Newly developed electrosynthesis of Layered Double Hydroxides: application to sensing, energy storage and conversion

Layered Double hydroxides (LDHs) have been widely studied for their plethora of fascinating features and applications. The potentiostatic electrodeposition of LDHs has been extensively applied in the literature as a fast and direct method to substitute classical chemical routes. However, it does not usually allow for a fine control of the M(II)/M(III) ratio in the synthesized material and it is not suitable for large anions intercalation. Therefore, in this work a novel protocol has been proposed with the aim to overcome all these constraints using a method based on potentiodynamic synthesis. LDHs of controlled composition were prepared using different molar ratios of the trivalent to bivalent cations in the electrolytic solution ranging from 1:1 to 1:4. Moreover, we were able to produce electrochemically LDHs intercalated with carbon nanomaterials for the first time. A one-step procedure which contemporaneously allows for the Ni/Al-LDH synthesis, the reduction of graphene oxide (GO) and its intercalation inside the structure has been developed. The synthesised materials have been applied in several fields of interest. First of all, LDHs with a ratio 3:1 were exploited, and displayed good performances as catalysts for 5-(hydroxymethyl)furfural electro-oxidation, thus suggesting to carry out further investigation for applications in the field of industrial catalysis. The same materials, but with different metals ratios, were tested as catalysts for Oxygen Evolution Reaction, obtaining results comparable to LDHs synthesised by the classical co-precipitation method and also a better activity with respect to LDHs obtained by the potentiostatic approach. The composite material based on LDH and reduced graphene oxide was employed to fabricate a cathode of a hybrid supercapacitor coupled with an activated carbon anode. We can thus conclude that, to date, the potentiodynamic method has the greatest potential for the rapid synthesis of reproducible films of Co and Ni-based LDHs with controlled composition.

Towards eco-friendly batteries: concepts for lithium and sodium ion batteries

Several possibilities are arising aiming the development of “greener”, more sustainable energy storage systems. One point is the completely water-based processing of battery electrodes, thus being able to renounce the use of toxic solvents in the preparation process. Despite its advantage of lower cost and eco-friendlyness, there is the need of similar mechanical and electrochemichal behavior for boosting this preparation mode. Another point – accompanying the water-based processing - is the replacement of solvent-based polymer binders by water-based ones. These binders can be based on fluorinated, crude-oil based polymers on the one side, but also on naturally abundant and economic friendly biopolymers. The most common anode materials, graphite and lithium titanate (LTO), have been subjected a water-based preparation route with different binder systems. LTO is a promising anode material for lithium ion batteries (LIBs), as it shows excellent safety characteristics, does not form a significant SEI and its volume change upon intercalation of lithium ions is negligible. Unfortunately, this material suffers from a rather low electric conductivity - that is why an intensive study on improved current collector surfaces for LTO electrodes was performed. In order to go one step ahead towards sustainable energy storage, anode and cathode active materials for a sodium ion battery were synthesized. Anode active material resulted in a successful product which was then subjected to further electrochemical tests. In this PhD work the development of “greener” energy storage possibilities is tested under several aspects. The ecological impact of raw materials and required battery components is examined in detail.

Theoretical and experimental study of novel hybrid composite and metal-composites interfaces

The growing demand for lightweight solutions in every field of engineering is driving the industry to seek new technological solutions to exploit the full potential of different materials. The combination of dissimilar materials with distinct property ranges embodies a transparent allocation of component functions while allowing an optimal mix of their characteristics. From both technological and design perspectives, the interaction between dissimilar materials can lead to severe defects that compromise a multi-material hybrid component's performance and its structural integrity. This thesis aims to develop methodologies for designing, manufacturing, and monitoring of hybrid metal-composite joints and hybrid composite components. In Chapter 1, a methodology for designing and manufacturing hybrid aluminum/composite co-cured tubes is assessed. In Chapter 2, a full-field methodology for fiber misalignment detection and stiffness prediction for hybrid, long fiber reinforced composite systems is shown and demonstrated. Chapter 3 reports the development of a novel technology for joining short fiber systems and metals in a one-step co-curing process using lattice structures. Chapter 4 is dedicated to a novel analytical framework for the design optimization of two lattice architectures.

Towards a sustainable approach for Cultural Heritage Conservation: developing micro-structured green materials and analytical protocols for their performance assessment

Cleaning is one of the most important and delicate procedures that are part of the restoration process. When developing new systems, it is fundamental to consider its selectivity towards the layer to-be-removed, non-invasiveness towards the one to-be-preserved, its sustainability and non-toxicity. Besides assessing its efficacy, it is important to understand its mechanism by analytical protocols that strike a balance between cost, practicality, and reliable interpretation of results. In this thesis, the development of cleaning systems based on the coupling of electrospun fabrics (ES) and greener organic solvents is proposed. Electrospinning is a versatile technique that allows the production of micro/nanostructured non-woven mats, which have already been used as absorbents in various scientific fields, but to date, not in the restoration field. The systems produced proved to be effective for the removal of dammar varnish from paintings, where the ES not only act as solvent-binding agents but also as adsorbents towards the partially solubilised varnish due to capillary rise, thus enabling a one-step procedure. They have also been successfully applied for the removal of spray varnish from marble substrates and wall paintings. Due to the materials' complexity, the procedure had to be adapted case-by-case and mechanical action was still necessary. According to the spinning solution, three types of ES mats have been produced: polyamide 6,6, pullulan and pullulan with melanin nanoparticles. The latter, under irradiation, allows for a localised temperature increase accelerating and facilitating the removal of less soluble layers (e.g. reticulated alkyd-based paints). All the systems produced, and the mock-ups used were extensively characterised using multi-analytical protocols. Finally, a monitoring protocol and image treatment based on photoluminescence macro-imaging is proposed. This set-up allowed the study of the removal mechanism of dammar varnish and semi-quantify its residues. These initial results form the basis for optimising the acquisition set-up and data processing.

Conditional entropy and predictability for non-reversible Markov systems

The purpose of this thesis is to clarify the role of non-equilibrium stationary currents of Markov processes in the context of the predictability of future states of the system. Once the connection between the predictability and the conditional entropy is established, we provide a comprehensive approach to the definition of a multi-particle Markov system. In particular, starting from the well-known theory of random walk on network, we derive the non-linear master equation for an interacting multi-particle system under the one-step process hypothesis, highlighting the limits of its tractability and the prop- erties of its stationary solution. Lastly, in order to study the impact of the NESS on the predictability at short times, we analyze the conditional entropy by modulating the intensity of the stationary currents, both for a single-particle and a multi-particle Markov system. The results obtained analytically are numerically tested on a 5-node cycle network and put in correspondence with the stationary entropy production. Furthermore, because of the low dimensionality of the single-particle system, an analysis of its spectral properties as a function of the modulated stationary currents is performed.

An exploration of the experience of implementing the second step violence prevention curriculum in one primary general learning disabilities class /

Violence has always been a part of the human experience, and therefore, a popular topic for research. It is a controversial issue, mostly because the possible sources of violent behaviour are so varied, encompassing both biological and environmental factors. However, very little disagreement is found regarding the severity of this societal problem. Most researchers agree that the number and intensity of aggressive acts among adults and children is growing. Not surprisingly, many educational policies, programs, and curricula have been developed to address this concern. The research favours programs which address the root causes of violence and seek to prevent rather than provide consequences for the undesirable behaviour. But what makes a violence prevention program effective? How should educators choose among the many curricula on the market? After reviewing the literature surrounding violence prevention programs and their effectiveness, The Second Step Violence Prevention Curriculum surfaced as unique in many ways. It was designed to address the root causes of violence in an active, student-centred way. Empathy training, anger management, interpersonal cognitive problem solving, and behavioural social skills form the basis of this program. Published in 1992, the program has been the topic of limited research, almost entirely carried out using quantitative methodologies.The purpose of this study was to understand what happens when the Second Step Violence Prevention Curriculum is implemented with a group of students and teachers. I was not seeking a statistical correlation between the frequency of violence and program delivery, as in most prior research. Rather, I wished to gain a deeper understanding of the impact ofthe program through the eyes of the participants. The Second Step Program was taught to a small, primary level, general learning disabilities class by a teacher and student teacher. Data were gathered using interviews with the teachers, personal observations, staff reports, and my own journal. Common themes across the four types of data collection emerged during the study, and these themes were isolated and explored for meaning. Findings indicate that the program does not offer a "quick fix" to this serious problem. However, several important discoveries were made. The teachers feU that the program was effective despite a lack of concrete evidence to support this claim. They used the Second Step strategies outside their actual instructional time and felt it made them better educators and disciplinarians. The students did not display a marked change in their behaviour during or after the program implementation, but they were better able to speak about their actions, the source of their aggression, and the alternatives which were available. Although they were not yet transferring their knowledge into positive action,a heightened awareness was evident. Finally, staff reports and my own journal led me to a deeper understanding ofhow perception frames reality. The perception that the program was working led everyone to feel more empowered when a violent incident occurred, and efforts were made to address the cause rather than merely to offer consequences. A general feeling that we were addressing the problem in a productive way was prevalent among the staff and students involved. The findings from this investigation have many implications for research and practice. Further study into the realm of violence prevention is greatly needed, using a balance of quantitative and qualitative methodologies. Such a serious problem can only be effectively addressed with a greater understanding of its complexities. This study also demonstrates the overall positive impact of the Second Step Violence Prevention Curriculum and, therefore, supports its continued use in our schools.

Early intervention: Narratives of learning, discipline and enculturation

Current understandings about literacy have moved away from the belief that literacy is simply a process that individuals do in their heads. These understandings do not negate the importance of the individual aspects of literacy learning, but they emphasize understandings of literacy as a social practice. In many cases, responses to early literacy intervention seem to be grounded in theories that appear out of step with current literacy research and consequent evidence that literacy is socially and culturally constructed. One such response is the Reading Recovery programme based on Clay’s theory of literacy acquisition. Clay (1992) describes the programme as a second chance to learn. However, others have suggested that programmes like Reading Recovery may in fact work toward the marginalization of particular groups, thereby helping to maintain the status quo along class, gender and ethnic lines. This article allows two professionals to bring their insider’s knowledge of Reading Recovery to an analysis of the construction of the programme. The article interweaves this analysis with the personal narratives of the researchers as they negotiated the borders between different understandings and beliefs about literacy and literacy pedagogy.

CLFP intrinsic constraints-based group management of blended learning situations

When applying a Collaborative Learning Flow Pattern (CLFP) to structure sequences of activities in real contexts, one of the tasks is to organize groups of students according to the constraints imposed by the pattern. Sometimes,unexpected events occurring at runtime force this pre-defined distribution to be changed. In such situations, an adjustment of the group structures to be adapted to the new context is needed. If the collaborative pattern is complex, this group redefinitionmight be difficult and time consuming to be carried out in real time. In this context, technology can help on notifying the teacher which incompatibilitiesbetween the actual context and the constraints imposed by the pattern. This chapter presents a flexible solution for supporting teachers in the group organization profiting from the intrinsic constraints defined by a CLFPs codified in IMS Learning Design. A prototype of a web-based tool for the TAPPS and Jigsaw CLFPs and the preliminary results of a controlled user study are alsopresented as a first step towards flexible technological systems to support grouping tasks in this context.

A catalogue of Primitive Scenario-Types : The First Step to the Automation of Learning Scenarios

Peer-reviewed

Collaborative reflection : supporting one practitioner's development of online learning communities /

This is a study of one participant's reflective practice as she worked to develop online communities in a face-to-face science course. Her process of reflective practice was examined in order to address factors that influenced her learning path, and the benefits and challenges of collaborative action research. These research goals were pursued using a collaborative action research methodology, initially chosen for its close match with Schon's (1983) model of reflective practice. The participant's learning fit vnth Mezirow's (1991) model of transformative learning. She began with beliefs that matched her goals, and she demonstrated significant learning in three areas. First, she demonstrated instrumental learning around the constraints of workload and time, and achieving online learning community indicators. Second, she demonstrated communicative learning that helped her to see her own needs for feedback and communication more clearly, and how other process partners had been a support to her. Third, her emancipatory learning saw her revisiting and questioning her goals. It was through the reflective conversation during the planned meetings and the researcher's reframing and interrogation of that reflection that the participant was able to clarify and extend her thinking, and in so doing, critically reflect on her practice as she worked to develop online learning communities. In this way, the collaborative action research methodology was an embodiment of co-constructivism through collaborative reflective practice. Schon's (1983) model of reflective practice positions a lone practitioners moving through cycles ofplan-act-observe-reflect. The results fi"om this study suggest that collaboration is an important piece of the reflective practice model.

Reinforcement Learning Approaches to Power System Scheduling

One major component of power system operation is generation scheduling. The objective of the work is to develop efficient control strategies to the power scheduling problems through Reinforcement Learning approaches. The three important active power scheduling problems are Unit Commitment, Economic Dispatch and Automatic Generation Control. Numerical solution methods proposed for solution of power scheduling are insufficient in handling large and complex systems. Soft Computing methods like Simulated Annealing, Evolutionary Programming etc., are efficient in handling complex cost functions, but find limitation in handling stochastic data existing in a practical system. Also the learning steps are to be repeated for each load demand which increases the computation time.Reinforcement Learning (RL) is a method of learning through interactions with environment. The main advantage of this approach is it does not require a precise mathematical formulation. It can learn either by interacting with the environment or interacting with a simulation model. Several optimization and control problems have been solved through Reinforcement Learning approach. The application of Reinforcement Learning in the field of Power system has been a few. The objective is to introduce and extend Reinforcement Learning approaches for the active power scheduling problems in an implementable manner. The main objectives can be enumerated as:(i) Evolve Reinforcement Learning based solutions to the Unit Commitment Problem.(ii) Find suitable solution strategies through Reinforcement Learning approach for Economic Dispatch. (iii) Extend the Reinforcement Learning solution to Automatic Generation Control with a different perspective. (iv) Check the suitability of the scheduling solutions to one of the existing power systems.First part of the thesis is concerned with the Reinforcement Learning approach to Unit Commitment problem. Unit Commitment Problem is formulated as a multi stage decision process. Q learning solution is developed to obtain the optimwn commitment schedule. Method of state aggregation is used to formulate an efficient solution considering the minimwn up time I down time constraints. The performance of the algorithms are evaluated for different systems and compared with other stochastic methods like Genetic Algorithm.Second stage of the work is concerned with solving Economic Dispatch problem. A simple and straight forward decision making strategy is first proposed in the Learning Automata algorithm. Then to solve the scheduling task of systems with large number of generating units, the problem is formulated as a multi stage decision making task. The solution obtained is extended in order to incorporate the transmission losses in the system. To make the Reinforcement Learning solution more efficient and to handle continuous state space, a fimction approximation strategy is proposed. The performance of the developed algorithms are tested for several standard test cases. Proposed method is compared with other recent methods like Partition Approach Algorithm, Simulated Annealing etc.As the final step of implementing the active power control loops in power system, Automatic Generation Control is also taken into consideration.Reinforcement Learning has already been applied to solve Automatic Generation Control loop. The RL solution is extended to take up the approach of common frequency for all the interconnected areas, more similar to practical systems. Performance of the RL controller is also compared with that of the conventional integral controller.In order to prove the suitability of the proposed methods to practical systems, second plant ofNeyveli Thennal Power Station (NTPS IT) is taken for case study. The perfonnance of the Reinforcement Learning solution is found to be better than the other existing methods, which provide the promising step towards RL based control schemes for practical power industry.Reinforcement Learning is applied to solve the scheduling problems in the power industry and found to give satisfactory perfonnance. Proposed solution provides a scope for getting more profit as the economic schedule is obtained instantaneously. Since Reinforcement Learning method can take the stochastic cost data obtained time to time from a plant, it gives an implementable method. As a further step, with suitable methods to interface with on line data, economic scheduling can be achieved instantaneously in a generation control center. Also power scheduling of systems with different sources such as hydro, thermal etc. can be looked into and Reinforcement Learning solutions can be achieved.

Learning one-to-one.

Recurso para la enseñanza individualizada del inglés. Está estructurado en dos partes: la primera ofrece una visión general de las áreas de la metodología que son más relevantes para esta modalidad de enseñanza, y la segunda tiene actividades para su uso en las clases individuales. El contenido de las lecciones dependerá del contexto y de las necesidades de sus estudiantes. Puede centrarse en el inglés de conversación, de negocios, para viajar o para exámenes.

Fan Culture as an Informal Learning Environment : Presentation of a NGL project

Fan culture is a subculture that has developed explosively on the internet over the last decades. Fans are creating their own films, translations, fiction, fan art, blogs, role play and also various forms that are all based on familiar popular culture creations like TV-series, bestsellers, anime, manga stories and games. In our project, we analyze two of these subculture genres, fan fiction and scanlation. Amateurs, and sometimes professional writers, create new stories by adapting and developing existing storylines and characters from the original. In this way, a "network" of texts occurs, and writers step into an intertextual dialogue with established writers such as JK Rowling (Harry Potter) and Stephanie Meyer (Twilight). Literary reception and creation then merge into a rich reciprocal creative activity which includes comments and feedback from the participators in the community. The critical attitude of the fans regarding quality and the frustration at waiting for the official translation of manga books led to the development of scanlation, which is an amateur translation of manga distributed on the internet.  Today, young internet users get involved in conceptual discussions of intertextuality and narrative structures through fan activity. In the case of scanlation, the scanlators practice the skills and techniques of translating in an informal environment. This phenomenon of participatory culture has been observed by scholars and it is concluded that they contribute to the development of a student’s literacy and foreign language skills. Furthermore, there is no doubt that the fandom related to Japanese cultural products such as manga, anime and videogames is one of the strong motives for foreign students to start learning Japanese. This is something to take into pedagogical consideration when we develop web-based courses. Fan fiction and fan culture make it ​​possible to have an intensive transcultural dialogue between participators throughout the world and is of great interest when studying the interaction between formal and informal learning that puts the student in focus

Preliminary diagnosis of ophtalmological diseases through machine learning techniques

Fundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP)