TAUOLA the library for tau lepton decay, and KKMC/KORALB/KORALZ/... status report

The status of the Monte Carlo programs for the simulation of the $\tau$ lepton production in high energy accelerator experiments and decay is reviewed. In particular, the status of the following packages is discussed: (i) TAUOLA for tau-lepton decay, (ii) PHOTOS for radiative corrections in decays, (iii) KORALB, KORALZ, KKMC packages for tau-pair production in e+e- collisions and (iv) universal interface of TAUOLA for the decay of tau-leptons produced by``any'' generator. Special emphasis on requirements from new and future experiments is given. Some considerations about the software organization necessary to keep simultaneously distinct physics initializations for TAUOLA are also included.Comment: latex 7 pages, including 1 table and 5 figure files, all 6 in postscript format. Presented on 'Sixth international workshop on tau lepton physics', Victoria Canada, September 200

An Alternative Approach to the Calculation and Analysis of Connectivity in the World City Network

Empirical research on world cities often draws on Taylor's (2001) notion of an 'interlocking network model', in which office networks of globalized service firms are assumed to shape the spatialities of urban networks. In spite of its many merits, this approach is limited because the resultant adjacency matrices are not really fit for network-analytic calculations. We therefore propose a fresh analytical approach using a primary linkage algorithm that produces a one-mode directed graph based on Taylor's two-mode city/firm network data. The procedure has the advantage of creating less dense networks when compared to the interlocking network model, while nonetheless retaining the network structure apparent in the initial dataset. We randomize the empirical network with a bootstrapping simulation approach, and compare the simulated parameters of this null-model with our empirical network parameter (i.e. betweenness centrality). We find that our approach produces results that are comparable to those of the standard interlocking network model. However, because our approach is based on an actual graph representation and network analysis, we are able to assess cities' position in the network at large. For instance, we find that cities such as Tokyo, Sydney, Melbourne, Almaty and Karachi hold more strategic and valuable positions than suggested in the interlocking networks as they play a bridging role in connecting cities across regions. In general, we argue that our graph representation allows for further and deeper analysis of the original data, further extending world city network research into a theory-based empirical research approach.Comment: 18 pages, 9 figures, 2 table

Doxorubicin versus doxorubicin and cisplatin in endometrial carcinoma: definitive results of a randomised study (55872) by the EORTC Gynaecological Cancer Group

BACKGROUND: Combination chemotherapy yields better response rates which do not always lead to a survival advantage. The aim of this study was to investigate whether the reported differences in the efficacy and toxicity of monotherapy with doxorubicin (DOX) versus combination therapy with cisplatin (CDDP) in endometrial adenocarcinoma lead to significant advantage in favour of the combination. PATIENTS AND METHODS: Eligible patients had histologically-proven advanced and/or recurrent endometrial adenocarcinoma and were chemo-naïve. Treatment consisted of either DOX 60 mg/m(2) alone or CDDP 50 mg/m2 added to DOX 60 mg/m2, every 4 weeks. RESULTS: A total of 177 patients were entered and median follow-up is 7.1 years. The combination DOX-CDDP was more toxic than DOX alone. Haematological toxicity consisted mainly of white blood cell toxicity grade 3 and 4 (55% versus 30%). Non-haematological toxicity consisted mainly of grade 3 and 4 alopecia (72% versus 65%) and nausea/vomiting (36 % versus 12%). The combination DOX-CDDP provided a significantly higher response rate than single agent DOX (P <0.001). Thirty-nine patients (43%) responded on DOX-CDDP [13 complete responses (CRs) and 26 partial responses (PRs)], versus 15 patients (17%) on DOX alone (8 CR and 7 PR). The median overall survival (OS) was 9 months in the DOX-CDDP arm versus 7 months in the DOX alone arm (Wilcoxon P = 0.0654). Regression analysis showed that WHO performance status was statistically significant as a prognostic factor for survival, and stratifying for this factor, treatment effect reaches significance (hazard ratio = 1.46, 95% confidence interval 1.05-2.03, P = 0.024). CONCLUSIONS: In comparison to single agent DOX, the combination of DOX-CDDP results in higher but acceptable toxicity. The response rate produced is significantly higher, and a modest survival benefit is achieved with this combination regimen, especially in patients with a good performance status

Insight into the molecular requirements for pathogenicity of Fusarium oxysporum f. sp. lycopersici through large-scale insertional mutagenesis

An insertional mutagenesis screen identifies pathogenicity-related genes in the plant fungal pathogen Fusarium oxysporum

Granger causality revisited

This technical paper offers a critical re-evaluation of (spectral) Granger causality measures in the analysis of biological timeseries. Using realistic (neural mass) models of coupled neuronal dynamics, we evaluate the robustness of parametric and nonparametric Granger causality. Starting from a broad class of generative (state-space) models of neuronal dynamics, we show how their Volterra kernels prescribe the second-order statistics of their response to random fluctuations; characterised in terms of cross-spectral density, cross-covariance, autoregressive coefficients and directed transfer functions. These quantities in turn specify Granger causality - providing a direct (analytic) link between the parameters of a generative model and the expected Granger causality. We use this link to show that Granger causality measures based upon autoregressive models can become unreliable when the underlying dynamics is dominated by slow (unstable) modes - as quantified by the principal Lyapunov exponent. However, nonparametric measures based on causal spectral factors are robust to dynamical instability. We then demonstrate how both parametric and nonparametric spectral causality measures can become unreliable in the presence of measurement noise. Finally, we show that this problem can be finessed by deriving spectral causality measures from Volterra kernels, estimated using dynamic causal modelling