Algoritmos de agrupamento aplicados a dados de expressão gênica de câncer: um estudo comparativo

The use of clustering methods for the discovery of cancer subtypes has drawn a great deal of attention in the scientific community. While bioinformaticians have proposed new clustering methods that take advantage of characteristics of the gene expression data, the medical community has a preference for using classic clustering methods. There have been no studies thus far performing a large-scale evaluation of different clustering methods in this context. This work presents the first large-scale analysis of seven different clustering methods and four proximity measures for the analysis of 35 cancer gene expression data sets. Results reveal that the finite mixture of Gaussians, followed closely by k-means, exhibited the best performance in terms of recovering the true structure of the data sets. These methods also exhibited, on average, the smallest difference between the actual number of classes in the data sets and the best number of clusters as indicated by our validation criteria. Furthermore, hierarchical methods, which have been widely used by the medical community, exhibited a poorer recovery performance than that of the other methods evaluated. Moreover, as a stable basis for the assessment and comparison of different clustering methods for cancer gene expression data, this study provides a common group of data sets (benchmark data sets) to be shared among researchers and used for comparisons with new methods

Cultura organizacional e avaliação em larga escala: faces e interfaces a partir da análise de escolas públicas municipais

Pós-graduação em Educação - FFC

As representações da equipe escolar frente aos resultados do SARESP, quanto à leitura

Pós-graduação em Educação - FFC

Avaliação em larga escala, gestão e qualidade de ensino em duas escolas públicas municipais

Coordenação de Aperfeiçoamento de Pessoal de Nível Superior (CAPES)

Ensino de Ciências e os sistemas de avaliação em larga escala na educação básica: processos formativos e aprendizagens profissionais da docência

Pós-graduação em Educação para a Ciência - FC

Saberes docentes, sistema de avaliação de rendimento escolar do Estado de São Paulo e ensino de Ciências: um estudo de caso a partir de situações de ensino-aprendizagem

Coordenação de Aperfeiçoamento de Pessoal de Nível Superior (CAPES)

Avaliações externas e em larga escala nas redes de educação básica dos Estados brasileiros

Pós-graduação em Educação - FCT

A legitimação das avaliações em larga escala no discurso sobre gestão educacional

Pós-graduação em Educação - FFC

Argumentação em foco: a perspectiva de avaliação do ENEM

Nowadays ENEM is the main large-scale evaluation instrument of Brazilian education. Universities also often use it in order to select their candidates. Reading exam seeks to evaluate student’s capacity of producing argumentative and dissertation prose writing about a social, scientific, cultural or political theme. This paper is located in this context: we want to discuss the evaluation of ENEM’s Writing Exam argumentation. Our startpoint is presuppose that the capacity to develop a well-argued text evaluation goes through several specific skills, which cover different aspects of what is understood about argumentation process. Therefore, considering argumentation as an object of different theoretical approaches and covers different concepts, we intend to verify not only the approaches, but also subjacent concepts and how they were converted into skills and competences established on the ENEM Writing Exam’s matrix of correction. With regard to the nature, it is a theoretical paper, in other words, we intend to offer only a discussion about the theme, not necessarily offering a practical application. Concerning to the goals, it has an exploratory character as we intend to offer a problem treatment, in order to make it more explicit and them construct some hypotheses. In these terms, we surveyed some theoretical approaches about argumentation and presented three conceptions: rhetorical argumentation, textual argumentation and linguistics argumentation. At next, we analyzed the participant’s guide (ENEM’s 2013 Writing Exam ) and how each one of these conceptions are mobilized in the writing evaluation, beginning from how they are considered on the description of competences and skills up to used on correction. This analysis shows that is not assumed a very well established theoretical base, which can contribute to a certain fragility on the Writing Exam evaluation process.

Retrieval of grassland biophysical parameters using multitemporal optical and radar satellite data

The amount and quality of available biomass is a key factor for the sustainable livestock industry and agricultural management related decision making. Globally 31.5% of land cover is grassland while 80% of Ireland’s agricultural land is grassland. In Ireland, grasslands are intensively managed and provide the cheapest feed source for animals. This dissertation presents a detailed state of the art review of satellite remote sensing of grasslands, and the potential application of optical (Moderate–resolution Imaging Spectroradiometer (MODIS)) and radar (TerraSAR-X) time series imagery to estimate the grassland biomass at two study sites (Moorepark and Grange) in the Republic of Ireland using both statistical and state of the art machine learning algorithms. High quality weather data available from the on-site weather station was also used to calculate the Growing Degree Days (GDD) for Grange to determine the impact of ancillary data on biomass estimation. In situ and satellite data covering 12 years for the Moorepark and 6 years for the Grange study sites were used to predict grassland biomass using multiple linear regression, Neuro Fuzzy Inference Systems (ANFIS) models. The results demonstrate that a dense (8-day composite) MODIS image time series, along with high quality in situ data, can be used to retrieve grassland biomass with high performance (R2 = 0:86; p < 0:05, RMSE = 11.07 for Moorepark). The model for Grange was modified to evaluate the synergistic use of vegetation indices derived from remote sensing time series and accumulated GDD information. As GDD is strongly linked to the plant development, or phonological stage, an improvement in biomass estimation would be expected. It was observed that using the ANFIS model the biomass estimation accuracy increased from R2 = 0:76 (p < 0:05) to R2 = 0:81 (p < 0:05) and the root mean square error was reduced by 2.72%. The work on the application of optical remote sensing was further developed using a TerraSAR-X Staring Spotlight mode time series over the Moorepark study site to explore the extent to which very high resolution Synthetic Aperture Radar (SAR) data of interferometrically coherent paddocks can be exploited to retrieve grassland biophysical parameters. After filtering out the non-coherent plots it is demonstrated that interferometric coherence can be used to retrieve grassland biophysical parameters (i. e., height, biomass), and that it is possible to detect changes due to the grass growth, and grazing and mowing events, when the temporal baseline is short (11 days). However, it not possible to automatically uniquely identify the cause of these changes based only on the SAR backscatter and coherence, due to the ambiguity caused by tall grass laid down due to the wind. Overall, the work presented in this dissertation has demonstrated the potential of dense remote sensing and weather data time series to predict grassland biomass using machine-learning algorithms, where high quality ground data were used for training. At present a major limitation for national scale biomass retrieval is the lack of spatial and temporal ground samples, which can be partially resolved by minor modifications in the existing PastureBaseIreland database by adding the location and extent ofeach grassland paddock in the database. As far as remote sensing data requirements are concerned, MODIS is useful for large scale evaluation but due to its coarse resolution it is not possible to detect the variations within the fields and between the fields at the farm scale. However, this issue will be resolved in terms of spatial resolution by the Sentinel-2 mission, and when both satellites (Sentinel-2A and Sentinel-2B) are operational the revisit time will reduce to 5 days, which together with Landsat-8, should enable sufficient cloud-free data for operational biomass estimation at a national scale. The Synthetic Aperture Radar Interferometry (InSAR) approach is feasible if there are enough coherent interferometric pairs available, however this is difficult to achieve due to the temporal decorrelation of the signal. For repeat-pass InSAR over a vegetated area even an 11 days temporal baseline is too large. In order to achieve better coherence a very high resolution is required at the cost of spatial coverage, which limits its scope for use in an operational context at a national scale. Future InSAR missions with pair acquisition in Tandem mode will minimize the temporal decorrelation over vegetation areas for more focused studies. The proposed approach complements the current paradigm of Big Data in Earth Observation, and illustrates the feasibility of integrating data from multiple sources. In future, this framework can be used to build an operational decision support system for retrieval of grassland biophysical parameters based on data from long term planned optical missions (e. g., Landsat, Sentinel) that will ensure the continuity of data acquisition. Similarly, Spanish X-band PAZ and TerraSAR-X2 missions will ensure the continuity of TerraSAR-X and COSMO-SkyMed.

Soil organic carbon stocks in estuarine and marine mangrove ecosystems are driven by nutrient colimitation of P and N

Mangroves play an important role in carbon sequestration, but soil organic carbon (SOC) stocks differ between marine and estuarine mangroves, suggesting differing processes and drivers of SOC accumulation. Here, we compared undegraded and degraded marine and estuarine mangroves in a regional approach across the Indonesian archipelago for their SOC stocks and evaluated possible drivers imposed by nutrient limitations along the land-to-sea gradients. SOC stocks in natural marine mangroves (271–572 Mg ha-1 m-1 were much higher than under estuarine mangroves (100–315 Mg ha-1 m-1 with a further decrease caused by degradation to 80–132 Mg ha-1 m-1. Soils differed in C/N ratio (marine: 29–64; estuarine: 9–28), δ15N (marine: 0.6 to 0.7‰; estuarine: 2.5 to 7.2‰), and plant-available P (marine: 2.3–6.3 mg kg-1; estuarine: 0.16–1.8 mg kg-1). We found N and P supply of sea-oriented mangroves primarily met by dominating symbiotic N2 fixation from air and P import from sea, while mangroves on the landward gradient increasingly covered their demand in N and P from allochthonous sources and SOM recycling. Pioneer plants favored by degradation further increased nutrient recycling from soil resulting in smaller SOC stocks in the topsoil. These processes explained the differences in SOC stocks along the land-to-sea gradient in each mangrove type as well as the SOC stock differences observed between estuarine and marine mangrove ecosystems. This first large-scale evaluation of drivers of SOC stocks under mangroves thus suggests a continuum in mangrove functioning across scales and ecotypes and additionally provides viable proxies for carbon stock estimations in PES or REDD schemes.

Evaluation of a large-eddy model simulation of a mixed-phase altocumulus cloud using microwave radiometer, lidar and Doppler radar data

Using the Met Office large-eddy model (LEM) we simulate a mixed-phase altocumulus cloud that was observed from Chilbolton in southern England by a 94 GHz Doppler radar, a 905 nm lidar, a dual-wavelength microwave radiometer and also by four radiosondes. It is important to test and evaluate such simulations with observations, since there are significant differences between results from different cloud-resolving models for ice clouds. Simulating the Doppler radar and lidar data within the LEM allows us to compare observed and modelled quantities directly, and allows us to explore the relationships between observed and unobserved variables. For general-circulation models, which currently tend to give poor representations of mixed-phase clouds, the case shows the importance of using: (i) separate prognostic ice and liquid water, (ii) a vertical resolution that captures the thin layers of liquid water, and (iii) an accurate representation the subgrid vertical velocities that allow liquid water to form. It is shown that large-scale ascents and descents are significant for this case, and so the horizontally averaged LEM profiles are relaxed towards observed profiles to account for these. The LEM simulation then gives a reasonable. cloud, with an ice-water path approximately two thirds of that observed, with liquid water at the cloud top, as observed. However, the liquid-water cells that form in the updraughts at cloud top in the LEM have liquid-water paths (LWPs) up to half those observed, and there are too few cells, giving a mean LWP five to ten times smaller than observed. In reality, ice nucleation and fallout may deplete ice-nuclei concentrations at the cloud top, allowing more liquid water to form there, but this process is not represented in the model. Decreasing the heterogeneous nucleation rate in the LEM increased the LWP, which supports this hypothesis. The LEM captures the increase in the standard deviation in Doppler velocities (and so vertical winds) with height, but values are 1.5 to 4 times smaller than observed (although values are larger in an unforced model run, this only increases the modelled LWP by a factor of approximately two). The LEM data show that, for values larger than approximately 12 cm s(-1), the standard deviation in Doppler velocities provides an almost unbiased estimate of the standard deviation in vertical winds, but provides an overestimate for smaller values. Time-smoothing the observed Doppler velocities and modelled mass-squared-weighted fallspeeds shows that observed fallspeeds are approximately two-thirds of the modelled values. Decreasing the modelled fallspeeds to those observed increases the modelled IWC, giving an IWP 1.6 times that observed.

Evaluation of wind-induced internal pressure in low-rise buildings: A multi scale experimental and numerical approach

Hurricane is one of the most destructive and costly natural hazard to the built environment and its impact on low-rise buildings, particularity, is beyond acceptable. The major objective of this research was to perform a parametric evaluation of internal pressure (IP) for wind-resistant design of low-rise buildings and wind-driven natural ventilation applications. For this purpose, a multi-scale experimental, i.e. full-scale at Wall of Wind (WoW) and small-scale at Boundary Layer Wind Tunnel (BLWT), and a Computational Fluid Dynamics (CFD) approach was adopted. This provided new capability to assess wind pressures realistically on internal volumes ranging from small spaces formed between roof tiles and its deck to attic to room partitions. Effects of sudden breaching, existing dominant openings on building envelopes as well as compartmentalization of building interior on the IP were systematically investigated. Results of this research indicated: (i) for sudden breaching of dominant openings, the transient overshooting response was lower than the subsequent steady state peak IP and internal volume correction for low-wind-speed testing facilities was necessary. For example a building without volume correction experienced a response four times faster and exhibited 30–40% lower mean and peak IP; (ii) for existing openings, vent openings uniformly distributed along the roof alleviated, whereas one sided openings aggravated the IP; (iii) larger dominant openings exhibited a higher IP on the building envelope, and an off-center opening on the wall exhibited (30–40%) higher IP than center located openings; (iv) compartmentalization amplified the intensity of IP and; (v) significant underneath pressure was measured for field tiles, warranting its consideration during net pressure evaluations. The study aimed at wind driven natural ventilation indicated: (i) the IP due to cross ventilation was 1.5 to 2.5 times higher for Ainlet/Aoutlet>1 compared to cases where Ainlet/Aoutlet<1, this in effect reduced the mixing of air inside the building and hence the ventilation effectiveness; (ii) the presence of multi-room partitioning increased the pressure differential and consequently the air exchange rate. Overall good agreement was found between the observed large-scale, small-scale and CFD based IP responses. Comparisons with ASCE 7-10 consistently demonstrated that the code underestimated peak positive and suction IP.

Evaluation of the carbon content of aerosols from the burning of biomass in the Brazilian Amazon using thermal, optical and thermal-optical analysis methods

Aerosol samples were collected at a pasture site in the Amazon Basin as part of the project LBA-SMOCC-2002 (Large-Scale Biosphere-Atmosphere Experiment in Amazonia - Smoke Aerosols, Clouds, Rainfall and Climate: Aerosols from Biomass Burning Perturb Global and Regional Climate). Sampling was conducted during the late dry season, when the aerosol composition was dominated by biomass burning emissions, especially in the submicron fraction. A 13-stage Dekati low-pressure impactor (DLPI) was used to collect particles with nominal aerodynamic diameters (D(p)) ranging from 0.03 to 0.10 mu m. Gravimetric analyses of the DLPI substrates and filters were performed to obtain aerosol mass concentrations. The concentrations of total, apparent elemental, and organic carbon (TC, EC(a), and OC) were determined using thermal and thermal-optical analysis (TOA) methods. A light transmission method (LTM) was used to determine the concentration of equivalent black carbon (BC(e)) or the absorbing fraction at 880 nm for the size-resolved samples. During the dry period, due to the pervasive presence of fires in the region upwind of the sampling site, concentrations of fine aerosols (D(p) < 2.5 mu m: average 59.8 mu g m(-3)) were higher than coarse aerosols (D(p) > 2.5 mu m: 4.1 mu g m(-3)). Carbonaceous matter, estimated as the sum of the particulate organic matter (i.e., OC x 1.8) plus BC(e), comprised more than 90% to the total aerosol mass. Concentrations of EC(a) (estimated by thermal analysis with a correction for charring) and BC(e) (estimated by LTM) averaged 5.2 +/- 1.3 and 3.1 +/- 0.8 mu g m(-3), respectively. The determination of EC was improved by extracting water-soluble organic material from the samples, which reduced the average light absorption Angstrom exponent of particles in the size range of 0.1 to 1.0 mu m from >2.0 to approximately 1.2. The size-resolved BC(e) measured by the LTM showed a clear maximum between 0.4 and 0.6 mu m in diameter. The concentrations of OC and BC(e) varied diurnally during the dry period, and this variation is related to diurnal changes in boundary layer thickness and in fire frequency.

Evaluation of Eucalyptus grandis Hill ex Maiden biopulping with Ceriporiopsis subvermispora under non-aseptic conditions

In biopulping, efficient wood colonization by a selected white-rot fungus depends on previous wood chip decontamination to avoid the growth of primary molds. Although simple to perform in the laboratory, in large-scale biopulping trials, complete wood decontamination is difficult to achieve. Furthermore, the use of fungal growth promoters such as corn steep liquor enhances the risk of culture contamination. This paper evaluates the ability of the biopulping fungus Ceriporiopsis subvermispora to compete with indigenous fungi in cultures of fresh or poorly decontaminated Eucalyptus grandis wood chips. While cultures containing autoclaved wood chips were completely free of contaminants, primary molds grew rapidly when non-autoclaved wood chips were used, resulting in heavily contaminated cultures, regardless of the C. subvermispora inoculum/wood ratio evaluated (5, 50 and 3000 mg mycelium kg(-1) wood). Studies on benomyl-amended medium suggested that the fungi involved competed by consumption of the easily available nutrient sources, with C. subvermispora less successful than the contaminant fungi. The use of acid-washed wood chips decreased the level of such contaminant fungi, but production of manganese peroxidase and xylanases was also decreased under these conditions. Nevertheless, chemithermomechanical pulping of acid-washed samples biotreated under non-aseptic conditions gave similar fibrillation improvements compared to samples subjected to the standard biodegradation process using autoclaved wood chips.