Analisi di una piattaforma di sviluppo per BPMN: Activiti

Si tratta di un'analisi della piattaforma di sviluppo per BPMN Activiti. Viene prima spiegata la notazione del Business Process Modeling e poi viene descritto il funzionamento e la struttura di Activiti. Infine viene spiegato come usare le API fornite insieme al motore.

Multiphase flow in porous media: meta-modeling techniques for sensitivity analysis and risk assessment

One of the biggest challenges that contaminant hydrogeology is facing, is how to adequately address the uncertainty associated with model predictions. Uncertainty arise from multiple sources, such as: interpretative error, calibration accuracy, parameter sensitivity and variability. This critical issue needs to be properly addressed in order to support environmental decision-making processes. In this study, we perform Global Sensitivity Analysis (GSA) on a contaminant transport model for the assessment of hydrocarbon concentration in groundwater. We provide a quantification of the environmental impact and, given the incomplete knowledge of hydrogeological parameters, we evaluate which are the most influential, requiring greater accuracy in the calibration process. Parameters are treated as random variables and a variance-based GSA is performed in a optimized numerical Monte Carlo framework. The Sobol indices are adopted as sensitivity measures and they are computed by employing meta-models to characterize the migration process, while reducing the computational cost of the analysis. The proposed methodology allows us to: extend the number of Monte Carlo iterations, identify the influence of uncertain parameters and lead to considerable saving computational time obtaining an acceptable accuracy.

Modeling Ultrafast Spectroscopy of the NADH Dimer: From UV-VIS to X-rays

Ultrafast pump-probe spectroscopy is a conceptually simple and versatile tool for resolving photoinduced dynamics in molecular systems. Due to the fast development of new experimental setups, such as synchrotron light sources and X-ray free electron lasers (XFEL), new spectral windows are becoming accessible. On the one hand, these sources have enabled scientist to access faster and faster time scales and to reach unprecedent insights into dynamical properties of matter. On the other hand, the complementarity of well-developed and novel techniques allows to study the same physical process from different points of views, integrating the advantages and overcoming the limitations of each approach. In this context, it is highly desirable to reach a clear understanding of which type of spectroscopy is more suited to capture a certain facade of a given photo-induced process, that is, to establish a correlation between the process to be unraveled and the technique to be used. In this thesis, I will show how computational spectroscopy can be a tool to establish such a correlation. I will study a specific process, which is the ultrafast energy transfer in the nicotinamide adenine dinucleotide dimer (NADH). This process will be observed in different spectral windows (from UV-VIS to X-rays), accessing the ability of different spectroscopic techniques to unravel the system evolution by means of state-of-the-art theoretical models and methodologies. The comparison of different spectroscopic simulations will demonstrate their complementarity, eventually allowing to identify the type of spectroscopy that is best suited to resolve the ultrafast energy transfer.

Investigating perceptual multisensory impairments in Autism through a neural network: a possible neural implementation for the shift from cross-modal competition to facilitation

Resolution of multisensory deficits has been observed in teenagers with Autism Spectrum Disorders (ASD) for complex, social speech stimuli; this resolution extends to more basic multisensory processing, involving low-level stimuli. In particular, a delayed transition of multisensory integration (MSI) from a default state of competition to one of facilitation has been observed in ASD children. In other terms, the complete maturation of MSI is achieved later in ASD. In the present study a neuro-computational model is used to reproduce some patterns of behavior observed experimentally, modeling a bisensory reaction time task, in which auditory and visual stimuli are presented in random sequence alone (A or V) or together (AV). The model explains how the default competitive state can be implemented via mutual inhibition between primary sensory areas, and how the shift toward the classical multisensory facilitation, observed in adults, is the result of inhibitory cross-modal connections becoming excitatory during the development. Model results are consistent with a stronger cross-modal inhibition in ASD children, compared to normotypical (NT) ones, suggesting that the transition toward a cooperative interaction between sensory modalities takes longer to occur. Interestingly, the model also predicts the difference between unisensory switch trials (in which sensory modality switches) and unisensory repeat trials (in which sensory modality repeats). This is due to an inhibitory mechanism, characterized by a slow dynamics, driven by the preceding stimulus and inhibiting the processing of the incoming one, when of the opposite sensory modality. These findings link the cognitive framework delineated by the empirical results to a plausible neural implementation.

Kinetic modeling for the synthesis of ethyl levulinate

This work is focused on studying the kinetics of esterification of levulinic acid in an isothermal batch reactor using ethanol as a reactant and as a protic polar solvent at the same time and in the presence of an acid catalyst (sulfuric acid). The choice of solvent is important as it affects the kinetics and thermodynamics of the reaction system moreover, the knowledge of the reaction kinetics plays an important role in the design of the process. This work is divided into two stages; The first stage is the experimental part in which the experimental matrix was developed by changing the process variables one at a time (temperature, molar ratio between reactants, and catalyst concentration) in order to study their influence on the kinetics; the second stage is using the obtained data from the experiments to build the modeling part in order to estimate the thermodynamics parameters.