Temperature effect on (2+1) experimental Kardar-Parisi-Zhang growth

We report on the effect of substrate temperature (T) on both local structure and long-wavelength fluctuations of polycrystalline CdTe thin films deposited on Si(001). A strong T-dependent mound evolution is observed and explained in terms of the energy barrier to inter-grain diffusion at grain boundaries, as corroborated by Monte Carlo simulations. This leads to transitions from uncorrelated growth to a crossover from random-to-correlated growth and transient anomalous scaling as T increases. Due to these finite-time effects, we were not able to determine the universality class of the system through the critical exponents. Nevertheless, we demonstrate that this can be circumvented by analyzing height, roughness and maximal height distributions, which allow us to prove that CdTe grows asymptotically according to the Kardar-Parisi-Zhang (KPZ) equation in a broad range of T. More important, one finds positive (negative) velocity excess in the growth at low (high) T, indicating that it is possible to control the KPZ non-linearity by adjusting the temperature.Comment: 6 pages, 5 figure

Cooperation between university and industry in the research of the suitability of agile methodologies in software development

Choosing a proper approach to manage a software development project is critical to increasing the chances to succeed in the venture. One of the great dilemmas nowadays concerns the option for an Agile or a traditional approach. There are several characteristics of software projects and the business environment in which they are carried out that must be considered while choosing the most appropriate development process. Although Agile development methodologies have been increasingly expanding and consolidating worldwide as an effective way of building software in the last two decades, they are not a one-size-fits-all approach. Knowing when to use Agile and which methodology is most suitable are the great questions that we aimed to answer in this study. In this paper, through a comprehensive revision of the Agile literature and an exploratory study, with the realization of focus group sessions with Agile practitioners and an interview with an Agile expert actively engaged in the software industry, we explored the characteristics of software development projects and organisational environments, identifying those that favour the use of an Agile approach. We also studied the main aspects that lead Agile teams to opt for one of the common Agile frameworks: Scrum, Extreme Programming (XP), Kanban, or Lean Software Development (LSD). The major goal of our study, clarifying the main aspects to be considered in the choice of an Agile methodology, is to support the decision-maker in the process of selecting an appropriate development approach.info:eu-repo/semantics/acceptedVersio

Personalized modeling for prediction with decision-path models

Deriving predictive models in medicine typically relies on a population approach where a single model is developed from a dataset of individuals. In this paper we describe and evaluate a personalized approach in which we construct a new type of decision tree model called decision-path model that takes advantage of the particular features of a given person of interest. We introduce three personalized methods that derive personalized decision-path models. We compared the performance of these methods to that of Classification And Regression Tree (CART) that is a population decision tree to predict seven different outcomes in five medical datasets. Two of the three personalized methods performed statistically significantly better on area under the ROC curve (AUC) and Brier skill score compared to CART. The personalized approach of learning decision path models is a new approach for predictive modeling that can perform better than a population approach