639 resultados para Fano Partitions


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The purpose of discussed optimal valid partitioning (OVP) methods is uncovering of ordinal or continuous explanatory variables effect on outcome variables of different types. The OVP approach is based on searching partitions of explanatory variables space that in the best way separate observations with different levels of outcomes. Partitions of single variables ranges or two-dimensional admissible areas for pairs of variables are searched inside corresponding families. Statistical validity associated with revealed regularities is estimated with the help of permutation test repeating search of optimal partition for each permuted dataset. Method for output regularities selection is discussed that is based on validity evaluating with the help of two types of permutation tests.

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Composition problem is considered for partition constrained vertex subsets of n dimensional unit cube E^n . Generating numerical characteristics of E^n subsets partitions is considered by means of the same characteristics in 1 − n dimensional unit cube, and construction of corresponding subsets is given for a special particular case. Using pairs of lower layer characteristic vectors for E^(1-n) more characteristic vectors for E^n are composed which are boundary from one side, and which take part in practical recognition of validness of a given candidate vector of partitions.

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A partition of a positive integer n is a way of writing it as the sum of positive integers without regard to order; the summands are called parts. The number of partitions of n, usually denoted by p(n), is determined asymptotically by the famous partition formula of Hardy and Ramanujan [5]. We shall introduce the uniform probability measure P on the set of all partitions of n assuming that the probability 1/p(n) is assigned to each n-partition. The symbols E and V ar will be further used to denote the expectation and variance with respect to the measure P . Thus, each conceivable numerical characteristic of the parts in a partition can be regarded as a random variable.

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2000 Mathematics Subject Classification: Primary 46H05, 46H20; Secondary 46M20.

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2000 Mathematics Subject Classification: 05E05, 14N10, 57R45.

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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.

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Produced water constitutes the largest volume of waste from offshore oil and gas operations and is composed of a wide range of organic and inorganic compounds. Although treatment processes have to meet strict oil in water regulations, the definition of “oil” is a function of the analysis process and may include aliphatic hydrocarbons which have limited environmental impact due to degradability whilst ignoring problematic dissolved petroleum species. This thesis presents the partitioning behavior of oil in produced water as a function of temperature and salinity to identify compounds of environmental concern. Phenol, p-cresol, and 4-tert-butylphenol were studied because of their xenoestrogenic power; other compounds studied are polycyclic aromatic hydrocarbon PAHs which include naphthalene, fluorene, phenanthrene, and pyrene. Partitioning experiments were carried out in an Innova incubator for 48 hours, temperature was varied from 4゚C to 70゚C, and two salinity levels of 46.8‰ and 66.8‰ were studied. Results obtained showed that the dispersed oil concentration in the water reduces with settling time and equilibrium was attained at 48 h settling time. Polycyclic aromatic hydrocarbons (PAHs) partitions based on dispersed oil concentration whereas phenols are not significantly affected by dispersed oil concentration. Higher temperature favors partitioning of PAHs into the water phase. Salinity has negligible effect on partitioning pattern of phenols and PAHs studied. Simulation results obtained from the Aspen HYSYS model shows that temperature and oil droplet distribution greatly influences the efficiency of produced water treatment system.

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Lo scopo di questo elaborato è stato individuare una possibile correlazione tra le condizioni ambientali e la presenza di Escherichia coli in vongole lupino. I dati relativi a campioni raccolti nel periodo 2008-2015 nella zona tra Cervia e Fano sono stati messi in relazione con alcuni parametri quali salinità dell’acqua, temperatura, ossigeno di fondo, pH e livello del fiume Marecchia. Sono stati presi in considerazione oltre 350 campioni, in cui i conteggi di E. coli mediante tecnica MPN sono stati suddivisi in tre categorie: cariche basse (<50 MPN/100g); cariche intermedie (50-230 MPN/100g); cariche alte, ossia non conformi al regolamento europeo (>230 MPN/100g). L’eventuale significatività della relazione tra E. coli e le variabili considerate è stata valutata attraverso il test chi-quadrato e il test di Kruskal-Wallis. Per quanto riguarda il test chi-quadrato, eseguito in relazione ad anno, mese e stagione, si è visto che i campioni più inquinati derivano dagli anni 2010 e 2012, dai mesi novembre/dicembre e in generale dalla stagione autunnale. L’analisi della varianza tramite test di Kruskal-Wallis ha evidenziato che le frequenze dei campioni nelle tre categorie non sono significative in relazione alla salinità. Al contrario, per i parametri temperatura e livello del fiume Marecchia sono stati ottenuti risultati significativi: infatti, le cariche microbiche più alte corrispondono a temperature più basse delle acque e a periodi di maggiore portata del fiume. Questo episodio riflette sicuramente un aspetto biologico legato al ciclo vitale di Chamelea gallina, che vive la sua fase riproduttiva nella stagione più calda, diminuendo quindi la sua attività filtrante, fonte di contaminazione. Al contempo questo andamento è anche spiegabile dall’apporto di contaminanti dalle precipitazioni e dai fiumi che trascinano sostanze organiche inquinanti di natura antropica, che costituiscono fonte di nutrimento per le specie microbiche come E. coli ed altri enterobatteri.

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Deep-water coral ecosystems are hot spots of biodiversity and provide habitats and refuges for several deep-sea species. However, their role in shaping the biodiversity of the surrounding open slopes is still poorly known. We investigated how meiofaunal biodiversity varies with and is related to the occurrence of deep-water living scleractinian corals and coral rubble in two deep-sea areas (the Rockall Bank, northeastern Atlantic) and the Santa Maria di Leuca (central Mediterranean). In both areas, replicated sampling on alive and dead coral areas and from the adjacent slope sediments without corals (at the same and increasing depths) allowed us to demonstrate that sediments surrounding the living corals and coral rubble were characterised by higher meiofaunal biodiversity (as number of higher taxa, and nematode species richness) than the slope sediments. Despite the soft sediments surrounding the living coral having a higher nutritional value than those not associated with corals, with the opposite seen for coral rubble, the presence of both alive and dead corals had a significant effect on nematode assemblages. Our data suggest that, due particularly to the effects on habitat heterogeneity/complexity, both living coral and coral rubble promoted higher biodiversity levels than in surrounding slope sediments. We conclude that the protection of deep-water corals can be crucial to preserve the biodiversity of surrounding open slopes, and that the protection of dead corals, a so-far almost neglected habitat in terms of biological conservation, can further contribute to the maintenance of a high deep-sea biodiversity along continental margins.

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The Banisteriopsis genus is widespread in traditional medicine. This work aims to contribute with information about the chemical composition and on the evaluation of the biological activity of the essential oil, the ethanol extract of the leaves and partitions of the Banisteriopsis laevifolia. The phytochemical screeningtest of ethanol extract and partitions of leaves indicated the presence of flavonoids, terpenoids, saponins, phenols and steroids compounds. Nitrogenous compounds, characteristic of some species of this family, were not detected. Flavonoids were the predominant metabolite, with the highest concentrations on the partitions ethyl acetate and n-butanol. The antibacterial activity, antifungal and cytotoxicity of the essetial oil, ethanol extract and partitions were assyed by microdilution broth method (MBM), where the minimum inhibitory concentrations (MIC) were calculated. The ethanol extract and partitions did not inhibit growth against to Gram positive bacteria tested, with MIC less than 400 mg L-1. For the Gram negative bacteria tested, the hexane and hydroethanol partitios were more effective against F. nucleatum bacteria (MIC 100 ug mL-1). The ethanol extract showed antifungal activity with MIC of 31.2 mg L-1. Ethyl acetate and n-butanol partitions showed MIC 187.5 mg L-1 and 93.7 mg L-1, respectively, arousing interest for isolation studies. The antioxidant activity was evaluated by the DPPH free radical method. The ethanolic extract, ethyl acetate and n-butanol partitions were active, since they showed EC50 values (4.53 ug mL-1, 4.07 and 8.39 ug mL-1, respectively), values equivalent to the BHT (7.3 mg L-1). The analysis by HPLC-MS/MS of the most active fractions (ethyl acetate and n-butanol) identified phenolic compounds (flavonols and phenolic acids) which exert recognized biological activity. The GC-MS analysis of the essential oils from leaves collected in two periods studied (dry and wet), showed a small variation in the number of compounds. The major classes identified for the oil collected in the dry period were aliphatic alcohols (23,4%), terpenoids (18.7%), sterols (10.4%) and long-chain alkanes (9.2%) compounds. Terpenoids (26.8%) were the major class for the rain season. The major compounds (3Z) -hexenol, phytol and untriacontano are present in the two seasons but in different amounts (19.4%, 9.8% and 7.5% during the dry season, and 17.0 %, 14.9% and 15.3% in the rainy season, respectively). The essential oil from rainy season was not effective against to the oral bacteria Gram positive and Gram negative tested. However, showed significant antifungal activity with MIC 1000 mg L-1 against Candidas. Thus, the promising results with respect to biological assays of ethanolic extract and partitions from B. laevifolia contributed to the chemical and biological knowledge of the species B. laevifolia.

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This thesis analyzes the Chow motives of 3 types of smooth projective varieties: the desingularized elliptic self fiber product, the Fano surface of lines on a cubic threefold and an ample hypersurface of an Abelian variety. For the desingularized elliptic self fiber product, we use an isotypic decomposition of the motive to deduce the Murre conjectures. We also prove a result about the intersection product. For the Fano surface of lines, we prove the finite-dimensionality of the Chow motive. Finally, we prove that an ample hypersurface on an Abelian variety possesses a Chow-Kunneth decomposition for which a motivic version of the Lefschetz hyperplane theorem holds.

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Fitting statistical models is computationally challenging when the sample size or the dimension of the dataset is huge. An attractive approach for down-scaling the problem size is to first partition the dataset into subsets and then fit using distributed algorithms. The dataset can be partitioned either horizontally (in the sample space) or vertically (in the feature space), and the challenge arise in defining an algorithm with low communication, theoretical guarantees and excellent practical performance in general settings. For sample space partitioning, I propose a MEdian Selection Subset AGgregation Estimator ({\em message}) algorithm for solving these issues. The algorithm applies feature selection in parallel for each subset using regularized regression or Bayesian variable selection method, calculates the `median' feature inclusion index, estimates coefficients for the selected features in parallel for each subset, and then averages these estimates. The algorithm is simple, involves very minimal communication, scales efficiently in sample size, and has theoretical guarantees. I provide extensive experiments to show excellent performance in feature selection, estimation, prediction, and computation time relative to usual competitors.

While sample space partitioning is useful in handling datasets with large sample size, feature space partitioning is more effective when the data dimension is high. Existing methods for partitioning features, however, are either vulnerable to high correlations or inefficient in reducing the model dimension. In the thesis, I propose a new embarrassingly parallel framework named {\em DECO} for distributed variable selection and parameter estimation. In {\em DECO}, variables are first partitioned and allocated to m distributed workers. The decorrelated subset data within each worker are then fitted via any algorithm designed for high-dimensional problems. We show that by incorporating the decorrelation step, DECO can achieve consistent variable selection and parameter estimation on each subset with (almost) no assumptions. In addition, the convergence rate is nearly minimax optimal for both sparse and weakly sparse models and does NOT depend on the partition number m. Extensive numerical experiments are provided to illustrate the performance of the new framework.

For datasets with both large sample sizes and high dimensionality, I propose a new "divided-and-conquer" framework {\em DEME} (DECO-message) by leveraging both the {\em DECO} and the {\em message} algorithm. The new framework first partitions the dataset in the sample space into row cubes using {\em message} and then partition the feature space of the cubes using {\em DECO}. This procedure is equivalent to partitioning the original data matrix into multiple small blocks, each with a feasible size that can be stored and fitted in a computer in parallel. The results are then synthezied via the {\em DECO} and {\em message} algorithm in a reverse order to produce the final output. The whole framework is extremely scalable.

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Owing to their important roles in biogeochemical cycles, phytoplankton functional types (PFTs) have been the aim of an increasing number of ocean color algorithms. Yet, none of the existing methods are based on phytoplankton carbon (C) biomass, which is a fundamental biogeochemical and ecological variable and the "unit of accounting" in Earth system models. We present a novel bio-optical algorithm to retrieve size-partitioned phytoplankton carbon from ocean color satellite data. The algorithm is based on existing methods to estimate particle volume from a power-law particle size distribution (PSD). Volume is converted to carbon concentrations using a compilation of allometric relationships. We quantify absolute and fractional biomass in three PFTs based on size - picophytoplankton (0.5-2 µm in diameter), nanophytoplankton (2-20 µm) and microphytoplankton (20-50 µm). The mean spatial distributions of total phytoplankton C biomass and individual PFTs, derived from global SeaWiFS monthly ocean color data, are consistent with current understanding of oceanic ecosystems, i.e., oligotrophic regions are characterized by low biomass and dominance of picoplankton, whereas eutrophic regions have high biomass to which nanoplankton and microplankton contribute relatively larger fractions. Global climatological, spatially integrated phytoplankton carbon biomass standing stock estimates using our PSD-based approach yield - 0.25 Gt of C, consistent with analogous estimates from two other ocean color algorithms and several state-of-the-art Earth system models. Satisfactory in situ closure observed between PSD and POC measurements lends support to the theoretical basis of the PSD-based algorithm. Uncertainty budget analyses indicate that absolute carbon concentration uncertainties are driven by the PSD parameter No which determines particle number concentration to first order, while uncertainties in PFTs' fractional contributions to total C biomass are mostly due to the allometric coefficients. The C algorithm presented here, which is not empirically constrained a priori, partitions biomass in size classes and introduces improvement over the assumptions of the other approaches. However, the range of phytoplankton C biomass spatial variability globally is larger than estimated by any other models considered here, which suggests an empirical correction to the No parameter is needed, based on PSD validation statistics. These corrected absolute carbon biomass concentrations validate well against in situ POC observations.

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About one-third of the carbon dioxide (CO2) released into the atmosphere as a result of human activity has been absorbed by the oceans, where it partitions into the constituent ions of carbonic acid. This leads to ocean acidification, one of the major threats to marine ecosystems and particularly to calcifying organisms such as corals, foraminifera and coccolithophores. Coccolithophores are abundant phytoplankton that are responsible for a large part of modern oceanic carbonate production. Culture experiments investigating the physiological response of coccolithophore calcification to increased CO2 have yielded contradictory results between and even within species. Here we quantified the calcite mass of dominant coccolithophores in the present ocean and over the past forty thousand years, and found a marked pattern of decreasing calcification with increasing partial pressure of CO2 and concomitant decreasing concentrations of CO3. Our analyses revealed that differentially calcified species and morphotypes are distributed in the ocean according to carbonate chemistry. A substantial impact on the marine carbon cycle might be expected upon extrapolation of this correlation to predicted ocean acidification in the future. However, our discovery of a heavily calcified Emiliania huxleyi morphotype in modern waters with low pH highlights the complexity of assemblage-level responses to environmental forcing factors.

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Tetradiids are a group of colonial, tubular fossils that occur globally in Middle to Upper Ordovician strata. Tetradiids were first described as a type of tabulate coral; however, based on their four-fold symmetry, division, and presence of a central-sparry canal, they were recently reinterpreted as a florideophyte rhodophyte algae, a reinterpretation that is tested in this thesis. This study focused on understanding the affinity and taphonomy of this order of fossil. Research was conducted by stratigraphic and petrographic analyses of the Black River Group in the Kingston, Ontario region. Tetradiid occurrences were divided into fragment or colonial, with three morphologies of tetradiids described (Tetradium, Phytopsis and Paratetradium). Morphology is specific to depositional environment, with compact Tetradium consistently within ooid grainstones and open branching Phytopsis and chained Paratetradium consistently within mudstones. Two types of patch reefs were recognized: a Paratetradium bioherm, and a Paratetradium, Phytopsis, stromatolite bioherm. The presence of bioherms implies that tetradiids were capable of hypercalcifying. Preservation styles of tetradiids were investigated, and were compared to brachiopods, echinoderms, mollusks, and ooids. Tetradiids were preferentially preserved as molds and demonstrated complete dissolution of skeletal material. Rare specimens, however, demonstrated preserved horizontal partitions, central plates, and a double wall. Skeletal molds were filled with either calcite spar, mud or encrusted by a cryptomicrobial colony. Both calcitic and aragonitic ooids were discovered. The co-occurrence of aragonitic ooids, aragonitic crytodontids, and the evolution of aragonitic, hypercalcifying tetradiids is interpreted as representing the geochemical favoring of aragonite and HMC in a time of global calcite seas. The geochemical favoring of aragonite is interpreted to be independent to global Mg: Ca ratios, but was the result of increased saturation levels and temperature driven by high atmospheric pCO2. Based on the presence of epitheca, tabulae, septa, and the commonality of growth forms, tetradiids are interpreted as an order of Cnidaria. The evolution of an aragonitic skeleton in tetradiids is interpreted to be the result of de novo acquisition of a skeleton from an unmineralized clade.