Estimation of genetic parameters for partial egg production periods by means of random regression models

Conselho Nacional de Desenvolvimento Científico e Tecnológico (CNPq)

Estimation and evaluation of dynamic properties as indicators of changes on soil structure in sugarcane fields of São Paulo State - Brazil

The indiscriminate management and use of soils without moisture control has changed the structure of it due to the increment of the traffic by agricultural machines through the years, causing in consequence, a soil compaction and yield reduction in the areas of intensive traffic. The purpose of this work was to estimate and to evaluate the performance of preconsolidation pressure of the soil and shear stress as indicators of changes on soil structure in fields cropped with sugarcane, as well as the impact of management processes in an Eutrorthox soil structure located in São Paulo State. The experimental field was located in Piracicaba's rural area (São Paulo State, Brazil) and has been cropped with sugarcane, in the second harvest cycle. The soil was classified by Empresa Brasileira de Pesquisa Agropecuária (EMBRAPA) [Empresa Brasileira de Pesquisa Agropecuária (EMBRAPA), 1999. Centro Nacional de Pesquisa de Solos. Sistema Brasileiro de Classificao de Solos, Empresa Brasileira de Pesquisa Agropecuária (EMBRAPA), Brasilia, 412 pp.] as an Eutrorthox. Undisturbed samples were collected and georeferenced in a grid of 60 m x 60 m from two depths: 0-0.10 m (superficial layer - SL) and in the layer of greatest mechanical resistance (LGMR), previously identified by cone index (CI). The investigated variables were pressure preconsolidation (sigma(p)), apparent cohesion (c) and internal friction angle (phi). The conclusions from the results were that the SLSC was predicted satisfactorily from up as a function of soil moisture; thus, decisions about machinery size and loading (contact pressures) can be taken. Apparent cohesion (c), internal friction angle (phi) and the Coulomb equation were significantly altered by traffic intensity. The sigma(p), c and phi maps were shown to be important tools to localize and visualize soil compaction and mechanical resistance zones. They constitute a valuable resource to evaluate the traffic impact in areas cropped with sugarcane in State of São Paulo, Brazil. (C) 2008 Elsevier B.V. All rights reserved.

Partial purification and properties of cellulase-free alkaline xylanase produced by Rhizopus stolonifer in solid-state fermentation

Rhizopus stolonifer was cultivated in wheat bran to produce a cellulase-free alkaline xylanase. The purified enzyme obtained after molecular exclusion chromatography in Sephacryl S-200 HR showed optimum temperature as 45 degrees C and hydrolysis pHs optima as pH 6.0 and 9.0. Xylanase presented higher Vmax at pH 9.0 (0.87 mu mol/mg protein) than at pH 6.0 and minor Km at pH 6.0 (7.42 mg/mL)than at pH 9.0.

Production and partial characterization of polygalacturonases produced by thermophilic Monascus sp N8 and by thermotolerant Aspergillus sp N12 on solid-state fermentation

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

Production and partial characterization of serine and metallo peptidases secreted by Aspergillus fumigatus Fresenius in submerged and solid state fermentation

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

Estimation of Submerged Aquatic Vegetation Height and Distribution in Nova Avanhandava Reservoir (São Paulo State, Brazil) Using Bio-Optical Modeling

Conselho Nacional de Desenvolvimento Científico e Tecnológico (CNPq)

Estimation of chlorophyll-a concentration and the trophic state of the Barra Bonita hydroelectric reservoir using oli/landsat-8 images

Reservoirs are artificial environments built by humans, and the impacts of these environments are not completely known. Retention time and high nutrient availability in the water increases the eutrophic level. Eutrophication is directly correlated to primary productivity by phytoplankton. These organisms have an important role in the environment. However, high concentrations of determined species can lead to public health problems. Species of cyanobacteria produce toxins that in determined concentrations can cause serious diseases in the liver and nervous system, which could lead to death. Phytoplankton has photoactive pigments that can be used to identify these toxins. Thus, remote sensing data is a viable alternative for mapping these pigments, and consequently, the trophic. Chlorophyll-a (Chl-a) is present in all phytoplankton species. Therefore, the aim of this work was to evaluate the performance of images of the sensor Operational Land Imager (OLI) onboard the Landsat-8 satellite in determining Chl-a concentrations and estimating the trophic level in a tropical reservoir. Empirical models were fitted using data from two field surveys conducted in May and October 2014 (Austral Autumn and Austral Spring, respectively). Models were applied in a temporal series of OLI images from May 2013 to October 2014. The estimated Chl-a concentration was used to classify the trophic level from a trophic state index that adopted the concentration of this pigment-like parameter. The models of Chl-a concentration showed reasonable results, but their performance was likely impaired by the atmospheric correction. Consequently, the trophic level classification also did not obtain better results.

Rapid estimation of cartilage T2 based on double echo at steady state (DESS) with 3 Tesla

The double-echo-steady-state (DESS) sequence generates two signal echoes that are characterized by a different contrast behavior. Based on these two contrasts, the underlying T2 can be calculated. For a flip-angle of 90 degrees , the calculated T2 becomes independent of T1, but with very low signal-to-noise ratio. In the present study, the estimation of cartilage T2, based on DESS with a reduced flip-angle, was investigated, with the goal of optimizing SNR, and simultaneously minimizing the error in T2. This approach was validated in phantoms and on volunteers. T2 estimations based on DESS at different flip-angles were compared with standard multiecho, spin-echo T2. Furthermore, DESS-T2 estimations were used in a volunteer and in an initial study on patients after cartilage repair of the knee. A flip-angle of 33 degrees was the best compromise for the combination of DESS-T2 mapping and morphological imaging. For this flip angle, the Pearson correlation was 0.993 in the phantom study (approximately 20% relative difference between SE-T2 and DESS-T2); and varied between 0.429 and 0.514 in the volunteer study. Measurements in patients showed comparable results for both techniques with regard to zonal assessment. This DESS-T2 approach represents an opportunity to combine morphological and quantitative cartilage MRI in a rapid one-step examination.

Extended kalman filter for estimation of parameters in nonlinear state-space models of biochemical networks.

It is system dynamics that determines the function of cells, tissues and organisms. To develop mathematical models and estimate their parameters are an essential issue for studying dynamic behaviors of biological systems which include metabolic networks, genetic regulatory networks and signal transduction pathways, under perturbation of external stimuli. In general, biological dynamic systems are partially observed. Therefore, a natural way to model dynamic biological systems is to employ nonlinear state-space equations. Although statistical methods for parameter estimation of linear models in biological dynamic systems have been developed intensively in the recent years, the estimation of both states and parameters of nonlinear dynamic systems remains a challenging task. In this report, we apply extended Kalman Filter (EKF) to the estimation of both states and parameters of nonlinear state-space models. To evaluate the performance of the EKF for parameter estimation, we apply the EKF to a simulation dataset and two real datasets: JAK-STAT signal transduction pathway and Ras/Raf/MEK/ERK signaling transduction pathways datasets. The preliminary results show that EKF can accurately estimate the parameters and predict states in nonlinear state-space equations for modeling dynamic biochemical networks.

Maximum likelihood estimation of new state space models for operational modal analysis

The modal analysis of a structural system consists on computing its vibrational modes. The experimental way to estimate these modes requires to excite the system with a measured or known input and then to measure the system output at different points using sensors. Finally, system inputs and outputs are used to compute the modes of vibration. When the system refers to large structures like buildings or bridges, the tests have to be performed in situ, so it is not possible to measure system inputs such as wind, traffic, . . .Even if a known input is applied, the procedure is usually difficult and expensive, and there are still uncontrolled disturbances acting at the time of the test. These facts led to the idea of computing the modes of vibration using only the measured vibrations and regardless of the inputs that originated them, whether they are ambient vibrations (wind, earthquakes, . . . ) or operational loads (traffic, human loading, . . . ). This procedure is usually called Operational Modal Analysis (OMA), and in general consists on to fit a mathematical model to the measured data assuming the unobserved excitations are realizations of a stationary stochastic process (usually white noise processes). Then, the modes of vibration are computed from the estimated model. The first issue investigated in this thesis is the performance of the Expectation- Maximization (EM) algorithm for the maximum likelihood estimation of the state space model in the field of OMA. The algorithm is described in detail and it is analysed how to apply it to vibration data. After that, it is compared to another well known method, the Stochastic Subspace Identification algorithm. The maximum likelihood estimate enjoys some optimal properties from a statistical point of view what makes it very attractive in practice, but the most remarkable property of the EM algorithm is that it can be used to address a wide range of situations in OMA. In this work, three additional state space models are proposed and estimated using the EM algorithm: • The first model is proposed to estimate the modes of vibration when several tests are performed in the same structural system. Instead of analyse record by record and then compute averages, the EM algorithm is extended for the joint estimation of the proposed state space model using all the available data. • The second state space model is used to estimate the modes of vibration when the number of available sensors is lower than the number of points to be tested. In these cases it is usual to perform several tests changing the position of the sensors from one test to the following (multiple setups of sensors). Here, the proposed state space model and the EM algorithm are used to estimate the modal parameters taking into account the data of all setups. • And last, a state space model is proposed to estimate the modes of vibration in the presence of unmeasured inputs that cannot be modelled as white noise processes. In these cases, the frequency components of the inputs cannot be separated from the eigenfrequencies of the system, and spurious modes are obtained in the identification process. The idea is to measure the response of the structure corresponding to different inputs; then, it is assumed that the parameters common to all the data correspond to the structure (modes of vibration), and the parameters found in a specific test correspond to the input in that test. The problem is solved using the proposed state space model and the EM algorithm. Resumen El análisis modal de un sistema estructural consiste en calcular sus modos de vibración. Para estimar estos modos experimentalmente es preciso excitar el sistema con entradas conocidas y registrar las salidas del sistema en diferentes puntos por medio de sensores. Finalmente, los modos de vibración se calculan utilizando las entradas y salidas registradas. Cuando el sistema es una gran estructura como un puente o un edificio, los experimentos tienen que realizarse in situ, por lo que no es posible registrar entradas al sistema tales como viento, tráfico, . . . Incluso si se aplica una entrada conocida, el procedimiento suele ser complicado y caro, y todavía están presentes perturbaciones no controladas que excitan el sistema durante el test. Estos hechos han llevado a la idea de calcular los modos de vibración utilizando sólo las vibraciones registradas en la estructura y sin tener en cuenta las cargas que las originan, ya sean cargas ambientales (viento, terremotos, . . . ) o cargas de explotación (tráfico, cargas humanas, . . . ). Este procedimiento se conoce en la literatura especializada como Análisis Modal Operacional, y en general consiste en ajustar un modelo matemático a los datos registrados adoptando la hipótesis de que las excitaciones no conocidas son realizaciones de un proceso estocástico estacionario (generalmente ruido blanco). Posteriormente, los modos de vibración se calculan a partir del modelo estimado. El primer problema que se ha investigado en esta tesis es la utilización de máxima verosimilitud y el algoritmo EM (Expectation-Maximization) para la estimación del modelo espacio de los estados en el ámbito del Análisis Modal Operacional. El algoritmo se describe en detalle y también se analiza como aplicarlo cuando se dispone de datos de vibraciones de una estructura. A continuación se compara con otro método muy conocido, el método de los Subespacios. Los estimadores máximo verosímiles presentan una serie de propiedades que los hacen óptimos desde un punto de vista estadístico, pero la propiedad más destacable del algoritmo EM es que puede utilizarse para resolver un amplio abanico de situaciones que se presentan en el Análisis Modal Operacional. En este trabajo se proponen y estiman tres modelos en el espacio de los estados: • El primer modelo se utiliza para estimar los modos de vibración cuando se dispone de datos correspondientes a varios experimentos realizados en la misma estructura. En lugar de analizar registro a registro y calcular promedios, se utiliza algoritmo EM para la estimación conjunta del modelo propuesto utilizando todos los datos disponibles. • El segundo modelo en el espacio de los estados propuesto se utiliza para estimar los modos de vibración cuando el número de sensores disponibles es menor que vi Resumen el número de puntos que se quieren analizar en la estructura. En estos casos es usual realizar varios ensayos cambiando la posición de los sensores de un ensayo a otro (múltiples configuraciones de sensores). En este trabajo se utiliza el algoritmo EM para estimar los parámetros modales teniendo en cuenta los datos de todas las configuraciones. • Por último, se propone otro modelo en el espacio de los estados para estimar los modos de vibración en la presencia de entradas al sistema que no pueden modelarse como procesos estocásticos de ruido blanco. En estos casos, las frecuencias de las entradas no se pueden separar de las frecuencias del sistema y se obtienen modos espurios en la fase de identificación. La idea es registrar la respuesta de la estructura correspondiente a diferentes entradas; entonces se adopta la hipótesis de que los parámetros comunes a todos los registros corresponden a la estructura (modos de vibración), y los parámetros encontrados en un registro específico corresponden a la entrada en dicho ensayo. El problema se resuelve utilizando el modelo propuesto y el algoritmo EM.

Partial molar volume, surface area, and hydration changes for equilibrium unfolding and formation of aggregation transition state: High-pressure and cosolute studies on recombinant human IFN-γ

The equilibrium dissociation of recombinant human IFN-γ was monitored as a function of pressure and sucrose concentration. The partial molar volume change for dissociation was −209 ± 13 ml/mol of dimer. The specific molar surface area change for dissociation was 12.7 ± 1.6 nm2/molecule of dimer. The first-order aggregation rate of recombinant human IFN-γ in 0.45 M guanidine hydrochloride was studied as a function of sucrose concentration and pressure. Aggregation proceeded through a transition-state species, N*. Sucrose reduced aggregation rate by shifting the equilibrium between native state (N) and N* toward the more compact N. Pressure increased aggregation rate through increased solvation of the protein, which exposes more surface area, thus shifting the equilibrium away from N toward N*. The changes in partial molar volume and specific molar surface area between the N* and N were −41 ± 9 ml/mol of dimer and 3.5 ± 0.2 nm2/molecule, respectively. Thus, the structural change required for the formation of the transition state for aggregation is small relative to the difference between N and the dissociated state. Changes in waters of hydration were estimated from both specific molar surface area and partial molar volume data. From partial molar volume data, estimates were 25 and 128 mol H2O/mol dimer for formation of the aggregation transition state and for dissociation, respectively. From surface area data, estimates were 27 and 98 mol H2O/mol dimer. Osmotic stress theory yielded values ≈4-fold larger for both transitions.

An exploratory memorandum on partial unemployment benefits in the state unemployment compensation systems,

Mode of access: Internet.