Global α\alpha-decay study based on the mass table of the relativistic continuum Hartree-Bogoliubov theory

The $\alpha$-decay energies ($Q_\alpha$) are systematically investigated with the nuclear masses for $10 \leq Z \leq 120$ isotopes obtained by the relativistic continuum Hartree-Bogoliubov (RCHB) theory with the covariant density functional PC-PK1, and compared with available experimental values. It is found that the $\alpha$-decay energies deduced from the RCHB results present similar pattern as those from available experiments. Owing to the large predicted $Q_\alpha$ values ($\geq$ 4 MeV), many undiscovered heavy nuclei in the proton-rich side and super-heavy nuclei may have large possibilities for $\alpha$-decay. The influence of nuclear shell structure on $\alpha$-decay energies is also analysed.Comment: 7 pages, 4 figures. arXiv admin note: text overlap with arXiv:1309.3987 by other author

Lacustrine Turbidites from Tropical African Lakes as Indicators of Hydrologic and Climatic Changes

Flood-sourced turbidites (i.e. hyperpycnites) preserved in lake basins are proven indicators of hydrologic changes, yet their usefulness as recorders of tropical paleoclimate variability has long been overlooked. The primary focus of this dissertation research is to investigate the late Quaternary hydroclimatic changes in tropical Africa, using hyperpycnites, dated sediment cores, and high-resolution seismic reflection profiles from Lake Kivu in the East African Rift and Lake Bosumtwi in equatorial West Africa. A secondary focus of this dissertation is to image ancient turbidite systems of the Lake Albert rift in East Africa, using 2-D and 3-D seismic reflection data, and to assess the structural controls on turbidite sedimentation. Reoccurring megaturbidites (covering \u3e200 km2) over the past ~12 k.y. were revealed by integrating seismic reflection data and sediment core results from Lake Kivu, which is subject to potential limnic overturns and degassing events. Sedimentological evidence and seismic and lake-floor bathymetric data suggest that the turbidites were sourced by hyperpycnal river flows during exceptional floods. Time series of turbidite bed-thickness and accumulation rate were generated and compared with regional paleohydrologic records of tropical East Africa, and it is found that the temporal occurrence of the turbidites is climatically controlled. It is also suggested that extreme floods in Lake Kivu\u27s recent history may have triggered deep mixing events, and that potential geologic hazards associated with extraordinary turbidity currents may pose a risk to the current gas-extraction efforts in the lake. To further evaluate the effectiveness of lacustrine hyperpycnites as indicators of tropical African hydroclimatic changes, a 65 k.y. record of extreme hydrologic events in equatorial West Africa was reconstructed, using flood-sourced turbidites, seismic and sedimentological lake-level indicators, and paleohydrologic proxies, including total organic carbon and carbon isotopes, from the Lake Bosumtwi impact crater. Peak turbidite sedimentation is found to correlate with intervals of high TOC and markedly negative d13C values, suggesting that the turbidites were deposited during periods of high lake-levels. The multi-proxy paleohydrologic record from Lake Bosumtwi suggests that over the past 65 k.y., millennial-scale variability of hydrologic extremes in equatorial West Africa was linked to North Atlantic climate, with exceptional rainfall events linked to Dansgaard-Oeschger interstadials and megadrought events associated with slowdowns of the North Atlantic Meridional Overturning circulation during Heinrich stadials. Finally, 2-D and 3-D seismic reflection data from the Lake Albert Rift were analyzed to assess turbidite sedimentology in tectonically active rift lakes. Large channelized turbidite systems were observed and characterized in 3-D seismic data using seismic attribute analyses. In the absence of sediment failures and related mass transport deposits from the seismic record, it is postulated that the turbidites were sourced by hyperpycnal river flows during floods, and that there was a change in the sediment source of the turbidites, caused by drainage reversals due to rift shoulder uplift. Sediment dispersal pathways, changes in depositional facies, and evolution of the sublacustrine turbidite systems are largely controlled by syndepositional tectonism in that system

A novel method for multiple phenotype association studies based on genotype and phenotype network

Joint analysis of multiple correlated phenotypes for genome-wide association studies (GWAS) can identify and interpret pleiotropic loci which are essential to understand pleiotropy in diseases and complex traits. Meanwhile, constructing a network based on associations between phenotypes and genotypes provides a new insight to analyze multiple phenotypes, which can explore whether phenotypes and genotypes might be related to each other at a higher level of cellular and organismal organization. In this paper, we first develop a bipartite signed network by linking phenotypes and genotypes into a Genotype and Phenotype Network (GPN). The GPN can be constructed by a mixture of quantitative and qualitative phenotypes and is applicable to binary phenotypes with extremely unbalanced case-control ratios in large-scale biobank datasets. We then apply a powerful community detection method to partition phenotypes into disjoint network modules based on GPN. Finally, we jointly test the association between multiple phenotypes in a network module and a single nucleotide polymorphism (SNP). Simulations and analyses of 72 complex traits in the UK Biobank show that multiple phenotype association tests based on network modules detected by GPN are much more powerful than those without considering network modules. The newly proposed GPN provides a new insight to investigate the genetic architecture among different types of phenotypes. Multiple phenotypes association studies based on GPN are improved by incorporating the genetic information into the phenotype clustering. Notably, it might broaden the understanding of genetic architecture that exists between diagnoses, genes, and pleiotropy

Phototropic Multiresponsive Active Nanogels

Aqueous dispersions of nanogels that respond to switches in environmental pH and/or temperature by changes in their hydrodynamic radius (R-h) and/or zeta-potential are prepared by reversible addition-fragmentation chain-transfer (RAFT) polymerization-induced thermal (70 degrees C) self-assembly (PITSA) of N-isopropylacrylamide (NIPAM) in the presence of a poly(methacrylic acid) (PMAA)-substituted macromolecular chain transfer agent and a cross-linker. Photochromic spiropyran (SP) moieties are coupled to the carboxylic acid groups of the nanogels. Upon UV irradiation, the neutral SP isomerizes to the zwitterionic merocyanine (ME) form. Upon UV light irradiation, microgels formed by assembly of SP nanogels undergo a collective motion toward the UV-light source.Peer reviewe

Gene-based association tests using GWAS summary statistics and incorporating eQTL

Although genome-wide association studies (GWAS) have been successfully applied to a variety of complex diseases and identified many genetic variants underlying complex diseases via single marker tests, there is still a considerable heritability of complex diseases that could not be explained by GWAS. One alternative approach to overcome the missing heritability caused by genetic heterogeneity is gene-based analysis, which considers the aggregate effects of multiple genetic variants in a single test. Another alternative approach is transcriptome-wide association study (TWAS). TWAS aggregates genomic information into functionally relevant units that map to genes and their expression. TWAS is not only powerful, but can also increase the interpretability in biological mechanisms of identified trait associated genes. In this study, we propose a powerful and computationally efficient gene-based association test, called Overall. Using extended Simes procedure, Overall aggregates information from three types of traditional gene-based association tests and also incorporates expression quantitative trait locus (eQTL) information into a gene-based association test using GWAS summary statistics. We show that after a small number of replications to estimate the correlation among the integrated gene-based tests, the p values of Overall can be calculated analytically. Simulation studies show that Overall can control type I error rates very well and has higher power than the tests that we compared with. We also apply Overall to two schizophrenia GWAS summary datasets and two lipids GWAS summary datasets. The results show that this newly developed method can identify more significant genes than other methods we compared with

Risk assessment of subway station fire by using a Bayesian network-based scenario evolution model

Subway station fires frequently result in massive casualties, economic losses and even social panic due to the massive passenger flow, semiconfined space and limited conditions for escape and smoke emissions. The combination of different states of fire hazard factors increases the uncertainty and complexity of the evolution path of subway station fires and causes difficulty in assessing fire risk. Traditional methods cannot describe the development process of subway station fires, and thus, cannot assess fire risk under different fire scenarios. To realise scenario-based fire risk assessment, the elements that correspond to each scenario state during fire development in subway stations are identified in this study to explore the intrinsic driving force of fire evolution. Accordingly, a fire scenario evolution model of subway stations is constructed. Then, a Bayesian network is adopted to construct a scenario evolution probability calculation model for calculating the occurrence probability of each scenario state during subway station fire development and identifying critical scenario elements that promote fire evolution. Xi’an subway station system is used as a case to illustrate the application of Bayesian network-based scenario evolution model, providing a practical management tool for fire safety managers. The method adopted in this study enables managers to predict fire risk in each scenario and understand the evolution path of subway station fire, supporting the establishment of fire response strategies based on “scenario–response” planning.</p

Analysis of Multi-Element Blended Course Teaching and Learning Mode Based on Student-Centered Concept under the Perspective of “Internet+”

The integration of Internet and education has changed students’ learning environment and affected their learning behavior, which poses a greater challenge to the traditional teaching mode. Through the SWOT analysis of the “student centered” multi-element blended teaching mode in the era of “Internet + education”, it is concluded that the adaptability of learners themselves and the mismatch between teachers’ educational ideas and this teaching model delay the development of education to a certain extent. Some suggestions are put forward, such as strengthening the supervision and guidance, implementing the teaching and learning model scientifically, improving teachers’ ideology and comprehensive quality, and making full use of the characteristics of Internet opening, sharing and collaboration to construct the public service system and platform of national educational resources

A clustering linear combination method for multiple phenotype association studies based on GWAS summary statistics

There is strong evidence showing that joint analysis of multiple phenotypes in genome-wide association studies (GWAS) can increase statistical power when detecting the association between genetic variants and human complex diseases. We previously developed the Clustering Linear Combination (CLC) method and a computationally efficient CLC (ceCLC) method to test the association between multiple phenotypes and a genetic variant, which perform very well. However, both of these methods require individual-level genotypes and phenotypes that are often not easily accessible. In this research, we develop a novel method called sCLC for association studies of multiple phenotypes and a genetic variant based on GWAS summary statistics. We use the LD score regression to estimate the correlation matrix among phenotypes. The test statistic of sCLC is constructed by GWAS summary statistics and has an approximate Cauchy distribution. We perform a variety of simulation studies and compare sCLC with other commonly used methods for multiple phenotype association studies using GWAS summary statistics. Simulation results show that sCLC can control Type I error rates well and has the highest power in most scenarios. Moreover, we apply the newly developed method to the UK Biobank GWAS summary statistics from the XIII category with 70 related musculoskeletal system and connective tissue phenotypes. The results demonstrate that sCLC detects the most number of significant SNPs, and most of these identified SNPs can be matched to genes that have been reported in the GWAS catalog to be associated with those phenotypes. Furthermore, sCLC also identifies some novel signals that were missed by standard GWAS, which provide new insight into the potential genetic factors of the musculoskeletal system and connective tissue phenotypes