Trends and cycles in regional economic growth : how spatial differences formed the Swedish growth experience 1860-2009.

Using a novel dataset on regional GDP per worker 1860-2009, this paper analyzes communalities in regional long-term growth trajectories for 24 Swedish provinces. Wavelet Analysis and Principal Component Analysis are used to decompose regional growth trajectories, and to assess to what extent growth in regions share common trend and cyclical properties. It is found that regional trend growth shows strong common features among groups of regions. Primarily natural resource rich regions benefited from the First Industrial Revolution. Contrary to regional development in many other European economies, a strong growth surge in Sweden later benefited virtually the whole country during the Second Industrial Revolution. Growth in this countrywide trend slowed down in the 1970s, when the metropolitan regions became main growth engines. In mid- and short-term cyclical movements regions display more heterogeneous growth patterns, and evidence of mid-term sequential lead-lag patterns in regional growth is found, especially between core and periphery.Economic history; Economic geography; Regional growth; Wavelet analysis; Sweden;

The Investigation of the Low Temperature Combustion of Mesitylene and Tert-Amyl Methyl Ether by Synchrotron Photoionization Mass Spectrometry

This thesis describes the combustion experiments performed at the Chemical Dynamics Beamline of the Advanced Light Source (ALS) located at the Lawrence Berkeley National Laboratories (LBNL). The need for renewable fuel sources, the need for the study of their combustion in the contexts of homogenous charge combustion ignition (HCCI) engines can be found in Chapter 1. The components of the experimental set-up used throughout this thesis—time-of-flight mass spectrometer, Excimer laser, vacuum pumps and other components—and the components of ALS responsible in synchrotron radiation generation and processing—the linear accelerator, the booster ring, insertion devices, gas filters and monochromator are explained in Chapter 2. The data analysis method and the computational method used in the data analysis are expounded in Chapter 3. There are two combustion systems being investigated in this thesis. Mesitylene, an aromatic fuel additive, is proposed to be jet fuel, and its combustion is described in Chapter 4. Semi-biorenewable tert-amyl methyl ether (TAME) is studied in Chapter 5. Thermodynamic calculations, proposed mechanism, product identification and branching fractions are included in the analysis of the combustion of all these molecules

Stringent Nucleotide Recognition by the Ribosome at the Middle Codon Position.

Accurate translation of the genetic code depends on mRNA:tRNA codon:anticodon base pairing. Here we exploit an emissive, isosteric adenosine surrogate that allows direct measurement of the kinetics of codon:anticodon University of California base formation during protein synthesis. Our results suggest that codon:anticodon base pairing is subject to tighter constraints at the middle position than at the 5'- and 3'-positions, and further suggest a sequential mechanism of formation of the three base pairs in the codon:anticodon helix

Non-Parametric Estimation of Forecast Distributions in Non-Gaussian, Non-linear State Space Models

The object of this paper is to produce non-parametric maximum likelihood estimates of forecast distributions in a general non-Gaussian, non-linear state space setting. The transition densities that define the evolution of the dynamic state process are represented in parametric form, but the conditional distribution of the non-Gaussian variable is estimated non-parametrically. The filtering and prediction distributions are estimated via a computationally efficient algorithm that exploits the functional relationship between the observed variable, the state variable and a measurement error with an invariant distribution. Simulation experiments are used to document the accuracy of the non-parametric method relative to both correctly and incorrectly specified parametric alternatives. In an empirical illustration, the method is used to produce sequential estimates of the forecast distribution of realized volatility on the S&P500 stock index during the recent financial crisis. A resampling technique for measuring sampling variation in the estimated forecast distributions is also demonstrated.Probabilistic Forecasting; Non-Gaussian Time Series; Grid-based Filtering; Penalized Likelihood; Subsampling; Realized Volatility.