Microbial phyllosphere populations are more complex than previously realized

Phyllosphere microbial communities were evaluated on leaves of field-grown plant species by culture-dependent and -independent methods. Denaturing gradient gel electrophoresis (DGGE) with 16S rDNA primers generally indicated that microbial community structures were similar on different individuals of the same plant species, but unique on different plant species. Phyllosphere bacteria were identified from Citrus sinesis (cv. Valencia) by using DGGE analysis followed by cloning and sequencing of the dominant rDNA bands. Of the 17 unique sequences obtained, database queries showed only four strains that had been described previously as phyllosphere bacteria. Five of the 17 sequences had 16S similarities lower than 90% to database entries, suggesting that they represent previously undescribed species. In addition, three fungal species were also identified. Very different 16S rDNA DGGE banding profiles were obtained when replicate cv. Valencia leaf samples were cultured in BIOLOG EcoPlates for 4.5 days. All of these rDNA sequences had 97–100% similarity to those of known phyllosphere bacteria, but only two of them matched those identified by the culture independent DGGE analysis. Like other studied ecosystems, microbial phyllosphere communities therefore are more complex than previously thought, based on conventional culture-based methods.

New trends in natural language processing: statistical natural language processing.

The field of natural language processing (NLP) has seen a dramatic shift in both research direction and methodology in the past several years. In the past, most work in computational linguistics tended to focus on purely symbolic methods. Recently, more and more work is shifting toward hybrid methods that combine new empirical corpus-based methods, including the use of probabilistic and information-theoretic techniques, with traditional symbolic methods. This work is made possible by the recent availability of linguistic databases that add rich linguistic annotation to corpora of natural language text. Already, these methods have led to a dramatic improvement in the performance of a variety of NLP systems with similar improvement likely in the coming years. This paper focuses on these trends, surveying in particular three areas of recent progress: part-of-speech tagging, stochastic parsing, and lexical semantics.

Variabilidade intratípica de HPV 16 em relação à origem étnica e HLA de uma população de alto risco para o câncer do colo do útero

A infecção por papilomavirus é a principal causa de desenvolvimento de neoplasias intraepiteliais cervicais (NIC) e câncer do colo do útero (CCU). Estudos epidemiológicos têm demonstrado que a persistência do genoma viral encontra-se associado a variantes moleculares específicas de papilomavirus humano (HPV) de alto risco. As moléculas HLA de classe II têm um importante papel na resposta imune. Associações entre HLA e CCU ou infecção por HPV tem sido demonstrado em diferentes populações. O nosso objetivo foi verificar se a variabilidade de HLA-DRB1 e DQB1 estavam associada ao CCU e NIC III em mulheres de Belém, uma população formada pelos 3 principais grupos étnicos humanos e uma área de alto risco para o CCU no Norte do Brasil. Foi investigada a existência de diferenças na distribuição de alelos HLA entre mulheres com CCU e NIC III portadoras de diferentes variantes de HPV-16 e mulheres citologicamente normais. Os genes HLA DQB1 e DRB1 foram tipados pelo método de PCR-SSO em 95 casos e 287 controles de mulheres com citologia normal atendidas em um centro de prevenção do colo do útero na mesma cidade. As variantes de HPV-16 foram tipadas por sequenciamento de um fragmento da região controladora do genoma viral (LCR). O polimorfismo na posição 350 do gene E6 foi tipado baseado em um protocolo de hibridização em pontos, para identificar a alteração na posição 350T→G. A magnitude das associações foi estimada por odds ratio (OR) e os respectivos intervalos de confiança (IC), ajustados para potenciais fatores de confusão. Uma associação positiva foi observada entre CCU e os haplótipos DRB1* 150 l-DQB1*0602, DRB1*04-DQB1*0301 e DRB1*1602-DQB1*0301. Ao contrário, DRB1*01-DQB1*0501 mostrou um efeito protetor. Os alelos DRB1*0804, DQB1*0402 apresentaram efeito protetor contra positividade por HPV. O alelo DQB1*0502 e o grupo DRB1*15 foram positivamente associados. Os nossos resultados mostram que as associações positivas de DRB1*1501 e DRB1*1602 podem ser atribuídas a variantes asiático-americanas quando comparado a variantes européias. O risco conferido a DRB1*1501 foi encontrado associado tanto a variantes E6350G quanto a variantes E6350T, entretanto, o maior efeito foi devido às variantes E6250T. A associação positiva de DRB1*1602 foi significativa somente no grupo de mulheres positivas para E6350G. Estes resultados estão de acordo com a composição étnica da população estudada bem como um maior potencial oncogênico de certas variantes. Nossos dados sugerem que a contribuição dos alelos HLA na susceptibilidade genética ao CCU difere de acordo com a distribuição das variantes de HPV em uma dada região geográfica ou grupo étnico.

Real time optimization in chemical process: evaluation of strategies, improvements and industrial application.

The increasing economic competition drives the industry to implement tools that improve their processes efficiencies. The process automation is one of these tools, and the Real Time Optimization (RTO) is an automation methodology that considers economic aspects to update the process control in accordance with market prices and disturbances. Basically, RTO uses a steady-state phenomenological model to predict the process behavior, and then, optimizes an economic objective function subject to this model. Although largely implemented in industry, there is not a general agreement about the benefits of implementing RTO due to some limitations discussed in the present work: structural plant/model mismatch, identifiability issues and low frequency of set points update. Some alternative RTO approaches have been proposed in literature to handle the problem of structural plant/model mismatch. However, there is not a sensible comparison evaluating the scope and limitations of these RTO approaches under different aspects. For this reason, the classical two-step method is compared to more recently derivative-based methods (Modifier Adaptation, Integrated System Optimization and Parameter estimation, and Sufficient Conditions of Feasibility and Optimality) using a Monte Carlo methodology. The results of this comparison show that the classical RTO method is consistent, providing a model flexible enough to represent the process topology, a parameter estimation method appropriate to handle measurement noise characteristics and a method to improve the sample information quality. At each iteration, the RTO methodology updates some key parameter of the model, where it is possible to observe identifiability issues caused by lack of measurements and measurement noise, resulting in bad prediction ability. Therefore, four different parameter estimation approaches (Rotational Discrimination, Automatic Selection and Parameter estimation, Reparametrization via Differential Geometry and classical nonlinear Least Square) are evaluated with respect to their prediction accuracy, robustness and speed. The results show that the Rotational Discrimination method is the most suitable to be implemented in a RTO framework, since it requires less a priori information, it is simple to be implemented and avoid the overfitting caused by the Least Square method. The third RTO drawback discussed in the present thesis is the low frequency of set points update, this problem increases the period in which the process operates at suboptimum conditions. An alternative to handle this problem is proposed in this thesis, by integrating the classic RTO and Self-Optimizing control (SOC) using a new Model Predictive Control strategy. The new approach demonstrates that it is possible to reduce the problem of low frequency of set points updates, improving the economic performance. Finally, the practical aspects of the RTO implementation are carried out in an industrial case study, a Vapor Recompression Distillation (VRD) process located in Paulínea refinery from Petrobras. The conclusions of this study suggest that the model parameters are successfully estimated by the Rotational Discrimination method; the RTO is able to improve the process profit in about 3%, equivalent to 2 million dollars per year; and the integration of SOC and RTO may be an interesting control alternative for the VRD process.

Tackling redundancy in text summarization through different levels of language analysis

One of the main challenges to be addressed in text summarization concerns the detection of redundant information. This paper presents a detailed analysis of three methods for achieving such goal. The proposed methods rely on different levels of language analysis: lexical, syntactic and semantic. Moreover, they are also analyzed for detecting relevance in texts. The results show that semantic-based methods are able to detect up to 90% of redundancy, compared to only the 19% of lexical-based ones. This is also reflected in the quality of the generated summaries, obtaining better summaries when employing syntactic- or semantic-based approaches to remove redundancy.

EnvironmentalWaveletTool: Continuous and discrete wavelet analysis and filtering for environmental time series

A MATLAB-based computer code has been developed for the simultaneous wavelet analysis and filtering of several environmental time series, particularly focused on the analyses of cave monitoring data. The continuous wavelet transform, the discrete wavelet transform and the discrete wavelet packet transform have been implemented to provide a fast and precise time–period examination of the time series at different period bands. Moreover, statistic methods to examine the relation between two signals have been included. Finally, the entropy of curves and splines based methods have also been developed for segmenting and modeling the analyzed time series. All these methods together provide a user-friendly and fast program for the environmental signal analysis, with useful, practical and understandable results.

Evaluation of sampling method effects in 3D non-rigid registration

Since the beginning of 3D computer vision problems, the use of techniques to reduce the data to make it treatable preserving the important aspects of the scene has been necessary. Currently, with the new low-cost RGB-D sensors, which provide a stream of color and 3D data of approximately 30 frames per second, this is getting more relevance. Many applications make use of these sensors and need a preprocessing to downsample the data in order to either reduce the processing time or improve the data (e.g., reducing noise or enhancing the important features). In this paper, we present a comparison of different downsampling techniques which are based on different principles. Concretely, five different downsampling methods are included: a bilinear-based method, a normal-based, a color-based, a combination of the normal and color-based samplings, and a growing neural gas (GNG)-based approach. For the comparison, two different models have been used acquired with the Blensor software. Moreover, to evaluate the effect of the downsampling in a real application, a 3D non-rigid registration is performed with the data sampled. From the experimentation we can conclude that depending on the purpose of the application some kernels of the sampling methods can improve drastically the results. Bilinear- and GNG-based methods provide homogeneous point clouds, but color-based and normal-based provide datasets with higher density of points in areas with specific features. In the non-rigid application, if a color-based sampled point cloud is used, it is possible to properly register two datasets for cases where intensity data are relevant in the model and outperform the results if only a homogeneous sampling is used.

Numerical and experimental investigation of structural stiffness influence on ratcheting convection cell in granular soils under cyclic loading

Lateral cyclic loaded structures in granular soils can lead to an accumulation of irreversible strains by changing their mechanical response (densification) and forming a closed convective cell in the upper layer of the bedding. In the present thesis the convective cell dimension, formation and grain migration inside this closed volume have been studied and presented in relation to structural stiffness and different loads. This relation was experimentally investigated by applying a cyclic lateral force to a scaled flexible vertical element embedded in dry granular soil. The model was monitored with a camera in order to derive the displacement field by means of the PIV technique. Modelling large soil deformation turns out to be difficult, using mesh-based methods. Consequently, a mesh-free approach (DEM) was chosen in order to investigate the granular flow with the aim of extracting interesting micromechanical information. In both the numerical and experimental analyses the effect of different loading magnitudes and different dimensions of the vertical element were considered. The main results regarded the different development, shape and dimensions of the convection cell and the surface settlements. Moreover, the Discrete Element Method has proven to give satisfactory results in the modelling of large deformation phenomena such as the ratcheting convective cell.

A Multiplex Real-Time PCR with High Resolution Melting Analysis for the Characterization of Antimicrobial Resistance in Neisseria gonorrhoeae.

Resistance to antibiotics used against Neisseria gonorrhoeae infections is a major public health concern. Antimicrobial resistance (AMR) testing relies on time-consuming culture-based methods. Development of rapid molecular tests for detecting AMR determinants could provide valuable tools for surveillance, epidemiological studies and to inform individual case management. We developed a fast (<1.5 hrs) SYBR-green based real-time PCR method with high resolution melting (HRM) analysis. One triplex and three duplex reactions included two sequences for N. gonorrhoeae identification and seven determinants of resistance to extended-spectrum cephalosporins (ESCs), azithromycin, ciprofloxacin, and spectinomycin. The method was validated by testing 39 previously fully-characterized N. gonorrhoeae strains, 19 commensal Neisseria spp., and an additional panel of 193 gonococcal isolates. Results were compared with culture-based AMR determination. The assay correctly identified N. gonorrhoeae and the presence or absence of the seven AMR determinants. There was some cross-reactivity with non-gonococcal Neisseria species and the detection limit was 10(3)-10(4) gDNA copies/reaction. Overall, the platform accurately detected resistance to ciprofloxacin (sensitivity and specificity, 100%), ceftriaxone (sensitivity 100%, specificity 90%), cefixime (sensitivity 92%, specificity 94%), azithromycin and spectinomycin (both sensitivity and specificity, 100%). In conclusion, our methodology accurately detects mutations generating resistance to antibiotics used to treat gonorrhea. Low assay sensitivity prevents direct diagnostic testing of clinical specimens but this method can be used to screen collections of gonococcal isolates for AMR more quickly than with current culture-based AMR testing.

Nitrogen isotopic composition and chemical composition of altered oceanic crust from ODP Legs 129 and 185

Knowledge of the subduction input flux of nitrogen (N) in altered oceanic crust (AOC) is critical in any attempt to mass-balance N across arc-trench systems on a global or individual-margin basis. We have employed sealed-tube, carrier-gas-based methods to examine the N concentrations and isotopic compositions of AOC. Analyses of 53 AOC samples recovered on DSDP/ODP legs from the North and South Pacific, the North Atlantic, and the Antarctic oceans (with larger numbers of samples from Site 801 outboard of the Mariana trench and Site 1149 outboard of the Izu trench), and 14 composites for the AOC sections at Site 801, give N concentrations of 1.3 to 18.2 ppm and d15N_air of -11.6? to +8.3?, indicating significant N enrichment probably during the early stages of hydrothermal alteration of the oceanic basalts. The N-d15N modeling for samples from Sites 801 and 1149 (n=39) shows that the secondary N may come from (1) the sedimentary N in the intercalated sediments and possibly overlying sediments via fluid-sediment/rock interaction, and (2) degassed mantle N2 in seawater via alteration-related abiotic reduction processes. For all Site 801 samples, weak correlation of N and K2O contents indicates that the siting of N in potassic alteration phases strongly depends on N availability and is possibly influenced by highly heterogeneous temperature and redox conditions during hydrothermal alteration. The upper 470-m AOC recovered by ODP Legs 129 and 185 delivers approximately 800 kg/km N annually into the Mariana margin. If the remaining less-altered oceanic crust (assuming 6.5 km, mostly dikes and gabbros) has MORB-like N of 1.5 ppm, the entire oceanic crust transfers 5100 kg/km N annually into that trench. This N input flux is twice as large as the annual N input of 2500 kg/km in seafloor sediments subducting into the same margin, demonstrating that the N input in oceanic crust, and its isotopic consequences, must be considered in any assessment of convergent margin N flux.

Traffic safety demonstration program modeling system. Volume IV: appendices.

National Highway Traffic Safety Administration, Washington, D.C.

Traffic safety demonstration program modeling system. Volume I: technical summary. Final report.

National Highway Traffic Safety Administration, Washington, D.C.

Traffic safety demonstration program modeling system. Volume II: system manual. Final report.

National Highway Traffic Safety Administration, Washington, D.C.

Towards Accurate and Efficient Description of Excited States

Thesis (Ph.D.)--University of Washington, 2016-06

Depression Management Using Electronic Health Record: Individual Progression Prediction

Thesis (Master's)--University of Washington, 2016-06