Cross-correlation of the CMB and radio galaxies in real, harmonic and wavelet spaces: detection of the integrated Sachs-Wolfe effect and dark energy constraints

We report the first detection of the ISW effect in wavelet space, at scales in the sky around 7 degrees with a significance of around 3.3 sigma, by cross-correlating the WMAP first-year data and the NRAO VLA Sky Survey (NVSS). In addition, we present a detailed comparison among the capabilities of three different techniques for two different objectives: to detect the ISW and to put constraints in the nature of the dark energy. The three studied techniques are: the cross-angular power spectrum (CAPS, harmonic space), the correlation function (CCF, real space) and the covariance of the Spherical Mexican Hat Wavelet (SMHW) coefficients (CSMHW, wavelet space). We prove that the CSMHW is expected to provide a higher detection of the ISW effect for a certain scale. This prediction has been corroborated by the analysis of the data. The SMHW analysis shows that the cross-correlation signal is caused neither by systematic effects nor foreground contamination. However, by taking into account the information encoded in all the multipoles/scales/angles, the CAPS provides slightly better constraints than the SMHW in the cosmological parameters that define the nature of the dark energy. The limits provided by the CCF are wider than for the other two methods. Two different cases have been studied: 1) a flat Lambda-CDM universe and 2) a flat universe with an equation of state parameter different from -1. In the first case, the CAPS provides (for a bias value of b = 1.6) 0.59 < Lambda density < 0.84 (at 1 sigma CL). Moreover, the CAPS rejects the range Lambda density < 0.1 at 3.5 sigma, which is the highest detection of the dark energy reported up to date. In the second case, the CAPS gives 0.50 < dark energy density < 0.82 and -1.16 < w < 0.43 (at 1 sigma CL).Comment: 12 pages, 7 figures, accepted for publication in MNRAS. Analysis redone. Changes in the estimation of the cosmological parametres. Additional comparison between wavelets and more standard technique

Expected optimal feedback with Time-Varying Parameters

In this paper we derive the closed loop form of the Expected Optimal Feedback rule, sometimes called passive learning stochastic control, with time varying parameters. As such this paper extends the work of Kendrick (1981,2002, Chapter 6) where parameters are assumed to vary randomly around a known constant mean. Furthermore, we show that the cautionary myopic rule in Beck and Wieland (2002) model, a test bed for comparing various stochastic optimizations approaches, can be cast into this framework and can be treated as a special case of this solution.Optimal experimentation, stochastic optimization, time-varying parameters, expected optimal feedback

Expected optimal feedback with Time-Varying Parameters

In this paper we derive, by using dynamic programming, the closed loop form of the Expected Optimal Feedback rule with time varying parameter. As such this paper extends the work of Kendrick (1981, 2002, Chapter 6) for the time varying parameter case. Furthermore, we show that the Beck and Wieland (2002) model can be cast into this framework and can be treated as a special case of this solution.

Approximating an Infinite Horizon Model in the Presence of Optimal Experimentation

In an recent article Amman and Tucci (2020) make a comparison of the two dominant approaches for solving models with optimal experimentation in economics; the value function approach and an approximation approach. The approximation approach goes back to engineering literature in the 1970ties (cf. Tse &amp; Bar-Shalom, 1973). Kendrick (1981) introduces this approach in economics. By using the same model and dataset as in Beck and Wieland (2002), Amman and Tucci conclude that differences may be small between the both approaches. In the previous paper we did not present the derivation of the approximation approach for this class of models. Hence, here we will present all derivations of the approximation approach for the case where there is an infinite horizon as is most common in economic models. By presenting the derivations, a better understanding and insight is obtained by the reader on how the value function is adequately approximated

The Dual Approch in an Infinite Horizon Model with a Time-Varying Parameter

In a previous paper Amman and Tucci (2017) discuss the DUAL control method, based on Tse and Bar-Shalom (1973) and (Kendrick, 1981) seminal works, applied to the BMW infinite horizon model with an unknown but constant parameter. In these pages the DUAL solution to the BMW infinite horizon model with one time-varying parameter is reported. The special case where the desired path for the state and control are set equal to 0 and the linear system has no constant is considered. The appropriate Riccati quantities for the augmented system are derived and the time- invariant feedback rule are defined following the same steps as in Amman and Tucci (2017). Finally the new approximate cost-to-go is presented. Two cases are considered. In the first one the optimal control is selected using the updated estimate of the time-varying parameter in the model. In the second one only an old estimate of that parameter is available at the time the decision maker chooses her/his control. For the reader’s sake, most of the technical derivations are confined to a number of short appendices

How Active is Active Learning: Value Function Method Versus an Approximation Method

In a previous paper Amman et al. (Macroecon Dyn, 2018) compare the two dominant approaches for solving models with optimal experimentation (also called active learn- ing), i.e. the value function and the approximation method. By using the same model and dataset as in Beck and Wieland (J Econ Dyn Control 26:1359–1377, 2002), they find that the approximation method produces solutions close to those generated by the value function approach and identify some elements of the model specifications which affect the difference between the two solutions. They conclude that differences are small when the effects of learning are limited. However the dataset used in the experiment describes a situation where the controller is dealing with a nonstationary process and there is no penalty on the control. The goal of this paper is to see if their conclusions hold in the more commonly studied case of a controller facing a stationary process and a positive penalty on the control

Optimization of graphene-based materials outperforming host epoxy matrices

The degree of graphite exfoliation and edge-carboxylated layers can be controlled and balanced to design lightweight materials characterized by both low electrical percolation thresholds (EPT) and improved mechanical properties. So far, this challenging task has been undoubtedly very hard to achieve. The results presented in this paper highlight the effect of exfoliation degree and the role of edge-carboxylated graphite layers to give self-assembled structures embedded in the polymeric matrix. Graphene layers inside the matrix may serve as building blocks of complex systems that could outperform the host matrix. Improvements in electrical percolation and mechanical performance have been obtained by a synergic effect due to finely balancing the degree of exfoliation and the chemistry of graphene edges which favors the interfacial interaction between polymer and carbon layers. In particular, for epoxy-based resins including two partially exfoliated graphite samples, differing essentially in the content of carboxylated groups, the percolation threshold reduces from 3 wt% down to 0.3 wt%, as the carboxylated group content increases up to 10 wt%. Edge-carboxylated nanosheets also increase the nanofiller/epoxy matrix interaction, determining a relevant reinforcement in the elastic modulus

The Role of the NRF2 Pathway in Maintaining and Improving Cognitive Function

Nuclear factor (erythroid-derived 2)-like 2 (NRF2) is a redox-sensitive transcription factor that binds to the antioxidant response element consensus sequence, decreasing reactive oxygen species and regulating the transcription of a wide array of genes, including antioxidant and detoxifying enzymes, regulating genes involved in mitochondrial function and biogenesis. Moreover, NRF2 has been shown to directly regulate the expression of anti-inflammatory mediators reducing the expression of pro-inflammatory cytokines. In recent years, attention has turned to the role NRF2 plays in the brain in different diseases such Alzheimer’s disease, Parkinson’s disease, Huntington’s disease and others. This review focused on the evidence, derived in vitro, in vivo and from clinical trials, supporting a role for NRF2 activation in maintaining and improving cognitive function and how its activation can be used to elicit neuroprotection and lead to cognitive enhancement. The review also brings a critical discussion concerning the possible prophylactic and/or therapeutic use of NRF2 activators in treating cognitive impairment-related conditions

Three years field trials to assess the effect of kaolin made particles and copper on olive-fruit fly (B.oleae Gmelin) infestations in Sicily

In most countries of Mediterranean Basin, Bactrocera oleae (Gmel), the olive fruit fly, is the key pest insect on olives. In Sicily this pest causes losses of fruits and a poor quality olive oil. Many researchers have recently carried out some field studies which were based on the use of kaolin and copper against the olive-fruit fly. In the last years these products have been effective several times in reducing olive fly infestation. Kaolin had, also, some important effect in reducing heat-stress in fruit crops and olive-trees. The aim of the present study was to assess the effect of kaolin and copper treatment on olive infestations in Sicily and to evaluate chemical and sensory parameters of oils extracted. For this reason, within 2003-2005, the IX Servizio of Assessorato Regionale Agricoltura e Foreste, selected some olive groves where to carry out trials with kaolin and copper and to realize information and divulgation activities