Heritability, the proportion of phenotypic variance explained by genetic factors, can be estimated from pedigree data 1 , but such estimates are uninformative with respect to the underlying genetic architecture. Analyses of data from genome-wide association studies (GWAS) on unrelated individuals have shown that for human traits and disease, approximately one-third to two-thirds of heritability is captured by common SNPs 2-5 . It is not known whether the remaining heritability is due to the imperfect tagging of causal variants by common SNPs, in particular if the causal variants are rare, or other reasons such as overestimation of heritability from pedigree data. Here we show that pedigree heritability for height and body mass index (BMI) appears to be fully recovered from whole-genome sequence (WGS) data on 21,620 unrelated individuals of European ancestry. We assigned 47.1 million genetic variants to groups based upon their minor allele frequencies (MAF) and linkage disequilibrium (LD) with variants nearby, and estimated and partitioned variation accordingly. The estimated heritability was 0.79 (SE 0.09) for height and 0.40 (SE 0.09) for BMI, consistent with pedigree estimates. Low-MAF variants in low LD with neighbouring variants were enriched for heritability, to a greater extent for protein altering variants, consistent with negative selection thereon. Cumulatively variants in the MAF range of 0.0001 to 0.1 explained 0.54 (SE 0.05) and 0.51 (SE 0.11) of heritability for height and BMI, respectively. Our results imply that the still missing heritability of complex traits and disease is accounted for by rare variants, in particular those in regions of low LD.

This paper considers cloud radio access network with simultaneous wireless information and power transfer and finite capacity fronthaul, where the remote radio heads are equipped with renewable energy resources and can trade energy with the grid. Due to uneven distribution of mobile radio traffic and inherent intermittent nature of renewable energy resources, the remote radio heads may need real-time energy provisioning to meet the users' demands. Given the amount of available energy resources at remote radio heads, this paper introduces two provisioning strategies to strike an optimum balance among the total power consumption in the fronthaul, through adjusting the degree of partial cooperation among the remote radio heads, the total transmit power and the maximum or the overall real-time energy demand. More specifically, this paper formulates two sparse optimization problems and applies reweighted 1 -norm approximation for 0 -norm and semidefinite relaxation to develop two iterative algorithms for the proposed strategies. Simulation results confirm that both of the proposed strategies outperform two other recently proposed schemes in terms of improving energy efficiency and reducing overall energy cost of the network.Index Terms-C-RAN, real-time energy trading, sparse beamforming, SWIPT, fronthaul link capacity constraints.

Although many loci have been associated with height in European ancestry populations, very few have been identified in African ancestry individuals. Furthermore, many of the known loci have yet to be generalized to and fine-mapped within a large-scale African ancestry sample. We performed sex-combined and sex-stratified meta-analyses in up to 52,764 individuals with height and genome-wide genotyping data from the African Ancestry Anthropometry Genetics Consortium (AAAGC). We additionally combined our African ancestry meta-analysis results with published European genome-wide association study (GWAS) data. In the African ancestry analyses, we identified three novel loci (SLC4A3, NCOA2, ECD/FAM149B1) in sex-combined results and two loci (CRB1, KLF6) in women only. In the African plus European sex-combined GWAS, we identified an additional three novel loci (RCCD1, G6PC3, CEP95) which were equally driven by AAAGC and European results. Among 39 genome-wide significant signals at known loci, conditioning index SNPs from European studies identified 20 secondary signals. Two of the 20 new secondary signals and none of the 8 novel loci had minor allele frequencies (MAF) < 5%. Of 802 known European height signals, 643 displayed directionally consistent associations with height, of which 205 were nominally significant (p < 0.05) in the African ancestry sex-combined sample. Furthermore, 148 of 241 loci contained %20 variants in the credible sets that jointly account for 99% of the posterior probability of driving the associations. In summary, trans-ethnic meta-analyses revealed novel signals and further improved fine-mapping of putative causal variants in loci shared between African and European ancestry populations.

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Recently, equipping the base stations (BSs) with renewable energy harvesters for green communications has been considered as a promising technique to benefit both the environment and the retailer. However, the uneven distribution of renewable energy generation and the drastically increasing demand for mobile data has put forward the new challenge for the retailer. To tackle this problem, we propose a real-time base-station energy management (RBEM) strategy using renewable energy sources for green communications in coordinated multipoint networks with simultaneous wireless information and power transfer, where all the BSs collaborate to maintain the real-time supply and demand power balancing at the BSs, in order to reduce the overall energy cost of the retailer. The RBEM strategy is formulated as a non-convex linear combinational optimization problem to jointly minimize the energy consumption and energy trading, whilst accounting for the quality-of-service requirements for information receiving terminals and power transfer requirements for energy receiving terminals (ETs). Moreover, an iterative algorithm is proposed to determine the sources of energy harvested by the ETs. The original non-convex problem can be transformed into a numerically tractable form and solved using the semidefinite relaxation approach. Our simulation results confirm that the proposed RBEM strategy significantly reduces overall energy cost of the retailer.

If citing, it is advised that you check and use the publisher's definitive version for pagination, volume/issue, and date of publication details. And where the final published version is provided on the Research Portal, if citing you are again advised to check the publisher's website for any subsequent corrections.

In Smart Grid, the integration of Information and Communications Technology (ICT) systems and power systems has enabled real-time services and distributed controls, while the fusion of technologies necessitates a profound and versatile platform for the interdisciplinary research and evaluation. This article introduces a Software Defined Smart Grid testbed architecture, which integrates real-world wireless communication systems and Artificial Intelligence algorithms to provide a re-configurable framework to meet different real-time Smart Grid testbed design requirements. Through prototyping and experiments, the architecture shows great potential in addressing co-evaluation challenges of ICT systems and power systems, as well as supporting real-time Smart Grid evaluations. INDEX TERMS Artificial intelligence (AI), coevaluation, information and communications system, smart grid, software defined radio, testbed, wireless communications.

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