Functional application of lactic acid bacteria exopolysaccharide in complex food systems

Lactic acid bacteria expolysaccharides (LAB-EPS), in particular those formed from sucrose have the potential to improve food and beverage rheology and enhance their sensory properties potentially replacing or reducing expensive hydrocolloids currently used as improvers in food and beverage industries. Addition of sucrose not only enables EPS formation but also affects organic acid formation, thus influencing the sensory properties of the resulting food/beverage products. The first part of the study the organoleptic modulation of barley malt derived wort fermented using in situ produced bacterial polysaccharides has been investigated. Weisella cibaria MG1 was capable to produce exopolysaccharides during sucrosesupplemented barley malt derived wort fermentation. Even though the strain dominated the (sucrose-supplemented) wort fermentation, it was found to produce EPS (14.4 g l-1) with lower efficiency than in SucMRS (34.6 g l-1). Higher maltose concentration in wort led to the increased formation of oligosaccharide (OS) at the expense of EPS. Additionally, small amounts of organic acids were formed and ethanol remained below 0.5% (v/v). W. cibaria MG1 fermented worts supplemented with 5 or 10% sucrose displayed a shear-thinning behaviour indicating the formation of polymers. This report showed how novel and nutritious LAB fermented wort-base beverage with prospects for further advancements can be formulated using tailored microbial cultures. In the next step, the impact of exopolysaccharide-producing Weissella cibaria MG1 on the ability to improve rheological properties of fermented plant-based milk substitute plant based soy and quinoa grain was evaluated. W. cibaria MG1 grew well in soy milk, exceeding a cell count of log 8 cfu/g within 6 h of fermentation. The presence of W. cibaria MG1 led to a decrease in gelation and fermentation time. EPS isolated from soy yoghurts supplemented with sucrose were higher in molecular weight (1.1 x 108 g/mol vs 6.6 x 107 g/mol), and resulted in reduced gel stiffness (190 ± 2.89 Pa vs 244 ± 15.9 Pa). Soy yoghurts showed typical biopolymer gels structure and the network structure changed to larger pores and less cross-linking in the presence of sucrose and increasing molecular weight of the EPS. In situ investigation of Weissella cibaria MG1 producing EPS on quinoa-based milk was performed. The production of quinoa milk, starting from wholemeal quinoa flour, was optimised to maximise EPS production. On doing that, enzymatic destructuration of protein and carbohydrate components of quinoa milk was successfully achieved applying alpha-amylase and proteases treatments. Fermented wholemeal quinoa milk using Weissella cibaria MG1 showed high viable cell counts (>109 cfu/mL), a pH of 5.16, and significantly higher water holding capacity (WHC, 100 %), viscosity (> 0. 5 Pa s) and exopolysaccharide (EPS) amount (40 mg/L) than the chemically acidified control. High EPS (dextran) concentration in quinoa milk caused earlier aggregation because more EPS occupy more space, and the chenopodin were forced to interact with each other. Direct observation of microstructure in fermented quinoa milk indicated that the network structures of EPS-protein could improve the texture of fermented quinoa milk. Overall, Weissella cibaria MG1 showed favorable technology properties and great potential for further possible application in the development of high viscosity fermented quinoa milk. The last part of the study investigate the ex-situ LAB-EPS (dextran) application compared to other hydrocolloids as a novel food ingredient to compensate for low protein in biscuit and wholemeal wheat flour. Three hydrocolloids, xanthan gum, dextran and hydroxypropyl methylcellulose, were incorporated into bread recipes based on high-protein flours, low-protein flours and coarse wholemeal flour. Hydrocolloid levels of 0–5 % (flour basis) were used in bread recipes to test the water absorption. The quality parameters of dough (farinograph, extensograph, rheofermentometre) and bread (specific volume, crumb structure and staling profile) were determined. Results showed that xanthan had negative impact on the dough and bread quality characteristics. HPMC and dextran generally improved dough and bread quality and showed dosage dependence. Volume of low-protein flour breads were significantly improved by incorporation of 0.5 % of the latter two hydrocolloids. However, dextran outperformed HPMC regarding initial bread hardness and staling shelf life regardless the flour applied in the formulation.

Dynamic Programming Approaches for Estimating and Applying Large-scale Discrete Choice Models

People go through their life making all kinds of decisions, and some of these decisions affect their demand for transportation, for example, their choices of where to live and where to work, how and when to travel and which route to take. Transport related choices are typically time dependent and characterized by large number of alternatives that can be spatially correlated. This thesis deals with models that can be used to analyze and predict discrete choices in large-scale networks. The proposed models and methods are highly relevant for, but not limited to, transport applications. We model decisions as sequences of choices within the dynamic discrete choice framework, also known as parametric Markov decision processes. Such models are known to be difficult to estimate and to apply to make predictions because dynamic programming problems need to be solved in order to compute choice probabilities. In this thesis we show that it is possible to explore the network structure and the flexibility of dynamic programming so that the dynamic discrete choice modeling approach is not only useful to model time dependent choices, but also makes it easier to model large-scale static choices. The thesis consists of seven articles containing a number of models and methods for estimating, applying and testing large-scale discrete choice models. In the following we group the contributions under three themes: route choice modeling, large-scale multivariate extreme value (MEV) model estimation and nonlinear optimization algorithms. Five articles are related to route choice modeling. We propose different dynamic discrete choice models that allow paths to be correlated based on the MEV and mixed logit models. The resulting route choice models become expensive to estimate and we deal with this challenge by proposing innovative methods that allow to reduce the estimation cost. For example, we propose a decomposition method that not only opens up for possibility of mixing, but also speeds up the estimation for simple logit models, which has implications also for traffic simulation. Moreover, we compare the utility maximization and regret minimization decision rules, and we propose a misspecification test for logit-based route choice models. The second theme is related to the estimation of static discrete choice models with large choice sets. We establish that a class of MEV models can be reformulated as dynamic discrete choice models on the networks of correlation structures. These dynamic models can then be estimated quickly using dynamic programming techniques and an efficient nonlinear optimization algorithm. Finally, the third theme focuses on structured quasi-Newton techniques for estimating discrete choice models by maximum likelihood. We examine and adapt switching methods that can be easily integrated into usual optimization algorithms (line search and trust region) to accelerate the estimation process. The proposed dynamic discrete choice models and estimation methods can be used in various discrete choice applications. In the area of big data analytics, models that can deal with large choice sets and sequential choices are important. Our research can therefore be of interest in various demand analysis applications (predictive analytics) or can be integrated with optimization models (prescriptive analytics). Furthermore, our studies indicate the potential of dynamic programming techniques in this context, even for static models, which opens up a variety of future research directions.

Microbial community composition of sandy intertidal sediments of Sylt-Rømø Basin, Wadden Sea

Molecular biological methods were used to investigate the microbial diversity and community structure in intertidal sandy sediments near the island of Sylt (Wadden Sea) at a site which was characterized for transport and mineralization rates in de Beer et al., (2005, hdl:10013/epic.21375). The sampling was performed during low tide in the middle of the flat, approximately 40 m in the offshore direction from the high water line on October 6, 1999, March 7, 2000, and July 5, 2000. Two parallel cores were collected from each season for molecular analyses. Within 2 h after sampling the sediment cores were sub-sampled and fixed in formaldehyde for FISH analysis. The cells were hybridized, stained with 4',6'-diamidino-2-phenylindole (DAPI) and microscopically counted as described previously [55]. Details of probes and formamide concentrations which were used are shown in further details. Counts are reported as means calculated from 10-15 randomly chosen microscopic fields corresponding to 700-1000 DAPI-stained cells. Values were corrected for the signals counted with the probe NON338. Fluorescence in situ hybridization (FISH)with group-specific rRNA-targeted oligonucleotide probes were used to characterize the microbial community structure over depth (0-12 cm) and seasons (March, July, October). We found high abundances of bacteria with total cell numbers up to 3×109 cells ml-1 and a clear seasonal variation, with higher values in July and October versus March. The microbial community was dominated by members of the Planctomycetes, the Cytophaga/Flavobacterium group, Gammaproteobacteria, and bacteria of the Desulfosarcina/Desulfococcus group. The high abundance (1.5×10**7 - 1.8×10**8 cells/ml accounting for 3-19% of all cells) of presumably aerobic heterotrophic polymer-degrading planctomycetes is in line with the high permeability, deep oxygen penetration, and the high rates of aerobic mineralization of algal biomass measured in the sandy sediments by de Beer et al., (2005, hdl:10013/epic.21375). The high and stable abundance of members of the Desulfosarcina/Desulfococcus group, both over depth and season, suggests that these bacteria may play a more important role than previously assumed based on low sulfate reduction rates in parallel cores de Beer et al., (2005).

Pollen from 50 lake surface samples in Brandenburg, Germany, in 2009

Past changes in plant and landscape diversity can be evaluated through pollen analysis, however, pollen based diversity indexes are potentially biased by differential pollen production and deposition. Studies examining the relationship between pollen and landscape diversity are therefore needed. The aim of this study is to evaluate how different pollen based indexes capture aspects of landscape diversity. Pollen counts were obtained from surface samples of 50 small to medium sized lakes in Brandenburg (Northeast Germany) and compiled into two sets, with one containing all pollen counts from terrestrial plants and the second restricted to wind-pollinated taxa. Both sets were adjusted for the pollen production/dispersal bias using the REVEALS model. A high resolution biotope map was used to extract the density of total biotopes and different biotopes per area as parameters describing landscape diversity. In addition tree species diversity was obtained from forest inventory data. The Shannon index and the number of taxa in a sample of 10 pollen grains are highly correlated and provide a useful measure of pollen type diversity which corresponds best to landscape diversity within one km of the lake and the proportion of non-forested area within seven km. Adjustments of the pollen production/dispersal bias only slightly improve the relationships between pollen diversity and landscape diversity for the restricted dataset as well as for the forest inventory data and corresponding pollen types. Using rarefaction analysis, we propose the following convention: pollen type diversity is represented by the number of types in a small sample (low count e.g. 10), pollen type richness is the number of types in a large sample (high count e.g. 500) and pollen sample evenness is characterized by the ratio of the two. Synthesis. Pollen type diversity is a robust index that captures vegetation structure and landscape diversity. It is ideally suited for between site comparisons as it does not require high pollen counts. In concert with pollen type richness and evenness, it helps evaluating the effect of climate change and human land use on vegetation structure on long timescales.

Cross-section and panel estimates of peer effects in early adolescent cannabis use: With a little help from my ‘friends once removed’

Peer effects in adolescent cannabis are difficult to estimate, due in part to the lack of appropriate data on behaviour and social ties. This paper exploits survey data that have many desirable properties and have not previously been used for this purpose. The data set, collected from teenagers in three annual waves from 2002-2004 contains longitudinal information about friendship networks within schools (N = 5,020). We exploit these data on network structure to estimate peer effects on adolescents from their nominated friends within school using two alternative approaches to identification. First, we present a cross-sectional instrumental variable (IV) estimate of peer effects that exploits network structure at the second degree, i.e. using information on friends of friends who are not themselves ego’s friends to instrument for the cannabis use of friends. Second, we present an individual fixed effects estimate of peer effects using the full longitudinal structure of the data. Both innovations allow a greater degree of control for correlated effects than is commonly the case in the substance-use peer effects literature, improving our chances of obtaining estimates of peer effects than can be plausibly interpreted as causal. Both estimates suggest positive peer effects of non-trivial magnitude, although the IV estimate is imprecise. Furthermore, when we specify identical models with behaviour and characteristics of randomly selected school peers in place of friends’, we find effectively zero effect from these ‘placebo’ peers, lending credence to our main estimates. We conclude that cross-sectional data can be used to estimate plausible positive peer effects on cannabis use where network structure information is available and appropriately exploited.

Rede Social Pessoal, Qualidade de Vida e Depressão em Idosos

Em Portugal e no Mundo Ocidental a população está a envelhecer, colocando esta nova realidade enormes desafios à sociedade. A sua crescente relevância deve-se sobretudo às consideráveis repercussões a nível pessoal, familiar, sociopolítico e económico e que afetam pessoas de todas as idades e a sociedade como um todo, colocando desafios específicos relativamente às relações interpessoais, à qualidade de vida e à saúde mental na pessoa idosa. Deste modo, o presente trabalho tem como objetivo analisar a associação entre a qualidade de vida, a depressão e as características das redes sociais pessoais dos idosos. Participaram no estudo 317 indivíduos, sendo 202 do sexo feminino e 115 do sexo masculino, com idade igual ou superior a 65 anos, com uma média de 77 anos (DP=7,57). Na recolha de dados recorremos a três instrumentos: Geriatric Depression Scale (GDS Short Form 15), (Yesavage et al., 1983; Almeida & Almeida, 1999); Instrumento de Avaliação de Qualidade de Vida da OMS (WHOQOL), (OMS, 1998; Canavarro et al., 2006); Instrumento de Avaliação das Redes Sociais Pessoais (IARSP – Idosos), (Guadalupe, 2010; Guadalupe & Vicente, 2012). Dos resultados destacamos que as características funcionais da rede social pessoal se diferenciaram de forma estatisticamente significativa entre as subamostras de idosos segundo os níveis de qualidade de vida percebida. Saliente-se que, além da relação significativa entre a depressão e qualidade de vida, em que os idosos com um nível mais baixo de qualidade de vida percebida apresentam maiores níveis de depressão (p<0,001), as características funcionais das redes sociais apresentam uma associação clara com a qualidade de vida (p<0,005) e a maioria com a depressão (p<0,014), o que não acontece com as estruturais e com as relacionais-contextuais. Outros resultados indicam que indivíduos com diferentes níveis de qualidade de vida percebida possuem uma estrutura idêntica da rede social pessoal. Ao nível da análise da associação entre as variáveis funcionais da Rede Social Pessoal, Qualidade de Vida e Depressão, o modelo analítico transmite-nos indicadores de investigação e intervenção precisos, o que demonstra a necessidade da continuidade e aprofundamento do presente estudo num âmbito amostral mais alargado e heterogéneo. / In Portugal and in the eastern world, the aging of population creates huge challenges to societies. It's growing relevance is owed to considerable repercussions on the personal, familiar, socio-politic and economic level that affect people of all ages and society as a whole, creating specific challenges regarding interpersonal relationships, quality of life and mental health of the elderly. The current work has the objective of analyzing the association between quality of life, depression and the characteristics of personal social networks of the elderly. 317 individuals have participated in this study, 202 female and 115 male, with age equal or above 65 years old, with an average of 77 years old (DP=7,57). We used three assessment instruments to collect data: Geriatric Depression Scale (GDS Short Form 15), (Yesavage et al., 1983; Almeida & Almeida, 1999); WHO’s Quality of Life Evaluation instrument (WHOQOL) (WHO, 1998; Canavarro et al., 2006); Personal Social Network Analysis Tool (IARSP-Elderly),(Guadalupe, 2010; Guadalupe & Vicente, 2012). The results show that the functional personal network characteristics are significantly different according to their level of quality of life. It should also be noted that not only there is a significant association between depression and quality of life, in which elderly people with a lower quality of life level show higher levels of depression (p<0,001), there is also a clear association between the functional social network characteristics and quality of life (p<0,005), and the majority with depression (p<0,014), which doesn’t happen with structural and relational-contextual social network characteristics. Other results indicate that different levels of quality of life acquire an identical social network structure. On the matter of association between the functional variables of social networks, quality of fife and depression, the analytic model shows precise indicators of research and intervention, which instills us a need to continue and enlarge this study with an wider and more heterogeneous sample.

Machine learning and data decompositions for complex networked dynamical systems

Thesis (Ph.D.)--University of Washington, 2016-08

Bayesian nonparametric latent variable models

L’un des problèmes importants en apprentissage automatique est de déterminer la complexité du modèle à apprendre. Une trop grande complexité mène au surapprentissage, ce qui correspond à trouver des structures qui n’existent pas réellement dans les données, tandis qu’une trop faible complexité mène au sous-apprentissage, c’est-à-dire que l’expressivité du modèle est insuffisante pour capturer l’ensemble des structures présentes dans les données. Pour certains modèles probabilistes, la complexité du modèle se traduit par l’introduction d’une ou plusieurs variables cachées dont le rôle est d’expliquer le processus génératif des données. Il existe diverses approches permettant d’identifier le nombre approprié de variables cachées d’un modèle. Cette thèse s’intéresse aux méthodes Bayésiennes nonparamétriques permettant de déterminer le nombre de variables cachées à utiliser ainsi que leur dimensionnalité. La popularisation des statistiques Bayésiennes nonparamétriques au sein de la communauté de l’apprentissage automatique est assez récente. Leur principal attrait vient du fait qu’elles offrent des modèles hautement flexibles et dont la complexité s’ajuste proportionnellement à la quantité de données disponibles. Au cours des dernières années, la recherche sur les méthodes d’apprentissage Bayésiennes nonparamétriques a porté sur trois aspects principaux : la construction de nouveaux modèles, le développement d’algorithmes d’inférence et les applications. Cette thèse présente nos contributions à ces trois sujets de recherches dans le contexte d’apprentissage de modèles à variables cachées. Dans un premier temps, nous introduisons le Pitman-Yor process mixture of Gaussians, un modèle permettant l’apprentissage de mélanges infinis de Gaussiennes. Nous présentons aussi un algorithme d’inférence permettant de découvrir les composantes cachées du modèle que nous évaluons sur deux applications concrètes de robotique. Nos résultats démontrent que l’approche proposée surpasse en performance et en flexibilité les approches classiques d’apprentissage. Dans un deuxième temps, nous proposons l’extended cascading Indian buffet process, un modèle servant de distribution de probabilité a priori sur l’espace des graphes dirigés acycliques. Dans le contexte de réseaux Bayésien, ce prior permet d’identifier à la fois la présence de variables cachées et la structure du réseau parmi celles-ci. Un algorithme d’inférence Monte Carlo par chaîne de Markov est utilisé pour l’évaluation sur des problèmes d’identification de structures et d’estimation de densités. Dans un dernier temps, nous proposons le Indian chefs process, un modèle plus général que l’extended cascading Indian buffet process servant à l’apprentissage de graphes et d’ordres. L’avantage du nouveau modèle est qu’il admet les connections entres les variables observables et qu’il prend en compte l’ordre des variables. Nous présentons un algorithme d’inférence Monte Carlo par chaîne de Markov avec saut réversible permettant l’apprentissage conjoint de graphes et d’ordres. L’évaluation est faite sur des problèmes d’estimations de densité et de test d’indépendance. Ce modèle est le premier modèle Bayésien nonparamétrique permettant d’apprendre des réseaux Bayésiens disposant d’une structure complètement arbitraire.

Spike-timing dependent plasticity and connectivity in primate sensorimotor cortex

Thesis (Ph.D.)--University of Washington, 2016-06

Requirement Risk Level Forecast Using Bayesian Networks Classifiers

Requirement engineering is a key issue in the development of a software project. Like any other development activity it is not without risks. This work is about the empirical study of risks of requirements by applying machine learning techniques, specifically Bayesian networks classifiers. We have defined several models to predict the risk level for a given requirement using three dataset that collect metrics taken from the requirement specifications of different projects. The classification accuracy of the Bayesian models obtained is evaluated and compared using several classification performance measures. The results of the experiments show that the Bayesians networks allow obtaining valid predictors. Specifically, a tree augmented network structure shows a competitive experimental performance in all datasets. Besides, the relations established between the variables collected to determine the level of risk in a requirement, match with those set by requirement engineers. We show that Bayesian networks are valid tools for the automation of risks assessment in requirement engineering.

Activity-based life cycle costing model for cost estimation and monitoring – Case: manned and autonomous dry bulk carrier

Recent developments in automation, robotics and artificial intelligence have given a push to a wider usage of these technologies in recent years, and nowadays, driverless transport systems are already state-of-the-art on certain legs of transportation. This has given a push for the maritime industry to join the advancement. The case organisation, AAWA initiative, is a joint industry-academia research consortium with the objective of developing readiness for the first commercial autonomous solutions, exploiting state-of-the-art autonomous and remote technology. The initiative develops both autonomous and remote operation technology for navigation, machinery, and all on-board operating systems. The aim of this study is to develop a model with which to estimate and forecast the operational costs, and thus enable comparisons between manned and autonomous cargo vessels. The building process of the model is also described and discussed. Furthermore, the model’s aim is to track and identify the critical success factors of the chosen ship design, and to enable monitoring and tracking of the incurred operational costs as the life cycle of the vessel progresses. The study adopts the constructive research approach, as the aim is to develop a construct to meet the needs of a case organisation. Data has been collected through discussions and meeting with consortium members and researchers, as well as through written and internal communications material. The model itself is built using activity-based life cycle costing, which enables both realistic cost estimation and forecasting, as well as the identification of critical success factors due to the process-orientation adopted from activity-based costing and the statistical nature of Monte Carlo simulation techniques. As the model was able to meet the multiple aims set for it, and the case organisation was satisfied with it, it could be argued that activity-based life cycle costing is the method with which to conduct cost estimation and forecasting in the case of autonomous cargo vessels. The model was able to perform the cost analysis and forecasting, as well as to trace the critical success factors. Later on, it also enabled, albeit hypothetically, monitoring and tracking of the incurred costs. By collecting costs this way, it was argued that the activity-based LCC model is able facilitate learning from and continuous improvement of the autonomous vessel. As with the building process of the model, an individual approach was chosen, while still using the implementation and model building steps presented in existing literature. This was due to two factors: the nature of the model and – perhaps even more importantly – the nature of the case organisation. Furthermore, the loosely organised network structure means that knowing the case organisation and its aims is of great importance when conducting a constructive research.

Dynamic Programming Approaches for Estimating and Applying Large-scale Discrete Choice Models

People go through their life making all kinds of decisions, and some of these decisions affect their demand for transportation, for example, their choices of where to live and where to work, how and when to travel and which route to take. Transport related choices are typically time dependent and characterized by large number of alternatives that can be spatially correlated. This thesis deals with models that can be used to analyze and predict discrete choices in large-scale networks. The proposed models and methods are highly relevant for, but not limited to, transport applications. We model decisions as sequences of choices within the dynamic discrete choice framework, also known as parametric Markov decision processes. Such models are known to be difficult to estimate and to apply to make predictions because dynamic programming problems need to be solved in order to compute choice probabilities. In this thesis we show that it is possible to explore the network structure and the flexibility of dynamic programming so that the dynamic discrete choice modeling approach is not only useful to model time dependent choices, but also makes it easier to model large-scale static choices. The thesis consists of seven articles containing a number of models and methods for estimating, applying and testing large-scale discrete choice models. In the following we group the contributions under three themes: route choice modeling, large-scale multivariate extreme value (MEV) model estimation and nonlinear optimization algorithms. Five articles are related to route choice modeling. We propose different dynamic discrete choice models that allow paths to be correlated based on the MEV and mixed logit models. The resulting route choice models become expensive to estimate and we deal with this challenge by proposing innovative methods that allow to reduce the estimation cost. For example, we propose a decomposition method that not only opens up for possibility of mixing, but also speeds up the estimation for simple logit models, which has implications also for traffic simulation. Moreover, we compare the utility maximization and regret minimization decision rules, and we propose a misspecification test for logit-based route choice models. The second theme is related to the estimation of static discrete choice models with large choice sets. We establish that a class of MEV models can be reformulated as dynamic discrete choice models on the networks of correlation structures. These dynamic models can then be estimated quickly using dynamic programming techniques and an efficient nonlinear optimization algorithm. Finally, the third theme focuses on structured quasi-Newton techniques for estimating discrete choice models by maximum likelihood. We examine and adapt switching methods that can be easily integrated into usual optimization algorithms (line search and trust region) to accelerate the estimation process. The proposed dynamic discrete choice models and estimation methods can be used in various discrete choice applications. In the area of big data analytics, models that can deal with large choice sets and sequential choices are important. Our research can therefore be of interest in various demand analysis applications (predictive analytics) or can be integrated with optimization models (prescriptive analytics). Furthermore, our studies indicate the potential of dynamic programming techniques in this context, even for static models, which opens up a variety of future research directions.

GenoPopTaille. Moving stock assessment into the future

At the ecosystem level, sustainable exploitation of fisheries resources depends not only on the status of target species but also on that of bycatch species, some of which are even more sensitive to exploitation. This is the case for a number of elasmobranchs (skates, rays and sharks) species whose abundance declined during the 20th century. Further, the biology of elamobranchs is still poorly known and traditional fisheries stock assessment methods using fisheries catches and scientific survey data for estimating abundance are expensive or even inapplicable due to the small numbers observed. The GenoPopTaille project attempts to apply to the case of the thornback ray (Raja clavata) recent genetic-based methods for absolute population abundance estimation as well as characterizing its genetic diversity and population structure in the Northeast Atlantic. The poster will present the objectives, challenges and progress made so far by the project.

Método de análise de vulnerabilidade utilizando redes complexas : aplicação na rede de transporte aéreo brasileira

Dissertação (mestrado)—Universidade de Brasília, Faculdade de Tecnologia, Departamento de Engenharia Civil e Ambiental, 2016.

Hyperlinks in e-books : expanding the functionality of end-notes

With its powerful search engines and billions of published pages, the Worldwide Web has become the ultimate tool to explore the human experience. But, despite the advent of the digital revolution, e-books, at their core, have remained remarkably similar to their printed siblings. This has resulted in a clear dichotomy between two ways of reading: on one side, the multi-dimensional world of the Web; on the other, the linearity of books and e-books. My investigation of the literature indicates that the focus of attempts to merge these two modes of production, and hence of reading, has been the insertion of interactivity into fiction. As I will show in the Literature Review, a clear thrust of research since the early 1990s, and in my opinion the most significant, has concentrated on presenting the reader with choices that affect the plot. This has resulted in interactive stories in which the structure of the narrative can be altered by the reader of experimental fiction. The interest in this area of research is not surprising, as the interaction of readers with the fabric of the narrative provides a fertile ground for exploring, analysing, and discussing issues of plot consistency and continuity. I found in the literature several papers concerned with the effects of hyperlinking on literature, but none about how hyperlinked material and narrative could be integrated without compromising the narrative flow as designed by the author. It led me to think that the researchers had accepted hypertextuality and the linear organisation of fiction as being antithetical, thereby ignoring the possibility of exploiting the first while preserving the second. All the works I consulted were focussed on exploring the possibilities provided to authors (and readers) by hypertext or how hypertext literature affects literary criticism. This was true in earlier works by Landow and Harpold and remained true in later works by Bolter and Grusin. To quote another example, in his book Hypertext 3.0, Landow states: “Most who have speculated on the relation between hypertextuality and fiction concentrate [...] on the effects it will have on linear narrative”, and “hypertext opens major questions about story and plot by apparently doing away with linear organization” (Landow, 2006, pp. 220, 221). In other words, the authors have added narrative elements to Web pages, effectively placing their stories in a subordinate role. By focussing on “opening up” the plots, the researchers have missed the opportunity to maintain the integrity of their stories and use hyperlinked information to provide interactive access to backstory and factual bases. This would represent a missing link between the traditional way of reading, in which the readers have no influence on the path the author has laid out for them, and interactive narrative, in which the readers choose their way across alternatives, thereby, at least to a certain extent, creating their own path. It would be, to continue the metaphor, as if the readers could follow the main path created by the author while being able to get “sidetracked” into exploring hyperlinked material. In Hypertext 3.0, Landow refers to an “Axial structure [of hypertext] characteristic of electronic books and scholarly books with foot-and endnotes” versus a “Network structure of hypertext” (Landow, 2006, p. 70). My research aims at generalising the axial structure and extending it to fiction without losing the linearity at its core. In creative nonfiction, the introduction of places, scenes, and settings, together with characterisation, brings to life the facts without altering them; while much fiction draws on facts to provide a foundation, or narrative elements, for the work. But how can the reader distinguish between facts and representations? For example, to what extent do dialogues and perceptions present what was actually said and thought? Some authors of creative nonfiction use end-notes to provide comments and citations while minimising disruption the flow of the main text, but they are limited in scope and constrained in space. Each reader should be able to enjoy the narrative as if it were a novel but also to explore the facts at the level of detail s/he needs. For this to be possible, end-notes should provide a Web-like way of exploring in more detail what the author has already researched. My research aims to develop ways of integrating narrative prose and hyperlinked documents into a Hyperbook. Its goal is to create a new writing paradigm in which a story incorporates a gateway to detailed information. While creative nonfiction uses the techniques of fictional writing to provide reportage of actual events and fact-based fiction illuminates the affectual dimensions of what happened (e.g., Kate Grenville’s The Secret River and Hilary Mantel’s Wolf Hall), Hyperbooks go one step further and link narrative prose to the details of the events on which the narrative is based or, more in general, to information the reader might find of interest. My dissertation introduces and utilises Hyperbooks to engage in two parallel types of investigation Build knowledge about Italian WWII POWs held in Australia and present it as part of a novella in Hyperbook format. Develop a new piece of technology capable of extending the writing and reading process.