Clustering in complex networks. II. Percolation properties

The percolation properties of clustered networks are analyzed in detail. In the case of weak clustering, we present an analytical approach that allows us to find the critical threshold and the size of the giant component. Numerical simulations confirm the accuracy of our results. In more general terms, we show that weak clustering hinders the onset of the giant component whereas strong clustering favors its appearance. This is a direct consequence of the differences in the k-core structure of the networks, which are found to be totally different depending on the level of clustering. An empirical analysis of a real social network confirms our predictions.

Kernel-based Mapping of Meteorological Fields in Complex Orography

Due to the advances in sensor networks and remote sensing technologies, the acquisition and storage rates of meteorological and climatological data increases every day and ask for novel and efficient processing algorithms. A fundamental problem of data analysis and modeling is the spatial prediction of meteorological variables in complex orography, which serves among others to extended climatological analyses, for the assimilation of data into numerical weather prediction models, for preparing inputs to hydrological models and for real time monitoring and short-term forecasting of weather.In this thesis, a new framework for spatial estimation is proposed by taking advantage of a class of algorithms emerging from the statistical learning theory. Nonparametric kernel-based methods for nonlinear data classification, regression and target detection, known as support vector machines (SVM), are adapted for mapping of meteorological variables in complex orography.With the advent of high resolution digital elevation models, the field of spatial prediction met new horizons. In fact, by exploiting image processing tools along with physical heuristics, an incredible number of terrain features which account for the topographic conditions at multiple spatial scales can be extracted. Such features are highly relevant for the mapping of meteorological variables because they control a considerable part of the spatial variability of meteorological fields in the complex Alpine orography. For instance, patterns of orographic rainfall, wind speed and cold air pools are known to be correlated with particular terrain forms, e.g. convex/concave surfaces and upwind sides of mountain slopes.Kernel-based methods are employed to learn the nonlinear statistical dependence which links the multidimensional space of geographical and topographic explanatory variables to the variable of interest, that is the wind speed as measured at the weather stations or the occurrence of orographic rainfall patterns as extracted from sequences of radar images. Compared to low dimensional models integrating only the geographical coordinates, the proposed framework opens a way to regionalize meteorological variables which are multidimensional in nature and rarely show spatial auto-correlation in the original space making the use of classical geostatistics tangled.The challenges which are explored during the thesis are manifolds. First, the complexity of models is optimized to impose appropriate smoothness properties and reduce the impact of noisy measurements. Secondly, a multiple kernel extension of SVM is considered to select the multiscale features which explain most of the spatial variability of wind speed. Then, SVM target detection methods are implemented to describe the orographic conditions which cause persistent and stationary rainfall patterns. Finally, the optimal splitting of the data is studied to estimate realistic performances and confidence intervals characterizing the uncertainty of predictions.The resulting maps of average wind speeds find applications within renewable resources assessment and opens a route to decrease the temporal scale of analysis to meet hydrological requirements. Furthermore, the maps depicting the susceptibility to orographic rainfall enhancement can be used to improve current radar-based quantitative precipitation estimation and forecasting systems and to generate stochastic ensembles of precipitation fields conditioned upon the orography.

Activation of the NLRP3 inflammasome in dendritic cells induces IL-1beta-dependent adaptive immunity against tumors.

The therapeutic efficacy of anticancer chemotherapies may depend on dendritic cells (DCs), which present antigens from dying cancer cells to prime tumor-specific interferon-gamma (IFN-gamma)-producing T lymphocytes. Here we show that dying tumor cells release ATP, which then acts on P2X(7) purinergic receptors from DCs and triggers the NOD-like receptor family, pyrin domain containing-3 protein (NLRP3)-dependent caspase-1 activation complex ('inflammasome'), allowing for the secretion of interleukin-1beta (IL-1beta). The priming of IFN-gamma-producing CD8+ T cells by dying tumor cells fails in the absence of a functional IL-1 receptor 1 and in Nlpr3-deficient (Nlrp3(-/-)) or caspase-1-deficient (Casp-1(-/-)) mice unless exogenous IL-1beta is provided. Accordingly, anticancer chemotherapy turned out to be inefficient against tumors established in purinergic receptor P2rx7(-/-) or Nlrp3(-/-) or Casp1(-/-) hosts. Anthracycline-treated individuals with breast cancer carrying a loss-of-function allele of P2RX7 developed metastatic disease more rapidly than individuals bearing the normal allele. These results indicate that the NLRP3 inflammasome links the innate and adaptive immune responses against dying tumor cells.

Rethinking study and management of agricultural systems for policy design

There is a concern that agriculture will no longer be able to meet, on a global scale, the growing demand for food. Facing such a challenge requires new patterns of thinking in the context of complexity and sustainability sciences. This paper, focused on the social dimension of the study and management of agricultural systems, suggests that rethinking the study of agricultural systems entails analyzing them as complex socio-ecological systems, as well as considering the differing thinking patterns of diverse stakeholders. The intersubjective nature of knowledge, as studied by different philosophical schools, needs to be better integrated into the study and management of agricultural systems than it is done so far, forcing us to accept that there are no simplistic solutions, and to seek a better understanding of the social dimension of agriculture. Different agriculture related problems require different policy and institutional approaches. Finally, the intersubjective nature of knowledge asks for the visualization of different framings and the power relations taking place in the decision-making process. Rethinking management of agricultural systems implies that policy making should be shaped by different principles: learning, flexibility, adaptation, scale-matching, participation, diversity enhancement and precaution hold the promise to significantly improve current standard management procedures.

Cardiac raptor deletion impairs adaptive hypertrophy, alters metabolic gene expression and causes heart failure in mice

Background: Mammalian target of rapamycin (mTOR), a central regulator of cell growth, is found in two structurally and functionally distinct multiprotein complexes called mTOR complex (mTORC)1 and mTORC2. The specific roles of each of these branches of mTOR signaling have not been dissected in the adult heart. In the present study, we aimed to bring new insights into the function of cardiac mTORC1-mediated signaling in physiological as well as pathological situations.Methods: We generated mice homozygous for loxP-flanked raptor and positive for the tamoxifen-inducible Cre recombinase (MerCreMer) under control of the α- myosin heavy chain promoter. The raptor gene encodes an essential component of mTORC1. Gene ablation was induced at the age of 10-12 weeks, and two weeks later the raptor cardiac-knockout (raptor-cKO) mice started voluntary cagewheel exercise or were subjected to transverse aortic constriction (TAC) to induce pressure overload.Results: In sedentary raptor-cKO mice, ejection fractions gradually decreased, resulting in significantly reduced values at 38 days (P < 0.001). Raptor-cKO mice started to die during the fifth week after the last tamoxifen injection. At that time, the mortality rate was 36% in sedentary (n = 11) and 64% in exercising (n = 14) mice. TAC-induced pressure overload resulted in severe cardiac dysfunction already at earlier timepoints. Thus, at 7-9 days after surgery, ejection fraction and fractional shortening values were 22.3% vs 43.5% and 10.2% vs 21.5% in raptor-cKO vs wild-type mice, respectively. This was accompanied by significant reductions of ventricular wall and septal thickness as well as an increase in left ventricular internal diameter. Moreover, ventricular weight to tibial length ratios were increased in wild-type, but not in the raptor-cKO TAC mice. Together, this shows that raptor-cKO mice rapidly developed dilated cardiomyopathy without going through a phase of adaptive hypertrophy. Expression of ANP and β-MHC was induced in all raptor-cKO mice irrespective of the cardiac load conditions. Consistent with reduced mTORC1 activity, phosphorylation of ribosomal S6 kinase and 4E-BP1 was blunted, indicating reduced protein synthesis. Moreover, expression of multiple genes involved in the regulation of energy metabolism was altered, and followed by a shift from fatty acid to glucose oxidation.Conclusion: Our study suggests that mTORC1 coordinates protein and energy metabolic pathways in the heart. Moreover, we demonstrate that raptor is essential for the cardiac adaptation to increased workload and importantly, also for normal physiological cardiac function.

Multidimensional Adaptations for Open Learning Management Systems

Our work is focused on alleviating the workload for designers of adaptive courses on the complexity task of authoring adaptive learning designs adjusted to specific user characteristics and the user context. We propose an adaptation platform that consists in a set of intelligent agents where each agent carries out an independent adaptation task. The agents apply machine learning techniques to support the user modelling for the adaptation process

Cross-species analysis of the replication complex of Old World arenaviruses reveals two nucleoprotein sites involved in L protein function.

Lassa virus (LASV) causing hemorrhagic Lassa fever in West Africa, Mopeia virus (MOPV) from East Africa, and lymphocytic choriomeningitis virus (LCMV) are the main representatives of the Old World arenaviruses. Little is known about how the components of the arenavirus replication machinery, i.e., the genome, nucleoprotein (NP), and L protein, interact. In addition, it is unknown whether these components can function across species boundaries. We established minireplicon systems for MOPV and LCMV in analogy to the existing LASV system and exchanged the components among the three systems. The functional and physical integrity of the resulting complexes was tested by reporter gene assay, Northern blotting, and coimmunoprecipitation studies. The minigenomes, NPs, and L proteins of LASV and MOPV could be exchanged without loss of function. LASV and MOPV L protein was also active in conjunction with LCMV NP, while the LCMV L protein required homologous NP for activity. Analysis of LASV/LCMV NP chimeras identified a single LCMV-specific NP residue (Ile-53) and the C terminus of NP (residues 340 to 558) as being essential for LCMV L protein function. The defect of LASV and MOPV NP in supporting transcriptional activity of LCMV L protein was not caused by a defect in physical NP-L protein interaction. In conclusion, components of the replication complex of Old World arenaviruses have the potential to functionally and physically interact across species boundaries. Residue 53 and the C-terminal domain of NP are important for function of L protein during genome replication and transcription.

Systems Genetics of Metabolism: The Use of the BXD Murine Reference Panel for Multiscalar Integration of Traits.

Metabolic homeostasis is achieved by complex molecular and cellular networks that differ significantly among individuals and are difficult to model with genetically engineered lines of mice optimized to study single gene function. Here, we systematically acquired metabolic phenotypes by using the EUMODIC EMPReSS protocols across a large panel of isogenic but diverse strains of mice (BXD type) to study the genetic control of metabolism. We generated and analyzed 140 classical phenotypes and deposited these in an open-access web service for systems genetics (www.genenetwork.org). Heritability, influence of sex, and genetic modifiers of traits were examined singly and jointly by using quantitative-trait locus (QTL) and expression QTL-mapping methods. Traits and networks were linked to loci encompassing both known variants and novel candidate genes, including alkaline phosphatase (ALPL), here linked to hypophosphatasia. The assembled and curated phenotypes provide key resources and exemplars that can be used to dissect complex metabolic traits and disorders.

Dynamic Modelling of Material Flows and Sustainable Resource Use: Case Studies in Regional Metabolism and Space Life Support Systems

Sustainable resource use is one of the most important environmental issues of our times. It is closely related to discussions on the 'peaking' of various natural resources serving as energy sources, agricultural nutrients, or metals indispensable in high-technology applications. Although the peaking theory remains controversial, it is commonly recognized that a more sustainable use of resources would alleviate negative environmental impacts related to resource use. In this thesis, sustainable resource use is analysed from a practical standpoint, through several different case studies. Four of these case studies relate to resource metabolism in the Canton of Geneva in Switzerland: the aim was to model the evolution of chosen resource stocks and flows in the coming decades. The studied resources were copper (a bulk metal), phosphorus (a vital agricultural nutrient), and wood (a renewable resource). In addition, the case of lithium (a critical metal) was analysed briefly in a qualitative manner and in an electric mobility perspective. In addition to the Geneva case studies, this thesis includes a case study on the sustainability of space life support systems. Space life support systems are systems whose aim is to provide the crew of a spacecraft with the necessary metabolic consumables over the course of a mission. Sustainability was again analysed from a resource use perspective. In this case study, the functioning of two different types of life support systems, ARES and BIORAT, were evaluated and compared; these systems represent, respectively, physico-chemical and biological life support systems. Space life support systems could in fact be used as a kind of 'laboratory of sustainability' given that they represent closed and relatively simple systems compared to complex and open terrestrial systems such as the Canton of Geneva. The chosen analysis method used in the Geneva case studies was dynamic material flow analysis: dynamic material flow models were constructed for the resources copper, phosphorus, and wood. Besides a baseline scenario, various alternative scenarios (notably involving increased recycling) were also examined. In the case of space life support systems, the methodology of material flow analysis was also employed, but as the data available on the dynamic behaviour of the systems was insufficient, only static simulations could be performed. The results of the case studies in the Canton of Geneva show the following: were resource use to follow population growth, resource consumption would be multiplied by nearly 1.2 by 2030 and by 1.5 by 2080. A complete transition to electric mobility would be expected to only slightly (+5%) increase the copper consumption per capita while the lithium demand in cars would increase 350 fold. For example, phosphorus imports could be decreased by recycling sewage sludge or human urine; however, the health and environmental impacts of these options have yet to be studied. Increasing the wood production in the Canton would not significantly decrease the dependence on wood imports as the Canton's production represents only 5% of total consumption. In the comparison of space life support systems ARES and BIORAT, BIORAT outperforms ARES in resource use but not in energy use. However, as the systems are dimensioned very differently, it remains questionable whether they can be compared outright. In conclusion, the use of dynamic material flow analysis can provide useful information for policy makers and strategic decision-making; however, uncertainty in reference data greatly influences the precision of the results. Space life support systems constitute an extreme case of resource-using systems; nevertheless, it is not clear how their example could be of immediate use to terrestrial systems.

Impact of direct seeding mulch-based cropping systems on soil nematodes in a long-term experiment in Madagascar

The objective of this work was to assess the effects of conventional tillage and of different direct seeding mulch-based cropping systems (DMC) on soil nematofauna characteristics. The long-term field experiment was carried out in the highlands of Madagascar on an andic Dystrustept soil. Soil samples were taken once a year during three successive years (14 to 16 years after installation of the treatments) from a 0-5-cm soil layer of a conventional tillage system and of three kinds of DMC: direct seeding on mulch from rotation soybean-maize residues; direct seeding of maize-maize rotation on living mulch of silverleaf (Desmodium uncinatum); direct seeding of bean (Phaseolus vulgaris)-soybean rotation on living mulch of kikuyu grass (Pennisetum clandestinum). The samples were compared with samples from natural fallows. The soil nematofauna, characterized by the abundance of different trophic groups and indices (MI, maturity index; EI and SI, enrichment and structure indices), allowed the discrimination of the different cropping systems. The different DMC treatments had a more complex soil food web than the tillage treatment: SI and MI were significantly greater in DMC systems. Moreover, DMC with dead mulch had a lower density of free-living nematodes than DMC with living mulch, which suggested a lower microbial activity.

Cross-frequency coupling in EEG revealed by adaptive oscillation tracking.

Introduction: Neuronal oscillations have been the focus of increasing interest in the neuroscientific community, in part because they have been considered as a possible integrating mechanism through which internal states can influence stimulus processing in a top-down way (Engel et al., 2001). Moreover, increasing evidence indicates that oscillations in different frequency bands interact with one other through coupling mechanisms (Jensen and Colgin, 2007). The existence and the importance of these cross-frequency couplings during various tasks have been verified by recent studies (Canolty et al., 2006; Lakatos et al., 2007). In this study, we measure the strength and directionality of two types of couplings - phase-amplitude couplings and phase-phase couplings - between various bands in EEG data recorded during an illusory contour experiment that were identified using a recently-proposed adaptive frequency tracking algorithm (Van Zaen et al., 2010). Methods: The data used in this study have been taken from a previously published study examining the spatiotemporal mechanisms of illusory contour processing (Murray et al., 2002). The EEG in the present study were from a subset of nine subjects. Each stimulus was composed of 'pac-man' inducers presented in two orientations: IC, when an illusory contour was present, and NC, when no contour could be detected. The signals recorded by the electrodes P2, P4, P6, PO4 and PO6 were averaged, and filtered into the following bands: 4-8Hz, 8-12Hz, 15-25Hz, 35-45Hz, 45-55Hz, 55-65Hz and 65-75Hz. An adaptive frequency tracking algorithm (Van Zaen et al., 2010) was then applied in each band in order to extract the main oscillation and estimate its frequency. This additional step ensures that clean phase information is obtained when taking the Hilbert transform. The frequency estimated by the tracker was averaged over sliding windows and then used to compare the two conditions. Two types of cross-frequency couplings were considered: phase-amplitude couplings and phase-phase couplings. Both types were measured with the phase locking value (PLV, Lachaux et al., 1999) over sliding windows. The phase-amplitude couplings were computed with the phase of the low frequency oscillation and the phase of the amplitude of the high frequency one. Different coupling coefficients were used when measuring phase-phase couplings in order to estimate different m:n synchronizations (4:3, 3:2, 2:1, 3:1, 4:1, 5:1, 6:1, 7:1, 8:1 and 9:1) and to take into account the frequency differences across bands. Moreover, the direction of coupling was estimated with a directionality index (Bahraminasab et al., 2008). Finally, the two conditions IC and NC were compared with ANOVAs with 'subject' as a random effect and 'condition' as a fixed effect. Before computing the statistical tests, the PLV values were transformed into approximately normal variables (Penny et al., 2008). Results: When comparing the mean estimated frequency across conditions, a significant difference was found only in the 4-8Hz band, such that the frequency within this band was significantly higher for IC than NC stimuli starting at ~250ms post-stimulus onset (Fig. 1; solid line shows IC and dashed line NC). Significant differences in phase-amplitude couplings were obtained only when the 4-8 Hz band was taken as the low frequency band. Moreover, in all significant situations, the coupling strength is higher for the NC than IC condition. An example of significant difference between conditions is shown in Fig. 2 for the phase-amplitude coupling between the 4-8Hz and 55-65Hz bands (p-value in top panel and mean PLV values in the bottom panel). A decrease in coupling strength was observed shortly after stimulus onset for both conditions and was greater for the condition IC. This phenomenon was observed with all other frequency bands. The results obtained for the phase-phase couplings were more complex. As for the phase-amplitude couplings, all significant differences were obtained when the 4-8Hz band was considered as the low frequency band. The stimulus condition exhibiting the higher coupling strength depended on the ratio of the coupling coefficients. When this ratio was small, the IC condition exhibited the higher phase-phase coupling strength. When this ratio was large, the NC condition exhibited the higher coupling strength. Fig. 3 shows the phase-phase couplings between the 4-8Hz and 35-45Hz bands for the coupling coefficient 6:1, and the coupling strength was significantly higher for the IC than NC condition. By contrast, for the coupling coefficient 9:1 the NC condition gave the higher coupling strength (Fig. 4). Control analyses verified that it is not a consequence of the frequency difference between the two conditions in the 4-8Hz band. The directionality measures indicated a transfer of information from the low frequency components towards the high frequency ones. Conclusions: Adaptive tracking is a feasible method for EEG analyses, revealing information both about stimulus-related differences and coupling patterns across frequencies. Theta oscillations play a central role in illusory shape processing and more generally in visual processing. The presence vs. absence of illusory shapes was paralleled by faster theta oscillations. Phase-amplitude couplings were decreased more for IC than NC and might be due to a resetting mechanism. The complex patterns in phase-phase coupling between theta and beta/gamma suggest that the contribution of these oscillations to visual binding and stimulus processing are not as straightforward as conventionally held. Causality analyses further suggest that theta oscillations drive beta/gamma oscillations (see also Schroeder and Lakatos, 2009). The present findings highlight the need for applying more sophisticated signal analyses in order to establish a fuller understanding of the functional role of neural oscillations.

Efficiency of informational transfer in regular and complex networks

We analyze the process of informational exchange through complex networks by measuring network efficiencies. Aiming to study nonclustered systems, we propose a modification of this measure on the local level. We apply this method to an extension of the class of small worlds that includes declustered networks and show that they are locally quite efficient, although their clustering coefficient is practically zero. Unweighted systems with small-world and scale-free topologies are shown to be both globally and locally efficient. Our method is also applied to characterize weighted networks. In particular we examine the properties of underground transportation systems of Madrid and Barcelona and reinterpret the results obtained for the Boston subway network.

Supergenes and complex phenotypes.

Understanding the molecular underpinnings of evolutionary adaptations is a central focus of modern evolutionary biology. Recent studies have uncovered a panoply of complex phenotypes, including locally adapted ecotypes and cryptic morphs, divergent social behaviours in birds and insects, as well as alternative metabolic pathways in plants and fungi, that are regulated by clusters of tightly linked loci. These 'supergenes' segregate as stable polymorphisms within or between natural populations and influence ecologically relevant traits. Some supergenes may span entire chromosomes, because selection for reduced recombination between a supergene and a nearby locus providing additional benefits can lead to locus expansions with dynamics similar to those known for sex chromosomes. In addition to allowing for the co-segregation of adaptive variation within species, supergenes may facilitate the spread of complex phenotypes across species boundaries. Application of new genomic methods is likely to lead to the discovery of many additional supergenes in a broad range of organisms and reveal similar genetic architectures for convergently evolved phenotypes.

Spatiotemporal adaptive multiscale multiphysics simulations of two-phase flow

We present a spatiotemporal adaptive multiscale algorithm, which is based on the Multiscale Finite Volume method. The algorithm offers a very efficient framework to deal with multiphysics problems and to couple regions with different spatial resolution. We employ the method to simulate two-phase flow through porous media. At the fine scale, we consider a pore-scale description of the flow based on the Volume Of Fluid method. In order to construct a global problem that describes the coarse-scale behavior, the equations are averaged numerically with respect to auxiliary control volumes, and a Darcy-like coarse-scale model is obtained. The space adaptivity is based on the idea that a fine-scale description is only required in the front region, whereas the resolution can be coarsened elsewhere. Temporal adaptivity relies on the fact that the fine-scale and the coarse-scale problems can be solved with different temporal resolution (longer time steps can be used at the coarse scale). By simulating drainage under unstable flow conditions, we show that the method is able to capture the coarse-scale behavior outside the front region and to reproduce complex fluid patterns in the front region.

Ground-state order and spin-lattice coupling in tetrahedral spin systems Cu2Te2O5X2 (X = Br or Cl)

High-resolution ac susceptibility and thermal conductivity measurement on Cu2Te2O5X2 (X=Br,Cl) single crystals are reported. For Br-sample, sample dependence prevents one from distinguishing between possibilities of magnetically ordered and spin-singlet ground states. In Cl-sample a three-dimensional transition at 18.5 K is accompanied by almost isotropic behavior of susceptibility and almost switching behavior of thermal conductivity. Thermal conductivity studies suggest the presence of a tremendous spin-lattice coupling characterizing Cl- but not Br-sample. Below the transition Cl-sample is in a complex magnetic state involving AF order but also the elements consistent with the presence of a gap in the excitation spectrum.