Network-based stochastic semisupervised learning

Semisupervised learning is a machine learning approach that is able to employ both labeled and unlabeled samples in the training process. In this paper, we propose a semisupervised data classification model based on a combined random-preferential walk of particles in a network (graph) constructed from the input dataset. The particles of the same class cooperate among themselves, while the particles of different classes compete with each other to propagate class labels to the whole network. A rigorous model definition is provided via a nonlinear stochastic dynamical system and a mathematical analysis of its behavior is carried out. A numerical validation presented in this paper confirms the theoretical predictions. An interesting feature brought by the competitive-cooperative mechanism is that the proposed model can achieve good classification rates while exhibiting low computational complexity order in comparison to other network-based semisupervised algorithms. Computer simulations conducted on synthetic and real-world datasets reveal the effectiveness of the model.

Experimental Investigation of the Hydrodynamic Coefficients of a Remotely Operated Vehicle Using a Planar Motion Mechanism

The determination of hydrodynamic coefficients of full scale underwater vehicles using system identification (SI) is an extremely powerful technique. The procedure is based on experimental runs and on the analysis of on-board sensors and thrusters signals. The technique is cost effective and it has high repeatability; however, for open-frame underwater vehicles, it lacks accuracy due to the sensors' noise and the poor modeling of thruster-hull and thruster-thruster interaction effects. In this work, forced oscillation tests were undertaken with a full scale open-frame underwater vehicle. These conducted tests are unique in the sense that there are not many examples in the literature taking advantage of a PMM installation for testing a prototype and; consequently, allowing the comparison between the experimental results and the ones estimated by parameter identification. The Morison's equation inertia and drag coefficients were estimated with two parameter identification methods, that is, the weighted and the ordinary least-squares procedures. It was verified that the in-line force estimated from Morison's equation agrees well with the measured one except in the region around the motion inversion points. On the other hand, the error analysis showed that the ordinary least-squares provided better accuracy and, therefore, was used to evaluate the ratio between inertia and drag forces for a range of Keulegan-Carpenter and Reynolds numbers. It was concluded that, although both experimental and estimation techniques proved to be powerful tools for evaluation of an open-frame underwater vehicle's hydrodynamic coefficients, the research provided a rich amount of reference data for comparison with reduced models as well as for dynamic motion simulation of ROVs. [DOI: 10.1115/1.4004952]

Stochastic simulation of time-series models combined with geostatistics to predict water-table scenarios in a Guarani Aquifer System outcrop area, Brazil

Stochastic methods based on time-series modeling combined with geostatistics can be useful tools to describe the variability of water-table levels in time and space and to account for uncertainty. Monitoring water-level networks can give information about the dynamic of the aquifer domain in both dimensions. Time-series modeling is an elegant way to treat monitoring data without the complexity of physical mechanistic models. Time-series model predictions can be interpolated spatially, with the spatial differences in water-table dynamics determined by the spatial variation in the system properties and the temporal variation driven by the dynamics of the inputs into the system. An integration of stochastic methods is presented, based on time-series modeling and geostatistics as a framework to predict water levels for decision making in groundwater management and land-use planning. The methodology is applied in a case study in a Guarani Aquifer System (GAS) outcrop area located in the southeastern part of Brazil. Communication of results in a clear and understandable form, via simulated scenarios, is discussed as an alternative, when translating scientific knowledge into applications of stochastic hydrogeology in large aquifers with limited monitoring network coverage like the GAS.

Algebraic-graph method for identification of islanding in power system grids

In this paper, a new algebraic-graph method for identification of islanding in power system grids is proposed. The proposed method identifies all the possible cases of islanding, due to the loss of a equipment, by means of a factorization of the bus-branch incidence matrix. The main features of this new method include: (i) simple implementation, (ii) high speed, (iii) real-time adaptability, (iv) identification of all islanding cases and (v) identification of the buses that compose each island in case of island formation. The method was successfully tested on large-scale systems such as the reduced south Brazilian system (45 buses/72 branches) and the south-southeast Brazilian system (810 buses/1340 branches). (C) 2011 Elsevier Ltd. All rights reserved.

Identification of 2 Novel ANTXR2 Mutations in Patients With Hyaline Fibromatosis Syndrome and Proposal of a Modified Grading System

Juvenile hyaline fibromatosis (JHF) and infantile systemic hyalinosis (ISH) are rare, autosomal recessive disorders of the connective tissue caused by mutations in the gene encoding the anthrax toxin receptor 2 protein (ANTXR2) located on chromosome 4q21. Characteristically, these conditions present with overlapping clinical features, such as nodules and/or pearly papules, gingival hyperplasia, flexion contractures of the joints, and osteolytic bone defects. The present report describes a pair of sibs and three other JHF/ISH patients whose diagnoses were based on typical clinical manifestations and confirmed by histopathologic analyses and/or molecular analysis. A comparison of ISH and JHF, additional thoughts about new terminology (hyaline fibromatosis syndrome) and a modified grading system are also included. (C) 2012 Wiley Periodicals, Inc.

Identification of bacteria in drinking and purified water during the monitoring of a typical water purification system

Abstract Background A typical purification system that provides purified water which meets ionic and organic chemical standards, must be protected from microbial proliferation to minimize cross-contamination for use in cleaning and preparations in pharmaceutical industries and in health environments. Methodology Samples of water were taken directly from the public distribution water tank at twelve different stages of a typical purification system were analyzed for the identification of isolated bacteria. Two miniature kits were used: (i) identification system (api 20 NE, Bio-Mérieux) for non-enteric and non-fermenting gram-negative rods; and (ii) identification system (BBL crystal, Becton and Dickson) for enteric and non-fermenting gram-negative rods. The efficiency of the chemical sanitizers used in the stages of the system, over the isolated and identified bacteria in the sampling water, was evaluated by the minimum inhibitory concentration (MIC) method. Results The 78 isolated colonies were identified as the following bacteria genera: Pseudomonas, Flavobacterium and Acinetobacter. According to the miniature kits used in the identification, there was a prevalence of isolation of P. aeruginosa 32.05%, P. picketti (Ralstonia picketti) 23.08%, P. vesiculares 12.82%,P. diminuta 11.54%, F. aureum 6.42%, P. fluorescens 5.13%, A. lwoffi 2.56%, P. putida 2.56%, P. alcaligenes 1.28%, P. paucimobilis 1.28%, and F. multivorum 1.28%. Conclusions We found that research was required for the identification of gram-negative non-fermenting bacteria, which were isolated from drinking water and water purification systems, since Pseudomonas genera represents opportunistic pathogens which disperse and adhere easily to surfaces, forming a biofilm which interferes with the cleaning and disinfection procedures in hospital and industrial environments.

Short Report: Identification of Oropouche Orthobunyavirus in the Cerebrospinal Fluid of Three Patients in the Amazonas, Brazil

Oropouche fever is the second most frequent arboviral infection in Brazil, surpassed only by dengue. Oropouche virus (OROV) causes large and explosive outbreaks of acute febrile illness in cities and villages in the Amazon and Central-Plateau regions. Cerebrospinal fluid (CSF) samples from 110 meningoencephalitis patients were analyzed. The RNA extracted from fluid was submitted to reverse transcription-polymerase chain reaction and sequencing to identify OROV. Three CSF samples showed the presence of OROV causing infection in the central nervous system (CNS). These patients are adults. Two of the patients had other diseases affecting CNS and immune systems: neurocysticercosis and acquired immunodeficiency syndrome, respectively. Nucleotide sequence analysis showed that the OROV from the CSF of these patients belonged to genotype I. We show here that severe Oropouche disease is occurring during outbreaks of this virus in Brazil

Capillary bioreactors based on human purine nucleoside phosphorylase: A new approach for ligands identification and characterization

The enzyme purine nucleoside phosphorylase (PNP) is a target for the discovery of new lead compounds employed on the treatment severe T-cell mediated disorders. Within this context, the development of new, direct, and reliable methods for ligands screening is an important task. This paper describes the preparation of fused silica capillaries human PNP (HsPNP) immobilized enzyme reactor (IMER). The activity of the obtained IMER is monitored on line in a multidimensional liquid chromatography system, by the quantification of the product formed throughout the enzymatic reaction. The Km value for the immobilized enzyme was about twofold higher than that measured for the enzyme in solution (255 +/- 29.2 mu M and 133 +/- 114.9 mu M, respectively). A new fourth-generation immucillin derivative (DI4G: IC50 = 40.6 +/- 0.36 nM), previously identified and characterized in HsPNP free enzyme assays, was used to validate the IMER as a screening method for HsPNP ligands. The validated method was also used for mechanistic studies with this inhibitor. This new approach is a valuable tool to PNP ligand screening, since it directly measures the hypoxanthine released by inosine phosphorolysis, thus furnishing more reliable results than those one used in a coupled enzymatic spectrophotometric assay. (C) 2011 Elsevier B.V. All rights reserved.

Evaluation of physiologic complexity in time series using generalized sample entropy and surrogate data analysis

Complexity in time series is an intriguing feature of living dynamical systems, with potential use for identification of system state. Although various methods have been proposed for measuring physiologic complexity, uncorrelated time series are often assigned high values of complexity, errouneously classifying them as a complex physiological signals. Here, we propose and discuss a method for complex system analysis based on generalized statistical formalism and surrogate time series. Sample entropy (SampEn) was rewritten inspired in Tsallis generalized entropy, as function of q parameter (qSampEn). qSDiff curves were calculated, which consist of differences between original and surrogate series qSampEn. We evaluated qSDiff for 125 real heart rate variability (HRV) dynamics, divided into groups of 70 healthy, 44 congestive heart failure (CHF), and 11 atrial fibrillation (AF) subjects, and for simulated series of stochastic and chaotic process. The evaluations showed that, for nonperiodic signals, qSDiff curves have a maximum point (qSDiff(max)) for q not equal 1. Values of q where the maximum point occurs and where qSDiff is zero were also evaluated. Only qSDiff(max) values were capable of distinguish HRV groups (p-values 5.10 x 10(-3); 1.11 x 10(-7), and 5.50 x 10(-7) for healthy vs. CHF, healthy vs. AF, and CHF vs. AF, respectively), consistently with the concept of physiologic complexity, and suggests a potential use for chaotic system analysis. (C) 2012 American Institute of Physics. [http://dx.doi.org/10.1063/1.4758815]

The rapid atmospheric monitoring system of the Pierre Auger Observatory

The Pierre Auger Observatory is a facility built to detect air showers produced by cosmic rays above 10(17) eV. During clear nights with a low illuminated moon fraction, the UV fluorescence light produced by air showers is recorded by optical telescopes at the Observatory. To correct the observations for variations in atmospheric conditions, atmospheric monitoring is performed at regular intervals ranging from several minutes (for cloud identification) to several hours (for aerosol conditions) to several days (for vertical profiles of temperature, pressure, and humidity). In 2009, the monitoring program was upgraded to allow for additional targeted measurements of atmospheric conditions shortly after the detection of air showers of special interest, e. g., showers produced by very high-energy cosmic rays or showers with atypical longitudinal profiles. The former events are of particular importance for the determination of the energy scale of the Observatory, and the latter are characteristic of unusual air shower physics or exotic primary particle types. The purpose of targeted (or "rapid") monitoring is to improve the resolution of the atmospheric measurements for such events. In this paper, we report on the implementation of the rapid monitoring program and its current status. The rapid monitoring data have been analyzed and applied to the reconstruction of air showers of high interest, and indicate that the air fluorescence measurements affected by clouds and aerosols are effectively corrected using measurements from the regular atmospheric monitoring program. We find that the rapid monitoring program has potential for supporting dedicated physics analyses beyond the standard event reconstruction.

A spatial stochastic model for rumor transmission

We consider an interacting particle system representing the spread of a rumor by agents on the d-dimensional integer lattice. Each agent may be in any of the three states belonging to the set {0,1,2}. Here 0 stands for ignorants, 1 for spreaders and 2 for stiflers. A spreader tells the rumor to any of its (nearest) ignorant neighbors at rate lambda. At rate alpha a spreader becomes a stifler due to the action of other (nearest neighbor) spreaders. Finally, spreaders and stiflers forget the rumor at rate one. We study sufficient conditions under which the rumor either becomes extinct or survives with positive probability.

Modeling and Identification of an Open-frame Underwater Vehicle: The Yaw Motion Dynamics

A semi-autonomous unmanned underwater vehicle (UUV), named LAURS, is being developed at the Laboratory of Sensors and Actuators at the University of Sao Paulo. The vehicle has been designed to provide inspection and intervention capabilities in specific missions of deep water oil fields. In this work, a method of modeling and identification of yaw motion dynamic system model of an open-frame underwater vehicle is presented. Using an on-board low cost magnetic compass sensor the method is based on the utilization of an uncoupled 1-DOF (degree of freedom) dynamic system equation and the application of the integral method which is the classical least squares algorithm applied to the integral form of the dynamic system equations. Experimental trials with the actual vehicle have been performed in a test tank and diving pool. During these experiments, thrusters responsible for yaw motion are driven by sinusoidal voltage signal profiles. An assessment of the feasibility of the method reveals that estimated dynamic system models are more reliable when considering slow and small sinusoidal voltage signal profiles, i.e. with larger periods and with relatively small amplitude and offset.

Ubiquitin proteasome system and the atypical kinase PfPK7 are involved in melatonin signaling in Plasmodium falciparum

We previously reported that melatonin modulates the Plasmodium falciparum erythrocytic cycle by increasing schizont stage population as well as diminishing ring stage population. In addition, the importance of calcium and cAMP in melatonin signaling pathway in P. falciparum was also demonstrated. Nevertheless, the molecular effectors of the indoleamine signaling pathway remain elusive. We now demonstrate by real-time PCR that melatonin treatment up-regulates genes related to ubiquitin/proteasome system (UPS) components and that luzindole, a melatonin receptor antagonist, inhibits UPS transcription modulation. We also show that protein kinase PfPK7, a P. falciparum orphan kinase, plays a crucial role in the melatonin transduction pathway, since following melatonin treatment of P. falciparum parasites where pfpk7 gene is disrupted (pfpk7- parasites) (i) the ratio of asexual stages remain unchanged, (ii) the increase in cytoplasmatic calcium in response to melatonin was strongly diminished and (iii) up-regulation of UPS genes did not occur. The wild-type melatonin-induced alterations in cell cycle features, calcium rise and UPS gene transcription were restored by re-introduction of a functional copy of the pfpk7 gene in the pfpk7- parasites.

Identification of novel components of NAD-utilizing metabolic pathways and prediction of their biochemical functions

Nicotinamide adenine dinucleotide (NAD) is a ubiquitous cofactor participating in numerous redox reactions. It is also a substrate for regulatory modifications of proteins and nucleic acids via the addition of ADP-ribose moieties or removal of acyl groups by transfer to ADP-ribose. In this study, we use in-depth sequence, structure and genomic context analysis to uncover new enzymes and substrate-binding proteins in NAD-utilizing metabolic and macromolecular modification systems. We predict that Escherichia coli YbiA and related families of domains from diverse bacteria, eukaryotes, large DNA viruses and single strand RNA viruses are previously unrecognized components of NAD-utilizing pathways that probably operate on ADP-ribose derivatives. Using contextual analysis we show that some of these proteins potentially act in RNA repair, where NAD is used to remove 2'-3' cyclic phosphodiester linkages. Likewise, we predict that another family of YbiA-related enzymes is likely to comprise a novel NAD-dependent ADP-ribosylation system for proteins, in conjunction with a previously unrecognized ADP-ribosyltransferase. A similar ADP-ribosyltransferase is also coupled with MACRO or ADP-ribosylglycohydrolase domain proteins in other related systems, suggesting that all these novel systems are likely to comprise pairs of ADP-ribosylation and ribosylglycohydrolase enzymes analogous to the DraG-DraT system, and a novel group of bacterial polymorphic toxins. We present evidence that some of these coupled ADP-ribosyltransferases/ribosylglycohydrolases are likely to regulate certain restriction modification enzymes in bacteria. The ADP-ribosyltransferases found in these, the bacterial polymorphic toxin and host-directed toxin systems of bacteria such as Waddlia also throw light on the evolution of this fold and the origin of eukaryotic polyADP-ribosyltransferases and NEURL4-like ARTs, which might be involved in centrosomal assembly. We also infer a novel biosynthetic pathway that might be involved in the synthesis of a nicotinate-derived compound in conjunction with an asparagine synthetase and AMPylating peptide ligase. We use the data derived from this analysis to understand the origin and early evolutionary trajectories of key NAD-utilizing enzymes and present targets for future biochemical investigations.

Modeling and identification of freeplay nonlinearity

A nonlinear analysis is performed for the purpose of identification of the pitch freeplay nonlinearity and its effect on the type of bifurcation of a two degree-of-freedom aeroelastic system. The databases for the identification are generated from experimental investigations of a pitch-plunge rigid airfoil supported by a nonlinear torsional spring. Experimental data and linear analysis are performed to validate the parameters of the linearized equations. Based on the periodic responses of the experimental data which included the flutter frequency and its third harmonics, the freeplay nonlinearity is approximated by a polynomial expansion up to the third order. This representation allows us to use the normal form of the Hopf bifurcation to characterize the type of instability. Based on numerical integrations, the coefficients of the polynomial expansion representing the freeplay nonlinearity are identified. Published by Elsevier Ltd.