Diffraction grating couplers milled in Si3N4 rib waveguides with a focused ion beam

Focused ion beam milling is a processing technology which allows flexible direct writing of nanometer scale features efficiently substituting electron beam lithography. No mask need results in ability for patterns writing even on fragile micromechanical devices. In this work we studied the abilities of the tool for fabrication of diffraction grating couplers in silicon nitride waveguides. The gratings were fabricated on a chip with extra fragile cantilevers of sub micron thickness. Optical characterization of the couplers was done using excitation of the waveguides in visible range by focused Gaussian beams of different waist sizes. Influence of Ga+ implantation on the device performance was studied.

Normaalijakaumaan perustuva mutaatio-operaatio differentiaalievoluutioalgoritmiin

Evoluutioalgoritmit ovat viime vuosina osoittautuneet tehokkaiksi menetelmiksi globaalien optimointitehtävien ratkaisuun. Niiden vahvuutena on etenkin yleiskäyttöisyys ja kyky löytää globaali ratkaisu juuttumatta optimoitavan tavoitefunktion paikallisiin optimikohtiin. Tässä työssä on tavoitteena kehittää uusi, normaalijakaumaan perustuva mutaatio-operaatio differentiaalievoluutioalgoritmiin, joka on eräs uusimmista evoluutiopohjaisista optimointialgoritmeista. Menetelmän oletetaan vähentävän entisestään sekä populaation ennenaikaisen suppenemisen, että algoritmin tilojen juuttumisen riskiä ja se on teoreettisesti osoitettavissa suppenevaksi. Tämä ei päde alkuperäisen differentiaalievoluution tapauksessa, koska on voitu osoittaa, että sen tilanmuutokset voivat pienellä todennäköisyydellä juuttua. Työssä uuden menetelmän toimintaa tarkastellaan kokeellisesti käyttäen testiongelmina monirajoiteongelmia. Rajoitefunktioiden käsittelyyn käytetään Jouni Lampisen kehittämää, Pareto-optimaalisuuden periaatteeseen perustuvaa menetelmää. Samalla saadaan kerättyä lisää kokeellista näyttöä myös tämän menetelmän toiminnasta. Kaikki käytetyt testiongelmat kyettiin ratkaisemaan sekä alkuperäisellä differentiaalievoluutiolla, että uutta mutaatio-operaatiota käyttävällä versiolla. Uusi menetelmä osoittautui kuitenkin luotettavammaksi sellaisissa tapauksissa, joissa alkuperäisellä algoritmilla oli vaikeuksia. Lisäksi useimmat ongelmat kyettiin ratkaisemaan luotettavasti pienemmällä populaation koolla kuin alkuperäistä differentiaalievoluutiota käytettäessä. Uuden menetelmän käyttö myös mahdollistaa paremmin sellaisten kontrolliparametrien käytön, joilla hausta saadaan rotaatioinvariantti. Laskennallisesti uusi menetelmä on hieman alkuperäistä differentiaalievoluutiota raskaampi ja se tarvitsee yhden kontrolliparametrin enemmän. Uusille kontrolliparametreille määritettiin kuitenkin mahdollisimman yleiskäyttöiset arvot, joita käyttämällä on mahdollista ratkaista suuri joukko erilaisia ongelmia.

From Full stopping to transparency in a holographic model of heavy ion collisions

We numerically simulate planar shock wave collisions in anti-de Sitter space as a model for heavy ion collisions of large nuclei. We uncover a crossover between two different dynamical regimes as a function of the collision energy. At low energies the shocks first stop and then explode in a manner approximately described by hydrodynamics, in close similarity with the Landau model. At high energies the receding fragments move outwards at the speed of light, with a region of negative energy density and negative longitudinal pressure trailing behind them. The rapidity distribution of the energy density at late times around midrapidity is not approximately boost invariant but Gaussian, albeit with a width that increases with the collision energy.

Probabilistic electrical resistivity tomography of a CO2 sequestration analog

Electrical resistivity tomography (ERT) is a well-established method for geophysical characterization and has shown potential for monitoring geologic CO2 sequestration, due to its sensitivity to electrical resistivity contrasts generated by liquid/gas saturation variability. In contrast to deterministic inversion approaches, probabilistic inversion provides the full posterior probability density function of the saturation field and accounts for the uncertainties inherent in the petrophysical parameters relating the resistivity to saturation. In this study, the data are from benchtop ERT experiments conducted during gas injection into a quasi-2D brine-saturated sand chamber with a packing that mimics a simple anticlinal geological reservoir. The saturation fields are estimated by Markov chain Monte Carlo inversion of the measured data and compared to independent saturation measurements from light transmission through the chamber. Different model parameterizations are evaluated in terms of the recovered saturation and petrophysical parameter values. The saturation field is parameterized (1) in Cartesian coordinates, (2) by means of its discrete cosine transform coefficients, and (3) by fixed saturation values in structural elements whose shape and location is assumed known or represented by an arbitrary Gaussian Bell structure. Results show that the estimated saturation fields are in overall agreement with saturations measured by light transmission, but differ strongly in terms of parameter estimates, parameter uncertainties and computational intensity. Discretization in the frequency domain (as in the discrete cosine transform parameterization) provides more accurate models at a lower computational cost compared to spatially discretized (Cartesian) models. A priori knowledge about the expected geologic structures allows for non-discretized model descriptions with markedly reduced degrees of freedom. Constraining the solutions to the known injected gas volume improved estimates of saturation and parameter values of the petrophysical relationship. (C) 2014 Elsevier B.V. All rights reserved.

Hardness of FRHC-Cu determined by statistical analysis

A statistical indentation method has been employed to study the hardness value of fire-refined high conductivity copper, using nanoindentation technique. The Joslin and Oliver approach was used with the aim to separate the hardness (H) influence of copper matrix, from that of inclusions and grain boundaries. This approach relies on a large array of imprints (around 400 indentations), performed at 150 nm of indentation depth. A statistical study using a cumulative distribution function fit and Gaussian simulated distributions, exhibits that H for each phase can be extracted when the indentation depth is much lower than the size of the secondary phases. It is found that the thermal treatment produces a hardness increase, due to the partly re-dissolution of the inclusions (mainly Pb and Sn) in the matrix.

Source separation techniques applied to linear prediction

The prediction filters are well known models for signal estimation, in communications, control and many others areas. The classical method for deriving linear prediction coding (LPC) filters is often based on the minimization of a mean square error (MSE). Consequently, second order statistics are only required, but the estimation is only optimal if the residue is independent and identically distributed (iid) Gaussian. In this paper, we derive the ML estimate of the prediction filter. Relationships with robust estimation of auto-regressive (AR) processes, with blind deconvolution and with source separation based on mutual information minimization are then detailed. The algorithm, based on the minimization of a high-order statistics criterion, uses on-line estimation of the residue statistics. Experimental results emphasize on the interest of this approach.

Improving algorithm speed in PNL mixture separation and Wiener system inversion

This paper proposes a very simple method for increasing the algorithm speed for separating sources from PNL mixtures or invertingWiener systems. The method is based on a pertinent initialization of the inverse system, whose computational cost is very low. The nonlinear part is roughly approximated by pushing the observations to be Gaussian; this method provides a surprisingly good approximation even when the basic assumption is not fully satisfied. The linear part is initialized so that outputs are decorrelated. Experiments shows the impressive speed improvement.

Nonlinear prediction based on score function

The linear prediction coding of speech is based in the assumption that the generation model is autoregresive. In this paper we propose a structure to cope with the nonlinear effects presents in the generation of the speech signal. This structure will consist of two stages, the first one will be a classical linear prediction filter, and the second one will model the residual signal by means of two nonlinearities between a linear filter. The coefficients of this filter are computed by means of a gradient search on the score function. This is done in order to deal with the fact that the probability distribution of the residual signal still is not gaussian. This fact is taken into account when the coefficients are computed by a ML estimate. The algorithm based on the minimization of a high-order statistics criterion, uses on-line estimation of the residue statistics and is based on blind deconvolution of Wiener systems [1]. Improvements in the experimental results with speech signals emphasize on the interest of this approach.

Gene filtering with optimal threshold selection

Gene filtering is a useful preprocessing technique often applied to microarray datasets. However, it is no common practice because clear guidelines are lacking and it bears the risk of excluding some potentially relevant genes. In this work, we propose to model microarray data as a mixture of two Gaussian distributions that will allow us to obtain an optimal filter threshold in terms of the gene expression level.

Correlation between charge transport and electroluminescence properties of Si-rich oxide/nitride/oxide-based light emitting capacitors.

The electrical and electroluminescence (EL) properties at room and high temperatures of oxide/ nitride/oxide (ONO)-based light emitting capacitors are studied. The ONO multidielectric layer is enriched with silicon by means of ion implantation. The exceeding silicon distribution follows a Gaussian profile with a maximum of 19%, centered close to the lower oxide/nitride interface. The electrical measurements performed at room and high temperatures allowed to unambiguously identify variable range hopping (VRH) as the dominant electrical conduction mechanism at low voltages, whereas at moderate and high voltages, a hybrid conduction formed by means of variable range hopping and space charge-limited current enhanced by Poole-Frenkel effect predominates. The EL spectra at different temperatures are also recorded, and the correlation between charge transport mechanisms and EL properties is discussed.

Candida albicans Inhibits Pseudomonas aeruginosa Virulence through Suppression of Pyochelin and Pyoverdine Biosynthesis.

Bacterial-fungal interactions have important physiologic and medical ramifications, but the mechanisms of these interactions are poorly understood. The gut is host to trillions of microorganisms, and bacterial-fungal interactions are likely to be important. Using a neutropenic mouse model of microbial gastrointestinal colonization and dissemination, we show that the fungus Candida albicans inhibits the virulence of the bacterium Pseudomonas aeruginosa by inhibiting P. aeruginosa pyochelin and pyoverdine gene expression, which plays a critical role in iron acquisition and virulence. Accordingly, deletion of both P. aeruginosa pyochelin and pyoverdine genes attenuates P. aeruginosa virulence. Heat-killed C. albicans has no effect on P. aeruginosa, whereas C. albicans secreted proteins directly suppress P. aeruginosa pyoverdine and pyochelin expression and inhibit P. aeruginosa virulence in mice. Interestingly, suppression or deletion of pyochelin and pyoverdine genes has no effect on P. aeruginosa's ability to colonize the GI tract but does decrease P. aeruginosa's cytotoxic effect on cultured colonocytes. Finally, oral iron supplementation restores P. aeruginosa virulence in P. aeruginosa and C. albicans colonized mice. Together, our findings provide insight into how a bacterial-fungal interaction can modulate bacterial virulence in the intestine. Previously described bacterial-fungal antagonistic interactions have focused on growth inhibition or colonization inhibition/modulation, yet here we describe a novel observation of fungal-inhibition of bacterial effectors critical for virulence but not important for colonization. These findings validate the use of a mammalian model system to explore the complexities of polymicrobial, polykingdom infections in order to identify new therapeutic targets for preventing microbial disease.

A statistical shape model of the human second cervical vertebra.

PURPOSE: Statistical shape and appearance models play an important role in reducing the segmentation processing time of a vertebra and in improving results for 3D model development. Here, we describe the different steps in generating a statistical shape model (SSM) of the second cervical vertebra (C2) and provide the shape model for general use by the scientific community. The main difficulties in its construction are the morphological complexity of the C2 and its variability in the population. METHODS: The input dataset is composed of manually segmented anonymized patient computerized tomography (CT) scans. The alignment of the different datasets is done with the procrustes alignment on surface models, and then, the registration is cast as a model-fitting problem using a Gaussian process. A principal component analysis (PCA)-based model is generated which includes the variability of the C2. RESULTS: The SSM was generated using 92 CT scans. The resulting SSM was evaluated for specificity, compactness and generalization ability. The SSM of the C2 is freely available to the scientific community in Slicer (an open source software for image analysis and scientific visualization) with a module created to visualize the SSM using Statismo, a framework for statistical shape modeling. CONCLUSION: The SSM of the vertebra allows the shape variability of the C2 to be represented. Moreover, the SSM will enable semi-automatic segmentation and 3D model generation of the vertebra, which would greatly benefit surgery planning.

Facing Structural Disadvantage: The Role of Ingroup Connectedness

This thesis focuses on the social-psychological factors that help coping with structural disadvantage, and specifically on the role of cohesive ingroups and the sense of connectedness and efficacy they entail in this process. It aims to complement existing group-based models of coping that are grounded in a categorization perspective to groups and consequently focus exclusively on the large-scale categories made salient in intergroup contexts of comparisons. The dissertation accomplishes this aim through a reconsideration of between-persons relational interdependence as a sufficient and independent antecedent of a sense of groupness, and the benefits that a sense of group connectedness in one's direct environment, regardless of the categorical or relational basis of groupness, might have in the everyday struggles of disadvantaged group members. The three empirical papers aim to validate this approach, outlined in the first theoretical introduction, by testing derived hypotheses. They are based on data collected with youth populations (15-30) from three institutions in French-speaking Switzerland within the context of a larger project on youth transitions. Methods of data collection are paper-pencil questionnaires and in-depth interviews with a selected sub-sample of participants. The key argument of the first paper is that members of socially disadvantaged categories face higher barriers to their life project and that a general sense of connectedness, either based on categorical identities or other proximal groups and relations, mitigates the feeling of powerlessness associated with this experience. The second paper develops and tests a model that defines individual needs satisfaction as antecedent of self-group bonds and the efficacy beliefs derived from these intragroup bonds as the mechanism underlining the role of ingroups in coping. The third paper highlights the complexities that might be associated with the construction of a sense of groupness directly from intergroup comparisons and categorization-based disadvantage, and points out a more subtle understanding of the processes underling the emergence of groupness out of the situation of structural disadvantage. Overall, the findings confirm the central role of ingroups in coping with structural disadvantage and the importance of an understanding of groupness and its role that goes beyond the dominant focus on intergroup contexts and categorization processes.

Antireflection coatings from analogy between electron scattering and spin precession

We use the analogy between scattering of a wave from a potential, and the precession of a spin-half particle in a magnetic field, to gain insight into the design of an antireflection coating for electrons in a semiconductor superlattice. It is shown that the classic recipes derived for optics are generally not applicable due to the different dispersion law for electrons. Using the stability conditions we show that a Poisson distribution of impedance steps is a better approximation than is a Gaussian distribution. Examples are given of filters with average transmissivity exceeding 95% over an allowed band.

Networks of noisy oscillators with correlated degree and frequency dispersion

We investigate how correlations between the diversity of the connectivity of networks and the dynamics at their nodes affect the macroscopic behavior. In particular, we study the synchronization transition of coupled stochastic phase oscillators that represent the node dynamics. Crucially in our work, the variability in the number of connections of the nodes is correlated with the width of the frequency distribution of the oscillators. By numerical simulations on Erdös-Rényi networks, where the frequencies of the oscillators are Gaussian distributed, we make the counterintuitive observation that an increase in the strength of the correlation is accompanied by an increase in the critical coupling strength for the onset of synchronization. We further observe that the critical coupling can solely depend on the average number of connections or even completely lose its dependence on the network connectivity. Only beyond this state, a weighted mean-field approximation breaks down. If noise is present, the correlations have to be stronger to yield similar observations.