Several studies in hydrology have reported differences in outcomes between models in which spatial autocorrelation (SAC) is accounted for and those in which SAC is not. However, the capacity to predict the magnitude of such differences is still ambiguous. In this thesis, I hypothesized that SAC, inherently possessed by a response variable, influences spatial modeling outcomes. I selected ten watersheds in the USA and analyzed them to determine whether water quality variables with higher Moran’s I values undergo greater increases in the coefficient of determination (R²) and greater decreases in residual SAC (rSAC) after spatial modeling. I compared non-spatial ordinary least squares to two spatial regression approaches, namely, spatial lag and error models. The predictors were the principal components of topographic, land cover, and soil group variables. The results revealed that water quality variables with higher inherent SAC showed more substantial increases in R² and decreases in rSAC after performing spatial regressions. In this study, I found a generally linear relationship between the spatial model outcomes (R² and rSAC) and the degree of SAC in each water quality variable. I suggest that the inherent level of SAC in response variables can predict improvements in models before spatial regression is performed. The benefits of this study go beyond modeling selection and performance, it has the potential to uncover hydrologic connectivity patterns that can serve as insights to water quality managers and policy makers.

Submitted by Luciana Ferreira (lucgeral@gmail.com) on 2015-01-27T13:40:32Z No. of bitstreams: 2 license_rdf: 23148 bytes, checksum: 9da0b6dfac957114c6a7714714b86306 (MD5) Dissertação - Paulo Henrique Ramos Guimarães - 2014.pdf: 1517515 bytes, checksum: 862883b307a6231b2a7f63d38c9f03ea (MD5) / Approved for entry into archive by Luciana Ferreira (lucgeral@gmail.com) on 2015-01-28T11:19:18Z (GMT) No. of bitstreams: 2 license_rdf: 23148 bytes, checksum: 9da0b6dfac957114c6a7714714b86306 (MD5) Dissertação - Paulo Henrique Ramos Guimarães - 2014.pdf: 1517515 bytes, checksum: 862883b307a6231b2a7f63d38c9f03ea (MD5) / Made available in DSpace on 2015-01-28T11:19:18Z (GMT). No. of bitstreams: 2 license_rdf: 23148 bytes, checksum: 9da0b6dfac957114c6a7714714b86306 (MD5) Dissertação - Paulo Henrique Ramos Guimarães - 2014.pdf: 1517515 bytes, checksum: 862883b307a6231b2a7f63d38c9f03ea (MD5) Previous issue date: 2014-02-28 / Coordenação de Aperfeiçoamento de Pessoal de Nível Superior - CAPES / Some spatial analysis methods have been applied in order to mitigate environmental variation. The objective of this study was to evaluate the efficiency of spatial statistical, through the method of Papadakis, relative to the analysis to augmented blocks Federer in the correction of environmental variation. Were evaluated 198 progenies S0:2 of rice and four witnesses for augmented blocks of Federer. Data set were taken in the grain yield (GY, kg ha- 1) and plant height (PH, cm). The data set were subjected to variance analyses and were estimated the genetic and phenotypic parameters. The different approaches (BAF and Papadakis) were compared as to their estimates of genetic and phenotypic parameters. The ranking of adjusted means in the two models analyzed was performed, and calculated the Spearman correlation. There have been improvements in the statistics that depict the experimental accuracy when the spatial analysis was, that affect the estimates of genetic and phenotypic parameters. The use of the Papadakis method yielded fewer iterations compared to BAF for the same value of . Was able to gain direct selection for the AP and PG characters when the Papadakis method was used. With the use of spatial analysis selection was less influenced by the effect of environmental variation. Finally it was found that the spatial analysis methods were effective in the removal of environmental effects highlighting the Papadakis method, indicating that it can provide improvement / Alguns métodos de análise espacial têm sido aplicados objetivando reduzir a variação ambiental. O objetivo deste trabalho foi avaliar a eficiência da análise espacial, por meio do método de Papadakis, em relação ao delineamento de blocos aumentados de Federer na correção da variação ambiental. Foram avaliadas 198 progênies S0:2 de arroz irrigado e quatro testemunhas no delineamento de blocos aumentados de Federer. Os caracteres avaliados foram: produção de grãos (PG, kg ha-1) e de altura de plantas (AP, cm). Foi efetuada análise de variância para os caracteres estudados e estimados os componentes de variância e os parâmetros genéticos e fenotípicos. As diferentes abordagens (BAF e Papadakis) foram comparadas quanto às suas estimativas de parâmetros genéticos e fenotípicos e correlação de Spearman. Houve melhorias nas estatísticas que retratam a precisão experimental quando a análise espacial foi utilizada, isto influenciou as estimativas de parâmetros genéticos e fenótipos. O uso do método de Papadakis apresentou a necessidade de uso de menor número de repetições em relação ao BAF para o mesmo valor de . Houve ganho de seleção direto para os caracteres AP e PG quando o método de Papadakis foi utilizado. Com o uso da análise espacial a seleção foi menos influenciada pelo efeito da variação ambiental. Por fim verificou-se que o método de Papadakis foi eficiente na remoção dos efeitos ambientais, indicando que o mesmo pode proporcionar melhoria na precisão experimental, o que torna o processo seletivo mais eficiente.

The diploma thesis is focused on the average monthly flows forecast in the selected hydrometric profile. Aim of this work will be evaluation of the calculated values and the interpretation of the results in understandable form. The next step will be find an appropriate connection between randomly-generated inputs in the form of random real flow series using the standard hydrological prediction models. This models are based on the principles of artificial intelligence and probability model. The result of the work will be verification of procedures and compilation of mean monthly flow stochastic forecast in selected hydrometric profile, which would be used for a reservoirs management, respectively for water systems management.

Today’s society is highly reliable on a working road infrastructure, which is because of collective efforts already built in terms of main net of roadways, and the attention is now paid to its service life primarily from a point of view of a climate change which is causing more frequent temperature extremes. This thesis sets its goal to perform basic tests for bitumen, especially ones dealing with low temperature properties, on types of bitumen usually used in out day to day world and asphalt mixtures made with those types of bitumen. The theoretical part talks about the basic definition of bitumen and studies performed on the similar issue. Practical part of the thesis is focused on performing the tests of bitumen and asphalt, which include but are not limited to, penetration test, softening point test, critical temperature detected by method by Fraasse and the bending beam rheometer and the test to set critical temperature of asphalt by using TSRST. At the end of the thesis the evaluation of results and its mutual correlation is performed.

Thesis (M. Sc. Agriculture (Animal Production)) -- University of Limpopo, 2022 / Weighing scales are typically out of reach for small-scale farmers due to expensive cost and a lack of operational expertise. However, understanding body weight and its relationship to linear body measures are critical for farmers making management decisions. Single nucleotide polymorphisms (SNPs) are significant because they influence the coding area of the DNA, leading to changes to the amino acid sequences, which might affect the animal's phenotype. The current study sought to find genetic indicators of the insulin-like growth factor 1 gene that may be exploited for breeding selection in order to improve the growth traits of Kalahari Red goats. The research was carried out at the Zuurfontein farm in Polokwane. As experimental animals, fifty (n = 50) Kalahari Red goats (8 males and 42 females) aged 2 to 3 years were used. A balance weighing scale was used to record body weight, and a measuring tape was used to capture linear body measures. Blood samples were obtained from the jugular vein once per animal using vacutainer blood collecting tubes. The deoxyribonucleic acid (DNA) was extracted and purified according to the methodology provided by Noegen's Genomic DNA isolation kit. Pearson’s correlation was used to achieve the correlation between the growth traits, Simple linear regression was performed to predict body weight from linear body measurements, Polymerase Chain Reaction-Restriction Fragment Length Polymorphism (PCR-RFLP) was utilized to discover the single nucleotide polymorphism, Chi-square test (χ2) was performed to assess the allele frequencies for Hardy-Weinberg equilibrium and General Linear Model (GLM) was performed for marker-trait association analysis. The mean square error (MSE) and coefficient of determination (R2) were exercised to choose the best regression model. Correlation results indicated a high positive significant correlation (P < 0.01) among BW and RH (r = 0.69), BL (r = 0.92), HG (r = 0.91), WH (r = 0.85) in bucks. While it does, all the linear body measurements indicated a high positive significant correlation (P < 0.01) expect SH (r = 0.41) which had a positive significant correlation (P < 0.05). Simple linear regression findings highlighted that BL had minimum MSE and highest R2 in bucks while in does HG had minimum MSE and highest R2. PCR-RFLP results indicated that two fragment patterns (two fragments and one fragment) were identified. Two genotypes were identified, KK with one fragment and KM with two fragments. The genotype frequency of KK was higher than that of KM and K allele had a higher allelic frequency than the M allele. The χ2 results showed that the Kalahari Red goats population used was not in Hardy Weinberg equilibrium (HWE) (χ2 = 0.39*). Marker-trait association findings by GLM indicated that the genotypes (KK and KM) had no association with the growth traits measured. In conclusion, correlation findings suggest that BW had a higher relationship with BL and HG in Kalahari Red goats. The regression results suggest that in bucks, an increase of 1 cm of BL might increase body weight by 1.24 kg, whereas it does, a 1 cm increase of HG might increase the body weight by 0.73 kg. The χ2 results suggest that the studied population gene and genotypic frequencies keep on changing from generation to generation and the marker-traits association results suggest that the genotypes identified had no relationship with growth traits in Kalahari Red goats. Further studies need to be conducted on single nucleotide polymorphism of IGF-1 and their relationship with growth traits using a larger sample, more growth traits and targeting more exons. / National Research Foundation (NRF)

Seleção de características é um tópico muito importante em aplicações de reconhecimento de padrões, especialmente em bioinformática, cujos problemas são geralmente tratados sobre um conjunto de dados envolvendo muitas variáveis e poucas observações. Este trabalho analisa aspectos de seleção de características no problema de identificação de redes de regulação gênica a partir de sinais de expressão gênica. Particularmente, propusemos um modelo de redes gênicas probabilísticas (PGN) que devolve uma rede construída a partir da aplicação recorrente de algoritmos de seleção de características orientados por uma função critério baseada em entropia condicional. Tal critério embute a estimação do erro por penalização de amostras raramente observadas. Resultados desse modelo aplicado a dados sintéticos e a conjuntos de dados de microarray de Plasmodium falciparum, um agente causador da malária, demonstram a validade dessa técnica, tendo sido capaz não apenas de reproduzir conhecimentos já produzidos anteriormente, como também de produzir novos resultados. Outro aspecto investigado nesta tese é o fenômeno da predição intrinsecamente multivariada (IMP), ou seja, o fato de um conjunto de características ser um ótimo caracterizador dos objetos em questão, mas qualquer de seus subconjuntos propriamente contidos não conseguirem representá-los de forma satisfatória. Neste trabalho, as condições para o surgimento desse fenômeno foram obtidas de forma analítica para conjuntos de 2 e 3 características em relação a uma variável alvo. No contexto de redes de regulação gênica, foram obtidas evidências de que genes alvo de conjuntos IMP possuem um enorme potencial para exercerem funções vitais em sistemas biológicos. O fenômeno conhecido como canalização é particularmente importante nesse contexto. Em dados de microarray de melanoma, constatamos que o gene DUSP1, conhecido por exercer função canalizadora, foi aquele que obteve o maior número de conjuntos de genes IMP, sendo que todos eles possuem lógicas de predição canalizadoras. Além disso, simulações computacionais para construção de redes com 3 ou mais genes mostram que o tamanho do território de um gene alvo pode ter um impacto positivo em seu teor de IMP com relação a seus preditores. Esta pode ser uma evidência que confirma a hipótese de que genes alvo de conjuntos IMP possuem a tendência de controlar diversas vias metabólicas cruciais para a manutenção das funções vitais de um organismo. / Feature selection is a crucial topic in pattern recognition applications, especially in bioinformatics, where problems usually involve data with a large number of variables and small number of observations. The present work addresses feature selection aspects in the problem of gene regulatory network identification from expression profiles. Particularly, we proposed a probabilistic genetic network model (PGN) that recovers a network constructed from the recurrent application of feature selection algorithms guided by a conditional entropy based criterion function. Such criterion embeds error estimation by penalization of rarely observed patterns. Results from this model applied to synthetic and real data sets obtained from Plasmodium falciparum microarrays, a malaria agent, demonstrate the validity of this technique. This method was able to not only reproduce previously produced knowledge, but also to produce other potentially relevant results. The intrinsically multivariate prediction (IMP) phenomenon has been also investigated. This phenomenon is related to the fact of a feature set being a nice predictor of the objects in study, but all of its properly contained subsets cannot predict such objects satisfactorily. In this work, the conditions for the rising of this phenomenon were analitically obtained for sets of 2 and 3 features regarding a target variable. In the gene regulatory networks context, evidences have been achieved in which target genes of IMP sets possess a great potential to execute vital functions in biological systems. The phenomenon known as canalization is particularly important in this context. In melanoma microarray data, we verified that DUSP1 gene, known by having canalization function, was the one which composed the largest number of IMP gene sets. It was also verified that all these sets have canalizing predictive logics. Moreover, computational simulations for generation of networks with 3 or more genes show that the territory size of a target gene can contribute positively to its IMP score with regard to its predictors. This could be an evidence that confirms the hypothesis stating that target genes of IMP sets are inclined to control several metabolic pathways essential to the maintenance of the vital functions of an organism.

Seleção de características é um tópico muito importante em aplicações de reconhecimento de padrões, especialmente em bioinformática, cujos problemas são geralmente tratados sobre um conjunto de dados envolvendo muitas variáveis e poucas observações. Este trabalho analisa aspectos de seleção de características no problema de identificação de redes de regulação gênica a partir de sinais de expressão gênica. Particularmente, propusemos um modelo de redes gênicas probabilísticas (PGN) que devolve uma rede construída a partir da aplicação recorrente de algoritmos de seleção de características orientados por uma função critério baseada em entropia condicional. Tal critério embute a estimação do erro por penalização de amostras raramente observadas. Resultados desse modelo aplicado a dados sintéticos e a conjuntos de dados de microarray de Plasmodium falciparum, um agente causador da malária, demonstram a validade dessa técnica, tendo sido capaz não apenas de reproduzir conhecimentos já produzidos anteriormente, como também de produzir novos resultados. Outro aspecto investigado nesta tese é o fenômeno da predição intrinsecamente multivariada (IMP), ou seja, o fato de um conjunto de características ser um ótimo caracterizador dos objetos em questão, mas qualquer de seus subconjuntos propriamente contidos não conseguirem representá-los de forma satisfatória. Neste trabalho, as condições para o surgimento desse fenômeno foram obtidas de forma analítica para conjuntos de 2 e 3 características em relação a uma variável alvo. No contexto de redes de regulação gênica, foram obtidas evidências de que genes alvo de conjuntos IMP possuem um enorme potencial para exercerem funções vitais em sistemas biológicos. O fenômeno conhecido como canalização é particularmente importante nesse contexto. Em dados de microarray de melanoma, constatamos que o gene DUSP1, conhecido por exercer função canalizadora, foi aquele que obteve o maior número de conjuntos de genes IMP, sendo que todos eles possuem lógicas de predição canalizadoras. Além disso, simulações computacionais para construção de redes com 3 ou mais genes mostram que o tamanho do território de um gene alvo pode ter um impacto positivo em seu teor de IMP com relação a seus preditores. Esta pode ser uma evidência que confirma a hipótese de que genes alvo de conjuntos IMP possuem a tendência de controlar diversas vias metabólicas cruciais para a manutenção das funções vitais de um organismo. / Feature selection is a crucial topic in pattern recognition applications, especially in bioinformatics, where problems usually involve data with a large number of variables and small number of observations. The present work addresses feature selection aspects in the problem of gene regulatory network identification from expression profiles. Particularly, we proposed a probabilistic genetic network model (PGN) that recovers a network constructed from the recurrent application of feature selection algorithms guided by a conditional entropy based criterion function. Such criterion embeds error estimation by penalization of rarely observed patterns. Results from this model applied to synthetic and real data sets obtained from Plasmodium falciparum microarrays, a malaria agent, demonstrate the validity of this technique. This method was able to not only reproduce previously produced knowledge, but also to produce other potentially relevant results. The intrinsically multivariate prediction (IMP) phenomenon has been also investigated. This phenomenon is related to the fact of a feature set being a nice predictor of the objects in study, but all of its properly contained subsets cannot predict such objects satisfactorily. In this work, the conditions for the rising of this phenomenon were analitically obtained for sets of 2 and 3 features regarding a target variable. In the gene regulatory networks context, evidences have been achieved in which target genes of IMP sets possess a great potential to execute vital functions in biological systems. The phenomenon known as canalization is particularly important in this context. In melanoma microarray data, we verified that DUSP1 gene, known by having canalization function, was the one which composed the largest number of IMP gene sets. It was also verified that all these sets have canalizing predictive logics. Moreover, computational simulations for generation of networks with 3 or more genes show that the territory size of a target gene can contribute positively to its IMP score with regard to its predictors. This could be an evidence that confirms the hypothesis stating that target genes of IMP sets are inclined to control several metabolic pathways essential to the maintenance of the vital functions of an organism.

The diploma thesis is focused on the long term prediction of mean monthly flows in hydrometric profile for purposes of reservoir control optimization and optimization of reservoir systems. Discharges were predicted using by artificial neural network method. Predicted flows were statistically evaluated by relevant coefficients and then compared with the measured flows for given river hydrometric profiles.

The issue of the relationship between water discharge and the suspended sediment loads is a globally highly addressed topic. Knowing the suspended sediment loads in the streams avoids problems with over-filling of water cannons and thus prevents insufficient capacity of water reservoirs. This thesis is partly a follow-up to the bachelor thesis, which extends and introduces new procedures. Neural networks, more specifically multilayer perceptron neural networks, are used to analyse the relationship between water discharge and suspended sediment loads. The results of the networks are then processed in Excel into graphs and evaluated using the coefficient of determination, Nash-Sutcliffe coefficient and RMSE coefficient. The practical application is solved on two profiles - the profile Podhradí nad Dyjí and the profile Židlochovice. Each profile is examined in a different period.

This work solves creation of calibration relations to determine cube compressive strength, dynamic and static elastic modulus of alkali-activated concrete by non-destructive methods. Alkali-activated concrete is spoken of as a new material used in civil engineering. It shows different properties than normal concrete based on Portland cement. That's why the modification of common calibration relation seems necessary. Fresh concrete was made in the concrete plan ŽPSV a.s., Uherský Ostroh in three mixtures and always in the number of 18 cubes and 3 prisms. The samples were tested by impact hammer Schmidt type L, type N, SilverSchmidt PC-N and by ultrasound in 6 time periods of three specimens. After that, the cube compressive strength was determined. Status of static elastic modulus was determined in a time period of 28 days. The results are calibration relations to determine the progress of compressive strength and modulus of elasticity for each method and their combination.