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Moduli Spaces of Abelian Differentials: The Principal Boundary, Counting Problems and the Siegel--Veech Constants [article]

Alex Eskin, Howard Masur, Anton Zorich
2004 arXiv   pre-print
The constant is found from a Siegel--Veech formula.  ...  Computing the Siegel-Veech Constants.  ...  Now everything is ready to compute the Siegel-Veech constant c (C) .  ... 
arXiv:math/0202134v2 fatcat:f2kdbq6yv5dfhbequeygt5qmjy

Volumes of Strata of Abelian Differentials and Siegel–Veech Constants in Large Genera

Alex Eskin, Anton Zorich
2015 Arnold Mathematical Journal  
We state conjectures on the asymptotic behavior of the volumes of moduli spaces of Abelian differentials and their Siegel-Veech constants as genus tends to infinity.  ...  Research of Alex Eskin is partially supported by NSF Grant. Research of Anton Zorich is partially supported by IUF and by ANR.  ...  Recall that the original definition of the Siegel-Veech constant comes from counting of closed geodesics.  ... 
doi:10.1007/s40598-015-0028-0 fatcat:4utyglydm5gtfgo7h5p5ovzg7q

Rich or Thin?* [chapter]

Susanna Siegel, Alex Byrne
2017 Current Controversies in Philosophy of Perception  
In reply, Siegel makes two points.  ...  Let us see how Siegel explains the question up for debate.  ... 
doi:10.4324/9781315733029-6 fatcat:n4a5rzhddbfvdg6ng6um6qe6i4

Recombination of Artificial Neural Networks [article]

Aaron Vose, Jacob Balma, Alex Heye, Alessandro Rigazzi, Charles Siegel, Diana Moise, Benjamin Robbins, Rangan Sukumar
2019 arXiv   pre-print
We propose a genetic algorithm (GA) for hyperparameter optimization of artificial neural networks which includes chromosomal crossover as well as a decoupling of parameters (i.e., weights and biases) from hyperparameters (e.g., learning rate, weight decay, and dropout) during sexual reproduction. Children are produced from three parents; two contributing hyperparameters and one contributing the parameters. Our version of population-based training (PBT) combines traditional gradient-based
more » ... hes such as stochastic gradient descent (SGD) with our GA to optimize both parameters and hyperparameters across SGD epochs. Our improvements over traditional PBT provide an increased speed of adaptation and a greater ability to shed deleterious genes from the population. Our methods improve final accuracy as well as time to fixed accuracy on a wide range of deep neural network architectures including convolutional neural networks, recurrent neural networks, dense neural networks, and capsule networks.
arXiv:1901.03900v1 fatcat:kcxcxrd5lraafeyymfu3pnw5om

MOESM8 of p66ShcA functions as a contextual promoter of breast cancer metastasis

Kyle Lewis, Alex Kiepas, Jesse Hudson, Julien Senecal, Jacqueline Ha, Elena Voorand, Matthew Annis, Valerie Sabourin, Ryuhjin Ahn, Rachel Selva, Sébastien Tabariès, Brian Hsu (+8 others)
2020 Figshare  
Additional file 8: Figure S8. ShcA p66 is dispensable for invadopodia formation and gelatin degradation. 488 fluorescently-labeled degradation is represented by signal void. (A) Total surface area degraded (μm2) was determined from images taken from three independent experiments (n = 120 FOV, n = 30 each for 4T1-537 (par), p66CR (VC), p66CR (WT) and p66CR (S36A)) and error bars represent s.e.m. (B) Punctate and Large gelatin degradation patches, representative images shown, were classified
more » ... tatively. Frequency of degradation pattern taken from quantified images used for (A). (C) and (D), group the quantified total surface area degraded (μm2) per FOV, from (A), into Punctate and Large degradation patterns, respectively. (E) Representative images of quantified gelatin degradation: F-Actin (green) stained by 647-phalloidin and 488-labelled gelatin (grey). Scale bar is 20 μm in length. Statistical analysis performed using a one-way Anova with a Tukey's multiple comparisons test (*P
doi:10.6084/m9.figshare.11626674.v1 fatcat:ujzidzhe2fd5jlqgoihex4bilu

MOESM5 of p66ShcA functions as a contextual promoter of breast cancer metastasis

Kyle Lewis, Alex Kiepas, Jesse Hudson, Julien Senecal, Jacqueline Ha, Elena Voorand, Matthew Annis, Valerie Sabourin, Ryuhjin Ahn, Rachel Selva, Sébastien Tabariès, Brian Hsu (+8 others)
2020 Figshare  
Additional file 5: Figure S5. p66ShcA does not alter the mesenchymal properties of 4T1-derived triple negative breast cancers. (A) Immunoblot analysis of whole cell lysates isolated from 4T1-537 parental, p66-CR (VC), p66-CR (WT) and p66-CR (S36A) mammary tumors (n = 18 each) using ShcA-, E-Cadherin, Vimentin and Tubulin-specific antibodies. (B-D) Densitometric quantification of mammary tumors shown in panel A for the (B) p66ShcA/Tubulin, (C) p66ShcA/p52ShcA, (D) E-Cadherin/Tubulin and (E)
more » ... tin/Tubulin ratios. The data is normalized to the parental 4T1-537 tumors.
doi:10.6084/m9.figshare.11626659.v1 fatcat:v54sk3oktrcz5mksufdsnvl5la

MOESM1 of p66ShcA functions as a contextual promoter of breast cancer metastasis

Kyle Lewis, Alex Kiepas, Jesse Hudson, Julien Senecal, Jacqueline Ha, Elena Voorand, Matthew Annis, Valerie Sabourin, Ryuhjin Ahn, Rachel Selva, Sébastien Tabariès, Brian Hsu (+8 others)
2020 Figshare  
Additional file 1: Figure S1. Non-mitochondrial p66ShcA restrains metastatic progression in a luminal breast cancer model. (A) Immunoblot analysis of vector control (VC), p66ShcA-WT and p66ShcA-S36A overexpressing NIC cells using ShcA- and Tubulin-specific antibodies. (B) Mammary fat pad (MFP) injection of VC, p66ShcA-WT and p66ShcA-S36A overexpressing NIC cells. The data is shown as average tumor volume (mm3) ± SEM (n = 7 tumors/group). Immunohistochemical staining of the indicated mammary
more » ... rs using (C) Ki67 and (D) cleaved Caspase-3 specific antibodies. Representative images are shown. (E) Percentage of tumor burden in the lungs of mice bearing VC, p66ShcA-WT and p66ShcA-S36A overexpressing NIC tumors. Mammary tumors were resected at 500 mm3 and the development of lung metastases was quantified 28 days later. The data is shown as average lung tumor burden ±SEM (n = 9–12 mice/group). Representative images are shown. Statistical analysis was performed using a one-way Anova with a Tukey's multiple comparisons test (*P
doi:10.6084/m9.figshare.11626629 fatcat:4d35n55wlbh27iqflhwezxh66y

MOESM12 of p66ShcA functions as a contextual promoter of breast cancer metastasis

Kyle Lewis, Alex Kiepas, Jesse Hudson, Julien Senecal, Jacqueline Ha, Elena Voorand, Matthew Annis, Valerie Sabourin, Ryuhjin Ahn, Rachel Selva, Sébastien Tabariès, Brian Hsu (+8 others)
2020 Figshare  
Additional file 12: Figure S12. MAPK family members are not regulated by p66ShcA in lung-metastatic 4T1 breast cancer cells. Whole cell lysates were generated from the indicated cell lines grown under the following conditions: 10% FBS versus 0% FBS for 16 h; 1 mM phenformin for 2 h; 20 μM sodium arsenate for 4 h; suspension cultures on ultra-low attachment plates for 16 h. Immunoblot analysis was performed using phospho-specific and total antibodies against ERK, p38MAPK and JNK.
doi:10.6084/m9.figshare.11626617.v1 fatcat:si52x752nnejdhtfdalwlcvlje

MOESM7 of p66ShcA functions as a contextual promoter of breast cancer metastasis

Kyle Lewis, Alex Kiepas, Jesse Hudson, Julien Senecal, Jacqueline Ha, Elena Voorand, Matthew Annis, Valerie Sabourin, Ryuhjin Ahn, Rachel Selva, Sébastien Tabariès, Brian Hsu (+8 others)
2020 Figshare  
Additional file 7: Figure S7. A p66ShcA-induced epithelial to mesenchymal transition is dispensable for metastatic progression in a luminal breast cancer model. Immunohistochemical analysis of vector control (VC), p66ShcA-WT and p66ShcA-S36A overexpressing NIC mammary tumors using (A) E-Cadherin and (B) Vimentin-specific antibodies. The data is shown as average tumor volume (mm3) ± SEM (n = 7 tumors/group). Representative images are shown. Statistical analysis was performed using a one-way Anova with a Tukey's multiple comparisons test (*P
doi:10.6084/m9.figshare.11626671 fatcat:vkmpgq2j4rhsvoiaw2omaefkki

MOESM13 of p66ShcA functions as a contextual promoter of breast cancer metastasis

Kyle Lewis, Alex Kiepas, Jesse Hudson, Julien Senecal, Jacqueline Ha, Elena Voorand, Matthew Annis, Valerie Sabourin, Ryuhjin Ahn, Rachel Selva, Sébastien Tabariès, Brian Hsu (+8 others)
2020 Figshare  
Additional file 13. Supplemental methods.
doi:10.6084/m9.figshare.11626623.v1 fatcat:6xhkynslkbhmfpr6nvb567p64u

MOESM11 of p66ShcA functions as a contextual promoter of breast cancer metastasis

Kyle Lewis, Alex Kiepas, Jesse Hudson, Julien Senecal, Jacqueline Ha, Elena Voorand, Matthew Annis, Valerie Sabourin, Ryuhjin Ahn, Rachel Selva, Sébastien Tabariès, Brian Hsu (+8 others)
2020 Figshare  
Additional file 11: Figure S11. Src family kinase activation is increased by non-mitochondrial p66ShcA pools in mammary tumors. (A) Whole cell lysates were generated from the indicated cell lines grown under the following conditions: 10% FBS versus 0% FBS for 16 h; 1 mM phenformin for 2 h; 20 μM sodium arsenate for 4 h; suspension cultures on ultra-low attachment plates for 16 h. Immunoblot analysis was performed using pSFK and Src specific antibodies. Percentage of pSFK positive pixels in
more » ... ry breast tumors (n = 6–7 tumors/genotype) (B) and in individual lung-metastatic lesions (C) derived from 4T1-537 p66-CR (VC), p66-CR (WT) and p66-CR (S36A) breast cancer cells. For the lung metastases: p66-CR (VC), n = 318 lesions; p66-CR (WT), n = 308 lesions; p66-CR (S36A), n = 318 lesions. (B, C) Representative IHC images for primary breast tumors and lung metastases are shown. Statistical analysis performed using a one-way Anova with a Tukey's multiple comparisons test (*P
doi:10.6084/m9.figshare.11626608.v1 fatcat:6f7jug6pkreo7gmymhgeuyep7q

MOESM6 of p66ShcA functions as a contextual promoter of breast cancer metastasis

Kyle Lewis, Alex Kiepas, Jesse Hudson, Julien Senecal, Jacqueline Ha, Elena Voorand, Matthew Annis, Valerie Sabourin, Ryuhjin Ahn, Rachel Selva, Sébastien Tabariès, Brian Hsu (+8 others)
2020 Figshare  
Additional file 6: Figure S6. p66ShcA minimally impacts the growth properties of lung-metastatic triple negative primary breast tumors. Quantification of the percentage (A) Ki67 positive cells and (B) cleaved Caspase-3 positive cells in 4T1-537 parental, p66-CR, p66-CR (WT) and p66-CR (S36A) mammary tumors. The data is shown as positivity ± SEM and is representative of 9–10 tumors per group. Representative images are shown below each graph.
doi:10.6084/m9.figshare.11626665 fatcat:iy44awrzynbf7lttwsax5rogmu

MOESM3 of p66ShcA functions as a contextual promoter of breast cancer metastasis

Kyle Lewis, Alex Kiepas, Jesse Hudson, Julien Senecal, Jacqueline Ha, Elena Voorand, Matthew Annis, Valerie Sabourin, Ryuhjin Ahn, Rachel Selva, Sébastien Tabariès, Brian Hsu (+8 others)
2020 Figshare  
Additional file 3: Figure S3. p66ShcA is phosphorylated on Ser36 in 4T1-537 breast cancer cells. (A) Immunoblot analysis of whole cell lysates isolated from 4T1-537 p66-CR (VC), p66-CR (WT) and p66-CR (S36A) breast cancer cells treated with PBS, 1 mM phenformin (2 h) or 20 μM sodium arsenite (4 h) using pSer-p66ShcA, ShcA- and Tubulin-specific antibodies. (B) DCFDA flow cytometric staining demonstrating ROS production in response to phenformin or sodium arsenite treatment.
doi:10.6084/m9.figshare.11626644 fatcat:3zkdlrdewndfta5ihhlbgh5fqm

MOESM10 of p66ShcA functions as a contextual promoter of breast cancer metastasis

Kyle Lewis, Alex Kiepas, Jesse Hudson, Julien Senecal, Jacqueline Ha, Elena Voorand, Matthew Annis, Valerie Sabourin, Ryuhjin Ahn, Rachel Selva, Sébastien Tabariès, Brian Hsu (+8 others)
2020 Figshare  
Additional file 10: Figure S10. AMPK activation is not appreciably regulated by p66ShcA in mammary tumors. (A) Whole cell lysates were generated from the indicated cell lines grown under the following conditions: 10% FBS versus 0% FBS for 16 h; 1 mM phenformin for 2 h; 20 μM sodium arsenate for 4 h; suspension cultures on ultra-low attachment plates for 16 h. Immunoblot analysis was performed using pAMPK and AMPK specific antibodies. Percentage of pAMPK positive pixels in primary breast tumors
more » ... n = 7–8 tumors/genotype) (B) and in individual lung-metastatic lesions (c) derived from 4T1-537 p66-CR (VC), p66-CR (WT) and p66-CR (S36A) breast cancer cells. For the lung metastases: p66-CR (VC), n = 214 lesions; p66-CR (WT), n = 194 lesions; p66-CR (S36A), n = 202 lesions. (B, C) Representative IHC images for primary breast tumors and lung metastases are shown.
doi:10.6084/m9.figshare.11626602.v1 fatcat:rwq4senlojctlbah444zatod3m

Moduli spaces of Abelian differentials: The principal boundary, counting problems, and the Siegel–Veech constants

Alex Eskin, Howard Masur, Anton Zorich
2003 Publications mathématiques (Bures-sur-Yvette)  
The constant c is found from a Siegel-Veech formula.  ...  Computing the Siegel-Veech Constants.  ...  Now everything is ready to compute the Siegel-Veech constant c (C) .  ... 
doi:10.1007/s10240-003-0015-1 fatcat:htpn4igg4zb7lkgswdmtgw6kgu
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