Ultraconserved elements (UCEs) resolve the phylogeny of Australasian smurf-weevils nork Matthew H. Van Dam (4610857)

“...<div><p>Weevils (Curculionoidea) comprise one of the most diverse groups of organisms on earth. There is hardly a vascular plant or plant part without its own species of weevil feeding on it and weevil species diversity is greater than the number of fishes, birds, reptiles, amphibians and mammals combined. ...”

A blocked staggered-level design for an experiment with two hard-to-change factors nork Peter Goos (805576)

“...The experiment was run in blocks and involved one quantitative hard-to-change factor, one two-level categorical hard-to-change factor, and three quantitative easy-to-change factors. ...”

Nuclear Translocation of hARD1 Contributes to Proper Cell Cycle Progression nork Ji-Hyeon Park (554738)

“...The high homology and widespread expression of ARD1 across multiple species and tissues signify that it serves a fundamental role in cells. Human ARD1 (hARD1) has been suggested to be involved in diverse biological processes, and its role in cell proliferation and cancer development has been recently drawing attention. ...”

Evaluation of stiffness feedback for hard nodule identification on a phantom silicone model nork Min Li (12799)

“...<div><p>Haptic information in robotic surgery can significantly improve clinical outcomes and help detect hard soft-tissue inclusions that indicate potential abnormalities. ...”

Species matter for predicting the functioning of evolving microbial communities – An eco-evolutionary model nork Timothy G. Barraclough (7274534)

“...Yet predicting dynamics and functioning of these complex systems is hard, making interventions to enhance functioning harder still. ...”

Supplementary Figure 1 from The evolution and fate of diversity under hard and soft selection nork Patrick Chen (4343074)

“...Each point is the mean proportion of resistant individuals from evolved lines undergoing either soft or hard selection (n=12 for each treatment). ...”

Delete one edge on Karate network to change the consensus opinion—<i>β</i> = 1. nork Xi Chen (35903)

Gaiak:

For the Karate network. nork Xi Chen (35903)

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Influence of edge edition on consensus. nork Xi Chen (35903)

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Graphical illustration of Case 2 from Theorem 1 (i.e. <i>p</i> < 0 and <i>β</i> ≥ −1/<i>p</i>). nork Xi Chen (35903)

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Opinion formation on the star graph. nork Xi Chen (35903)

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Based on one ER model (<i>n</i> = 100, <i>ρ</i> = 0.0606), one WS model (<i>n</i> = 100, <i>K</i> = 6, <i>σ</i> = 0.2), and one BA model (<i>n</i> = 100, <i>M</i>₀ = 4,... nork Xi Chen (35903)

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For 1,000 random y(0) on Karate network. nork Xi Chen (35903)

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Based on three WS models with different rewiring probabilities (<i>n</i> = 100, <i>K</i> = 6, <i>σ</i> = 0.1, 0.3, 0.8). nork Xi Chen (35903)

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<i>β</i>^<i>P</i> for real-world twitter datasets. nork Xi Chen (35903)

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For 1,000 random y(0). nork Xi Chen (35903)

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For a random opinion vector y(0) with mean −0.0395, on 1,000 ER models with <i>n</i> = 100 and <i>ρ</i> = 0.4. nork Xi Chen (35903)

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For a random opinion vector y(0), on ER models with <i>n</i> = 100 and <i>ρ</i> ∈ (0,1]. nork Xi Chen (35903)

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<i>x</i>₁(<i>t</i> + 1) as a function of <i>x</i>_2,3,4,5(<i>t</i>). nork Xi Chen (35903)

Gaiak:

Add one edge on Karate network to change the consensus opinion—<i>β</i> = 1. nork Xi Chen (35903)

Gaiak: