Neste trabalho foi analisada a influência de um evento sobre o mercado de ações brasileiro a partir das redes, e suas árvores geradoras mínimas, obtidas de medidas de dependência baseadas nas correlações de Pearson, de Spearman e de Kendall. O evento considerado foi a notícia da noite de 17 de maio de 2017 em que o dono da empresa brasileira JBS, Joesley Batista, gravou o então Presidente da República Michel Temer autorizando a compra do silêncio de um Deputado Federal. O dia seguinte a notícia, 18 de maio de 2017, foi definido como o dia do evento. Foram coletados dados de alta frequência de 58 ações do Ibovespa no período de 11 a 25 de maio de 2017. As alterações nas redes das ações do mercado foram analisadas comparando-se o período anterior e posterior ao evento em duas escalas de tempo: (1) Redes diárias: cinco pregões antes do evento, o dia do evento e, cinco pregões depois do evento, com cotações a cada 15 minutos; (2) Agrupadas em antes e depois: agrupando os dados dos 5 dias antes e dos 5 dias depois do evento. O estudo das redes diárias indicou mudança de tendência nas suas propriedades no decorrer do período que contém o evento, com cotações a cada 15 minutos. Isto sugeriu que análise do efeito médio contido nos dados agrupados antes de depois do evento poderiam tornar mais evidente as mudanças na estrutura de rede das ações. As redes antes e depois do evento apresentaram mudanças significativas nas suas métricas que ficaram mais evidenciadas nas árvores geradoras mínimas. As redes geradas pelas correlações de Kendall e Spearman apresentaram um número maior de agrupamentos antes e depois do evento e, após o evento, as árvores geradoras mínimas apresentaram uma redução do número de agrupamentos de ações para todos os tipos de correlação. As distribuições de grau ponderado após o evento indicam uma probabilidade maior de vértices com graus distante da média. As métricas das árvores geradoras mínimas por correlação de Spearman sofreram a maior variação, seguidas pelas de Kendall e Pearson, e também, indicaram que as redes após o evento ficaram mais robustas, ou seja, mais rígidas. A maior robustez das redes após o evento indica maior conectividade do mercado, tornando-o, como um todo, mais suscetível ao impacto de novos acontecimentos. / In this work the influence of an event on the Brazilian stock market was analyzed from networks and its minimum spanning trees obtained from measures of dependence based on the Pearson, Spearman, and Kendall\'s correlations. The event considered was the news in the evening of May 17, 2017 in which the owner of the Brazilian company JBS, Joesley Batista, recorded the Brazilian President Michel Temer authorizing the purchase of the silence of a congress member. The day just after the news, May 18, 2017, was defined as the event day. High-frequency data from 58 Ibovespa shares were collected from 11 to 25 May 2017. Changes in the stocks networks were analyzed comparing the period before and after the event in two time scales: (1) Daily networks: five trade sections before the event, the day of the event and, five trade sections after the event, with price every 15 minutes; (2) Grouped before and after do evento: grouping data from 5 days before and 5 days after event. The study of the daily networks indicated a change of trend in their properties during the period that contains the event, with quotations every 15 minutes. The study of daily networks indicated a change of trend in their properties during the period containing the event. This suggested that analysis of the mean effect of grouped data before and after the event could highlight the changes in the network structure. The networks before and after the event showed significant changes in their metrics, which became more evident from the minimum spanning trees. After the event, the minimum spanning trees for grouped data got a smaller number of clusters in the networks for all kind of correlations. The networks generated by Kendall and Spearman correlations presented a larger number of clusters before and after the event. The weighted degree distributions after the event suggest a power law decay tail for all the correlations considered and indicates a higher probability of vertices with weighted degrees far away from the mean weighted degree. The minimum spanning tree metrics generated by Spearman correlation suffered the greatest variation, followed by those of Kendall and Pearson; and their values indicates that after the event the networks became more robust, that is, more rigid. The increase in the networks robustness after the event indicates a higher market connectivity, making it as a whole, more susceptible to the impact of new events.

This thesis develops an optimal interpolation method that takes daily precipitation values collected from weather stations and produces precipitation estimates on a grid. The method, called Hybrid 2.0, combines EOF-based linear interpolation with the nearest-station method. Gridded monthly precipitation is first obtained via EOF, then distributed among days via nearest station. Hybrid 2.0 builds on an earlier method, called Hybrid 1.0, that applies an inverse-distance weighting method to obtain gridded monthly values. Hybrid 2.0 uses these monthly Hybrid 1.0 values as inputs when constructing EOF functions. The data used in this thesis were obtained from the Meteorological Service of Canada. Few weather stations were located in the northern and mountain regions of Alberta prior to 1950. As a result, the Hybrid 1.0 gridded results underestimate precipitation in these regions for that period. The main contribution of Hybrid 2.0 is a substantial reduction in this bias, obtained by implicitly taking topographic elevation into account. Bias reduction is achieved by extracting EOFs from Hybrid 1.0 output for 1951-2002, when many more stations were present in the northern and mountain regions. Hybrid 2.0 is shown to be more accurate in interpolating both monthly and daily precipitation in Alberta, when compared with Hybrid 1.0 and other methods. The thesis also provides detailed analyses of precipitation trends and droughts using the gridded Hybrid 2.0 daily values. Optimality of the selected EOF modes and sensitivity to data error in the EOF-based linear reconstruction are also discussed in this thesis. Agricultural uses of historical climate data have become extremely important. Applications include: enabling prompt, optimal decisions on market prices and disaster aid, designing future agricultural practices such as adaptation to climate and technology changes, and managing risks for agricultural producers and governments in areas such as drought monitoring. Many applications require a reliable interpolation technique to accurately reconstruct daily climate estimates onto grids of various resolutions. The gridded Hybrid 2.0 daily precipitation values produced by this thesis satisfy this requirement and can be used as inputs for many agricultural applications. / Applied Mathematics

Les travaux présentés portent sur les retombées atmosphériques en zone rurale et s'inscrivent dans le cadre du programme français de Mesure des Retombées Atmosphériques (MERA). Les polluants mesurés dans les stations du dispositif sont en rapport avec les problèmes des pluies acides et de la pollution photochimique. Deux tests statistiques pour détecter et estimer les tendances au sein de séries chronologiques ont été utilisés. La procédure est basée sur le test non paramétrique de Mann-Kendall pour déterminer la tendance et sur la méthode de Sen pour en estimer la magnitude. Ces tests ont été appliqués aux 5.000.000 de données MERA, annuelles, saisonnières et mensuelles sur la période 1990-2003, puis, aux émissions nationales et européennes des principaux polluants précurseurs. L'acidité moyenne des pluies, après avoir baissée au début des années 90, augmente légèrement depuis 1996 alors que les émissions de composés acidifiants diminuent. Cette observation semble être corrélée à la diminution en cations basiques, NH4+ et aux aérosols acides. Les concentrations en composés soufrés (gaz et aérosols) ont fortement diminué depuis le début des années 90 associées aux fortes réductions d'émission. Pour l'O3, une augmentation des teneurs est observée entre 1995 et 2003, associée à une diminution des émissions de précurseurs. Plusieurs facteurs peuvent expliquer cette augmentation : les changements des émissions de précurseurs, les échanges strato-troposphériques, le transport intercontinental, les changements climatiques, le rapport COV/NOx, les émissions des composés bio-géogéniques. Prochainement, des prévisions subjectives par extrapolations linéaires pourront être effectuées avec un intervalle de confiance à 99%.

The purpose of the study was to examine the temporal trends of three monthly variables: stream runoff, rainfall and air temperature and to find out if any correlation exists between rainfall and stream runoff in the Blue Ridge and Piedmont provinces of the southeast United States. Trend significance was determined using the non-parametric Mann-Kendall test on a monthly and annual basis. GIS analysis was used to find and integrate the urban and non-urban stream gauging, rainfall and temperature stations in the study area. The Mann-Kendall test showed a statistically insignificant temporal trend for all three variables. The correlation of 0.4 was observed for runoff and rainfall, which showed that these two parameters are moderately correlated.

No description available.

Analysing the repeated debates within American conservatism over the place of Abraham Lincoln within American history.

Submitted by Automa??o e Estat?stica (sst@bczm.ufrn.br) on 2017-03-07T18:19:08Z No. of bitstreams: 1 CaioVasconcelosPinheiroDaCosta_DISSERT.pdf: 3451357 bytes, checksum: e54c55afe01cf7feb106c7ed5857980e (MD5) / Approved for entry into archive by Arlan Eloi Leite Silva (eloihistoriador@yahoo.com.br) on 2017-03-07T18:44:49Z (GMT) No. of bitstreams: 1 CaioVasconcelosPinheiroDaCosta_DISSERT.pdf: 3451357 bytes, checksum: e54c55afe01cf7feb106c7ed5857980e (MD5) / Made available in DSpace on 2017-03-07T18:44:49Z (GMT). No. of bitstreams: 1 CaioVasconcelosPinheiroDaCosta_DISSERT.pdf: 3451357 bytes, checksum: e54c55afe01cf7feb106c7ed5857980e (MD5) Previous issue date: 2014-12-15 / Este trabalho realizou um estudo a partir de um conjunto de dados meteorol?gicos coletados na cidade de Natal/RN e adjac?ncias, identificando evid?ncias de altera??es no seu clima urbano no per?odo de 1970 a 2010. As vari?veis utilizadas foram: temperatura m?dia, temperatura m?nima e umidade relativa. Os dados foram obtidos a partir das esta??es meteorol?gicas localizada no Campus Central da Universidade Federal do Rio Grande do Norte (UFRN), que faz parte da rede de observa??es do Instituto Nacional de Meteorologia (INMET), e do Centro de Lan?amento da Barreira do Inferno (CLBI), localizadas dentro de uma ?rea urbana e de uma ?rea de prote??o permanente (APP), respectivamente. Foi realizada uma an?lise sobre a varia??o sazonal das vari?veis meteorol?gicas.Al?m disso, foram avaliadas as tend?nciasnas s?ries temporais,utilizando para isso o template MAKESENS, que aplica o teste de Mann-Kendall e o m?todo de estimativa de inclina??es de Sen sobre o conjunto de dados. Para a temperatura m?dia, na UFRN/INMET, houve tend?ncia de crescimento nos meses de maio, julho e setembro, nos n?veis de signific?ncia de 10%, 5% e 10%, respectivamente. No CLBI, s? houve tend?ncia de crescimento da temperatura m?dia no m?s de fevereiro, no n?vel de signific?ncia de 10%. Em rela??o ? temperatura m?nima, houve tend?ncia de crescimento com signific?ncia estat?stica em quatro s?ries (janeiro, novembro, dezembro e m?dia anual) na UFRN/INMET, nos n?veis de 10%, 10%, 5% e 5%, respectivamente, e apenas em uma no CLBI, no m?s de setembro, no n?vel de signific?ncia de 10%. Em rela??o ? umidade relativa, os resultados foram extremamente discrepantes. Para a UFRN/INMET, houve tend?ncia de decrescimento com signific?ncia estat?stica em 7 das 13 s?ries, sendo elas janeiro, mar?o, abril, maio, outubro, novembro e m?dia anual, nos n?veis de 5%, 1%, 0,1%, 10%, 5%, 5% e 0,1%, respectivamente, enquanto que no CLBI houve uma tend?ncia predominante de crescimento, com signific?ncia de 1% em junho e de 5% em agosto.Essas tend?ncias s?o mais evidentes na ?rea urbana em rela??o ?ssuas adjac?ncias, evidenciando algumas caracter?sticas t?picas das Ilhas de Calor Urbanas. / This work conducted a study from a set of meteorological data collected in the city of Natal / RN and surroundings, identifying evidence of changes in its urban climate during the period from 1970 to 2010. The variables used were: average temperature, minimum temperature and relative humidity. Data were obtained from the meteorological stations located in the Central Campus of the Federal University of Rio Grande do Norte (UFRN) that is part of the network of observations from the National Institute of Meteorology (INMET) and from Barreira do Inferno Launch Center (CLBI), located inside an urban area and inside a permanent protection area (APP), respectively. An analysis of the seasonal variation of the meteorological variables was performed. In addition, the trends were evaluated in time series, using for this the template MAKESENS, that applies the Mann-Kendall test and Sen's slopes estimates with the data set. For the average temperature in UFRN/INMET, there was growth trend in May, July and September, at the significance levels of 10%, 5% and 10%, respectively. In CLBI, there was only upward trend in average temperature in February, at the 10% significance level. Regarding the minimum temperature, there was growth trend with statistical significance in four series (January, November, December and annual average) in UFRN/INMET, at the levels of 10%, 10%, 5% and 5%, respectively, and just one in CLBI, in September, at the 10% significance level. In relation to the relative humidity, the results were extremely disparate. To UFRN/INMET, there was decreasing trend with statistically significance in 7 of the 13 series, these being January, March, April, May, October, November and annual average, at the levels of 5%, 1%, 0.1%, 10%, 5%, 5% and 0.1%, respectively, while in CLBI there was a prevailing trend of growth, with a significance of 1% in June and 5% in August.These trends are more pronounced in urban areas compared to surrounding area, showing some typical characteristics of Urban Heat Islands.

The objective of this study is to investigate land-use changes and water quality trends within the headwaters of the Alafia River watershed. Water quality data were obtained from the Environmental Protection Commission of Hillsborough County (EPCHC). Eleven water quality parameters selected for analysis included: temperature (˚C), dissolved oxygen (DO), percent saturation of DO, conductivity, pH, total phosphorous (TP), total nitrogen (TN), ammonium, chlorophyll-a (uncorrected), fecal coliforms, and enterococci. ArcMap® & SWFWMD data were used to map EPCHC sampling stations, calculate contributing watershed size, and determine land-use changes over the course of the sampling period; 17 stations were chosen for this study. The annual average for each of the water quality parameters was calculated along with a Mann-Kendall Trend Analysis in order to determine if any of the observed trends were statistically significant. A non-parametric Kendall’s tau-b correlation and stepwise multiple linear regression tests were conducted in SPSS to determine if any statistically significant relationships between water quality data, land-use and basin size exist. The land-use results showed every basin consisted of some percentage of Low Density Residential, Cropland & Pastureland, Reservoirs, and Streams & Lake Swamps. In addition, no basin comprised of more than 20% wetlands and often it appears urbanization was at the sacrifice of agricultural lands, as opposed to wetlands. The trends in water quality showed eight of the 17 basins had at least one statistically significant trend. Analysis of the data used for this study has shown instances where water quality measurements were in violation of state standards. Changes in water quality can be statistically related to changes in land-use and basin size as both the correlation and the regression showed consistent relationships between several LULC types and water quality parameters: increases in Commercial & Services causes increased nutrients (TP and TN); Cropland & Pastureland causes decreased DO and DO% Saturation; increases in Tree Crops causes a decrease in pH; increasing Other Open Lands Rural causes a decrease in temperature; and increases in Shrub & Brushland cause decreases in conductivity and pH. As these relationships are based on the results from both analyses, it would seem that these relationships are the most reliable, and are key results of the study. These key relationships might be areas that future water resource managers may want to focus on in order to more efficiently improve or regulate water quality within headwater streams.

Neste trabalho foi analisada a influência de um evento sobre o mercado de ações brasileiro a partir das redes, e suas árvores geradoras mínimas, obtidas de medidas de dependência baseadas nas correlações de Pearson, de Spearman e de Kendall. O evento considerado foi a notícia da noite de 17 de maio de 2017 em que o dono da empresa brasileira JBS, Joesley Batista, gravou o então Presidente da República Michel Temer autorizando a compra do silêncio de um Deputado Federal. O dia seguinte a notícia, 18 de maio de 2017, foi definido como o dia do evento. Foram coletados dados de alta frequência de 58 ações do Ibovespa no período de 11 a 25 de maio de 2017. As alterações nas redes das ações do mercado foram analisadas comparando-se o período anterior e posterior ao evento em duas escalas de tempo: (1) Redes diárias: cinco pregões antes do evento, o dia do evento e, cinco pregões depois do evento, com cotações a cada 15 minutos; (2) Agrupadas em antes e depois: agrupando os dados dos 5 dias antes e dos 5 dias depois do evento. O estudo das redes diárias indicou mudança de tendência nas suas propriedades no decorrer do período que contém o evento, com cotações a cada 15 minutos. Isto sugeriu que análise do efeito médio contido nos dados agrupados antes de depois do evento poderiam tornar mais evidente as mudanças na estrutura de rede das ações. As redes antes e depois do evento apresentaram mudanças significativas nas suas métricas que ficaram mais evidenciadas nas árvores geradoras mínimas. As redes geradas pelas correlações de Kendall e Spearman apresentaram um número maior de agrupamentos antes e depois do evento e, após o evento, as árvores geradoras mínimas apresentaram uma redução do número de agrupamentos de ações para todos os tipos de correlação. As distribuições de grau ponderado após o evento indicam uma probabilidade maior de vértices com graus distante da média. As métricas das árvores geradoras mínimas por correlação de Spearman sofreram a maior variação, seguidas pelas de Kendall e Pearson, e também, indicaram que as redes após o evento ficaram mais robustas, ou seja, mais rígidas. A maior robustez das redes após o evento indica maior conectividade do mercado, tornando-o, como um todo, mais suscetível ao impacto de novos acontecimentos. / In this work the influence of an event on the Brazilian stock market was analyzed from networks and its minimum spanning trees obtained from measures of dependence based on the Pearson, Spearman, and Kendall\'s correlations. The event considered was the news in the evening of May 17, 2017 in which the owner of the Brazilian company JBS, Joesley Batista, recorded the Brazilian President Michel Temer authorizing the purchase of the silence of a congress member. The day just after the news, May 18, 2017, was defined as the event day. High-frequency data from 58 Ibovespa shares were collected from 11 to 25 May 2017. Changes in the stocks networks were analyzed comparing the period before and after the event in two time scales: (1) Daily networks: five trade sections before the event, the day of the event and, five trade sections after the event, with price every 15 minutes; (2) Grouped before and after do evento: grouping data from 5 days before and 5 days after event. The study of the daily networks indicated a change of trend in their properties during the period that contains the event, with quotations every 15 minutes. The study of daily networks indicated a change of trend in their properties during the period containing the event. This suggested that analysis of the mean effect of grouped data before and after the event could highlight the changes in the network structure. The networks before and after the event showed significant changes in their metrics, which became more evident from the minimum spanning trees. After the event, the minimum spanning trees for grouped data got a smaller number of clusters in the networks for all kind of correlations. The networks generated by Kendall and Spearman correlations presented a larger number of clusters before and after the event. The weighted degree distributions after the event suggest a power law decay tail for all the correlations considered and indicates a higher probability of vertices with weighted degrees far away from the mean weighted degree. The minimum spanning tree metrics generated by Spearman correlation suffered the greatest variation, followed by those of Kendall and Pearson; and their values indicates that after the event the networks became more robust, that is, more rigid. The increase in the networks robustness after the event indicates a higher market connectivity, making it as a whole, more susceptible to the impact of new events.

No description available.