Interference management in underlay in-band D2D-enhanced cellular networks : (Invited Paper)

© 2018 IEEE. Recently, it has been standardized by the 3rd Generation Partnership Project (3GPP) [1] that device-to-device (D2D) communications should use uplink resources when coexisting with conventional cellular communications. With uplink resource sharing, both cellular and D2D links cause significant co-channel interference. In this paper, we consider a D2D mode selection criterion based on the maximum received signal strength (MRSS) for each user equipment (UE) to control the D2D-to-cellular interference. Specifically, a UE will operate in a cellular mode, if its received signal strength from the strongest base station (BS) is larger than a threshold β; otherwise, it will operate in a D2D mode. Furthermore, in our study, cellular UEs, D2D transmit UEs and D2D receiver UEs constitute the entire UE set, which is a more practical assumption than dropping more UEs for D2D reception only in existing works. The coverage probability and the area spectral efficiency (ASE) are derived for both the cellular network and the D2D one. Through our theoretical and numerical analyses, we quantify the performance gains brought by D2D communications and provide guidelines for selecting the parameters for network operations

Estimation of unsaturated hydraulic conductivity of granular soils from particle size parameters

Estimation of unsaturated hydraulic conductivity could benefit many engineering or research problems such as water flow in the vadose zone, unsaturated seepage and capillary barriers for underground waste isolation. The unsaturated hydraulic conductivity of a soil is related to its saturated hydraulic conductivity value as well as its water retention behaviour. By following the first author's previous work, the saturated hydraulic conductivity and water retention curve (WRC) of sandy soils can be estimated from their basic gradation parameters. In this paper, we further suggest the applicable range of the estimation method is for soils with d10 > 0.02mm and Cu < 20, in which d10 is the grain diameter corresponding to 10% passing and Cu is the coefficient of uniformity (Cu= d60/d10). The estimation method is also modified to consider the porosity variation effect. Then the proposed method is applied to predict unsaturated hydraulic conductivity properties of different sandy soils and also compared with laboratory and field test results. The comparison shows that the newly developed estimation method, which predicts the relative permeability of unsaturated sands from basic grain size parameters and porosity, generally has a fair agreement with measured data. It also indicates that the air-entry value is mainly relative to the mean grain size and porosity value change from the intrinsic value. The rate of permeability decline with suction is mainly associated with grain size polydispersity

Using the Pareto principle in genome-wide breeding value estimation

Genome-wide breeding value (GWEBV) estimation methods can be classified based on the prior distribution assumptions of marker effects. Genome-wide BLUP methods assume a normal prior distribution for all markers with a constant variance, and are computationally fast. In Bayesian methods, more flexible prior distributions of SNP effects are applied that allow for very large SNP effects although most are small or even zero, but these prior distributions are often also computationally demanding as they rely on Monte Carlo Markov chain sampling. In this study, we adopted the Pareto principle to weight available marker loci, i.e., we consider that x% of the loci explain (100 - x)% of the total genetic variance. Assuming this principle, it is also possible to define the variances of the prior distribution of the 'big' and 'small' SNP. The relatively few large SNP explain a large proportion of the genetic variance and the majority of the SNP show small effects and explain a minor proportion of the genetic variance. We name this method MixP, where the prior distribution is a mixture of two normal distributions, i.e. one with a big variance and one with a small variance. Simulation results, using a real Norwegian Red cattle pedigree, show that MixP is at least as accurate as the other methods in all studied cases. This method also reduces the hyper-parameters of the prior distribution from 2 (proportion and variance of SNP with big effects) to 1 (proportion of SNP with big effects), assuming the overall genetic variance is known. The mixture of normal distribution prior made it possible to solve the equations iteratively, which greatly reduced computation loads by two orders of magnitude. In the era of marker density reaching million(s) and whole-genome sequence data, MixP provides a computationally feasible Bayesian method of analysis

Accuracy of direct genomic values in Holstein bulls and cows using subsets of SNP markers

Background: At the current price, the use of high-density single nucleotide polymorphisms (SNP) genotyping assays in genomic selection of dairy cattle is limited to applications involving elite sires and dams. The objective of this study was to evaluate the use of low-density assays to predict direct genomic value (DGV) on five milk production traits, an overall conformation trait, a survival index, and two profit index traits (APR, ASI). Methods. Dense SNP genotypes were available for 42,576 SNP for 2,114 Holstein bulls and 510 cows. A subset of 1,847 bulls born between 1955 and 2004 was used as a training set to fit models with various sets of pre-selected SNP. A group of 297 bulls born between 2001 and 2004 and all cows born between 1992 and 2004 were used to evaluate the accuracy of DGV prediction. Ridge regression (RR) and partial least squares regression (PLSR) were used to derive prediction equations and to rank SNP based on the absolute value of the regression coefficients. Four alternative strategies were applied to select subset of SNP, namely: subsets of the highest ranked SNP for each individual trait, or a single subset of evenly spaced SNP, where SNP were selected based on their rank for ASI, APR or minor allele frequency within intervals of approximately equal length. Results: RR and PLSR performed very similarly to predict DGV, with PLSR performing better for low-density assays and RR for higher-density SNP sets. When using all SNP, DGV predictions for production traits, which have a higher heritability, were more accurate (0.52-0.64) than for survival (0.19-0.20), which has a low heritability. The gain in accuracy using subsets that included the highest ranked SNP for each trait was marginal (5-6%) over a common set of evenly spaced SNP when at least 3,000 SNP were used. Subsets containing 3,000 SNP provided more than 90% of the accuracy that could be achieved with a high-density assay for cows, and 80% of the high-density assay for young bulls. Conclusions: Accurate genomic evaluation of the broader bull and cow population can be achieved with a single genotyping assays containing ∼ 3,000 to 5,000 evenly spaced SNP

Best Linear Unbiased Prediction of Genomic Breeding Values Using a Trait-Specific Marker-Derived Relationship Matrix

With the availability of high density whole-genome single nucleotide polymorphism chips, genomic selection has become a promising method to estimate genetic merit with potentially high accuracy for animal, plant and aquaculture species of economic importance. With markers covering the entire genome, genetic merit of genotyped individuals can be predicted directly within the framework of mixed model equations, by using a matrix of relationships among individuals that is derived from the markers. Here we extend that approach by deriving a marker-based relationship matrix specifically for the trait of interest

Sensitivity to Gravitational Waves from Compact Binary Coalescences Achieved during LIGO's Fifth and Virgo's First Science Run

We summarize the sensitivity achieved by the LIGO and Virgo gravitational wave detectors for compact binary coalescence (CBC) searches during LIGO's fifth science run and Virgo's first science run. We present noise spectral density curves for each of the four detectors that operated during these science runs which are representative of the typical performance achieved by the detectors for CBC searches. These spectra are intended for release to the public as a summary of detector performance for CBC searches during these science runs.Comment: 12 pages, 5 figure

Search for Gravitational Waves from Low Mass Compact Binary Coalescence in LIGO's Sixth Science Run and Virgo's Science Runs 2 and 3

We report on a search for gravitational waves from coalescing compact binaries using LIGO and Virgo observations between July 7, 2009 and October 20, 2010. We searched for signals from binaries with total mass between 2 and 25 solar masses; this includes binary neutron stars, binary black holes, and binaries consisting of a black hole and neutron star. The detectors were sensitive to systems up to 40 Mpc distant for binary neutron stars, and further for higher mass systems. No gravitational-wave signals were detected. We report upper limits on the rate of compact binary coalescence as a function of total mass, including the results from previous LIGO and Virgo observations. The cumulative 90%-confidence rate upper limits of the binary coalescence of binary neutron star, neutron star- black hole and binary black hole systems are 1.3 x 10^{-4}, 3.1 x 10^{-5} and 6.4 x 10^{-6} Mpc^{-3}yr^{-1}, respectively. These upper limits are up to a factor 1.4 lower than previously derived limits. We also report on results from a blind injection challenge.Comment: 11 pages, 5 figures. For a repository of data used in the publication, go to: . Also see the announcement for this paper on ligo.org at: <http://www.ligo.org/science/Publication-S6CBCLowMass/index.php

Implementation and testing of the first prompt search for gravitational wave transients with electromagnetic counterparts

Aims. A transient astrophysical event observed in both gravitational wave (GW) and electromagnetic (EM) channels would yield rich scientific rewards. A first program initiating EM follow-ups to possible transient GW events has been developed and exercised by the LIGO and Virgo community in association with several partners. In this paper, we describe and evaluate the methods used to promptly identify and localize GW event candidates and to request images of targeted sky locations. Methods. During two observing periods (Dec 17 2009 to Jan 8 2010 and Sep 2 to Oct 20 2010), a low-latency analysis pipeline was used to identify GW event candidates and to reconstruct maps of possible sky locations. A catalog of nearby galaxies and Milky Way globular clusters was used to select the most promising sky positions to be imaged, and this directional information was delivered to EM observatories with time lags of about thirty minutes. A Monte Carlo simulation has been used to evaluate the low-latency GW pipeline's ability to reconstruct source positions correctly. Results. For signals near the detection threshold, our low-latency algorithms often localized simulated GW burst signals to tens of square degrees, while neutron star/neutron star inspirals and neutron star/black hole inspirals were localized to a few hundred square degrees. Localization precision improves for moderately stronger signals. The correct sky location of signals well above threshold and originating from nearby galaxies may be observed with ~50% or better probability with a few pointings of wide-field telescopes.Comment: 17 pages. This version (v2) includes two tables and 1 section not included in v1. Accepted for publication in Astronomy & Astrophysic

First Low-Latency LIGO+Virgo Search for Binary Inspirals and their Electromagnetic Counterparts

Aims. The detection and measurement of gravitational-waves from coalescing neutron-star binary systems is an important science goal for ground-based gravitational-wave detectors. In addition to emitting gravitational-waves at frequencies that span the most sensitive bands of the LIGO and Virgo detectors, these sources are also amongst the most likely to produce an electromagnetic counterpart to the gravitational-wave emission. A joint detection of the gravitational-wave and electromagnetic signals would provide a powerful new probe for astronomy. Methods. During the period between September 19 and October 20, 2010, the first low-latency search for gravitational-waves from binary inspirals in LIGO and Virgo data was conducted. The resulting triggers were sent to electromagnetic observatories for followup. We describe the generation and processing of the low-latency gravitational-wave triggers. The results of the electromagnetic image analysis will be described elsewhere. Results. Over the course of the science run, three gravitational-wave triggers passed all of the low-latency selection cuts. Of these, one was followed up by several of our observational partners. Analysis of the gravitational-wave data leads to an estimated false alarm rate of once every 6.4 days, falling far short of the requirement for a detection based solely on gravitational-wave data.Comment: 13 pages, 13 figures. For a repository of data used in the publication, go to: http://dcc.ligo.org/cgi-bin/DocDB/ShowDocument?docid=P1100065 Also see the announcement for this paper on ligo.org at: http://www.ligo.org/science/Publication-S6CBCLowLatency

Diversity of Prophage DNA Regions of Streptococcus agalactiae Clonal Lineages from Adults and Neonates with Invasive Infectious Disease

The phylogenetic position and prophage DNA content of the genomes of 142 S. agalactiae (group-B streptococcus, GBS) isolates responsible for bacteremia and meningitis in adults and neonates were studied and compared. The distribution of the invasive isolates between the various serotypes, sequence types (STs) and clonal complexes (CCs) differed significantly between adult and neonatal isolates. Use of the neighbor-net algorithm with the PHI test revealed evidence for recombination in the population studied (PHI, P = 2.01×10−6), and the recombination-mutation ratio (R/M) was 6∶7. Nevertheless, the estimated R/M ratio differed between CCs. Analysis of the prophage DNA regions of the genomes of the isolates assigned 90% of the isolates to five major prophage DNA groups: A to E. The mean number of prophage DNA fragments amplified per isolate varied from 2.6 for the isolates of prophage DNA group E to 4.0 for the isolates of prophage DNA group C. The isolates from adults and neonates with invasive diseases were distributed differently between the various prophage DNA groups (P<0.00001). Group C prophage DNA fragments were found in 52% of adult invasive isolates, whereas 74% of neonatal invasive isolates had prophage DNA fragments of groups A and B. Differences in prophage DNA content were also found between serotypes, STs and CCs (P<0.00001). All the ST-1 and CC1 isolates, mostly of serotype V, belonged to the prophage DNA group C, whereas 84% of the ST-17 and CC17 isolates, all of serotype III, belonged to prophage DNA groups A and B. These data indicate that the transduction mechanisms, i.e., gene transfer from one bacterium to another by a bacteriophage, underlying genetic recombination in S. agalactiae species, are specific to each intraspecies lineage and population of strains responsible for invasive diseases in adults and neonates