982 resultados para Heterogeneous networks
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[cat] En aquest treball s'analitza un model estocàstic en temps continu en el que l'agent decisor descompta les utilitats instantànies i la funció final amb taxes de preferència temporal constants però diferents. En aquest context es poden modelitzar problemes en els quals, quan el temps s'acosta al moment final, la valoració de la funció final incrementa en comparació amb les utilitats instantànies. Aquest tipus d'asimetria no es pot descriure ni amb un descompte estàndard ni amb un variable. Per tal d'obtenir solucions consistents temporalment es deriva l'equació de programació dinàmica estocàstica, les solucions de la qual són equilibris Markovians. Per a aquest tipus de preferències temporals, s'estudia el model clàssic de consum i inversió (Merton, 1971) per a les funcions d'utilitat del tipus CRRA i CARA, comparant els equilibris Markovians amb les solucions inconsistents temporalment. Finalment es discuteix la introducció del temps final aleatori.
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Networks famously epitomize the shift from 'government' to 'governance' as governing structures for exercising control and coordination besides hierarchies and markets. Their distinctive features are their horizontality, the interdependence among member actors and an interactive decision-making style. Networks are expected to increase the problem-solving capacity of political systems in a context of growing social complexity, where political authority is increasingly fragmented across territorial and functional levels. However, very little attention has been given so far to another crucial implication of network governance - that is, the effects of networks on their members. To explore this important question, this article examines the effects of membership in European regulatory networks on two crucial attributes of member agencies, which are in charge of regulating finance, energy, telecommunications and competition: organisational growth and their regulatory powers. Panel analysis applied to data on 118 agencies during a ten-year period and semi-structured interviews provide mixed support regarding the expectation of organisational growth while strongly confirming the positive effect of networks on the increase of the regulatory powers attributed to member agencies.
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Abstract : The human body is composed of a huge number of cells acting together in a concerted manner. The current understanding is that proteins perform most of the necessary activities in keeping a cell alive. The DNA, on the other hand, stores the information on how to produce the different proteins in the genome. Regulating gene transcription is the first important step that can thus affect the life of a cell, modify its functions and its responses to the environment. Regulation is a complex operation that involves specialized proteins, the transcription factors. Transcription factors (TFs) can bind to DNA and activate the processes leading to the expression of genes into new proteins. Errors in this process may lead to diseases. In particular, some transcription factors have been associated with a lethal pathological state, commonly known as cancer, associated with uncontrolled cellular proliferation, invasiveness of healthy tissues and abnormal responses to stimuli. Understanding cancer-related regulatory programs is a difficult task, often involving several TFs interacting together and influencing each other's activity. This Thesis presents new computational methodologies to study gene regulation. In addition we present applications of our methods to the understanding of cancer-related regulatory programs. The understanding of transcriptional regulation is a major challenge. We address this difficult question combining computational approaches with large collections of heterogeneous experimental data. In detail, we design signal processing tools to recover transcription factors binding sites on the DNA from genome-wide surveys like chromatin immunoprecipitation assays on tiling arrays (ChIP-chip). We then use the localization about the binding of TFs to explain expression levels of regulated genes. In this way we identify a regulatory synergy between two TFs, the oncogene C-MYC and SP1. C-MYC and SP1 bind preferentially at promoters and when SP1 binds next to C-NIYC on the DNA, the nearby gene is strongly expressed. The association between the two TFs at promoters is reflected by the binding sites conservation across mammals, by the permissive underlying chromatin states 'it represents an important control mechanism involved in cellular proliferation, thereby involved in cancer. Secondly, we identify the characteristics of TF estrogen receptor alpha (hERa) target genes and we study the influence of hERa in regulating transcription. hERa, upon hormone estrogen signaling, binds to DNA to regulate transcription of its targets in concert with its co-factors. To overcome the scarce experimental data about the binding sites of other TFs that may interact with hERa, we conduct in silico analysis of the sequences underlying the ChIP sites using the collection of position weight matrices (PWMs) of hERa partners, TFs FOXA1 and SP1. We combine ChIP-chip and ChIP-paired-end-diTags (ChIP-pet) data about hERa binding on DNA with the sequence information to explain gene expression levels in a large collection of cancer tissue samples and also on studies about the response of cells to estrogen. We confirm that hERa binding sites are distributed anywhere on the genome. However, we distinguish between binding sites near promoters and binding sites along the transcripts. The first group shows weak binding of hERa and high occurrence of SP1 motifs, in particular near estrogen responsive genes. The second group shows strong binding of hERa and significant correlation between the number of binding sites along a gene and the strength of gene induction in presence of estrogen. Some binding sites of the second group also show presence of FOXA1, but the role of this TF still needs to be investigated. Different mechanisms have been proposed to explain hERa-mediated induction of gene expression. Our work supports the model of hERa activating gene expression from distal binding sites by interacting with promoter bound TFs, like SP1. hERa has been associated with survival rates of breast cancer patients, though explanatory models are still incomplete: this result is important to better understand how hERa can control gene expression. Thirdly, we address the difficult question of regulatory network inference. We tackle this problem analyzing time-series of biological measurements such as quantification of mRNA levels or protein concentrations. Our approach uses the well-established penalized linear regression models where we impose sparseness on the connectivity of the regulatory network. We extend this method enforcing the coherence of the regulatory dependencies: a TF must coherently behave as an activator, or a repressor on all its targets. This requirement is implemented as constraints on the signs of the regressed coefficients in the penalized linear regression model. Our approach is better at reconstructing meaningful biological networks than previous methods based on penalized regression. The method is tested on the DREAM2 challenge of reconstructing a five-genes/TFs regulatory network obtaining the best performance in the "undirected signed excitatory" category. Thus, these bioinformatics methods, which are reliable, interpretable and fast enough to cover large biological dataset, have enabled us to better understand gene regulation in humans.
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Abstract In social insects, workers perform a multitude of tasks, such as foraging, nest construction, and brood rearing, without central control of how work is allocated among individuals. It has been suggested that workers choose a task by responding to stimuli gathered from the environment. Response-threshold models assume that individuals in a colony vary in the stimulus intensity (response threshold) at which they begin to perform the corresponding task. Here we highlight the limitations of these models with respect to colony performance in task allocation. First, we show with analysis and quantitative simulations that the deterministic response-threshold model constrains the workers' behavioral flexibility under some stimulus conditions. Next, we show that the probabilistic response-threshold model fails to explain precise colony responses to varying stimuli. Both of these limitations would be detrimental to colony performance when dynamic and precise task allocation is needed. To address these problems, we propose extensions of the response-threshold model by adding variables that weigh stimuli. We test the extended response-threshold model in a foraging scenario and show in simulations that it results in an efficient task allocation. Finally, we show that response-threshold models can be formulated as artificial neural networks, which consequently provide a comprehensive framework for modeling task allocation in social insects.
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This paper analyses and discusses arguments that emerge from a recent discussion about the proper assessment of the evidential value of correspondences observed between the characteristics of a crime stain and those of a sample from a suspect when (i) this latter individual is found as a result of a database search and (ii) remaining database members are excluded as potential sources (because of different analytical characteristics). Using a graphical probability approach (i.e., Bayesian networks), the paper here intends to clarify that there is no need to (i) introduce a correction factor equal to the size of the searched database (i.e., to reduce a likelihood ratio), nor to (ii) adopt a propositional level not directly related to the suspect matching the crime stain (i.e., a proposition of the kind 'some person in (outside) the database is the source of the crime stain' rather than 'the suspect (some other person) is the source of the crime stain'). The present research thus confirms existing literature on the topic that has repeatedly demonstrated that the latter two requirements (i) and (ii) should not be a cause of concern.
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A Knudsen flow reactor has been used to quantify surface functional groups on aerosols collected in the field. This technique is based on a heterogeneous titration reaction between a probe gas and a specific functional group on the particle surface. In the first part of this work, the reactivity of different probe gases on laboratory-generated aerosols (limonene SOA, Pb(NO3)2, Cd(NO3)2) and diesel reference soot (SRM 2975) has been studied. Five probe gases have been selected for the quantitative determination of important functional groups: N(CH3)3 (for the titration of acidic sites), NH2OH (for carbonyl functions), CF3COOH and HCl (for basic sites of different strength), and O3 (for oxidizable groups). The second part describes a field campaign that has been undertaken in several bus depots in Switzerland, where ambient fine and ultrafine particles were collected on suitable filters and quantitatively investigated using the Knudsen flow reactor. Results point to important differences in the surface reactivity of ambient particles, depending on the sampling site and season. The particle surface appears to be multi-functional, with the simultaneous presence of antagonistic functional groups which do not undergo internal chemical reactions, such as acid-base neutralization. Results also indicate that the surface of ambient particles was characterized by a high density of carbonyl functions (reactivity towards NH2OH probe in the range 0.26-6 formal molecular monolayers) and a low density of acidic sites (reactivity towards N(CH3)3 probe in the range 0.01-0.20 formal molecular monolayer). Kinetic parameters point to fast redox reactions (uptake coefficient ?0>10-3 for O3 probe) and slow acid-base reactions (?0<10-4 for N(CH3)3 probe) on the particle surface. [Authors]
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Six gases (N((CH3)3), NH2OH, CF3COOH, HCl, NO2, O3) were selected to probe the surface of seven combustion aerosol (amorphous carbon, flame soot) and three types of TiO2 nanoparticles using heterogeneous, that is gas-surface reactions. The gas uptake to saturation of the probes was measured under molecular flow conditions in a Knudsen flow reactor and expressed as a density of surface functional groups on a particular aerosol, namely acidic (carboxylic) and basic (conjugated oxides such as pyrones, N-heterocycles) sites, carbonyl (R1-C(O)-R2) and oxidizable (olefinic, -OH) groups. The limit of detection was generally well below 1% of a formal monolayer of adsorbed probe gas. With few exceptions most investigated aerosol samples interacted with all probe gases which points to the coexistence of different functional groups on the same aerosol surface such as acidic and basic groups. Generally, the carbonaceous particles displayed significant differences in surface group density: Printex 60 amorphous carbon had the lowest density of surface functional groups throughout, whereas Diesel soot recovered from a Diesel particulate filter had the largest. The presence of basic oxides on carbonaceous aerosol particles was inferred from the ratio of uptakes of CF3COOH and HCl owing to the larger stability of the acetate compared to the chloride counterion in the resulting pyrylium salt. Both soots generated from a rich and a lean hexane diffusion flame had a large density of oxidizable groups similar to amorphous carbon FS 101. TiO2 15 had the lowest density of functional groups among the three studied TiO2 nanoparticles for all probe gases despite the smallest size of its primary particles. The used technique enabled the measurement of the uptake probability of the probe gases on the various supported aerosol samples. The initial uptake probability, g0, of the probe gas onto the supported nanoparticles differed significantly among the various investigated aerosol samples but was roughly correlated with the density of surface groups, as expected. [Authors]
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This paper advocates the adoption of a mixed-methods research design to describe and analyze ego-centered social networks in transnational family research. Drawing on the experience of the Social Networks Influences on Family Formation project (2004-2005), I show how the combined use of network generators and semistructured interviews (N = 116) produces unique data on family configurations and their impact on life course choices. A mixed-methods network approach presents specific advantages for research on children in transnational families. On the one hand, quantitative analyses are crucial for reconstructing and measuring the potential and actual relational support available to children in a context where kin interactions may be hindered by temporary and prolonged periods of separation. On the other hand, qualitative analyses can address strategies and practices employed by families to maintain relationships across international borders and geographic distance, as well as the implications of those strategies for children's well-being.
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Ectopic or tertiary lymphoid tissues (TLTs) are often induced at sites of chronic inflammation. They typically contain various hematopoietic cell types, high endothelial venules, and follicular dendritic cells; and are organized in lymph node-like structures. Although fibroblastic stromal cells may play a role in TLT induction and persistence, they have remained poorly defined. Herein, we report that TLTs arising during inflammation in mice and humans in a variety of tissues (eg, pancreas, kidney, liver, and salivary gland) contain stromal cell networks consisting of podoplanin(+) T-zone fibroblastic reticular cells (TRCs), distinct from follicular dendritic cells. Similar to lymph nodes, TRCs were present throughout T-cell-rich areas and had dendritic cells associated with them. They expressed lymphotoxin (LT) β receptor (LTβR), produced CCL21, and formed a functional conduit system. In rat insulin promoter-CXCL13-transgenic pancreas, the maintenance of TRC networks and conduits was partially dependent on LTβR and on lymphoid tissue inducer cells expressing LTβR ligands. In conclusion, TRCs and conduits are hallmarks of secondary lymphoid organs and of well-developed TLTs, in both mice and humans, and are likely to act as important scaffold and organizer cells of the T-cell-rich zone.
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Tiivistelmä: Kunnostusojituksen pitkän ajan vaikutus valumaveden ominaisuuksiin
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The determination of line crossing sequences between rollerball pens and laser printers presents difficulties that may not be overcome using traditional techniques. This research aimed to study the potential of digital microscopy and 3-D laser profilometry to determine line crossing sequences between a toner and an aqueous ink line. Different paper types, rollerball pens, and writing pressure were tested. Correct opinions of the sequence were given for all case scenarios, using both techniques. When the toner was printed before the ink, a light reflection was observed in all crossing specimens, while this was never observed in the other sequence types. The 3-D laser profilometry, more time-consuming, presented the main advantage of providing quantitative results. The findings confirm the potential of the 3-D laser profilometry and demonstrate the efficiency of digital microscopy as a new technique for determining the sequence of line crossings involving rollerball pen ink and toner. With the mass marketing of laser printers and the popularity of rollerball pens, the determination of line crossing sequences between such instruments is encountered by forensic document examiners. This type of crossing presents difficulties with optical microscopic line crossing techniques involving ballpoint pens or gel pens and toner (1-4). Indeed, the rollerball's aqueous ink penetrates through the toner and is absorbed by the fibers of the paper, leaving the examiner with the impression that the toner is above the ink even when it is not (5). Novotny and Westwood (3) investigated the possibility of determining aqueous ink and toner crossing sequences by microscopic observation of the intersection before and after toner removal. A major disadvantage of their study resides in destruction of the sample by scraping off the toner line to see what was underneath. The aim of this research was to investigate the ways to overcome these difficulties through digital microscopy and three-dimensional (3-D) laser profilometry. The former was used as a technique for the determination of sequences between gel pen and toner printing strokes, but provided less conclusive results than that of an optical stereomicroscope (4). 3-D laser profilometry, which allows one to observe and measure the topography of a surface, has been the subject of a number of recent studies in this area. Berx and De Kinder (6) and Schirripa Spagnolo (7,8) have tested the application of laser profilometry to determine the sequence of intersections of several lines. The results obtained in these studies overcome disadvantages of other methods applied in this area, such as scanning electron microscope or the atomic force microscope. The main advantages of 3-D laser profilometry include the ease of implementation of the technique and its nondestructive nature, which does not require sample preparation (8-10). Moreover, the technique is reproducible and presents a high degree of freedom in the vertical axes (up to 1000 μm). However, when the paper surface presents a given roughness, if the pen impressions alter the paper with a depth similar to the roughness of medium, the results are not always conclusive (8). It becomes difficult in this case to distinguish which characteristics can be imputed to the pen impressions or the quality of the paper surface. This important limitation is assessed by testing different types of paper of variable quality (of different grammage and finishing) and the writing pressure. The authors will therefore assess the limits of 3-D laser profilometry technique and determine whether the method can overcome such constraints. Second, the authors will investigate the use of digital microscopy because it presents a number of advantages: it is efficient, user-friendly, and provides an objective evaluation and interpretation.