Photomultiplier nonlinear response in time-domain laser-induced luminescence spectroscopy

A new procedure to find the limiting range of the photomultiplier linear response of a low-cost, digital oscilloscope-based time-resolved laser-induced luminescence spectrometer (TRLS), is presented. A systematic investigation on the instrument response function with different signal input terminations, and the relationship between the luminescence intensity reaching the photomultiplier and the measured decay time are described. These investigations establish that setting the maximum intensity of the luminescence signal below 0.3V guarantees, for signal input terminations equal or higher than 99.7 ohm, a linear photomultiplier response.

Temporal variability of soil CO2 emission after conventional and reduced tillage described by an exponential decay in time model

To study Assessing the impact of tillage practices on soil carbon losses dependents it is necessary to describe the temporal variability of soil CO2 emission after tillage. It has been argued that large amounts of CO2 emitted after tillage may serve as an indicator for longer-term changes in soil carbon stocks. Here we present a two-step function model based on soil temperature and soil moisture including an exponential decay in time component that is efficient in fitting intermediate-term emission after disk plow followed by a leveling harrow (conventional), and chisel plow coupled with a roller for clod breaking (reduced) tillage. Emission after reduced tillage was described using a non-linear estimator with determination coefficient (R²) as high as 0.98. Results indicate that when emission after tillage is addressed it is important to consider an exponential decay in time in order to predict the impact of tillage in short-term emissions.

Machine vision methods for process measurements in pulping

The papermaking industry has been continuously developing intelligent solutions to characterize the raw materials it uses, to control the manufacturing process in a robust way, and to guarantee the desired quality of the end product. Based on the much improved imaging techniques and image-based analysis methods, it has become possible to look inside the manufacturing pipeline and propose more effective alternatives to human expertise. This study is focused on the development of image analyses methods for the pulping process of papermaking. Pulping starts with wood disintegration and forming the fiber suspension that is subsequently bleached, mixed with additives and chemicals, and finally dried and shipped to the papermaking mills. At each stage of the process it is important to analyze the properties of the raw material to guarantee the product quality. In order to evaluate properties of fibers, the main component of the pulp suspension, a framework for fiber characterization based on microscopic images is proposed in this thesis as the first contribution. The framework allows computation of fiber length and curl index correlating well with the ground truth values. The bubble detection method, the second contribution, was developed in order to estimate the gas volume at the delignification stage of the pulping process based on high-resolution in-line imaging. The gas volume was estimated accurately and the solution enabled just-in-time process termination whereas the accurate estimation of bubble size categories still remained challenging. As the third contribution of the study, optical flow computation was studied and the methods were successfully applied to pulp flow velocity estimation based on double-exposed images. Finally, a framework for classifying dirt particles in dried pulp sheets, including the semisynthetic ground truth generation, feature selection, and performance comparison of the state-of-the-art classification techniques, was proposed as the fourth contribution. The framework was successfully tested on the semisynthetic and real-world pulp sheet images. These four contributions assist in developing an integrated factory-level vision-based process control.

Parameter identification in time series models

Time series analysis can be categorized into three different approaches: classical, Box-Jenkins, and State space. Classical approach makes a basement for the analysis and Box-Jenkins approach is an improvement of the classical approach and deals with stationary time series. State space approach allows time variant factors and covers up a broader area of time series analysis. This thesis focuses on parameter identifiablity of different parameter estimation methods such as LSQ, Yule-Walker, MLE which are used in the above time series analysis approaches. Also the Kalman filter method and smoothing techniques are integrated with the state space approach and MLE method to estimate parameters allowing them to change over time. Parameter estimation is carried out by repeating estimation and integrating with MCMC and inspect how well different estimation methods can identify the optimal model parameters. Identification is performed in probabilistic and general senses and compare the results in order to study and represent identifiability more informative way.

From being ill in time to love of eternity

N/A

The claim of Amasa Stetson, of Massachusetts, on the United States, for money advanced, in fulfilling the orders of the Government while discharging the duties of Commissary General of Purchases, in time of the late war with Great Britain ; and for services rendered. --

Claim relating to the War of 1812.

Short run and long run causality in time series: Inference

We propose methods for testing hypotheses of non-causality at various horizons, as defined in Dufour and Renault (1998, Econometrica). We study in detail the case of VAR models and we propose linear methods based on running vector autoregressions at different horizons. While the hypotheses considered are nonlinear, the proposed methods only require linear regression techniques as well as standard Gaussian asymptotic distributional theory. Bootstrap procedures are also considered. For the case of integrated processes, we propose extended regression methods that avoid nonstandard asymptotics. The methods are applied to a VAR model of the U.S. economy.

Many-electron relativistic calculation and interpretation of atomic processes in time dependent heavy-ion scattering

The time dependence of a heavy-ion-atom collision system is solved via a set of coupled channel equations using energy eigenvalues and matrix elements from a self-consistent field relativistic molecular many-electron Dirac-Fock-Slater calculation. Within this independent particle model we give a full many-particle interpretation by performing a small number of single-particle calculations. First results for the P(b) curves for the Ne K-hole excitation for the systems F{^8+} - Ne and F{^6+} - Ne as examples are discussed.

Gender differences in time allocation of poor children in Colombia

This paper studies the effect of credit constraints and constraints on transfers between parents and children, on differences in labor and schooling across children within the same household, with an application to gender. When families are unconstrained in these respects, differences in labor supply or education are driven by differences in wages or returns to education. If the family faces an imperfect capital market, the labor supply of each child is inefficient, but differences across children are still driven by comparative advantage. However, if interfamily transfers are constrained so that parents cannot offset inequality between their children, they will favor the human capital accumulation of the more disadvantaged child -generally the one who works more as a child. We use our theory to examine the gender gap in child labor. Using a sample of poor families in Colombia, we conform our predictions among rural households, although this is less clear for urban households. The gender gap is largely explained by the wage gap between girls and boys. Moreover, families with the potential to make capital transfers to adult children (e.g. those with large animals), can compensate adult sons for their greater child labor and reduced educational attainment. In such families, as predicted, the male/female labor gap is greater.

Lost in time : a key stage 3 development study.

Estudia la historia social de Gran Bretaña en los últimos mil años, a través de un viaje en el tiempo en una nave espacial averiada. Cumple con los requisitos del currículo nacional inglés para la etapa de 3 de secundaria (key stage 3).Este texto esta preparado para el Schools History Project creado en 1972 para mejorar el estudio de la historia entre estudiantes de trece a dieciséis años. Reconsidera las formas en que la historia contribuye a las necesidades educativas de los jóvenes, y por ello idea nuevos objetivos, nuevos criterios para la planificación y desarrollo del curso, así como de nuevos materiales de apoyo. Requiere nuevos criterios de evaluación y, por tanto nuevos exámenes y, adquirió mayor expansión con la introducción del General Certificate of Secondary Education (GCSE) en 1987.

Simple experiments in time.

Con materiales de uso corriente, los niños pueden realizar más de cuarenta juegos y experimentos sencillos que les ayudaran a comprender mejor qué es el tiempo y cómo se mide. Las actividades son fáciles de realizar y están dirigidas a niños, a partir de diez años, que ya han alcanzado un nivel aceptable de lectura comprensiva. Estos experimentos no entrañan ningún peligro y no requieren el uso de sustancias ni materiales especiales.