<p> Some cumulative mass-yield ratios for thermal to epi-thermal neutron fissions of 239Pu have been measured by nondestructive Ge(Li) spectrometric and radiochemical methods. The mass-yield ratios of 85mKr, 91Sr- 91mY, 92Sr, 97Nb-97Zr, 99mTc, 103Ru, 105Ru, 131I, 132Te-132I, 133I, 135I-135Xe, 140Ba-140La, 143Ce and 147Nd for both thermal to epi-Cd and thermal to epi-Sm fissions did not show any significant fluctuations. The yields of 72Zn and 166Dy-166Ho in epi-Sm fission were found to be 30±2% lower than in the fission caused by thermal neutrons. Similarly the yields of 115Cd and 112Pd were found to be lower by 46±2% and 24±3% respectively. The 77 mass chain, measured as both 77Ge and 77As, showed only a very slight, if any, decrease for epi-Cd and epi-Sm fissions as compared with thermal neutron fissions.</p> <p> The results are consistent with the two-mode-of-fission hypothesis. An attempt has also been made to correlate the observations with the effect of the spin states of the fissioning nucleus at the saddle point.</p> / Thesis / Doctor of Philosophy (PhD)

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No description available.

A system of equations was developed and incorporated into the PTAEDA2 loblolly pine stand simulator to provide growth projections from time of planting. Annual height growth is predicted using a two-parameter Weibull function, where distribution parameters are estimated from equations that utilize site index and age as predictor variables. Allometric equations are employed to estimate tree diameter and height-to-crown attributes. First year after planting mortality estimates are based on physiographic region and drainage class, with adjustments for bedding or discing site preparation treatments. Thereafter, a simple mortality function is used. The onset of competition is defined through a point density measure, which was conditioned to correspond with inflection points of basal area growth curves from observed data. Early silvicultural treatment response functions were also developed. These equations modify growth for shearing and piling, discing, and bedding site preparation methods, fertilization with phosphorous, nitrogen, and/or potassium, and 1-year or 2-year herbaceous weed control treatments. Differential responses due to drainage class and physiographic region are included in the response functions where necessary. Equations that account for interactions between certain treatments are used to adjust response levels where treatments have similar effects site conditions. Analyses of pre-competitive growth projections where no treatments are specified reveal that a small amount of over-prediction is present when compared with observed data. Predicted values in the post-competitive growth phase confirm that the addition of the pre-competitive growth system did not significantly affect the predictive behavior of the PTAEDA2 model. The simulated growth responses attributed to early silvicultural treatments are consistent with response levels reported in other studies. / Ph. D.

Accurately predicting sediment delivery has been a long-standing problem in the field of water resource management. Many different watershed equations and models have been developed such as the Universal Soil Loss Equation (USLE), the Geo-spatial interface for the Water Erosion Prediction Program (GeoWEPP) and many more, however, these models have not always been able to reliably predict in-stream sediment loads. In this study, two scales, watershed and site level, are used to understand where sediment transported in-stream is being produced. At the watershed scale, USLE was used to estimate sediment yield and then different factors such as connectivity topographic indices were applied as discount factors in an attempt to improve these estimates. The different parameters were then compared to turbidity to determine the level of accuracy of each method. It was found that USLE is not able to predict in-stream turbidity levels in the study area watersheds in Virginia and North Carolina. An implicit assumption of USLE is that runoff is produced on steeper slopes and that sediment production occurs on these hillslopes. However, it was found that flatter-sloped areas were highly correlated with in-stream turbidity. It was also found that in-channel and site-specific parameters such as bank height/slope and level of confinement at higher flows were more accurate predictors of in-stream sediment levels. Overall, turbidity and in-stream sediment levels are not well predicted by models that employ USLE. The distribution of runoff source areas, and channel/bank properties appear to be good predictors of sediment production at the watershed scale. These results indicate that sediment production and transport, as conceptualized by common models and equations, often associate sediment source areas with geomorphic and hydrologic processes in ways that are not consistent with the results of this study. Our results show that sediment is most likely being sourced from the channels and in stream areas. / Master of Science / Predicting how sediment moves through a watershed has been a long-standing problem in the field of water resource management. There are many equations and models that have been developed to calculated the amount of sediment that exits a watershed; such as the Universal Soil Loss Equation (USLE), the Geo-spatial interface for the Water Erosion Prediction Program (GeoWEPP) and many more. However, these models have not always been reliable or accurate in their predictions. In this study, two scales, watershed and site level, are used to understand where sediment transported within streams is being produced. At the watershed scale, USLE was used to estimate sediment leaving a system and then different factors, with different approaches to the understanding of sediment movement, were applied as discount factors in an attempt to improve these estimates. The different values that were calculated were then compared to turbidity to determine the level of accuracy of each parameter. It was found that USLE is not able to predict in-stream turbidity levels in the study area watersheds in Virginia and North Carolina. An assumption of USLE is that runoff is produced on steeper slopes and that sediment erosion occurs on these steeper sloped areas. However, it was found that flatter-sloped areas were highly correlated with turbidity. It was also found that in-channel and site-specific parameters such as bank height/slope and the level of confinement at higher flows were more accurate predictors of turbidity. Overall, USLE and models that used USLE were not able to predict turbidity. The distribution of runoff source areas and channel/bank properties appear to be good predictors of turbidity at the watershed scale. These results indicate that sediment movement, as conceptualized by common models and equations, often associate sediment source areas with watershed level morphology and hydrology in ways that are not consistent with the results of this study. Our results show that sediment is most likely being produced from the channels and in stream areas.

Sendo o cereal mais produzido no mundo e em larga expansão, os sistemas de produção de milho são altamente complexos e sua produção é diretamente dependente de fatores ligados tanto ao clima local quanto ao manejo da cultura. Para auxiliar na determinação tanto dos patamares produtivos de milho quanto quantificar o impacto causado por condições adversas tanto de clima quanto de manejo, pode-se lançar mão do uso de modelos de simulação de culturas. Para que os modelos possam ser devidamente aplicados, uma base solida de dados meteorológicos deve ser consistida, a fim de alimentar esses modelos. Nesse sentido, o presente estudo teve como objetivos: i) avaliar dois sistemas de obtenção de dados meteorológicos, o NASA-POWER e o DailyGridded, comparando-os com dados medidos em estações de solo; ii) calibrar, testar e combinar os modelos de simulação MZA-FAO, CSM DSSAT Ceres-Maize e APSIM-Maize, a fim de estimar as produtividades potenciais e atingíveis do milho no Brasil; iii) avaliar o impacto na produtividade causado pelo posicionamento da semeadura em diferentes tipos de solo; iv) desenvolver e avaliar um sistema de previsão de safra baseado em modelos de simulação; v) mapear as produtividades potencial, atingível e real do milho no Brasil, identificando regiões mais aptas ao cultivo e vi) determinar e mapear as quebras de produtividade, ou yield gaps (YG) da cultura do milho no Brasil. Comparando os dados climáticos dos sistemas em ponto de grade com os dados de estações meteorológicas de superfície, na escala diária, encontrou-se boa correlação entre as variáveis meteorológicas, inclusive para a chuva, com R2 da ordem de 0,58 e índice d = 0,85. O desempenho da combinação dos modelos ao final da calibração e ajuste se mostrou superior ao desempenho dos modelos individuais, com erros absolutos médios relativamente baixos (EAM = 627 kg ha-1) e com boa precisão (R2 = 0,62) e ótima acurácia (d = 1,00). Durante a avaliação da influência das épocas de semeadura e do tipo de solo no patamar produtivo do milho, observou-se que esse varia de acordo com a região estudada e apresenta seus valores máximos e com menores riscos à produção quando a semeaduras coincidem com o início do período de chuvas do local. O sistema de previsão de safra, baseado em modelos de simulação de cultura teve seu melhor desempenho simulando produtividades de milho semeados no início da safra e no final da safrinha, sendo capaz de prever de forma satisfatória a produtividade com até 25 dias antes da colheita. Para o estudo dos YGs, 152 locais foram avaliados e suas produtividades potenciais e atingíveis foram comparadas às produtividades reais, obtidas junto ao IBGE. Os maiores YGs referentes ao déficit hídrico se deram em solos arenosos e durante os meses de outono e inverno, usualmente mais secos na maioria das regiões brasileiras, atingindo valores de quebra superiores a 12000 kg ha-1. Quanto ao YG causado pelo manejo, esse foi maior nas regiões menos tecnificadas, como na região Norte e na Nordeste, apresentando valores superiores a 6000 kg ha-1. Já as regiões mais tecnificadas e tradicionais na produção de milho, como a região Sul e a Centro-Oeste, os YGs referentes ao manejo foram inferiores a 3500 kg ha-1 na maioria dos casos. / Maize is the most important cereal cultivated in the world, being its production system very complex and its productivity directly affected by climatic and crop management factors. In order to quantify the impacts caused by water and crop management deficits on maize yield, the use of crop simulation models is very useful. For properly apply these models, a solid basis of meteorological data is required. In this sense, the present study had as objectives: i) to evaluate two meteorological gridded data, NASA-POWER and DailyGridded, by comparing them with measured data from surface stations; (ii) to calibrate, evaluate and combine the MZA-FAO, CSM DSSAT Ceres-Maize and APSIM-Maize simulation models to estimate the maize potential and attainable yields in Brazil; iii) to evaluate the impact caused by the different sowing dates and soil types on maize yield; iv) to develop and evaluate a crop forecasting system based on crop simulation models and climatological data; v) to map the potential and the attainable maize yields in Brazil, identifying the most suitable regions for cultivation, and vi) to determine and map maize yields and yield gaps (YG) in Brazil. Comparing the gridded climatic data with observed ones, on a daily basis, a good agreement was found for all weather variables, including rainfall, with R2 = 0.58 and d = 0,85. The performances of the combination of the models at the end of the calibration and evaluation phases were better than those obtained with the individual models, with relatively low mean absolute error (EAM = 627 kg ha-1) and with good precision (R2 = 0.62) and accuracy (d = 1.00). During the evaluation of different sowing dates and soil types on maize yield, it was observed that this variable depends on the region and presents the maximum values and, consequently, the minimum risk during the sowings in the beginning of the rainy season of each site. The crop forecasting system, based on crop simulation models, had its best performance for simulating maize yields when the sowings were performed at the beginning of the main season and at the end of the second season, when it was able to predict yield satisfactorily 25 days before harvest. For the YG analysis, 152 sites were assessed and their potential and attainable yields were compared to the actual yields reported by IBGE. The highest YGs caused by water deficit occurred for sandy soils and during the autumn and winter months, usually dry in most of Brazilian regions, reaching values above 12000 kg ha-1. For YG caused by crop management, the values were higher in the less technified regions, such as in the North and Northeast regions, with values above 6000 kg ha-1. In contrast, more traditional maize production regions, such as the South and Center-West, presented YG caused by crop management, lower than 3500 kg ha-1 in most cases.

Dentre as espécies florestais, o Eucalyptus é o gênero florestal mais plantado no Brasil, com aproximadamente 7,8 milhões de hectares, tendo grande importância econômica para o país. Desta maneira, é importante um melhor conhecimento e quantificação dos fatores que condicionam e reduzem o crescimento e a produtividade das florestas. Assim, este estudo teve por objetivos: i) adaptar, calibrar e avaliar o Modelo da Zona Agroecológica (MZA-FAO) para a estimação do crescimento e da produtividade de oito clones de eucalipto em diferentes regiões brasileiras; ii) determinar a magnitude e as principais causas das quebras de produtividade (yield gaps) da cultura do eucalipto em diferentes regiões produtoras do estado de Minas Gerais; e iii) avaliar a influência de eventos de El Niño, La Niña e Neutros na produtividade de eucaliptos em diferentes localidades produtoras do Brasil. Foram adaptados e calibrados os coeficientes do MZA-FAO, como a correção para o índice de colheita (Cc), o coeficiente de sensibilidade ao déficit hídrico (ky), as curvas características de índice de área foliar (IAF), crescimento radicular (Zr) e coeficiente de cultura (kc), além da inclusão de funções de penalização da produtividade do eucalipto por ocorrência de eventos de geada (ffrost) e mortalidade por longos períodos de deficiência hídrica (fwd). A inclusão das funções de penalização e a calibração dos coeficientes resultaram em uma melhora significativa no desempenho (acurácia e precisão) do modelo, com a REQM passando de 110 m3 ha-1, na fase inicial de calibração, para 39 m3 ha-1, na fase final de calibração, R2 passando de 0,73 para 0,82 e índice d indo de 0,70 para 0,93. Com relação às quebras de produtividade, a deficiência hídrica foi o principal fator de quebra de produtividade, correspondendo a 77% da quebra total (QT), enquanto que as perdas decorrentes do déficit de manejo corresponderam a 23% da QT. Para avaliar o crescimento do eucalipto em eventos de ENOS, no período de 1983 a 2016, foi considerado o Incremento Corrente Anual (ICA) no período de máximo crescimento, ou seja, no 3° ano de seu ciclo. As produtividades e as perdas de produtividade do eucalipto durante a atuação dos eventos de ENOS mostraram-se amplamente variáveis tanto espacialmente quanto temporalmente, como consequência dos diferentes regimes térmicos e hídricos das regiões produtoras, não sendo observado um padrão claro para a relação ENOS e produtividade do eucalipto em diferentes regiões brasileiras avaliadas. / Among the forest species, the Eucalyptus is the most planted one in Brazil, with approximately 7.8 million hectares, having a huge economic importance for the country. Therefore, a better knowledge and quantification of the factors that affect forests growth and yield is of high important. Based on that, this study had as objectives: i) to adapt, calibrate and evaluate the Agroecological Zone Model (AEZ-FAO) to estimate growth and yield of eight eucalyptus clones in different Brazilian producing regions; ii) to identify the magnitude and major causes of yield gaps of eucalyptus in different producing regions of Minas Gerais state, Brazil; and iii) to identify the influence of El Niño, La Niña and Neutral events on eucalyptus yield in 12 Brazilian producing regions. The model´s coefficients, such as correction for the harvest index (Cc), water deficit sensitivity index (ky), leaf area index curve (LAI), root growth curve (Zr) and crop coefficient (kc), were calibrated. Penalization functions for considering the occurrence of frost events (ffrost) and mortality by long periods of accumulated water deficit (fwd) were also included in the model. The calibration and adaptation of the model resulted in a significant improvement of its performance (accuracy and precision), for both calibration and evaluation phases. The RMSE was 110 m3 ha-1 in the initial phase of calibration while in the final phase, RMSE was reduced to 39 m3 ha-1, the R2 was increase from 0.73 to 0.82, and the agreement index (d) was also improved going from 0.70 to 0.93. In relation to the yield gaps, the water deficit was the main factor of yield reduction, corresponding to 77% of the total yield gap (YGT), while losses due to sub-optimum management corresponded to 23% of YGT. In order to evaluate the eucalyptus growth under different ENSO events, from 1983 to 2016, the Current Annual Increment (CAI) in the period of maximum growth, 3rd year of the cycle, was used. The eucalyptus yield and yield gap during the ENSO events were widely variable both spatially and temporally as a consequence of the different thermal and water regimes of the producing regions. It was not possible to identify a clear pattern thee relationship between ENSO and eucalyptus yield in the different Brazilian regions assessed.

Dentre as espécies florestais, o Eucalyptus é o gênero florestal mais plantado no Brasil, com aproximadamente 7,8 milhões de hectares, tendo grande importância econômica para o país. Desta maneira, é importante um melhor conhecimento e quantificação dos fatores que condicionam e reduzem o crescimento e a produtividade das florestas. Assim, este estudo teve por objetivos: i) adaptar, calibrar e avaliar o Modelo da Zona Agroecológica (MZA-FAO) para a estimação do crescimento e da produtividade de oito clones de eucalipto em diferentes regiões brasileiras; ii) determinar a magnitude e as principais causas das quebras de produtividade (yield gaps) da cultura do eucalipto em diferentes regiões produtoras do estado de Minas Gerais; e iii) avaliar a influência de eventos de El Niño, La Niña e Neutros na produtividade de eucaliptos em diferentes localidades produtoras do Brasil. Foram adaptados e calibrados os coeficientes do MZA-FAO, como a correção para o índice de colheita (Cc), o coeficiente de sensibilidade ao déficit hídrico (ky), as curvas características de índice de área foliar (IAF), crescimento radicular (Zr) e coeficiente de cultura (kc), além da inclusão de funções de penalização da produtividade do eucalipto por ocorrência de eventos de geada (ffrost) e mortalidade por longos períodos de deficiência hídrica (fwd). A inclusão das funções de penalização e a calibração dos coeficientes resultaram em uma melhora significativa no desempenho (acurácia e precisão) do modelo, com a REQM passando de 110 m3 ha-1, na fase inicial de calibração, para 39 m3 ha-1, na fase final de calibração, R2 passando de 0,73 para 0,82 e índice d indo de 0,70 para 0,93. Com relação às quebras de produtividade, a deficiência hídrica foi o principal fator de quebra de produtividade, correspondendo a 77% da quebra total (QT), enquanto que as perdas decorrentes do déficit de manejo corresponderam a 23% da QT. Para avaliar o crescimento do eucalipto em eventos de ENOS, no período de 1983 a 2016, foi considerado o Incremento Corrente Anual (ICA) no período de máximo crescimento, ou seja, no 3° ano de seu ciclo. As produtividades e as perdas de produtividade do eucalipto durante a atuação dos eventos de ENOS mostraram-se amplamente variáveis tanto espacialmente quanto temporalmente, como consequência dos diferentes regimes térmicos e hídricos das regiões produtoras, não sendo observado um padrão claro para a relação ENOS e produtividade do eucalipto em diferentes regiões brasileiras avaliadas. / Among the forest species, the Eucalyptus is the most planted one in Brazil, with approximately 7.8 million hectares, having a huge economic importance for the country. Therefore, a better knowledge and quantification of the factors that affect forests growth and yield is of high important. Based on that, this study had as objectives: i) to adapt, calibrate and evaluate the Agroecological Zone Model (AEZ-FAO) to estimate growth and yield of eight eucalyptus clones in different Brazilian producing regions; ii) to identify the magnitude and major causes of yield gaps of eucalyptus in different producing regions of Minas Gerais state, Brazil; and iii) to identify the influence of El Niño, La Niña and Neutral events on eucalyptus yield in 12 Brazilian producing regions. The model´s coefficients, such as correction for the harvest index (Cc), water deficit sensitivity index (ky), leaf area index curve (LAI), root growth curve (Zr) and crop coefficient (kc), were calibrated. Penalization functions for considering the occurrence of frost events (ffrost) and mortality by long periods of accumulated water deficit (fwd) were also included in the model. The calibration and adaptation of the model resulted in a significant improvement of its performance (accuracy and precision), for both calibration and evaluation phases. The RMSE was 110 m3 ha-1 in the initial phase of calibration while in the final phase, RMSE was reduced to 39 m3 ha-1, the R2 was increase from 0.73 to 0.82, and the agreement index (d) was also improved going from 0.70 to 0.93. In relation to the yield gaps, the water deficit was the main factor of yield reduction, corresponding to 77% of the total yield gap (YGT), while losses due to sub-optimum management corresponded to 23% of YGT. In order to evaluate the eucalyptus growth under different ENSO events, from 1983 to 2016, the Current Annual Increment (CAI) in the period of maximum growth, 3rd year of the cycle, was used. The eucalyptus yield and yield gap during the ENSO events were widely variable both spatially and temporally as a consequence of the different thermal and water regimes of the producing regions. It was not possible to identify a clear pattern thee relationship between ENSO and eucalyptus yield in the different Brazilian regions assessed.

Sendo o cereal mais produzido no mundo e em larga expansão, os sistemas de produção de milho são altamente complexos e sua produção é diretamente dependente de fatores ligados tanto ao clima local quanto ao manejo da cultura. Para auxiliar na determinação tanto dos patamares produtivos de milho quanto quantificar o impacto causado por condições adversas tanto de clima quanto de manejo, pode-se lançar mão do uso de modelos de simulação de culturas. Para que os modelos possam ser devidamente aplicados, uma base solida de dados meteorológicos deve ser consistida, a fim de alimentar esses modelos. Nesse sentido, o presente estudo teve como objetivos: i) avaliar dois sistemas de obtenção de dados meteorológicos, o NASA-POWER e o DailyGridded, comparando-os com dados medidos em estações de solo; ii) calibrar, testar e combinar os modelos de simulação MZA-FAO, CSM DSSAT Ceres-Maize e APSIM-Maize, a fim de estimar as produtividades potenciais e atingíveis do milho no Brasil; iii) avaliar o impacto na produtividade causado pelo posicionamento da semeadura em diferentes tipos de solo; iv) desenvolver e avaliar um sistema de previsão de safra baseado em modelos de simulação; v) mapear as produtividades potencial, atingível e real do milho no Brasil, identificando regiões mais aptas ao cultivo e vi) determinar e mapear as quebras de produtividade, ou yield gaps (YG) da cultura do milho no Brasil. Comparando os dados climáticos dos sistemas em ponto de grade com os dados de estações meteorológicas de superfície, na escala diária, encontrou-se boa correlação entre as variáveis meteorológicas, inclusive para a chuva, com R2 da ordem de 0,58 e índice d = 0,85. O desempenho da combinação dos modelos ao final da calibração e ajuste se mostrou superior ao desempenho dos modelos individuais, com erros absolutos médios relativamente baixos (EAM = 627 kg ha-1) e com boa precisão (R2 = 0,62) e ótima acurácia (d = 1,00). Durante a avaliação da influência das épocas de semeadura e do tipo de solo no patamar produtivo do milho, observou-se que esse varia de acordo com a região estudada e apresenta seus valores máximos e com menores riscos à produção quando a semeaduras coincidem com o início do período de chuvas do local. O sistema de previsão de safra, baseado em modelos de simulação de cultura teve seu melhor desempenho simulando produtividades de milho semeados no início da safra e no final da safrinha, sendo capaz de prever de forma satisfatória a produtividade com até 25 dias antes da colheita. Para o estudo dos YGs, 152 locais foram avaliados e suas produtividades potenciais e atingíveis foram comparadas às produtividades reais, obtidas junto ao IBGE. Os maiores YGs referentes ao déficit hídrico se deram em solos arenosos e durante os meses de outono e inverno, usualmente mais secos na maioria das regiões brasileiras, atingindo valores de quebra superiores a 12000 kg ha-1. Quanto ao YG causado pelo manejo, esse foi maior nas regiões menos tecnificadas, como na região Norte e na Nordeste, apresentando valores superiores a 6000 kg ha-1. Já as regiões mais tecnificadas e tradicionais na produção de milho, como a região Sul e a Centro-Oeste, os YGs referentes ao manejo foram inferiores a 3500 kg ha-1 na maioria dos casos. / Maize is the most important cereal cultivated in the world, being its production system very complex and its productivity directly affected by climatic and crop management factors. In order to quantify the impacts caused by water and crop management deficits on maize yield, the use of crop simulation models is very useful. For properly apply these models, a solid basis of meteorological data is required. In this sense, the present study had as objectives: i) to evaluate two meteorological gridded data, NASA-POWER and DailyGridded, by comparing them with measured data from surface stations; (ii) to calibrate, evaluate and combine the MZA-FAO, CSM DSSAT Ceres-Maize and APSIM-Maize simulation models to estimate the maize potential and attainable yields in Brazil; iii) to evaluate the impact caused by the different sowing dates and soil types on maize yield; iv) to develop and evaluate a crop forecasting system based on crop simulation models and climatological data; v) to map the potential and the attainable maize yields in Brazil, identifying the most suitable regions for cultivation, and vi) to determine and map maize yields and yield gaps (YG) in Brazil. Comparing the gridded climatic data with observed ones, on a daily basis, a good agreement was found for all weather variables, including rainfall, with R2 = 0.58 and d = 0,85. The performances of the combination of the models at the end of the calibration and evaluation phases were better than those obtained with the individual models, with relatively low mean absolute error (EAM = 627 kg ha-1) and with good precision (R2 = 0.62) and accuracy (d = 1.00). During the evaluation of different sowing dates and soil types on maize yield, it was observed that this variable depends on the region and presents the maximum values and, consequently, the minimum risk during the sowings in the beginning of the rainy season of each site. The crop forecasting system, based on crop simulation models, had its best performance for simulating maize yields when the sowings were performed at the beginning of the main season and at the end of the second season, when it was able to predict yield satisfactorily 25 days before harvest. For the YG analysis, 152 sites were assessed and their potential and attainable yields were compared to the actual yields reported by IBGE. The highest YGs caused by water deficit occurred for sandy soils and during the autumn and winter months, usually dry in most of Brazilian regions, reaching values above 12000 kg ha-1. For YG caused by crop management, the values were higher in the less technified regions, such as in the North and Northeast regions, with values above 6000 kg ha-1. In contrast, more traditional maize production regions, such as the South and Center-West, presented YG caused by crop management, lower than 3500 kg ha-1 in most cases.