Novel techniques for kinetic model identification and improvement

Physics-based kinetic models are regarded as key tools for supporting the design and control of chemical processes and for understanding which degrees of freedom ultimately determine the observed behaviour of chemical systems. These models are formulated as sets of differential and algebraic equations where many state variables and parameters may be involved. Nonetheless, the translation of the available experimental evidence into an appropriate set of model equations is a time and resource intensive task that significantly relies on the presence of experienced scientists. Automated reactor platforms are increasingly being applied in research laboratories to generate large amounts of kinetic data with minimum human intervention. However, in most cases, these platforms do not implement software for the online identification of physics-based kinetic models. While automated reactor technologies have significantly improved the efficiency in the data collection process, the analysis of the data for modelling purposes still represents a tedious process that is mainly carried out a-posteriori by the scientist. This project focuses on how to systematically solve some relevant problems in kinetic modelling studies that would normally require the intervention of experienced modellers to be addressed. Specifically, the following challenges are considered: i) the selection of a robust model parametrisation to reduce the chance of numerical failures in the course of the model identification process; ii) the experimental design and parameter estimation problems in conditions of structural model uncertainty; iii) the improvement of approximated models embracing the available experimental evidence. The work presented in this Thesis paves the way towards fully automated kinetic modelling platforms through the development of intelligent algorithms for experimental design and model building under system uncertainty. The project aims at the definition of comprehensive and systematic modelling frameworks to make the modelling activity more efficient and less sensitive to human error and bias

An evolutionary approach to kinetic modelling inspired by Lamarckian inheritance

The mechanistic description of kinetic phenomena requires the construction of systems of differential and algebraic equations where a high number of parameters and state variables may be involved. The complexity associated with kinetic phenomena frequently leads to the construction of kinetic models characterised by some degree of approximation. Whenever an approximated model is falsified by observations, its mathematical structure should be evolved embracing the available experimental evidence [1]. Nonetheless, improving a model is a time and resource intensive task that heavily relies on the presence of experienced researchers. An evolutionary approach to kinetic modelling is proposed in this work which is inspired by the theory of evolution proposed by Jean-Baptiste Lamarck, namely the theory of Lamarckian inheritance [2]. The approach is illustrated qualitatively in the sketch in Figure 1. Lamarck states that the evolution of living beings is directly driven by their interaction with the environment. The use/disuse of an organ determines the evolution of that organ towards higher/lower complexity. The long neck of the giraffe is frequently reported as an example to explain Lamarck’s theory. Primitive giraffes with a short neck would strive to reach the highest leaves. This behaviour, driven by necessities of adaptation, would lead to an elongation of the neck during the giraffe’s lifetime and the characteristic of the long neck is inherited by the offspring. Lamarck’s theory is now widely dismissed. Nonetheless, the field of epigenetics stemmed directly from Lamarck’s philosophy and aims at explaining the complex mechanisms behind the hereditability of environment-driven phenotype changes [3]. In this work, the principles of Lamarckian inheritance are translated into a framework for kinetic model building. In the proposed framework, the evolution of model structures is data-driven. When the model is over-fitting, model parameters that are irrelevant for representing the data are removed from the model structure. When the model is under-fitting, relevant model parameters are evolved into more complex state-dependent expressions. A statistical index, namely a Model Modification Index (MMI), based on the Lagrange multipliers statistic [4], is proposed as a measure of model misspecification to support the evolution of approximated kinetic models towards higher levels of complexity. The use of the MMI is demonstrated in a simulated case study to diagnose misspecification in an approximated kinetic model of baker’s yeast growth [5]. Please click Additional Files below to see the full abstract

Identification of kinetic models of methanol oxidation on silver in the presence of uncertain catalyst behavior

Catalytic oxidation of methanol to formaldehyde is an important industrial process due to the value of formaldehyde either as a final product or as a precursor of numerous chemicals. The study of kinetics in this system is hindered by sources of uncertainty that are inherently associated to the nature and state of the catalyst (e.g., uncertain reactivity level, deactivation phenomena), the measurement system and the structure of the kinetic model equations. In this work, a simplified kinetic model is identified from data collected from continuous flow microreactor systems where catalysts with assorted levels of reactivity are employed. Tailored model-based data mining methods are proposed and applied for the effective estimation of the kinetic parameters and for identifying robust experimental conditions to be exploited for the kinetic characterization of catalysts with different reactivity, whose kinetic behavior is yet to be investigated

Tobacco Addiction and Smoking Status in Heroin Addicts under Methadone vs. Buprenorphine Therapy

Aims of the present investigation were: (i) to assess the prevalence of current smokers and relative smoking status among a large number of heroin addicts attending opioid-substitution therapy prevalence; (ii) to evaluate the relationship between the type (methadone, buprenorphine) and dosage of opioid substitution therapy and nicotine dependence. Three hundred and five (305) heroin addicts under opioid-substitution therapy were recruited at five Addiction Units. All participants completed a questionnaire assessing sociodemographic information, type and dose of opioid-substitution therapy, smoking history and status, Fagerström Test for Nicotine Dependence (FTND), and the Zung Self-Rating Depression scale (SDS). 298 subjects, out of 305 (97.2%) were smokers, with an average of 20.5 cigarette/day and a median FTND of 6. Our data confirmed the high prevalence of smokers among heroin addicts, the highest described in the literature to date among heroin addicts under substitution therapies, without any significant difference between methadone vs. buprenorphine therapy groups. There was no correlation between dose of methadone or buprenorphine and average number of cigarettes/day. Patients in substance abuse treatment very frequently smoke cigarettes and often die of tobacco-related diseases. Substance abuse treatment programs too often ignore tobacco use. We hope that these findings will help to incorporate smoking cessation in substance abuse treatments

Adherence issues related to sublingual immunotherapy as perceived by allergists

Objectives: Sublingual immunotherapy (SLIT) is a viable alternative to subcutaneous immunotherapy to treat allergic rhinitis and asthma, and is widely used in clinical practice in many European countries. The clinical efficacy of SLIT has been established in a number of clinical trials and meta-analyses. However, because SLIT is self-administered by patients without medical supervision, the degree of patient adherence with treatment is still a concern. The objective of this study was to evaluate the perception by allergists of issues related to SLIT adherence. Methods: We performed a questionnaire-based survey of 296 Italian allergists, based on the adherence issues known from previous studies. The perception of importance of each item was assessed by a VAS scale ranging from 0 to 10. Results: Patient perception of clinical efficacy was considered the most important factor (ranked 1 by 54% of allergists), followed by the possibility of reimbursement (ranked 1 by 34%), and by the absence of side effects (ranked 1 by 21%). Patient education, regular follow-up, and ease of use of SLIT were ranked first by less than 20% of allergists. Conclusion: These findings indicate that clinical efficacy, cost, and side effects are perceived as the major issues influencing patient adherence to SLIT, and that further improvement of adherence is likely to be achieved by improving the patient information provided by prescribers. © 2010 Scurati et al, publisher and licensee Dove Medical Press Ltd

Diagnosis and management of Cornelia de Lange syndrome:first international consensus statement

Cornelia de Lange syndrome (CdLS) is an archetypical genetic syndrome that is characterized by intellectual disability, well-defined facial features, upper limb anomalies and atypical growth, among numerous other signs and symptoms. It is caused by variants in any one of seven genes, all of which have a structural or regulatory function in the cohesin complex. Although recent advances in next-generation sequencing have improved molecular diagnostics, marked heterogeneity exists in clinical and molecular diagnostic approaches and care practices worldwide. Here, we outline a series of recommendations that document the consensus of a group of international experts on clinical diagnostic criteria, both for classic CdLS and non-classic CdLS phenotypes, molecular investigations, long-term management and care planning

Selective growth of ZnO nanowires on substrates patterned by photolithography and inkjet printing

Zinc oxide nanowires (ZnO NWs) were grown by a two-step growth method, involving the deposition of a patterned ZnO thin seeding layer and the chemical vapor deposition (CVD) of ZnO NWs. Two ways of patterning the seed layer were performed. The seeding solution containing ZnO precursors was deposited by sol–gel/spin coating technique and patterned by photolithography. In the other case, the seeding solution was directly printed by inkjet printing only on selected portion of the substrate areas. In both cases, crystallization of the seed layer was achieved by thermal annealing in ambient air. Vertically aligned ZnO NWs were then grown by CVD on patterned, seeded substrates. The structure and morphology of ZnO NWs was analyzed by means of X-ray diffraction and field emission scanning electron microscopy measurements, respectively, while the vibrational properties were evaluated through Raman spectroscopy. Results showed that less-defective, vertically aligned, c-axis oriented ZnO NWs were grown on substrates patterned by photolithography while more defective nanostructures were grown on printed seed layer. A feature size of 30 µm was transferred into the patterned seed layer, and a good selectivity in growing ZnO NWs was obtained

Selective growth of ZnO nanowires on substrates patterned by photolithography and inkjet printing

Zinc oxide nanowires (ZnO NWs) were grown by a two-step growth method, involving the deposition of a patterned ZnO thin seeding layer and the chemical vapor deposition (CVD) of ZnO NWs. Two ways of patterning the seed layer were performed. The seeding solution containing ZnO precursors was deposited by sol–gel/spin coating technique and patterned by photolithography. In the other case, the seeding solution was directly printed by inkjet printing only on selected portion of the substrate areas. In both cases, crystallization of the seed layer was achieved by thermal annealing in ambient air. Vertically aligned ZnO NWs were then grown by CVD on patterned, seeded substrates. The structure and morphology of ZnO NWs was analyzed by means of X-ray diffraction and field emission scanning electron microscopy measurements, respectively, while the vibrational properties were evaluated through Raman spectroscopy. Results showed that less-defective, vertically aligned, c-axis oriented ZnO NWs were grown on substrates patterned by photolithography while more defective nanostructures were grown on printed seed layer. A feature size of 30 µm was transferred into the patterned seed layer, and a good selectivity in growing ZnO NWs was obtained

La recezione dell’opera di Rubem Alves in Italia: contributo pedagogico e teologico

Se si tratta di provare a descrivere la recezione del pensiero di Rubem Alves attraverso le pubblicazioni apparse nel mercato editoriale italiano, la prima cosa da fare è provare a rendere conto delle stesse, in una per quanto rapida presentazione. Dopo le opere di carattere teologico tradotte in italiano ancora ad inizio anni ’70 (“Teologia della speranza umana” e “Il figlio del domani” entrambi per Queriniana), un certo successo editoriale lo gode il libro “Parole da mangiare” (edizioni Qiqjaon, 1998). Qualche anno dopo, per i tipi EMI viene pubblicato “La scuola che ho sempre sognato” (2003), mentre l’editore Qiqiaon propone un altro piccolo volume dal titolo “Il canto della vita” nel 2013. Se fin qui si tratta di traduzioni, nel 2014 l’editore Pazzini pubblica un volume che raccoglie e ordina i brevi racconti che Alves mensilmente pubblica, a partire dal 1999, nella rubrica “La pagina di Alves” sulla rivista interculturale “CEM-mondialità”. Così anche il volume dal titolo “Pedagogia del desiderio” dell’anno successivo, pubblicato da EDB, è una raccolta scelta tra i tanti racconti di carattere educativo e pedagogico di Alves apparsi nella rivista. Nel 2018, infine, ancora la comunità di Bose, responsabile delle edizioni Qiqajon, pubblica un nuovo libretto a firma di Alves sui temi della fragilità e della vecchiaia titolandolo “La bellezza del crepuscolo”