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Stochastic Ambient Calculus

Maria G. Vigliotti, Peter G. Harrison
2006 Electronical Notes in Theoretical Computer Science  
We use F, G for probability distribution functions.  ... 
doi:10.1016/j.entcs.2006.07.018 fatcat:ttrfyefn5nhwrmtmdrhoj2jjvi

Vasopressin and the mature coronary collateral circulation

K G Peters, M L Marcus, D G Harrison
1989 Circulation  
Vasopressin and the Mature Coronary Collateral Circulation Kevin G. Peters, MD, Melvin L. Marcus, MD, and David G.  ...  Harrison, MD In isolated vascular rings, we have shown that mature coronary collateral vessels are highly responsive to the vasoconstrictor effects of vasopressin.  ... 
doi:10.1161/01.cir.79.6.1324 pmid:2720931 fatcat:dfkerkqt7fdsdfbswgiskyiotq

Growth Differentiation Factor 9 Is a Germ Cell Regulator of Sertoli Cell Function

Peter K. Nicholls, Craig A. Harrison, Robert B. Gilchrist, Paul G. Farnworth, Peter G. Stanton
2009 Endocrinology  
ml; Novo-Nordisk, Sydney, NSW, Australia), transferrin (5 g/ml; Sigma Chemical), sodium selenite (50 ng/ml; Sigma Chemical), and penicillin (200 U/ml)-streptomycin (200 g/ml)-Fungizone (0.5 g/ml) (CSL,  ...  Localization shown in the 3-(D and E), 9-(F), and 18-dpp testis (G and H). Arrowheads indicate specific BMP15 staining in gonocytes (D) and spermatocytes (G).  ... 
doi:10.1210/en.2008-1048 pmid:19106224 fatcat:2g6htkm5mnefrk7y7z7twg7kbu

A new approach to recursion removal

Peter G. Harrison, Hessam Khoshnevisan
1992 Theoretical Computer Science  
Harrison, P.G. and H. Khoshnevisan, A new approach to recursion removal, Theoretical Computer Science 93 (1992) 91-113.  ...  , G,g=g.  ...  The else part Hf= * 0 [fc sub 1, id] is linear and for all functions g, we may write where G1g=[G,g,id], GZg=GJgOsubl, G,g=g. . 1 . 1 is already in a tail-recursive form and the derivation of the resultant  ... 
doi:10.1016/0304-3975(92)90213-y fatcat:tdcmlxp7vbc75dhw2fb4s5jtzu

Turning back time in Markovian process algebra

Peter G. Harrison
2003 Theoretical Computer Science  
That is, equate the known product of the rates around the cycle in G with the symbolic product of the rates around the reversed cycle in G.  ...  Now let us try to apply the RCAT to a G-network of two nodes.  ... 
doi:10.1016/s0304-3975(02)00375-4 fatcat:gn4iho5fwvgxtjbaingalgg75q

Quantiles of Sojourn Times [chapter]

Peter G. Harrison, William J. Knottenbelt
2006 Advances in Computer Science and Engineering: Texts  
Harrison and W.J. Knottenbelt Chain Analyser interface language 30, 31 .  ...  Harrison and W.Numerical and analytical cycle time densities for the tree-like queueing network of Figure 3 with 27 customers (10 874 304 states).  ... 
doi:10.1142/9781860948923_0010 fatcat:stcelcfui5e3dmcdacofndvehu

Extra-ovarian expression and activity of growth differentiation factor 9

Yao Wang, Peter K Nicholls, Peter G Stanton, Craig A Harrison, Mai Sarraj, Robert B Gilchrist, Jock K Findlay, Paul G Farnworth
2009 Journal of Endocrinology  
(G) The foetal male adrenal gland at 14 . 5 days post-coitum (!100) included unstained cells and cells with strong cytoplasmic staining for GDF9.  ... 
doi:10.1677/joe-08-0563 pmid:19505950 fatcat:bhp3kawr7zfy5itg3vehc5hod4

Performance Enhancement by Means of Task Replication [chapter]

Peter G. Harrison, Zhan Qiu
2013 Lecture Notes in Computer Science  
Jobs F mn (t) = F nm (t) G k (x) = L n+k,n x n n=1 ∞ ∑ = L n,n+k x n n=1 ∞ ∑ G(x, y) = L n+k,n x n y k k=1 ∞ ∑ n=1 ∞ ∑ = L n,n+k x n y k k=1 ∞ ∑ n=1 ∞ ∑ = G k (x)y k k=1 ∞ ∑ L mn (s) = L nm (s) = L n+k  ...  ρ 2 , ρ) + 2H 0 (ρ) + G 0 (ρ 2 ) + L 0,0 ] π mn = (1− ρ) 2 ρ m+n ▸ Traffic equations: + throughput of queue 2 ▸ Utilisation: Spectral Expansion Method (SEM) p − = 1 1− π 0 π m P(1 ≤ N ≤ m) m=1 ∞ ∑ λ +  ... 
doi:10.1007/978-3-642-40725-3_15 fatcat:u6m4q6bflrdpzc5icrdaro54qi

Linearisation: An optimisation for nonlinear functional programs

Peter G. Harrison
1988 Science of Computer Programming  
G-'(a + b; c) = G-'( G,G;'a + GG-'b; GG-'c) = G-'G( G;'a + G-lb; G-'c) = G;'a + G-lb; G-'c. Cl Proposition 3.6.  ...  such that Vu, b, c, G( a + b; c) = Gta + Gb; Gc and G has an inverse, G-', then Vu, b, c, G-'(a + b; c) = G;'a + G-lb; G-'c provided G;' exists.  ...  Note that pk 3 rti = qi for k d i, so that only (m -k+ 1) tests are necessary in the evaluation of the kth component of g.  ... 
doi:10.1016/0167-6423(88)90052-4 fatcat:7wpkbavqnrbq5fwznyogs56q6q

Passage time distributions in large Markov chains

Peter G. Harrison, William J. Knottenbelt
2002 Performance Evaluation Review  
Let G be the network's normalising constant function for the joint equilibrium state probabilities, i.e. at population n, G(n) = M i=1 ni = n ni ≥ 0 M i=1 x n i i where xi = vi/µi.  ...  Then we have the following result [10, 13, 8] . of path z = (z1, z2, . . . , zm) (m ≤ M ) is L(s|z) = 1 G(n − 1) × M i=1 ui = n − 1 ui ≥ 0 M i=1 x u i i m j=1 µz j s + µz j uz j +1 where z1 = 1, zm is  ... 
doi:10.1145/511399.511345 fatcat:vo2cgdcbubaizctv7xbggtdgxq

Blending randomness in closed queueing network models

Giuliano Casale, Mirco Tribastone, Peter G. Harrison
2014 Performance evaluation (Print)  
Peter Harrison is also supported by the EPSRC project APROPOS (EP/I030921/1). The authors thank Juan Fernando Peréz for helpful comments during the revision of this work.  ...  Acknowledgement The work of Giuliano Casale and Peter Harrison is supported by the European project MODAClouds (FP7-318484). Mirco Tribastone is supported by the European project ASCENS.  ... 
doi:10.1016/j.peva.2014.09.001 fatcat:egnpnsx2a5bavnfapntzpu22hy

miR-206 enforces a slow muscle phenotype [article]

Kristen K. Bjorkman, Martin G. Guess, Brooke C. Harrison, Michael M. Polmear, Angela K. Peter, Leslie A. Leinwand
2019 bioRxiv   pre-print
A more refined muscle consensus site has been proposed that has a more specific core hexamer (CA(C/G)(C/G)TG) and extended flanking sequence (Yutzey and Konieczny, 1992) .  ...  J Appl Physiol 106:582-595. doi:10.1152/japplphysiol.90780.2008 Allen DL, Harrison BC, Maass A, Bell ML, Byrnes WC, Leinwand LA. 2001.  ... 
doi:10.1101/756981 fatcat:hfjqpyb3hfe5no6vkfs7tyhoh4

Analytic models for multistage interconnection networks

Peter G. Harrison
1991 Journal of Parallel and Distributed Computing  
Peter G Harrison Department of Computing Imperial College London Central to all parallel architectures is a switching network which facilitates the communication between a machine's components necessary  ...  N) i=l By a result in [Bu73l, the normalising constant can be computed by the following simple recurrence: G(N) = g(M,N) where g(m,n) = g(m-I,n) + xmg(m,n-I) (m,n~l) server j is non-zero, i.e. cffkl  ...  m (p) m + .t:~:::... _ _ _ _ _ _ _ _ G(N-l)1l where for ~O.  ... 
doi:10.1016/0743-7315(91)90006-u fatcat:b4bvp5v66vh35pjoqmwwjv7zu4

Analysis of stochastic Petri nets with signals

Andrea Marin, Simonetta Balsamo, Peter G. Harrison
2012 Performance evaluation (Print)  
G-networks.  ...  Another significant difference from what is known in G-networks is that SPNs with signals may have rate-dependent  ...  Under this assumption we have the following equilibrium probability distribution: π(m) ∝ χ E χ 2 H (χ G + χ I ) 2 χ D χ F χ 2 G χ I m1 χ F χ G χ I χ E χ H (χ G + χ I ) m2 χ H (χ G + χ I ) χ F χ G m3 ·  ... 
doi:10.1016/j.peva.2012.06.003 fatcat:cdiumyejxzedpby7gtt72hzehi

Clinical trial data validate the C-peptide estimate model in type 1 diabetes

John M. Wentworth, Naiara G. Bediaga, Stephen E. Gitelman, Carmela Evans-Molina, Peter A. Gottlieb, Peter G. Colman, Michael J. Haller, Leonard C. Harrison
2020 Diabetologia  
Figure 1 presents the ATG/G-CSF trial primary outcome according to measured (CP STIM ) and modelled (CP EST ) beta cell function.  ...  We excluded two participants with incomplete data, resulting in 28, 29 and 30 participants in the ATG/G-CSF, ATG/ placebo and placebo/placebo groups, respectively.  ...  Figure 1 presents the ATG/G-CSF trial primary outcome according to measured (CP STIM ) and modelled (CP EST ) beta cell function.  ... 
doi:10.1007/s00125-020-05088-6 pmid:31982961 fatcat:rulew5b6qbetpdqp5vbis6h5ku
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