Étude des systèmes complexes - Des réseaux au connectome du cerveau

La connectomique est l’étude des cartes de connectivité du cerveau (animal ou humain), qu’on nomme connectomes. À l’aide des outils développés par la science des réseaux complexes, la connectomique tente de décrire la complexité fonctionnelle et structurelle du cerveau. L’organisation des connexions du connectome, particulièrement la hiérarchie sous-jacente, joue un rôle majeur. Jusqu’à présent, les modèles hiérarchiques utilisés en connectomique sont pauvres en propriétés émergentes et présentent des structures régulières. Or, la complexité et la richesse hiérarchique du connectome et de réseaux réels ne sont pas saisies par ces modèles. Nous introduisons un nouveau modèle de croissance de réseaux hiérarchiques basé sur l’attachement préférentiel (HPA - Hierarchical preferential attachment). La calibration du modèle sur les propriétés structurelles de réseaux hiérarchiques réels permet de reproduire plusieurs propriétés émergentes telles que la navigabilité, la fractalité et l’agrégation. Le modèle permet entre autres de contrôler la structure hiérarchique et apporte un support supplémentaire quant à l’influence de la structure sur les propriétés émergentes. Puisque le cerveau est continuellement en activité, nous nous intéressons également aux propriétés dynamiques sur des structures hiérarchiques produites par HPA. L’existence d’états dynamiques d’activité soutenue, analogues à l’état minimal de l’activité cérébrale, est étudiée en imposant une dynamique neuronale binaire. Bien que l’organisation hiérarchique favorise la présence d’un état d’activité minimal, l’activité persistante émerge du contrôle de la propagation par la structure du réseau.

School leaders as both colonized and colonizers: understanding professional identity in an era of no child left behind

This study positioned the federal No Child Left Behind (NCLB) Act of 2002 as a reified colonizing entity, inscribing its hegemonic authority upon the professional identity and work of school principals within their school communities of practice. Pressure on educators and students intensifies each year as the benchmark for Adequate Yearly Progress under the NCLB policy is raised, resulting in standards-based reform, scripted curriculum and pedagogy, absence of elective subjects, and a general lack of autonomy critical to the work of teachers as they approach each unique class and student (Crocco & Costigan, 2007; Mabry & Margolis, 2006). Emphasis on high stakes standardized testing as the indicator for student achievement (Popham, 2005) affects educators’ professional identity through dramatic pedagological and structural changes in schools (Day, Flores, & Viana, 2007). These dramatic changes to the ways our nation conducts schooling must be understood and thought about critically from school leaders’ perspectives as their professional identity is influenced by large scale NCLB school reform. The author explored the impact No Child Left Behind reform had on the professional identity of fourteen, veteran Illinois principals leading in urban, small urban, suburban, and rural middle and elementary schools. Qualitative data were collected during semi-structured interviews and focus groups and analyzed using a dual theoretical framework of postcolonial and identity theories. Postcolonial theory provided a lens from which the author applied a metaphor of colonization to principals’ experiences as colonized-colonizers in a time of school reform. Principal interview data illustrated many examples of NCLB as a colonizing authority having a significant impact on the professional identity of school leaders. This framework was used to interpret data in a unique and alternative way and contributed to the need to better understand the ways school leaders respond to district-level, state-level, and national-level accountability policies (Sloan, 2000). Identity theory situated principals as professionals shaped by the communities of practice in which they lead. Principals’ professional identity has become more data-driven as a result of NCLB and their role as instructional leaders has intensified. The data showed that NCLB has changed the work and professional identity of principals in terms of use of data, classroom instruction, Response to Intervention, and staffing changes. Although NCLB defines success in terms of meeting or exceeding the benchmark for Adequate Yearly Progress, principals’ view AYP as only one measurement of their success. The need to meet the benchmark for AYP is a present reality that necessitates school-wide attention to reading and math achievement. At this time, principals leading in affluent, somewhat homogeneous schools typically experience less pressure and more power under NCLB and are more often labeled “successful” school communities. In contrast, principals leading in schools with more heterogeneity experience more pressure and lack of power under NCLB and are more often labeled “failing” school communities. Implications from this study for practitioners and policymakers include a need to reexamine the intents and outcomes of the policy for all school communities, especially in terms of power and voice. Recommendations for policy reform include moving to a growth model with multi-year assessments that make sense for individual students rather than one standardized test score as the measure for achievement. Overall, the study reveals enhancements and constraints NCLB policy has caused in a variety of school contexts, which have affected the professional identity of school leaders.

A Caputo fractional derivative of a function with respect to another function

In this paper we consider a Caputo type fractional derivative with respect to another function. Some properties, like the semigroup law, a relationship between the fractional derivative and the fractional integral, Taylor’s Theorem, Fermat’s Theorem, etc., are studied. Also, a numerical method to deal with such operators, consisting in approximating the fractional derivative by a sum that depends on the first-order derivative, is presented. Relying on examples, we show the efficiency and applicability of the method. Finally, an application of the fractional derivative, by considering a Population Growth Model, and showing that we can model more accurately the process using different kernels for the fractional operator is provided.

Essays on Macroeconomic Trends and Cycles

This dissertation describes two studies on macroeconomic trends and cycles. The first chapter studies the impact of Information Technology (IT) on the U.S. labor market. Over the past 30 years, employment and income shares of routine-intensive occupations have declined significantly relative to nonroutine occupations, and the overall U.S. labor income share has declined relative to capital. Furthermore, the decline of routine employment has been largely concentrated during recessions and ensuing recoveries. I build a model of unbalanced growth to assess the role of computerization and IT in driving these labor market trends and cycles. I augment a neoclassical growth model with exogenous IT progress as a form of Routine-Biased Technological Change (RBTC). I show analytically that RBTC causes the overall labor income share to follow a U-shaped time path, as the monotonic decline of routine labor share is increasingly offset by the monotonic rise of nonroutine labor share and the elasticity of substitution between the overall labor and capital declines under IT progress. Quantitatively, the model explains nearly all the divergence between routine and nonroutine labor in the period 1986-2014, as well as the mild decline of the overall labor share between 1986 and the early 2000s. However, the model with IT progress alone cannot explain the accelerated decline of labor income share after the early 2000s, suggesting that other factors, such as globalization, may have played a larger role in this period. Lastly, when nonconvex labor adjustment costs are present, the model generates a stepwise decline in routine labor hours, qualitatively consistent with the data. The timing of these trend adjustments can be significantly affected by aggregate productivity shocks and concentrated in recessions. The second chapter studies the implications of loss aversion on the business cycle dynamics of aggregate consumption and labor hours. Loss aversion refers to the fact that people are distinctively more sensitive to losses than to gains. Loss averse agents are very risk averse around the reference point and exhibit asymmetric responses to positive and negative income shocks. In an otherwise standard Real Business Cycle (RBC) model, I study loss aversion in both consumption alone and consumption-and-leisure together. My results indicate that how loss aversion affects business cycle dynamics depends critically on the nature of the reference point. If, for example, the reference point is status quo, loss aversion dramatically lowers the effective inter-temporal rate of substitution and induces excessive consumption smoothing. In contrast, if the reference point is fixed at a constant level, loss aversion generates a flat region in the decision rules and asymmetric impulse responses to technology shocks. Under a reasonable parametrization, loss aversion has the potential to generate asymmetric business cycles with deeper and more prolonged recessions.

Early life history of larvae and early juvenile atlantic horse mackerel trachurus trachurus off the portuguese west coast

Early life history traits (ELHTs) are key to understand recruitment patterns in marine animals. However, for reef fishes, studies on ELHTs are mainly focused on tropical systems and little is known for temperate reefs. In this study we used SMURFs (Standard Monitoring Units for the Recruitment of Reef Fishes) to collect fish in a temperate rocky reef system (Arrábida Marine Park, Portugal) on a weekly basis for three months during the recruitment period. Six sub-surface SMURFs sampled 2490 Atlantic horse mackerel (Trachurus trachurus) postlarvae and juveniles. Sagittal and lapilli otoliths were extracted from a subsample of 296 fish and ELHTs, such as size and age at settlement, growth rate and age at first secondary growth formation were examined. Additionally, we tested three growth curves and selected the best suited to back-calculate the hatching pattern based on the lengths of all sampled fish. Standard length ranged from 6.13 mm to 48.56 mm and subsampled fish were aged between 19 days to 44 days. Age and size at settlement were estimated between 19 days and 36 days for individuals of 6.13 mm and 24.95 mm, respectively. Otolith shape changed clearly with increasing age and, on average, secondary growth started to form on day 33 (±3 days). Age/length relationship was well described by a Gompertz growth model which was used to back-calculate hatching dates. Four distinct hatching cohorts were identified with fish of the earliest cohort showing a faster body and otolith growth. This study indicates that the nearshore environment might have an important role in the early growth, development and hence recruitment of Atlantic horse mackerel. Information on the early life history of Atlantic horse mackerel is key to understand recruitment processes for this economically and biologically important species.

Evaluation of Information Entropy from Acoustic Emission Waveforms as a Fatigue Damage Metric for Al7075-T6

Information entropy measured from acoustic emission (AE) waveforms is shown to be an indicator of fatigue damage in a high-strength aluminum alloy. Several tension-tension fatigue experiments were performed with dogbone samples of aluminum alloy, Al7075-T6, a commonly used material in aerospace structures. Unlike previous studies in which fatigue damage is simply measured based on visible crack growth, this work investigated fatigue damage prior to crack initiation through the use of instantaneous elastic modulus degradation. Three methods of measuring the AE information entropy, regarded as a direct measure of microstructural disorder, are proposed and compared with traditional damage-related AE features. Results show that one of the three entropy measurement methods appears to better assess damage than the traditional AE features, while the other two entropies have unique trends that can differentiate between small and large cracks.

Multifactorial analysis of changes in body mass index across the adult life course: a study with 65 years of follow-up

Background: Although the negative consequences on health of being obese are well known, most adults gain weight across the lifespan. The general increase in body mass index (BMI) is mainly considered to originate from behavioral and environmental changes; however, few studies have evaluated the influence of these factors on change in BMI in the presence of genetic risk. We aimed to study the influence of multifactorial causes of change in BMI, over 65 years. Methods and Findings: Totally, 6130 participants from TwinGene, who had up to five assessments, and 536 from the Swedish Adoption/Twin Study of Aging, who had up to 12 assessments, ranging over 65 years were included. The influence of lifestyle factors, birth cohort, cardiometabolic diseases and an individual obesity genetic risk score (OGRS) based on 32 single nucleotide polymorphisms on change in BMI was evaluated with a growth model. For both sexes, BMI increased from early adulthood to age of 65 years, after which the increase leveled off; BMI declined after age of 80 years. A higher OGRS, birth after 1925 and cardiometabolic diseases were associated with higher average BMI and a steeper increase in BMI prior to 65 years of age. Among men, few factors were identified that influence BMI trajectories in late life, whereas for women type 2 diabetes mellitus and dementia were associated with a steeper decrease in BMI after the age of 65 years. Conclusions: There are two turning points in BMI in late adulthood, one at the age of 65 years and one at the age 80 years. Factors associated with an increase in BMI in midlife were not associated with an increase in BMI after the age of 65 years. These findings indicate that the causes and consequences of change in BMI differ across the lifespan. Current health recommendations need to be adjusted accordingly.

El efecto de la definición regulatoria de banda ancha sobre la difusión y la competencia del mercado de servicios de Internet fijo en Colombia

A partir de la dinámica evolutiva de la economía de las Tecnologías de la Información y las Comunicaciones y el establecimiento de estándares mínimos de velocidad en distintos contextos regulatorios a nivel mundial, en particular en Colombia, en el presente artículo se presentan diversas aproximaciones empíricas para evaluar los efectos reales que conlleva el establecimiento de definiciones de servicios de banda ancha en el mercado de Internet fijo. Con base en los datos disponibles para Colombia sobre los planes de servicios de Internet fijo ofrecidos durante el periodo 2006-2012, se estima para los segmentos residencial y corporativo el proceso de difusión logístico modificado y el modelo de interacción estratégica para identificar los impactos generados sobre la masificación del servicio a nivel municipal y sobre las decisiones estratégicas que adoptan los operadores, respectivamente. Respecto a los resultados, se encuentra, por una parte, que las dos medidas regulatorias establecidas en Colombia en 2008 y 2010 presentan efectos significativos y positivos sobre el desplazamiento y el crecimiento de los procesos de difusión a nivel municipal. Por otra parte, se observa sustituibilidad estratégica en las decisiones de oferta de velocidad de descarga por parte de los operadores corporativos mientras que, a partir del análisis de distanciamiento de la velocidad ofrecida respecto al estándar mínimo de banda ancha, se demuestra que los proveedores de servicios residenciales tienden a agrupar sus decisiones de velocidad alrededor de los niveles establecidos por regulación.

Does international trade produce convergence?

In spite of increasing globalization around the world, the effects of international trade on economic growth are not very clear. I consider an endogenous economic growth model in an open economy with the Home Market Effect (HME) and non-homothetic preferences in order to identify some determinants of the different results in this relationship. The model shows how trade between similar countries leads to convergence in economic growth when knowledge spillovers are present, while trade between very asymmetric countries produces divergence and may become trade in a poverty or growth trap. The results for welfare move in the same direction as economic growth since convergence implies increases in welfare for both countries, while divergence leads to increases in welfare for the largest country and the opposite for its commercial partner in the absence of knowledge spillovers. International trade does not implicate greater welfare as is usual in a static context under CES preferences.

Modelos estocásticos de crescimento individual e desenvolvimento de software de estimação e previsão

Os modelos de crescimento individual são geralmente adaptações de modelos de crescimento de populações. Inicialmente estes modelos eram apenas determinísticos, isto é, não incorporavam as flutuações aleatórias do ambiente. Com o desenvolvimento da teoria do cálculo estocástico podemos adicionar um termo estocástico, que representa a aleatoriedade ambiental que influencia o processo em estudo. Actualmente, o estudo do crescimento individual em ambiente aleatório é cada vez mais importante, não apenas pela vertente financeira, mas também devido às suas aplicações nas áreas da saúde e da pecuária, entre outras. Problemas como o ajustamento de modelos de crescimento individual, estimação de parâmetros e previsão de tamanhos futuros são tratados neste trabalho. São apresentadas novas aplicações do modelo estocástico monomolecular generalizado e um novo software de aplicação deste e de outros modelos. ABSTRACT: Individual growth models are usually adaptations of growth population models. Initially these models were only deterministic, that is, they did not incorporate the random fluctuations of the environment. With the development of the theory of stochastic calculus, we can add a stochastic term that represents the random environmental influences in the process under study. Currently, the study of individual growth in a random environment is increasingly important, not only by the financial scope but also because of its applications in health care and livestock production, among others. Problems such as adjustment of an individual growth model, estimation of parameters and prediction of future sizes are treated in this work. New applications of the generalized stochastic monomolecular model and a new software applied to this and other models are presented.

Damage and fracture algorithm using the screened Poisson equation and local remeshing

We propose a crack propagation algorithm which is independent of particular constitutive laws and specific element technology. It consists of a localization limiter in the form of the screened Poisson equation with local mesh refinement. This combination allows the cap- turing of strain localization with good resolution, even in the absence of a sufficiently fine initial mesh. In addition, crack paths are implicitly defined from the localized region, cir- cumventing the need for a specific direction criterion. Observed phenomena such as mul- tiple crack growth and shielding emerge naturally from the algorithm. In contrast with alternative regularization algorithms, curved cracks are correctly represented. A staggered scheme for standard equilibrium and screened equations is used. Element subdivision is based on edge split operations using a given constitutive quantity (either damage or void fraction). To assess the robustness and accuracy of this algorithm, we use both quasi-brittle benchmarks and ductile tests.

Fracture Toughening and Self-Healing of Composite Laminates by Nanofibrous Mats Interleaving

Composite laminates present important advantages compared to conventional monolithic materials, mainly because for equal stiffness and strength they have a weight up to four times lower. However, due to their ply-by-ply nature, they are susceptible to delamination, whose propagation can bring the structure to a rapid catastrophic failure. In this thesis, in order to increase the service life of composite materials, two different approaches were explored: increase the intrinsic resistance of the material or confer to them the capability of self-repair. The delamination has been hindered through interleaving the composite laminates with polymeric nanofibers, which completed the hierarchical reinforcement scale of the composite. The manufacturing process for the integration of the nanofibrous mat in the laminate was optimized, resulting in an enhancement of mode I fracture toughness up to 250%. The effect of the geometrical dimensions of the nano-reinforcement on the architecture of the micro one (UD and woven laminates) was studied on mode I and II. Moreover, different polymeric materials were employed as nanofibrous reinforcement (Nylon 66 and polyvinylidene fluoride). The nano toughening mechanism was studied by micrograph analysis of the crack path and SEM analysis of the fracture surface. The fatigue behavior to the onset of the delamination and the crack growth rate for woven laminates interleaved with Nylon 66 nanofibers was investigated. Furthermore, the impact behavior of GLARE aluminum-glass epoxy laminates, toughened with Nylon 66 nanofibers was investigated. Finally, the possibility of confer to the composite material the capability of self-repair was explored. An extrinsic self-healing-system, based on core-shell nanofibers filled with a two-component epoxy system, was developed by co-electrospinning technique. The healing potential of the nano vascular system has been proved by microscope electron observation of the healing agent release as result of the vessels rupture and the crosslinking reaction was verified by thermal analysis.

Essays on asset pricing

The first chapter provides evidence that aggregate Research and Development (R&D) investment drives a persistent component in productivity growth and that this embodies a risk priced in financial markets. In a semi-endogenous growth model, this component is identified by the R&D in excess of equilibrium levels and can be approximated by the Error Correction Term in the cointegration between R&D and Total Factor Productivity. Empirically, the component results being well defined and it satisfies all key theoretical predictions: it exhibits appropriate persistency, it forecasts productivity growth, and it is associated with a cross-sectional risk premium. CAPM is the most foundational model in financial economics, but is known to empirically underestimate expected returns of low-risk assets and overestimate those with high risk. The second chapter studies how risks omission and funding tightness jointly contribute to explaining this anomaly, with the former affecting the definition of assets’ riskiness and the latter affecting how risk is remunerated. Theoretically, the two effects are shown to counteract each other. Empirically, the spread related to binding leverage constraints is found to be significant at 2% yearly. Nonetheless, average returns of portfolios that exploit this anomaly are found to mostly reflect omitted risks, in contrast to their employment in previous literature. The third chapter studies how ‘sustainability’ of assets affect discount rates, which is intrinsically mediated by the risk profile of the assets themselves. This has implications for the assessment of the sustainability-related spread and for hedging changes in the sustainability concern. This mechanism is tested on the ESG-score dimension for US data, with inconclusive evidence regarding the existence of an ESG-related premium in the first place. Also, the risk profile of the long-short ESG portfolio is not likely to impact the sign of its average returns with respect to the sustainability-spread, for the time being.

Partial-hepatectomized (70%) Model Shows A Correlation Between Hepatocyte Growth Factor Levels And Beta-cell Mass.

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Adapting the CROPGRO perennial forage model to predict growth of Brachiaria brizantha

Warm-season grasses are economically important for cattle production in tropical regions, and tools to aid in management and research of these forages would be highly beneficial. Crop simulation models synthesize numerous physiological processes and are important research tools for evaluating production of warm-season grasses. This research was conducted to adapt the perennial CROPGRO Forage model to simulate growth of the tropical species palisadegrass [Brachiaria brizantha (A. Rich.) Stapf. cv. Xaraes] and to describe model adaptation for this species. In order to develop the CROPGRO parameters for this species, we began with values and relationships reported in the literature. Some parameters and relationships were calibrated by comparison with observed growth, development, dry matter accumulation and partitioning during a 2-year experiment with Xaraes palisadegrass in Piracicaba, SP, Brazil. Starting with parameters for the bahiagrass (Paspalum notatum Flugge) perennial forage model, dormancy effects had to be minimized, and partitioning to storage tissue/root decreased, and partitioning to leaf and stem increased to provide for more leaf and stem growth and less root. Parameters affecting specific leaf area (SLA) and senescence of plant tissues were improved. After these changes were made to the model, biomass accumulation was better simulated, mean predicted herbage yield per cycle was 3573 kg ha(-1), with a RMSE of 538 kg DM ha(-1) (D-Stat = 0.838, simulated/observed ratio = 1.028). The results of the adaptation suggest that the CROPGRO model is an efficient tool to integrate physiological aspects of palisadegrass and can be used to simulate growth. (C) 2010 Elsevier B.V. All rights reserved.