Showing papers by "Polytechnic University of Turin published in 2013"

An atomic clock with $10^{-18}$ instability

Abstract: Atomic clocks have been instrumental in science and technology, leading to innovations such as global positioning, advanced communications, and tests of fundamental constant variation. Timekeeping precision at 1 part in 10 18 enables new timing applications in relativistic geodesy, enhanced Earth- and space-based navigation and telescopy, and new tests of physics beyond the standard model. Here, we describe the development and operation of two optical lattice clocks, both using spin-polarized, ultracold atomic ytterbium. A measurement comparing these systems demonstrates an unprecedented atomic clock instability of 1.6 × 10 –18 after only 7 hours of averaging.

Centrality dependence of pi, K, and p production in Pb-Pb collisions at root s(NN)=2.76 TeV

Abstract: In this paper measurements are presented of pi(+/-), K-+/-, p, and (p) over bar production at midrapidity (vertical bar y vertical bar < 0.5), in Pb-Pb collisions at root s(NN) = 2.76 TeV as a function of centrality. The measurement covers the transverse-momentum (p(T)) range from 100, 200, and 300 MeV/c up to 3, 3, and 4.6 GeV/c for pi, K, and p, respectively. The measured p(T) distributions and yields are compared to expectations based on hydrodynamic, thermal and recombination models. The spectral shapes of central collisions show a stronger radial flow than measured at lower energies, which can be described in hydrodynamic models. In peripheral collisions, the p(T) distributions are not well reproduced by hydrodynamic models. Ratios of integrated particle yields are found to be nearly independent of centrality. The yield of protons normalized to pions is a factor similar to 1.5 lower than the expectation from thermal models.

The integrated landscape of driver genomic alterations in glioblastoma

Abstract: Glioblastoma is one of the most challenging forms of cancer to treat. Here we describe a computational platform that integrates the analysis of copy number variations and somatic mutations and unravels the landscape of in-frame gene fusions in glioblastoma. We found mutations with loss of heterozygosity in LZTR1, encoding an adaptor of CUL3-containing E3 ligase complexes. Mutations and deletions disrupt LZTR1 function, which restrains the self renewal and growth of glioma spheres that retain stem cell features. Loss-of-function mutations in CTNND2 target a neural-specific gene and are associated with the transformation of glioma cells along the very aggressive mesenchymal phenotype. We also report recurrent translocations that fuse the coding sequence of EGFR to several partners, with EGFR-SEPT14 being the most frequent functional gene fusion in human glioblastoma. EGFR-SEPT14 fusions activate STAT3 signaling and confer mitogen independence and sensitivity to EGFR inhibition. These results provide insights into the pathogenesis of glioblastoma and highlight new targets for therapeutic intervention.

Static, free vibration and buckling analysis of isotropic and sandwich functionally graded plates using a quasi-3D higher-order shear deformation theory and a meshless technique

Abstract: In this paper the authors derive a higher-order shear deformation theory for modeling functionally graded plates accounting for extensibility in the thickness direction. The explicit governing equations and boundary conditions are obtained using the principle of virtual displacements under Carrera’s Unified Formulation. The static and eigenproblems are solved by collocation with radial basis functions. The efficiency of the present approach is assessed with numerical results including deflection, stresses, free vibration, and buckling of functionally graded isotropic plates and functionally graded sandwich plates.

Centrality determination of Pb-Pb collisions at root s(NN)=2.76 TeV with ALICE

Abstract: This publication describes the methods used to measure the centrality of inelastic Pb-Pb collisions at a center-of-mass energy of 2.76 TeV per colliding nucleon pair with ALICE. The centrality is a key parameter in the study of the properties of QCD matter at extreme temperature and energy density, because it is directly related to the initial overlap region of the colliding nuclei. Geometrical properties of the collision, such as the number of participating nucleons and the number of binary nucleon-nucleon collisions, are deduced from a Glauber model with a sharp impact parameter selection and shown to be consistent with those extracted from the data. The centrality determination provides a tool to compare ALICE measurements with those of other experiments and with theoretical calculations.

Opinion Fluctuations and Disagreement in Social Networks

Abstract: We study a tractable opinion dynamics model that generates long-run disagreements and persistent opinion fluctuations. Our model involves an inhomogeneous stochastic gossip process of continuous opinion dynamics in a society consisting of two types of agents: 1 regular agents who update their beliefs according to information that they receive from their social neighbors and 2 stubborn agents who never update their opinions and might represent leaders, political parties, or media sources attempting to influence the beliefs in the rest of the society. When the society contains stubborn agents with different opinions, the belief dynamics never lead to a consensus among the regular agents. Instead, beliefs in the society fail to converge almost surely, the belief profile keeps on fluctuating in an ergodic fashion, and it converges in law to a nondegenerate random vector. The structure of the graph describing the social network and the location of the stubborn agents within it shape the opinion dynamics. The expected belief vector is proved to evolve according to an ordinary differential equation coinciding with the Kolmogorov backward equation of a continuous-time Markov chain on the graph with absorbing states corresponding to the stubborn agents, and hence to converge to a harmonic vector, with every regular agent's value being the weighted average of its neighbors' values, and boundary conditions corresponding to the stubborn agents' beliefs. Expected cross products of the agents' beliefs allow for a similar characterization in terms of coupled Markov chains on the graph describing the social network. We prove that, in large-scale societies, which are highly fluid, meaning that the product of the mixing time of the Markov chain on the graph describing the social network and the relative size of the linkages to stubborn agents vanishes as the population size grows large, a condition of homogeneous influence emerges, whereby the stationary beliefs' marginal distributions of most of the regular agents have approximately equal first and second moments.

Influence of process parameters on surface roughness of aluminum parts produced by DMLS.

Abstract: Direct metal laser sintering (DMLS) is an additive manufacturing technique for the fabrication of near net-shaped parts directly from computer-aided design data by melting together different layers with the help of a laser source. This paper presents an investigation of the surface roughness of aluminum samples produced by DMLS. A model based on an L18 orthogonal array of Taguchi design was created to perform experimental planning. Some input parameters, namely laser power, scan speed, and hatching distance were selected for the investigation. The upper surfaces of the samples were analyzed before and after shot peening. The morphology was analyzed by means of field emission scanning electron microscope. Scan speed was found to have the greatest influence on the surface roughness. Further, shot peening can effectively reduce the surface roughness.

Experimental realization of quantum illumination.

Abstract: We present the first experimental realization of the quantum illumination protocol proposed by Lloyd [Science 321, 1463 (2008)] and S. Tan et al. [Phys. Rev. Lett. 101, 253601 (2008)], achieved in a simple feasible experimental scheme based on photon-number correlations. A main achievement of our result is the demonstration of a strong robustness of the quantum protocol to noise and losses that challenges some widespread wisdom about quantum technologies.

Computational Models for Polydisperse Particulate and Multiphase Systems

Abstract: Providing a clear description of the theory of polydisperse multiphase flows, with emphasis on the mesoscale modelling approach and its relationship with microscale and macroscale models, this all-inclusive introduction is ideal whether you are working in industry or academia. Theory is linked to practice through discussions of key real-world cases (particle/droplet/bubble coalescence, break-up, nucleation, advection and diffusion and physical- and phase-space), providing valuable experience in simulating systems that can be applied to your own applications. Practical cases of QMOM, DQMOM, CQMOM, EQMOM and ECQMOM are also discussed and compared, as are realizable finite-volume methods. This provides the tools you need to use quadrature-based moment methods, choose from the many available options, and design high-order numerical methods that guarantee realizable moment sets. In addition to the numerous practical examples, MATLAB scripts for several algorithms are also provided, so you can apply the methods described to practical problems straight away

Integrated transcriptional and competitive endogenous RNA networks are cross-regulated in permissive molecular environments

Abstract: Competitive endogenous (ce)RNAs cross-regulate each other through sequestration of shared microRNAs and form complex regulatory networks based on their microRNA signature. However, the molecular requirements for ceRNA cross-regulation and the extent of ceRNA networks remain unknown. Here, we present a mathematical mass-action model to determine the optimal conditions for ceRNA activity in silico. This model was validated using phosphatase and tensin homolog (PTEN) and its ceRNA VAMP (vesicle-associated membrane protein)-associated protein A (VAPA) as paradigmatic examples. A computational assessment of the complexity of ceRNA networks revealed that transcription factor and ceRNA networks are intimately intertwined. Notably, we found that ceRNA networks are responsive to transcription factor up-regulation or their aberrant expression in cancer. Thus, given optimal molecular conditions, alterations of one ceRNA can have striking effects on integrated ceRNA and transcriptional networks.

From Powders to Dense Metal Parts: Characterization of a Commercial AlSiMg Alloy Processed through Direct Metal Laser Sintering.

Abstract: In this paper, a characterization of an AlSiMg alloy processed by direct metal laser sintering (DMLS) is presented, from the analysis of the starting powders, in terms of size, morphology and chemical composition, through to the evaluation of mechanical and microstructural properties of specimens built along different orientations parallel and perpendicular to the powder deposition plane. With respect to a similar aluminum alloy as-fabricated, a higher yield strength of about 40% due to the very fine microstructure, closely related to the mechanisms involved in this additive process is observed.

K-S(0) and Lambda Production in Pb-Pb Collisions at root s(NN)=2: 76 TeV

Abstract: The ALICE measurement of K^0_S and {\Lambda} production at mid-rapidity in Pb-Pb collisions at sqrt(sNN) = 2.76 TeV is presented. The transverse momentum (pT) spectra are shown for several collision centrality intervals and in the pT range from 0.4 GeV/c (0.6 GeV/c for {\Lambda}) to 12 GeV/c. The pT dependence of the {\Lambda}/K^0_S ratios exhibits maxima in the vicinity of 3 GeV/c, and the positions of the maxima shift towards higher pT with increasing collision centrality. The magnitude of these maxima increases by almost a factor of three between most peripheral and most central Pb-Pb collisions. This baryon excess at intermediate pT is not observed in pp interactions at sqrt(s) = 0.9 TeV and at sqrt(s) = 7 TeV. Qualitatively, the baryon enhancement in heavy-ion collisions is expected from radial flow. However, the measured pT spectra above 2 GeV/c progressively decouple from hydrodynamical-model calculations. For higher values of pT, models that incorporate the influence of the medium on the fragmentation and hadronization processes describe qualitatively the pT dependence of the {\Lambda}/K^0_S ratio.

Long-range angular correlations of pi, K and p in p-Pb collisions at root s(NN)=5.02 TeV

Abstract: Angular correlations between unidentified charged trigger particles and various species of charged associated particles (unidentified particles, pions, kaons, protons and antiprotons) are measured by the ALICE detector in p-Pb collisions at a nucleon-nucleon centre-of-mass energy of 5.02 TeV in the transverse-momentum range 0.3 < p(T) < 4 GeV/c. The correlations expressed as associated yield per trigger particle are obtained in the pseudorapidity range vertical bar n(lab)vertical bar < 0.8. Fourier coefficients are extracted from the long-range correlations projected onto the azimuthal angle difference and studied as a function of p(T) and in intervals of event multiplicity. In high-multiplicity events, the second-order coefficient for protons, 4, is observed to be smaller than that for pions, v(2)(pi), up to about p(T) = 2 GeV/c. To reduce correlations due to jets, the per-trigger yield measured in low-multiplicity events is subtracted from that in high-multiplicity events. A two-ridge structure is obtained for all particle species. The Fourier decomposition of this structure shows that the second-order coefficients for pions and kaons are similar. The v(2)(p) is found to be smaller at low P-T and larger at higher p(T) than v(2)(pi), with a crossing occurring at about 2 GeV/c. This is qualitatively similar to the elliptic-flow pattern observed in heavy-ion collisions. A mass ordering effect at low transverse momenta is consistent with expectations from hydrodynamic model calculations assuming a collectively expanding system. (C) 2013 CERN. Published by Elsevier B.V. All rights reserved.

Performance of the ALICE VZERO system

Abstract: ALICE is an LHC experiment devoted to the study of strongly interacting matter in proton-proton, proton-nucleus and nucleus-nucleus collisions at ultra-relativistic energies. The ALICE VZERO system, made of two scintillator arrays at asymmetric positions, one on each side of the interaction point, plays a central role in ALICE. In addition to its core function as a trigger source, the VZERO system is used to monitor LHC beam conditions, to reject beam-induced backgrounds and to measure basic physics quantities such as luminosity, particle multiplicity, centrality and event plane direction in nucleus-nucleus collisions. After describing the VZERO system, this publication presents its performance over more than four years of operation at the LHC.

Cellulose-based Li-ion batteries: a review

Abstract: Li-ion batteries (LIBs) are the most employed power source in portable electronics (eg, cellular phones, laptop computers…) and are accounted as very promising storage/power systems for future electric/hybrid-electric powered transportation However for their future development, low production costs and environmental friendliness will be key parameters In this context, the introduction of water processable biosourced polymers such as cellulose and its derivatives is very interesting and is emerging as a viable route toward the development of green materials and processes for LIB manufacturing The present review briefly introduces the Li-ion technology and gives an overview on cellulose and cellulose derivatives for the elaboration of separators, electrolytes and electrodes

DNA: a novel, green, natural flame retardant and suppressant for cotton

Abstract: For the first time, deoxyribonucleic acid (DNA) from herring sperm has been employed as a novel flame retardant system for enhancing the thermal stability and flame retardant properties of cotton fabrics. Indeed, DNA could be considered an intrinsically intumescent flame retardant as it contains the three main components that are usually present in an intumescent formulation, namely: the phosphate groups, able to produce phosphoric acid, the deoxyribose units acting as a carbon source and blowing agents (upon heating a (poly)saccharide dehydrates forming char and releasing water) and the nitrogen-containing bases (guanine, adenine, thymine, and cytosine) that may release ammonia. The flammability tests in horizontal configuration have clearly shown that after two applications of a methane flame for 3 s, the DNA-treated cotton fabrics do not burn at all. Furthermore, when exposed to an irradiative heat flux of 35 kW m−2, no ignition has been observed. Finally, an LOI value of 28% has been achieved for the treated fabrics as opposed to 18% of the untreated fabric.

Topological Strata of Weighted Complex Networks.

Abstract: The statistical mechanical approach to complex networks is the dominant paradigm in describing natural and societal complex systems. The study of network properties, and their implications on dynamical processes, mostly focus on locally defined quantities of nodes and edges, such as node degrees, edge weights and –more recently– correlations between neighboring nodes. However, statistical methods quickly become cumbersome when dealing with many-body properties and do not capture the precise mesoscopic structure of complex networks. Here we introduce a novel method, based on persistent homology, to detect particular non-local structures, akin to weighted holes within the link-weight network fabric, which are invisible to existing methods. Their properties divide weighted networks in two broad classes: one is characterized by small hierarchically nested holes, while the second displays larger and longer living inhomogeneities. These classes cannot be reduced to known local or quasilocal network properties, because of the intrinsic non-locality of homological properties, and thus yield a new classification built on high order coordination patterns. Our results show that topology can provide novel insights relevant for many-body interactions in social and spatial networks. Moreover, this new method creates the first bridge between network theory and algebraic topology, which will allow to import the toolset of algebraic methods to complex systems.

Temporal locality in today's content caching: why it matters and how to model it

Abstract: The dimensioning of caching systems represents a difficult task in the design of infrastructures for content distribution in the current Internet. This paper addresses the problem of defining a realistic arrival process for the content requests generated by users, due its critical importance for both analytical and simulative evaluations of the performance of caching systems. First, with the aid of \youtube traces collected inside operational residential networks, we identify the characteristics of real traffic that need to be considered or can be safely neglected in order to accurately predict the performance of a cache. Second, we propose a new parsimonious traffic model, named the Shot Noise Model (SNM), that enables users to natively capture the dynamics of content popularity, whilst still being sufficiently simple to be employed effectively for both analytical and scalable simulative studies of caching systems. Finally, our results show that the SNM presents a much better solution to account for the temporal locality observed in real traffic compared to existing approaches.

Financial Literacy and the Demand for Financial Advice

Abstract: The low level of financial literacy across households suggests they are at risk of taking sub-optimal financial decisions. In this paper we assess to what extent financial advisors can substitute for low financial knowledge. We analyze the effect of investors' financial literacy on their demand of professional, non-independent advice. Using the 2007 Unicredit Customers' Survey we find that non-independent advisors are not sufficient to alleviate the problem of low financial literacy. Investors with a low level of financial literacy are less likely to consult with an advisor, while they delegate their portfolio choice more often or do not invest in risky assets. We explain this evidence with a highly stylized model of strategic interaction between investors and better informed advisors facing conflicts of interests. Advisors reveal information only to the more knowledgeable investors, who anticipating this are then more likely to consult with them.

Modeling the interactions between river morphodynamics and riparian vegetation

Abstract: The study of river-riparian vegetation interactions is an important and intriguing research field in geophysics. Vegetation is an active element of the ecological dynamics of a floodplain which interacts with the fluvial processes and affects the flow field, sediment transport, and the morphology of the river. In turn, the river provides water, sediments, nutrients, and seeds to the nearby riparian vegetation, depending on the hydrological, hydraulic, and geomorphological characteristic of the stream. In the past, the study of this complex theme was approached in two different ways. On the one hand, the subject was faced from a mainly qualitative point of view by ecologists and biogeographers. Riparian vegetation dynamics and its spatial patterns have been described and demonstrated in detail, and the key role of several fluvial processes has been shown, but no mathematical models have been proposed. On the other hand, the quantitative approach to fluvial processes, which is typical of engineers, has led to the development of several morphodynamic models. However, the biological aspect has usually been neglected, and vegetation has only been considered as a static element. In recent years, different scientific communities (ranging from ecologists to biogeographers and from geomorphologists to hydrologists and fluvial engineers) have begun to collaborate and have proposed both semiquantitative and quantitative models of river-vegetation interconnections. These models demonstrate the importance of linking fluvial morphodynamics and riparian vegetation dynamics to understand the key processes that regulate a riparian environment in order to foresee the impact of anthropogenic actions and to carefully manage and rehabilitate riparian areas. In the first part of this work, we review the main interactions between rivers and riparian vegetation, and their possible modeling. In the second part, we discuss the semiquantitative and quantitative models which have been proposed to date, considering both multi- and single-thread rivers.

Perturbation Biology: Inferring Signaling Networks in Cellular Systems

Abstract: We present a powerful experimental-computational technology for inferring network models that predict the response of cells to perturbations, and that may be useful in the design of combinatorial therapy against cancer The experiments are systematic series of perturbations of cancer cell lines by targeted drugs, singly or in combination The response to perturbation is quantified in terms of relative changes in the measured levels of proteins, phospho-proteins and cellular phenotypes such as viability Computational network models are derived de novo, ie, without prior knowledge of signaling pathways, and are based on simple non-linear differential equations The prohibitively large solution space of all possible network models is explored efficiently using a probabilistic algorithm, Belief Propagation (BP), which is three orders of magnitude faster than standard Monte Carlo methods Explicit executable models are derived for a set of perturbation experiments in SKMEL-133 melanoma cell lines, which are resistant to the therapeutically important inhibitor of RAF kinase The resulting network models reproduce and extend known pathway biology They empower potential discoveries of new molecular interactions and predict efficacious novel drug perturbations, such as the inhibition of PLK1, which is verified experimentally This technology is suitable for application to larger systems in diverse areas of molecular biology

Novel cobalt/nickel–tungsten-sulfide catalysts for electrocatalytic hydrogen generation from water

Abstract: The potential of water (photo)electrolysis technology to provide hydrogen as a fuel on a large scale depends on how viable electrocatalysts for the water oxidation reaction (WOR) and the hydrogen evolution reaction (HER) are and whether they can be constructed from elements which are abundant in the Earth's crust. Here we show that ternary sulfides of cobalt–tungsten and nickel–tungsten (MWSx where M is Co or Ni) are efficient and robust electrocatalysts for the HER in water over a wide pH range. These novel ternary sulfides were readily grown on a conducting electrode surface by employing a scalable electrodeposition process from aqueous solutions of [M(WS4)2]2−. In terms of HER activity, the MWSx catalysts represent attractive alternatives to platinum. Moreover, we show that the HER activity is governed by the nature of the metal M within M–S–W heterobimetallic sulfide centres, located in the WS2-like layered structure of MWSx. Our work provides structural and mechanistic keys to understand how HER activity is promoted in previously described nickel and cobalt-doped molybdenum and tungsten sulfide materials.