Monotone graph limits and quasimonotone graphs

The recent theory of graph limits gives a powerful framework for understanding the properties of suitable (convergent) sequences $(G_n)$ of graphs in terms of a limiting object which may be represented by a symmetric function $W$ on $[0,1]$, i.e., a kernel or graphon. In this context it is natural to wish to relate specific properties of the sequence to specific properties of the kernel. Here we show that the kernel is monotone (i.e., increasing in both variables) if and only if the sequence satisfies a `quasi-monotonicity' property defined by a certain functional tending to zero. As a tool we prove an inequality relating the cut and $L^1$ norms of kernels of the form $W_1-W_2$ with $W_1$ and $W_2$ monotone that may be of interest in its own right; no such inequality holds for general kernels.Comment: 38 page

Platform Dependent Verification: On Engineering Verification Tools for 21st Century

The paper overviews recent developments in platform-dependent explicit-state LTL model checking.Comment: In Proceedings PDMC 2011, arXiv:1111.006

Thermal and mechanical properties of hemp fabric-reinforced nanoclay-cement nano-composites

The influence of nanoclay on thermal and mechanical properties of hemp fabric-reinforced cement composite is presented in this paper. Results indicate that these properties are improved as a result of nanoclay addition. An optimum replacement of ordinary Portland cement with 1 wt% nanoclay is observed through improved thermal stability, reduced porosity and water absorption as well as increased density, flexural strength, fracture toughness and impact strength of hemp fabric-reinforced nanocomposite. The microstructural analyses indicate that the nanoclay behaves not only as a filler to improve the microstructure but also as an activator to promote the pozzolanic reaction and thus improve the adhesion between hemp fabric and nanomatrix

Examination of Msh6- and Msh3-deficient Mice in Class Switching Reveals Overlapping and Distinct Roles of MutS Homologues in Antibody Diversification

Somatic hypermutation and class switch recombination (CSR) contribute to the somatic diversification of antibodies. It has been shown that MutS homologue (Msh)6 (in conjunction with Msh2) but not Msh3 is involved in generating A/T base substitutions in somatic hypermutation. However, their roles in CSR have not yet been reported. Here we show that Msh6−/− mice have a decrease in CSR, whereas Msh3−/− mice do not. When switch regions were analyzed for mutations, deficiency in Msh6 was associated with an increase in transition mutations at G/C basepairs, mutations at RGYW/WRCY hotspots, and a small increase in the targeting of G/C bases. In addition, Msh6−/− mice exhibited an increase in the targeting of recombination sites to GAGCT/GGGGT consensus repeats and hotspots in Sγ3 but not in Sμ. In contrast to Msh2−/− mice, deficiency in Msh6 surprisingly did not change the characteristics of Sμ-Sγ3 switch junctions. However, Msh6−/− mice exhibited a change in the positioning of Sμ and Sγ3 junctions. Although none of these changes were seen in Msh3−/− mice, they had a higher percentage of large inserts in their switch junctions. Together, our data suggest that MutS homologues Msh2, Msh3, and Msh6 play overlapping and distinct roles during antibody diversification processes

Land subsidence hazard in iran revealed by country-scale analysis of sentinel-1 insar

Many areas across Iran are subject to land subsidence, a sign of exceeding stress due to the over-extraction of groundwater during the past decades. This paper uses a huge dataset of Sentinel-1, acquired since 2014 in 66 image frames of 250×250km, to identify and monitor land subsidence across Iran. Using a two-step time series analysis, we first identify subsidence zones at a medium scale of 100m across the country. For the first time, our results provide a comprehensive nationwide map of subsidence in Iran and recognize its spatial distribution and magnitude. Then, in the second step of analysis, we quantify the deformation time series at the highest possible resolution to study its impact on civil infrastructure. The results spots the hazard posed by land subsidence to different infrastructure. Examples of road and railways affected by land subsidence hazard in Tehran and Mashhad, two of the most populated cities in Iran, are presented in this study

Exploring cloud-based platforms for rapid insar time series analysis

The idea of near real-time deformation analysis using Synthetic Aperture Radar (SAR) data as a response to natural and anthropogenic disasters has been an interesting topic in the last years. A major limiting factor for this purpose has been the non-availability of both spatially and temporally homogeneous SAR datasets. This has now been resolved thanks to the SAR data provided by the Sentinel-1A/B missions, freely available at a global scale via the Copernicus program of the European Space Agency (ESA). Efficient InSAR analysis in the era of Sentinel demands working with cloud-based platforms to tackle problems posed by large volumes of data. In this study, we explore a variety of existing cloud-based platforms for Multioral Interferometric SAR (MTI) analysis and discuss their opportunities and limitations

Linear, Deterministic, and Order-Invariant Initialization Methods for the K-Means Clustering Algorithm

Over the past five decades, k-means has become the clustering algorithm of choice in many application domains primarily due to its simplicity, time/space efficiency, and invariance to the ordering of the data points. Unfortunately, the algorithm's sensitivity to the initial selection of the cluster centers remains to be its most serious drawback. Numerous initialization methods have been proposed to address this drawback. Many of these methods, however, have time complexity superlinear in the number of data points, which makes them impractical for large data sets. On the other hand, linear methods are often random and/or sensitive to the ordering of the data points. These methods are generally unreliable in that the quality of their results is unpredictable. Therefore, it is common practice to perform multiple runs of such methods and take the output of the run that produces the best results. Such a practice, however, greatly increases the computational requirements of the otherwise highly efficient k-means algorithm. In this chapter, we investigate the empirical performance of six linear, deterministic (non-random), and order-invariant k-means initialization methods on a large and diverse collection of data sets from the UCI Machine Learning Repository. The results demonstrate that two relatively unknown hierarchical initialization methods due to Su and Dy outperform the remaining four methods with respect to two objective effectiveness criteria. In addition, a recent method due to Erisoglu et al. performs surprisingly poorly.Comment: 21 pages, 2 figures, 5 tables, Partitional Clustering Algorithms (Springer, 2014). arXiv admin note: substantial text overlap with arXiv:1304.7465, arXiv:1209.196

MSH2/MSH6 Complex Promotes Error-Free Repair of AID-Induced dU:G Mispairs as well as Error-Prone Hypermutation of A:T Sites

Mismatch repair of AID-generated dU:G mispairs is critical for class switch recombination (CSR) and somatic hypermutation (SHM) in B cells. The generation of a previously unavailable Msh2−/−Msh6−/− mouse has for the first time allowed us to examine the impact of the complete loss of MutSα on lymphomagenesis, CSR and SHM. The onset of T cell lymphomas and the survival of Msh2−/−Msh6−/− and Msh2−/−Msh6−/−Msh3−/− mice are indistinguishable from Msh2−/− mice, suggesting that MSH2 plays the critical role in protecting T cells from malignant transformation, presumably because it is essential for the formation of stable MutSα heterodimers that maintain genomic stability. The similar defects on switching in Msh2−/−, Msh2−/−Msh6−/− and Msh2−/−Msh6−/−Msh3−/− mice confirm that MutSα but not MutSβ plays an important role in CSR. Analysis of SHM in Msh2−/−Msh6−/− mice not only confirmed the error-prone role of MutSα in the generation of strand biased mutations at A:T bases, but also revealed an error-free role of MutSα when repairing some of the dU:G mispairs generated by AID on both DNA strands. We propose a model for the role of MutSα at the immunoglobulin locus where the local balance of error-free and error-prone repair has an impact in the spectrum of mutations introduced during Phase 2 of SHM

Crystal structure of the Ego1-Ego2-Ego3 complex and its role in promoting Rag GTPase-dependent TORC1 signaling

The target of rapamycin complex 1 (TORC1) integrates various hormonal and nutrient signals to regulate cell growth, proliferation, and differentiation. Amino acid-dependent activation of TORC1 is mediated via the yeast EGO complex (EGOC) consisting of Gtr1, Gtr2, Ego1, and Ego3. Here, we identify the previously uncharacterized Ycr075w-a/Ego2 protein as an additional EGOC component that is required for the integrity and localization of the heterodimeric Gtr1-Gtr2 GTPases, equivalent to mammalian Rag GTPases. We also report the crystal structure of the Ego1-Ego2-Ego3 ternary complex (EGO-TC) at 2.4 Å resolution, in which Ego2 and Ego3 form a heterodimer flanked along one side by Ego1. Structural data also reveal the structural conservation of protein components between the yeast EGO-TC and the human Ragulator, which acts as a GEF for Rag GTPases. Interestingly, however, artificial tethering of Gtr1-Gtr2 to the vacuolar membrane is sufficient to activate TORC1 in response to amino acids even in the absence of the EGO-TC. Our structural and functional data therefore support a model in which the EGO-TC acts as a scaffold for Rag GTPases in TORC1 signaling