283 research outputs found
Throughput and Robustness Guaranteed Beam Tracking for mmWave Wireless Networks
With the increasing demand of ultra-high-speed wireless communications and
the existing low frequency band (e.g., sub-6GHz) becomes more and more crowded,
millimeter-wave (mmWave) with large spectra available is considered as the most
promising frequency band for future wireless communications. Since the mmWave
suffers a serious path-loss, beamforming techniques shall be adopted to
concentrate the transmit power and receive region on a narrow beam for
achieving long distance communications. However, the mobility of users will
bring frequent beam handoff, which will decrease the quality of experience
(QoE). Therefore, efficient beam tracking mechanism should be carefully
researched. However, the existing beam tracking mechanisms concentrate on
system throughput maximization without considering beam handoff and link
robustness. This paper proposes a throughput and robustness guaranteed beam
tracking mechanism for mobile mmWave communication systems which takes account
of both system throughput and handoff probability. Simulation results show that
the proposed throughput and robustness guaranteed beam tracking mechanism can
provide better performance than the other beam tracking mechanisms.Comment: Accepted by IEEE/CIC ICCC 201
Robust estimates in generalized partially linear models
In this paper, we introduce a family of robust estimates for the parametric
and nonparametric components under a generalized partially linear model, where
the data are modeled by with
\mu_i=H(\eta(t_i)+\mathbf{x}_i^{\mathrm{T}}\beta), for some known
distribution function F and link function H. It is shown that the estimates of
are root-n consistent and asymptotically normal. Through a Monte Carlo
study, the performance of these estimators is compared with that of the
classical ones.Comment: Published at http://dx.doi.org/10.1214/009053606000000858 in the
Annals of Statistics (http://www.imstat.org/aos/) by the Institute of
Mathematical Statistics (http://www.imstat.org
Robust Estimation and Inference for Expected Shortfall Regression with Many Regressors
Expected Shortfall (ES), also known as superquantile or Conditional
Value-at-Risk, has been recognized as an important measure in risk analysis and
stochastic optimization, and is also finding applications beyond these areas.
In finance, it refers to the conditional expected return of an asset given that
the return is below some quantile of its distribution. In this paper, we
consider a recently proposed joint regression framework that simultaneously
models the quantile and the ES of a response variable given a set of
covariates, for which the state-of-the-art approach is based on minimizing a
joint loss function that is non-differentiable and non-convex. This inevitably
raises numerical challenges and limits its applicability for analyzing
large-scale data. Motivated by the idea of using Neyman-orthogonal scores to
reduce sensitivity with respect to nuisance parameters, we propose a
statistically robust (to highly skewed and heavy-tailed data) and
computationally efficient two-step procedure for fitting joint quantile and ES
regression models. With increasing covariate dimensions, we establish explicit
non-asymptotic bounds on estimation and Gaussian approximation errors, which
lay the foundation for statistical inference. Finally, we demonstrate through
numerical experiments and two data applications that our approach well balances
robustness, statistical, and numerical efficiencies for expected shortfall
regression
Beaver and Naked Mole Rat Genomes Reveal Common Paths to Longevity
Long-lived rodents have become an attractive model for the studies on aging. To understand evolutionary paths to long life, we prepare chromosome-level genome assemblies of the two longest-lived rodents, Canadian beaver (Castor canadensis) and naked mole rat (NMR, Heterocephalus glaber), which were scaffolded with in vitro proximity ligation and chromosome conformation capture data and complemented with long-read sequencing. Our comparative genomic analyses reveal that amino acid substitutions at disease-causing sites are widespread in the rodent genomes and that identical substitutions in long-lived rodents are associated with common adaptive phenotypes, e.g., enhanced resistance to DNA damage and cellular stress. By employing a newly developed substitution model and likelihood ratio test, we find that energy and fatty acid metabolism pathways are enriched for signals of positive selection in both long-lived rodents. Thus, the high-quality genome resource of long-lived rodents can assist in the discovery of genetic factors that control longevity and adaptive evolution
Considerable MHC Diversity Suggests That the Functional Extinction of Baiji Is Not Related to Population Genetic Collapse
To further extend our understanding of the mechanism causing the current nearly extinct status of the baiji (Lipotes vexillifer), one of the most critically endangered species in the world, genetic diversity at the major histocompatibility complex (MHC) class II DRB locus was investigated in the baiji. Nine highly divergent DRB alleles were identified in 17 samples, with an average of 28.4 (13.2%) nucleotide difference and 16.7 (23.5%) amino acid difference between alleles. The unexpectedly high levels of DRB allelic diversity in the baiji may partly be attributable to its evolutionary adaptations to the freshwater environment which is regarded to have a higher parasite diversity compared to the marine environment. In addition, balancing selection was found to be the main mechanisms in generating sequence diversity at baiji DRB gene. Considerable sequence variation at the adaptive MHC genes despite of significant loss of neutral genetic variation in baiji genome might suggest that intense selection has overpowered random genetic drift as the main evolutionary forces, which further suggested that the critically endangered or nearly extinct status of the baiji is not an outcome of genetic collapse
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