Ultra-Low Temperature Partial Oxidation: Detailed Kinetics, Safety, and Environmental Issues

The innovation in several industrial sectors has been recently characterized by the need for reducing the operative temperature either for economic or environmental related aspects. Promising technological solutions require the acquisition of fundamental-based knowledge to produce safe and robust systems. In this sense, reactive systems often represent the bottleneck. For these reasons, this work was focused on the integration of chemical (i.e., detailed kinetic mechanism) and physical (i.e., computational fluid dynamics) models. A theoretical-based kinetic mechanism mimicking the behaviour of oxygenated fuels and their intermediates under oxidative conditions in a wide range of temperature and pressure was developed. Its validity was tested against experimental data collected in this work by using the heat flux burner, as well as measurements retrieved from the current literature. Besides, estimations deriving from existing models considered as the benchmark in the combustion field were compared with the newly generated mechanism. The latter was found to be the most accurate for the investigated conditions and fuels. Most influential species and reactions on the combustion of butyl acetate were identified. The corresponding thermodynamic parameter and rate coefficients were quantified through ab initio calculations. A reduced detailed kinetic mechanism was produced and implemented in an open-source computational fluid dynamics model to characterize pool fires caused by the accidental release of aviation fuel and liquefied natural gas, at first. Eventually, partial oxidation processes involving light alkenes were optimized following the quick, fair, and smoot (QFS) paradigm. The proposed procedure represents a comprehensive and multidisciplinary approach for the construction and validation of accurate models, allowing for the characterization of developing industrial sectors and techniques.

Self-supervised information retrieval: a novel approach based on Deep Metric Learning and Neural Language Models

Most of the existing open-source search engines, utilize keyword or tf-idf based techniques to find relevant documents and web pages relative to an input query. Although these methods, with the help of a page rank or knowledge graphs, proved to be effective in some cases, they often fail to retrieve relevant instances for more complicated queries that would require a semantic understanding to be exploited. In this Thesis, a self-supervised information retrieval system based on transformers is employed to build a semantic search engine over the library of Gruppo Maggioli company. Semantic search or search with meaning can refer to an understanding of the query, instead of simply finding words matches and, in general, it represents knowledge in a way suitable for retrieval. We chose to investigate a new self-supervised strategy to handle the training of unlabeled data based on the creation of pairs of ’artificial’ queries and the respective positive passages. We claim that by removing the reliance on labeled data, we may use the large volume of unlabeled material on the web without being limited to languages or domains where labeled data is abundant.

Advanced X-ray techniques for the structural characterisation of Prussian Blue Analogue cathode materials

The thesis is dedicated to the implementation of advanced x-ray-based techniques for the investigation of the battery systems, more predominantly, the cathode materials. The implemented characterisation methods include synchrotron based x-ray absorption spectroscopy, powder x-ray diffraction, 2-dimensional x-ray fluorescence, full field transmission soft x-ray microscopy, and laboratory x-ray photoelectron spectroscopy. The research highlights the different areas of expertise for each described method, in terms of material characterisation, exploring their complementarities and intersections. The results are focused over manganese hexacyanoferrate and partially Ni substituted manganese hexacyanoferrate, through both organic and aqueous battery systems. In aqueous system, the modification of cathode composition has been observed with various techniques, indicating to the processes occurring in bulk, surface, locally or in long-range, including with the speciation by 2-dimensional scanning, and the time-resolution, by the implementation of the operando measurements. In organic media, the inhomogenisation of the cathode material during the aging process was investigated by the development of the special image treatment procedure for the maps, obtained from the transmission soft x-ray microscopy. It worth mentioning, that apart from the combination of the outcomes from the various x-ray measurements, the exploration of the new capabilities was also conducted, namely, probing the oxidation state of the element with the synchrotron-based 2-dimensional x-ray fluorescence technique, which, generally, with conventional set up, is not possible to achieve. The results and methodology from this thesis can, of course, be generalised on the characterisation of the other battery systems, and not only, as the x-ray techniques are one of the most informative and sophisticated methods for advanced structural investigation of the materials.

Knowledge-based Chord Embeddings

This thesis develops AI methods as a contribution to computational musicology, an interdisciplinary field that studies music with computers. In systematic musicology a composition is defined as the combination of harmony, melody and rhythm. According to de La Borde, harmony alone "merits the name of composition". This thesis focuses on analysing the harmony from a computational perspective. We concentrate on symbolic music representation and address the problem of formally representing chord progressions in western music compositions. Informally, chords are sets of pitches played simultaneously, and chord progressions constitute the harmony of a composition. Our approach combines ML techniques with knowledge-based techniques. We design and implement the Modal Harmony ontology (MHO), using OWL. It formalises one of the most important theories in western music: the Modal Harmony Theory. We propose and experiment with different types of embedding methods to encode chords, inspired by NLP and adapted to the music domain, using both statistical (extensional) knowledge by relying on a huge dataset of chord annotations (ChoCo), intensional knowledge by relying on MHO and a combination of the two. The methods are evaluated on two musicologically relevant tasks: chord classification and music structure segmentation. The former is verified by comparing the results of the Odd One Out algorithm to the classification obtained with MHO. Good performances (accuracy: 0.86) are achieved. We feed a RNN for the latter, using our embeddings. Results show that the best performance (F1: 0.6) is achieved with embeddings that combine both approaches. Our method outpeforms the state of the art (F1 = 0.42) for symbolic music structure segmentation. It is worth noticing that embeddings based only on MHO almost equal the best performance (F1 = 0.58). We remark that those embeddings only require the ontology as an input as opposed to other approaches that rely on large datasets.

Delivery Of A Urology Online Course Using Moodle Versus Didactic Lectures Methods.

To subjectively and objectively compare an accessible interactive electronic library using Moodle with lectures for urology teaching of medical students. Forty consecutive fourth-year medical students and one urology teacher were exposed to two teaching methods (4 weeks each) in the form of problem-based learning: - lectures and - student-centered group discussion based on Moodle (modular object-oriented dynamic learning environment) full time online delivered (24/7) with video surgeries, electronic urology cases and additional basic principles of the disease process. All 40 students completed the study. While 30% were moderately dissatisfied with their current knowledge base, online learning course delivery using Moodle was considered superior to the lectures by 86% of the students. The study found the following observations: (1) the increment in learning grades ranged from 7.0 to 9.7 for students in the online Moodle course compared to 4.0-9.6 to didactic lectures; (2) the self-reported student involvement in the online course was characterized as large by over 60%; (3) the teacher-student interaction was described as very frequent (50%) and moderately frequent (50%); and (4) more inquiries and requisitions by students as well as peer assisting were observed from the students using the Moodle platform. The Moodle platform is feasible and effective, enthusing medical students to learn, improving immersion in the urology clinical rotation and encouraging the spontaneous peer assisted learning. Future studies should expand objective evaluations of knowledge acquisition and retention.

Cromatografia de afinidade por íons metálicos imobilizados (IMAC) de biomoléculas: aspectos fundamentais e aplicações tecnológicas

Immobilized Metal Ion Affinity Cromatography - IMAC - is a group-specific based adsorption applied to the purification and structure-function studies of proteins and nucleic acids. The adsorption is based on coordination between a metal ion chelated on the surface of a solid matrix and electron donor groups at the surface of the biomolecule. IMAC is a highly selective, low cost, and easily scaled-up technique being used in research and commercial operations. A separation process can be designed for a specific molecule by just selecting an appropriate metal ion, chelating agent, and operational conditions such as pH, ionic strength, and buffer type.

Pre-processing for noise detection in gene expression classification data

Due to the imprecise nature of biological experiments, biological data is often characterized by the presence of redundant and noisy data. This may be due to errors that occurred during data collection, such as contaminations in laboratorial samples. It is the case of gene expression data, where the equipments and tools currently used frequently produce noisy biological data. Machine Learning algorithms have been successfully used in gene expression data analysis. Although many Machine Learning algorithms can deal with noise, detecting and removing noisy instances from the training data set can help the induction of the target hypothesis. This paper evaluates the use of distance-based pre-processing techniques for noise detection in gene expression data classification problems. This evaluation analyzes the effectiveness of the techniques investigated in removing noisy data, measured by the accuracy obtained by different Machine Learning classifiers over the pre-processed data.

A fuzzy reed-frost model for epidemic spreading

In this paper, we present a fuzzy approach to the Reed-Frost model for epidemic spreading taking into account uncertainties in the diagnostic of the infection. The heterogeneities in the infected group is based on the clinical signals of the individuals (symptoms, laboratorial exams, medical findings, etc.), which are incorporated into the dynamic of the epidemic. The infectivity level is time-varying and the classification of the individuals is performed through fuzzy relations. Simulations considering a real problem with data of the viral epidemic in a children daycare are performed and the results are compared with a stochastic Reed-Frost generalization

Effects of Varenicline in Adult Smokers: A Multinational, 24-Week, Randomized, Double-Blind, Placebo-Controlled Study

Background: Prevalence rates of smoking are rising in developing countries. Previous trials evaluating the efficacy and tolerability of the smoking-cessation medication varenicline have used largely participants of Caucasian origin. Objective: This study was conducted to evaluate the efficacy and tolerability of varenicline in populations of participants from Latin America, Africa, and the Middle East to investigate potential differences in the therapeutic response to varenicline. Methods: This multinational, randomized, double-blind, placebo-controlled trial was conducted at 42 centers in 11 countries (Latin America: Brazil, Colombia, Costa Rica, Mexico, and Venezuela; Africa: Egypt and South Africa; Middle East: Jordan, Lebanon, Saudi Arabia, and the United Arab Emirates). Participants were male and female smokers aged 18 to 75 years who were motivated to stop smoking; smoked >= 10 cigarettes/d, with no cumulative period of abstinence >3 months in the previous year; and who had no serious or unstable disease within the previous 6 months. Subjects were randomized in a 2:1 ratio to receive varenicline 1 mg or placebo, BID for 12 weeks, with a 12-week nontreatment follow-up. Brief smoking-cessation counseling was provided. The main outcome measures were carbon monoxide confirmed continuous abstinence rate (CAR) at weeks 9 to 12 and weeks 9 to 24. Adverse events (AEs) were recorded for tolerability assessment. Results: Overall, 588 subjects (varenicline, 390; placebo, 198) were randomized and treated. The mean (SD) ages of subjects in the varenicline and placebo groups were 43.1 (10.8) and 43.9 (10.8) years, respectively; 57.7% and 65.7% were male; and the mean (SD) weights were 75.0 (16.0) and 76.7 (16.3) kg (range, 40.0-130.0 and 45.6-126.0 kg). CAR at weeks 9 to 12 was significantly higher with varenicline than with placebo (53.59% vs 18.69%; odds ratio [OR] = 5.76; 95% CI, 3.74-8.88; P < 0.0001), and this rate was maintained during weeks 9 to 24 (39.74% vs 13.13%; OR = 4.78; 95% CI, 2.97-7.68; P < 0.0001). Nausea, headache, and insomnia were the most commonly reported AEs with varenicline and were reported numerically more frequently in the varenicline group compared with the placebo group. Serious AEs (SAEs) were reported in 2.8% of varenicline recipients compared with 1.0% in the placebo group, with 6 subjects reporting psychiatric SAEs compared with none in the placebo group. Conclusion: Based on these data, varenicline was apparently efficacious and generally well tolerated as a smoking-cessation aid in smokers from selected sites in Latin America, Africa, and the Middle East. ClinicalTrials. gov identifier: NCT00594204. (Clin Ther. 2011;33:465-477) (C) 2011 Published by Elsevier HS Journals, Inc.

A simple and effective inverse projection scheme for void distribution control in topology optimization

The ability to control both the minimum size of holes and the minimum size of structural members are essential requirements in the topology optimization design process for manufacturing. This paper addresses both requirements by means of a unified approach involving mesh-independent projection techniques. An inverse projection is developed to control the minimum hole size while a standard direct projection scheme is used to control the minimum length of structural members. In addition, a heuristic scheme combining both contrasting requirements simultaneously is discussed. Two topology optimization implementations are contributed: one in which the projection (either inverse or direct) is used at each iteration; and the other in which a two-phase scheme is explored. In the first phase, the compliance minimization is carried out without any projection until convergence. In the second phase, the chosen projection scheme is applied iteratively until a solution is obtained while satisfying either the minimum member size or minimum hole size. Examples demonstrate the various features of the projection-based techniques presented.

Methylation patterns revealed by MSAP profiling in genetically stable somatic embryogenic cultures of Ocotea catharinensis (Lauraceae)

Ocotea catharinensis is a rare tree species indigenous to the Atlantic rainforest of South America. In spite of its value as a hardwood species, it is in danger of extinction. The species erratically produces seeds showing irregular flowering and slow growth. Therefore, plants are not easily replaced. Tissue culture-based techniques are commonly used for obtaining living material for tree propagation and in vitro preservation. Therefore, a high-frequency somatic embryogenic system was developed for the species. In the present work, the genetic fidelity of cell aggregates and somatic embryos at various stages of in vitro development of O. catharinensis was investigated using RAPD and AFLP markers. Both analyses confirmed the absence of genetic variation in all developmental stages of O. catharinensis embryogenic cultures, verifying that the in vitro system is genetically stable. The cultures were also analyzed for their methylation profiles at 5`-CCGG-3` sites by identifying methylation-sensitive amplification polymorphisms. Some of these markers differentiated cell aggregates from embryo bodies. The sequencing of ten MSAP markers revealed that four sequences showed significant similarity to genes encoding plant proteins. Particularly, the predicted amino acid sequence of the fragment designated as OcEaggHMttc155 was similar to the enzyme 1-aminocyclopropane-1-carboxylate oxidase (ACO), which is involved in the biosynthesis of ethylene, and its expression was reported to occur from the beginning to the intermediate stages of plant embryo development. Here, we suggest that this enzyme is possibly involved in the control of the earliest stages of somatic embryogenesis of O. catharinensis, and an approach to study ACO expression during somatic embryogenesis is proposed.

Quantum dynamics of three coupled atomic Bose-Einstein condensates

The simplest model of three coupled Bose-Einstein condensates is investigated using a group theoretical method. The stationary solutions are determined using the SU(3) group under the mean-field approximation. This semiclassical analysis, using system symmetries, shows a transition in the dynamics of the system from self trapping to delocalization at a critical value for the coupling between the condensates. The global dynamics are investigated by examination of the stable points, and our analysis shows that the structure of the stable points depends on the ratio of the condensate coupling to the particle-particle interaction, and undergoes bifurcations as this ratio is varied. This semiclassical model is compared to a full quantum treatment, which also displays a dynamical transition. The quantum case has collapse and revival sequences superimposed on the semiclassical dynamics, reflecting the underlying discreteness of the spectrum. Nonzero circular current states are also demonstrated as one of the higher-dimensional effects displayed in this system.

Frequency of concurrent autoimmune disorders in patients with autoimmune hepatitis - Effect of age, gender, and genetic background

Background: Concurrent autoimmune disorders (CAIDs) have been shown to occur in 22% to 34% of the patients with autoimmune hepatitis (AIH). Their presence has been linked to female gender, older age, and to certain HLA antigens, namely HLA-A11. DRB1*04, and DRB4*01. Aims: To assess the frequency and nature of CAID in Brazilian patients with AIH types 1 (AIH-1) and 2 (AIH-2) and to investigate the influence of age, gender, and genetic background in their occurrence. Patients and Methods: The presence and nature of CAID was studied in 143 patients [117 females, median age 11 (1.3 to 69)] with AIH-1 (n = 125) and AIH-2 (n = 28). HLA typing and tumor necrosis factor a gene promoter and exon I cytotoxic T lymphocyte associated antigen 4 (CTLA-4) gene polymorphisms were determined by polymerase chain reaction-based techniques. Results: The frequency of CAID was similar in patients with AIH-1 (14%) and AIH-2 (18%), but their nature was shown to vary. Arthritis was seen in half of the patients (n = 8) with CAID and AIH-1 and in none of those with AIH-2. Subjects with AIH-1 and CAID were shown to be older [24 (1.3 to 6 1) vs. 11 (1.3 to 69) y P = 0.02] and to have more often circulating antinuclear antibody (76% vs. 40%, P = 0.008) and less frequently antiactin antibodies (33% vs. 75%, P = 0.008) when compared with their counterparts without CAID. No particular HLA-DR and DQ alleles, as well as tumor necrosis factor a and CTLA-4 genotypes, were associated with CAID. Conclusions: The nature, but not the frequency, of CAID was shown to vary in AIH-1 and AIH-2. In subjects with AIH-1, CAID was linked to older subjects and to the presence of antinuclear antibody. No predisposition to CAID was associated to HLA-DRB1*04 or DDB4*01 alleles. The observed lower frequency of CAID could be attributed to the lower age of disease onset in Brazilians and to differences in HLA-encoded susceptibility to AIH-1 observed in South America.

A fuzzy Reed-Frost model for epidemic spreading

In this paper, we present a fuzzy approach to the Reed-Frost model for epidemic spreading taking into account uncertainties in the diagnostic of the infection. The heterogeneities in the infected group is based on the clinical signals of the individuals (symptoms, laboratorial exams, medical findings, etc.), which are incorporated into the dynamic of the epidemic. The infectivity level is time-varying and the classification of the individuals is performed through fuzzy relations. Simulations considering a real problem with data of the viral epidemic in a children daycare are performed and the results are compared with a stochastic Reed-Frost generalization.

The effects of cinnarizine on menopausal symptoms in women

Objective To evaluate the effectiveness and safety of cinnarizine in the treatment of menopausal symptoms. Design A total of 100 climacteric and symptomatic women participated in a double-blind, placebo-controlled study. They were divided into two groups of the same size: Gcin, intake of 25 mg of cinnarizine every 12 h for 6 months (n = 50); and Gpla, placebo intake every 12 hours for 6 months (n = 50). Menopausal symptoms were evaluated according to the Kupperman menopausal index on the first visit and at 6 months of treatment. A total of 62 women completed the study: 27 from the Gcin group and 35 from the Gpla group. Results Based on the Kupperman menopausal index, there were no statistically significant differences between the two groups before and after the treatment. Conclusion Our data suggest cinnarizine is not effective on menopausal symptoms because it had no more efficacy than placebo.