Relativistic deformed mean-field calculation of binding energy differences of mirror nuclei

Binding energy differences of mirror nuclei for A = 15, 17, 27, 29, 31, 33, 39 and 41 are calculated in the framework of relativistic deformed mean-field theory. To fully include the effects of the polarization of the nuclear core due to the extra particle or hole, the spatial components of the vector meson fields and the photon are taken into account in a self-consistent manner. The calculated binding energy differences are systematically smaller than the experimental values and lend support to the existency of the Okamoto-Nolen-Schiffer anomaly found decades ago in nonrelativistic calculations, For the majority of the nuclei studied, however, the results are such that the anomaly is significantly smaller than the one obtained within state-of-the-art nonrelativistic calculations.

PRODUCTIVITY OF CANE SUGAR: LINEAR AND SPATIAL VARIABILITY BETWEEN COMPONENTS AND TECHNOLOGICAL PRODUCTION

Nowadays, the culture of the sugarcane plays an important role regarding the Brazilian reality, especially in the aspect related to the alternative energy sources. In 2009, the municipality of Suzanapolis (SP), in the Brazilian Cerrado, an experiment was conducted with the culture of the sugarcane in a Red eutrophic, with the aim of selecting, using Pearson correlation coefficients, modeling, simple, linear and multiple regressions and spatial correlation, and also the best technological and productive components, to explain the variability of the productivity of the sugarcane. The geostatistical grid was installed in order to collect the data, with 120 sampling points, in an area of 14.53 ha. For the simple linear regressions, the plants population is the component of production that presents the best quadratic correlation with the productivity of the sugarcane, given by: PRO = -0.553**xPOP(2)+16.14*xPOP-15.77. However, for multiple linear regressions, the equation PRO = -21.11+4.92xPOP**+0.76xPUR** is the one that best presents in order to estimate that productivity. Spatially, the best correlation with yield of the sugarcane is also determined by the component of the production population of plants.

Spatial and temporal heterogeneity in the Jurumirim Reservoir, São Paulo, Brazil

Jurumirim is a large tropical reservoir with remarkable spatial gradients. This structure seems to be determined by a longitudinal gradient in the trophic conditions along the main axis of the reservoir. Nutrient-rich waters enter from the main tributary river, Paranapanema, and towards the dam there is a lacustrine zone that is deeper and more oligotrophic. Additional variability is derived from two important lateral components: the entrance of the Taquari River, the second largest tributary, bringing waters with higher pH and alkalinity; and the Ribeirão das Posses arm, a sheltered bay where the hydrodynamic conditions promote a high growth of phytoplankton. However, such a spatial pattern is not static. It can become either more defined, during the dry season (late autumn and winter), or less evident, during the expansion of the lotic conditions in the rainy period (late spring and summer). Seasonal processes of stratification/destratification determine the temporal changes in the lacustrine zone but, unlike the upstream regions, the dam zone of the reservoir seems to be little affected by periodic pulses of modifications produced by intensive rains. The presence of extensive wetlands and oxbow lagoons in the mouth zones of the main rivers also constitutes an important source of spatial variability and should be considered in the future.

Spatial correlation between the composition of the clay fraction and contents of available phosphorus of an Oxisol at hillslope scale

Relief is regarded as the abiotic factor most strongly influencing pedogenic processes at a local scale. The spatial correlations between the composition of the clay fraction (iron - Fe and aluminum - Al oxides, kaolinite and organic matter - OM) and contents of available phosphorus (P) of an Oxisol were evaluated at hillslope scale under sugarcane cultivation. A total of 119 samples were collected at intersection points on a 100. ×. 100. m georeferenced grid of regularly spaced points 10. m apart in the 0.2-0.4. m depth in an area consisting of two landform components namely: component I (an area with a linear hillslope curvature), and component II (one with a concave-convex hillslope curvature). Soil OM and available P contents were subjected to descriptive statistics and geostatistical analyses in order to assess their variability and spatial dependence. All attributes studied were spatially dependent. Available phosphorus had positive spatial correlation with high crystalline goethite, hematite and gibbsite. Identifying small hillslope curvatures is useful with a view to better understanding their relationships with soil organic matter and available phosphorus, as well as kaolinite and Fe and Al oxide attributes. A simple correlation analysis by itself is inadequate to relate attributes, which requires a supplemental, geostatistical technique. © 2012 Elsevier B.V..

Chlorophyll a spatial inference using artificial neural network from multispectral images and in situ measurements

Considering the importance of monitoring the water quality parameters, remote sensing is a practicable alternative to limnological variables detection, which interacts with electromagnetic radiation, called optically active components (OAC). Among these, the phytoplankton pigment chlorophyll a is the most representative pigment of photosynthetic activity in all classes of algae. In this sense, this work aims to develop a method of spatial inference of chlorophyll a concentration using Artificial Neural Networks (ANN). To achieve this purpose, a multispectral image and fluorometric measurements were used as input data. The multispectral image was processed and the net training and validation dataset were carefully chosen. From this, the neural net architecture and its parameters were defined to model the variable of interest. In the end of training phase, the trained network was applied to the image and a qualitative analysis was done. Thus, it was noticed that the integration of fluorometric and multispectral data provided good results in the chlorophyll a inference, when combined in a structure of artificial neural networks.

Temporal and Spatial Variability of Limnological Characteristics in Areas under the Influence of Tilapia Cages in the Chavantes Reservoir, Paranapanema River, Brazil

The influence of tilapia cages on limnological characteristics of the Chavantes Reservoir, Paranapanema River, Brazil, was investigated in March and June 2007. Principal components analysis was used to compare the transparency; dissolved oxygen; temperature; total organic nitrogen, phosphorus, and dissolved solids; chlorophyll aand electrical conductivity of fish farm 1 (239.3m.t.), 2 (461.5m.t.) and areas without cages, in the lacustrine and river-reservoir transition regions. The variables differentiated the regions and areas with and without cages. In March, in the lacustrine region, there was a thermal and chemical stratification, and in the transition region, there was a temperature and oxygen reduction gradient between the surface and bottom that was also observed in June in fish farm 1. The higher transparency confirmed the increased light penetration in the lacustrine region. In the transition region, there were higher turbidity, total dissolved solid, and conductivity values that are likely related to allochthonous material flow and transport. In fish farms, lower oxygen and pH values indicate intense decomposition and respiration. The generally higher total dissolved solid and nutrient values, turbidity, and conductivity and the lower transparency in one or both fish farms indicate their contribution to eutrophication, demonstrating the need for careful monitoring.

Community-wide spatial and temporal discordances of seed-seedling shadows in a tropical rainforest

Fundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP)