Mapping an uncertainty zone between interpolated types of a categorical variable

Conselho Nacional de Desenvolvimento Científico e Tecnológico (CNPq)

Activation function study for wavelet network

The main purpose of this paper is to investigate theoretically and experimentally the use of family of Polynomial Powers of the Sigmoid (PPS) Function Networks applied in speech signal representation and function approximation. This paper carries out practical investigations in terms of approximation fitness (LSE), time consuming (CPU Time), computational complexity (FLOP) and representation power (Number of Activation Function) for different PPS activation functions. We expected that different activation functions can provide performance variations and further investigations will guide us towards a class of mappings associating the best activation function to solve a class of problems under certain criteria.

Mapping Wigner distribution functions into semiclassical distribution functions

A mapping that relates the Wigner phase-space distribution function of a given stationary quantum mechani-cal wave function, a solution of the Schrödinger equation, to a specific solution of the Liouville equation, both subject to the same potential, is studied. By making this mapping, bound states are described by semiclassical distribution functions still depending on Planck's constant, whereas for elastic scattering of a particle by a potential they do not depend on it, the classical limit being reached in this case. Following this method, the mapped distributions of a particle bound in the Pöschl-Teller potential and also in a modified oscillator potential are obtained.

Mapping eIF5A binding sites for Dys1 and Lia1: In vivo evidence for regulation of eIF5A hypusination

The evolutionarily conserved factor eIF5A is the only protein known to undergo hypusination, a unique posttranslational modification triggered by deoxyhypusine synthase (Dys1). Although eIF5A is essential for cell viability, the function of this putative translation initiation factor is still obscure. To identify eIF5A-binding proteins that could clarify its function, we screened a two-hybrid library and identified two eIF-5A partners in S. cerevisiae: Dys1 and the protein encoded by the gene YJR070C, named Lia1 (Ligand of eIF5A). The interactions were confirmed by GST pulldown. Mapping binding sites for these proteins revealed that both eIF5A domains can bind to Dys1, whereas the C-terminal domain is sufficient to bind Lia1. We demonstrate for the first time in vivo that the N-terminal α-helix of Dys1 can modulate enzyme activity by inhibiting eIF5A interaction. We suggest that this inhibition be abrogated in the cell when hypusinated and functional eIF5A is required. © 2003 Published by Elsevier B.V. on behalf of the Federation of European Biochemical Societies.

A new approach to soil classification mapping based on the spatial distribution of soil properties

Coordenação de Aperfeiçoamento de Pessoal de Nível Superior (CAPES)

Mapping an uncertainty zone between interpolated types of a categorical variable

Categorical data cannot be interpolated directly because they are outcomes of discrete random variables. Thus, types of categorical variables are transformed into indicator functions that can be handled by interpolation methods. Interpolated indicator values are then backtransformed to the original types of categorical variables. However, aspects such as variability and uncertainty of interpolated values of categorical data have never been considered. In this paper we show that the interpolation variance can be used to map an uncertainty zone around boundaries between types of categorical variables. Moreover, it is shown that the interpolation variance is a component of the total variance of the categorical variables, as measured by the coefficient of unalikeability. (C) 2011 Elsevier Ltd. All rights reserved.

Intelligence systems methodology: a systemic approach to the organizational intelligence function

Organizational intelligence can be seen as a function of the viable structure of an organization. With the integration of the Viable System Model and Soft Systems Methodology (systemic approaches of organizational management) focused on the role of the intelligence function, it is possible to elaborate a model of action with a structured methodology to prospect, select, treat and distribute information to the entire organization that improves the efficacy and efficiency of all processes. This combination of methodologies is called Intelligence Systems Methodology (ISM) whose assumptions and dynamics are delimited in this paper. The ISM is composed of two simultaneous activities: the Active Environmental Mapping and the Stimulated Action Cycle. The elaboration of the formal ISM description opens opportunities for applications of the methodology on real situations, offering a new path for this specific issue of systems thinking: the intelligence systems. Knowledge Management Research & Practice (2012) 10, 141-152. doi:10.1057/kmrp.2011.44

The C-4-Dicarboxylate carriers DcuB and DctA of Escherichia coli: function as cosensors and topology

Das fakultativ anaerobe Enterobakterium Escherichia coli nutzt C4-Dicarboxylate sowohl unter aeroben als auch anaeroben Bedingungen als Kohlenstoff- und Energiequelle. Die Aufnahme der C4-Dicarboxylaten und die Energiekonservierung mittels Fumaratatmung wird durch das Zweikomponentensystem DcuSR reguliert. Die Sensorhistidinkinase DcuS und der nachgeschaltete Responseregulator DcuR aktivieren bei Verfügbarkeit von C4-Dicarboxylaten die Expression der Gene für den Succinat Transporter DctA, den anaeroben Fumarat/Succinat Antiporter DcuB, die Fumarase B sowie die Fumaratreduktase FrdABCD. Die Transportproteine DctA und DcuB wiederum regulieren die Expression der DcuSR-abhängigen Gene negativ. Fehlen von DctA oder DcuB resultiert bereits ohne Effektor in einer maximalen Expression von dctA bzw. dcuB. Durch gerichtete und ungerichtete Mutagenese wurde gezeigt, dass die Transportfunktion des Carriers DcuB unabhängig von seiner regulatorischen Funktion ist. DcuB kann daher als Cosensor des DcuSR Systems angesehen werden.rnUnter Verwendung von Reportergenfusionen von C-terminal verkürzten Konstrukten von DcuB mit der Alkalischen Phosphatase und der β-Galactosidase wurde die Topologie des Multitransmembranproteins DcuB bestimmt. Zusätzlich wurde die Zugänglichkeit bestimmter Aminosäurereste durch chemische Modifikation mit membran-durchlässigen und membran-undurchlässigen Thiolreagenzien untersucht. Die erhaltenen Ergebnisse deuten auf die Existenz eines tief in die Membran reichenden, hydrophilen Kanal hin, welcher zum Periplasma hin geöffnet ist. Mit Hilfe der Topologie-Studien, des Hydropathie-Blots und der Sekundärstruktur-Vorhersage wurde ein Modell des Carriers erstellt. DcuB besitzt kurze, periplasmatisch liegende Proteinenden, die durch 12 Transmembranhelices und zwei große hydrophile Schleifen jeweils zwischen TM VII/VIII und TM XI/XII verbunden sind. Die regulatorisch relevanten Reste K353, T396 und D398 befinden sich innerhalb von TM XI sowie auf der angrenzenden cytoplasmatischen Schleife XI-XII. Unter Berücksichtigung der strukturellen und funktionellen Aspekte wurde ein Regulationsmodell erstellt, welches die gemeinsam durch DcuB und DcuS kontrollierte C4-Dicarboxylat-abhängige Genexpression darstellt. rnDer Effekt von DctA und DcuSR auf die Expression einer dctA´-´lacZ Reportergenfusion und auf die aerobe C4-Dicarboxylat-Aufnahme wurde untersucht. In-vivo FRET-Messungen weisen auf eine direkte Wechselwirkung zwischen dem Carrier DctA und dem Sensor DcuS hin. Dieses Ergebnis stützt die Theorie der Regulation von DcuS durch C4-Dicarboxylate und durch die Cosensoren DctA bzw. DcuB mittels direkter Protein-Protein Interaktion.rn

Learning with Kernels on Graphs: DAG-based kernels, data streams and RNA function prediction.

In many application domains data can be naturally represented as graphs. When the application of analytical solutions for a given problem is unfeasible, machine learning techniques could be a viable way to solve the problem. Classical machine learning techniques are defined for data represented in a vectorial form. Recently some of them have been extended to deal directly with structured data. Among those techniques, kernel methods have shown promising results both from the computational complexity and the predictive performance point of view. Kernel methods allow to avoid an explicit mapping in a vectorial form relying on kernel functions, which informally are functions calculating a similarity measure between two entities. However, the definition of good kernels for graphs is a challenging problem because of the difficulty to find a good tradeoff between computational complexity and expressiveness. Another problem we face is learning on data streams, where a potentially unbounded sequence of data is generated by some sources. There are three main contributions in this thesis. The first contribution is the definition of a new family of kernels for graphs based on Directed Acyclic Graphs (DAGs). We analyzed two kernels from this family, achieving state-of-the-art results from both the computational and the classification point of view on real-world datasets. The second contribution consists in making the application of learning algorithms for streams of graphs feasible. Moreover,we defined a principled way for the memory management. The third contribution is the application of machine learning techniques for structured data to non-coding RNA function prediction. In this setting, the secondary structure is thought to carry relevant information. However, existing methods considering the secondary structure have prohibitively high computational complexity. We propose to apply kernel methods on this domain, obtaining state-of-the-art results.

Thin-Film Sparse Boundary Array Design for Passive Acoustic Mapping During Ultrasound Therapy

A new 2-D hydrophone array for ultrasound therapy monitoring is presented, along with a novel algorithm for passive acoustic mapping using a sparse weighted aperture. The array is constructed using existing polyvinylidene fluoride (PVDF) ultrasound sensor technology, and is utilized for its broadband characteristics and its high receive sensitivity. For most 2-D arrays, high-resolution imagery is desired, which requires a large aperture at the cost of a large number of elements. The proposed array's geometry is sparse, with elements only on the boundary of the rectangular aperture. The missing information from the interior is filled in using linear imaging techniques. After receiving acoustic emissions during ultrasound therapy, this algorithm applies an apodization to the sparse aperture to limit side lobes and then reconstructs acoustic activity with high spatiotemporal resolution. Experiments show verification of the theoretical point spread function, and cavitation maps in agar phantoms correspond closely to predicted areas, showing the validity of the array and methodology.

An integrative transcranial magnetic stimulation mapping technique using non-linear curve fitting

The aim of this study is to develop a new simple method for analyzing one-dimensional transcranial magnetic stimulation (TMS) mapping studies in humans. Motor evoked potentials (MEP) were recorded from the abductor pollicis brevis (APB) muscle during stimulation at nine different positions on the scalp along a line passing through the APB hot spot and the vertex. Non-linear curve fitting according to the Levenberg-Marquardt algorithm was performed on the averaged amplitude values obtained at all points to find the best-fitting symmetrical and asymmetrical peak functions. Several peak functions could be fitted to the experimental data. Across all subjects, a symmetric, bell-shaped curve, the complementary error function (erfc) gave the best results. This function is characterized by three parameters giving its amplitude, position, and width. None of the mathematical functions tested with less or more than three parameters fitted better. The amplitude and position parameters of the erfc were highly correlated with the amplitude at the hot spot and with the location of the center of gravity of the TMS curve. In conclusion, non-linear curve fitting is an accurate method for the mathematical characterization of one-dimensional TMS curves. This is the first method that provides information on amplitude, position and width simultaneously.

Sequential Quantitative Trait Locus Mapping in Experimental Crosses

The etiology of complex diseases is heterogeneous. The presence of risk alleles in one or more genetic loci affects the function of a variety of intermediate biological pathways, resulting in the overt expression of disease. Hence, there is an increasing focus on identifying the genetic basis of disease by sytematically studying phenotypic traits pertaining to the underlying biological functions. In this paper we focus on identifying genetic loci linked to quantitative phenotypic traits in experimental crosses. Such genetic mapping methods often use a one stage design by genotyping all the markers of interest on the available subjects. A genome scan based on single locus or multi-locus models is used to identify the putative loci. Since the number of quantitative trait loci (QTLs) is very likely to be small relative to the number of markers genotyped, a one-stage selective genotyping approach is commonly used to reduce the genotyping burden, whereby markers are genotyped solely on individuals with extreme trait values. This approach is powerful in the presence of a single quantitative trait locus (QTL) but may result in substantial loss of information in the presence of multiple QTLs. Here we investigate the efficiency of sequential two stage designs to identify QTLs in experimental populations. Our investigations for backcross and F2 crosses suggest that genotyping all the markers on 60% of the subjects in Stage 1 and genotyping the chromosomes significant at 20% level using additional subjects in Stage 2 and testing using all the subjects provides an efficient approach to identify the QTLs and utilizes only 70% of the genotyping burden relative to a one stage design, regardless of the heritability and genotyping density. Complex traits are a consequence of multiple QTLs conferring main effects as well as epistatic interactions. We propose a two-stage analytic approach where a single-locus genome scan is conducted in Stage 1 to identify promising chromosomes, and interactions are examined using the loci on these chromosomes in Stage 2. We examine settings under which the two-stage analytic approach provides sufficient power to detect the putative QTLs.

T2 mapping in the knee after microfracture at 3.0 T: correlation of global T2 values and clinical outcome - preliminary results

OBJECTIVE: The aim of our study was to correlate global T2 values of microfracture repair tissue (RT) with clinical outcome in the knee joint. METHODS: We assessed 24 patients treated with microfracture in the knee joint. Magnetic resonance (MR) examinations were performed on a 3T MR unit, T2 relaxation times were obtained with a multi-echo spin-echo technique. T2 maps were obtained using a pixel wise, mono-exponential non-negative least squares fit analysis. Slices covering the cartilage RT were selected and region of interest analysis was done. An individual T2 index was calculated with global mean T2 of the RT and global mean T2 of normal, hyaline cartilage. The Lysholm score and the International Knee Documentation Committee (IKDC) knee evaluation forms were used for the assessment of clinical outcome. Bivariate correlation analysis and a paired, two tailed t test were used for statistics. RESULTS: Global T2 values of the RT [mean 49.8ms, standards deviation (SD) 7.5] differed significantly (P<0.001) from global T2 values of normal, hyaline cartilage (mean 58.5ms, SD 7.0). The T2 index ranged from 61.3 to 101.5. We found the T2 index to correlate with outcome of the Lysholm score (r(s)=0.641, P<0.001) and the IKDC subjective knee evaluation form (r(s)=0.549, P=0.005), whereas there was no correlation with the IKDC knee form (r(s)=-0.284, P=0.179). CONCLUSION: These findings indicate that T2 mapping is sensitive to assess RT function and provides additional information to morphologic MRI in the monitoring of microfracture.

Laser Doppler imaging for intraoperative human brain mapping

The identification and accurate location of centers of brain activity are vital both in neuro-surgery and brain research. This study aimed to provide a non-invasive, non-contact, accurate, rapid and user-friendly means of producing functional images intraoperatively. To this end a full field Laser Doppler imager was developed and integrated within the surgical microscope and perfusion images of the cortical surface were acquired during awake surgery whilst the patient performed a predetermined task. The regions of brain activity showed a clear signal (10-20% with respect to the baseline) related to the stimulation protocol which lead to intraoperative functional brain maps of strong statistical significance and which correlate well with the preoperative fMRI and intraoperative cortical electro-stimulation. These initial results achieved with a prototype device and wavelet based regressor analysis (the hemodynamic response function being derived from MRI applications) demonstrate the feasibility of LDI as an appropriate technique for intraoperative functional brain imaging.

Interaction between effects of genes coding for dopamine and glutamate transmission on striatal and parahippocampal function

The genes for the dopamine transporter (DAT) and the D-Amino acid oxidase activator (DAOA or G72) have been independently implicated in the risk for schizophrenia and in bipolar disorder and/or their related intermediate phenotypes. DAT and G72 respectively modulate central dopamine and glutamate transmission, the two systems most robustly implicated in these disorders. Contemporary studies have demonstrated that elevated dopamine function is associated with glutamatergic dysfunction in psychotic disorders. Using functional magnetic resonance imaging we examined whether there was an interaction between the effects of genes that influence dopamine and glutamate transmission (DAT and G72) on regional brain activation during verbal fluency, which is known to be abnormal in psychosis, in 80 healthy volunteers. Significant interactions between the effects of G72 and DAT polymorphisms on activation were evident in the striatum, parahippocampal gyrus, and supramarginal/angular gyri bilaterally, the right insula, in the right pre-/postcentral and the left posterior cingulate/retrosplenial gyri (P < 0.05, FDR-corrected across the whole brain). This provides evidence that interactions between the dopamine and the glutamate system, thought to be altered in psychosis, have an impact in executive processing which can be modulated by common genetic variation.