Foreground removal requirements for measuring large-scale CMB B-modes in light of BICEP2

The most convincing confirmation that the B-mode polarization signal detected at degree scales by BICEP2 is due to the Cosmic Microwave Background (CMB) would be the measurement of its large-scale counterpart. We assess the requirements for diffuse component separation accuracy over large portions of the sky in order to measure the large-scale B-mode signal corresponding to a tensor to scalar ratio of r=0.1-0.2. We use the method proposed by Bonaldi & Ricciardi (2011) to forecast the performances of different simulated experiments taking into account noise and foreground removal issues. We do not consider instrumental systematics, and we implicitly assume that they are not the dominant source of error. If this is the case, the confirmation of an r=0.1-0.2 signal is achievable by Planck even for conservative assumptions regarding the accuracy of foreground cleaning. Our forecasts suggest that the combination of this experiment with BICEP2 will lead to an improvement of 25-45% in the constraint on r. A next-generation CMB polarization satellite, represented in this work by the COrE experiment, can reduce dramatically (by almost another order of magnitude) the uncertainty on r. In this case, however, the accuracy of foreground removal becomes critical to fully benefit from the increase in sensitivity.Comment: 8 pages, 3 figures, 1 table. Accepted by MNRA

A chemically driven fluctuating ratchet model for actomyosin interaction

With reference to the experimental observations by T. Yanagida and his co-workers on actomyosin interaction, a Brownian motor of fluctuating ratchet kind is designed with the aim to describe the interaction between a Myosin II head and a neighboring actin filament. Our motor combines the dynamics of the myosin head with a chemical external system related to the ATP cycle, whose role is to provide the energy supply necessary to bias the motion. Analytical expressions for the duration of the ATP cycle, for the Gibbs free energy and for the net displacement of the myosin head are obtained. Finally, by exploiting a method due to Sekimoto (1997, J. Phys. Soc. Jpn., 66, 1234), a formula is worked out for the amount of energy consumed during the ATP cycle.Comment: 15 pages. 1 figur

Forecast B-modes detection at large scales in presence of noise and foregrounds

We investigate the detectability of the primordial CMB polarization B-mode power spectrum on large scales in the presence of instrumental noise and realistic foreground contamination. We have worked out a method to estimate the errors on component separation and to propagate them up to the power spectrum estimation. The performances of our method are illustrated by applying it to the instrumental specifications of the Planck satellite and to the proposed configuration for the next generation CMB polarization experiment COrE. We demonstrate that a proper component separation step is required in order achieve the detection of B-modes on large scales and that the final sensitivity to B-modes of a given experiment is determined by a delicate balance between noise level and residual foregrounds, which depend on the set of frequencies exploited in the CMB reconstruction, on the signal-to-noise of each frequency map, and on our ability to correctly model the spectral behavior of the foreground components. We have produced a flexible software tool that allows the comparison of performances on B-mode detection of different instrumental specifications (choice of frequencies, noise level at each frequency, etc.) as well as of different proposed approaches to component separation.Comment: 7 pages, 2 tables, 1 figure, accepted by MNRA

WMAP 3yr data with the CCA: anomalous emission and impact of component separation on the CMB power spectrum

The Correlated Component Analysis (CCA) allows us to estimate how the different diffuse emissions mix in CMB experiments, exploiting also complementary information from other surveys. It is especially useful to deal with possible additional components. An application of CCA to WMAP maps assuming that only the canonical Galactic emissions are present, highlights the widespread presence of a spectrally flat "synchrotron" component, largely uncorrelated with the synchrotron template, suggesting that an additional foreground is indeed required. We have tested various spectral shapes for such component, namely a power law as expected if it is flat synchrotron, and two spectral shapes that may fit the spinning dust emission: a parabola in the logS - log(frequency) plane, and a grey body. Quality tests applied to the reconstructed CMB maps clearly disfavour two of the models. The CMB power spectra, estimated from CMB maps reconstructed exploiting the three surviving foreground models, are generally consistent with the WMAP ones, although at least one of them gives a significantly higher quadrupole moment than found by the WMAP team. Taking foreground modeling uncertainties into account, we find that the mean quadrupole amplitude for the three "good" models is less than 1 sigma below the expectation from the standard LambdaCDM model. Also the other reported deviations from model predictions are found not to be statistically significant, except for the excess power at l~40. We confirm the evidence for a marked North-South asymmetry in the large scale (l < 20) CMB anisotropies. We also present a first, albeit preliminary, all-sky map of the "anomalous" component.Comment: 14 pages, 17 figures, submitted to MNRAS, references adde

Biological aspects of mTOR in leukemia

The mammalian target of rapamycin (mTOR) is a central processor of intra-and extracellular signals, regulating many fundamental cellular processes such as metabolism, growth, proliferation, and survival. Strong evidences have indicated that mTOR dysregulation is deeply implicated in leukemogenesis. This has led to growing interest in the development of modulators of its activity for leukemia treatment. This review intends to provide an outline of the principal biological and molecular functions of mTOR. We summarize the current understanding of how mTOR interacts with microRNAs, with components of cell metabolism, and with controllers of apoptotic machinery. Lastly, from a clinical/translational perspective, we recapitulate the therapeutic results in leukemia, obtained by using mTOR inhibitors as single agents and in combination with other compounds

Nonminimal 331 model for lepton flavor universality violation in b → sll decays

The 331 models constitute an extension of the Standard Model (SM) obtained by enlarging the SM gauge group SU(3)C×SU(2)L×U(1)Y to the group SU(3)C×SU(3)L×U(1)X. We investigate how a nonminimal 331 model may embed lepton flavor universality violating contributions to b→sℓℓ processes without introducing lepton flavor violation, as suggested by the recent LHCb measurements of the ratios RK and RK∗. We discuss the model-independent scenarios of new physics in b→sℓℓ currently favored by the data that could be accommodated by this model and consider a few phenomenological constraints on this model

Correlated Component Analysis for diffuse component separation with error estimation on simulated Planck polarization data

We present a data analysis pipeline for CMB polarization experiments, running from multi-frequency maps to the power spectra. We focus mainly on component separation and, for the first time, we work out the covariance matrix accounting for errors associated to the separation itself. This allows us to propagate such errors and evaluate their contributions to the uncertainties on the final products.The pipeline is optimized for intermediate and small scales, but could be easily extended to lower multipoles. We exploit realistic simulations of the sky, tailored for the Planck mission. The component separation is achieved by exploiting the Correlated Component Analysis in the harmonic domain, that we demonstrate to be superior to the real-space application (Bonaldi et al. 2006). We present two techniques to estimate the uncertainties on the spectral parameters of the separated components. The component separation errors are then propagated by means of Monte Carlo simulations to obtain the corresponding contributions to uncertainties on the component maps and on the CMB power spectra. For the Planck polarization case they are found to be subdominant compared to noise.Comment: 17 pages, accepted in MNRA

Covert brand recognition engages emotion-specific brain networks

Consumer goods' brands have become a major driver of consumers' choice: they have got symbolic, relational and even social properties that add substantial cultural and affective value to goods and services. Therefore, measuring the role of brands in consumers' cognitive and affective processes would be very helpful to better understand economic decision making. This work aimed at finding the neural correlates of automatic, spontaneous emotional response to brands, showing how deeply integrated are consumption symbols within the cognitive and affective processes of individuals. Functional magnetic resonance imaging (fMRI) was measured during a visual oddball paradigm consisting in the presentation of scrambled pictures as frequent stimuli, colored squares as targets, and brands and emotional pictures (selected from the International Affective Picture System [IAPS]) as emotionally-salient distractors. Affective rating of brands was assessed individually after scanning by a validated questionnaire. Results showed that, similarly to IAPS pictures, brands activated a well-defined emotional network, including amygdala and dorsolateral prefrontal cortex, highly specific of affective valence. In conclusion, this work identified the neural correlates of brands within cognitive and affective processes of consumers

Dynamic simulation driven design and management of production facilities in agricultural/food industry

An industrial plant in the agro-food sector can be considered a complex system as it is composed of numerous types of machines and it is characterized by a strong variation (seasonality) in the agricultural production. Whenever the dynamic behavior of the plants during operation is considered, system and design complexities increase. Reliable operation of food processing farms is primarily dependent on perfect balance between variable supply and product storage at each given time. To date, the classical modus operandi of food processing management systems is carried out under stationary and average conditions. Moreover, most of the systems installed for agricultural and food industries are sized using average production data. This often results in a mismatch between the actual operation and the expected operation. Consequently, the system is not optimized for the needs of a specific company. Also, the system is not flexible to the evolution that the production process could possibly have in the future. Promising techniques useful to solve the above-described problems could possibly be borrowed from demand side management (DSM) in smart grid systems. Such techniques allow customers to make dynamically informed decisions regarding their energy demand and help the energy providers in reducing the peak load demand and reshape the load profile. DSM is successfully used to improve the energy management system and we conjecture that DSM could be suitably adapted to food processing management. In this paper we describe how DSM could be exploited in the intelligent management of production facilities serving agricultural and food industry. The main objective is, indeed, to present how methods for modelling and implementing the dynamic simulation used for the optimization of the energy management in smart grid systems can be applied to a fruit and vegetables processing plant through a suitable adaptation