Showing papers by "University of Trento published in 2011"

Light Propagation with Phase Discontinuities: Generalized Laws of Reflection and Refraction

Abstract: Conventional optical components rely on gradual phase shifts accumulated during light propagation to shape light beams. New degrees of freedom are attained by introducing abrupt phase changes over the scale of the wavelength. A two-dimensional array of optical resonators with spatially varying phase response and subwavelength separation can imprint such phase discontinuities on propagating light as it traverses the interface between two media. Anomalous reflection and refraction phenomena are observed in this regime in optically thin arrays of metallic antennas on silicon with a linear phase variation along the interface, which are in excellent agreement with generalized laws derived from Fermat’s principle. Phase discontinuities provide great flexibility in the design of light beams, as illustrated by the generation of optical vortices through use of planar designer metallic interfaces.

Classification of primary progressive aphasia and its variants

Abstract: This article provides a classification of primary progressive aphasia (PPA) and its 3 main variants to improve the uniformity of case reporting and the reliability of research results. Criteria for the 3 variants of PPA—nonfluent/agrammatic, semantic, and logopenic—were developed by an international group of PPA investigators who convened on 3 occasions to operationalize earlier published clinical descriptions for PPA subtypes. Patients are first diagnosed with PPA and are then divided into clinical variants based on specific speech and language features characteristic of each subtype. Classification can then be further specified as “imaging-supported” if the expected pattern of atrophy is found and “with definite pathology” if pathologic or genetic data are available. The working recommendations are presented in lists of features, and suggested assessment tasks are also provided. These recommendations have been widely agreed upon by a large group of experts and should be used to ensure consistency of PPA classification in future studies. Future collaborations will collect prospective data to identify relationships between each of these syndromes and specific biomarkers for a more detailed understanding of clinicopathologic correlations.

The productivity crisis in pharmaceutical R&D

Abstract: Advances in the understanding of the molecular basis of diseases have expanded the number of plausible therapeutic targets for the development of innovative agents in recent decades. However, although investment in pharmaceutical research and development (R&D) has increased substantially in this time, the lack of a corresponding increase in the output in terms of new drugs being approved indicates that therapeutic innovation has become more challenging. Here, using a large database that contains information on R&D projects for more than 28,000 compounds investigated since 1990, we examine the decline of R&D productivity in pharmaceuticals in the past two decades and its determinants. We show that this decline is associated with an increasing concentration of R&D investments in areas in which the risk of failure is high, which correspond to unmet therapeutic needs and unexploited biological mechanisms. We also investigate the potential variations in productivity with regard to the regional location of companies and find that although companies based in the United States and Europe differ in the composition of their R&D portfolios, there is no evidence of any productivity gap.

Segmentation as selective search for object recognition

Abstract: For object recognition, the current state-of-the-art is based on exhaustive search. However, to enable the use of more expensive features and classifiers and thereby progress beyond the state-of-the-art, a selective search strategy is needed. Therefore, we adapt segmentation as a selective search by reconsidering segmentation: We propose to generate many approximate locations over few and precise object delineations because (1) an object whose location is never generated can not be recognised and (2) appearance and immediate nearby context are most effective for object recognition. Our method is class-independent and is shown to cover 96.7% of all objects in the Pascal VOC 2007 test set using only 1,536 locations per image. Our selective search enables the use of the more expensive bag-of-words method which we use to substantially improve the state-of-the-art by up to 8.5% for 8 out of 20 classes on the Pascal VOC 2010 detection challenge.

Molecular Characterization of Neuroendocrine Prostate Cancer and Identification of New Drug Targets

Abstract: Neuroendocrine prostate cancer (NEPC) is an aggressive subtype of prostate cancer that most commonly evolves from preexisting prostate adenocarcinoma (PCA). Using next-generation RNA sequencing and oligonucleotide arrays, we profiled 7 NEPC, 30 PCA, and 5 benign prostate tissue (BEN) samples and validated findings in tumors from a large cohort of patients (37 with NEPC, 169 with PCA, and 22 with BEN) using immunohistochemistry and FISH. We discovered significant overexpression and gene amplification of AURKA and MYCN in 40% of NEPC and 5% of PCA tumors, respectively, and evidence that they cooperate to induce a neuroendocrine phenotype in prostate cells. There was dramatic and enhanced sensitivity of NEPC (and MYCN overexpressing PCA) to Aurora kinase inhibitor therapy both in vitro and in vivo , with complete suppression of neuroendocrine marker expression following treatment. We propose that alterations in Aurora kinase A and N-myc are involved in the development of NEPC and that future clinical trials will help determine the efficacy of Aurora kinase inhibitor therapy. Significance: We report on the largest in-depth molecular analysis of NEPC and provide new insight into molecular events involved in the progression of prostate cancer. Cancer Discovery; 1(6) ; 487–95. ©2011 AACR . Read the Commentary on this article by Aparicio et al., [p. 466][1] This article is highlighted in the In This Issue feature, [p. 457][2] [1]: /lookup/volpage/1/466?iss=6 [2]: /lookup/volpage/1/457?iss=6

Observation and studies of jet quenching in PbPb collisions at √sNN=2.76 TeV

Abstract: Jet production in PbPb collisions at a nucleon-nucleon center-of-mass energy of 2.76 TeV was studied with the CMS detector at the LHC, using a data sample corresponding to an integrated luminosity of 6.7 inverse microbarns. Jets are reconstructed using the energy deposited in the CMS calorimeters and studied as a function of collision centrality. With increasing collision centrality, a striking imbalance in dijet transverse momentum is observed, consistent with jet quenching. The observed effect extends from the lower cut-off used in this study (jet transverse momentum = 120 GeV/c) up to the statistical limit of the available data sample (jet transverse momentum approximately 210 GeV/c). Correlations of charged particle tracks with jets indicate that the momentum imbalance is accompanied by a softening of the fragmentation pattern of the second most energetic, away-side jet. The dijet momentum balance is recovered when integrating low transverse momentum particles distributed over a wide angular range relative to the direction of the away-side jet.

l 2,1 -norm regularized discriminative feature selection for unsupervised learning

Abstract: Compared with supervised learning for feature selection, it is much more difficult to select the discriminative features in unsupervised learning due to the lack of label information. Traditional unsupervised feature selection algorithms usually select the features which best preserve the data distribution, e.g., manifold structure, of the whole feature set. Under the assumption that the class label of input data can be predicted by a linear classifier, we incorporate discriminative analysis and l2,1-norm minimization into a joint framework for unsupervised feature selection. Different from existing unsupervised feature selection algorithms, our algorithm selects the most discriminative feature subset from the whole feature set in batch mode. Extensive experiment on different data types demonstrates the effectiveness of our algorithm.

Differential Evolution as Applied to Electromagnetics

Abstract: In electromagnetics, optimization problems generally require high computational resources and involve a large number of unknowns. They are usually characterized by non-convex functionals and continuous spaces suitable for strategies based on Differential Evolution (DE). In such a framework, this paper is aimed at presenting an overview of Differential Evolution-based approaches used in electromagnetics, pointing out novelties and customizations with respect to other fields of application. Starting from a general description of the evolutionary mechanism of Differential Evolution, Differential Evolution-based techniques for electromagnetic optimization are presented. Some hints on the convergence properties and the sensitivity to control parameters are also given. Finally, a comprehensive coverage of different Differential Evolution formulations in solving optimization problems in the area of computational electromagnetics is presented, focusing on antenna synthesis and inverse scattering.

Classification of Hyperspectral Images by Using Extended Morphological Attribute Profiles and Independent Component Analysis

Abstract: In this letter, a technique based on independent component analysis (ICA) and extended morphological attribute profiles (EAPs) is presented for the classification of hyperspectral images. The ICA maps the data into a subspace in which the components are as independent as possible. APs, which are extracted by using several attributes, are applied to each image associated with an extracted independent component, leading to a set of extended EAPs. Two approaches are presented for including the computed profiles in the analysis. The features extracted by the morphological processing are then classified with an SVM. The experiments carried out on two hyperspectral images proved the effectiveness of the proposed technique.

Programming wireless sensor networks: Fundamental concepts and state of the art

Abstract: Wireless sensor networks (WSNs) are attracting great interest in a number of application domains concerned with monitoring and control of physical phenomena, as they enable dense and untethered deployments at low cost and with unprecedented flexibility. However, application development is still one of the main hurdles to a wide adoption of WSN technology. In current real-world WSN deployments, programming is typically carried out very close to the operating system, therefore requiring the programmer to focus on low-level system issues. This not only distracts the programmer from the application logic, but also requires a technical background rarely found among application domain experts. The need for appropriate high-level programming abstractions, capable of simplifying the programming chore without sacrificing efficiency, has long been recognized, and several solutions have hitherto been proposed, which differ along many dimensions. In this article, we survey the state of the art in programming approaches for WSNs. We begin by presenting a taxonomy of WSN applications, to identify the fundamental requirements programming platforms must deal with. Then, we introduce a taxonomy of WSN programming approaches that captures the fundamental differences among existing solutions, and constitutes the core contribution of this article. Our presentation style relies on concrete examples and code snippets taken from programming platforms representative of the taxonomy dimensions being discussed. We use the taxonomy to provide an exhaustive classification of existing approaches. Moreover, we also map existing approaches back to the application requirements, therefore providing not only a complete view of the state of the art, but also useful insights for selecting the programming abstraction most appropriate to the application at hand.

Polariton Superfluids Reveal Quantum Hydrodynamic Solitons

Abstract: A quantum fluid passing an obstacle behaves differently from a classical one. When the flow is slow enough, the quantum gas enters a superfluid regime, and neither whirlpools nor waves form around the obstacle. For higher flow velocities, it has been predicted that the perturbation induced by the defect gives rise to the turbulent emission of quantized vortices and to the nucleation of solitons. Using an interacting Bose gas of exciton-polaritons in a semiconductor microcavity, we report the transition from superfluidity to the hydrodynamic formation of oblique dark solitons and vortex streets in the wake of a potential barrier. The direct observation of these topological excitations provides key information on the mechanisms of superflow and shows the potential of polariton condensates for quantum turbulence studies.

The developmental roots of fairness: infants’ reactions to equal and unequal distributions of resources

Abstract: The problem of how to distribute available resources among members of a group is a central aspect of social life. Adults react negatively to inequitable distributions and several studies have reported negative reactions to inequity also in non-human primates and dogs. We report two experiments on infants' reactions to equal and unequal distributions. In two experiments, infants' looking times and manual choices provide, for the first time, converging evidence suggesting that infants aged 12 to 18 months (mean age 16 months) attend to the outcomes of distributive actions to evaluate agents' actions and to reason about agents' dispositions. The results provide support for recent theoretical proposals on the developmental roots of social evaluation skills and a sense of fairness.

Scaffolds for tissue engineering and 3D cell culture.

Abstract: In tissue engineering applications or even in 3D cell cultures, the biological cross talk between cells and the scaffold is controlled by the material properties and scaffold characteristics. In order to induce cell adhesion, proliferation, and activation, materials used for the fabrication of scaffolds must possess requirements such as intrinsic biocompatibility and proper chemistry to induce molecular biorecognition from cells. Materials, scaffold mechanical properties and degradation kinetics should be adapted to the specific tissue engineering application to guarantee the required mechanical functions and to accomplish the rate of the new-tissue formation. For scaffolds, pore distribution, exposed surface area, and porosity play a major role, whose amount and distribution influence the penetration and the rate of penetration of cells within the scaffold volume, the architecture of the produced extracellular matrix, and for tissue engineering applications, the final effectiveness of the regenerative process. Depending on the fabrication process, scaffolds with different architecture can be obtained, with random or tailored pore distribution. In the recent years, rapid prototyping computer-controlled techniques have been applied to the fabrication of scaffolds with ordered geometry. This chapter reviews the principal polymeric materials that are used for the fabrication of scaffolds and the scaffold fabrication processes, with examples of properties and selected applications.

How we BLESSed distributional semantic evaluation

Abstract: We introduce BLESS, a data set specifically designed for the evaluation of distributional semantic models BLESS contains a set of tuples instantiating different, explicitly typed semantic relations, plus a number of controlled random tuples It is thus possible to assess the ability of a model to detect truly related word pairs, as well as to perform in-depth analyses of the types of semantic relations that a model favors We discuss the motivations for BLESS, describe its construction and structure, and present examples of its usage in the evaluation of distributional semantic models

Search for supersymmetry at the LHC in events with jets and missing transverse energy

Abstract: A search for events with jets and missing transverse energy is performed in a data sample of pp collisions collected at sqrt(s) = 7 TeV by the CMS experiment at the LHC. The analyzed data sample corresponds to an integrated luminosity of 1.14 inverse femtobarns. In this search, a kinematic variable, alphaT, is used as the main discriminator between events with genuine and misreconstructed missing transverse energy. No excess of events over the standard model expectation is found. Exclusion limits in the parameter space of the constrained minimal supersymmetric extension of the standard model are set. In this model, squark masses below 1.1 TeV are excluded at 95% CL. Gluino masses below 1.1 TeV are also ruled out at 95% CL for values of the universal scalar mass parameter below 500 GeV.

Bayesian Compressive Sampling for Pattern Synthesis With Maximally Sparse Non-Uniform Linear Arrays

Abstract: A numerically-efficient technique based on the Bayesian compressive sampling (BCS) for the design of maximally-sparse linear arrays is introduced. The method is based on a probabilistic formulation of the array synthesis and it exploits a fast relevance vector machine (RVM) for the problem solution. The proposed approach allows the design of linear arrangements fitting desired power patterns with a reduced number of non-uniformly spaced active elements. The numerical validation assesses the effectiveness and computational efficiency of the proposed approach as a suitable complement to existing state-of-the-art techniques for the design of sparse arrays.

White matter damage in primary progressive aphasias: a diffusion tensor tractography study

Abstract: Primary progressive aphasia is a clinical syndrome that encompasses three major phenotypes: non-fluent/agrammatic, semantic and logopenic. These clinical entities have been associated with characteristic patterns of focal grey matter atrophy in left posterior frontoinsular, anterior temporal and left temporoparietal regions, respectively. Recently, network-level dysfunction has been hypothesized but research to date has focused largely on studying grey matter damage. The aim of this study was to assess the integrity of white matter tracts in the different primary progressive aphasia subtypes. We used diffusion tensor imaging in 48 individuals: nine non-fluent, nine semantic, nine logopenic and 21 age-matched controls. Probabilistic tractography was used to identify bilateral inferior longitudinal (anterior, middle, posterior) and uncinate fasciculi (referred to as the ventral pathway); and the superior longitudinal fasciculus segmented into its frontosupramarginal, frontoangular, frontotemporal and temporoparietal components, (referred to as the dorsal pathway). We compared the tracts’ mean fractional anisotropy, axial, radial and mean diffusivities for each tract in the different diagnostic categories. The most prominent white matter changes were found in the dorsal pathways in non-fluent patients, in the two ventral pathways and the temporal components of the dorsal pathways in semantic variant, and in the temporoparietal component of the dorsal bundles in logopenic patients. Each of the primary progressive aphasia variants showed different patterns of diffusion tensor metrics alterations: non-fluent patients showed the greatest changes in fractional anisotropy and radial and mean diffusivities; semantic variant patients had severe changes in all metrics; and logopenic patients had the least white matter damage, mainly involving diffusivity, with fractional anisotropy altered only in the temporoparietal component of the dorsal pathway. This study demonstrates that both careful dissection of the main language tracts and consideration of all diffusion tensor metrics are necessary to characterize the white matter changes that occur in the variants of primary progressive aphasia. These results highlight the potential value of diffusion tensor imaging as a new tool in the multimodal diagnostic evaluation of primary progressive aphasia.

Batch-Mode Active-Learning Methods for the Interactive Classification of Remote Sensing Images

Abstract: This paper investigates different batch-mode active-learning (AL) techniques for the classification of remote sensing (RS) images with support vector machines. This is done by generalizing to multiclass problem techniques defined for binary classifiers. The investigated techniques exploit different query functions, which are based on the evaluation of two criteria: uncertainty and diversity. The uncertainty criterion is associated to the confidence of the supervised algorithm in correctly classifying the considered sample, while the diversity criterion aims at selecting a set of unlabeled samples that are as more diverse (distant one another) as possible, thus reducing the redundancy among the selected samples. The combination of the two criteria results in the selection of the potentially most informative set of samples at each iteration of the AL process. Moreover, we propose a novel query function that is based on a kernel-clustering technique for assessing the diversity of samples and a new strategy for selecting the most informative representative sample from each cluster. The investigated and proposed techniques are theoretically and experimentally compared with state-of-the-art methods adopted for RS applications. This is accomplished by considering very high resolution multispectral and hyperspectral images. By this comparison, we observed that the proposed method resulted in better accuracy with respect to other investigated and state-of-the art methods on both the considered data sets. Furthermore, we derived some guidelines on the design of AL systems for the classification of different types of RS images.

Artificial gauge field for photons in coupled cavity arrays

Abstract: We propose and characterize solid-state photonic structures where light experiences an artificial gauge field. A nontrivial phase for photons tunneling between adjacent sites of a coupled cavity array can be obtained by inserting optically active materials in the structure or by inducing a suitable coupling of the propagation and polarization degrees of freedom. We also discuss the feasibility of observing strong gauge field effects in the optical spectra of realistic systems, including the Hofstadter butterfly spectrum.

Origin of strong photon antibunching in weakly nonlinear photonic molecules

Abstract: In a recent work [Liew and Savona, Phys. Rev. Lett. 104, 183601 (2010)] it was numerically shown that a resonantly driven photonic ``molecule'' consisting of two coupled cavities can exhibit strong photon antibunching with a surprisingly weak Kerr nonlinearity. Here, we analytically identify the subtle quantum interference effect that is responsible for the predicted efficient photon blockade effect. We then extend the theory to the experimentally relevant Jaynes-Cummings system consisting of a single quantum emitter in a coupled-cavity structure and predict the strong antibunching even for single-atom cooperativity on the order of or smaller than unity. The potential of this quantum interference effect in the realization of strongly correlated photonic systems with only weak material nonlinearities is assessed by comparing on-site and inter-site correlations in a ring of three coupled photonic molecules.

Are sexualized women complete human beings? Why men and women dehumanize sexually objectified women

Abstract: Focusing on the dehumanization of sexually objectified targets, study 1 tested the extent to which objectified and non-objectified male and female publicity photos were associated with human compared to animal concepts. Results confirmed the hypothesis that, among all targets, only objectified women were associated with less human concepts. This pattern of results emerged for both male and female participants but likely for different reasons. Study 2 directly looked at female and male participants' affinity with sexually objectified women. Results indicated that the more women distanced themselves from sexually objectified women the more they dehumanized them, whereas men's sexual attraction moderated their tendency to dehumanize female targets. In study 3, this latter motivation was operationalized as the activation of a sex goal and showed to trigger man's but not woman's dehumanization of female targets. Overall, the present set of studies show that only sexually objectified women are dehumanized by both men and women but for different reasons. Whereas sexual attraction shifts a men's focus of a female target away from her personality onto her body triggering a dehumanization process, women are more inclined to dehumanize their sexually objectified counterparts the more they distance themselves from these sexualized representations of their gender category. Copyright © 2011 John Wiley & Sons, Ltd.

Upsilon production cross section in pp collisions at √s=7 TeV

Abstract: The Upsilon production cross section in proton-proton collisions at sqrt(s) = 7 TeV is measured using a data sample collected with the CMS detector at the LHC, corresponding to an integrated luminosity of 3.1 +/- 0.3 inverse picobarns. Integrated over the rapidity range |y|<2, we find the product of the Upsilon(1S) production cross section and branching fraction to dimuons to be sigma(pp to Upsilon(1S) X) B(Upsilon(1S) to mu+ mu-) = 7.37 +/- 0.13^{+0.61}_{-0.42}\pm 0.81 nb, where the first uncertainty is statistical, the second is systematic, and the third is associated with the estimation of the integrated luminosity of the data sample. This cross section is obtained assuming unpolarized Upsilon(1S) production. If the Upsilon(1S) production polarization is fully transverse or fully longitudinal the cross section changes by about 20%. We also report the measurement of the Upsilon(1S), Upsilon(2S), and Upsilon(3S) differential cross sections as a function of transverse momentum and rapidity.

Flash‐Sintering of Cubic Yttria‐Stabilized Zirconia at 750°C for Possible Use in SOFC Manufacturing

Abstract: We show that cubic 8 mol% yttria (8YSZ) can be sintered at 750°C with the application of DC electrical fields; in comparison the lowest sintering temperature for 3YSZ was 850°C. Furthermore, cubic zirconia exhibits the onset of flash sintering at 30 V/ cm, whereas 3YSZ begins flash sintering at 60 V/cm. However, the volume specific power dissipation for the onset of flash sintering remains similar at ∼10 mW/mm 3 . The easier sintering of 8YSZ is ascribed to its higher ionic conductivity.

Measurement of the inclusive W and Z production cross sections in pp collisions at √s = 7 TeV with the CMS experiment

Abstract: A measurement of inclusive W and Z production cross sections in pp collisions at sqrt(s)=7 TeV is presented. The electron and muon decay channels are analyzed in a data sample collected with the CMS detector at the LHC and corresponding to an integrated luminosity of 36 inverse picobarns. The measured inclusive cross sections are sigma(pp-> WX) B(W-> l nu) = 10.30 +/- 0.02 (stat.) +/- 0.10 (syst.) +/- 0.10 (th.) +/- 0.41 (lumi.) nb and sigma(pp -> ZX) B(Z-> l^+l^-) = 0.974 +/- 0.007 (stat.) +/- 0.007 (syst.) +/- 0.018 (th.) +/- 0.039 (lumi.) nb, limited to the dilepton invariant mass range 60 to 120 GeV. The luminosity-independent cross section ratios are [sigma(pp->WX) B(W-> l nu)]/[sigma(pp-> ZX) B(Z->l^+l^-)] = 10.54 +/- 0.07 (stat.) +/- 0.08 (syst.) +/- 0.16 (th.) and [sigma(pp->W^+X) B(W^+ -> l^+nu)] / [sigma(pp->W^- X) B(W^- -> l^- nu)] = 1.421 +/- 0.006 (stat.) +/- 0.014 (syst.) +/- 0.029 (th.). The measured values agree with next-to-next-to-leading order QCD cross section calculations based on recent parton distribution functions.

Measurements of inclusive W and Z cross sections in pp collisions at \sqrt {s} = 7 TeV

Abstract: Measurements of inclusive W and Z boson production cross sections in pp collisions at sqrt(s)=7 TeV are presented, based on 2.9 inverse picobarns of data recorded by the CMS detector at the LHC. The measurements, performed in the electron and muon decay channels, are combined to give sigma(pp to WX) times B(W to muon or electron + neutrino) = 9.95 \pm 0.07(stat.) \pm 0.28(syst.) \pm 1.09(lumi.) nb and sigma(pp to ZX) times B(Z to oppositely charged muon or electron pairs) = 0.931 \pm 0.026(stat.) \pm 0.023(syst.) \pm 0.102(lumi.) nb. Theoretical predictions, calculated at the next-to-next-to-leading order in QCD using recent parton distribution functions, are in agreement with the measured cross sections. Ratios of cross sections, which incur an experimental systematic uncertainty of less than 4%, are also reported.

Harmonic Beamforming in Time-Modulated Linear Arrays

Abstract: In this paper, the synthesis of simultaneous multibeams through time-modulated linear arrays is studied. Unlike classical phased arrays where the antenna aperture is usually shared to generate multiple beams, the periodic on-off sequences controlling the static excitations are properly defined by means of an optimization strategy based on the Particle Swarm algorithm to afford desired multiple patterns at harmonic frequencies to make practical application of these harmonic beams which are typically regarded as an undesirable effect in time-modulated arrays. The synthesis of simultaneous broadside sum and difference patterns, flat-top and narrow beam patterns, and steered multibeams is enabled as assessed by a set of selected results reported and discussed to show the potentialities of the proposed method. Comparisons with previously published results are reported, as well.