Measuring Bottleneck Link Speed in Package-Switched Networks

The quality of available network connections can often have a large impact on the performance of distributed applications. For example, document transfer applications such as FTP, Gopher and the World Wide Web suffer increased response times as a result of network congestion. For these applications, the document transfer time is directly related to the available bandwidth of the connection. Available bandwidth depends on two things: 1) the underlying capacity of the path from client to server, which is limited by the bottleneck link; and 2) the amount of other traffic competing for links on the path. If measurements of these quantities were available to the application, the current utilization of connections could be calculated. Network utilization could then be used as a basis for selection from a set of alternative connections or servers, thus providing reduced response time. Such a dynamic server selection scheme would be especially important in a mobile computing environment in which the set of available servers is frequently changing. In order to provide these measurements at the application level, we introduce two tools: bprobe, which provides an estimate of the uncongested bandwidth of a path; and cprobe, which gives an estimate of the current congestion along a path. These two measures may be used in combination to provide the application with an estimate of available bandwidth between server and client thereby enabling application-level congestion avoidance. In this paper we discuss the design and implementation of our probe tools, specifically illustrating the techniques used to achieve accuracy and robustness. We present validation studies for both tools which demonstrate their reliability in the face of actual Internet conditions; and we give results of a survey of available bandwidth to a random set of WWW servers as a sample application of our probe technique. We conclude with descriptions of other applications of our measurement tools, several of which are currently under development.

Trade & Cap: A Customer-Managed, Market-Based System for Trading Bandwidth Allowances at a Shared Link

We propose Trade & Cap (T&C), an economics-inspired mechanism that incentivizes users to voluntarily coordinate their consumption of the bandwidth of a shared resource (e.g., a DSLAM link) so as to converge on what they perceive to be an equitable allocation, while ensuring efficient resource utilization. Under T&C, rather than acting as an arbiter, an Internet Service Provider (ISP) acts as an enforcer of what the community of rational users sharing the resource decides is a fair allocation of that resource. Our T&C mechanism proceeds in two phases. In the first, software agents acting on behalf of users engage in a strategic trading game in which each user agent selfishly chooses bandwidth slots to reserve in support of primary, interactive network usage activities. In the second phase, each user is allowed to acquire additional bandwidth slots in support of presumed open-ended need for fluid bandwidth, catering to secondary applications. The acquisition of this fluid bandwidth is subject to the remaining "buying power" of each user and by prevalent "market prices" – both of which are determined by the results of the trading phase and a desirable aggregate cap on link utilization. We present analytical results that establish the underpinnings of our T&C mechanism, including game-theoretic results pertaining to the trading phase, and pricing of fluid bandwidth allocation pertaining to the capping phase. Using real network traces, we present extensive experimental results that demonstrate the benefits of our scheme, which we also show to be practical by highlighting the salient features of an efficient implementation architecture.

Leptin metabolically licenses T cells for activation to link nutrition and immunity.

Immune responses are highly energy-dependent processes. Activated T cells increase glucose uptake and aerobic glycolysis to survive and function. Malnutrition and starvation limit nutrients and are associated with immune deficiency and increased susceptibility to infection. Although it is clear that immunity is suppressed in times of nutrient stress, mechanisms that link systemic nutrition to T cell function are poorly understood. We show in this study that fasting leads to persistent defects in T cell activation and metabolism, as T cells from fasted animals had low glucose uptake and decreased ability to produce inflammatory cytokines, even when stimulated in nutrient-rich media. To explore the mechanism of this long-lasting T cell metabolic defect, we examined leptin, an adipokine reduced in fasting that regulates systemic metabolism and promotes effector T cell function. We show that leptin is essential for activated T cells to upregulate glucose uptake and metabolism. This effect was cell intrinsic and specific to activated effector T cells, as naive T cells and regulatory T cells did not require leptin for metabolic regulation. Importantly, either leptin addition to cultured T cells from fasted animals or leptin injections to fasting animals was sufficient to rescue both T cell metabolic and functional defects. Leptin-mediated metabolic regulation was critical, as transgenic expression of the glucose transporter Glut1 rescued cytokine production of T cells from fasted mice. Together, these data demonstrate that induction of T cell metabolism upon activation is dependent on systemic nutritional status, and leptin links adipocytes to metabolically license activated T cells in states of nutritional sufficiency.

THE COMPLETE PRELUDES OF ALEXANDER SCRIABIN: THE EVOLUTION OF HIS REVOLUTIONARY COMPOSITIONAL STYLE

During the second half of the nineteenth century, a series of remarkable advances in musical composition emerged in the works of such innovative spirits as Franz Liszt, Hector Berlioz and Richard Wagner. Their pioneering works exerted an extraordinary impact on the music of the subsequent generation of composers--of disparate nationalities-who were active at the dawn of the 20th century: Including most notably Claude-Achille Debussy, Gustav Mahler, Richard Strauss, and Alexander Nikolayevich Scriabin. These important musical figures, each one leaving an indelible and formative imprint on late-nineteenth century Romantic style, together launched the modern era in music. Scriabin stands alone as a transcendental visionary: His music, initiated in the fashion of Chopin and Liszt, wanders through the realms of Debussy and Wagner, and, ultimately abandoning late Romantic tradition, unlocks the heretofore unforeseen power of atonality, bitonality, polyrhythms and key-signature free compositions. Arguably, Scriabin's compositions count among the most innovative, idiosyncratic and bewitching of all time. The development of Scriabin's groundbreaking compositional style is best understood by means of his piano works, which comprise the majority of his oeuvre. Beyond the larger works-his twelve sonatas, a concerto and a fantasy-Scriabin's piano explorations are also represented by miniature gems: The mazurkas, impromptus, waltzes, poems, a polonaise, etudes, nocturnes, morceaux and, in particular, the preludes. Scriabin's 90 preludes for piano, arranged in several opus numbers, richly exemplify the striking evolution of his ingenious music, his idiosyncratic philosophy and his provocative personality.

Computational Inference of Genome-Wide Protein-DNA Interactions Using High-Throughput Genomic Data

Transcriptional regulation has been studied intensively in recent decades. One important aspect of this regulation is the interaction between regulatory proteins, such as transcription factors (TF) and nucleosomes, and the genome. Different high-throughput techniques have been invented to map these interactions genome-wide, including ChIP-based methods (ChIP-chip, ChIP-seq, etc.), nuclease digestion methods (DNase-seq, MNase-seq, etc.), and others. However, a single experimental technique often only provides partial and noisy information about the whole picture of protein-DNA interactions. Therefore, the overarching goal of this dissertation is to provide computational developments for jointly modeling different experimental datasets to achieve a holistic inference on the protein-DNA interaction landscape.

We first present a computational framework that can incorporate the protein binding information in MNase-seq data into a thermodynamic model of protein-DNA interaction. We use a correlation-based objective function to model the MNase-seq data and a Markov chain Monte Carlo method to maximize the function. Our results show that the inferred protein-DNA interaction landscape is concordant with the MNase-seq data and provides a mechanistic explanation for the experimentally collected MNase-seq fragments. Our framework is flexible and can easily incorporate other data sources. To demonstrate this flexibility, we use prior distributions to integrate experimentally measured protein concentrations.

We also study the ability of DNase-seq data to position nucleosomes. Traditionally, DNase-seq has only been widely used to identify DNase hypersensitive sites, which tend to be open chromatin regulatory regions devoid of nucleosomes. We reveal for the first time that DNase-seq datasets also contain substantial information about nucleosome translational positioning, and that existing DNase-seq data can be used to infer nucleosome positions with high accuracy. We develop a Bayes-factor-based nucleosome scoring method to position nucleosomes using DNase-seq data. Our approach utilizes several effective strategies to extract nucleosome positioning signals from the noisy DNase-seq data, including jointly modeling data points across the nucleosome body and explicitly modeling the quadratic and oscillatory DNase I digestion pattern on nucleosomes. We show that our DNase-seq-based nucleosome map is highly consistent with previous high-resolution maps. We also show that the oscillatory DNase I digestion pattern is useful in revealing the nucleosome rotational context around TF binding sites.

Finally, we present a state-space model (SSM) for jointly modeling different kinds of genomic data to provide an accurate view of the protein-DNA interaction landscape. We also provide an efficient expectation-maximization algorithm to learn model parameters from data. We first show in simulation studies that the SSM can effectively recover underlying true protein binding configurations. We then apply the SSM to model real genomic data (both DNase-seq and MNase-seq data). Through incrementally increasing the types of genomic data in the SSM, we show that different data types can contribute complementary information for the inference of protein binding landscape and that the most accurate inference comes from modeling all available datasets.

This dissertation provides a foundation for future research by taking a step toward the genome-wide inference of protein-DNA interaction landscape through data integration.

A new method based on Markov chains for deriving SB2 orbits directly from their spectra

info:eu-repo/semantics/published

Parliamentary party loyalty and party family: the missing link?

info:eu-repo/semantics/inPress

Aplicación de cadenas absorbentes de Markov a un modelo de autofecundación en alohexaploides

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Caminhos e percursos da Geometria Analítica: estudo histórico e epistemológico

A Geometria Analítica é parte integrante dos conteúdos a serem trabalhados na Educação Básica. Além disso, os conceitos trabalhados na Educação Básica são aprofundados nos componentes curriculares dos cursos de graduação das ciências exatas tais como Engenharia, Ciências da Computação, Arquitetura, Matemática, Física, etc. Seu estudo é relevante, pois é uma ferramenta importante para o Cálculo Diferencial e Integral e é uma das principais referências em um primeiro curso de Álgebra Linear. Este trabalho tem por objetivo apresentar um estudo histórico e epistemológico das primeiras contribuições da Geometria. É importante que o professor discuta os acontecimentos históricos ao trabalhar com os conteúdos da Geometria Analítica, propor aos alunos os problemas matemáticos que originaram os conceitos da Geometria Analítica e possibilite ao aluno a construção do conhecimento e não apenas para a resolução de algoritmos.

Identificando a geometria nas construções indígenas

Atualmente, a escola vive sempre procurando acompanhar as constantes transformações do mundo “globalizado”, e isso se transforma numa luta, às vezes desigual, pela conquista do universo dos estudantes tão bombardeado de novidades audiovisuais e eletrônicas. Neste trabalho, mostra‐se como a partir do estudo do meio, foi possível despertar o interesse de estudantes brasileiros do ensino médio pela Geometria presente na construção da maloca de indígenas Uitoto da Amazônia colombiana. Mostra também, que além dos meios tecnológicos disponíveis, o professor de matemática pode utilizar os recursos existentes na comunidade ou na própria escola como objeto de ensino atrativo, pois tudo depende da forma como este objeto irá ser usado.

Stochastic monotonicity and duality for continuous time Markov chains with general q-Matrix

The key problems in discussing stochastic monotonicity and duality for continuous time Markov chains are to give the criteria for existence and uniqueness and to construct the associated monotone processes in terms of their infinitesimal q -matrices. In their recent paper, Chen and Zhang [6] discussed these problems under the condition that the given q-matrix Q is conservative. The aim of this paper is to generalize their results to a more general case, i.e., the given q-matrix Q is not necessarily conservative. New problems arise 'in removing the conservative assumption. The existence and uniqueness criteria for this general case are given in this paper. Another important problem, the construction of all stochastically monotone Q-processes, is also considered.

Existence, recurrence and equilibrium properties of Markov branching processes with instantaneous immigration

Attention has recently focussed on stochastic population processes that can undergo total annihilation followed by immigration into state j at rate αj. The investigation of such models, called Markov branching processes with instantaneous immigration (MBPII), involves the study of existence and recurrence properties. However, results developed to date are generally opaque, and so the primary motivation of this paper is to construct conditions that are far easier to apply in practice. These turn out to be identical to the conditions for positive recurrence, which are very easy to check. We obtain, as a consequence, the surprising result that any MBPII that exists is ergodic, and so must possess an equilibrium distribution. These results are then extended to more general MBPII, and we show how to construct the associated equilibrium distributions.

Applications of Feller-Reuter-Riley transition functions

A Feller–Reuter–Riley function is a Markov transition function whose corresponding semigroup maps the set of the real-valued continuous functions vanishing at infinity into itself. The aim of this paper is to investigate applications of such functions in the dual problem, Markov branching processes, and the Williams-matrix. The remarkable property of a Feller–Reuter–Riley function is that it is a Feller minimal transition function with a stable q-matrix. By using this property we are able to prove that, in the theory of branching processes, the branching property is equivalent to the requirement that the corresponding transition function satisfies the Kolmogorov forward equations associated with a stable q-matrix. It follows that the probabilistic definition and the analytic definition for Markov branching processes are actually equivalent. Also, by using this property, together with the Resolvent Decomposition Theorem, a simple analytical proof of the Williams' existence theorem with respect to the Williams-matrix is obtained. The close link between the dual problem and the Feller–Reuter–Riley transition functions is revealed. It enables us to prove that a dual transition function must satisfy the Kolmogorov forward equations. A necessary and sufficient condition for a dual transition function satisfying the Kolmogorov backward equations is also provided.

Feller transition functions, Resolvent Decomposition Theorems, and their application in unstable denumerable Markov processes

This paper surveys the recent progresses made in the field of unstable denumerable Markov processes. Emphases are laid upon methodology and applications. The important tools of Feller transition functions and Resolvent Decomposition Theorems are highlighted. Their applications particularly in unstable denumerable Markov processes with a single instantaneous state and Markov branching processes are illustrated.

A Markov modulated Poisson process model for rainfall increments

The problems encountered when using traditional rectangular pulse hierarchical point processmodels for fine temporal resolution and the growing number of available tip-time records suggest that rainfall increments from tipping-bucket gauges be modelled directly. Poisson processes are used with an arrival rate modulated by a Markov chain in Continuous time. The paper shows how, by using two or three states for this chain, much of the structure of the rainfall intensity distribution and the wet/dry sequences can be represented for time-scales as small as 5 minutes.