Reduced ceria nanofilms from structure prediction

Experimentally, Ce2O3 films are used to study cerium oxide in its fully or partially reduced state, as present in many applications. We have explored the space of low energy Ce2O3 nanofilms using structure prediction and density functional calculations, yielding more than 30 distinct nanofilm structures. First, our results help to rationalize the roles of thermodynamics and kinetics in the preparation of reduced ceria nanofilms with different bulk crystalline structures (e.g. A-type or bixbyite) depending on the support used. Second, we predict a novel, as yet experimentally unresolved, nanofilm which has a structure that does not correspond to any previously reported bulk A2B3 phase and which has an energetic stability between that of A-type and bixbyite. To assist identification and fabrication of this new Ce2O3 nanofilm we calculate some observable properties and propose supports for its epitaxial growth.

Prediction of individual automobile RBNS claim reserves in the context of Solvency II

Automobile bodily injury (BI) claims remain unsettled for a long time after the accident. The estimation of an accurate reserve for Reported But Not Settled (RBNS) claims is therefore vital for insurers. In accordance with the recommendation included in the Solvency II project (CEIOPS, 2007) a statistical model is here implemented for RBNS reserve estimation. Lognormality on empirical compensation cost data is observed for different levels of BI severity. The individual claim provision is estimated by allocating the expected mean compensation for the predicted severity of the victim’s injury, for which the upper bound is also computed. The BI severity is predicted by means of a heteroscedastic multiple choice model, because empirical evidence has found that the variability in the latent severity of injured individuals travelling by car is not constant. It is shown that this methodology can improve the accuracy of RBNS reserve estimation at all stages, as compared to the subjective assessment that has traditionally been made by practitioners.

Optimal latent period in a bacteriophage population model structured by infection-age

We study the lysis timing of a bacteriophage population by means of a continuously infection-age-structured population dynamics model. The features of the model are the infection process of bacteria, the death process, and the lysis process which means the replication of bacteriophage viruses inside bacteria and the destruction of them. The time till lysis (or latent period) is assumed to have an arbitrary distribution. We have carried out an optimization procedure, and we have found that the latent period corresponding to maximal fitness (i.e. maximal growth rate of the bacteriophage population) is of fixed length. We also study the dependence of the optimal latent period on the amount of susceptible bacteria and the number of virions released by a single infection. Finally, the evolutionarily stable strategy of the latent period is also determined as a fixed period taking into account that super-infections are not considered

Minimization of the experimental workload for the prediction of pollutants propagation in rivers. Mathematical modelling and knowledge re-use

The present thesis in focused on the minimization of experimental efforts for the prediction of pollutant propagation in rivers by mathematical modelling and knowledge re-use. Mathematical modelling is based on the well known advection-dispersion equation, while the knowledge re-use approach employs the methods of case based reasoning, graphical analysis and text mining. The thesis contribution to the pollutant transport research field consists of: (1) analytical and numerical models for pollutant transport prediction; (2) two novel techniques which enable the use of variable parameters along rivers in analytical models; (3) models for the estimation of pollutant transport characteristic parameters (velocity, dispersion coefficient and nutrient transformation rates) as functions of water flow, channel characteristics and/or seasonality; (4) the graphical analysis method to be used for the identification of pollution sources along rivers; (5) a case based reasoning tool for the identification of crucial information related to the pollutant transport modelling; (6) and the application of a software tool for the reuse of information during pollutants transport modelling research. These support tools are applicable in the water quality research field and in practice as well, as they can be involved in multiple activities. The models are capable of predicting pollutant propagation along rivers in case of both ordinary pollution and accidents. They can also be applied for other similar rivers in modelling of pollutant transport in rivers with low availability of experimental data concerning concentration. This is because models for parameter estimation developed in the present thesis enable the calculation of transport characteristic parameters as functions of river hydraulic parameters and/or seasonality. The similarity between rivers is assessed using case based reasoning tools, and additional necessary information can be identified by using the software for the information reuse. Such systems represent support for users and open up possibilities for new modelling methods, monitoring facilities and for better river water quality management tools. They are useful also for the estimation of environmental impact of possible technological changes and can be applied in the pre-design stage or/and in the practical use of processes as well.

Application of GA-PLS and GA-KPLS calculations for the prediction of the retention indices of essential oils

Genetic algorithm and partial least square (GA-PLS) and kernel PLS (GA-KPLS) techniques were used to investigate the correlation between retention indices (RI) and descriptors for 117 diverse compounds in essential oils from 5 Pimpinella species gathered from central Turkey which were obtained by gas chromatography and gas chromatography-mass spectrometry. The square correlation coefficient leave-group-out cross validation (LGO-CV) (Q²) between experimental and predicted RI for training set by GA-PLS and GA-KPLS was 0.940 and 0.963, respectively. This indicates that GA-KPLS can be used as an alternative modeling tool for quantitative structure-retention relationship (QSRR) studies.

Models and applications for risk assessment and prediction of Asian soybean rust epidemics

Asian rust of soybean [Glycine max (L.) Merril] is one of the most important fungal diseases of this crop worldwide. The recent introduction of Phakopsora pachyrhizi Syd. & P. Syd in the Americas represents a major threat to soybean production in the main growing regions, and significant losses have already been reported. P. pachyrhizi is extremely aggressive under favorable weather conditions, causing rapid plant defoliation. Epidemiological studies, under both controlled and natural environmental conditions, have been done for several decades with the aim of elucidating factors that affect the disease cycle as a basis for disease modeling. The recent spread of Asian soybean rust to major production regions in the world has promoted new development, testing and application of mathematical models to assess the risk and predict the disease. These efforts have included the integration of new data, epidemiological knowledge, statistical methods, and advances in computer simulation to develop models and systems with different spatial and temporal scales, objectives and audience. In this review, we present a comprehensive discussion on the models and systems that have been tested to predict and assess the risk of Asian soybean rust. Limitations, uncertainties and challenges for modelers are also discussed.

Evaluating the success of software development projects in Russia, Ukraine, and Belarus

The size and complexity of projects in the software development are growing very fast. At the same time, the proportion of successful projects is still quite low according to the previous research. Although almost every project's team knows main areas of responsibility which would help to finish project on time and on budget, this knowledge is rarely used in practice. So it is important to evaluate the success of existing software development projects and to suggest a method for evaluating success chances which can be used in the software development projects. The main aim of this study is to evaluate the success of projects in the selected geographical region (Russia-Ukraine-Belarus). The second aim is to compare existing models of success prediction and to determine their strengths and weaknesses. Research was done as an empirical study. A survey with structured forms and theme-based interviews were used as the data collection methods. The information gathering was done in two stages. At the first stage, project manager or someone with similar responsibilities answered the questions over Internet. At the second stage, the participant was interviewed; his or her answers were discussed and refined. It made possible to get accurate information about each project and to avoid errors. It was found out that there are many problems in the software development projects. These problems are widely known and were discussed in literature many times. The research showed that most of the projects have problems with schedule, requirements, architecture, quality, and budget. Comparison of two models of success prediction presented that The Standish Group overestimates problems in project. At the same time, McConnell's model can help to identify problems in time and avoid troubles in future. A framework for evaluating success chances in distributed projects was suggested. The framework is similar to The Standish Group model but it was customized for distributed projects.

Structured software development with the IPIDDDT method - A lean method for small agile organizations

A software development process is a predetermined sequence of steps to create a piece of software. A software development process is used, so that an implementing organization could gain significant benefits. The benefits for software development companies, that can be attributed to software process improvement efforts, are improved predictability in the development effort and improved quality software products. The implementation, maintenance, and management of a software process as well as the software process improvement efforts are expensive. Especially the implementation phase is expensive with a best case scenario of a slow return on investment. Software processes are rare in very small software development companies because of the cost of implementation and an improbable return on investment. This study presents a new method to enable benefits that are usually related to software process improvement to small companies with a low cost. The study presents reasons for the development of the method, a description of the method, and an implementation process for the method, as well as a theoretical case study of a method implementation. The study's focus is on describing the method. The theoretical use case is used to illustrate the theory of the method and the implementation process of the method. The study ends with a few conclusions on the method and on the method's implementation process. The main conclusion is that the method requires further study as well as implementation experiments to asses the value of the method.

Comparação de taxas de erosão em estradas florestais estimadas pelo modelo WEPP (Water Erosion Prediction Project) modificado em relção a medições experimentais

O objetivo do trabalho foi testar o modelo WEPP (Water Erosion Prediction Project), através de comparações entre volume de enxurrada e perda de solo observados experimentalmente, provenientes dos segmentos de estradas florestais submetidas à chuva natural com inclinações de 1 e 7% e comprimentos de rampa de 20 e 40 m, e aqueles preditos pelo aplicativo, visando o desenvolvimento de um modelo brasileiro de predição de erosão em estradas florestais. Na determinação da quantidade do material erodido foram instalados tambores coletores, com capacidade de 209,25 litros, localizados na parte inferior das estradas, onde foram inseridas tubulações de PVC de 2 polegadas para coleta dos sedimentos provenientes da estrada propriamente dita. Nos tambores coletores foram feitos orifícios nivelados e perfeitamente iguais, posicionados a 0,65 m do fundo do primeiro e a 0,60 m do fundo do segundo, que funcionaram como um divisor Geib. Nas parcelas de 20 e 40 m de comprimento foram feitos cinco e sete orifícios, respectivamente, no primeiro e segundo tambores. O terceiro tambor foi utilizado para coletar o excedente da enxurrada proveniente do segundo tambor. Os tambores foram ligados em série, através de cano PVC de 2 polegadas. Os dados de volume e intensidade de precipitação diária foram obtidos com a instalação de pluviômetro e pluviógrafo no local. O período de coleta de dados foi de um ano, concentrando-se na época das chuvas. Posteriormente, os arquivos de clima, precipitação, solo, inclinação e comprimento do segmento foram introduzidos e adaptados ao modelo de predição de erosão WEPP com o propósito de testá-lo, visando a confecção de um modelo apropriado às condições brasileiras.

Experiences in using a structured method in finding and defining new innovations: the strategic options approach

Investment decision-making on far-reaching innovation ideas is one of the key challenges practitioners and academics face in the field of innovation management. However, the management practices and theories strongly rely on evaluation systems that do not fit in well with this setting. These systems and practices normally cannot capture the value of future opportunities under high uncertainty because they ignore the firm’s potential for growth and flexibility. Real options theory and options-based methods have been offered as a solution to facilitate decision-making on highly uncertain investment objects. Much of the uncertainty inherent in these investment objects is attributable to unknown future events. In this setting, real options theory and methods have faced some challenges. First, the theory and its applications have largely been limited to market-priced real assets. Second, the options perspective has not proved as useful as anticipated because the tools it offers are perceived to be too complicated for managerial use. Third, there are challenges related to the type of uncertainty existing real options methods can handle: they are primarily limited to parametric uncertainty. Nevertheless, the theory is considered promising in the context of far-reaching and strategically important innovation ideas. The objective of this dissertation is to clarify the potential of options-based methodology in the identification of innovation opportunities. The constructive research approach gives new insights into the development potential of real options theory under non-parametric and closeto- radical uncertainty. The distinction between real options and strategic options is presented as an explanans for the discovered limitations of the theory. The findings offer managers a new means of assessing future innovation ideas based on the frameworks constructed during the course of the study.

Growth and yield prediction using the modified Buckman model

A model to manage even-aged stands was developed using a modification of the Buckman model. Data from Eucalyptus urophylla and Eucalyptus cloeziana stands located in the Northern region of Minas Gerais State, Brazil were used in the formulation of the system. The proposed model generated precise and unbiased estimates in non-thinned stands.

DYNAMICS AND PREDICTION OF DIAMETRIC STRUCTURE IN TWO ATLANTIC FOREST FRAGMENTS IN NORTHEASTERN BRAZIL

ABSTRACT Monitoring analyses aim to understand the processes that drive changes in forest structure and, along with prediction studies, may assist in the management planning and conservation of forest remnants. The objective of this study was to analyze the forest dynamics in two Atlantic rainforest fragments in Pernambuco, Brazil, and to predict their future forest diameter structure using the Markov chain model. We used continuous forest inventory data from three surveys in two forest fragments of 87 ha (F1) and 388 ha (F2). We calculated the annual rates of mortality and recruitment, the mean annual increment, and the basal area for each of the 3-year periods. Data from the first and second surveys were used to project the third inventory measurements, which were compared to the observed values in the permanent plots using chi-squared tests (a = 0.05). In F1, a decrease in the number of individuals was observed due to mortality rates being higher than recruitment rates; however, there was an increase in the basal area. In this fragment, the fit to the Markov model was adequate. In F2, there was an increase in both the basal area and the number of individuals during the 6-year period due to the recruitment rate exceeding the mortality rate. For this fragment, the fit of the model was unacceptable. Hence, for the studied fragments, the demographic rates influenced the stem density more than the floristic composition. Yet, even with these intense dynamics, both fragments showed active growth.