Role of modelling on state and parameter estimation

In process industry, plants are generally operated at conditions that differ from the designed ones mainly due to disturbances. Disturbances can enter the system in form of fluctuations in feed flow, temperature and composition, or fluctuation of the utilities quality. These events cause a deterioration of the plant performance that cannot be quantified and online compensated by means of controllers unless online measurements of the quality targets (e.g. concentration, conversion, etc) are available. However the problem of online monitoring cannot be always solved in practice by means of hardware analysers because of unreliable and delayed measurements. An alternative approach is based on estimators that infer the variables of interests by means of secondary measurements and a often nonlinear model of the process. This type of realization of observers can include the online estimation of model parameters for a more accurate alignment of the model with the process behaviour. This work addresses the role of the estimation model on estimation performance. Recent studies [1, 2] pointed out that for a defined set of plant measurements the choice of the estimation model and the innovated states play a key role on the performance of the estimator regardless the algorithm employed. Even if in the cited studies some features of the estimation model (such as level of detail, computational complexity) have been taken into account, the effect on the estimation performance of model manipulations such as variables and parameters scaling [3] and transformation have not been investigated yet. For this reason the role of different realizations of the same estimation model needs to be further investigated

On the model-based monitoring of industrial batch crystallizers

Crystallization is an important separation process to obtain high value-added chemicals in crystalline form from liquid solution in pharmaceutical, food and fine chemical industries. As most of the particulate processes, the quality of the solid product is determined by its particle size distribution (PSD). The achievement of the desired quality targets of the fine crystalline products relies on an efficient online process monitoring for separation supervision and control. However, hardware analyzers able to online measure the PSD and the solute concentration are rarely available, due to their costs \cite{Multi}. These unmeasured process variables can be estimated by state estimators that combine information from the process model and secondary measurements. The problem of designing state observers for online monitoring the PSD evolution has been mostly addressed under the assumption that some PSD measurements were available (see \cite{Mesb} and literature therein), which is not likely in practice. This work proposes a methodology to asses the feasibility of using common measurements (e.g. temperature and liquid fraction) for estimation purposes based on local observability \cite{Herm} and detectability \cite{AlFer} arguments. The results are supported using a data-derived technique, with data generated by a simulation model of the industrial crystallizer. Based on the results of the observability analysis, the structure of a state estimator is proposed

Role of modelling on state and parameter estimation

In process industry, plants are generally operated at conditions that differ from the designed ones mainly due to disturbances. Disturbances can enter the system in form of fluctuations in feed flow, temperature and composition, or fluctuation of the utilities quality. These events cause a deterioration of the plant performance that cannot be quantified and online compensated by means of controllers unless online measurements of the quality targets (e.g. concentration, conversion, etc) are available. However the problem of online monitoring cannot be always solved in practice by means of hardware analysers because of unreliable and delayed measurements. An alternative approach is based on estimators that infer the variables of interests by means of secondary measurements and a often nonlinear model of theprocess. This type of realization of observers can include the online estimation of model parameters for a more accurate alignment of the model with the process behaviour.This work addresses the role of the estimation model on estimation performance. Recent studies [1, 2] pointed out that for a defined set of plant measurements the choice of the estimation model and the innovated states play a key role on the performance of the estimator regardless the algorithm employed. Even if in the cited studies some features of the estimation model (such as level of detail, computational complexity) have been taken into account, the effect on the estimation performance of model manipulations such as variables and parameters scaling [3] and transformation have not been investigated yet. For this reason the role of different realizations of the same estimation model needs to be further investigated

A multistage design procedure for planning and implementing public charging infrastructures for electric vehicles

Presented in this paper is a Multistage Design Procedure (MSDP) for planning and implementing Public Charging Infrastructures (PCIs) to satisfy intracity charging demand of Electric Vehicles (EVs). The proposed MSDP splits planning and design processes into multiple stages, from macroscale to fine-scale levels. Consequently, the preliminary results achieved at each stage can be refined at the subsequent stages, leading to determine the accurate number and precise geographical location of each charging point. The main advantage of the proposed approach is that it splits a very complicated procedure into multiple and simpler stages, at each of which appropriate goals, targets and constraints can be included. As a result, the iterative interactions among all the stakeholders involved in the PCI design process are significantly simplified. The proposed MSDP has been employed in the planning and design of the PCI of the Italian island of Sardinia, accordingly to all the public bodies

From Ethanol to Salsolinol: Role of Ethanol Metabolites in the Effects of Ethanol

In spite of the global reputation of ethanol as the psychopharmacologically active ingredient of alcoholic drinks, the neurobiological basis of the central effects of ethanol still presents some dark sides due to a number of unanswered questions related to both its precise mechanism of action and its metabolism. Accordingly, ethanol represents the interesting example of a compound whose actions cannot be explained as simply due to the involvement of a single receptor/neurotransmitter, a scenario further complicated by the robust evidence that two main metabolites, acetaldehyde and salsolinol, exert many effects similar to those of their parent compound. The present review recapitulates, in a perspective manner, the major and most recent advances that in the last decades boosted a significant growth in the understanding on the role of ethanol metabolism, in particular, in the neurobiological basis of its central effects

Stress among medical students: Factor structure of the University Stress Scale among Italian students

Objectives The main purpose of the current study was to investigate the psychometric properties of the Italian version of the University Stress Scale (USS) among Italian medical students. Design, setting and participants A cross-sectional observational study based on data from an online cross-sectional survey from 11 to 23 December 2018. A total of 1858 Italian medical students participated in the study. Outcome measures We measured perceived stress among medical students using the USS, the Effort-Reward Imbalance Student Questionnaire (ERI-SQ) and the Kessler-10 (K10). Results Results showed that a bifactor-Exploratory Structural Equation Modeling solution provided excellent levels of fit to the data. Our results suggest that the modified version of 19 items of the Italian version of the USS does not have a simple unidimensional structure. Overall, an inspection of ancillary indices (omega indices, ECV and percentage of uncontaminated correlations) revealed that these were too low to suggest the use of the USS as a composite measure of university stress. We tested an alternative unidimensional short form (eight items; USS-S) that assessed all the five sources of stress. This version provided a good fit to the data. Evidence of convergent validity of the USS-S was observed by analysing the correlations between the USS and ERI-SQ (ranging from-0.34 to 0.37, all p<0.01). Finally, based on the clinical cut-off recommended on the K10, results from receiver operating characteristic showed that considering the clinical cut-off of the USS is 7.5 and that 59.70% of medical students reported stress levels in the clinical range. Conclusion Finally, our results showed a lack of support for using the USS to measure a general university stress factor, as the general USS factor accounted for little variance in our sample. In this sense, stress scores among Italian students can be better assessed by the use of the USS-S

Follicular thyroid carcinoma: Differences in clinical relevance between minimally invasive and widely invasive tumors

Evidence on the biological behavior and clinical courses of minimally invasive and widely invasive follicular thyroid carcinoma (MI-FTC, WI-FTC) is still debatable. The current study was conducted to identify differences between MI and WI tumors and those prognostic parameters influencing late outcome such as local recurrence and survival

Type 2 diabetes mellitus, physical activity, exercise self-efficacy, and body satisfaction. An application of the transtheoretical model in older adults

Physical activity (PA) is a relevant component of the treatment of Type 2 diabetes mellitus (T2DM). However, to prevent its related morbidities, PA requires an immediate and lasting change of lifestyle. Exercise self-efficacy and body satisfaction were used in a sample of older adults with T2DM, classified in different stages of change, to predict levels of PA. Results show that exercise self-efficacy increases linearly from precontemplation to maintenance stage, while body satisfaction shows an inverted U shape. However, only stages of change, other than exercise self-efficacy, add a significant and noticeable contribution to prediction of levels of PA. This evidence claims a tailored approach to PA in older adults with T2DM and advises behavioural health interventions based on exercise self- efficacy

Stress among medical students: factor structure of the University Stress Scale among Italian students

OBJECTIVES: The main purpose of the current study was to investigate the psychometric properties of the Italian version of the University Stress Scale (USS) among Italian medical students. DESIGN, SETTING AND PARTICIPANTS: A cross-sectional observational study based on data from an online cross-sectional survey from 11 to 23 December 2018. A total of 1858 Italian medical students participated in the study. OUTCOME MEASURES: We measured perceived stress among medical students using the USS, the Effort-Reward Imbalance Student Questionnaire (ERI-SQ) and the Kessler-10 (K10). RESULTS: Results showed that a bifactor-Exploratory Structural Equation Modeling solution provided excellent levels of fit to the data. Our results suggest that the modified version of 19 items of the Italian version of the USS does not have a simple unidimensional structure. Overall, an inspection of ancillary indices (omega indices, ECV and percentage of uncontaminated correlations) revealed that these were too low to suggest the use of the USS as a composite measure of university stress. We tested an alternative unidimensional short form (eight items; USS-S) that assessed all the five sources of stress. This version provided a good fit to the data. Evidence of convergent validity of the USS-S was observed by analysing the correlations between the USS and ERI-SQ (ranging from -0.34 to 0.37, all p<0.01). Finally, based on the clinical cut-off recommended on the K10, results from receiver operating characteristic showed that considering the clinical cut-off of the USS is 7.5 and that 59.70% of medical students reported stress levels in the clinical range. CONCLUSION: Finally, our results showed a lack of support for using the USS to measure a general university stress factor, as the general USS factor accounted for little variance in our sample. In this sense, stress scores among Italian students can be better assessed by the use of the USS-S