Language comparison via network topology

Modeling relations between languages can offer understanding of language characteristics and uncover similarities and differences between languages. Automated methods applied to large textual corpora can be seen as opportunities for novel statistical studies of language development over time, as well as for improving cross-lingual natural language processing techniques. In this work, we first propose how to represent textual data as a directed, weighted network by the text2net algorithm. We next explore how various fast, network-topological metrics, such as network community structure, can be used for cross-lingual comparisons. In our experiments, we employ eight different network topology metrics, and empirically showcase on a parallel corpus, how the methods can be used for modeling the relations between nine selected languages. We demonstrate that the proposed method scales to large corpora consisting of hundreds of thousands of aligned sentences on an of-the-shelf laptop. We observe that on the one hand properties such as communities, capture some of the known differences between the languages, while others can be seen as novel opportunities for linguistic studies

Spatiotemporal correlations of handset-based service usages

We study spatiotemporal correlations and temporal diversities of handset-based service usages by analyzing a dataset that includes detailed information about locations and service usages of 124 users over 16 months. By constructing the spatiotemporal trajectories of the users we detect several meaningful places or contexts for each one of them and show how the context affects the service usage patterns. We find that temporal patterns of service usages are bound to the typical weekly cycles of humans, yet they show maximal activities at different times. We first discuss their temporal correlations and then investigate the time-ordering behavior of communication services like calls being followed by the non-communication services like applications. We also find that the behavioral overlap network based on the clustering of temporal patterns is comparable to the communication network of users. Our approach provides a useful framework for handset-based data analysis and helps us to understand the complexities of information and communications technology enabled human behavior.Comment: 11 pages, 15 figure

Testing special relativity with geodetic VLBI

Geodetic Very Long Baseline Interferometry (VLBI) measures the group delay in the barycentric reference frame. As the Earth is orbiting around the Solar system barycentre with the velocity $V$ of 30 km/s, VLBI proves to be a handy tool to detect the subtle effects of the special and general relativity theory with a magnitude of $(V/\textrm{c})^2$. The theoretical correction for the second order terms reaches up to 300~ps, and it is implemented in the geodetic VLBI group delay model. The total contribution of the second order terms splits into two effects - the variation of the Earth scale, and the deflection of the apparent position of the radio source. The Robertson-Mansouri-Sexl (RMS) generalization of the Lorenz transformation is used for many modern tests of the special relativity theory. We develop an alteration of the RMS formalism to probe the Lorenz invariance with the geodetic VLBI data. The kinematic approach implies three parameters (as a function of the moving reference frame velocity) and the standard Einstein synchronisation. A generalised relativistic model of geodetic VLBI data includes all three parameters that could be estimated. Though, since the modern laboratory Michelson-Morley and Kennedy-Thorndike experiments are more accurate than VLBI technique, the presented equations may be used to test the VLBI group delay model itself.Comment: Proceedings of the IAG 2017 Scientific Meeting, Kobe, Japa

Best Unbiased Estimates for the Microwave Background Anisotropies

It is likely that the observed distribution of the microwave background temperature over the sky is only one realization of the underlying random process associated with cosmological perturbations of quantum-mechanical origin. If so, one needs to derive the parameters of the random process, as accurately as possible, from the data of a single map. These parameters are of the utmost importance, since our knowledge of them would help us to reconstruct the dynamical evolution of the very early Universe. It appears that the lack of ergodicity of a random process on a 2-sphere does not allow us to do this with arbitrarily high accuracy. We are left with the problem of finding the best unbiased estimators of the participating parameters. A detailed solution to this problem is presented in this article. The theoretical error bars for the best unbiased estimates are derived and discussed.Comment: 26 pages, revtex; minor modifications, 8 new references, to be published in Phys. Rev.

MAXIPOL: a balloon-borne experiment for measuring the polarization anisotropy of the cosmic microwave background radiation

We discuss MAXIPOL, a bolometric balloon-borne experiment designed to measure the E-mode polarization anisotropy of the cosmic microwave background radiation (CMB) on angular scales of 10 arcmin to 2 degrees. MAXIPOL is the first CMB experiment to collect data with a polarimeter that utilizes a rotating half-wave plate and fixed wire-grid polarizer. We present the instrument design, elaborate on the polarimeter strategy and show the instrument performance during flight with some time domain data. Our primary data set was collected during a 26 hour turnaround flight that was launched from the National Scientific Ballooning Facility in Ft. Sumner, New Mexico in May 2003. During this flight five regions of the sky were mapped. Data analysis is in progress

A computational approach to chemical etiologies of diabetes.

Computational meta-analysis can link environmental chemicals to genes and proteins involved in human diseases, thereby elucidating possible etiologies and pathogeneses of non-communicable diseases. We used an integrated computational systems biology approach to examine possible pathogenetic linkages in type 2 diabetes (T2D) through genome-wide associations, disease similarities, and published empirical evidence. Ten environmental chemicals were found to be potentially linked to T2D, the highest scores were observed for arsenic, 2,3,7,8-tetrachlorodibenzo-p-dioxin, hexachlorobenzene, and perfluorooctanoic acid. For these substances we integrated disease and pathway annotations on top of protein interactions to reveal possible pathogenetic pathways that deserve empirical testing. The approach is general and can address other public health concerns in addition to identifying diabetogenic chemicals, and offers thus promising guidance for future research in regard to the etiology and pathogenesis of complex diseases

Network Analysis of Oyster Transcriptome Revealed a Cascade of Cellular Responses during Recovery after Heat Shock

Oysters, as a major group of marine bivalves, can tolerate a wide range of natural and anthropogenic stressors including heat stress. Recent studies have shown that oysters pretreated with heat shock can result in induced heat tolerance. A systematic study of cellular recovery from heat shock may provide insights into the mechanism of acquired thermal tolerance. In this study, we performed the first network analysis of oyster transcriptome by reanalyzing microarray data from a previous study. Network analysis revealed a cascade of cellular responses during oyster recovery after heat shock and identified responsive gene modules and key genes. Our study demonstrates the power of network analysis in a non-model organism with poor gene annotations, which can lead to new discoveries that go beyond the focus on individual genes

The Gene Expression Analysis of Blood Reveals S100A11 and AQP9 as Potential Biomarkers of Infective Endocarditis

BACKGROUND: The diagnostic and prognostic assessments of infective endocarditis (IE) are challenging. To investigate the host response during IE and to identify potential biomarkers, we determined the circulating gene expression profile using whole genome microarray analysis. METHODS AND RESULTS: A transcriptomic case-control study was performed on blood samples from patients with native valve IE (n = 39), excluded IE after an initial suspicion (n = 10) at patient's admission, and age-matched healthy controls (n = 10). Whole genome microarray analysis showed that patients with IE exhibited a specific transcriptional program with a predominance of gene categories associated with cell activation as well as innate immune and inflammatory responses. Quantitative real-time RT-PCR performed on a selection of highly modulated genes showed that the expression of the gene encoding S100 calcium binding protein A11 (S100A11) was significantly increased in patients with IE in comparison with controls (P<0.001) and patients with excluded IE (P<0.05). Interestingly, the upregulated expression of the S100A11 gene was more pronounced in staphylococcal IE than in streptococcal IE (P<0.01). These results were confirmed by serum concentrations of the S100A11 protein. Finally, we showed that in patients with IE, the upregulation of the aquaporin-9 gene (AQP9) was significantly associated with the occurrence of acute heart failure (P = 0.02). CONCLUSIONS: Using transcriptional signatures of blood samples, we identified S100A11 as a potential diagnostic marker of IE, and AQP9 as a potential prognostic factor

The Discovery of Putative Urine Markers for the Specific Detection of Prostate Tumor by Integrative Mining of Public Genomic Profiles

Urine has emerged as an attractive biofluid for the noninvasive detection of prostate cancer (PCa). There is a strong imperative to discover candidate urinary markers for the clinical diagnosis and prognosis of PCa. The rising flood of various omics profiles presents immense opportunities for the identification of prospective biomarkers. Here we present a simple and efficient strategy to derive candidate urine markers for prostate tumor by mining cancer genomic profiles from public databases. Prostate, bladder and kidney are three major tissues from which cellular matters could be released into urine. To identify urinary markers specific for PCa, upregulated entities that might be shed in exosomes of bladder cancer and kidney cancer are first excluded. Through the ontology-based filtering and further assessment, a reduced list of 19 entities encoding urinary proteins was derived as putative PCa markers. Among them, we have found 10 entities closely associated with the process of tumor cell growth and development by pathway enrichment analysis. Further, using the 10 entities as seeds, we have constructed a protein-protein interaction (PPI) subnetwork and suggested a few urine markers as preferred prognostic markers to monitor the invasion and progression of PCa. Our approach is amenable to discover and prioritize potential markers present in a variety of body fluids for a spectrum of human diseases

A Review of One-Way and Two-Way Experiments to Test the Isotropy of the Speed of Light

As we approach the 125th anniversary of the Michelson-Morley experiment in 2012, we review experiments that test the isotropy of the speed of light. Previous measurements are categorized into one-way (single-trip) and two-way (round-trip averaged or over closed paths) approaches and the level of experimental verification that these experiments provide is discussed. The isotropy of the speed of light is one of the postulates of the Special Theory of Relativity (STR) and, consequently, this phenomenon has been subject to considerable experimental scrutiny. Here, we tabulate significant experiments performed since 1881 and attempt to indicate a direction for future investigation.Comment: Updated Fig. 7 and references; Revised sections 3.2 and 4. Accepted in the Indian Journal of Physics on March 30, 201