Engineering bio-based polymers using alternative solvents and processes

The work presented in this thesis explores novel routes for the processing of bio-based polymers, developing a sustainable approach based on the use of alternative solvents such as supercritical carbon dioxide (scCO2), ionic liquids (ILs) and deep eutectic solvents (DES). The feasibility to produce polymeric foams via supercritical fluid (SCF) foaming, combined with these solvents was assessed, in order to replace conventional foaming techniques that use toxic and harmful solvents. A polymer processing methodology is presented, based on SCF foaming and using scCO2 as a foaming agent. The SCF foaming of different starch based polymeric blends was performed, namely starch/poly(lactic acid) (SPLA) and starch/poly(ε-caprolactone) (SPCL). The foaming process is based on the fact that CO2 molecules can dissolve in the polymer, changing their mechanical properties and after suitable depressurization, are able to create a foamed (porous) material. In these polymer blends, CO2 presents limited solubility and in order to enhance the foaming effect, two different imidazolium based ILs (IBILs) were combined with this process, by doping the blends with IL. The use of ILs proved useful and improved the foaming effect in these starch-based polymer blends. Infrared spectroscopy (FTIR-ATR) proved the existence of interactions between the polymer blend SPLA and ILs, which in turn diminish the forces that hold the polymeric structure. This is directly related with the ability of ILs to dissolve more CO2. This is also clear from the sorption experiments results, where the obtained apparent sorption coefficients in presence of IL are higher compared to the ones of the blend SPLA without IL. The doping of SPCL with ILs was also performed. The foaming of the blend was achieved and resulted in porous materials with conductivity values close to the ones of pure ILs. This can open doors to applications as self-supported conductive materials. A different type of solvents were also used in the previously presented processing method. If different applications of the bio-based polymers are envisaged, replacing ILs must be considered, especially due to the poor sustainability of some ILs and the fact that there is not a well-established toxicity profile. In this work natural DES – NADES – were the solvents of choice. They present some advantages relatively to ILs since they are easy to produce, cheaper, biodegradable and often biocompatible, mainly due to the fact that they are composed of primary metabolites such as sugars, carboxylic acids and amino-acids. NADES were prepared and their physicochemical properties were assessed, namely the thermal behavior, conductivity, density, viscosity and polarity. With this study, it became clear that these properties can vary with the composition of NADES, as well as with their initial water content. The use of NADES in the SCF foaming of SPCL, acting as foaming agent, was also performed and proved successful. The SPCL structure obtained after SCF foaming presented enhanced characteristics (such as porosity) when compared with the ones obtained using ILs as foaming enhancers. DES constituted by therapeutic compounds (THEDES) were also prepared. The combination of choline chloride-mandelic acid, and menthol-ibuprofen, resulted in THEDES with thermal behavior very distinct from the one of their components. The foaming of SPCL with THEDES was successful, and the impregnation of THEDES in SPCL matrices via SCF foaming was successful, and a controlled release system was obtained in the case of menthol-ibuprofen THEDES.

Combining data mining and evolutionary computation for multi-criteria optimization of earthworks

Earthworks tasks aim at levelling the ground surface at a target construction area and precede any kind of structural construction (e.g., road and railway construction). It is comprised of sequential tasks, such as excavation, transportation, spreading and compaction, and it is strongly based on heavy mechanical equipment and repetitive processes. Under this context, it is essential to optimize the usage of all available resources under two key criteria: the costs and duration of earthwork projects. In this paper, we present an integrated system that uses two artificial intelligence based techniques: data mining and evolutionary multi-objective optimization. The former is used to build data-driven models capable of providing realistic estimates of resource productivity, while the latter is used to optimize resource allocation considering the two main earthwork objectives (duration and cost). Experiments held using real-world data, from a construction site, have shown that the proposed system is competitive when compared with current manual earthwork design.

Earthwork optimization system for sustainable highway construction

In highway construction, earthworks refer to the tasks of excavation, transportation, spreading and compaction of geomaterial (e.g. soil, rockfill and soil-rockfill mixture). Whereas relying heavily on machinery and repetitive processes, these tasks are highly susceptible to optimization. In this context Artificial Intelligent techniques, such as Data Mining and modern optimization can be applied for earthworks. A survey of these applications shows that they focus on the optimization of specific objectives and/or construction phases being possible to identify the capabilities and limitations of the analyzed techniques. Thus, according to the pinpointed drawbacks of these techniques, this paper describes a novel intelligent earthwork optimization system, capable of integrating DM, modern optimization and GIS technologies in order to optimize the earthwork processes throughout all phases of design and construction work. This integration system allows significant savings in time, cost and gas emissions contributing for a more sustainable construction.

In silico constraint-based strain optimization methods: the quest for optimal cell factories

Shifting from chemical to biotechnological processes is one of the cornerstones of 21st century industry. The production of a great range of chemicals via biotechnological means is a key challenge on the way toward a bio-based economy. However, this shift is occurring at a pace slower than initially expected. The development of efficient cell factories that allow for competitive production yields is of paramount importance for this leap to happen. Constraint-based models of metabolism, together with in silico strain design algorithms, promise to reveal insights into the best genetic design strategies, a step further toward achieving that goal. In this work, a thorough analysis of the main in silico constraint-based strain design strategies and algorithms is presented, their application in real-world case studies is analyzed, and a path for the future is discussed.

On the routines of wild-type silk fibroin processing toward silk-inspired materials: a review

For years, silk fibroin of a domestic silkworm, Bombyx mori, has been recognized as a valuable material and extensively used. In the last decades, new application fields are emerging for this versatile material. Those final, specific applications of silk dictate the way it has been processed in industry and research. This review focuses on the description of various approaches for silk downstream processing in a laboratory scale, that fall within several categories. The detailed description of workflow possibilities from the naturally found material to a finally formulated product is presented. Considerable attention is given to (bio-) chemical approaches of silk fibroin transformation, particularly, to its enzyme-driven modifications. The focus of the current literature survey is exclusively on the methods applied in research and not industry.

Combining non-dominance, objective-order and spread metric to extend firefly algorithm to multi-objective optimization

In this paper, we propose an extension of the firefly algorithm (FA) to multi-objective optimization. FA is a swarm intelligence optimization algorithm inspired by the flashing behavior of fireflies at night that is capable of computing global solutions to continuous optimization problems. Our proposal relies on a fitness assignment scheme that gives lower fitness values to the positions of fireflies that correspond to non-dominated points with smaller aggregation of objective function distances to the minimum values. Furthermore, FA randomness is based on the spread metric to reduce the gaps between consecutive non-dominated solutions. The obtained results from the preliminary computational experiments show that our proposal gives a dense and well distributed approximated Pareto front with a large number of points.

Development of procedures for the design, optimization and manufacturing of customized orthopaedic and trauma implants: Geometrical/anatomical modelling from 3D medical imaging

Tese de Doutoramento (Programa Doutoral em Engenharia Biomédica)

Adhesive bioactive coatings inspired by sea life

Inspired by nature, in particular by the marine mussels adhesive proteins (MAPs) and by the tough brick-and-mortar nacre-like structure, novel multilayered films are prepared in the present work. Organic-inorganic multilayered films, with an architecture similar to nacre based on bioactive glass nanoparticles (BG), chitosan and hyaluronic acid modified with catechol groups, which are the main responsible for the outstanding adhesion in MAPs, are developed for the first time. The biomimetic conjugate is prepared by carbodiimide chemistry and analyzed by ultraviolet-visible spectrophotometry. The build-up of the multilayered films is monitored with a quartz crystal microbalance with dissipation monitoring and their topography is characterized by atomic force microscopy. The mechanical properties reveal that the films containing catechol groups and BG present an enhanced adhesion. Moreover, the bioactivity of the films upon immersion in a simulated body fluid solution for 7 days is evaluated by scanning electron microscopy coupled with energy dispersive X-ray spectroscopy, Fourier transform infrared spectroscopy and X-ray diffraction. It was found that the constructed films promote the formation of bone-like apatite in vitro. Such multifunctional mussel inspired LbL films, which combine enhanced adhesion and bioactivity, could be potentially used as coatings of a variety of implants for orthopedic applications.

Vermiculite bio-barriers for Cu and Zn remediation: an eco-friendly approach for freshwater and sediments protection

The increase in heavy metal contamination in freshwater systems causes serious environmental problems in most industrialized countries, and the effort to find ecofriendly techniques for reducing water and sediment contamination is fundamental for environmental protection. Permeable barriers made of natural clays can be used as low-cost and eco-friendly materials for adsorbing heavy metals from water solution and thus reducing the sediment contamination. This study discusses the application of permeable barriers made of vermiculite clay for heavy metals remediation at the interface between water and sediments and investigates the possibility to increase their efficiency by loading the vermiculite surface with a microbial biofilm of Pseudomonas putida, which is well known to be a heavy metal accumulator. Some batch assays were performed to verify the uptake capacity of two systems and their adsorption kinetics, and the results indicated that the vermiculite bio-barrier system had a higher removal capacity than the vermiculite barrier (?34.4 and 22.8 % for Cu and Zn, respectively). Moreover, the presence of P. putida biofilm strongly contributed to fasten the kinetics of metals adsorption onto vermiculite sheets. In open-system conditions, the presence of a vermiculite barrier at the interface between water and sediment could reduce the sediment contamination up to 20 and 23 % for Cu and Zn, respectively, highlighting the efficiency of these eco-friendly materials for environmental applications. Nevertheless, the contribution of microbial biofilm in open-system setup should be optimized, and some important considerations about biofilm attachment in a continuous-flow system have been discussed.

COMMIT: Convex Optimization Modeling for Microstructure Informed Tractography.

Tractography is a class of algorithms aiming at in vivo mapping the major neuronal pathways in the white matter from diffusion magnetic resonance imaging (MRI) data. These techniques offer a powerful tool to noninvasively investigate at the macroscopic scale the architecture of the neuronal connections of the brain. However, unfortunately, the reconstructions recovered with existing tractography algorithms are not really quantitative even though diffusion MRI is a quantitative modality by nature. As a matter of fact, several techniques have been proposed in recent years to estimate, at the voxel level, intrinsic microstructural features of the tissue, such as axonal density and diameter, by using multicompartment models. In this paper, we present a novel framework to reestablish the link between tractography and tissue microstructure. Starting from an input set of candidate fiber-tracts, which are estimated from the data using standard fiber-tracking techniques, we model the diffusion MRI signal in each voxel of the image as a linear combination of the restricted and hindered contributions generated in every location of the brain by these candidate tracts. Then, we seek for the global weight of each of them, i.e., the effective contribution or volume, such that they globally fit the measured signal at best. We demonstrate that these weights can be easily recovered by solving a global convex optimization problem and using efficient algorithms. The effectiveness of our approach has been evaluated both on a realistic phantom with known ground-truth and in vivo brain data. Results clearly demonstrate the benefits of the proposed formulation, opening new perspectives for a more quantitative and biologically plausible assessment of the structural connectivity of the brain.

Optimization of treatment with interferon beta in multiple sclerosis. Usefulness of automatic system application criteria

Background. A software based tool has been developed (Optem) to allow automatize the recommendations of the Canadian Multiple Sclerosis Working Group for optimizing MS treatment in order to avoid subjective interpretation. METHODS: Treatment Optimization Recommendations (TORs) were applied to our database of patients treated with IFN beta1a IM. Patient data were assessed during year 1 for disease activity, and patients were assigned to 2 groups according to TOR: "change treatment" (CH) and "no change treatment" (NCH). These assessments were then compared to observed clinical outcomes for disease activity over the following years. RESULTS: We have data on 55 patients. The "change treatment" status was assigned to 22 patients, and "no change treatment" to 33 patients. The estimated sensitivity and specificity according to last visit status were 73.9% and 84.4%. During the following years, the Relapse Rate was always higher in the "change treatment" group than in the "no change treatment" group (5 y; CH: 0.7, NCH: 0.07; p < 0.001, 12 m - last visit; CH: 0.536, NCH: 0.34). We obtained the same results with the EDSS (4 y; CH: 3.53, NCH: 2.55, annual progression rate in 12 m - last visit; CH: 0.29, NCH: 0.13). CONCLUSION: Applying TOR at the first year of therapy allowed accurate prediction of continued disease activity in relapses and disability progression.

Decrease in beta-Cell Proliferation Precedes Apoptosis during Diabetes Development in Bio-Breeding/Worcester Rat: Beneficial Role of Exendin-4

In autoimmune type 1 diabetes mellitus, proinflammatory cytokine-mediated apoptosis of beta-cells has been considered to be the first event directly responsible for beta-cell mass reduction. In the Bio-Breeding (BB) rat, an in vivo model used in the study of autoimmune diabetes, beta-cell apoptosis is observed from 9 wk of age and takes place after an insulitis period that begins at an earlier age. Previous studies by our group have shown an antiproliferative effect of proinflammatory cytokines on cultured beta-cells in Wistar rats, an effect that was partially reversed by Exendin-4, an analogue of glucagon-like peptide-1. In the current study, the changes in beta-cell apoptosis and proliferation during insulitis stage were also determined in pancreatic tissue sections in normal and thymectomized BB rats, as well as in Wistar rats of 5, 7, 9, and 11 wk of age. Although stable beta-cell proliferation in Wistar and thymectomized BB rats was observed along the course of the study, a decrease in beta-cell proliferation and beta-cell mass from the age of 5 wk, and prior to the commencement of apoptosis, was noted in BB rats. Exendin-4, in combination with anti-interferon-gamma antibody, induced a near-total recovery of beta-cell proliferation during the initial stages of insulitis. This highlights the importance of early intervention and, as well, the possibilities of new therapeutic approaches in preventing autoimmune diabetes by acting, initially, in the insulitis stage and, subsequently, on beta-cell regeneration and on beta-cell apoptosis.

Low-dose multidetector computed tomography of the cervical spine: optimization of iterative reconstruction strength levels.

BACKGROUND: Iterative reconstruction (IR) techniques reduce image noise in multidetector computed tomography (MDCT) imaging. They can therefore be used to reduce radiation dose while maintaining diagnostic image quality nearly constant. However, CT manufacturers offer several strength levels of IR to choose from. PURPOSE: To determine the optimal strength level of IR in low-dose MDCT of the cervical spine. MATERIAL AND METHODS: Thirty consecutive patients investigated by low-dose cervical spine MDCT were prospectively studied. Raw data were reconstructed using filtered back-projection and sinogram-affirmed IR (SAFIRE, strength levels 1 to 5) techniques. Image noise, signal-to-noise ratio (SNR), and contrast-to-noise ratio (CNR) were measured at C3-C4 and C6-C7 levels. Two radiologists independently and blindly evaluated various anatomical structures (both dense and soft tissues) using a 4-point scale. They also rated the overall diagnostic image quality using a 10-point scale. RESULTS: As IR strength levels increased, image noise decreased linearly, while SNR and CNR both increased linearly at C3-C4 and C6-C7 levels (P < 0.001). For the intervertebral discs, the content of neural foramina and dural sac, and for the ligaments, subjective image quality scores increased linearly with increasing IR strength level (P ≤ 0.03). Conversely, for the soft tissues and trabecular bone, the scores decreased linearly with increasing IR strength level (P < 0.001). Finally, the overall diagnostic image quality scores increased linearly with increasing IR strength level (P < 0.001). CONCLUSION: The optimal strength level of IR in low-dose cervical spine MDCT depends on the anatomical structure to be analyzed. For the intervertebral discs and the content of neural foramina, high strength levels of IR are recommended.

An Analysis of black-box optimization problems in reinsurance: evolutionary-based approaches

Black-box optimization problems (BBOP) are de ned as those optimization problems in which the objective function does not have an algebraic expression, but it is the output of a system (usually a computer program). This paper is focussed on BBOPs that arise in the eld of insurance, and more speci cally in reinsurance problems. In this area, the complexity of the models and assumptions considered to de ne the reinsurance rules and conditions produces hard black-box optimization problems, that must be solved in order to obtain the optimal output of the reinsurance. The application of traditional optimization approaches is not possible in BBOP, so new computational paradigms must be applied to solve these problems. In this paper we show the performance of two evolutionary-based techniques (Evolutionary Programming and Particle Swarm Optimization). We provide an analysis in three BBOP in reinsurance, where the evolutionary-based approaches exhibit an excellent behaviour, nding the optimal solution within a fraction of the computational cost used by inspection or enumeration methods.

La vénerie royale / Robert de Salnove ; précédée d'une notice bio-bibliographique sur l'auteur, par le commandant G. de Marolles...

Collection : Les maîtres de la vénerie ; 4