Looking for intrinsic charm in the forward region at BNL RHIC and CERN LHC

The complete understanding of the basic constituents of hadrons and the hadronic dynamics at high energies are two of the main challenges for the theory of strong interactions. In particular, the existence of intrinsic heavy quark components in the hadron wave function must be confirmed (or disproved). In this paper we propose a new mechanism for the production of D-mesons at forward rapidities based on the Color Glass Condensate (CGC) formalism and demonstrate that the resulting transverse momentum spectra are strongly dependent on the behavior of the charm distribution at large Bjorken x. Our results show clearly that the hypothesis of intrinsic charm can be tested in pp and p(d)A collisions at RHIC and LHC. (C) 2010 Elsevier B.V. All rights reserved.

Center of mass energy and system-size dependence of photon production at forward rapidity at RHIC

We present the multiplicity and pseudorapidity distributions of photons produced in Au + Au and Cu + Cu collisions at root(s)NN = 62.4 and 200 GeV. The photons are measured in the region -3.7 < eta < -2.3 using the photon Multiplicity detector in the STAR experiment at RHIC. The number of photons produced per average number of participating nucleon pairs increases with the beam energy and is independent of (lie collision centrality. For collisions with similar average numbers of participating nucleons the photon multiplicities are observed to be similar for An + Au and Cu + Cu collisions at a given beam energy. The ratios of the number of charged particles to photons in the measured pseudorapidity range are found to be 1.4 +/- 0.1 and 1.2 +/- 0.1 for root(s)NN = 62.4 and 200 GeV, respectively. The energy dependence of this ratio could reflect varying contributions from baryons to charged particles, while mesons are the dominant contributors to photon production in the given kinematic region. The photon pseudorapidity distributions normalized by average number of participating nucleon pairs, when plotted as a function of eta-Y(beam), are found to follow a longitudinal scaling independent of centrality and colliding ion species at both beam energies. (C) 2009 Elsevier B.V. All rights reserved.

The influence of ARIMA-GARCH parameters in feed forward neural networks prediction

The objective of this article is to find out the influence of the parameters of the ARIMA-GARCH models in the prediction of artificial neural networks (ANN) of the feed forward type, trained with the Levenberg-Marquardt algorithm, through Monte Carlo simulations. The paper presents a study of the relationship between ANN performance and ARIMA-GARCH model parameters, i.e. the fact that depending on the stationarity and other parameters of the time series, the ANN structure should be selected differently. Neural networks have been widely used to predict time series and their capacity for dealing with non-linearities is a normally outstanding advantage. However, the values of the parameters of the models of generalized autoregressive conditional heteroscedasticity have an influence on ANN prediction performance. The combination of the values of the GARCH parameters with the ARIMA autoregressive terms also implies in ANN performance variation. Combining the parameters of the ARIMA-GARCH models and changing the ANN`s topologies, we used the Theil inequality coefficient to measure the prediction of the feed forward ANN.

Handling Mitigating Circumstances for Electronic Contracts

Electronic contracts are a means of representing agreed responsibilities and expected behaviour of autonomous agents acting on behalf of businesses. They can be used to regulate behaviour by providing negative consequences, penalties, where the responsibilities and expectations are not met, i.e. the contract is violated. However, long-term business relationships require some flexibility in the face of circumstances that do not conform to the assumptions of the contract, that is, mitigating circumstances. In this paper, we describe how contract parties can represent and enact policies on mitigating circumstances. As part of this, we require records of what has occurred within the system leading up to a violation: the provenance of the violation. We therefore bring together contract-based and provenance systems to solve the issue of mitigating circumstances.

Determining the Trustworthiness of New Electronic Contracts

Expressing contractual agreements electronically potentially allows agents to automatically perform functions surrounding contract use: establishment, fulfilment, renegotiation etc. For such automation to be used for real business concerns, there needs to be a high level of trust in the agent-based system. While there has been much research on simulating trust between agents, there are areas where such trust is harder to establish. In particular, contract proposals may come from parties that an agent has had no prior interaction with and, in competitive business-to-business environments, little reputation information may be available. In human practice, trust in a proposed contract is determined in part from the content of the proposal itself, and the similarity of the content to that of prior contracts, executed to varying degrees of success. In this paper, we argue that such analysis is also appropriate in automated systems, and to provide it we need systems to record salient details of prior contract use and algorithms for assessing proposals on their content. We use provenance technology to provide the former and detail algorithms for measuring contract success and similarity for the latter, applying them to an aerospace case study.

Electronic Business Contracts between Services

Electronic contracts mirror the paper versions exchanged between businesses today, and offer the possibility of dynamic, automatic creation and enforcement of restrictions and compulsions on service behaviour that are designed to ensure business objectives are met. Where there are many contracts within a particular application, it can be difficult to determine whether the system can reliably fulfil them all, yet computer-parsable electronic contracts may allow such verification to be automated. In this chapter, we describe a conceptual framework and architecture specification in which normative business contracts can be electronically represented, verified, established, renewed, and so on. In particular, we aim to allow systems containing multiple contracts to be checked for conflicts and violations of business objectives. We illustrate the framework and architecture with an aerospace aftermarket example.

Using Normative Markov Decision Processes for Evaluating Electronic Contracts: A Case Study in a Simulated Aerospace Aftermarket

Before signing electronic contracts, a rational agent should estimate the expected utilities of these contracts and calculate the violation risks related to them. In order to perform such pre-signing procedures, this agent has to be capable of computing a policy taking into account the norms and sanctions in the contracts. In relation to this, the contribution of this work is threefold. First, we present the Normative Markov Decision Process, an extension of the Markov Decision Process for explicitly representing norms. In order to illustrate the usage of our framework, we model an example in a simulated aerospace aftermarket. Second, we specify an algorithm for identifying the states of the process which characterize the violation of norms. Finally, we show how to compute policies with our framework and how to calculate the risk of violating the norms in the contracts by adopting a particular policy.

Optimal performance fee and flow of funds in asset management contracts

This paper investigates the importance of ow of funds as an implicit incentive in the asset management industry. We build a two-period bi- nomial moral hazard model to explain the trade-o¤s between ow, per- formance and fees where e¤ort depends on the combination of implicit ( ow of funds) and explicit (performance fee) incentives. Two cases are considered. With full commitment, the investor s relevant trade-o¤ is to give up expected return in the second period vis-à-vis to induce e¤ort in the rst period. The more concerned the investor is with today s pay- o¤, the more willing he will be to give up expected return in the second period by penalizing negative excess return in the rst period. Without full commitment, the investor learns some symmetric and imperfect infor- mation about the ability of the manager to obtain positive excess return. In this case, observed returns reveal ability as well as e¤ort choices. We show that powerful implicit incentives may explain the ow-performance relationship with a numerical solution. Besides, risk aversion explains the complementarity between performance fee and ow of funds.

Non-monotone insurance contracts and their empirical consequences

The goal of this paper is to show the possibility of a non-monotone relation between coverage ans risk which has been considered in the literature of insurance models since the work of Rothschild and Stiglitz (1976). We present an insurance model where the insured agents have heterogeneity in risk aversion and in lenience (a prevention cost parameter). Risk aversion is described by a continuous parameter which is correlated with lenience and for the sake of simplicity, we assume perfect correlation. In the case of positive correlation, the more risk averse agent has higher cosr of prevention leading to a higher demand for coverage. Equivalently, the single crossing property (SCP) is valid and iplies a positive correlation between overage and risk in equilibrium. On the other hand, if the correlation between risk aversion and lenience is negative, not only may the SCP be broken, but also the monotonocity of contracts, i.e., the prediction that high (low) risk averse types choose full (partial) insurance. In both cases riskiness is monotonic in risk aversion, but in the last case there are some coverage levels associated with two different risks (low and high), which implies that the ex-ante (with respect to the risk aversion distribution) correlation between coverage and riskiness may have every sign (even though the ex-post correlation is always positive). Moreover, using another instrument (a proxy for riskiness), we give a testable implication to desentangle single crossing ans non single croosing under an ex-post zero correlation result: the monotonicity of coverage as a function os riskiness. Since by controlling for risk aversion (no asymmetric information), coverage is monotone function of riskiness, this also fives a test for asymmetric information. Finally, we relate this theoretical results to empirical tests in the recent literature, specially the Dionne, Gouruéroux and Vanasse (2001) work. In particular, they found an empirical evidence that seems to be compatible with asymmetric information and non single crossing in our framework. More generally, we build a hidden information model showing how omitted variables (asymmetric information) can bias the sign of the correlation of equilibrium variables conditioning on all observable variables. We show that this may be the case when the omitted variables have a non-monotonic relation with the observable ones. Moreover, because this non-dimensional does not capture this deature. Hence, our main results is to point out the importance of the SPC in testing predictions of the hidden information models.