The impact of measurement errors in the identification of regulatory networks

Background: There are several studies in the literature depicting measurement error in gene expression data and also, several others about regulatory network models. However, only a little fraction describes a combination of measurement error in mathematical regulatory networks and shows how to identify these networks under different rates of noise. Results: This article investigates the effects of measurement error on the estimation of the parameters in regulatory networks. Simulation studies indicate that, in both time series (dependent) and non-time series (independent) data, the measurement error strongly affects the estimated parameters of the regulatory network models, biasing them as predicted by the theory. Moreover, when testing the parameters of the regulatory network models, p-values computed by ignoring the measurement error are not reliable, since the rate of false positives are not controlled under the null hypothesis. In order to overcome these problems, we present an improved version of the Ordinary Least Square estimator in independent (regression models) and dependent (autoregressive models) data when the variables are subject to noises. Moreover, measurement error estimation procedures for microarrays are also described. Simulation results also show that both corrected methods perform better than the standard ones (i.e., ignoring measurement error). The proposed methodologies are illustrated using microarray data from lung cancer patients and mouse liver time series data. Conclusions: Measurement error dangerously affects the identification of regulatory network models, thus, they must be reduced or taken into account in order to avoid erroneous conclusions. This could be one of the reasons for high biological false positive rates identified in actual regulatory network models.

Theory manual to OctVCE – a cartesian cell CFD code with special application to blast wave problems, Department of Mechanical Engineering Report 2007/12

OctVCE is a cartesian cell CFD code produced especially for numerical simulations of shock and blast wave interactions with complex geometries, in particular, from explosions. Virtual Cell Embedding (VCE) was chosen as its cartesian cell kernel for its simplicity and sufficiency for practical engineering design problems. The code uses a finite-volume formulation of the unsteady Euler equations with a second order explicit Runge-Kutta Godonov (MUSCL) scheme. Gradients are calculated using a least-squares method with a minmod limiter. Flux solvers used are AUSM, AUSMDV and EFM. No fluid-structure coupling or chemical reactions are allowed, but gas models can be perfect gas and JWL or JWLB for the explosive products. This report also describes the code’s ‘octree’ mesh adaptive capability and point-inclusion query procedures for the VCE geometry engine. Finally, some space will also be devoted to describing code parallelization using the shared-memory OpenMP paradigm. The user manual to the code is to be found in the companion report 2007/13.

An economic evaluation of plasma production via erythroplasmapheresis and whole blood collection

This paper presents cost-effectiveness analyses (CEAs) of plasma collection via two alternative methods: whole blood collection (WBC) and erythroplasmapheresis collection (EPC). The objective of the study is to provide an answer to the question 'What is the least-cost method of plasma production'. This question is answered, both from the viewpoint of the blood collection agency (using financial CEA) and from that of 'society' as a whole (using economic CEA). We employ detailed financial data and economic survey data for collections made by a blood collection agency and to WBC and EPC donors in Brisbane, Australia. The results indicate that, despite the superior yield provided by EPC, WBC is actually more cost-effective. This result is robust to thorough sensitivity analysis and arises regardless of whether an economic or financial perspective is taken. We conclude that, ceteris paribus, the cost of recruiting new plasma donors would need to be quite substantial for marginal investments in EPC to be considered cost-effective. Crown Copyright (C) 2002 Published by Elsevier Science Ltd. All rights reserved.

Environmental factors associated with adults' participation in physical activity : A review

Background: Promoting physical activity is a public health priority, and changes in the environmental Contexts of adults' activity choices are believed to be crucial. However, of the factors associated with physical activity, environmental influences are among the least understood. Method: Using journal scans and computerized literature database searches, we identified 19 quantitative studies that assessed the relationships With physical activity behavior of perceived and objectively determined physical environment attributes. Findings were categorized into those examining five categories: accessibility of facilities, opportunities for activity, weather, safety, and aesthetic attributes. Results: Accessibility, opportunities, and aesthetic attributes had significant associations with physical activity, Weather and safety showed less-strong relationships. Where Studies pooled different categories to create composite variables, the associations were less likely to be statistically significant. Conclusions: Physical environment factors have consistent associations with physical activity behavior. Further development of ecologic and environmental models, together with behavior-specific and context-specific measurement strategies, should help in further understanding of these associations. Prospective Studies are required to identify possible causal relationships.

Influence of strawberry jam color and phenolic compounds on acceptance during storage

The objective of this study was to evaluate the influence of the color and phenolic compounds of strawberry jam on acceptance during storage. Jams were processed, stored for 120 days and evaluated monthly for chromatic characteristics, total phenolic compounds, total anthocyanins (ANT), total ellagic acid (TEA), flavonoids and free ellagic acid (FEA), and sensory acceptance as well. Data were submitted to analysis of variance (ANOVA) and the means were compared by the Least Significant Difference (LSD). Cluster Analysis and Partial Least Square Regression (PLS) were performed to investigate the relationships between instrumental data and acceptance. Contents of ANT, TEA and redness decreased during storage. Other chemical characteristics and sensory acceptance showed a nonlinear behavior. Higher acceptance was observed after 60 days, suggesting a trend of quality improvement followed by decline to the initial levels. The same trend was observed for lightness, non-pigment flavonoids and FEA. According to PLS map, for consumers in cluster 2, acceptance was associated to jams at 60 days and to luminosity, FEA, and non-pigment flavonoids. For cluster 1, a positive association between flavor liking, jam at initial storage, and the contents of TEA and ANT was indicated. Jams at 120 days were positively associated to hue and negatively associated to color liking, for cluster 1. Color and texture were positively correlated to overall liking for cluster 2, whereas for cluster 1, overall acceptance seemed to be more associated to flavor liking. Changes in color and phenolic compounds slightly influenced the acceptance of strawberry jams, but in different ways for consumers clusters.

Confiança organizacional e compartilhamento e uso do conhecimento tácito

Este estudo investiga a influência da confiança organizacional no desejo de usar e compartilhar o conhecimento tácito, baseado em hipóteses sobre a relação entre capacidade, benevolência e integridade nesse desejo. A amostra foi formada por 655 militares do Exército, instituição caracterizada por cultura de elevada exigência de confiança individual e organizacional, coletada em três instituições de formação de oficiais. O uso da técnica de modelagem de equações estruturais (partial least square) apresentou resultados que sugerem que esse desejo não é significativamente influenciado pela intensidade da confiança organizacional, definida com base na capacidade, benevolência e integridade dos indivíduos. Esses resultados refutam pesquisas anteriores de Holste e Fields, que destacam a influência do fator afeição no compartilhamento e o fator cognição no uso do conhecimento tácito, indicando a necessidade de compreender melhor os estímulos ao uso e compartilhamento do conhecimento dentro das estruturas organizacionais.

Monitoring the ex-vivo expansion of human mesenchymal stem/stromal cells in xeno-free microcarrier-based reactor systems by MIR spectroscopy

Human mesenchymal stem/stromal cells (MSCs) have received considerable attention in the field of cell-based therapies due to their high differentiation potential and ability to modulate immune responses. However, since these cells can only be isolated in very low quantities, successful realization of these therapies requires MSCs ex-vivo expansion to achieve relevant cell doses. The metabolic activity is one of the parameters often monitored during MSCs cultivation by using expensive multi-analytical methods, some of them time-consuming. The present work evaluates the use of mid-infrared (MIR) spectroscopy, through rapid and economic high-throughput analyses associated to multivariate data analysis, to monitor three different MSCs cultivation runs conducted in spinner flasks, under xeno-free culture conditions, which differ in the type of microcarriers used and the culture feeding strategy applied. After evaluating diverse spectral preprocessing techniques, the optimized partial least square (PLS) regression models based on the MIR spectra to estimate the glucose, lactate and ammonia concentrations yielded high coefficients of determination (R2 ≥ 0.98, ≥0.98, and ≥0.94, respectively) and low prediction errors (RMSECV ≤ 4.7%, ≤4.4% and ≤5.7%, respectively). Besides PLS models valid for specific expansion protocols, a robust model simultaneously valid for the three processes was also built for predicting glucose, lactate and ammonia, yielding a R2 of 0.95, 0.97 and 0.86, and a RMSECV of 0.33, 0.57, and 0.09 mM, respectively. Therefore, MIR spectroscopy combined with multivariate data analysis represents a promising tool for both optimization and control of MSCs expansion processes.

Comparative analysis of near and mid-infrared spectroscopy to monitor recombinant cyprosin production

Infrared spectroscopy, either in the near and mid (NIR/MIR) region of the spectra, has gained great acceptance in the industry for bioprocess monitoring according to Process Analytical Technology, due to its rapid, economic, high sensitivity mode of application and versatility. Due to the relevance of cyprosin (mostly for dairy industry), and as NIR and MIR spectroscopy presents specific characteristics that ultimately may complement each other, in the present work these techniques were compared to monitor and characterize by in situ and by at-line high-throughput analysis, respectively, recombinant cyprosin production by Saccharomyces cerevisiae. Partial least-square regression models, relating NIR and MIR-spectral features with biomass, cyprosin activity, specific activity, glucose, galactose, ethanol and acetate concentration were developed, all presenting, in general, high regression coefficients and low prediction errors. In the case of biomass and glucose slight better models were achieved by in situ NIR spectroscopic analysis, while for cyprosin activity and specific activity slight better models were achieved by at-line MIR spectroscopic analysis. Therefore both techniques enabled to monitor the highly dynamic cyprosin production bioprocess, promoting by this way more efficient platforms for the bioprocess optimization and control.

Modelação e identificação de motor DC

O modelo matemático de um sistema real permite o conhecimento do seu comportamento dinâmico e é geralmente utilizado em problemas de engenharia. Por vezes os parâmetros utilizados pelo modelo são desconhecidos ou imprecisos. O envelhecimento e o desgaste do material são fatores a ter em conta pois podem causar alterações no comportamento do sistema real, podendo ser necessário efetuar uma nova estimação dos seus parâmetros. Para resolver este problema é utilizado o software desenvolvido pela empresa MathWorks, nomeadamente, o Matlab e o Simulink, em conjunto com a plataforma Arduíno cujo Hardware é open-source. A partir de dados obtidos do sistema real será aplicado um Ajuste de curvas (Curve Fitting) pelo Método dos Mínimos Quadrados de forma a aproximar o modelo simulado ao modelo do sistema real. O sistema desenvolvido permite a obtenção de novos valores dos parâmetros, de uma forma simples e eficaz, com vista a uma melhor aproximação do sistema real em estudo. A solução encontrada é validada com recurso a diferentes sinais de entrada aplicados ao sistema e os seus resultados comparados com os resultados do novo modelo obtido. O desempenho da solução encontrada é avaliado através do método das somas quadráticas dos erros entre resultados obtidos através de simulação e resultados obtidos experimentalmente do sistema real.

Methacholine Dose-Response Slopes from Maximal Bronchial Challenge Tests in Asthmatic Children: Methodological Aspects

To determine whether the slope of a maximal bronchial challenge test (in which FEV1 falls by over 50%) could be extrapolated from a standard bronchial challenge test (in which FEV1 falls up to 20%), 14 asthmatic children performed a single maximal bronchial challenge test with methacholin(dose range: 0.097–30.08 umol) by the dosimeter method. Maximal dose-response curves were included according to the following criteria: (1) at least one more dose beyond a FEV1 ù 20%; and (2) a MFEV1 ù 50%. PD20 FEV1 was calculated, and the slopes of the early part of the dose-response curve (standard dose-response slopes) and of the entire curve (maximal dose-response slopes) were calculated by two methods: the two-point slope (DRR) and the least squares method (LSS) in % FEV1 × umol−1. Maximal dose-response slopes were compared with the corresponding standard dose-response slopes by a paired Student’s t test after logarithmic transformation of the data; the goodness of fit of the LSS was also determined. Maximal dose-response slopes were significantly different (p < 0.0001) from those calculated on the early part of the curve: DRR20% (91.2 ± 2.7 FEV1% z umol−1)was 2.88 times higher than DRR50% (31.6 ± 3.4 DFEV1% z umol−1), and the LSS20% (89.1 ± 2.8% FEV1 z umol−1) was 3.10 times higher than LSS 50% (28.8 ± 1.5%FEV1 z umol−1). The goodness of fit of LSS 50% was significant in all cases, whereas LSS 20% failed to be significant in one. These results suggest that maximal dose-response slopes cannot be predicted from the data of standard bronchial challenge tests.

Green IT adoption via virtualization

Dissertação apresentada como requisito parcial para obtenção do grau de Mestre em Estatística e Gestão de Informação

Analysis and simulation of social unrest in Europe: towards understanding social unrest in Europe

Dissertation submitted in partial fulfillment of the requirements for the Degree of Master of Science in Geospatial Technologies

The use of analytical hierarchy process in spatial decision support system for land use management

Geographic information systems give us the possibility to analyze, produce, and edit geographic information. Furthermore, these systems fall short on the analysis and support of complex spatial problems. Therefore, when a spatial problem, like land use management, requires a multi-criteria perspective, multi-criteria decision analysis is placed into spatial decision support systems. The analytic hierarchy process is one of many multi-criteria decision analysis methods that can be used to support these complex problems. Using its capabilities we try to develop a spatial decision support system, to help land use management. Land use management can undertake a broad spectrum of spatial decision problems. The developed decision support system had to accept as input, various formats and types of data, raster or vector format, and the vector could be polygon line or point type. The support system was designed to perform its analysis for the Zambezi river Valley in Mozambique, the study area. The possible solutions for the emerging problems had to cover the entire region. This required the system to process large sets of data, and constantly adjust to new problems’ needs. The developed decision support system, is able to process thousands of alternatives using the analytical hierarchy process, and produce an output suitability map for the problems faced.

Assessing Cybersecurity service quality in corporate environments

This study assess the quality of Cybersecurity as a service provided by IT department in corporate network and provides analysis about the service quality impact on the user, seen as a consumer of the service, and on the organization as well. In order to evaluate the quality of this service, multi-item instrument “SERVQUAL” was used for measuring consumer perceptions of service quality. To provide insights about Cybersecurity service quality impact, DeLone and McLean information systems success model was used. To test this approach, data was collected from over one hundred users from different industries and partial least square (PLS) was used to estimate the research model. This study found that SERVQUAL is adequate to assess Cybersecurity service quality and also found that Cybersecurity service quality positively influences the Cybersecurity use and individual impact in Cybersecurity.

Orthogonal models, structure crossing, nesting and inference

We intend to study the algebraic structure of the simple orthogonal models to use them, through binary operations as building blocks in the construction of more complex orthogonal models. We start by presenting some matrix results considering Commutative Jordan Algebras of symmetric matrices, CJAs. Next, we use these results to study the algebraic structure of orthogonal models, obtained by crossing and nesting simpler ones. Then, we study the normal models with OBS, which can also be orthogonal models. We intend to study normal models with OBS (Orthogonal Block Structure), NOBS (Normal Orthogonal Block Structure), obtaining condition for having complete and suffcient statistics, having UMVUE, is unbiased estimators with minimal covariance matrices whatever the variance components. Lastly, see ([Pereira et al. (2014)]), we study the algebraic structure of orthogonal models, mixed models whose variance covariance matrices are all positive semi definite, linear combinations of known orthogonal pairwise orthogonal projection matrices, OPOPM, and whose least square estimators, LSE, of estimable vectors are best linear unbiased estimator, BLUE, whatever the variance components, so they are uniformly BLUE, UBLUE. From the results of the algebraic structure we will get explicit expressions for the LSE of these models.