Estudo de níveis de ozônio troposférico usando métodos de estatística univariada e multivariada para duas localidades da cidade do Rio de Janeiro

Com cada vez mais intenso desenvolvimento urbano e industrial, atualmente um desafio fundamental é eliminar ou reduzir o impacto causado pelas emissões de poluentes para a atmosfera. No ano de 2012, o Rio de Janeiro sediou a Rio +20, a Conferência das Nações Unidas sobre Desenvolvimento Sustentável, onde representantes de todo o mundo participaram. Na época, entre outros assuntos foram discutidos a economia verde e o desenvolvimento sustentável. O O3 troposférico apresenta-se como uma variável extremamente importante devido ao seu forte impacto ambiental, e conhecer o comportamento dos parâmetros que afetam a qualidade do ar de uma região, é útil para prever cenários. A química das ciências atmosféricas e meteorologia são altamente não lineares e, assim, as previsões de parâmetros de qualidade do ar são difíceis de serem determinadas. A qualidade do ar depende de emissões, de meteorologia e topografia. Os dados observados foram o dióxido de nitrogênio (NO2), monóxido de nitrogênio (NO), óxidos de nitrogênio (NOx), monóxido de carbono (CO), ozônio (O3), velocidade escalar vento (VEV), radiação solar global (RSG), temperatura (TEM), umidade relativa (UR) e foram coletados através da estação móvel de monitoramento da Secretaria do Meio Ambiente (SMAC) do Rio de Janeiro em dois locais na área metropolitana, na Pontifícia Universidade Católica (PUC-Rio) e na Universidade do Estado do Rio de Janeiro (UERJ) no ano de 2011 e 2012. Este estudo teve três objetivos: (1) analisar o comportamento das variáveis, utilizando o método de análise de componentes principais (PCA) de análise exploratória, (2) propor previsões de níveis de O3 a partir de poluentes primários e de fatores meteorológicos, comparando a eficácia dos métodos não lineares, como as redes neurais artificiais (ANN) e regressão por máquina de vetor de suporte (SVM-R), a partir de poluentes primários e de fatores meteorológicos e, finalmente, (3) realizar método de classificação de dados usando a classificação por máquina de vetor suporte (SVM-C). A técnica PCA mostrou que, para conjunto de dados da PUC as variáveis NO, NOx e VEV obtiveram um impacto maior sobre a concentração de O3 e o conjunto de dados da UERJ teve a TEM e a RSG como as variáveis mais importantes. Os resultados das técnicas de regressão não linear ANN e SVM obtidos foram muito próximos e aceitáveis para o conjunto de dados da UERJ apresentando coeficiente de determinação (R2) para a validação, 0,9122 e 0,9152 e Raiz Quadrada do Erro Médio Quadrático (RMECV) 7,66 e 7,85, respectivamente. Quanto aos conjuntos de dados PUC e PUC+UERJ, ambas as técnicas, obtiveram resultados menos satisfatórios. Para estes conjuntos de dados, a SVM mostrou resultados ligeiramente superiores, e PCA, SVM e ANN demonstraram sua robustez apresentando-se como ferramentas úteis para a compreensão, classificação e previsão de cenários da qualidade do ar

Análise de componentes principais aplicada a ruído eletroquímico

Neste trabalho foi utilizado um método matemático para classificar registros de potencial e corrente de ensaios de corrosão na técnica de amperimetria de resistência nula (ZRA). Foi aplicado o método estatístico de múltiplas variáveis simples chamado Análise dos Componentes Principais (PCA), cujo objetivo principal foi identificar padrões nestes dados de ruído eletroquímico. Foram testados o aço carbono UNS G10200, os aços inoxidáveis austenítico UNS S31600 e o superduplex UNS S32750 em meios de ácido sulfúrico (5% H2SO4), cloreto férrico (0,1 mol/L FeCl3) e hidróxido de sódio (0,1% NaOH). Os ensaios foram replicados com oito repetições para se ter reprodutibilidade e conhecimento dos aspectos estatísticos envolvidos. Os resultados mostraram que a análise de componentes principais pode ser utilizada como uma ferramenta para analisar sinais de ruído eletroquímico, identificando os clusters dos comportamentos potencial-tempo, corrente-tempo e acessoriamente identificar os outliersdos registros temporais.

Surface temperature and precipitation variations in the western U.S. and their relation to large scale circulation indices [abstract]

EXTRACT (SEE PDF FOR FULL ABSTRACT): An analysis of the principal components of surface temperature and precipitation in the western U.S. is presented. Data consist of monthly mean temperature and total precipitation for 66 climate divisions west of the Continental Divide, for the years 1931-1984. The analysis is repeated for three separate combinations of months - the water year (Oct - Sept), the cool season (Oct - Mar) and the warm season (Apr - Sept). Inspection of monthly precipitation climatology indicates that selection of these combinations of months results in very few awkward splittings of the natural precipitation seasons found in the West.

An objective classification of climatic regions in the Pacific and Indian oceans

We have applied a number of objective statistical techniques to define homogeneous climatic regions for the Pacific Ocean, using COADS (Woodruff et al 1987) monthly sea surface temperature (SST) for 1950-1989 as the key variable. The basic data comprised all global 4°x4° latitude/longitude boxes with enough data available to yield reliable long-term means of monthly mean SST. An R-mode principal components analysis of these data, following a technique first used by Stidd (1967), yields information about harmonics of the annual cycles of SST. We used the spatial coefficients (one for each 4-degree box and eigenvector) as input to a K-means cluster analysis to classify the gridbox SST data into 34 global regions, in which 20 comprise the Pacific and Indian oceans. Seasonal time series were then produced for each of these regions. For comparison purposes, the variance spectrum of each regional anomaly time series was calculated. Most of the significant spectral peaks occur near the biennial (2.1-2.2 years) and ENSO (~3-6 years) time scales in the tropical regions. Decadal scale fluctuations are important in the mid-latitude ocean regions.

Development of low entropy coding in a recurrent network.

In this paper we present an unsupervised neural network which exhibits competition between units via inhibitory feedback. The operation is such as to minimize reconstruction error, both for individual patterns, and over the entire training set. A key difference from networks which perform principal components analysis, or one of its variants, is the ability to converge to non-orthogonal weight values. We discuss the network's operation in relation to the twin goals of maximizing information transfer and minimizing code entropy, and show how the assignment of prior probabilities to network outputs can help to reduce entropy. We present results from two binary coding problems, and from experiments with image coding.

Deep-sea benthic footprint of the Deepwater Horizon blowout

The Deepwater Horizon (DWH) accident in the northern Gulf of Mexico occurred on April 20, 2010 at a water depth of 1525 meters, and a deep-sea plume was detected within one month. Oil contacted and persisted in parts of the bottom of the deep-sea in the Gulf of Mexico. As part of the response to the accident, monitoring cruises were deployed in fall 2010 to measure potential impacts on the two main soft-bottom benthic invertebrate groups: macrofauna and meiofauna. Sediment was collected using a multicorer so that samples for chemical, physical and biological analyses could be taken simultaneously and analyzed using multivariate methods. The footprint of the oil spill was identified by creating a new variable with principal components analysis where the first factor was indicative of the oil spill impacts and this new variable mapped in a geographic information system to identify the area of the oil spill footprint. The most severe relative reduction of faunal abundance and diversity extended to 3 km from the wellhead in all directions covering an area about 24 km2. Moderate impacts were observed up to 17 km towards the southwest and 8.5 km towards the northeast of the wellhead, covering an area 148 km2. Benthic effects were correlated to total petroleum hydrocarbon, polycyclic aromatic hydrocarbons and barium concentrations, and distance to the wellhead; but not distance to hydrocarbon seeps. Thus, benthic effects are more likely due to the oil spill, and not natural hydrocarbon seepage. Recovery rates in the deep sea are likely to be slow, on the order of decades or longer.

落叶栎树在中国的地理替代分布及其气候制约

栎属（Quercus L.）按落叶习性可自然分为落叶类型和常绿类型，我国落叶栎类共有20个种和9个变种。落叶栎是栎属中较为进化的一个类群，源于横断山区和云贵高原;除新疆外，全国各省都有落叶栎的天然分布，一些亲缘关系密切的树种之间呈现出较为明显的地理替代分布格局。本研究的目的在于：（1）应用BIOCLIM模型模拟预测落叶栎类植物的潜在分布区，分析其目前的分布格局以及下一步的发展趋势;（2）分析造成落叶栎树地理替代分布格局的主导气候因子，探讨气候因子对不同落叶栎树种地理分布格局的制约作用。 本文以16个在中国具有成片天然分布区的落叶栎树种（包括变种）为研究对象，利用已核对的标本数据以及13个栅格化环境变量图层（分辨率为1km×1km），按照分类（全国广布型、南方广布型、南方狭域型和北方狭域型）和不分类（全部16种）两种处理方式，通过BIOCLIM模型模拟得出了它们的潜在核心分布区和潜在边缘分布区。在运行模型之前，除必选的海拔高程图层外，采用了主成分分析（PCA）的方法从30个候选的气候变量图层中筛选出对相应落叶栎树种的地理分布格局有较大影响的12个图层作为输入图层。然后，本文通过比较两种处理所得模拟结果的ROC（Receiver Operator Characteristic）曲线下方面积AUC（Area Under the Curve），同时结合文献分析来推测不同落叶栎树种地理分布格局的稳定性及发展趋势。结果表明，在无人类活动干扰且种源传播不受阻碍的情况下，全国广布型和南方广布型落叶栎目前的分布格局在维持稳定的基础上有向周边地区扩展的趋势;南方狭域型和北方狭域型落叶栎的分布格局则基本保持稳定，短期内发生扩散的可能很小。 论文中计算了每个落叶栎树种所在分布范围的气候指标（共11个），以便进行下一步的研究。以蒙古栎（Q. mongolica）、辽东栎（Q. wutaishanica）与槲栎（Q. aliena）、锐齿槲栎（Q. aliena var. acuteserrata）、北京槲栎（Q. aliena var. pekingensis）这两组地理替代系列为研究对象，分别采用独立样本t检验和单因素方差分析的方法，分析了气候因子对其地理替代分布格局的主导作用。结果表明，冬季的低温、较高的气温年较差和大陆度是蒙古栎向东北替代辽东栎的主要原因;槲栎向北被北京槲栎和锐齿槲栎替代的主要原因是生长季高温和冬季高温对其分布的双重制约;除最暖月（7月）最高温外，北京槲栎的各项水热指标与另两种槲栎均存在极显著差异，对冬季低温和较大的年较差的适应可能是限制其向南分布的主要原因。 本研究最后部分的内容是对不同类型落叶栎分布区的气候参数进行的主成分分析。结果表明，生长季温度是制约落叶栎分布的最主要的气候因子;寒冷程度和冬季的低温则对其在大尺度范围的扩散有较大影响;另外，降水、年较差与大陆度对落叶栎的向北分布也起着重要的作用。

The zonation of soft-bottom sediments in Gorgan Bay (Caspian Sea) using macrobenthos as indicator of ecological health

In this study, in order to assess the ecological health status and zoning of soft bottom of Gorgan Bay, the spatial and temporal distribution of macrofauna and their relationship with environmental stress were investigated. Sediment samples were collected using a Van Veen grab at 22 sampling points, seasonally during 2012-2013. The averages (±SD) of the percentages of sand, silt, clay and TOM (Total Organic Matter) in the sediment samples were determined (44.4± 15, 53.4 ± 14, and 2.2 ±2.2 and 7.2% ± 1.6, respectively). Our results showed that mean (range) of Al, As, Cu, Fe, Ni, Pb and Zn in the sediment samples were 1.2 % (0.4-2.1), 4.8 (2.5- 10.3) ppm, 10.5 (4.4-16.9) ppm, 1 (0.4 – 1.6) % , 13.6 (6.2-21.5) ppm, 9.1 (4.7-12.9) ppm and 23.9 (3.1-39.4) ppm, respectively. In spring, both Al and Ni were higher than the guideline level. In the event that arsenic was exceeds the guidelines in summer. In this study, 14 species of macrofauna from 12 families were identified. Polychaeta with 3 species was the most dominant group in terms of abundance. The four most abundant taxa making up 85% of all specimens (Streblospio gynobranchiata, Tubificidae, Hediste versicolor and Abra segmentum). The western area were characterized by the higher species diversity (H', 1.94). So Gorgan Bay presents transitional macrobenthic assemblages that are spatially distributed along substrate gradients .The mean of Shannon index, BENTIX, BO2A, AMBI and M-AMBI in the bay was 1.3, 2.2, 0.4, 3.2 and 0.65 respectively. According to the results of these indices, ecological status of the western part of the bay assessed better than the other parts. According to the results of the nmMDS (non-metric Multidimensional Scaling), PCA (Principal Components Analysis), the map of distribution of heavy metals and the map of the ecological status , it seems Gorgan Bay is divided into two separate zones (the eastern and the western parts).M-AMBI finaly introduced reliable index for assessing the ecological status of the Bay.

Mandibular morphometric variation among Chinese cercopithecoids and the unique structure of the snub-nosed monkey (Rhinopithecus) mandible

In order to understand how mandibular structure differs among the Chinese cercopithecoids (Rhinopithecus, Trachypithecus and Macaca), particularly the uniqueness of the snub-nosed monkeys (Rhinopithecus), we analysed ten mandibular measurements by principal components analysis (PCA), and examined scaling patterns. The results provided by the PCA illustrated differences due to size among the cercopithecoids and the relationship between colobines (Trachypithecus and Rhinopithecus) and cercopithecines, in which macaques (Macaca) are included. Allometric analysis indicated that, biomechanically, there is not a marked difference between macaques and leaf-eating monkeys. This may be associated with the fact that both share some similar ecology and niches in south and southwest China. The snub-nosed monkeys exhibit a significantly more robust mandible, evident in the symphysis, corpus, condyle, and masticatory momentum arm. This supports the hypothesis, based on the study of dental structure, that Rhinopithecus is a unique group in Asian Old World monkeys (OWMs) and has developed some unique characteristics in order to adapt to the tough food available in the severe cold climate of the Plateaux of Qinghai-Tibet, Yun-Gui and Qingling in China.

MULTIVARIATE COMPARISON OF THE FORELIMB BETWEEN STUMP-TAILED AND RHESUS MACAQUES

Rhesus macaques and stump-tailed macaques are sympatric in western Yunnan (China), coexisting or occupying habitats that show little difference. This paper tests hypotheses based on theoretical expectation from the differing biomechanical demands of terrestrial and arboreal quadrupedalism in stump-tailed macaques and rhesus macaques, respectively. Individuals of these two macaque taxa were markedly separated by the first two principal components and discriminant analyses based on 18 variables of the upper limb. The rhesus macaques appear to be more adapted for arboreal quadruped habits because of elongation of the clavicle and forearm, a larger humeral head and greater midshaft sagittal diameters of the radius and ulna.

Morphometric analysis of Macaca arctoides and M-thibetana in relation to other macaque species

As a first step in reviewing the classification of the two stump-tailed macaque species, Macaca arctoides and M. thibetana, as compared with other species of the genus Macaca, 72 linear dental and cranial variables of 11 macaque species were examined by morphometric analyses. The results indicate that the two stump-tailed species are the largest of the macaques and although rather similar overall, they exhibit significant differences in the pattern of variation in most of the five skull regions as shown by Principal Components and Canonical Variate Analyses. Euclidean Distances based on Canonical Variate scores indicate that the females of M. arctoides and M. thibetana are more widely separated than eight other pairs of macaque species, and that the separations of the respective males are greater than those of three other pairs of species. These findings are consistent with FOODEN's classification of the stump-tailed macaques as two separate species (FOODEN, 1976; FOODEN et al., 1985). The present results suggest, as other researchers have proposed on the basis of external features, biochemistry and genetics, that the two stump-tailed macaque species and M. assamensis are closely related. The results also tentatively imply associations with M. fuscata and M. sylvanus but these require further study. The findings have implications for the assessment of the various Chinese Pleistocene macaque fossils.

Genetic Diversity of the Plankton Community and Its Relation to Taxonomic Composition and Environmental Factors in Lake Xiliang

Genetic diversity of the plankton community in Lake Xiliang was depicted by polymerase chain reaction-denaturing gradient gel electrophoresis (PCR-DGGE) fingerprinting. Seventy-seven bands (33 of 16S rDNA and 44 of 18S rDNA) were detected, sixty-two planktonic taxa were identified in six sample stations in November 2007. The most common taxa were Ceratium hirundinella, Bdelloidea, Keratella cochlearis, Polyarthra trigla, and copepod nauplii. Based on environmental factors, taxonomic composition, and PCR-DGGE fingerprinting, unweighted pair-group method using arithmetic averages clustering and principal components analysis were used to analyze habitat similarities. There was distinct spatial heterogeneity in Lake Xiliang, and the genetic diversity of the plankton community was closely related to taxonomic composition and environmental factors.

Mobility and profiles of polychlorinated dibenzo-p-dioxins and dibenzofurans in sediment of Ya-Er Lake, China

The sediment of Ya-Er Lake had been heavily polluted by polychlorinated dibenzo-p-dioxins and dibenzofurans (PCDD/Fs) from the former chloralkali industry. The total amounts of PCDD/Fs and I-TEQ decreased along the water flow direction and also decreased from top to bottom layers of sediment cores. Sediment of Pond 1 was dominated by PCDF, especially TCDF. In contrast, in the other four ponds, PCDD dominated in all layers and octachlorinated dibenzo-p-dioxin (OCDD) predominated in all of the homologues. When homologue profiles from sediments and water samples were compared using principal component analysis (PCA), the first two principal components represented 95.2% of the variance in the data. The first component explained 75.9% of the variance and the second one 19.3%. Two clusters were most distinct, presenting a shift in PCDD/Fs composition from PCDF to heptachlorinated dibenzo-p-dioxin (HpCDD) and OCDD in sediments and water from Pond I to Ponds 2-5. The pattern variation between Pond 1 and Ponds 2-5 in Ya-Er Lake was most likely due to the change of process in the chemical plant after the dams between the ponds were built. The results of the present study also showed that log K-oc of PCDD/Fs calculated from data of sediment and water in the field were comparable with theoretical log K-oc. The results also implied that the concentrations of PCDD/Fs in water and sediments could be predicted from each other by log K-oc. (C) 2001 Elsevier Science Ltd. All rights reserved.

Dietary-morphological relationships of fishes in Liangzi Lake, China

Species in Liangzi Lake were clustered into four trophic groups: Hemiramphus kurumeus and Hemiculter bleekeri bleekeri fed predominantly on terrestrial insects; Carassius auratus auratus and Abbottina rivularis on non-animal food; Hypseleotris swinhonis, Ctenogobius giurinus, Pseudorasbora parva and Toxabramis swinhonis on cladocerans or copepods; Culterichthys erythropterus on decapod shrimps. Gut length, mouth width, mouth height, gill raker length and gill raker spacing, varied widely among species. With the exception of three species pairs (H. swinhonis, C. glurinus; C. erythropterus, H. kurumeus; T. swinhonis, H. bleekeri bleekeri), principal components analysis of morphological variables revealed over-dispersion of species. Canonical correspondence analysis of dietary and morphological data revealed five significant dietary-morphological correlations. The first three roots explained > 85% of the total variance. The first root reflected mainly the relationship of gut length to non-animal feud, with an increase in gut length associated with an increase in non-animal food. The second root was influenced strongly by the relationship of the gill raker spacing to consumption of copepods, with an increase in gill raker spacing associated positively with copepods in the diet. The third root was influenced by the relationship of mouth gape to consumption of fish and decapod shrimps, with an increase in mouth gape associated with more fish and decapod shrimps in the diet. These significant dietary-morphological relationships supported the eco-morphological hypotheses that fish morphology influence food use, and morphological variation is important in determining ecological segregation of co-existing fish species. (C) 2001 The Fisheries Society of the British Isles.

A New Discrimination Method of Maize Seed Varieties Based on Near-Infrared Spectroscopy

A new discrimination method for the maize seed varieties based on the near-infrared spectroscopy was proposed. The reflectance spectra of maize seeds were obtained by a FT-NIR spectrometer (12 000-4 000 cm(-1)). The original spectra data were preprocessed by first derivative method. Then the principal component analysis (PCA) was used to compress the spectra data. The principal components with the cumulate reliabilities more than 80% were used to build the discrimination models. The model was established by Psi-3 neuron based on biomimetic pattern recognition (BPR). Especially, the parameter of the covering index was proposed to assist to discriminating the variety of a seed sample. The authors tested the discrimination capability of the model through four groups of experiments. There were 10, 18, 26 and 34 varieties training the discrimination models in these experiments, respectively. Additionally, another seven maize varieties and nine wheat varieties were used to test the capability of the models to reject the varieties not participating in training the models. Each group of the experiment was repeated three times by selecting different training samples at random. The correct classification rates of the models in the four-group experiments were above 91. 8%. The correct rejection rates for the varieties not participating in training the models all attained above 95%. Furthermore, the performance of the discrimination models did not change obviously when using the different training samples. The results showed that this discrimination method can not only effectively recognize the maize seed varieties, but also reject the varieties not participating in training the model. It may be practical in the discrimination of maize seed varieties.