Review of ground-based measurements

Early measurements of the solar constant are described and discussed with particular emphasis on the Smithsonian program. A brief description is given of the monitoring program currently operating at San Diego State

Possible relationships between solar activity and atmospheric constituents

The large body of data on solar variations and atmospheric constituents collected between 1902 and 1953 by the Astrophysical Observatory of the Smithsonian Institution (APO) was examined. Short-term variations in amounts of atmospheric aerosols and water vapor due to seasonal changes, volcanic activity, air pollution, and frontal activity are discussed. Preliminary evidence indicates that increased solar activity is at times associated with a decrease in attenuation due to airborne particulates

Development of a Vibroacoustic Noise Prediction Model for Multi-Layered Concentric Cylinders Under Electromagnetic Forced Vibration

Vibracoustic noise prediction models for electrically excited cylinders are used to predict the noise emissions for operating dry-type air-core reactors. These reactors are used to limit current and regulate voltage in electrical transmission and distribution grids. During operation, these reactors produce unwanted, electrically induced noise which is created by forced vibration due to the generated magnetic field from the electrical load being applied to the coil. The reactors designed with complex constructions having multiple winding coils will produce greater amounts of structure-borne sound. Given that these dynamically behave as multiple layers of concentric cylinders, cylindrical vibration theory can be used to predict their behaviour. The goal of this research was to construct and validate an innovative vibracoustic prediction model that accurately represents the mechanisms of the structure-borne noise generation of the reactor to accurately predict the noise emission levels during the design phase.For the Trench Limited Coil Operations, having the ability to accurately predict the noise produced by a reactor in the early design stage is critical to maintain a competitive edge in the competitive reactor market by ensuring that acoustic specifications are met. A review of the literature has shown very little work has been done to develop the science to accurately predict the noise generation for complex reactor construction with multiple winding coil packages. Also, the validation process for the current models do not consider a large frequency range and various electrical excitation frequencies. The novelty of this research is the construction of a cylindrical vibroacoustic noise prediction model for complex reactors of multiple winding packages in conjunction with the validation across a wide range of electrical excitation frequencies.In this dissertation, a detailed test and literature review is simultaneously presented in order to guide the development of an improved vibroacoustic model and to validate the noise prediction outcomes. A comprehensive literature review found various vibroacoustic models have been developed to represent the vibrational excitation of the reactor cylinder, and in turn compute the output noise emissions. Comprehensive noise and vibration testing of two prototype reactors with induced electrical excitation was conducted using CPB, FFT, directivity, noise source identification (NSI) and Modal analysis. From these analyses, the construction of the model was guided by considering the natural structural modes. In addition, a bank of noise emission data for validation of the proposed models was complied. Through the validation process of comparing the proposed vibroacoustic models with the collected reactor noise data, a recommended method for noise prediction was developed. The models coined the Cylindrical Vibroacoustic Model (both single and multiple layered models) were deemed to be the most effective and accurate method for reactor noise prediction. The methodology considers the cylindrical construction of the reactor with multiple layers of concentric cylinders and has been validated over a large electrical excitation frequency range. The outcome of this more versatile vibroacoustic model is the ability to better predict the noise emissions for complex reactor constructions having multiple winding coil packages

Consumers response to different pricing systems in the performing arts industry

More research is required in the field of performing arts, whose link with business management is often weak and lacks specific theories and expertise. Performing arts’ revenues are undermined by external and internal barriers, such as reduced government spending, increased competition and shifting consumers’ needs. This results in organizations struggling in making ends meet and an audience participation rate that has not grown over the last two decades. Working on good pricing strategies becomes urgent, especially in a field were the relation between quality and price is difficult to assess, due to the nature of cultural products, and consumers often strive in taking purchase decisions. This thesis undertakes an experimental approach in order to investigate under which conditions consumers’ demand increases. Two pricing models are compared, subscription and membership, which respectively represent a more traditional and a more innovative form of loyalty. Additionally, the effect of a positive price anchor is tested, through the use of single ticket price information as a reference price. As expected, results confirmed a positive effect of the use of single ticket price information on demands for loyalty formulas as well as a higher demand for membership than for subscription, a less flexible pricing model. Additionally, main effects of demographic variables led to the definition of a proper target for membership, which showed its potential in not only retaining existing audience but also attracting new ones whose needs are so far not satisfied.É necessária mais pesquisa no domínio das artes performativas, cuja ligação com a gestão empresarial é frequentemente fraca e carece de teorias e competências específicas. As receitas das artes performativas são ameaçadas por barreiras externas e internas, como a redução dos gastos governamentais, o aumento da concorrência e a mudança das necessidades dos consumidores. Isso resulta em dificuldades para as organizações, que lutam para fazer face às despesas e uma taxa de participação da audiência que não cresceu nas últimas duas décadas. Desenvolver boas estratégias de preços torna-se urgente, especialmente num campo onde a relação qualidade/preço é difícil de avaliar. Esta tese desenvolve uma abordagem experimental para investigar em que condições aumenta a procura dos consumidores. Dois modelos de preços são comparados: Subscrição e Adesão (Associação), que representam respectivamente uma forma mais tradicional e mais inovadora de fidelidade. Adicionalmente, o efeito de uma âncora de preço positiva é testado, através da utilização da informação de preço de bilhete único como um preço de referência. Como esperado, os resultados confirmaram um efeito positivo da utilização de informações relativas ao preço do bilhete único sobre as fórmulas da procura de fidelidade, assim como uma maior procura por adesão do que pela assinatura (modelo de preços menos flexível). Além disso, os principais efeitos das variáveis demográficas levaram à definição de um alvo adequado para a adesão, o que mostrou o seu potencial não só para manter o público existente, mas também para atrair novo público, cujas necessidades até agora não são satisfeitas

Integrated computational extraction of cross-cancer poly-omic signatures

Understanding the interplay between metabolism and genetic regulation is considered key to shed light on the mechanisms underlying cancer onset and progression. In thiswork, we reconstruct a number of tumor-specific genome-scale metabolic models and inspect estimated flux profiles via statistical analysis, characterizing the detailed metabolicresponse associated to altered regulation in various tissues. We thus demonstrate that combining complementary computational techniques it is possible to identify polyomicdifferences and commonalities across cancer types

Predictive analytics of environmental adaptability in multi-omic network models.

Bacterial phenotypic traits and lifestyles in response to diverse environmental conditions depend on changes in the internal molecular environment. However, predicting bacterial adaptability is still difficult outside of laboratory controlled conditions. Many molecular levels can contribute to the adaptation to a changing environment: pathway structure, codon usage, metabolism. To measure adaptability to changing environmental conditions and over time, we develop a multi-omic model of Escherichia coli that accounts for metabolism, gene expression and codon usage at both transcription and translation levels. After the integration of multiple omics into the model, we propose a multiobjective optimization algorithm to find the allowable and optimal metabolic phenotypes through concurrent maximization or minimization of multiple metabolic markers. In the condition space, we propose Pareto hypervolume and spectral analysis as estimators of short term multi-omic (transcriptomic and metabolic) evolution, thus enabling comparative analysis of metabolic conditions. We therefore compare, evaluate and cluster different experimental conditions, models and bacterial strains according to their metabolic response in a multidimensional objective space, rather than in the original space of microarray data. We finally validate our methods on a phenomics dataset of growth conditions. Our framework, named METRADE, is freely available as a MATLAB toolbox

Poly-omic statistical methods describe cyanobacterial metabolic adaptation to fluctuating environments

In this work, a genome-scale metabolic model of Synechococcus sp. PCC 7002 which utilizes flux balance analysis across multiple layers is analyzed to observe flux response between 23 growth conditions. This is achieved by setting reactions involved in biomass accumulation and energy production as objectives for bi-level linear optimization, thus serving to improve the characterization of mechanisms underlying these processes in photoautotrophic microalgae. Additionally, the incorporation of statistical techniques such as k-means clustering and principal component analysis (PCA) contribute to reducing dimensionality and inferring latent patterns