Texture analysis as a tool to study the kinetics of wet agglomeration processes

In this work wet granulation experiments were carried out in a planetary mixer with the aim to develop a novel analytical tool based on surface texture analysis. The evolution of a simple formulation (300 g of microcrystalline cellulose with a solid binders pre-dispersed in water) was monitored from the very beginning up to the end point and information on the kinetics of granulation as well as on the effect of liquid binder amount were collected. Agreement between texture analysis and granules particle size distribution obtained by sieving analysis was always found. The method proved to be robust enough to easily monitor the process and its use for more refined analyses on the different rate processes occurring during granulation is also suggested

Influence of process variables on the properties of simvastatin self-emulsifying granules obtained through high shear wet granulation

Improvements of the oral bioavailability of lipophilic drugs can be obtained using lipidic formulations such as the self-emulsifying drug delivery systems. The high shear wet granulation (HSWG), using microemulsions as binder, is a viable process to produce self-emulsifying granules. However only few information are present in the literature on the effect of process variables on the properties of the granules obtained with these binders. Consequently, this article compares the effects of some relevant experimental variables (impeller speed and massing time) on thefinal technological and pharmaceutical properties of the granules produced using simple water, or alternatively, a microemulsion as binder and containing simvastatin (SV) as model drug. The effects of the variables were determined by evaluating the granule median diameter, their particle size distribution, roundness, disintegration time and dissolution rate of SV. Results clearly demonstrated that the microemulsion-based process was less sensitive tooperating conditions than the water-based process. With microemulsion the nucleation process and growth regimes were more difficult to control, resulting in products with broader PSDs. At the same operatingconditions microemulsion-based granules were more brittle but rounder and showed smaller median diameter compared to water-based granules. The dissolution rate of simvastatin was not significantly affected by the operating conditions

Tecniche di documentazione dei tappeti musivi del sito archeologico di Umm Al-Rasas – Kastron Mefaa (Giordania)

The research expedition of the CNR-ITABC in the archaeological site of Umm Al-Rasas, near Madaba (Jordan) was partially supported by the Italian Foreign Ministry. It started in 2013 and was mainly focused on the 3D documentation of two Byzantine churches with magnificent floor mosaics, dedicated to Saint Stephen and Bishop Sergius respectively. To improve the analysis of the archaeological structures, different investigation techniques were used and reciprocally integrated, in an effort to create geometric models enabling the interpretation of data related to the masonry and floor mosaics, as well as to the documentation of the archaeological area. In order to facilitate handling and mobility, lightweight tools were chosen and Micro Photogrammetry and Close Range Photogrammetry methods were applied. A correct description of the floor warp was achieved thanks to laser scanner techniques and the resulting geometric data were integrated with the chromatic data coming from photogrammetry, obtaining a 3D restitution of the two adjacent structures and a metric and spatial analysis of their morphological features. New devices, specifically designed for the project, helped to solve some practical problems that the survey operations had to cope with during the fieldwork. This paper illustrates the results of the survey, which will be useful to develop restoration projects in order to make the whole archaeological site attractive to tourists

Computing Inferences for Large-Scale Continuous-Time Markov Chains by Combining Lumping with Imprecision

If the state space of a homogeneous continuous-time Markov chain is too large, making inferences - here limited to determining marginal or limit expectations - becomes computationally infeasible. Fortunately, the state space of such a chain is usually too detailed for the inferences we are interested in, in the sense that a less detailed - smaller - state space suffices to unambiguously formalise the inference. However, in general this so-called lumped state space inhibits computing exact inferences because the corresponding dynamics are unknown and/or intractable to obtain. We address this issue by considering an imprecise continuous-time Markov chain. In this way, we are able to provide guaranteed lower and upper bounds for the inferences of interest, without suffering from the curse of dimensionality.Comment: 9th International Conference on Soft Methods in Probability and Statistics (SMPS 2018

Rapidly-Disintegrating Laminar Extrudates: Preliminary Experiments upon an Age Appropriate Pediatric Formulation

The aim of the present investigation is to produce rapidly disintegrating laminar extrudates for delivering ibuprofen in the mouth of paediatric patients. This laminar shape is particularly convenient for drug delivering in the mouth and can be easily cut in cut in different sizes allowing for a convenient adjustment of the drug dose depending on the age of the patient. Due to the fact that in paediatric formulations, the selection of the excipients is always a challenging issue and the reduction of their amount is always highly desirable, in this study to select the most appropriate composition to achieve a rapid disintegration and simultaneously permit a high amount of ibuprofen in the system, an experimental design for mixtures was employed and the disintegration time in simulated saliva was used as experimental response. In addition, after solid state analyses to check possible insurgence of drug-excipients interactions, laminar extrudates were characterised in terms of mechanical properties and in vitro dissolution performances. Extrudates with the desired uniform laminar shape, constant thickness (2 mm) and a very high content of drug (82% wt) were produced. These products exhibited a short disintegration time. The dose for a patient of 6-12 years corresponded to a length of extrudate between 1-1.5 cm, perfectly compatible with a formulation orodispersible thin laminar extrudate intended for a paediatric patient (Figure 1)

Computing inferences for large-scale continuous-time Markov chains by combining lumping with imprecision

If the state space of a homogeneous continuous-time Markov chain is too large, making inferences—here limited to determining marginal or limit expectations—becomes computationally infeasible. Fortunately, the state space of such a chain is usually too detailed for the inferences we are interested in, in the sense that a less detailed—smaller—state space suffices to unambiguously formalise the inference. However, in general this so-called lumped state space inhibits computing exact inferences because the corresponding dynamics are unknown and/or intractable to obtain. We address this issue by considering an imprecise continuous-time Markov chain. In this way, we are able to provide guaranteed lower and upper bounds for the inferences of interest, without suffering from the curse of dimensionality

Advances in Choice Experiment for the evaluation of environmental goods and services

Over the last years, Choice Experiment (CE) methodology has increased its diffusion in several environmental contexts. Despite the increasing popularity of the method, there are still aspects that are not fully explored yet. In particular, the research areas explored in the thesis are: i) the analysis of the effect of information treatments in CEs; ii) the development of frameworks to include spatial variables in discrete choice models; iii) the analysis of the effect of individuals’ psychological traits on preferences towards environmental goods and services; iv) the comparison of existing model specifications which allow to account for preference heterogeneity. Most of the research questions were investigated by applying discrete choice modeling to data collected in two case studies: i) the analysis of social demand for landslide protection in Val del Boite (Veneto region), ii) the analysis of the demand of different heating system of households of the Veneto region. The remaining part of the analysis, instead, involved data generated by means of a simulation study. The thesis is organized in five chapters. Chapter 1 introduces the Choice Experiment method, outlines the research objectives and illustrates the case studies. Chapter 2 focuses on the exploration of the effect of information treatments on the stability of preference estimates and it is based on data analysis carried out from the first case study. Preferences were retrieved before and after providing respondents with scientific-based information, based on visual simulations of possible landslide events. This enabled to measure information effects. Choice data were used to estimate a Mixed Logit model (MXL) in WTP space to obtain robust estimates of marginal willingness-to-pay estimates and control for the effect of information. Overall, it was found that mWTP estimates are dependent on information. The geographical distribution of such effects was illustrated by means of maps of willingness to pay values. Chapters 3-4 illustrate analysis carried out on data retrieved from the second case study. Chapter 3 aims to analyze how geographical variables influence individuals’ sensitivity to key features of heating systems. A MXL model was estimated to spatially characterize preference heterogeneity. The results showed that geographical variables are in fact significant sources of variation of individual’s sensitivity to the investigated attributes of heating systems. Thematic maps were produced to illustrate the distribution of willingness to pay to avoid CO2 emissions across the region and to validate the estimates ex-post. Chapter 4 roots on previous theoretical evidence which suggests that beliefs and attitudes of individual consumers play a crucial role in the diffusion of innovative products. A Latent Class-Random Parameter (LC-RPL) model was estimated to analyze preferences of households for key features of ambient heating systems. The model specification allowed to evaluate the coherence of the underlying preference structure using as criteria psychological constructs from the Theory of Diffusion of Innovation by Rogers. The results broadly support this theory by providing evidence of segmentation of the population consistent with the individuals’ propensity to adopt innovations. It was also found that preferences for heating systems and respondents’ willingness to pay for their key features vary across segments. Chapter 5 illustrates the results of a Monte-Carlo experiment aimed at retrieving the required number of parameters and sample sizes to obtain good approximations of true distributions with Logit-mixed logit (LML) models. These models were recently introduced by Train (2016) and are a key advancement in methods to represent the random taste heterogeneity in logit-type models as they generalize many previous parametric and seminonparametric specifications. The performance of LML models are also compared with those of parametric specifications based on normal mixing distributions. The results suggest that LML models outperform parametric models only at large sample sizes. LML Mmdel specifications with large number of parameters outperformed those with small number parameters only at large sample sizes as well. Finally, chapter 6 draws the conclusions of the thesis