Implementation of an intelligent sensor for measurement and prediction of solar radiation and atmospheric temperature

Dissertação de mestrado, Engenharia Electrónica e Telecomunicações, Faculdade de Ciências e Tecnologia, Universidade do Algarve, 2011

Prediction of peptide and protein propensity for amyloid formation

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Large-scale prediction of seagrass distribution: the case of Cymodocea nodosa (Mediterranean-Atlantic)

Understanding the factors that affect seagrass meadows encompassing their entire range of distribution is challenging yet important for their conservation. We model the environmental niche of Cymodocea nodosa using a combination of environmental variables and landscape metrics to examine factors defining its distribution and find suitable habitats for the species. The most relevant environmental variables defining the distribution of C. nodosa were sea surface temperature (SST) and salinity. We found suitable habitats at SST from 5.8 ºC to 26.4 ºC and salinity ranging from 17.5 to 39.3. Optimal values of mean winter wave height ranged between 1.2 m and 1.5 m, while waves higher than 2.5 m seemed to limit the presence of the species. The influence of nutrients and pH, despite having weight on the models, was not so clear in terms of ranges that confine the distribution of the species. Landscape metrics able to capture variation in the coastline enhanced significantly the accuracy of the models, despite the limitations caused by the scale of the study. By contrasting predictive approaches, we defined the variables affecting the distributional areas that seem unsuitable for C. nodosa as well as those suitable habitats not occupied by the species. These findings are encouraging for its use in future studies on climate-related marine range shifts and meadow restoration projects of these fragile ecosystems.

Protein expression of Myt272-3 recombinant clone and in silico prediction of a possible vaccine candidate against Mycobacterium tuberculosis

Purpose: To investigate the expression of Myt272-3 recombinant protein and also to predict a possible protein vaccine candidate against Mycobacterium tuberculosis . Methods: Myt272-3 protein was expressed in pET30a+-Myt272-3 clone. The purity of the protein was determined using Dynabeads® His-Tag Isolation & Pulldown. Protein sequence was analysed in silico using bioinformatics software for the prediction of allergenicity, antigenicity, MHC-I and MHC-II binding, and B-cell epitope binding. Results: The candidate protein was a non-allergen with 15.19 % positive predictive value. It was also predicted to be antigenic, with binding affinity to MHC-I and MHC-II, as well as B-cell epitope binding. Conclusion: The predicted results obtained in this study provide a guide for practical design of a new tuberculosis vaccine.

Modern Computational Chemistry Methods for Prediction of Ground- and Excited-State Properties in Open-Shell Systems

The main goal of the research presented in this work is to provide some important insights about computational modeling of open-shell species. Such projects are: the investigation of the size-extensivity error in Equation-of-Motion Coupled Cluster methods, the analysis of the Long-Range corrected scheme in predicting UV-Vis spectra of Cu(II) complexes with the 4-imidazole acetate and its ethylated derivative, and the exploration of the importance of choosing a proper basis set for the description of systems such as the lithium monoxide anion. The most significant findings of this research are: (i) The contribution of the left operator to the size-extensivity error of the CR-EOMCC(2,3) approach, (ii) The cause of d-d shifts when varying the range-separation parameter and the amount of the exact exchange arising from the imbalanced treatment of localized vs. delocalized orbitals via the "tuned" CAM-B3LYP* functional, (iii) The proper acidity trend of the first-row hydrides and their lithiated analogs that may be reversed if the basis sets are not correctly selected.

COMPUTATIONAL PREDICTION OF THE SPORULATION NETWORK IN CLOSTRIDIUM THERMOCELLUM

Sporulation is a process in which some bacteria divide asymmetrically to form tough protective endospores, which help them to survive in a hazardous environment for a quite long time. The factors which can trigger this process are diverse. Heat, radiation, chemicals and lacking of nutrition can all lead to the formation of endospores. This phenomenon will lead to low productivity during industrial production. However, the sporulation mechanism in a spore-forming bacterium, Clostridium theromcellum, is still unclear. Therefore, if a regulation network of sporulation can be built, we may figure out ways to inhibit this process. In this study, a computational method is applied to predict the sporulation network in Clostridium theromcellum. A working sporulation network model with 40 new predicted genes and 4 function groups is built by using a network construction program, CINPER. 5 sets of microarray expression data in Clostridium theromcellum under different conditions have been collected. The analysis shows the predicted result is reasonable.

The Performance and Service Life Prediction of High Performance Concrete in Sulfate and Acidic Environments

Concrete substructures are often subjected to environmental deterioration, such as sulfate and acid attack, which leads to severe damage and causes structure degradation or even failure. In order to improve the durability of concrete, the High Performance Concrete (HPC) has become widely used by partially replacing cement with pozzolanic materials. However, HPC degradation mechanisms in sulfate and acidic environments are not completely understood. It is therefore important to evaluate the performance of the HPC in such conditions and predict concrete service life by establishing degradation models. This study began with a review of available environmental data in the State of Florida. A total of seven bridges have been inspected. Concrete cores were taken from these bridge piles and were subjected for microstructural analysis using Scanning Electron Microscope (SEM). Ettringite is found to be the products of sulfate attack in sulfate and acidic condition. In order to quantitatively analyze concrete deterioration level, an image processing program is designed using Matlab to obtain quantitative data. Crack percentage (Acrack/Asurface) is used to evaluate concrete deterioration. Thereafter, correlation analysis was performed to find the correlation between five related variables and concrete deterioration. Environmental sulfate concentration and bridge age were found to be positively correlated, while environmental pH level was found to be negatively correlated. Besides environmental conditions, concrete property factor was also included in the equation. It was derived from laboratory testing data. Experimental tests were carried out implementing accelerated expansion test under controlled environment. Specimens of eight different mix designs were prepared. The effect of pozzolanic replacement rate was taken into consideration in the empirical equation. And the empirical equation was validated with existing bridges. Results show that the proposed equations compared well with field test results with a maximum deviation of ± 20%. Two examples showing how to use the proposed equations are provided to guide the practical implementation. In conclusion, the proposed approach of relating microcracks to deterioration is a better method than existing diffusion and sorption models since sulfate attack cause cracking in concrete. Imaging technique provided in this study can also be used to quantitatively analyze concrete samples.

Meshfree Method for Prediction of Thermal Properties of Porous Ceramic Materials

In the presented thesis work, meshfree method with distance fields is applied to create a novel computational approach which enables inclusion of the realistic geometric models of the microstructure and liberates Finite Element Analysis(FEA) from thedependance on and limitations of meshing of fine microstructural feature such as splats and porosity.Manufacturing processes of ceramics produce materials with complex porosity microstructure.Geometry of pores, their size and location substantially affect macro scale physical properties of the material. Complex structure and geometry of the pores severely limit application of modern Finite Element Analysis methods because they require construction of spatial grids (meshes) that conform to the geometric shape of the structure. As a result, there are virtually no effective tools available for predicting overall mechanical and thermal properties of porous materials based on their microstructure. This thesis is a separate handling and controls of geometric and physical computational models that are seamlessly combined at solution run time. Using the proposedapproach we will determine the effective thermal conductivity tensor of real porous ceramic materials featuring both isotropic and anisotropic thermal properties. This work involved development and implementation of numerical algorithms, data structure, and software.

Motivated reasoning in the prediction of sports outcomes and the belief in the “hot hand”

The present paper explores the role of motivation to observe a certain outcome in people's predictions, causal attributions, and beliefs about a streak of binary outcomes (basketball scoring shots). In two studies we found that positive streaks (points scored by the participants' favourite team) lead participants to predict the streak's continuation (belief in the hot hand), but negative streaks lead to predictions of its end (gambler's fallacy). More importantly, these wishful predictions are supported by strategic attributions and beliefs about how and why a streak might unfold. Results suggest that the effect of motivation on predictions is mediated by a serial path via causal attributions to the teams at play and belief in the hot hand.

Change, stability and prediction of gross motor co-ordination in portuguese children

The knowledge about intra- and inter-individual variation can stimulate attempts at description, interpretation and prediction of motor co-ordination (MC). Aim: To analyse change, stability and prediction of motor co-ordination (MC) in children. Subjects and methods: A total of 158 children, 83 boys and 75 girls, aged 6, 7 and 8 years, were evaluated in 2006 and re-evaluated in 2012 at 12, 13 and 14 years of age. MC was assessed through the Kiphard-Schilling’s body co-ordination test and growth, skeletal maturity, physical fitness, fundamental motor skills (FMS), physical activity and socioeconomic status (SES) were measured and/or estimated. Results: Repeated-measures MANOVA indicated that there was a significant effect of group, sex and time on a linear combination of the MC tests. Univariate tests revealed that group 3 (8–14 years) scored significantly better than group 1 (6–12 years) in all MC tests and boys performed better than girls in hopping for height and moving sideways. Scores in MC were also higher at follow-up than at baseline. Inter-age correlations for MC were between 0.15–0.74. Childhood predictors of MC were growth, physical fitness, FMS, physical activity and SES. Biological maturation did not contribute to prediction of MC. Conclusion: MC seemed moderately stable from childhood through adolescence and, additionally, inter-individual predictors at adolescence were growth, FMS, physical fitness, physical activity and SES.

Prediction of adult height in girls: the Beunen-MalinaFreitas method

The purpose of this study was to validate and cross-validate the Beunen-Malina-Freitas method for non-invasive prediction of adult height in girls. A sample of 420 girls aged 10–15 years from the Madeira Growth Study were measured at yearly intervals and then 8 years later. Anthropometric dimensions (lengths, breadths, circumferences, and skinfolds) were measured; skeletal age was assessed using the Tanner-Whitehouse 3 method and menarcheal status (present or absent) was recorded. Adult height was measured and predicted using stepwise, forward, and maximum R2 regression techniques. Multiple correlations, mean differences, standard errors of prediction, and error boundaries were calculated. A sample of the Leuven Longitudinal Twin Study was used to cross-validate the regressions. Age-specific coefficients of determination (R2) between predicted and measured adult height varied between 0.57 and 0.96, while standard errors of prediction varied between 1.1 and 3.9 cm. The cross-validation confirmed the validity of the Beunen-Malina-Freitas method in girls aged 12–15 years, but at lower ages the cross-validation was less consistent. We conclude that the Beunen-Malina-Freitas method is valid for the prediction of adult height in girls aged 12–15 years. It is applicable to European populations or populations of European ancestry.

Structured professional judgement approach to risk assessment: generalisability across patient groups for the prediction of adverse outcomes in secure mental health care

This is a redacted version of the the final thesis. Copyright material has been removed to comply with UK Copyright Law.

An Analysis of the Early Prediction of Highway Construction Project Completion using the Contract Status Report

History has shown that projects move in and out of poor status through the life of the project. Predicting the success or failure of a project to complete on time because of its recent history on the contract status report could provide our project managers another tool for monitoring contract progress. In many instances, poor contract progress results in the loss of contract time and late completion of projects. This research evaluates the combinations of work type, point in time physical work begins, recent poor status, and contract bid amount as indicators of late project completion.

Change, stability and prediction of gross motor co-ordination in portuguese children

The knowledge about intra- and inter-individual variation can stimulate attempts at description, interpretation and prediction of motor co-ordination (MC). Aim: To analyse change, stability and prediction of motor co-ordination (MC) in children. Subjects and methods: A total of 158 children, 83 boys and 75 girls, aged 6, 7 and 8 years, were evaluated in 2006 and re-evaluated in 2012 at 12, 13 and 14 years of age. MC was assessed through the Kiphard-Schilling’s body co-ordination test and growth, skeletal maturity, physical fitness, fundamental motor skills (FMS), physical activity and socioeconomic status (SES) were measured and/or estimated. Results: Repeated-measures MANOVA indicated that there was a significant effect of group, sex and time on a linear combination of the MC tests. Univariate tests revealed that group 3 (8–14 years) scored significantly better than group 1 (6–12 years) in all MC tests and boys performed better than girls in hopping for height and moving sideways. Scores in MC were also higher at follow-up than at baseline. Inter-age correlations for MC were between 0.15–0.74. Childhood predictors of MC were growth, physical fitness, FMS, physical activity and SES. Biological maturation did not contribute to prediction of MC. Conclusion: MC seemed moderately stable from childhood through adolescence and, additionally, inter-individual predictors at adolescence were growth, FMS, physical fitness, physical activity and SES.