodo (https://zenodo.org/record/4522679) under the MIT license.

Grid turbulence in shallow flows

2003 ◽  
Vol 489 ◽  
pp. 325-344 ◽  
Author(s):  
W. S. J. UIJTTEWAAL ◽  
G. H. JIRKA
Keyword(s):  
Grid Turbulence ◽  
Shallow Flows

scholarly journals Shallow Flows Over a Permeable Medium: The Hydrodynamics of Submerged Aquatic Canopies

2008 ◽  
Vol 78 (2) ◽  
pp. 309-326 ◽  
Author(s):  
Marco Ghisalberti ◽  
Heidi Nepf
Keyword(s):  
Shallow Flows
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