| 1. |
- Sampson, Joshua N., et al.
(författare)
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Analysis of Heritability and Shared Heritability Based on Genome-Wide Association Studies for 13 Cancer Types
- 2015
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Ingår i: Journal of the National Cancer Institute. - : Oxford University Press (OUP). - 0027-8874 .- 1460-2105. ; 107:12
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Tidskriftsartikel (refereegranskat)abstract
- Background: Studies of related individuals have consistently demonstrated notable familial aggregation of cancer. We aim to estimate the heritability and genetic correlation attributable to the additive effects of common single-nucleotide polymorphisms (SNPs) for cancer at 13 anatomical sites. Methods: Between 2007 and 2014, the US National Cancer Institute has generated data from genome-wide association studies (GWAS) for 49 492 cancer case patients and 34 131 control patients. We apply novel mixed model methodology (GCTA) to this GWAS data to estimate the heritability of individual cancers, as well as the proportion of heritability attributable to cigarette smoking in smoking-related cancers, and the genetic correlation between pairs of cancers. Results: GWAS heritability was statistically significant at nearly all sites, with the estimates of array-based heritability, h(l)(2), on the liability threshold (LT) scale ranging from 0.05 to 0.38. Estimating the combined heritability of multiple smoking characteristics, we calculate that at least 24% (95% confidence interval [CI] = 14% to 37%) and 7% (95% CI = 4% to 11%) of the heritability for lung and bladder cancer, respectively, can be attributed to genetic determinants of smoking. Most pairs of cancers studied did not show evidence of strong genetic correlation. We found only four pairs of cancers with marginally statistically significant correlations, specifically kidney and testes (rho = 0.73, SE = 0.28), diffuse large B-cell lymphoma (DLBCL) and pediatric osteosarcoma (rho = 0.53, SE = 0.21), DLBCL and chronic lymphocytic leukemia (CLL) (rho = 0.51, SE = 0.18), and bladder and lung (rho = 0.35, SE = 0.14). Correlation analysis also indicates that the genetic architecture of lung cancer differs between a smoking population of European ancestry and a nonsmoking Asian population, allowing for the possibility that the genetic etiology for the same disease can vary by population and environmental exposures. Conclusion: Our results provide important insights into the genetic architecture of cancers and suggest new avenues for investigation.
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| 2. |
- Glentis, George, et al.
(författare)
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Fast Implementation of SAR Imaging Using Sparse ML Methods
- 2013
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Ingår i: Signals, Systems and Computers, 2013 Asilomar Conference on. - 9781479923885 ; , s. 922-926
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Konferensbidrag (refereegranskat)abstract
- High-resolution sparse spectral estimation techniques have recently been shown to offer significant performance gains as compared to most conventional estimation approaches, although such methods typically suffer the drawback of being computationally cumbersome. In this paper, we seek to alleviate this drawback somewhat, examining computationally efficient implementations of the recent iterative sparse maximum likelihood-based approaches (SMLA), exploiting the inherent rich structure of these estimators. The derived implementations reduce the resulting computational complexity with at least one order of magnitude, while still yielding exact implementations. The effectiveness of the discussed techniques are illustrated using experimental examples.
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| 3. |
- Glentis, George-Othan, et al.
(författare)
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Non-Parametric High-Resolution SAR Imaging
- 2013
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Ingår i: IEEE Transactions on Signal Processing. - 1053-587X. ; 61:7, s. 1614-1624
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Tidskriftsartikel (refereegranskat)abstract
- The development of high-resolution two-dimensional spectral estimation techniques is of notable interest in synthetic aperture radar (SAR) imaging. Typically, data-independent techniques are exploited to form the SAR images, although such approaches will suffer from limited resolution and high sidelobe levels. Recent work on data-adaptive approaches have shown that both the iterative adaptive approach (IAA) and the sparse learning via iterative minimization (SLIM) algorithm offer excellent performance with high-resolution and low side lobe levels for both complete and incomplete data sets. Regrettably, both algorithms are computationally intensive if applied directly to the phase history data to form the SAR images. To help alleviate this, efficient implementations have also been proposed. In this paper, we further this work, proposing yet further improved implementation strategies, including approaches using the segmented IAA approach and the approximative quasi-Newton technique. Furthermore, we introduce a combined IAA-MAP algorithm as well as a hybrid IAA- and SLIM-based estimation scheme for SAR imaging. The effectiveness of the SAR imaging algorithms and the computational complexities of their fast implementations are demonstrated using the simulated Slicy data set and the experimentally measured GOTCHA data set.
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| 4. |
- Glentis, George-Othan, et al.
(författare)
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SAR Imaging via Efficient Implementations of Sparse ML Approaches
- 2014
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Ingår i: Signal Processing. - : Elsevier BV. - 0165-1684. ; 95:February, s. 15-26
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Tidskriftsartikel (refereegranskat)abstract
- High-resolution spectral estimation techniques are of notable interest for synthetic aperture radar (SAR) imaging. Several sparse estimation techniques have been shown to provide significant performance gains as compared to conventional approaches. We consider efficient implementation of the recent iterative sparse maximum likelihood-based approaches (SMLAs). Furthermore, we present approximative fast SMLA formulation using the Quasi-Newton approach, as well as consider hybrid SMLA-MAP algorithms. The effectiveness of the discussed techniques is illustrated using numerical and experimental examples.
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| 5. |
- Li, Ao, et al.
(författare)
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Genome architecture and selective signals compensatorily shape plastic response to a new environment
- 2023
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Ingår i: The Innovation. - 2666-6758. ; 4:4
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Tidskriftsartikel (refereegranskat)abstract
- Transcriptional plasticity interacts with natural selection in complex ways and is crucial for the survival of species under rapid climate change. How 3D genome architecture affects transcriptional plasticity and its interaction with genetic adaptation are unclear. We transplanted estuarine oysters to a new environment and found that genes located in active chromatin regions exhibited greater transcriptional plasticity, and changes in these regions were negatively correlated with selective signals. This indicates a trade-off be- tween 3D active regions and selective signals in shaping plastic responses to a new environment. Specifically, a mutation, lincRNA, and changes in the accessibility of a distal enhancer potentially affect its interaction with the ManIIa gene, which regulates the muscle function and survival of oysters. Our findings reveal that 3D genome architecture compensates for the role of genetic adaptation in environmental response to new environments and provide insights into synergetic genetic and epigenetic interactions critical for fitness-related trait and survival in a model marine species.
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| 6. |
- Ling, Jun, et al.
(författare)
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Multi-input multi-output underwater communications over sparse and frequency modulated acoustic channels
- 2011
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Ingår i: Journal of the Acoustical Society of America. - : Acoustical Society of America (ASA). - 0001-4966 .- 1520-8524. ; 130:1, s. 249-262
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Tidskriftsartikel (refereegranskat)abstract
- This paper addresses multi-input multi-output (MIMO) communications over sparse acoustic channels suffering from frequency modulations. An extension of the recently introduced SLIM algorithm, which stands for sparse learning via iterative minimization, is presented to estimate the sparse and frequency modulated acoustic channels. The extended algorithm is referred to as generalization of SLIM (GoSLIM). The sparseness is exploited through a hierarchical Bayesian model, and because GoSLIM is user parameter free, it is easy to use in practical applications. Moreover this paper considers channel equalization and symbol detection for various MIMO transmission schemes, including both space-time block coding and spatial multiplexing, under the challenging channel conditions. The effectiveness of the proposed approaches is demonstrated using in-water experimental measurements recently acquired during WHOI09 and ACOMM10 experiments.
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| 7. |
- Ling, Jun, et al.
(författare)
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On Bayesian channel estimation and FFT-based symbol detection in MIMO underwater acoustic communications
- 2014
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Ingår i: IEEE Journal of Oceanic Engineering. - 0364-9059 .- 1558-1691. ; 39:1, s. 59-73
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Tidskriftsartikel (refereegranskat)abstract
- Reliable channel estimation and effective interference cancellation are essential for enhancing the performance of multiple-input-multiple-output (MIMO) underwater acoustic communication (UAC) systems. In this paper, an efficient user-parameter-free Bayesian approach, referred to as sparse learning via iterative minimization (SLIM), is presented. SLIM provides good channel estimation performance along with reduced computational complexity compared to iterative adaptive approach (IAA). Moreover, RELAX-BLAST, which is a linear minimum mean-squared error (MMSE)-based symbol detection scheme, is implemented efficiently by making use of the conjugate gradient (CG) method and diagonalization properties of circulant matrices. The proposed algorithm requires only simple fast Fourier transform (FFT) operations and facilitates parallel implementations. These MIMO UAC techniques are evaluated using both simulated and in-water experimental examples. The 2008 Surface Processes and Acoustic Communications Experiment (SPACE08) experimental results show that the proposed MIMO UAC schemes can enjoy almost error-free performance even under severe ocean environments.
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| 8. |
- Lv, Fei, et al.
(författare)
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Ultraviolet-cured polyethylene oxide-based composite electrolyte enabling stable cycling of lithium battery at low temperature
- 2021
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Ingår i: Journal of Colloid and Interface Science. - : Elsevier. - 0021-9797 .- 1095-7103. ; 596, s. 257-266
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Tidskriftsartikel (refereegranskat)abstract
- The room and low-temperature performances of solid-state lithium batteries are crucial to expand their practical application. Polyethylene oxide (PEO) has received great attention as the most representative polymer electrolyte matrix. However, most PEO-based solid-state batteries need to operate at high temperature due to low room temperature ionic conductivity. Improving the ionic conductivity by adding plasticizers or reducing the crystallinity of PEO often compromises its mechanical strength. Here, an amorphous PEO-based composite solid-state electrolyte is obtained by ultraviolet (UV) polymerizing PEO and methacryloyloxypropyltrimethoxy silane (KH570)-modified SiO2 which demonstrates both satisfactory mechanical performance and high ionic conductivity at room (3.37 x 10(-4) S cm(-1)) and low temperatures (1.73 x 10(-4) S cm(-1) at 0 degrees C). In this electrolyte, the crystallinity of PEO is reduced through cross-linking, and therefore provides a fast Li+ ions transfer area. Moreover, the KH570-modified SiO2 inorganic particles promote the dissociation of lithium salts by Lewis acid centers to increase the ionic conductivity. Importantly, this kind of cross-linking networks endows the final electrolyte much higher mechanical strength than the pure PEO polymer electrolyte or PEO-inorganic filler blended systems. The solid-state LiFePO4/Li cell assembled with this electrolyte exhibits excellent cycling performance and high capacity at room and low temperatures.
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| 9. |
- Wang, Kui, et al.
(författare)
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Efficient electro-demulsification of O/W emulsions and simultaneous oil removal enabled by a multiscale porous biocarbon electrode
- 2024
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Ingår i: Chemical Engineering Journal. - : Elsevier BV. - 1385-8947 .- 1873-3212. ; 481
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Tidskriftsartikel (refereegranskat)abstract
- Emulsion wastewater contain substantial amounts of oil and various additives, which pose threats to the environment and human health. Demulsification is a crucial pretreatment stage for wastewater. This study aims to identify a novel electro-demulsification method with high oil removal efficiency and low energy consumption. Modified carbonized birch wood with a unique isotropic multiscale pore structure is used as a self-standing electrode to treat a toluene oil-in-water (O/W) emulsion. The electrode must have a highly porous structure to facilitate efficient water diffusion and oil adsorption. It must also have high electronic conductivity to expedite polarized molecular electrophoresis to realize penetration into the pores and, subsequently, demulsification. Guided by an applied electric field force, polarized O/W droplets are drawn toward the electrode, revealing electrical characteristics distinct from those of polarized organic molecules. This electric field force augments the capture and adhesion of droplets by the electric double layer at the electrode interface. Consequently, adsorbed droplets in close proximity to the electrode rupture due to the combined influence of the electric field force and the electrostatic effects stemming from the electrode's multiscale porous structure. This synergistic action enables demulsification to occur efficiently at low energy consumption levels. This study has revealed that electro-demulsification can effectively treat toluene emulsions stabilized by various surfactants and microemulsion containing toluene. Therefore, this electro-demulsification technology can be further developed for various types of water pollution.
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| 10. |
- Xu, Luzhou, et al.
(författare)
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Wideband source localization using sparse learning via iterative minimization
- 2013
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Ingår i: Signal Processing. - : Elsevier BV. - 0165-1684 .- 1872-7557. ; 93:12 SI, s. 3504-3514
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Tidskriftsartikel (refereegranskat)abstract
- In this paper, two extensions of the Sparse Learning via Iterative Minimization (SLIM) algorithm are presented for wideband source localization using a sensor array. The proposed methods exploit the joint sparse structure across all frequency bins, and estimate the spatial pseudo-spectra at various frequency bins jointly and iteratively. Via several numerical examples, we show that the proposed methods can provide high-resolution angle estimates and excellent sourcelocalization performance, and are able to resolve the left-right ambiguity problem, when used together with the vector sensor array technology.
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