Genome-wide association analysis of secondary imaging phenotypes from the Alzheimer's disease neuroimaging initiative study

The aim of this paper is to systematically evaluate a biased sampling issue associated with genome-wide association analysis (GWAS) of imaging phenotypes for most imaging genetic studies, including the Alzheimer’s Disease Neuroimaging Initiative (ADNI). Specifically, the original sampling scheme of these imaging genetic studies is primarily the retrospective case-control design, whereas most existing statistical analyses of these studies ignore such sampling scheme by directly correlating imaging phenotypes (called the secondary traits) with genotype. Although it has been well documented in genetic epidemiology that ignoring the case-control sampling scheme can produce highly biased estimates, and subsequently lead to misleading results and suspicious associations, such findings are not well documented in imaging genetics. We use extensive simulations and a large-scale imaging genetic data analysis of the Alzheimer’s Disease Neuroimag-ing Initiative (ADNI) data to evaluate the effects of the case-control sampling scheme on GWAS results based on some standard statistical methods, such as linear regression methods, while comparing it with several advanced statistical methods that appropriately adjust for the case-control sampling scheme

SemantIC: Semantic Interference Cancellation Towards 6G Wireless Communications

This letter proposes a novel anti-interference technique, semantic interference cancellation (SemantIC), for enhancing information quality towards the sixth-generation (6G) wireless networks. SemantIC only requires the receiver to concatenate the channel decoder with a semantic auto-encoder. This constructs a turbo loop which iteratively and alternately eliminates noise in the signal domain and the semantic domain. From the viewpoint of network information theory, the neural network of the semantic auto-encoder stores side information by training, and provides side information in iterative decoding, as an implementation of the Wyner-Ziv theorem. Simulation results verify the performance improvement by SemantIC without extra channel resource cost

Evolution of cold streams in hot gaseous halos

In the prevailing model of galaxy formation and evolution, the process of gas accretion onto central galaxies undergoes a transition from cold-dominated to hot-dominated modes. This shift occurs when the mass of the parent dark matter halos exceeds a critical threshold known as $M_{shock}$. Moreover, cold gas usually flows onto central galaxies through filamentary structures, currently referred to as cold streams. However, the evolution of cold streams in halos with masses around $M_{shock}$, particularly how they are disrupted, remains unclear. To address this issue, we conduct a set of idealised hydrodynamic simulations. Our simulations show that (1) for a gas metallicity $Z=0.001-0.1Z_{\odot}$, cold stream with an inflow rate $\sim 3\, \rm{M_{\odot}}/yr$ per each can persist and effectively transport cold and cool gas to the central region ($< 0.2$ virial radius) in halos with mass $10^{12}\, \rm{M_{\odot}}$, but is disrupted at a radius around $0.2$ virial radius due to compression heating for halos with mass $3 \times 10^{12}\, \rm{M_{\odot}}$. (2) At $z\sim 2$, the maximum halo mass that capable of hosting and sustaining cold streams $M_{stream}$ is between $1\times 10^{12} \rm{M_{\odot}}$ and $1.5\times 10^{12}\rm{M_{\odot}}$ for gas metallicity $Z=0.001Z_{\odot}$, while for a higher gas metallicity $Z=0.1Z_{\odot}$, this value increases to $\sim 1.5\times 10^{12}\rm{M_{\odot}}$. (3) The evolution and ultimate fate of cold streams are determined primarily by the rivalry between radiative cooling and compression. Stronger heating due to compression in halos more massive than $M_{stream}$ can surpass cooling and heat the gas in cold streams to the hot ($\geq 10^6\,$ K) phase.Comment: 26 pages, 18 figures, accepted for publication in MNRA

A Non-Stationary VVLC MIMO Channel Model for Street Corner Scenarios

In recent years, the application potential of visible light communication (VLC) technology as an alternative and supplement to radio frequency (RF) technology has attracted people's attention. The study of the underlying VLC channel is the basis for designing the VLC communication system. In this paper, a new non-stationary geometric street corner model is proposed for vehicular VLC (VVLC) multiple-input multiple-output (MIMO) channel. The proposed model takes into account changes in vehicle speed and direction. The category of scatterers includes fixed scatterers and mobile scatterers (MS). Based on the proposed model, we derive the channel impulse response (CIR) and explore the statistical characteristics of the VVLC channel. The channel gain and root mean square (RMS) delay spread of the VVLC channel are studied. In addition, the influence of velocity change on the statistical characteristics of the model is also investigated. The proposed channel model can guide future vehicle-to-infrastructure (V2I) and vehicle-to-vehicle (V2V) optical communication system design

Memory management in genome-wide association studies

Genome-wide association is a powerful tool for the identification of genes that underlie common diseases. Genome-wide association studies generate billions of genotypes and pose significant computational challenges for most users including limited computer memory. We applied a recently developed memory management tool to two analyses of North American Rheumatoid Arthritis Consortium studies and measured the performance in terms of central processing unit and memory usage. We conclude that our memory management approach is simple, efficient, and effective for genome-wide association studies

A genome-wide association analysis of Framingham Heart Study longitudinal data using multivariate adaptive splines

The Framingham Heart Study is a well known longitudinal cohort study. In recent years, the community-based Framingham Heart Study has embarked on genome-wide association studies. In this paper, we present a Framingham Heart Study genome-wide analysis for fasting triglycerides trait in the Genetic Analysis Workshop16 Problem 2 using multivariate adaptive splines for the analysis of longitudinal data (MASAL). With MASAL, we are able to perform analysis of genome-wide data with longitudinal phenotypes and covariates, making it possible to identify genes, gene-gene, and gene-environment (including time) interactions associated with the trait of interest. We conducted a permutation test to assess the associations between MASAL selected markers and triglycerides trait and report significant gene-gene and gene-environment interaction effects on the trait of interest