Introdução: as infecções são responsáveis por mais de um terço das mortes neonatais, sendo a sepse a de maior expressão. A sepse neonatal precoce (SNP) aumenta em cinco vezes a taxa de mortalidade entre recém-nascidos (RN) de termo e pré-termos tardios e em vinte e cinco vezes a taxa de mortalidade entre pré-termos extremos. A Variabilidade da Frequência Cardíaca (VFC) vem se mostrando capaz de antecipar o diagnóstico, reduzindo em 22% o risco relativo de mortalidade entre os pré-termos de muito baixo peso com sepse. Objetivo: verificar a VFC de RN com suspeita de SNP; identificar medidas significantes e verificar se, associadas a variáveis clínico-laboratoriais, aumentam a chance de identificar pacientes passíveis de desenvolver a doença. Método: utilizou-se um frequencímetro portátil para aferir as medidas da VFC nos domínios do tempo, da frequência e do Caos. Dentre elas, elegeu-se aquelas com curva ROC > 0,75 para, com seus valores de cut-off, aplicar regressão logística e identificar as que melhor se adequassem ao modelo. As variáveis clínico-laboratoriais significantes que restaram da análise univariada foram submetidas à análise multivariada a fim de identificar, também, as que melhor se adequassem ao modelo. Resultados: foram identificadas quatro variáveis clínico-laboratoriais (sexo masculino, idade gestacional < 34 semanas, Score de Rodwell e proteína C-reativa), e nove medidas da VFC (RRmean, SDNN, RR tri index, LF, HF, SD2 do plot de Poincaré, ShaEnt, CorrDim D2 e SamAsy). Cinco apresentaram área sob a curva ROC > 0,75: SDNN, RR tri index, LF, SD2 e CorrDim D2. Depois de aplicada a regressão logística, restou apenas a CorrDim D2 com cut-off = 0,1164. Identificadas, as variáveis foram submetidas ao cálculo do logit para, com isso, quantificar a chance do paciente suspeito de evoluir para a doença, na dependência das três variáveis eleitas: CorrDim D2, idade gestacional < 34 semanas e score de Rodwell. Conclusão: o estudo mostrou que tanto o modelo preditivo clinico como a CorrDim D2 são capazes, de forma independente, de estimar a chance que um futuro paciente com sepse suspeitada tem de efetivamente confirmar o diagnóstico de sepse. E que, além disso, se a CorrDim D2 for agregada ao modelo preditivo clínico, esta chance aumenta consideravelmente. / Introduction: infectious diseases are responsible for more than one-third of neonatal deaths, and sepsis is of great importance. Early Neonatal Sepsis (ENS) increases five times the mortality rate among term and late preterm newborns. Among extreme preterm babies the mortality rate increases by twenty-five times. Heart Rate Variability (HRV) has been showing to be capable of anticipating the diagnosis, thus reducing by 22 percent the relative risk of mortality of very low preterm babies with sepsis. Objective: to verify HRV of newborn babies suspects of having ENS; to identify significant measures of HRV and to verify if, associated to clinical-laboratorial variables, if they improve the chance of identifying patients exposed to developing ENS. Method: a portable frequencimeter was used to registering the measurements of HRV in the domains of time, of frequency and of chaos. Among them, only those with a ROC curve greater than 0.75 were chosen, with their cut-off values to enter a logistic regression with the aim of identifying those more suitable to the model. The clinical-laboratorial variables which were considered significant in a univariete analysis were also submitted to the multivariate analysis with the purpose of identifying those better fitted to the model. Results: four clinical-laboratorial variables (male sex, gestational age less than 34 weeks, the Rodwell Score and C-Reactive Protein); similarly, nine measures of HRV (RRmean, SDNN, RR tri index, LF, HF, SD2 of Poincaré plot, ShaEnt, CorrDimD2 and SamAsy). Five of them presented an area under the ROC curve greater than 0.75: SDNN, RR tri index, LF, SD2 and CorrDim D2. Once applied the logistic regression, only CorrDim D2 remained, with a cut-off value of 0.1164. The identified variables were, then, submitted to the calculation of the logit, with the purpose of quantifying the chance of a patient suspect of evolving to a sepsis, in the dependence of the three elected variables: CorrDim D2, gestational age under 34 weeks and the Score of Rodwell. Conclusion: the study showed that both, the predictive clinical model as CorrDim D2 are able, independently, to estimate the chance that a patient with suspected sepsis future has to effectively confirm the diagnosis of sepsis. And that, moreover, if the CorrDim D2 is aggregated to clinical predictive model, this chance increases considerably.

Introdução: as infecções são responsáveis por mais de um terço das mortes neonatais, sendo a sepse a de maior expressão. A sepse neonatal precoce (SNP) aumenta em cinco vezes a taxa de mortalidade entre recém-nascidos (RN) de termo e pré-termos tardios e em vinte e cinco vezes a taxa de mortalidade entre pré-termos extremos. A Variabilidade da Frequência Cardíaca (VFC) vem se mostrando capaz de antecipar o diagnóstico, reduzindo em 22% o risco relativo de mortalidade entre os pré-termos de muito baixo peso com sepse. Objetivo: verificar a VFC de RN com suspeita de SNP; identificar medidas significantes e verificar se, associadas a variáveis clínico-laboratoriais, aumentam a chance de identificar pacientes passíveis de desenvolver a doença. Método: utilizou-se um frequencímetro portátil para aferir as medidas da VFC nos domínios do tempo, da frequência e do Caos. Dentre elas, elegeu-se aquelas com curva ROC > 0,75 para, com seus valores de cut-off, aplicar regressão logística e identificar as que melhor se adequassem ao modelo. As variáveis clínico-laboratoriais significantes que restaram da análise univariada foram submetidas à análise multivariada a fim de identificar, também, as que melhor se adequassem ao modelo. Resultados: foram identificadas quatro variáveis clínico-laboratoriais (sexo masculino, idade gestacional < 34 semanas, Score de Rodwell e proteína C-reativa), e nove medidas da VFC (RRmean, SDNN, RR tri index, LF, HF, SD2 do plot de Poincaré, ShaEnt, CorrDim D2 e SamAsy). Cinco apresentaram área sob a curva ROC > 0,75: SDNN, RR tri index, LF, SD2 e CorrDim D2. Depois de aplicada a regressão logística, restou apenas a CorrDim D2 com cut-off = 0,1164. Identificadas, as variáveis foram submetidas ao cálculo do logit para, com isso, quantificar a chance do paciente suspeito de evoluir para a doença, na dependência das três variáveis eleitas: CorrDim D2, idade gestacional < 34 semanas e score de Rodwell. Conclusão: o estudo mostrou que tanto o modelo preditivo clinico como a CorrDim D2 são capazes, de forma independente, de estimar a chance que um futuro paciente com sepse suspeitada tem de efetivamente confirmar o diagnóstico de sepse. E que, além disso, se a CorrDim D2 for agregada ao modelo preditivo clínico, esta chance aumenta consideravelmente. / Introduction: infectious diseases are responsible for more than one-third of neonatal deaths, and sepsis is of great importance. Early Neonatal Sepsis (ENS) increases five times the mortality rate among term and late preterm newborns. Among extreme preterm babies the mortality rate increases by twenty-five times. Heart Rate Variability (HRV) has been showing to be capable of anticipating the diagnosis, thus reducing by 22 percent the relative risk of mortality of very low preterm babies with sepsis. Objective: to verify HRV of newborn babies suspects of having ENS; to identify significant measures of HRV and to verify if, associated to clinical-laboratorial variables, if they improve the chance of identifying patients exposed to developing ENS. Method: a portable frequencimeter was used to registering the measurements of HRV in the domains of time, of frequency and of chaos. Among them, only those with a ROC curve greater than 0.75 were chosen, with their cut-off values to enter a logistic regression with the aim of identifying those more suitable to the model. The clinical-laboratorial variables which were considered significant in a univariete analysis were also submitted to the multivariate analysis with the purpose of identifying those better fitted to the model. Results: four clinical-laboratorial variables (male sex, gestational age less than 34 weeks, the Rodwell Score and C-Reactive Protein); similarly, nine measures of HRV (RRmean, SDNN, RR tri index, LF, HF, SD2 of Poincaré plot, ShaEnt, CorrDimD2 and SamAsy). Five of them presented an area under the ROC curve greater than 0.75: SDNN, RR tri index, LF, SD2 and CorrDim D2. Once applied the logistic regression, only CorrDim D2 remained, with a cut-off value of 0.1164. The identified variables were, then, submitted to the calculation of the logit, with the purpose of quantifying the chance of a patient suspect of evolving to a sepsis, in the dependence of the three elected variables: CorrDim D2, gestational age under 34 weeks and the Score of Rodwell. Conclusion: the study showed that both, the predictive clinical model as CorrDim D2 are able, independently, to estimate the chance that a patient with suspected sepsis future has to effectively confirm the diagnosis of sepsis. And that, moreover, if the CorrDim D2 is aggregated to clinical predictive model, this chance increases considerably.

A evolução de sistemas distribuídos resultou em aumento significativo de complexidade para manutenção e gerenciamento, tornando pouco eficientes técnicas convencionais baseadas em intervenções manuais. Isso motivou pesquisas que deram origem ao paradigma de computação autônoma (Autonomic Computing), que provê aspectos de auto-configuração, auto-recuperação, auto-otimização e auto-proteção a fim de tornar sistemas auto-gerenciáveis. Nesse contexto, esta tese teve como objetivo prover autonomia a ambientes distribuídos, sem a necessidade de mudar o paradigma de programação e as aplicações de usuários. Para isso, propôs-se uma abordagem que emprega técnicas para compreensão e predição de dinâmicas comportamentais de processos, utilizando abordagens de sistemas dinâmicos, inteligência artificial e teoria do caos. Os estudos realizados no decorrer desta pesquisa demonstraram que, ao predizer padrões comportamentais, pode-se otimizar diversos aspectos de computação distribuída, suportando tomadas de decisão autônomas pelos ambientes. Para validar a abordagem proposta, foi desenvolvida uma política de escalonamento distribuído, denominada PredRoute, a qual utiliza o conhecimento sobre o comportamento de processos para otimizar, transparentemente, a alocação de recursos. Experimentos realizados demonstraram que essa política aumenta o desempenho em até 4 ordens de grandeza e apresenta baixo custo computacional, o que permite a sua adoção para escalonamento online de processos / The evolution of distributed systems resulted in a significant growth in management and support complexities, which uncovered the inefficiencies incurred by the usage of conventional management techniques, based in manual interventions. This, therefore, has motivated researches towards the concept of Autonomic Computing, which provides aspects of self-configuration, self-healing, self-optimization and self-protection, aiming at developing computer systems capable of self-management. In this context, this thesis was conceived with the goal of providing autonomy to distributed systems, without changing the programming paradigm or user applications. In order to reach this goal, we proposed an approach which employs techniques capable of modelling and predicting the dynamics of application behavior, using concepts introduced in dynamical systems, artificial intelligence, and chaos theory. The obtained results demonstrated that it is possible to optimize several aspects of distributed computing, providing support for autonomic computing capabilities to distributed environments. In order to validate the proposed approach, a distributed scheduling policy was developed, named PredRoute, which uses the knowledge about the process behavior to transparently optimize the resource allocation. Experimental results demonstrated that this policy can improve the system performance by up to a power of 4, and also requires a considerably low computational cost, which suggests its adoption for online process scheduling in distributed environments

Neste trabalho demonstramos que padrões e aleatoriedade estão intimamente relacionados, ao contrário do que intuitivamente é considerado como campos opostos. Esta abordagem visa dois propósitos: por um lado, obter vantagens das propriedades caóticas para medir pseudo-aleatoriedade, e por outro lado, extrair padrões de diagramas espaço-tempo como método de reconhecimento de padrões. Este trabalho centrou-se em dois métodos relacionados com sistemas complexos, como sistemas dinâmicos de tempo discreto, redes complexas, autômatos celulares (AC) e suas combinações. O primeiro método foi explorar as propriedades das profundezas do caos como fonte de pseudo-aleatoriedade a partir de sistemas dinâmicos caóticos, como o mapa logístico e o mapa da tenda. Observamos que os padrões desaparecem e a pseudo-aleatoriedade é aumentada pela remoção de k dígitos à direita da vírgula dos pontos de uma órbita original de um mapa caótico. Portanto, foi encontrada uma fonte caótica interessante para obter geradores de números de pseudo-aleatórios (PRNGs) parametrizada por k. Um segundo método foi proposto com base na incorporação de autômatos celulares na topologia de rede, também chamada de rede-autômato, visando caracterizar as redes a partir da dinâmica espaço-temporal intrínseca dessas redes. Quatro problemas de grande demanda foram explorados, tais como (i) identificar redes sociais online; (ii) identificar organismos de diferentes domínios da vida através de suas redes metabólicas; (iii) classificar padrões de distribuição de estômatos variando de acordo com diferentes condições ambientais; e (iv) o problema de identificação de autoria. Finalmente, essa mesma abordagem foi utilizada para analisar as sequências de números pseudo-aleatórios gerados pelo padrão ouro do k-mapa logístico no contexto do reconhecimento de padrões. A abordagem proposta permitiu explorar padrões e pseudoaleatoriedade extraídos de uma miríade de sistemas com resultados bem-sucedidos em termos de acerto e boa pseudo-aleatoriedade. Além disso, este trabalho trouxe consigo progressos significativos em aplicações de reconhecimento de padrões do mundo real de um amplo ramo de campos como criptografia, criptoanálise, biologia e ciência dos dados. / In this work, we demonstrate that patterns and randomness are close related, contrary to what intuitively is considered as opposite fields. We aimed for a pattern recognition approach that aims for two purposes: (i) to take advantages from the chaotic properties as a source of pseudo-randomness in order to measure pseudo-randomness and (ii) to extract patterns from spatio-temporal diagrams obtained from complex systems models as a pattern recognition method. This work has focused on different complex systems such as discrete dynamical systems, complex networks, cellular automata (CA), and their combinations. The first method was to explore the chaotic properties in a deep-zoom manner as a source of pseudo-randomness from chaotic dynamical systems such as the logistic map and the tent map. We observed that the patterns vanish and therefore pseudo-randomness is increased by removing k right digits from the original orbit sequences. Therefore, we found an interesting chaotic source to obtain pseudo-randomness number generators (PRNGs). A second method was proposed based on the embedding of cellular automata (CA) over a network topology, also called network automata, aiming to characterize networks from the intrinsic spatio-temporal dynamics of these networks. Various on-demand problems were explored such as (i) identifying online social networks; (ii) identifying organisms from distinct domains of life through their metabolic networks; (iii) classifying stomata distribution patterns varying according to different environmental conditions; and (iv) the authorship identification problem. Finally, this same approach was used to analyze the sequences of pseudo-random numbers generated by the gold standard k-logistic map in the context of pattern recognition. So far, the proposed pattern recognition approach based on non-linear systems allowed us to explored patterns and pseudo-randomness extracted from a myriad of systems with successful results in terms of accuracy and good pseudorandomness. The proposed method has made significant progress in real-world pattern recognition applications from a wide branch of fields such as Cryptography, Cryptanalysis, Biology and Data Science.

Small businesses are considered the backbone of the U.S. economy with significant contributions in the areas of job creation and economic development. However, 79% of small businesses fail within the first 5 years. This multiple case study aimed to explore strategies and knowledge of resources that owners of small businesses used to sustain business operations for longer than the first 5 years. The population included 5 minority owners of small businesses in Texas. Chaos theory formed the conceptual framework. The data collection process included semistructured interviews, member checks, field notes, company artifacts, and archival documents. Data were analyzed using Yin's data analysis steps of compiling, disassembling, reassembling, interpreting, and concluding. Three themes emerged from the analysis: effective management of the business environment, effective planning, and business owners' skills and knowledge. The U.S. Small Business Administration, local chambers of commerce, and owners of small businesses may benefit from the findings of this study by gaining an understanding of successful minority owners of small businesses' implemented strategies that enable business success and profitability. The implications of this study for positive social change include identifying sustainable strategies minority owners of small businesses can use to advance business growth, increase financial security, achieve employee job sustainability, and potentially stimulate the local community with job creation.

This paper analyzes two main frameworks that challenge the “mainstream” finance theory and the random walk hypothesis. The first framework is based on investor irrationality and is called Behavioural Finance. The second framework views the financial market as a chaotic system and is called Fractal Theory of a financial market. Behavioural Finance attacks the assumption of investor rationality, thus challenging the conventional finance theories on the micro level. Fractal Theory challenges the EMH and the “macroeconomics” of finance. This paper presents a step towards unifying the frameworks of Behavioural Finance and Fractal Theory. After a review of the relevant literature, a model of the financial market is suggested that rests on the predictions of both Behavioural Finance and Fractal Theory. As a next step, a mathematical algorithm is described that allows to test the financial market for consistency with the presented model. The mathematical algorithm is applied to 10 years of daily S&amp;P500 price quotes, and consistent statistical evidence shows that the predicted fractal pattern reveals itself in the S&amp;P500 prices. The new model outperforms the random walk in out-of-sample forecasting.

This thesis employs perspectives inspired by General Systems Theory to address issues in philosophy, including moral philosophy and philosophy of mind. I present an overview of a range of ideas from the study of physical systems that may be used to provide a firm physicalist foundation to explorations of some common questions in philosophy. I divide these topics into three categories: the Physical Category, the Relevance Category and the Signal Elements Category. I interpret concepts from General Systems Theory, including information and entropy, in a way that I believe facilitates their incorporation into philosophical discussion. I also explain various points arising from General Systems Theory, such as order and disorder, stability, complexity, and self-organisation, and show how ideas from these areas can be applied to certain philosophical problems. I explain relevance in terms of stability, in order to link these scientific perspectives to questions in moral philosophy. I suggest a possible physical foundation for a theory of morality, which takes the form of a variety of Utilitarianism, intended to balance the competing needs of open systems to manage entropy. Such a theory of morality must be capable of dealing with limitations arising from the physicality of information; I propose game theory as a solution to this problem. This thesis also covers issues connected to the above points regarding the nature of consciousness and communication. In particular, I examine the role of linguistic associations in consciousness; and some related features of language and other non-linear representational schemes.

This study was conducted to investigate the change in pre-service teacher education in Turkey by using Chaos Theory. The research questions were the following: 1) How did the 1982 restructuring relate to the 1998 restructuring? (2) What were the reasons for the anomalies that led to the 1998 restructuring? (3) How did the 1998 process of transformation work? (4) At which stage of the curve is the system now? (5) What are the possible paths the new model may evolve? The data sources in this qualitative research study were interviews and documents. The 28 participants of the interviews included some key decision-makers at related institutes and some academic staff at 8 different Education Faculties in Ankara, EskiSehir, Bolu, Adana, and KirSehir. The written documents included some relevant reports, meeting minutes, the proceedings of conferences and panel discussions, research articles, and some articles of four different newspapers in Turkey. A model of &lsquo / Change as Chaotic Transformation&rsquo / was designed by the researcher as a theoretical framework. The data, subjected to a content analysis, revealed that the logic of chaotic transformation has significant implications in investigating and understanding the stability versus instability phases in teacher education affairs in Turkey / roughly 1950s - 1970 (evolution and stability), 1970s (disequilibrium and turbulence), 1982 &ndash / early 1990s (&lsquo / forced stability&rsquo / ), and mid-1990s to 1998 (turbulence and transformation) are significant phases in this sense. The data also revealed that the reasons for the anomalies that led to the 1998 restructuring were in both program and administrative issues. Further, the process of transformation in 1998 was &lsquo / self-organization.&rsquo / It is found that presently the 1998 model is perceived as not yet institutionalized / the achievements in program issues realigned teacher education to its &lsquo / identity&rsquo / , but the path the new model may evolve depends on the clarification and institutionalization of &lsquo / governance&rsquo / and implementing strategies for developing &lsquo / human resources&rsquo / (the teacher educator profile).

This thesis examines the utility of mathematical complexity measures for the analysis of stratospheric dynamics. Through theoretical considerations and tests with artificial data sets, e.g., the iteration of the logistic map, suitable parameters are determined for the application of the statistical entropy measures sample entropy (SE) and Rényi entropy (RE) to methane (a long-lived stratospheric tracer) data from simulations of the SOCOL chemistry-climate model. The SE is shown to be useful for quantifying the variability of recurring patterns in a time series and is able to identify tropical patterns similar to those reported by previous studies of the ``tropical pipe'' region. However, the SE is found to be unsuitable for use in polar regions, due to the non-stationarity of the methane data at extra-tropical latitudes. It is concluded that the SE cannot be used to analyse climate complexity on a global scale. The focus is turned to the RE, which is a complexity measure of probability distribution functions (PDFs). Using the second order RE and a normalisation factor, zonal PDFs of ten consecutive days of methane data are created with a Bayesian optimal binning technique. From these, the RE is calculated for every day (moving 10-day window). The results indicate that the RE is a promising tool for identifying stratospheric mixing barriers. In Southern Hemisphere winter and early spring, RE produces patterns similar to those found in other studies of stratospheric mixing. High values of RE are found to be indicative of the strong fluctuations in tracer distributions associated with relatively unmixed air in general, and with gradients in the vicinity of mixing barriers, in particular. Lower values suggest more thoroughly mixed air masses. The analysis is extended to eleven years of model data. Realistic inter-annual variability of some of the RE structures is observed, particularly in the Southern Hemisphere. By calculating a climatological mean of the RE for this period, additional mixing patterns are identified in the Northern Hemisphere. The validity of the RE analysis and its interpretation is underlined by showing that qualitatively similar patterns can be seen when using observational satellite data of a different tracer. Compared to previous techniques, the RE has the advantage that it requires significantly less computational effort, as it can be used to derive dynamical information from model or measurement tracer data without relying on any additional input such as wind fields. The results presented in this thesis strongly suggest that the RE is a useful new metric for analysing stratospheric mixing and its variability from climate model data. Furthermore, it is shown that the RE measure is very robust with respect to data gaps, which makes it ideal for application to observations. Hence, using the RE for comparing observations of tracer distributions with those from model simulations potentially presents a novel approach for analysing mixing in the stratosphere.

Esta tese de doutorado analisa dois romances do escritor Norte-Americano Robert Coover como exemplos de escrita hipertextual e de hiperficção no suporte do livro de papel. A complexidade dos romances John's Wife e The Adventures of Lucky Pierre integra os elementos culturais característicos da atual fase do capitalismo e as práticas tecnologizadas que vêm forjando uma subjetividade diferente na escrita e leitura hipertextual, a subjetividade pós-humana. Os modelos da complexidade dos romances derivam do conceito de atratores estranhos da Teoria do Caos e de rizoma da Nomadologia. As transformações no grau de corporeidade dos personagens estabelecem o plano em que se discute a turbulência e a pós-humanidade. As noções de padrões dinâmicos e atratores estranhos e os conceitos do Corpo sem Órgãos e do Rizoma são interpretados para se revisar a narratologia e chegar a categorias apropriadas ao estudo dos romances. A leitura exercitada nesta tese põe em prática a proposta de leitura corpórea de Daniel Punday. As mudanças no grau de materialidade dos personagens são associadas aos estágios de ordem, turbulência e caos na estória, agindo sobre a constituição da subjetividade ao longo do processo de leitura. A inscrição dos planos de consistência que Coover realiza para se contrapor à linearidade e acomodar as feições hipertextuais nas narrativas em papel descreve a trajetória rizomática dos personagens. O presente estudo leva a concluir que a narrativa hoje se constitui antes como um regime numa relação rizomática com outros regimes na prática cultural do que como forma e gênero predominantemente literários. Também se conclui que a subjetividade pós-humana emerge alinhada a uma identidade de classe que tem nos romances hipertextuais a sua forma literária predileta. / This doctoral dissertation analyzes two novels by the American novelist Robert Coover as examples of hypertextual writing on the book bound page, as tokens of hyperfiction. The complexity displayed in the novels, John's Wife and The Adventures of Lucky Pierre, integrates the cultural elements that characterize the contemporary condition of capitalism and technologized practices that have fostered a different subjectivity evidenced in hypertextual writing and reading, the posthuman subjectivity. The models that account for the complexity of each novel are drawn from the concept of strange attractors in Chaos Theory and from the concept of rhizome in Nomadology. The transformations the characters undergo in the degree of their corporeality sets the plane on which to discuss turbulence and posthumanity. The notions of dynamic patterns and strange attractors, along with the concept of the Body without Organs and Rhizome are interpreted, leading to the revision of narratology and to analytical categories appropriate to the study of the novels. The reading exercised throughout this dissertation enacts Daniel Punday's corporeal reading. The changes in the characters' degree of materiality are associated with the stages of order, turbulence and chaos in the story, bearing on the constitution of subjectivity within and along the reading process. Coover's inscription of planes of consistency to counter linearity and accommodate hypertextual features to the paper supported narratives describes the characters' trajectory as rhizomatic. The study led to the conclusion that narrative today stands more as a regime in a rhizomatic relation with other regimes in cultural practice than as an exclusively literary form and genre. Besides this, posthuman subjectivity emerges as class identity, holding hypertextual novels as their literary form of choice.