Hydro-physical characterization of soils under tropical semi-deciduous forest

The study of the hydro-physical behavior in soils using toposequences is of great importance for better understanding the soil, water and vegetation relationships. This study aims to assess the hydro-physical and morphological characterization of soil from a toposequence in Galia, state of São Paulo, Brazil). The plot covers an area of 10.24 ha (320 × 320 m), located in a semi-deciduous seasonal forest. Based on ultra-detailed soil and topographic maps of the area, a representative transect from the soil in the plot was chosen. Five profiles were opened for the morphological description of the soil horizons, and hydro-physical and micromorphological analyses were performed to characterize the soil. Arenic Haplustult, Arenic Haplustalf and Aquertic Haplustalf were the soil types observed in the plot. The superficial horizons had lower density and greater hydraulic conductivity, porosity and water retention in lower tensions than the deeper horizons. In the sub-superficial horizons, greater water retention at higher tensions and lower hydraulic conductivity were observed, due to structure type and greater clay content. The differences observed in the water retention curves between the sandy E and the clay B horizons were mainly due to the size distribution, shape and type of soil pores.

Physical objects on navigation channal simulation models

This paper presents the results of a simulation using physical objects. This concept integrates the physical dimensions of an entity such as length, width, and weight, with the usual process flow paradigm, recurrent in the discrete event simulation models. Based on a naval logistics system, we applied this technique in an access channel of the largest port of Latin America. This system is composed by vessel movement constrained by the access channel dimensions. Vessel length and width dictates whether it is safe or not to have one or two ships simultaneously. The success delivered by the methodology proposed was an accurate validation of the model, approximately 0.45% of deviation, when compared to real data. Additionally, the model supported the design of new terminals operations for Santos, delivering KPIs such as: canal utilization, queue time, berth utilization, and throughput capability

Seasonal dynamics of cyanobacteria in a eutrophic reservoir (Arcoverde) in a semi-arid region of Brazil

Environmental conditions favor the predominance of dense populations of cyanobacteria in reservoirs in northeastern Brazil. The aim of this study was to understand cyanobacterial population dynamics in the rainy and dry seasons at two depths in the Arcoverde reservoir. Microalgae and cyanobacteria samples were collected during 24 hours with intervals of 4 hours (nycthemeral) at sub-surface and 10 m using a van Dorn bottle and a determined biomass. Physical and chemical variables were obtained and the data were analyzed using the principal component analysis (PCA). No nycthemeral variations in the taxonomic composition or distribution of the populations of cyanobacteria were found between the different times of day in either the rainy or dry season. In both seasons, the greatest biomass of the phytoplankton community was made up of cyanobacteria at two depths and all times of the day. Cylindrospermopsis raciborskii (Woloszynska) Seenayya et Subba Raju was dominant at all times of the day on both the surface and at the bottom. In the rainy season, the differences in cyanobacterial biomass between the surface and bottom were less significant than in the dry season. The differences in cyanobacterial biomass between surface and bottom were less pronounced than those found in the dry season. We concluded that a) physical variables better explain the alterations of species in the phytoplankton community in an environment dominated by cyanobacteria throughout the year; b) seasonal climatic factors associated to periods of stratification and de-stratification are important for alterations in the community and variations in biomass and, c) the turbidity caused by rainfall favored the emergence and establishment of other cyanobacteria, especially Planktothrix agardhii (Gomont) Anagnostidis & Komarek.

Stochastic simulation of time-series models combined with geostatistics to predict water-table scenarios in a Guarani Aquifer System outcrop area, Brazil

Stochastic methods based on time-series modeling combined with geostatistics can be useful tools to describe the variability of water-table levels in time and space and to account for uncertainty. Monitoring water-level networks can give information about the dynamic of the aquifer domain in both dimensions. Time-series modeling is an elegant way to treat monitoring data without the complexity of physical mechanistic models. Time-series model predictions can be interpolated spatially, with the spatial differences in water-table dynamics determined by the spatial variation in the system properties and the temporal variation driven by the dynamics of the inputs into the system. An integration of stochastic methods is presented, based on time-series modeling and geostatistics as a framework to predict water levels for decision making in groundwater management and land-use planning. The methodology is applied in a case study in a Guarani Aquifer System (GAS) outcrop area located in the southeastern part of Brazil. Communication of results in a clear and understandable form, via simulated scenarios, is discussed as an alternative, when translating scientific knowledge into applications of stochastic hydrogeology in large aquifers with limited monitoring network coverage like the GAS.

Detailed H-1 and C-13 NMR structural assignment and relative stereochemistry determination for three new and one known semi-synthetic sesquiterpene lactones

In this work is described a complete H-1 and C-13 NMR analysis for a group of four sesquiterpene lactones, three previously unknown. The unequivocal assignments were achieved by H-1 NMR, C-13{H-1} NMR, gCOSY. gHMQC, gHMBC and NOESY experiments and no ambiguities were left behind. All hydrogen coupling constants were measured, clarifying all hydrogen signals multiplicities. (C) 2011 Elsevier B.V. All rights reserved.

A semi-supervised classification technique based on interacting forces

Semi-supervised learning is a classification paradigm in which just a few labeled instances are available for the training process. To overcome this small amount of initial label information, the information provided by the unlabeled instances is also considered. In this paper, we propose a nature-inspired semi-supervised learning technique based on attraction forces. Instances are represented as points in a k-dimensional space, and the movement of data points is modeled as a dynamical system. As the system runs, data items with the same label cooperate with each other, and data items with different labels compete among them to attract unlabeled points by applying a specific force function. In this way, all unlabeled data items can be classified when the system reaches its stable state. Stability analysis for the proposed dynamical system is performed and some heuristics are proposed for parameter setting. Simulation results show that the proposed technique achieves good classification results on artificial data sets and is comparable to well-known semi-supervised techniques using benchmark data sets.

Monte Carlo Semi-Empirical Model for Si(Li) X-Ray Detector: Differences between Nominal and Fitted Parameters.

A detailed characterization of a X-ray Si(Li) detector was performed to obtain the energy dependence of efficiency in the photon energy range of 6.4 - 59.5 keV. which was measured and reproduced by Monte Carlo (MC) simulations. Significant discrepancies between MC and experimental values were found when lhe manufacturer parameters of lhe detector were used in lhe simulation. A complete Computerized Tomagraphy (CT) detector scan allowed to find the correct crystal dimensions and position inside the capsule. The computed efficiencies with the resulting detector model differed with the measured values no more than 10% in most of the energy range.