Impact of tree priors in species delimitation and phylogenetics of the genus Oligoryzomys (Rodentia: Cricetidae).

PubMed

da Cruz, Marcos de O R; Weksler, Marcelo

2018-02-01

The use of genetic data and tree-based algorithms to delimit evolutionary lineages is becoming an important practice in taxonomic identification, especially in morphologically cryptic groups. The effects of different phylogenetic and/or coalescent models in the analyses of species delimitation, however, are not clear. In this paper, we assess the impact of different evolutionary priors in phylogenetic estimation, species delimitation, and molecular dating of the genus Oligoryzomys (Mammalia: Rodentia), a group with complex taxonomy and morphological cryptic species. Phylogenetic and coalescent analyses included 20 of the 24 recognized species of the genus, comprising of 416 Cytochrome b sequences, 26 Cytochrome c oxidase I sequences, and 27 Beta-Fibrinogen Intron 7 sequences. For species delimitation, we employed the General Mixed Yule Coalescent (GMYC) and Bayesian Poisson tree processes (bPTP) analyses, and contrasted 4 genealogical and phylogenetic models: Pure-birth (Yule), Constant Population Size Coalescent, Multiple Species Coalescent, and a mixed Yule-Coalescent model. GMYC analyses of trees from different genealogical models resulted in similar species delimitation and phylogenetic relationships, with incongruence restricted to areas of poor nodal support. bPTP results, however, significantly differed from GMYC for 5 taxa. Oligoryzomys early diversification was estimated to have occurred in the Early Pleistocene, between 0.7 and 2.6 MYA. The mixed Yule-Coalescent model, however, recovered younger dating estimates for Oligoryzomys diversification, and for the threshold for the speciation-coalescent horizon in GMYC. Eight of the 20 included Oligoryzomys species were identified as having two or more independent evolutionary units, indicating that current taxonomy of Oligoryzomys is still unsettled. Copyright © 2017 Elsevier Inc. All rights reserved.

Parameter Estimation for Compact Binaries with Ground-Based Gravitational-Wave Observations Using the LALInference

NASA Technical Reports Server (NTRS)

Veitch, J.; Raymond, V.; Farr, B.; Farr, W.; Graff, P.; Vitale, S.; Aylott, B.; Blackburn, K.; Christensen, N.; Coughlin, M.

2015-01-01

The Advanced LIGO and Advanced Virgo gravitational wave (GW) detectors will begin operation in the coming years, with compact binary coalescence events a likely source for the first detections. The gravitational waveforms emitted directly encode information about the sources, including the masses and spins of the compact objects. Recovering the physical parameters of the sources from the GW observations is a key analysis task. This work describes the LALInference software library for Bayesian parameter estimation of compact binary signals, which builds on several previous methods to provide a well-tested toolkit which has already been used for several studies. We show that our implementation is able to correctly recover the parameters of compact binary signals from simulated data from the advanced GW detectors. We demonstrate this with a detailed comparison on three compact binary systems: a binary neutron star (BNS), a neutron star - black hole binary (NSBH) and a binary black hole (BBH), where we show a cross-comparison of results obtained using three independent sampling algorithms. These systems were analysed with non-spinning, aligned spin and generic spin configurations respectively, showing that consistent results can be obtained even with the full 15-dimensional parameter space of the generic spin configurations. We also demonstrate statistically that the Bayesian credible intervals we recover correspond to frequentist confidence intervals under correct prior assumptions by analysing a set of 100 signals drawn from the prior. We discuss the computational cost of these algorithms, and describe the general and problem-specific sampling techniques we have used to improve the efficiency of sampling the compact binary coalescence (CBC) parameter space.

Multilocus approach to clarify species status and the divergence history of the Bemisia tabaci (Hemiptera: Aleyrodidae) species complex.

PubMed

Hsieh, Chia-Hung; Ko, Chiun-Cheng; Chung, Cheng-Han; Wang, Hurng-Yi

2014-07-01

The sweet potato whitefly, Bemisia tabaci, is a highly differentiated species complex. Despite consisting of several morphologically indistinguishable entities and frequent invasions on all continents with important associated economic losses, the phylogenetic relationships, species status, and evolutionary history of this species complex is still debated. We sequenced and analyzed one mitochondrial and three single-copy nuclear genes from 9 of the 12 genetic groups of B. tabaci and 5 closely related species. Bayesian species delimitation was applied to investigate the speciation events of B. tabaci. The species statuses of the different genetic groups were strongly supported under different prior settings and phylogenetic scenarios. Divergence histories were estimated by a multispecies coalescence approach implemented in (*)BEAST. Based on mitochondrial locus, B. tabaci was originated 6.47 million years ago (MYA). Nevertheless, the time was 1.25MYA based on nuclear loci. According to the method of approximate Bayesian computation, this difference is probably due to different degrees of migration among loci; i.e., although the mitochondrial locus had differentiated, gene flow at nuclear loci was still possible, a scenario similar to parapatric mode of speciation. This is the first study in whiteflies using multilocus data and incorporating Bayesian coalescence approaches, both of which provide a more biologically realistic framework for delimiting species status and delineating the divergence history of B. tabaci. Our study illustrates that gene flow during species divergence should not be overlooked and has a great impact on divergence time estimation. Copyright © 2014 Elsevier Inc. All rights reserved.

Coalescent methods for estimating phylogenetic trees.

PubMed

Liu, Liang; Yu, Lili; Kubatko, Laura; Pearl, Dennis K; Edwards, Scott V

2009-10-01

We review recent models to estimate phylogenetic trees under the multispecies coalescent. Although the distinction between gene trees and species trees has come to the fore of phylogenetics, only recently have methods been developed that explicitly estimate species trees. Of the several factors that can cause gene tree heterogeneity and discordance with the species tree, deep coalescence due to random genetic drift in branches of the species tree has been modeled most thoroughly. Bayesian approaches to estimating species trees utilizes two likelihood functions, one of which has been widely used in traditional phylogenetics and involves the model of nucleotide substitution, and the second of which is less familiar to phylogeneticists and involves the probability distribution of gene trees given a species tree. Other recent parametric and nonparametric methods for estimating species trees involve parsimony criteria, summary statistics, supertree and consensus methods. Species tree approaches are an appropriate goal for systematics, appear to work well in some cases where concatenation can be misleading, and suggest that sampling many independent loci will be paramount. Such methods can also be challenging to implement because of the complexity of the models and computational time. In addition, further elaboration of the simplest of coalescent models will be required to incorporate commonly known issues such as deviation from the molecular clock, gene flow and other genetic forces.

Identifying the rooted species tree from the distribution of unrooted gene trees under the coalescent.

PubMed

Allman, Elizabeth S; Degnan, James H; Rhodes, John A

2011-06-01

Gene trees are evolutionary trees representing the ancestry of genes sampled from multiple populations. Species trees represent populations of individuals-each with many genes-splitting into new populations or species. The coalescent process, which models ancestry of gene copies within populations, is often used to model the probability distribution of gene trees given a fixed species tree. This multispecies coalescent model provides a framework for phylogeneticists to infer species trees from gene trees using maximum likelihood or Bayesian approaches. Because the coalescent models a branching process over time, all trees are typically assumed to be rooted in this setting. Often, however, gene trees inferred by traditional phylogenetic methods are unrooted. We investigate probabilities of unrooted gene trees under the multispecies coalescent model. We show that when there are four species with one gene sampled per species, the distribution of unrooted gene tree topologies identifies the unrooted species tree topology and some, but not all, information in the species tree edges (branch lengths). The location of the root on the species tree is not identifiable in this situation. However, for 5 or more species with one gene sampled per species, we show that the distribution of unrooted gene tree topologies identifies the rooted species tree topology and all its internal branch lengths. The length of any pendant branch leading to a leaf of the species tree is also identifiable for any species from which more than one gene is sampled.

Gravitational waves: search results, data analysis and parameter estimation: Amaldi 10 Parallel session C2.

PubMed

Astone, Pia; Weinstein, Alan; Agathos, Michalis; Bejger, Michał; Christensen, Nelson; Dent, Thomas; Graff, Philip; Klimenko, Sergey; Mazzolo, Giulio; Nishizawa, Atsushi; Robinet, Florent; Schmidt, Patricia; Smith, Rory; Veitch, John; Wade, Madeline; Aoudia, Sofiane; Bose, Sukanta; Calderon Bustillo, Juan; Canizares, Priscilla; Capano, Colin; Clark, James; Colla, Alberto; Cuoco, Elena; Da Silva Costa, Carlos; Dal Canton, Tito; Evangelista, Edgar; Goetz, Evan; Gupta, Anuradha; Hannam, Mark; Keitel, David; Lackey, Benjamin; Logue, Joshua; Mohapatra, Satyanarayan; Piergiovanni, Francesco; Privitera, Stephen; Prix, Reinhard; Pürrer, Michael; Re, Virginia; Serafinelli, Roberto; Wade, Leslie; Wen, Linqing; Wette, Karl; Whelan, John; Palomba, C; Prodi, G

The Amaldi 10 Parallel Session C2 on gravitational wave (GW) search results, data analysis and parameter estimation included three lively sessions of lectures by 13 presenters, and 34 posters. The talks and posters covered a huge range of material, including results and analysis techniques for ground-based GW detectors, targeting anticipated signals from different astrophysical sources: compact binary inspiral, merger and ringdown; GW bursts from intermediate mass binary black hole mergers, cosmic string cusps, core-collapse supernovae, and other unmodeled sources; continuous waves from spinning neutron stars; and a stochastic GW background. There was considerable emphasis on Bayesian techniques for estimating the parameters of coalescing compact binary systems from the gravitational waveforms extracted from the data from the advanced detector network. This included methods to distinguish deviations of the signals from what is expected in the context of General Relativity.

Gravitational Waves: Search Results, Data Analysis and Parameter Estimation. Amaldi 10 Parallel Session C2

NASA Technical Reports Server (NTRS)

Astone, Pia; Weinstein, Alan; Agathos, Michalis; Bejger, Michal; Christensen, Nelson; Dent, Thomas; Graff, Philip; Klimenko, Sergey; Mazzolo, Giulio; Nishizawa, Atsushi

2015-01-01

The Amaldi 10 Parallel Session C2 on gravitational wave(GW) search results, data analysis and parameter estimation included three lively sessions of lectures by 13 presenters, and 34 posters. The talks and posters covered a huge range of material, including results and analysis techniques for ground-based GW detectors, targeting anticipated signals from different astrophysical sources: compact binary inspiral, merger and ringdown; GW bursts from intermediate mass binary black hole mergers, cosmic string cusps, core-collapse supernovae, and other unmodeled sources; continuous waves from spinning neutron stars; and a stochastic GW background. There was considerable emphasis on Bayesian techniques for estimating the parameters of coalescing compact binary systems from the gravitational waveforms extracted from the data from the advanced detector network. This included methods to distinguish deviations of the signals from what is expected in the context of General Relativity.

Cross-Border Sexual Transmission of the Newly Emerging HIV-1 Clade CRF51_01B

PubMed Central

Cheong, Hui Ting; Ng, Kim Tien; Ong, Lai Yee; Chook, Jack Bee; Chan, Kok Gan; Takebe, Yutaka; Kamarulzaman, Adeeba; Tee, Kok Keng

2014-01-01

A novel HIV-1 recombinant clade (CRF51_01B) was recently identified among men who have sex with men (MSM) in Singapore. As cases of sexually transmitted HIV-1 infection increase concurrently in two socioeconomically intimate countries such as Malaysia and Singapore, cross transmission of HIV-1 between said countries is highly probable. In order to investigate the timeline for the emergence of HIV-1 CRF51_01B in Singapore and its possible introduction into Malaysia, 595 HIV-positive subjects recruited in Kuala Lumpur from 2008 to 2012 were screened. Phylogenetic relationship of 485 amplified polymerase gene sequences was determined through neighbour-joining method. Next, near-full length sequences were amplified for genomic sequences inferred to be CRF51_01B and subjected to further analysis implemented through Bayesian Markov chain Monte Carlo (MCMC) sampling and maximum likelihood methods. Based on the near full length genomes, two isolates formed a phylogenetic cluster with CRF51_01B sequences of Singapore origin, sharing identical recombination structure. Spatial and temporal information from Bayesian MCMC coalescent and maximum likelihood analysis of the protease, gp120 and gp41 genes suggest that Singapore is probably the country of origin of CRF51_01B (as early as in the mid-1990s) and featured a Malaysian who acquired the infection through heterosexual contact as host for its ancestral lineages. CRF51_01B then spread rapidly among the MSM in Singapore and Malaysia. Although the importation of CRF51_01B from Singapore to Malaysia is supported by coalescence analysis, the narrow timeframe of the transmission event indicates a closely linked epidemic. Discrepancies in the estimated divergence times suggest that CRF51_01B may have arisen through multiple recombination events from more than one parental lineage. We report the cross transmission of a novel CRF51_01B lineage between countries that involved different sexual risk groups. Understanding the cross-border transmission of HIV-1 involving sexual networks is crucial for effective intervention strategies in the region. PMID:25340817

Cross-border sexual transmission of the newly emerging HIV-1 clade CRF51_01B.

PubMed

Cheong, Hui Ting; Ng, Kim Tien; Ong, Lai Yee; Chook, Jack Bee; Chan, Kok Gan; Takebe, Yutaka; Kamarulzaman, Adeeba; Tee, Kok Keng

2014-01-01

A novel HIV-1 recombinant clade (CRF51_01B) was recently identified among men who have sex with men (MSM) in Singapore. As cases of sexually transmitted HIV-1 infection increase concurrently in two socioeconomically intimate countries such as Malaysia and Singapore, cross transmission of HIV-1 between said countries is highly probable. In order to investigate the timeline for the emergence of HIV-1 CRF51_01B in Singapore and its possible introduction into Malaysia, 595 HIV-positive subjects recruited in Kuala Lumpur from 2008 to 2012 were screened. Phylogenetic relationship of 485 amplified polymerase gene sequences was determined through neighbour-joining method. Next, near-full length sequences were amplified for genomic sequences inferred to be CRF51_01B and subjected to further analysis implemented through Bayesian Markov chain Monte Carlo (MCMC) sampling and maximum likelihood methods. Based on the near full length genomes, two isolates formed a phylogenetic cluster with CRF51_01B sequences of Singapore origin, sharing identical recombination structure. Spatial and temporal information from Bayesian MCMC coalescent and maximum likelihood analysis of the protease, gp120 and gp41 genes suggest that Singapore is probably the country of origin of CRF51_01B (as early as in the mid-1990s) and featured a Malaysian who acquired the infection through heterosexual contact as host for its ancestral lineages. CRF51_01B then spread rapidly among the MSM in Singapore and Malaysia. Although the importation of CRF51_01B from Singapore to Malaysia is supported by coalescence analysis, the narrow timeframe of the transmission event indicates a closely linked epidemic. Discrepancies in the estimated divergence times suggest that CRF51_01B may have arisen through multiple recombination events from more than one parental lineage. We report the cross transmission of a novel CRF51_01B lineage between countries that involved different sexual risk groups. Understanding the cross-border transmission of HIV-1 involving sexual networks is crucial for effective intervention strategies in the region.

Influence of gene flow on divergence dating - implications for the speciation history of Takydromus grass lizards.

PubMed

Tseng, Shu-Ping; Li, Shou-Hsien; Hsieh, Chia-Hung; Wang, Hurng-Yi; Lin, Si-Min

2014-10-01

Dating the time of divergence and understanding speciation processes are central to the study of the evolutionary history of organisms but are notoriously difficult. The difficulty is largely rooted in variations in the ancestral population size or in the genealogy variation across loci. To depict the speciation processes and divergence histories of three monophyletic Takydromus species endemic to Taiwan, we sequenced 20 nuclear loci and combined with one mitochondrial locus published in GenBank. They were analysed by a multispecies coalescent approach within a Bayesian framework. Divergence dating based on the gene tree approach showed high variation among loci, and the divergence was estimated at an earlier date than when derived by the species-tree approach. To test whether variations in the ancestral population size accounted for the majority of this variation, we conducted computer inferences using isolation-with-migration (IM) and approximate Bayesian computation (ABC) frameworks. The results revealed that gene flow during the early stage of speciation was strongly favoured over the isolation model, and the initiation of the speciation process was far earlier than the dates estimated by gene- and species-based divergence dating. Due to their limited dispersal ability, it is suggested that geographical isolation may have played a major role in the divergence of these Takydromus species. Nevertheless, this study reveals a more complex situation and demonstrates that gene flow during the speciation process cannot be overlooked and may have a great impact on divergence dating. By using multilocus data and incorporating Bayesian coalescence approaches, we provide a more biologically realistic framework for delineating the divergence history of Takydromus. © 2014 John Wiley & Sons Ltd.

Phylogenetic Analysis and Epidemic History of Hepatitis C Virus Genotype 2 in Tunisia, North Africa

PubMed Central

Rajhi, Mouna; Ghedira, Kais; Chouikha, Anissa; Djebbi, Ahlem; Cheikh, Imed; Ben Yahia, Ahlem; Sadraoui, Amel; Hammami, Walid; Azouz, Msaddek; Ben Mami, Nabil; Triki, Henda

2016-01-01

HCV genotype 2 (HCV-2) has a worldwide distribution with prevalence rates that vary from country to country. High genetic diversity and long-term endemicity were suggested in West African countries. A global dispersal of HCV-2 would have occurred during the 20th century, especially in European countries. In Tunisia, genotype 2 was the second prevalent genotype after genotype 1 and most isolates belong to subtypes 2c and 2k. In this study, phylogenetic analyses based on the NS5B genomic sequences of 113 Tunisian HCV isolates from subtypes 2c and 2k were carried out. A Bayesian coalescent-based framework was used to estimate the origin and the spread of these subtypes circulating in Tunisia. Phylogenetic analyses of HCV-2c sequences suggest the absence of country-specific or time-specific variants. In contrast, the phylogenetic grouping of HCV-2k sequences shows the existence of two major genetic clusters that may represent two distinct circulating variants. Coalescent analysis indicated a most recent common ancestor (tMRCA) of Tunisian HCV-2c around 1886 (1869–1902) before the introduction of HCV-2k in 1901 (1867–1931). Our findings suggest that the introduction of HCV-2c in Tunisia is possibly a result of population movements between Tunisia and European population following the French colonization. PMID:27100294

Phylogenetic Analysis and Epidemic History of Hepatitis C Virus Genotype 2 in Tunisia, North Africa.

PubMed

Rajhi, Mouna; Ghedira, Kais; Chouikha, Anissa; Djebbi, Ahlem; Cheikh, Imed; Ben Yahia, Ahlem; Sadraoui, Amel; Hammami, Walid; Azouz, Msaddek; Ben Mami, Nabil; Triki, Henda

2016-01-01

HCV genotype 2 (HCV-2) has a worldwide distribution with prevalence rates that vary from country to country. High genetic diversity and long-term endemicity were suggested in West African countries. A global dispersal of HCV-2 would have occurred during the 20th century, especially in European countries. In Tunisia, genotype 2 was the second prevalent genotype after genotype 1 and most isolates belong to subtypes 2c and 2k. In this study, phylogenetic analyses based on the NS5B genomic sequences of 113 Tunisian HCV isolates from subtypes 2c and 2k were carried out. A Bayesian coalescent-based framework was used to estimate the origin and the spread of these subtypes circulating in Tunisia. Phylogenetic analyses of HCV-2c sequences suggest the absence of country-specific or time-specific variants. In contrast, the phylogenetic grouping of HCV-2k sequences shows the existence of two major genetic clusters that may represent two distinct circulating variants. Coalescent analysis indicated a most recent common ancestor (tMRCA) of Tunisian HCV-2c around 1886 (1869-1902) before the introduction of HCV-2k in 1901 (1867-1931). Our findings suggest that the introduction of HCV-2c in Tunisia is possibly a result of population movements between Tunisia and European population following the French colonization.

Reconstruction of a windborne insect invasion using a particle dispersal model, historical wind data, and Bayesian analysis of genetic data

PubMed Central

Lander, Tonya A; Klein, Etienne K; Oddou-Muratorio, Sylvie; Candau, Jean-Noël; Gidoin, Cindy; Chalon, Alain; Roig, Anne; Fallour, Delphine; Auger-Rozenberg, Marie-Anne; Boivin, Thomas

2014-01-01

Understanding how invasive species establish and spread is vital for developing effective management strategies for invaded areas and identifying new areas where the risk of invasion is highest. We investigated the explanatory power of dispersal histories reconstructed based on local-scale wind data and a regional-scale wind-dispersed particle trajectory model for the invasive seed chalcid wasp Megastigmus schimitscheki (Hymenoptera: Torymidae) in France. The explanatory power was tested by: (1) survival analysis of empirical data on M. schimitscheki presence, absence and year of arrival at 52 stands of the wasp's obligate hosts, Cedrus (true cedar trees); and (2) Approximate Bayesian analysis of M. schimitscheki genetic data using a coalescence model. The Bayesian demographic modeling and traditional population genetic analysis suggested that initial invasion across the range was the result of long-distance dispersal from the longest established sites. The survival analyses of the windborne expansion patterns derived from a particle dispersal model indicated that there was an informative correlation between the M. schimitscheki presence/absence data from the annual surveys and the scenarios based on regional-scale wind data. These three very different analyses produced highly congruent results supporting our proposal that wind is the most probable vector for passive long-distance dispersal of this invasive seed wasp. This result confirms that long-distance dispersal from introduction areas is a likely driver of secondary expansion of alien invasive species. Based on our results, management programs for this and other windborne invasive species may consider (1) focusing effort at the longest established sites and (2) monitoring outlying populations remains critically important due to their influence on rates of spread. We also suggest that there is a distinct need for new analysis methods that have the capacity to combine empirical spatiotemporal field data, genetic data, and environmental data to investigate dispersal and invasion. PMID:25558356

Indigenous Wildlife Rabies in Taiwan: Ferret Badgers, a Long Term Terrestrial Reservoir.

PubMed

Lan, Yu-Ching; Wen, Tzai-Hung; Chang, Chao-Chin; Liu, Hsin-Fu; Lee, Pei-Fen; Huang, Chung-Yuan; Chomel, Bruno B; Chen, Yi-Ming A

2017-01-01

The emerging disease of rabies was confirmed in Taiwan ferret badgers (FBs) and reported to the World Organization for Animal Health (OIE) on July 17, 2013. The spread of wildlife rabies can be related to neighborhood countries in Asia. The phylogenetic analysis was conducted by maximum likelihood (ML) methods and the Bayesian coalescent approach based on the glycoprotein (G) and nucleoprotein (N) genes. The phylogeographic and spatial temporal dynamics of viral transmission were determined by using SPREAD, QGIS. Therefore, the origin and the change with time of the viruses can be identified. Results showed the rabies virus of FB strains in Taiwan is a unique clade among other strains in Asia. According to the phylogeographic coalescent tree, three major genotypes of the FB rabies virus have circulated in three different geographical areas in Taiwan. Two genotypes have distributed into central and southern Taiwan between two ecological river barriers. The third genotype has been limited in southeastern Taiwan by the natural mountain barrier. The diversity of FB rabies viruses indicates that the biological profile of FBs could vary in different geographical areas in Taiwan. An enhanced surveillance system needs to be established near the currently identified natural barriers for early warnings of the rabies virus outbreak in Taiwan.

Indigenous Wildlife Rabies in Taiwan: Ferret Badgers, a Long Term Terrestrial Reservoir

PubMed Central

Wen, Tzai-Hung; Liu, Hsin-Fu; Lee, Pei-Fen; Chomel, Bruno B.

2017-01-01

The emerging disease of rabies was confirmed in Taiwan ferret badgers (FBs) and reported to the World Organization for Animal Health (OIE) on July 17, 2013. The spread of wildlife rabies can be related to neighborhood countries in Asia. The phylogenetic analysis was conducted by maximum likelihood (ML) methods and the Bayesian coalescent approach based on the glycoprotein (G) and nucleoprotein (N) genes. The phylogeographic and spatial temporal dynamics of viral transmission were determined by using SPREAD, QGIS. Therefore, the origin and the change with time of the viruses can be identified. Results showed the rabies virus of FB strains in Taiwan is a unique clade among other strains in Asia. According to the phylogeographic coalescent tree, three major genotypes of the FB rabies virus have circulated in three different geographical areas in Taiwan. Two genotypes have distributed into central and southern Taiwan between two ecological river barriers. The third genotype has been limited in southeastern Taiwan by the natural mountain barrier. The diversity of FB rabies viruses indicates that the biological profile of FBs could vary in different geographical areas in Taiwan. An enhanced surveillance system needs to be established near the currently identified natural barriers for early warnings of the rabies virus outbreak in Taiwan. PMID:28497055

Assessing Species Boundaries Using Multilocus Species Delimitation in a Morphologically Conserved Group of Neotropical Freshwater Fishes, the Poecilia sphenops Species Complex (Poeciliidae)

PubMed Central

Bagley, Justin C.; Alda, Fernando; Breitman, M. Florencia; Bermingham, Eldredge; van den Berghe, Eric P.; Johnson, Jerald B.

2015-01-01

Accurately delimiting species is fundamentally important for understanding species diversity and distributions and devising effective strategies to conserve biodiversity. However, species delimitation is problematic in many taxa, including ‘non-adaptive radiations’ containing morphologically cryptic lineages. Fortunately, coalescent-based species delimitation methods hold promise for objectively estimating species limits in such radiations, using multilocus genetic data. Using coalescent-based approaches, we delimit species and infer evolutionary relationships in a morphologically conserved group of Central American freshwater fishes, the Poecilia sphenops species complex. Phylogenetic analyses of multiple genetic markers (sequences of two mitochondrial DNA genes and five nuclear loci) from 10/15 species and genetic lineages recognized in the group support the P. sphenops species complex as monophyletic with respect to outgroups, with eight mitochondrial ‘major-lineages’ diverged by ≥2% pairwise genetic distances. From general mixed Yule-coalescent models, we discovered (conservatively) 10 species within our concatenated mitochondrial DNA dataset, 9 of which were strongly supported by subsequent multilocus Bayesian species delimitation and species tree analyses. Results suggested species-level diversity is underestimated or overestimated by at least ~15% in different lineages in the complex. Nonparametric statistics and coalescent simulations indicate genealogical discordance among our gene tree results has mainly derived from interspecific hybridization in the nuclear genome. However, mitochondrial DNA show little evidence for introgression, and our species delimitation results appear robust to effects of this process. Overall, our findings support the utility of combining multiple lines of genetic evidence and broad phylogeographical sampling to discover and validate species using coalescent-based methods. Our study also highlights the importance of testing for hybridization versus incomplete lineage sorting, which aids inference of not only species limits but also evolutionary processes influencing genetic diversity. PMID:25849959

Assessing species boundaries using multilocus species delimitation in a morphologically conserved group of neotropical freshwater fishes, the Poecilia sphenops species complex (Poeciliidae).

PubMed

Bagley, Justin C; Alda, Fernando; Breitman, M Florencia; Bermingham, Eldredge; van den Berghe, Eric P; Johnson, Jerald B

2015-01-01

Accurately delimiting species is fundamentally important for understanding species diversity and distributions and devising effective strategies to conserve biodiversity. However, species delimitation is problematic in many taxa, including 'non-adaptive radiations' containing morphologically cryptic lineages. Fortunately, coalescent-based species delimitation methods hold promise for objectively estimating species limits in such radiations, using multilocus genetic data. Using coalescent-based approaches, we delimit species and infer evolutionary relationships in a morphologically conserved group of Central American freshwater fishes, the Poecilia sphenops species complex. Phylogenetic analyses of multiple genetic markers (sequences of two mitochondrial DNA genes and five nuclear loci) from 10/15 species and genetic lineages recognized in the group support the P. sphenops species complex as monophyletic with respect to outgroups, with eight mitochondrial 'major-lineages' diverged by ≥2% pairwise genetic distances. From general mixed Yule-coalescent models, we discovered (conservatively) 10 species within our concatenated mitochondrial DNA dataset, 9 of which were strongly supported by subsequent multilocus Bayesian species delimitation and species tree analyses. Results suggested species-level diversity is underestimated or overestimated by at least ~15% in different lineages in the complex. Nonparametric statistics and coalescent simulations indicate genealogical discordance among our gene tree results has mainly derived from interspecific hybridization in the nuclear genome. However, mitochondrial DNA show little evidence for introgression, and our species delimitation results appear robust to effects of this process. Overall, our findings support the utility of combining multiple lines of genetic evidence and broad phylogeographical sampling to discover and validate species using coalescent-based methods. Our study also highlights the importance of testing for hybridization versus incomplete lineage sorting, which aids inference of not only species limits but also evolutionary processes influencing genetic diversity.

Wright-Fisher diffusion bridges.

PubMed

Griffiths, Robert C; Jenkins, Paul A; Spanò, Dario

2017-10-06

The trajectory of the frequency of an allele which begins at x at time 0 and is known to have frequency z at time T can be modelled by the bridge process of the Wright-Fisher diffusion. Bridges when x=z=0 are particularly interesting because they model the trajectory of the frequency of an allele which appears at a time, then is lost by random drift or mutation after a time T. The coalescent genealogy back in time of a population in a neutral Wright-Fisher diffusion process is well understood. In this paper we obtain a new interpretation of the coalescent genealogy of the population in a bridge from a time t∈(0,T). In a bridge with allele frequencies of 0 at times 0 and T the coalescence structure is that the population coalesces in two directions from t to 0 and t to T such that there is just one lineage of the allele under consideration at times 0 and T. The genealogy in Wright-Fisher diffusion bridges with selection is more complex than in the neutral model, but still with the property of the population branching and coalescing in two directions from time t∈(0,T). The density of the frequency of an allele at time t is expressed in a way that shows coalescence in the two directions. A new algorithm for exact simulation of a neutral Wright-Fisher bridge is derived. This follows from knowing the density of the frequency in a bridge and exact simulation from the Wright-Fisher diffusion. The genealogy of the neutral Wright-Fisher bridge is also modelled by branching Pólya urns, extending a representation in a Wright-Fisher diffusion. This is a new very interesting representation that relates Wright-Fisher bridges to classical urn models in a Bayesian setting. Copyright © 2017 Elsevier Inc. All rights reserved.

Reconstructing gravitational wave source parameters via direct comparisons to numerical relativity II: Applications

NASA Astrophysics Data System (ADS)

O'Shaughnessy, Richard; Lange, Jacob; Healy, James; Carlos, Lousto; Shoemaker, Deirdre; Lovelace, Geoffrey; Scheel, Mark

2016-03-01

In this talk, we apply a procedure to reconstruct the parameters of sufficiently massive coalescing compact binaries via direct comparison with numerical relativity simulations. We illustrate how to use only comparisons between synthetic data and these simulations to reconstruct properties of a synthetic candidate source. We demonstrate using selected examples that we can reconstruct posterior distributions obtained by other Bayesian methods with our sparse grid. We describe how followup simulations can corroborate and improve our understanding of a candidate signal.

Approximate Bayesian estimation of extinction rate in the Finnish Daphnia magna metapopulation.

PubMed

Robinson, John D; Hall, David W; Wares, John P

2013-05-01

Approximate Bayesian computation (ABC) is useful for parameterizing complex models in population genetics. In this study, ABC was applied to simultaneously estimate parameter values for a model of metapopulation coalescence and test two alternatives to a strict metapopulation model in the well-studied network of Daphnia magna populations in Finland. The models shared four free parameters: the subpopulation genetic diversity (θS), the rate of gene flow among patches (4Nm), the founding population size (N0) and the metapopulation extinction rate (e) but differed in the distribution of extinction rates across habitat patches in the system. The three models had either a constant extinction rate in all populations (strict metapopulation), one population that was protected from local extinction (i.e. a persistent source), or habitat-specific extinction rates drawn from a distribution with specified mean and variance. Our model selection analysis favoured the model including a persistent source population over the two alternative models. Of the closest 750,000 data sets in Euclidean space, 78% were simulated under the persistent source model (estimated posterior probability = 0.769). This fraction increased to more than 85% when only the closest 150,000 data sets were considered (estimated posterior probability = 0.774). Approximate Bayesian computation was then used to estimate parameter values that might produce the observed set of summary statistics. Our analysis provided posterior distributions for e that included the point estimate obtained from previous data from the Finnish D. magna metapopulation. Our results support the use of ABC and population genetic data for testing the strict metapopulation model and parameterizing complex models of demography. © 2013 Blackwell Publishing Ltd.

Phylogenetic analysis at deep timescales: unreliable gene trees, bypassed hidden support, and the coalescence/concatalescence conundrum.

PubMed

Gatesy, John; Springer, Mark S

2014-11-01

Large datasets are required to solve difficult phylogenetic problems that are deep in the Tree of Life. Currently, two divergent systematic methods are commonly applied to such datasets: the traditional supermatrix approach (= concatenation) and "shortcut" coalescence (= coalescence methods wherein gene trees and the species tree are not co-estimated). When applied to ancient clades, these contrasting frameworks often produce congruent results, but in recent phylogenetic analyses of Placentalia (placental mammals), this is not the case. A recent series of papers has alternatively disputed and defended the utility of shortcut coalescence methods at deep phylogenetic scales. Here, we examine this exchange in the context of published phylogenomic data from Mammalia; in particular we explore two critical issues - the delimitation of data partitions ("genes") in coalescence analysis and hidden support that emerges with the combination of such partitions in phylogenetic studies. Hidden support - increased support for a clade in combined analysis of all data partitions relative to the support evident in separate analyses of the various data partitions, is a hallmark of the supermatrix approach and a primary rationale for concatenating all characters into a single matrix. In the most extreme cases of hidden support, relationships that are contradicted by all gene trees are supported when all of the genes are analyzed together. A valid fear is that shortcut coalescence methods might bypass or distort character support that is hidden in individual loci because small gene fragments are analyzed in isolation. Given the extensive systematic database for Mammalia, the assumptions and applicability of shortcut coalescence methods can be assessed with rigor to complement a small but growing body of simulation work that has directly compared these methods to concatenation. We document several remarkable cases of hidden support in both supermatrix and coalescence paradigms and argue that in most instances, the emergent support in the shortcut coalescence analyses is an artifact. By referencing rigorous molecular clock studies of Mammalia, we suggest that inaccurate gene trees that imply unrealistically deep coalescences debilitate shortcut coalescence analyses of the placental dataset. We document contradictory coalescence results for Placentalia, and outline a critical conundrum that challenges the general utility of shortcut coalescence methods at deep phylogenetic scales. In particular, the basic unit of analysis in coalescence analysis, the coalescence-gene, is expected to shrink in size as more taxa are analyzed, but as the amount of data for reconstruction of a gene tree ratchets downward, the number of nodes in the gene tree that need to be resolved ratchets upward. Some advocates of shortcut coalescence methods have attempted to address problems with inaccurate gene trees by concatenating multiple coalescence-genes to yield "gene trees" that better match the species tree. However, this hybrid concatenation/coalescence approach, "concatalescence," contradicts the most basic biological rationale for performing a coalescence analysis in the first place. We discuss this reality in the context of recent simulation work that also suggests inaccurate reconstruction of gene trees is more problematic for shortcut coalescence methods than deep coalescence of independently segregating loci is for concatenation methods. Copyright © 2014 Elsevier Inc. All rights reserved.

Automating approximate Bayesian computation by local linear regression.

PubMed

Thornton, Kevin R

2009-07-07

In several biological contexts, parameter inference often relies on computationally-intensive techniques. "Approximate Bayesian Computation", or ABC, methods based on summary statistics have become increasingly popular. A particular flavor of ABC based on using a linear regression to approximate the posterior distribution of the parameters, conditional on the summary statistics, is computationally appealing, yet no standalone tool exists to automate the procedure. Here, I describe a program to implement the method. The software package ABCreg implements the local linear-regression approach to ABC. The advantages are: 1. The code is standalone, and fully-documented. 2. The program will automatically process multiple data sets, and create unique output files for each (which may be processed immediately in R), facilitating the testing of inference procedures on simulated data, or the analysis of multiple data sets. 3. The program implements two different transformation methods for the regression step. 4. Analysis options are controlled on the command line by the user, and the program is designed to output warnings for cases where the regression fails. 5. The program does not depend on any particular simulation machinery (coalescent, forward-time, etc.), and therefore is a general tool for processing the results from any simulation. 6. The code is open-source, and modular.Examples of applying the software to empirical data from Drosophila melanogaster, and testing the procedure on simulated data, are shown. In practice, the ABCreg simplifies implementing ABC based on local-linear regression.

A multilocus evaluation of ermine (Mustela erminea) across the Holarctic, testing hypotheses of Pleistocene diversification in response to climate change

USGS Publications Warehouse

Dawson, Natalie G.; Hope, Andrew G.; Talbot, Sandra L.; Cook, Joseph A.

2013-01-01

Aim: We examined data for ermine (Mustela erminea) to test two sets of diversification hypotheses concerning the number and location of late Pleistocene refugia, the timing and mode of diversification, and the evolutionary influence of insularization. Location: Temperate and sub-Arctic Northern Hemisphere. Methods: We used up to two mitochondrial and four nuclear loci from 237 specimens for statistical phylogeographical and demographic analyses. Coalescent species-tree estimation used a Bayesian approach for clade divergence based on external mutation rate calibrations. Approximate Bayesian methods were used to assess population size, timing of divergence and gene flow. Results: Limited structure coupled with evidence of population growth across broad regions, including previously ice-covered areas, indicated expansion from multiple centres of differentiation, but high endemism along the North Pacific coast (NPC). A bifurcating model of diversification with recent growth spanning three glacial cycles best explained the empirical data. Main conclusions: A newly identified clade in North America indicated a fourth refugial area for ermine. The shallow coalescence of all extant ermine reflects a recent history of diversification overlying a deeper fossil record. Post-glacial colonization has led to potential contact zones for multiple lineages in north-western North America. A model of diversification of ermine accompanied by recent gene flow was marginally less well supported than a model of divergence of major clades in response to the most recent glacial cycles.

High endemism at cave entrances: a case study of spiders of the genus Uthina

PubMed Central

Yao, Zhiyuan; Dong, Tingting; Zheng, Guo; Fu, Jinzhong; Li, Shuqiang

2016-01-01

Endemism, which is typically high on islands and in caves, has rarely been studied in the cave entrance ecotone. We investigated the endemism of the spider genus Uthina at cave entrances. Totally 212 spiders were sampled from 46 localities, from Seychelles across Southeast Asia to Fiji. They mostly occur at cave entrances but occasionally appear at various epigean environments. Phylogenetic analysis of DNA sequence data from COI and 28S genes suggested that Uthina was grouped into 13 well-supported clades. We used three methods, the Bayesian Poisson Tree Processes (bPTP) model, the Bayesian Phylogenetics and Phylogeography (BPP) method, and the general mixed Yule coalescent (GMYC) model, to investigate species boundaries. Both bPTP and BPP identified the 13 clades as 13 separate species, while GMYC identified 19 species. Furthermore, our results revealed high endemism at cave entrances. Of the 13 provisional species, twelve (one known and eleven new) are endemic to one or a cluster of caves, and all of them occurred only at cave entrances except for one population of one species. The only widely distributed species, U. luzonica, mostly occurred in epigean environments while three populations were found at cave entrances. Additionally, eleven new species of the genus are described. PMID:27775081

Evolutionary history and dynamics of dog rabies virus in western and central Africa.

PubMed

Talbi, Chiraz; Holmes, Edward C; de Benedictis, Paola; Faye, Ousmane; Nakouné, Emmanuel; Gamatié, Djibo; Diarra, Abass; Elmamy, Bezeid Ould; Sow, Adama; Adjogoua, Edgard Valery; Sangare, Oumou; Dundon, William G; Capua, Ilaria; Sall, Amadou A; Bourhy, Hervé

2009-04-01

The burden of rabies in Africa is estimated at 24,000 human deaths year(-1), almost all of which result from infection with dog rabies viruses (RABV). To investigate the evolutionary dynamics of RABV in western and central Africa, 92 isolates sampled from 27 African countries over 29 years were collected and sequenced. This revealed that RABV currently circulating in dogs in this region fell into a single lineage designated 'Africa 2'. A detailed analysis of the phylogeographical structure of this Africa 2 lineage revealed strong population subdivision at the country level, with only limited movement of virus among localities, including a possible east-to-west spread across Africa. In addition, Bayesian coalescent analysis suggested that the Africa 2 lineage was introduced into this region of Africa only recently (probably <200 years ago), in accordance with the timescale of expanding European colonial influence and urbanization, and then spread relatively slowly, perhaps occupying the entire region in a 100 year period.

Species trees for the tree swallows (Genus Tachycineta): an alternative phylogenetic hypothesis to the mitochondrial gene tree.

PubMed

Dor, Roi; Carling, Matthew D; Lovette, Irby J; Sheldon, Frederick H; Winkler, David W

2012-10-01

The New World swallow genus Tachycineta comprises nine species that collectively have a wide geographic distribution and remarkable variation both within- and among-species in ecologically important traits. Existing phylogenetic hypotheses for Tachycineta are based on mitochondrial DNA sequences, thus they provide estimates of a single gene tree. In this study we sequenced multiple individuals from each species at 16 nuclear intron loci. We used gene concatenated approaches (Bayesian and maximum likelihood) as well as coalescent-based species tree inference to reconstruct phylogenetic relationships of the genus. We examined the concordance and conflict between the nuclear and mitochondrial trees and between concatenated and coalescent-based inferences. Our results provide an alternative phylogenetic hypothesis to the existing mitochondrial DNA estimate of phylogeny. This new hypothesis provides a more accurate framework in which to explore trait evolution and examine the evolution of the mitochondrial genome in this group. Copyright © 2012 Elsevier Inc. All rights reserved.

Can the Site-Frequency Spectrum Distinguish Exponential Population Growth from Multiple-Merger Coalescents?

PubMed Central

Eldon, Bjarki; Birkner, Matthias; Blath, Jochen; Freund, Fabian

2015-01-01

The ability of the site-frequency spectrum (SFS) to reflect the particularities of gene genealogies exhibiting multiple mergers of ancestral lines as opposed to those obtained in the presence of population growth is our focus. An excess of singletons is a well-known characteristic of both population growth and multiple mergers. Other aspects of the SFS, in particular, the weight of the right tail, are, however, affected in specific ways by the two model classes. Using an approximate likelihood method and minimum-distance statistics, our estimates of statistical power indicate that exponential and algebraic growth can indeed be distinguished from multiple-merger coalescents, even for moderate sample sizes, if the number of segregating sites is high enough. A normalized version of the SFS (nSFS) is also used as a summary statistic in an approximate Bayesian computation (ABC) approach. The results give further positive evidence as to the general eligibility of the SFS to distinguish between the different histories. PMID:25575536

Toward a DNA Taxonomy of Alpine Rhithrogena (Ephemeroptera: Heptageniidae) Using a Mixed Yule-Coalescent Analysis of Mitochondrial and Nuclear DNA

PubMed Central

Vuataz, Laurent; Sartori, Michel; Wagner, André; Monaghan, Michael T.

2011-01-01

Aquatic larvae of many Rhithrogena mayflies (Ephemeroptera) inhabit sensitive Alpine environments. A number of species are on the IUCN Red List and many recognized species have restricted distributions and are of conservation interest. Despite their ecological and conservation importance, ambiguous morphological differences among closely related species suggest that the current taxonomy may not accurately reflect the evolutionary diversity of the group. Here we examined the species status of nearly 50% of European Rhithrogena diversity using a widespread sampling scheme of Alpine species that included 22 type localities, general mixed Yule-coalescent (GMYC) model analysis of one standard mtDNA marker and one newly developed nDNA marker, and morphological identification where possible. Using sequences from 533 individuals from 144 sampling localities, we observed significant clustering of the mitochondrial (cox1) marker into 31 GMYC species. Twenty-one of these could be identified based on the presence of topotypes (expertly identified specimens from the species' type locality) or unambiguous morphology. These results strongly suggest the presence of both cryptic diversity and taxonomic oversplitting in Rhithrogena. Significant clustering was not detected with protein-coding nuclear PEPCK, although nine GMYC species were congruent with well supported terminal clusters of nDNA. Lack of greater congruence in the two data sets may be the result of incomplete sorting of ancestral polymorphism. Bayesian phylogenetic analyses of both gene regions recovered four of the six recognized Rhithrogena species groups in our samples as monophyletic. Future development of more nuclear markers would facilitate multi-locus analysis of unresolved, closely related species pairs. The DNA taxonomy developed here lays the groundwork for a future revision of the important but cryptic Rhithrogena genus in Europe. PMID:21611178

Origin of Clothing Lice Indicates Early Clothing Use by Anatomically Modern Humans in Africa

PubMed Central

Toups, Melissa A.; Kitchen, Andrew; Light, Jessica E.; Reed, David L.

2011-01-01

Clothing use is an important modern behavior that contributed to the successful expansion of humans into higher latitudes and cold climates. Previous research suggests that clothing use originated anywhere between 40,000 and 3 Ma, though there is little direct archaeological, fossil, or genetic evidence to support more specific estimates. Since clothing lice evolved from head louse ancestors once humans adopted clothing, dating the emergence of clothing lice may provide more specific estimates of the origin of clothing use. Here, we use a Bayesian coalescent modeling approach to estimate that clothing lice diverged from head louse ancestors at least by 83,000 and possibly as early as 170,000 years ago. Our analysis suggests that the use of clothing likely originated with anatomically modern humans in Africa and reinforces a broad trend of modern human developments in Africa during the Middle to Late Pleistocene. PMID:20823373

On incomplete sampling under birth-death models and connections to the sampling-based coalescent.

PubMed

Stadler, Tanja

2009-11-07

The constant rate birth-death process is used as a stochastic model for many biological systems, for example phylogenies or disease transmission. As the biological data are usually not fully available, it is crucial to understand the effect of incomplete sampling. In this paper, we analyze the constant rate birth-death process with incomplete sampling. We derive the density of the bifurcation events for trees on n leaves which evolved under this birth-death-sampling process. This density is used for calculating prior distributions in Bayesian inference programs and for efficiently simulating trees. We show that the birth-death-sampling process can be interpreted as a birth-death process with reduced rates and complete sampling. This shows that joint inference of birth rate, death rate and sampling probability is not possible. The birth-death-sampling process is compared to the sampling-based population genetics model, the coalescent. It is shown that despite many similarities between these two models, the distribution of bifurcation times remains different even in the case of very large population sizes. We illustrate these findings on an Hepatitis C virus dataset from Egypt. We show that the transmission times estimates are significantly different-the widely used Gamma statistic even changes its sign from negative to positive when switching from the coalescent to the birth-death process.

Coalescent-Based Analyses of Genomic Sequence Data Provide a Robust Resolution of Phylogenetic Relationships among Major Groups of Gibbons

PubMed Central

Shi, Cheng-Min; Yang, Ziheng

2018-01-01

Abstract The phylogenetic relationships among extant gibbon species remain unresolved despite numerous efforts using morphological, behavorial, and genetic data and the sequencing of whole genomes. A major challenge in reconstructing the gibbon phylogeny is the radiative speciation process, which resulted in extremely short internal branches in the species phylogeny and extensive incomplete lineage sorting with extensive gene-tree heterogeneity across the genome. Here, we analyze two genomic-scale data sets, with ∼10,000 putative noncoding and exonic loci, respectively, to estimate the species tree for the major groups of gibbons. We used the Bayesian full-likelihood method bpp under the multispecies coalescent model, which naturally accommodates incomplete lineage sorting and uncertainties in the gene trees. For comparison, we included three heuristic coalescent-based methods (mp-est, SVDQuartets, and astral) as well as concatenation. From both data sets, we infer the phylogeny for the four extant gibbon genera to be (Hylobates, (Nomascus, (Hoolock, Symphalangus))). We used simulation guided by the real data to evaluate the accuracy of the methods used. Astral, while not as efficient as bpp, performed well in estimation of the species tree even in presence of excessive incomplete lineage sorting. Concatenation, mp-est and SVDQuartets were unreliable when the species tree contains very short internal branches. Likelihood ratio test of gene flow suggests a small amount of migration from Hylobates moloch to H. pileatus, while cross-genera migration is absent or rare. Our results highlight the utility of coalescent-based methods in addressing challenging species tree problems characterized by short internal branches and rampant gene tree-species tree discordance. PMID:29087487

Rapid molecular evolution of human bocavirus revealed by Bayesian coalescent inference.

PubMed

Zehender, Gianguglielmo; De Maddalena, Chiara; Canuti, Marta; Zappa, Alessandra; Amendola, Antonella; Lai, Alessia; Galli, Massimo; Tanzi, Elisabetta

2010-03-01

Human bocavirus (HBoV) is a linear single-stranded DNA virus belonging to the Parvoviridae family that has recently been isolated from the upper respiratory tract of children with acute respiratory infection. All of the strains observed so far segregate into two genotypes (1 and 2) with a low level of polymorphism. Given the recent description of the infection and the lack of epidemiological and molecular data, we estimated the virus's rates of molecular evolution and population dynamics. A dataset of forty-nine dated VP2 sequences, including also eight new isolates obtained from pharyngeal swabs of Italian patients with acute respiratory tract infections, was submitted to phylogenetic analysis. The model parameters, evolutionary rates and population dynamics were co-estimated using a Bayesian Markov Chain Monte Carlo approach, and site-specific positive and negative selection was also investigated. Recombination was investigated by seven different methods and one suspected recombinant strain was excluded from further analysis. The estimated mean evolutionary rate of HBoV was 8.6x10(-4)subs/site/year, and that of the 1st+2nd codon positions was more than 15 times less than that of the 3rd codon position. Viral population dynamics analysis revealed that the two known genotypes diverged recently (mean tMRCA: 24 years), and that the epidemic due to HBoV genotype 2 grew exponentially at a rate of 1.01year(-1). Selection analysis of the partial VP2 showed that 8.5% of sites were under significant negative pressure and the absence of positive selection. Our results show that, like other parvoviruses, HBoV is characterised by a rapid evolution. The low level of polymorphism is probably due to a relatively recent divergence between the circulating genotypes and strong purifying selection acting on viral antigens.

Coalescence computations for large samples drawn from populations of time-varying sizes

PubMed Central

Polanski, Andrzej; Szczesna, Agnieszka; Garbulowski, Mateusz; Kimmel, Marek

2017-01-01

We present new results concerning probability distributions of times in the coalescence tree and expected allele frequencies for coalescent with large sample size. The obtained results are based on computational methodologies, which involve combining coalescence time scale changes with techniques of integral transformations and using analytical formulae for infinite products. We show applications of the proposed methodologies for computing probability distributions of times in the coalescence tree and their limits, for evaluation of accuracy of approximate expressions for times in the coalescence tree and expected allele frequencies, and for analysis of large human mitochondrial DNA dataset. PMID:28170404

Measuring neutron star tidal deformability with Advanced LIGO: A Bayesian analysis of neutron star-black hole binary observations

NASA Astrophysics Data System (ADS)

Kumar, Prayush; Pürrer, Michael; Pfeiffer, Harald P.

2017-02-01

The pioneering discovery of gravitational waves (GWs) by Advanced LIGO has ushered us into an era of observational GW astrophysics. Compact binaries remain the primary target sources for GW observation, of which neutron star-black hole (NSBH) binaries form an important subset. GWs from NSBH sources carry signatures of (a) the tidal distortion of the neutron star by its companion black hole during inspiral, and (b) its potential tidal disruption near merger. In this paper, we present a Bayesian study of the measurability of neutron star tidal deformability ΛNS∝(R /M )NS5 using observation(s) of inspiral-merger GW signals from disruptive NSBH coalescences, taking into account the crucial effect of black hole spins. First, we find that if nontidal templates are used to estimate source parameters for an NSBH signal, the bias introduced in the estimation of nontidal physical parameters will only be significant for loud signals with signal-to-noise ratios greater than ≃30 . For similarly loud signals, we also find that we can begin to put interesting constraints on ΛNS (factor of 1-2) with individual observations. Next, we study how a population of realistic NSBH detections will improve our measurement of neutron star tidal deformability. For an astrophysically likely population of disruptive NSBH coalescences, we find that 20-35 events are sufficient to constrain ΛNS within ±25 %- 50 % , depending on the neutron star equation of state. For these calculations we assume that LIGO will detect black holes with masses within the astrophysical mass gap. In case the mass gap remains preserved in NSBHs detected by LIGO, we estimate that approximately 25% additional detections will furnish comparable ΛNS measurement accuracy. In both cases, we find that it is the loudest 5-10 events that provide most of the tidal information, and not the combination of tens of low-SNR events, thereby facilitating targeted numerical-GR follow-ups of NSBHs. We find these results encouraging, and recommend that an effort to measure ΛNS be planned for upcoming NSBH observations with the LIGO-Virgo instruments.

Integrated Taxonomy and DNA Barcoding of Alpine Midges (Diptera: Chironomidae)

PubMed Central

Montagna, Matteo; Mereghetti, Valeria; Lencioni, Valeria; Rossaro, Bruno

2016-01-01

Rapid and efficient DNA-based tools are recommended for the evaluation of the insect biodiversity of high-altitude streams. In the present study, focused principally on larvae of the genus Diamesa Meigen 1835 (Diptera: Chironomidae), the congruence between morphological/molecular delimitation of species as well as performances in taxonomic assignments were evaluated. A fragment of the mitochondrial cox1 gene was obtained from 112 larvae, pupae and adults (Diamesinae, Orthocladiinae and Tanypodinae) that were collected in different mountain regions of the Alps and Apennines. On the basis of morphological characters 102 specimens were attributed to 16 species, and the remaining ten specimens were identified to the genus level. Molecular species delimitation was performed using: i) distance-based Automatic Barcode Gap Discovery (ABGD), with no a priori assumptions on species identification; and ii) coalescent tree-based approaches as the Generalized Mixed Yule Coalescent model, its Bayesian implementation and Bayesian Poisson Tree Processes. The ABGD analysis, estimating an optimal intra/interspecific nucleotide distance threshold of 0.7%-1.4%, identified 23 putative species; the tree-based approaches, identified between 25–26 entities, provided nearly identical results. All species belonging to zernyi, steinboecki, latitarsis, bertrami, dampfi and incallida groups, as well as outgroup species, are recovered as separate entities, perfectly matching the identified morphospecies. In contrast, within the cinerella group, cases of discrepancy arose: i) the two morphologically separate species D. cinerella and D. tonsa are neither monophyletic nor diagnosable exhibiting low values of between-taxa nucleotide mean divergence (0.94%); ii) few cases of larvae morphological misidentification were observed. Head capsule color is confirmed to be a valid character able to discriminate larvae of D. zernyi, D. tonsa and D. cinerella, but it is here better defined as a color gradient between the setae submenti and genal setae. DNA barcodes performances were high: average accuracy was ~89% and precision of ~99%. On the basis of the present data, we can thus conclude that molecular identification represents a promising tool that could be effectively adopted in evaluating biodiversity of high-altitude streams. PMID:26938660

Integrated Taxonomy and DNA Barcoding of Alpine Midges (Diptera: Chironomidae).

PubMed

Montagna, Matteo; Mereghetti, Valeria; Lencioni, Valeria; Rossaro, Bruno

2016-01-01

Rapid and efficient DNA-based tools are recommended for the evaluation of the insect biodiversity of high-altitude streams. In the present study, focused principally on larvae of the genus Diamesa Meigen 1835 (Diptera: Chironomidae), the congruence between morphological/molecular delimitation of species as well as performances in taxonomic assignments were evaluated. A fragment of the mitochondrial cox1 gene was obtained from 112 larvae, pupae and adults (Diamesinae, Orthocladiinae and Tanypodinae) that were collected in different mountain regions of the Alps and Apennines. On the basis of morphological characters 102 specimens were attributed to 16 species, and the remaining ten specimens were identified to the genus level. Molecular species delimitation was performed using: i) distance-based Automatic Barcode Gap Discovery (ABGD), with no a priori assumptions on species identification; and ii) coalescent tree-based approaches as the Generalized Mixed Yule Coalescent model, its Bayesian implementation and Bayesian Poisson Tree Processes. The ABGD analysis, estimating an optimal intra/interspecific nucleotide distance threshold of 0.7%-1.4%, identified 23 putative species; the tree-based approaches, identified between 25-26 entities, provided nearly identical results. All species belonging to zernyi, steinboecki, latitarsis, bertrami, dampfi and incallida groups, as well as outgroup species, are recovered as separate entities, perfectly matching the identified morphospecies. In contrast, within the cinerella group, cases of discrepancy arose: i) the two morphologically separate species D. cinerella and D. tonsa are neither monophyletic nor diagnosable exhibiting low values of between-taxa nucleotide mean divergence (0.94%); ii) few cases of larvae morphological misidentification were observed. Head capsule color is confirmed to be a valid character able to discriminate larvae of D. zernyi, D. tonsa and D. cinerella, but it is here better defined as a color gradient between the setae submenti and genal setae. DNA barcodes performances were high: average accuracy was ~89% and precision of ~99%. On the basis of the present data, we can thus conclude that molecular identification represents a promising tool that could be effectively adopted in evaluating biodiversity of high-altitude streams.

Inferences about binary stellar populations using gravitational wave observations

NASA Astrophysics Data System (ADS)

Wysocki, Daniel; Gerosa, Davide; O'Shaughnessy, Richard; Belczynski, Krzysztof; Gladysz, Wojciech; Berti, Emanuele; Kesden, Michael; Holz, Daniel

2018-01-01

With the dawn of gravitational wave astronomy, enabled by the LIGO and Virgo interferometers, we now have a new window into the Universe. In the short time these detectors have been in use, multiple confirmed detections of gravitational waves from compact binary coalescences have been made. Stellar binary systems are one of the likely progenitors of the observed compact binary sources. If this is indeed the case, then we can use measured properties of these binary systems to learn about their progenitors. We will discuss the Bayesian framework in which we make these inferences, and results which include mass and spin distributions.

Challenges in Species Tree Estimation Under the Multispecies Coalescent Model

PubMed Central

Xu, Bo; Yang, Ziheng

2016-01-01

The multispecies coalescent (MSC) model has emerged as a powerful framework for inferring species phylogenies while accounting for ancestral polymorphism and gene tree-species tree conflict. A number of methods have been developed in the past few years to estimate the species tree under the MSC. The full likelihood methods (including maximum likelihood and Bayesian inference) average over the unknown gene trees and accommodate their uncertainties properly but involve intensive computation. The approximate or summary coalescent methods are computationally fast and are applicable to genomic datasets with thousands of loci, but do not make an efficient use of information in the multilocus data. Most of them take the two-step approach of reconstructing the gene trees for multiple loci by phylogenetic methods and then treating the estimated gene trees as observed data, without accounting for their uncertainties appropriately. In this article we review the statistical nature of the species tree estimation problem under the MSC, and explore the conceptual issues and challenges of species tree estimation by focusing mainly on simple cases of three or four closely related species. We use mathematical analysis and computer simulation to demonstrate that large differences in statistical performance may exist between the two classes of methods. We illustrate that several counterintuitive behaviors may occur with the summary methods but they are due to inefficient use of information in the data by summary methods and vanish when the data are analyzed using full-likelihood methods. These include (i) unidentifiability of parameters in the model, (ii) inconsistency in the so-called anomaly zone, (iii) singularity on the likelihood surface, and (iv) deterioration of performance upon addition of more data. We discuss the challenges and strategies of species tree inference for distantly related species when the molecular clock is violated, and highlight the need for improving the computational efficiency and model realism of the likelihood methods as well as the statistical efficiency of the summary methods. PMID:27927902

Population dynamics and in vitro antibody pressure of porcine parvovirus indicate a decrease in variability.

PubMed

Streck, André Felipe; Homeier, Timo; Foerster, Tessa; Truyen, Uwe

2013-09-01

To estimate the impact of porcine parvovirus (PPV) vaccines on the emergence of new phenotypes, the population dynamic history of the virus was calculated using the Bayesian Markov chain Monte Carlo method with a Bayesian skyline coalescent model. Additionally, an in vitro model was performed with consecutive passages of the 'Challenge' strain (a virulent field strain) and NADL2 strain (a vaccine strain) in a PK-15 cell line supplemented with polyclonal antibodies raised against the vaccine strain. A decrease in genetic diversity was observed in the presence of antibodies in vitro or after vaccination (as estimated by the in silico model). We hypothesized that the antibodies induced a selective pressure that may reduce the incidence of neutral selection, which should play a major role in the emergence of new mutations. In this scenario, vaccine failures and non-vaccinated populations (e.g. wild boars) may have an important impact in the emergence of new phenotypes.

Estimating mutation parameters, population history and genealogy simultaneously from temporally spaced sequence data.

PubMed Central

Drummond, Alexei J; Nicholls, Geoff K; Rodrigo, Allen G; Solomon, Wiremu

2002-01-01

Molecular sequences obtained at different sampling times from populations of rapidly evolving pathogens and from ancient subfossil and fossil sources are increasingly available with modern sequencing technology. Here, we present a Bayesian statistical inference approach to the joint estimation of mutation rate and population size that incorporates the uncertainty in the genealogy of such temporally spaced sequences by using Markov chain Monte Carlo (MCMC) integration. The Kingman coalescent model is used to describe the time structure of the ancestral tree. We recover information about the unknown true ancestral coalescent tree, population size, and the overall mutation rate from temporally spaced data, that is, from nucleotide sequences gathered at different times, from different individuals, in an evolving haploid population. We briefly discuss the methodological implications and show what can be inferred, in various practically relevant states of prior knowledge. We develop extensions for exponentially growing population size and joint estimation of substitution model parameters. We illustrate some of the important features of this approach on a genealogy of HIV-1 envelope (env) partial sequences. PMID:12136032

Estimating mutation parameters, population history and genealogy simultaneously from temporally spaced sequence data.

PubMed

Drummond, Alexei J; Nicholls, Geoff K; Rodrigo, Allen G; Solomon, Wiremu

2002-07-01

Molecular sequences obtained at different sampling times from populations of rapidly evolving pathogens and from ancient subfossil and fossil sources are increasingly available with modern sequencing technology. Here, we present a Bayesian statistical inference approach to the joint estimation of mutation rate and population size that incorporates the uncertainty in the genealogy of such temporally spaced sequences by using Markov chain Monte Carlo (MCMC) integration. The Kingman coalescent model is used to describe the time structure of the ancestral tree. We recover information about the unknown true ancestral coalescent tree, population size, and the overall mutation rate from temporally spaced data, that is, from nucleotide sequences gathered at different times, from different individuals, in an evolving haploid population. We briefly discuss the methodological implications and show what can be inferred, in various practically relevant states of prior knowledge. We develop extensions for exponentially growing population size and joint estimation of substitution model parameters. We illustrate some of the important features of this approach on a genealogy of HIV-1 envelope (env) partial sequences.

Genetic divergence and phylogeographic history of two closely related species (Leucomeris decora and Nouelia insignis) across the 'Tanaka Line' in Southwest China.

PubMed

Zhao, Yu-Juan; Gong, Xun

2015-07-08

Leucomeris decora and Nouelia insignis (Asteraceae) are narrowly and allopatrically distributed species, separated by the important biogeographic boundary Tanaka Line in Southwest China. Previous morphological, cytogenetic and molecular studies suggested that L. decora is sister to N. insignis. However, it is less clear how the two species diverged, whether in full isolation or occurring gene flow across the Tanaka Line. Here, we performed a molecular study at the population level to characterize genetic differentiation and decipher phylogeographic history in two closely related species based on variation examined in plastid and nuclear DNAs using a coalescent-based approach. These morphologically distinct species share plastid DNA (cpDNA) haplotypes. In contrast, Bayesian analysis of nuclear DNA (nDNA) uncovered two distinct clusters corresponding to L. decora and N. insignis. Based on the IMa analysis, no strong indication of migration was detected based on both cpDNA and nDNA sequences. The molecular data pointed to a major west-east split in nuclear DNA between the two species corresponding with the Tanaka Line. The coalescent time estimate for all cpDNA haplotypes dated to the Mid-Late Pleistocene. The estimated demographic parameters showed that the population size of L. decora was similar to that of N. insignis and both experienced limited demographic fluctuations recently. The study revealed comprehensive species divergence and phylogeographic histories of N. insignis and L. decora divided by the Tanaka Line. The phylogeographic pattern inferred from cpDNA reflected ancestrally shared polymorphisms without post-divergence gene flow between species. The marked genealogical lineage divergence in nDNA provided some indication of Tanaka Line for its role as a barrier to plant dispersal, and lent support to its importance in promoting strong population structure and allopatric divergence.

Molecular characterization and epidemic history of hepatitis C virus using core sequences of isolates from Central Province, Saudi Arabia.

PubMed

Shier, Medhat K; Iles, James C; El-Wetidy, Mohammad S; Ali, Hebatallah H; Al Qattan, Mohammad M

2017-01-01

The source of HCV transmission in Saudi Arabia is unknown. This study aimed to determine HCV genotypes in a representative sample of chronically infected patients in Saudi Arabia. All HCV isolates were genotyped and subtyped by sequencing of the HCV core region and 54 new HCV isolates were identified. Three sets of primers targeting the core region were used for both amplification and sequencing of all isolates resulting in a 326 bp fragment. Most HCV isolates were genotype 4 (85%), whereas only a few isolates were recognized as genotype 1 (15%). With the assistance of Genbank database and BLAST, subtyping results showed that most of genotype 4 isolates were 4d whereas most of genotype 1 isolates were 1b. Nucleotide conservation and variation rates of HCV core sequences showed that 4a and 1b have the highest levels of variation. Phylogenetic analysis of sequences by Maximum Likelihood and Bayesian Coalescent methods was used to explore the source of HCV transmission by investigating the relationship between Saudi Arabia and other countries in the Middle East and Africa. Coalescent analysis showed that transmissions of HCV from Egypt to Saudi Arabia are estimated to have occurred in three major clusters: 4d was introduced into the country before 1900, the major 4a clade's MRCA was introduced between 1900 and 1920, and the remaining lineages were introduced between 1940 and 1960 from Egypt and Middle Africa. Results showed that no lineages seem to have crossed from Egypt to Saudi Arabia in the last 15 years. Finally, sequencing and characterization of new HCV isolates from Saudi Arabia will enrich the HCV database and help further studies related to treatment and management of the virus.

Molecular characterization and epidemic history of hepatitis C virus using core sequences of isolates from Central Province, Saudi Arabia

PubMed Central

Iles, James C.; El-Wetidy, Mohammad S.; Ali, Hebatallah H.; Al Qattan, Mohammad M.

2017-01-01

The source of HCV transmission in Saudi Arabia is unknown. This study aimed to determine HCV genotypes in a representative sample of chronically infected patients in Saudi Arabia. All HCV isolates were genotyped and subtyped by sequencing of the HCV core region and 54 new HCV isolates were identified. Three sets of primers targeting the core region were used for both amplification and sequencing of all isolates resulting in a 326 bp fragment. Most HCV isolates were genotype 4 (85%), whereas only a few isolates were recognized as genotype 1 (15%). With the assistance of Genbank database and BLAST, subtyping results showed that most of genotype 4 isolates were 4d whereas most of genotype 1 isolates were 1b. Nucleotide conservation and variation rates of HCV core sequences showed that 4a and 1b have the highest levels of variation. Phylogenetic analysis of sequences by Maximum Likelihood and Bayesian Coalescent methods was used to explore the source of HCV transmission by investigating the relationship between Saudi Arabia and other countries in the Middle East and Africa. Coalescent analysis showed that transmissions of HCV from Egypt to Saudi Arabia are estimated to have occurred in three major clusters: 4d was introduced into the country before 1900, the major 4a clade’s MRCA was introduced between 1900 and 1920, and the remaining lineages were introduced between 1940 and 1960 from Egypt and Middle Africa. Results showed that no lineages seem to have crossed from Egypt to Saudi Arabia in the last 15 years. Finally, sequencing and characterization of new HCV isolates from Saudi Arabia will enrich the HCV database and help further studies related to treatment and management of the virus. PMID:28863156

Epidemic history of hepatitis C virus infection in two remote communities in Nigeria, West Africa.

PubMed

Forbi, Joseph C; Purdy, Michael A; Campo, David S; Vaughan, Gilberto; Dimitrova, Zoya E; Ganova-Raeva, Lilia M; Xia, Guo-Liang; Khudyakov, Yury E

2012-07-01

We investigated the molecular epidemiology and population dynamics of HCV infection among indigenes of two semi-isolated communities in North-Central Nigeria. Despite remoteness and isolation, ~15% of the population had serological or molecular markers of hepatitis C virus (HCV) infection. Phylogenetic analysis of the NS5b sequences obtained from 60 HCV-infected residents showed that HCV variants belonged to genotype 1 (n=51; 85%) and genotype 2 (n=9; 15%). All sequences were unique and intermixed in the phylogenetic tree with HCV sequences from people infected from other West African countries. The high-throughput 454 pyrosequencing of the HCV hypervariable region 1 and an empirical threshold error correction algorithm were used to evaluate intra-host heterogeneity of HCV strains of genotype 1 (n=43) and genotype 2 (n=6) from residents of the communities. Analysis revealed a rare detectable intermixing of HCV intra-host variants among residents. Identification of genetically close HCV variants among all known groups of relatives suggests a common intra-familial HCV transmission in the communities. Applying Bayesian coalescent analysis to the NS5b sequences, the most recent common ancestors for genotype 1 and 2 variants were estimated to have existed 675 and 286 years ago, respectively. Bayesian skyline plots suggest that HCV lineages of both genotypes identified in the Nigerian communities experienced epidemic growth for 200-300 years until the mid-20th century. The data suggest a massive introduction of numerous HCV variants to the communities during the 20th century in the background of a dynamic evolutionary history of the hepatitis C epidemic in Nigeria over the past three centuries.

Insights into the phylogeny of Northern Hemisphere Armillaria: Neighbor-net and Bayesian analyses of translation elongation factor 1-α gene sequences.

PubMed

Klopfenstein, Ned B; Stewart, Jane E; Ota, Yuko; Hanna, John W; Richardson, Bryce A; Ross-Davis, Amy L; Elías-Román, Rubén D; Korhonen, Kari; Keča, Nenad; Iturritxa, Eugenia; Alvarado-Rosales, Dionicio; Solheim, Halvor; Brazee, Nicholas J; Łakomy, Piotr; Cleary, Michelle R; Hasegawa, Eri; Kikuchi, Taisei; Garza-Ocañas, Fortunato; Tsopelas, Panaghiotis; Rigling, Daniel; Prospero, Simone; Tsykun, Tetyana; Bérubé, Jean A; Stefani, Franck O P; Jafarpour, Saeideh; Antonín, Vladimír; Tomšovský, Michal; McDonald, Geral I; Woodward, Stephen; Kim, Mee-Sook

2017-01-01

Armillaria possesses several intriguing characteristics that have inspired wide interest in understanding phylogenetic relationships within and among species of this genus. Nuclear ribosomal DNA sequence-based analyses of Armillaria provide only limited information for phylogenetic studies among widely divergent taxa. More recent studies have shown that translation elongation factor 1-α (tef1) sequences are highly informative for phylogenetic analysis of Armillaria species within diverse global regions. This study used Neighbor-net and coalescence-based Bayesian analyses to examine phylogenetic relationships of newly determined and existing tef1 sequences derived from diverse Armillaria species from across the Northern Hemisphere, with Southern Hemisphere Armillaria species included for reference. Based on the Bayesian analysis of tef1 sequences, Armillaria species from the Northern Hemisphere are generally contained within the following four superclades, which are named according to the specific epithet of the most frequently cited species within the superclade: (i) Socialis/Tabescens (exannulate) superclade including Eurasian A. ectypa, North American A. socialis (A. tabescens), and Eurasian A. socialis (A. tabescens) clades; (ii) Mellea superclade including undescribed annulate North American Armillaria sp. (Mexico) and four separate clades of A. mellea (Europe and Iran, eastern Asia, and two groups from North America); (iii) Gallica superclade including Armillaria Nag E (Japan), multiple clades of A. gallica (Asia and Europe), A. calvescens (eastern North America), A. cepistipes (North America), A. altimontana (western USA), A. nabsnona (North America and Japan), and at least two A. gallica clades (North America); and (iv) Solidipes/Ostoyae superclade including two A. solidipes/ostoyae clades (North America), A. gemina (eastern USA), A. solidipes/ostoyae (Eurasia), A. cepistipes (Europe and Japan), A. sinapina (North America and Japan), and A. borealis (Eurasia) clade 2. Of note is that A. borealis (Eurasia) clade 1 appears basal to the Solidipes/Ostoyae and Gallica superclades. The Neighbor-net analysis showed similar phylogenetic relationships. This study further demonstrates the utility of tef1 for global phylogenetic studies of Armillaria species and provides critical insights into multiple taxonomic issues that warrant further study.

Solving the relativistic inverse stellar problem through gravitational waves observation of binary neutron stars

NASA Astrophysics Data System (ADS)

Abdelsalhin, Tiziano; Maselli, Andrea; Ferrari, Valeria

2018-04-01

The LIGO/Virgo Collaboration has recently announced the direct detection of gravitational waves emitted in the coalescence of a neutron star binary. This discovery allows, for the first time, to set new constraints on the behavior of matter at supranuclear density, complementary with those coming from astrophysical observations in the electromagnetic band. In this paper we demonstrate the feasibility of using gravitational signals to solve the relativistic inverse stellar problem, i.e., to reconstruct the parameters of the equation of state (EoS) from measurements of the stellar mass and tidal Love number. We perform Bayesian inference of mock data, based on different models of the star internal composition, modeled through piecewise polytropes. Our analysis shows that the detection of a small number of sources by a network of advanced interferometers would allow to put accurate bounds on the EoS parameters, and to perform a model selection among the realistic equations of state proposed in the literature.

Demographic history and gene flow during silkworm domestication

PubMed Central

2014-01-01

Background Gene flow plays an important role in domestication history of domesticated species. However, little is known about the demographic history of domesticated silkworm involving gene flow with its wild relative. Results In this study, four model-based evolutionary scenarios to describe the demographic history of B. mori were hypothesized. Using Approximate Bayesian Computation method and DNA sequence data from 29 nuclear loci, we found that the gene flow at bottleneck model is the most likely scenario for silkworm domestication. The starting time of silkworm domestication was estimated to be approximate 7,500 years ago; the time of domestication termination was 3,984 years ago. Using coalescent simulation analysis, we also found that bi-directional gene flow occurred during silkworm domestication. Conclusions Estimates of silkworm domestication time are nearly consistent with the archeological evidence and our previous results. Importantly, we found that the bi-directional gene flow might occur during silkworm domestication. Our findings add a dimension to highlight the important role of gene flow in domestication of crops and animals. PMID:25123546

Origin, Spread and Demography of the Mycobacterium tuberculosis Complex

PubMed Central

Wirth, Thierry; Hildebrand, Falk; Allix-Béguec, Caroline; Wölbeling, Florian; Kubica, Tanja; Kremer, Kristin; van Soolingen, Dick; Rüsch-Gerdes, Sabine; Locht, Camille; Brisse, Sylvain; Meyer, Axel

2008-01-01

The evolutionary timing and spread of the Mycobacterium tuberculosis complex (MTBC), one of the most successful groups of bacterial pathogens, remains largely unknown. Here, using mycobacterial tandem repeat sequences as genetic markers, we show that the MTBC consists of two independent clades, one composed exclusively of M. tuberculosis lineages from humans and the other composed of both animal and human isolates. The latter also likely derived from a human pathogenic lineage, supporting the hypothesis of an original human host. Using Bayesian statistics and experimental data on the variability of the mycobacterial markers in infected patients, we estimated the age of the MTBC at 40,000 years, coinciding with the expansion of “modern” human populations out of Africa. Furthermore, coalescence analysis revealed a strong and recent demographic expansion in almost all M. tuberculosis lineages, which coincides with the human population explosion over the last two centuries. These findings thus unveil the dynamic dimension of the association between human host and pathogen populations. PMID:18802459

Coalescence of viscous drops translating through a capillary tube

NASA Astrophysics Data System (ADS)

AlMatroushi, Eisa; Borhan, Ali

2014-03-01

An experimental study of the interaction and coalescence of viscous drops moving through a cylindrical capillary tube under low Reynolds number conditions is presented. The combined pressure- and buoyancy-driven motion of drops in a Newtonian continuous phase is examined. The interaction between two drops is quantified using image analysis, and measurements of the coalescence time are reported for various drop size ratios, Bond numbers, and viscosity ratios. The time scale for coalescence in the non-axisymmetric configuration is found to be substantially larger than that for coalescence in the axisymmetric configuration. Measurements of the radius of the liquid film formed between the two drops at the instant of apparent contact are used in conjunction with a planar film drainage model to predict the dependence of the coalescence time on drop size ratio for coalescence of low viscosity-ratio drops in the axisymmetric configuration.

Characterization of solids deposited on the modular caustic-side solvent extraction unit (MCU) coalescer media removed in October 2014

DOE Office of Scientific and Technical Information (OSTI.GOV)

Fondeur, F.

2016-03-01

In February 2015, Savannah River National Laboratory (SRNL) received a Strip Effluent (SE) coalescer (FLT-304) from MCU. That coalescer was first installed at MCU in July 2014 and removed in October 2014. While processing approximately 31,400 gallons of strip solution, the pressure drop steadily increased from 1 psi to beyond the administrative limit of 20 psi. The physical and chemical analysis was conducted on this coalescer to determine the mechanism that led to the plugging of this coalescer. Characterization of this coalescer revealed the adsorption of organic containing amines as well as MCU modifier. The amines are probably from themore » decomposition of the suppressor (TiDG) as well as from bacteria. This adsorption may have changed the surface energetics (characteristics) of the coalescer fibers and therefore, their wetting behavior. A very small amount of inorganic solids were found to have deposited on this coalescer (possibly an artifact of cleaning the coalescer with Boric acid. However, we believe that inorganic precipitation, as has been seen in the past, did not play a role in the high pressure drop rise of this coalescer. With regards to the current practice of reducing the radioactive content of the SE coalescer, it is recommended that future SE coalescer should be flushed with 10 mM boric acid which is currently used at MCU. Plugging of the SE coalescer was most likely due to the formation and accumulation of a water-in-oil emulsion that reduced the overall porosity of the coalescer. There is also evidence that a bimodal oil particle distribution may have entered and deposited in the coalescer and caused the initial increase in pressure drop.« less

Phase segregation due to simultaneous migration and coalescence

NASA Technical Reports Server (NTRS)

Davis, Robert H.

1994-01-01

The primary objective of the research is to perform ground-based analysis and experiments on the interaction and coalescence of drops (or bubbles) leading to macroscopic phase separation. Migration of the drops occurs as a result of the individual and collective action of gravity and thermocapillary effects. Larger drops migrate faster than smaller ones, leading to the possibility of collisions and coalescence. Coalescence increases the rate of macroscopic phase separation, since the result is larger drops with higher migration rates. It is hoped that the understanding gained will lead to the design of microgravity experiments to further elucidate the mechanisms governing coalescence and phase separation.

Phylodynamic Analysis Reveals CRF01_AE Dissemination between Japan and Neighboring Asian Countries and the Role of Intravenous Drug Use in Transmission

PubMed Central

Shiino, Teiichiro; Hattori, Junko; Yokomaku, Yoshiyuki; Iwatani, Yasumasa; Sugiura, Wataru

2014-01-01

Background One major circulating HIV-1 subtype in Southeast Asian countries is CRF01_AE, but little is known about its epidemiology in Japan. We conducted a molecular phylodynamic study of patients newly diagnosed with CRF01_AE from 2003 to 2010. Methods Plasma samples from patients registered in Japanese Drug Resistance HIV-1 Surveillance Network were analyzed for protease-reverse transcriptase sequences; all sequences undergo subtyping and phylogenetic analysis using distance-matrix-based, maximum likelihood and Bayesian coalescent Markov Chain Monte Carlo (MCMC) phylogenetic inferences. Transmission clusters were identified using interior branch test and depth-first searches for sub-tree partitions. Times of most recent common ancestor (tMRCAs) of significant clusters were estimated using Bayesian MCMC analysis. Results Among 3618 patient registered in our network, 243 were infected with CRF01_AE. The majority of individuals with CRF01_AE were Japanese, predominantly male, and reported heterosexual contact as their risk factor. We found 5 large clusters with ≥5 members and 25 small clusters consisting of pairs of individuals with highly related CRF01_AE strains. The earliest cluster showed a tMRCA of 1996, and consisted of individuals with their known risk as heterosexual contacts. The other four large clusters showed later tMRCAs between 2000 and 2002 with members including intravenous drug users (IVDU) and non-Japanese, but not men who have sex with men (MSM). In contrast, small clusters included a high frequency of individuals reporting MSM risk factors. Phylogenetic analysis also showed that some individuals infected with HIV strains spread in East and South-eastern Asian countries. Conclusions Introduction of CRF01_AE viruses into Japan is estimated to have occurred in the 1990s. CFR01_AE spread via heterosexual behavior, then among persons connected with non-Japanese, IVDU, and MSM. Phylogenetic analysis demonstrated that some viral variants are largely restricted to Japan, while others have a broad geographic distribution. PMID:25025900

Delimiting Coalescence Genes (C-Genes) in Phylogenomic Data Sets.

PubMed

Springer, Mark S; Gatesy, John

2018-02-26

coalescence methods have emerged as a popular alternative for inferring species trees with large genomic datasets, because these methods explicitly account for incomplete lineage sorting. However, statistical consistency of summary coalescence methods is not guaranteed unless several model assumptions are true, including the critical assumption that recombination occurs freely among but not within coalescence genes (c-genes), which are the fundamental units of analysis for these methods. Each c-gene has a single branching history, and large sets of these independent gene histories should be the input for genome-scale coalescence estimates of phylogeny. By contrast, numerous studies have reported the results of coalescence analyses in which complete protein-coding sequences are treated as c-genes even though exons for these loci can span more than a megabase of DNA. Empirical estimates of recombination breakpoints suggest that c-genes may be much shorter, especially when large clades with many species are the focus of analysis. Although this idea has been challenged recently in the literature, the inverse relationship between c-gene size and increased taxon sampling in a dataset-the 'recombination ratchet'-is a fundamental property of c-genes. For taxonomic groups characterized by genes with long intron sequences, complete protein-coding sequences are likely not valid c-genes and are inappropriate units of analysis for summary coalescence methods unless they occur in recombination deserts that are devoid of incomplete lineage sorting (ILS). Finally, it has been argued that coalescence methods are robust when the no-recombination within loci assumption is violated, but recombination must matter at some scale because ILS, a by-product of recombination, is the raison d'etre for coalescence methods. That is, extensive recombination is required to yield the large number of independently segregating c-genes used to infer a species tree. If coalescent methods are powerful enough to infer the correct species tree for difficult phylogenetic problems in the anomaly zone, where concatenation is expected to fail because of ILS, then there should be a decreasing probability of inferring the correct species tree using longer loci with many intralocus recombination breakpoints (i.e., increased levels of concatenation).

Delimiting Coalescence Genes (C-Genes) in Phylogenomic Data Sets

PubMed Central

Springer, Mark S.; Gatesy, John

2018-01-01

Summary coalescence methods have emerged as a popular alternative for inferring species trees with large genomic datasets, because these methods explicitly account for incomplete lineage sorting. However, statistical consistency of summary coalescence methods is not guaranteed unless several model assumptions are true, including the critical assumption that recombination occurs freely among but not within coalescence genes (c-genes), which are the fundamental units of analysis for these methods. Each c-gene has a single branching history, and large sets of these independent gene histories should be the input for genome-scale coalescence estimates of phylogeny. By contrast, numerous studies have reported the results of coalescence analyses in which complete protein-coding sequences are treated as c-genes even though exons for these loci can span more than a megabase of DNA. Empirical estimates of recombination breakpoints suggest that c-genes may be much shorter, especially when large clades with many species are the focus of analysis. Although this idea has been challenged recently in the literature, the inverse relationship between c-gene size and increased taxon sampling in a dataset—the ‘recombination ratchet’—is a fundamental property of c-genes. For taxonomic groups characterized by genes with long intron sequences, complete protein-coding sequences are likely not valid c-genes and are inappropriate units of analysis for summary coalescence methods unless they occur in recombination deserts that are devoid of incomplete lineage sorting (ILS). Finally, it has been argued that coalescence methods are robust when the no-recombination within loci assumption is violated, but recombination must matter at some scale because ILS, a by-product of recombination, is the raison d’etre for coalescence methods. That is, extensive recombination is required to yield the large number of independently segregating c-genes used to infer a species tree. If coalescent methods are powerful enough to infer the correct species tree for difficult phylogenetic problems in the anomaly zone, where concatenation is expected to fail because of ILS, then there should be a decreasing probability of inferring the correct species tree using longer loci with many intralocus recombination breakpoints (i.e., increased levels of concatenation). PMID:29495400

Hepatitis C virus diversification in Argentina: comparative analysis between the large city of Buenos Aires and the small rural town of O'Brien.

PubMed

Golemba, Marcelo D; Culasso, Andrés C A; Villamil, Federico G; Bare, Patricia; Gadano, Adrián; Ridruejo, Ezequiel; Martinez, Alfredo; Di Lello, Federico A; Campos, Rodolfo H

2013-01-01

The estimated prevalence of HCV infection in Argentina is around 2%. However, higher rates of infection have been described in population studies of small urban and rural communities. The aim of this work was to compare the origin and diversification of HCV-1b in samples from two different epidemiological scenarios: Buenos Aires, a large cosmopolitan city, and O'Brien, a small rural town with a high prevalence of HCV infection. The E1/E2 and NS5B regions of the viral genome from 83 patients infected with HCV-1b were sequenced. Phylogenetic analysis and Bayesian Coalescent methods were used to study the origin and diversification of HCV-1b in both patient populations. Samples from Buenos Aires showed a polyphyletic behavior with a tMRCA around 1887-1900 and a time of spread of infection approximately 60 years ago. In contrast, samples from ÓBrien showed a monophyletic behavior with a tMRCA around 1950-1960 and a time of spread of infection more recent than in Buenos Aires, around 20-30 years ago. Phylogenetic and coalescence analysis revealed a different behavior in the epidemiological histories of Buenos Aires and ÓBrien. HCV infection in Buenos Aires shows a polyphyletic behavior and an exponential growth in two phases, whereas that in O'Brien shows a monophyletic cluster and an exponential growth in one single step with a more recent tMRCA. The polyphyletic origin and the probability of encountering susceptible individuals in a large cosmopolitan city like Buenos Aires are in agreement with a longer period of expansion. In contrast, in less populated areas such as O'Brien, the chances of HCV transmission are strongly restricted. Furthermore, the monophyletic character and the most recent time of emergence suggest that different HCV-1b ancestors (variants) that were in expansion in Buenos Aires had the opportunity to colonize and expand in O'Brien.

Bayesian data analysis for newcomers.

PubMed

Kruschke, John K; Liddell, Torrin M

2018-02-01

This article explains the foundational concepts of Bayesian data analysis using virtually no mathematical notation. Bayesian ideas already match your intuitions from everyday reasoning and from traditional data analysis. Simple examples of Bayesian data analysis are presented that illustrate how the information delivered by a Bayesian analysis can be directly interpreted. Bayesian approaches to null-value assessment are discussed. The article clarifies misconceptions about Bayesian methods that newcomers might have acquired elsewhere. We discuss prior distributions and explain how they are not a liability but an important asset. We discuss the relation of Bayesian data analysis to Bayesian models of mind, and we briefly discuss what methodological problems Bayesian data analysis is not meant to solve. After you have read this article, you should have a clear sense of how Bayesian data analysis works and the sort of information it delivers, and why that information is so intuitive and useful for drawing conclusions from data.

EggLib: processing, analysis and simulation tools for population genetics and genomics

PubMed Central

2012-01-01

Background With the considerable growth of available nucleotide sequence data over the last decade, integrated and flexible analytical tools have become a necessity. In particular, in the field of population genetics, there is a strong need for automated and reliable procedures to conduct repeatable and rapid polymorphism analyses, coalescent simulations, data manipulation and estimation of demographic parameters under a variety of scenarios. Results In this context, we present EggLib (Evolutionary Genetics and Genomics Library), a flexible and powerful C++/Python software package providing efficient and easy to use computational tools for sequence data management and extensive population genetic analyses on nucleotide sequence data. EggLib is a multifaceted project involving several integrated modules: an underlying computationally efficient C++ library (which can be used independently in pure C++ applications); two C++ programs; a Python package providing, among other features, a high level Python interface to the C++ library; and the egglib script which provides direct access to pre-programmed Python applications. Conclusions EggLib has been designed aiming to be both efficient and easy to use. A wide array of methods are implemented, including file format conversion, sequence alignment edition, coalescent simulations, neutrality tests and estimation of demographic parameters by Approximate Bayesian Computation (ABC). Classes implementing different demographic scenarios for ABC analyses can easily be developed by the user and included to the package. EggLib source code is distributed freely under the GNU General Public License (GPL) from its website http://egglib.sourceforge.net/ where a full documentation and a manual can also be found and downloaded. PMID:22494792

A three-stage colonization model for the peopling of the Americas.

PubMed

Kitchen, Andrew; Miyamoto, Michael M; Mulligan, Connie J

2008-02-13

We evaluate the process by which the Americas were originally colonized and propose a three-stage model that integrates current genetic, archaeological, geological, and paleoecological data. Specifically, we analyze mitochondrial and nuclear genetic data by using complementary coalescent models of demographic history and incorporating non-genetic data to enhance the anthropological relevance of the analysis. Bayesian skyline plots, which provide dynamic representations of population size changes over time, indicate that Amerinds went through two stages of growth approximately 40,000 and approximately 15,000 years ago separated by a long period of population stability. Isolation-with-migration coalescent analyses, which utilize data from sister populations to estimate a divergence date and founder population sizes, suggest an Amerind population expansion starting approximately 15,000 years ago. These results support a model for the peopling of the New World in which Amerind ancestors diverged from the Asian gene pool prior to 40,000 years ago and experienced a gradual population expansion as they moved into Beringia. After a long period of little change in population size in greater Beringia, Amerinds rapidly expanded into the Americas approximately 15,000 years ago either through an interior ice-free corridor or along the coast. This rapid colonization of the New World was achieved by a founder group with an effective population size of approximately 1,000-5,400 individuals. Our model presents a detailed scenario for the timing and scale of the initial migration to the Americas, substantially refines the estimate of New World founders, and provides a unified theory for testing with future datasets and analytic methods.

EggLib: processing, analysis and simulation tools for population genetics and genomics.

PubMed

De Mita, Stéphane; Siol, Mathieu

2012-04-11

With the considerable growth of available nucleotide sequence data over the last decade, integrated and flexible analytical tools have become a necessity. In particular, in the field of population genetics, there is a strong need for automated and reliable procedures to conduct repeatable and rapid polymorphism analyses, coalescent simulations, data manipulation and estimation of demographic parameters under a variety of scenarios. In this context, we present EggLib (Evolutionary Genetics and Genomics Library), a flexible and powerful C++/Python software package providing efficient and easy to use computational tools for sequence data management and extensive population genetic analyses on nucleotide sequence data. EggLib is a multifaceted project involving several integrated modules: an underlying computationally efficient C++ library (which can be used independently in pure C++ applications); two C++ programs; a Python package providing, among other features, a high level Python interface to the C++ library; and the egglib script which provides direct access to pre-programmed Python applications. EggLib has been designed aiming to be both efficient and easy to use. A wide array of methods are implemented, including file format conversion, sequence alignment edition, coalescent simulations, neutrality tests and estimation of demographic parameters by Approximate Bayesian Computation (ABC). Classes implementing different demographic scenarios for ABC analyses can easily be developed by the user and included to the package. EggLib source code is distributed freely under the GNU General Public License (GPL) from its website http://egglib.sourceforge.net/ where a full documentation and a manual can also be found and downloaded.

DOE Office of Scientific and Technical Information (OSTI.GOV)

Del Pozzo, Walter; Nikhef National Institute for Subatomic Physics, Science Park 105, 1098 XG Amsterdam; Veitch, John

Second-generation interferometric gravitational-wave detectors, such as Advanced LIGO and Advanced Virgo, are expected to begin operation by 2015. Such instruments plan to reach sensitivities that will offer the unique possibility to test general relativity in the dynamical, strong-field regime and investigate departures from its predictions, in particular, using the signal from coalescing binary systems. We introduce a statistical framework based on Bayesian model selection in which the Bayes factor between two competing hypotheses measures which theory is favored by the data. Probability density functions of the model parameters are then used to quantify the inference on individual parameters. We alsomore » develop a method to combine the information coming from multiple independent observations of gravitational waves, and show how much stronger inference could be. As an introduction and illustration of this framework-and a practical numerical implementation through the Monte Carlo integration technique of nested sampling-we apply it to gravitational waves from the inspiral phase of coalescing binary systems as predicted by general relativity and a very simple alternative theory in which the graviton has a nonzero mass. This method can (and should) be extended to more realistic and physically motivated theories.« less

Molecular species delimitation methods recover most song-delimited cicada species in the European Cicadetta montana complex.

PubMed

Wade, E J; Hertach, T; Gogala, M; Trilar, T; Simon, C

2015-12-01

Molecular species delimitation is increasingly being used to discover and illuminate species level diversity, and a number of methods have been developed. Here, we compare the ability of two molecular species delimitation methods to recover song-delimited species in the Cicadetta montana cryptic species complex throughout Europe. Recent bioacoustics studies of male calling songs (premating reproductive barriers) have revealed cryptic species diversity in this complex. Maximum likelihood and Bayesian phylogenetic analyses were used to analyse the mitochondrial genes COI and COII and the nuclear genes EF1α and period for thirteen European Cicadetta species as well as the closely related monotypic genus Euboeana. Two molecular species delimitation methods, general mixed Yule-coalescent (GMYC) and Bayesian phylogenetics and phylogeography, identified the majority of song-delimited species and were largely congruent with each other. None of the molecular delimitation methods were able to fully recover a recent radiation of four Greek species. © 2015 European Society For Evolutionary Biology. Journal of Evolutionary Biology © 2015 European Society For Evolutionary Biology.

Sky island diversification meets the multispecies coalescent - divergence in the spruce-fir moss spider (Microhexura montivaga, Araneae, Mygalomorphae) on the highest peaks of southern Appalachia.

PubMed

Hedin, Marshal; Carlson, Dave; Coyle, Fred

2015-07-01

Microhexura montivaga is a miniature tarantula-like spider endemic to the highest peaks of the southern Appalachian mountains and is known only from six allopatric, highly disjunct montane populations. Because of severe declines in spruce-fir forest in the late 20th century, M. montivaga was formally listed as a US federally endangered species in 1995. Using DNA sequence data from one mitochondrial and seven nuclear genes, patterns of multigenic genetic divergence were assessed for six montane populations. Independent mitochondrial and nuclear discovery analyses reveal obvious genetic fragmentation both within and among montane populations, with five to seven primary genetic lineages recovered. Multispecies coalescent validation analyses [guide tree and unguided Bayesian Phylogenetics and Phylogeography (BPP), Bayes factor delimitation (BFD)] using nuclear-only data congruently recover six or seven distinct lineages; BFD analyses using combined nuclear plus mitochondrial data favour seven or eight lineages. In stark contrast to this clear genetic fragmentation, a survey of secondary sexual features for available males indicates morphological conservatism across montane populations. While it is certainly possible that morphologically cryptic speciation has occurred in this taxon, this system may alternatively represent a case where extreme population genetic structuring (but not speciation) leads to an oversplitting of lineage diversity by multispecies coalescent methods. Our results have clear conservation implications for this federally endangered taxon and illustrate a methodological issue expected to become more common as genomic-scale data sets are gathered for taxa found in naturally fragmented habitats. © 2015 John Wiley & Sons Ltd.

The effects of Medieval dams on genetic divergence and demographic history in brown trout populations

PubMed Central

2014-01-01

Background Habitat fragmentation has accelerated within the last century, but may have been ongoing over longer time scales. We analyzed the timing and genetic consequences of fragmentation in two isolated lake-dwelling brown trout populations. They are from the same river system (the Gudenå River, Denmark) and have been isolated from downstream anadromous trout by dams established ca. 600–800 years ago. For reference, we included ten other anadromous populations and two hatchery strains. Based on analysis of 44 microsatellite loci we investigated if the lake populations have been naturally genetically differentiated from anadromous trout for thousands of years, or have diverged recently due to the establishment of dams. Results Divergence time estimates were based on 1) Approximate Bayesian Computation and 2) a coalescent-based isolation-with-gene-flow model. Both methods suggested divergence times ca. 600–800 years bp, providing strong evidence for establishment of dams in the Medieval as the factor causing divergence. Bayesian cluster analysis showed influence of stocked trout in several reference populations, but not in the focal lake and anadromous populations. Estimates of effective population size using a linkage disequilibrium method ranged from 244 to > 1,000 in all but one anadromous population, but were lower (153 and 252) in the lake populations. Conclusions We show that genetic divergence of lake-dwelling trout in two Danish lakes reflects establishment of water mills and impassable dams ca. 600–800 years ago rather than a natural genetic population structure. Although effective population sizes of the two lake populations are not critically low they may ultimately limit response to selection and thereby future adaptation. Our results demonstrate that populations may have been affected by anthropogenic disturbance over longer time scales than normally assumed. PMID:24903056

The effects of Medieval dams on genetic divergence and demographic history in brown trout populations.

PubMed

Hansen, Michael M; Limborg, Morten T; Ferchaud, Anne-Laure; Pujolar, José-Martin

2014-06-05

Habitat fragmentation has accelerated within the last century, but may have been ongoing over longer time scales. We analyzed the timing and genetic consequences of fragmentation in two isolated lake-dwelling brown trout populations. They are from the same river system (the Gudenå River, Denmark) and have been isolated from downstream anadromous trout by dams established ca. 600-800 years ago. For reference, we included ten other anadromous populations and two hatchery strains. Based on analysis of 44 microsatellite loci we investigated if the lake populations have been naturally genetically differentiated from anadromous trout for thousands of years, or have diverged recently due to the establishment of dams. Divergence time estimates were based on 1) Approximate Bayesian Computation and 2) a coalescent-based isolation-with-gene-flow model. Both methods suggested divergence times ca. 600-800 years bp, providing strong evidence for establishment of dams in the Medieval as the factor causing divergence. Bayesian cluster analysis showed influence of stocked trout in several reference populations, but not in the focal lake and anadromous populations. Estimates of effective population size using a linkage disequilibrium method ranged from 244 to > 1,000 in all but one anadromous population, but were lower (153 and 252) in the lake populations. We show that genetic divergence of lake-dwelling trout in two Danish lakes reflects establishment of water mills and impassable dams ca. 600-800 years ago rather than a natural genetic population structure. Although effective population sizes of the two lake populations are not critically low they may ultimately limit response to selection and thereby future adaptation. Our results demonstrate that populations may have been affected by anthropogenic disturbance over longer time scales than normally assumed.

Unveiling an ancient biological invasion: molecular analysis of an old European alien, the crested porcupine (Hystrix cristata).

PubMed

Trucchi, Emiliano; Sbordoni, Valerio

2009-05-18

Biological invasions can be considered one of the main threats to biodiversity, and the recognition of common ecological and evolutionary features among invaders can help developing a predictive framework to control further invasions. In particular, the analysis of successful invasive species and of their autochthonous source populations by means of genetic, phylogeographic and demographic tools can provide novel insights into the study of biological invasion patterns. Today, long-term dynamics of biological invasions are still poorly understood and need further investigations. Moreover, distribution and molecular data on native populations could contribute to the recognition of common evolutionary features of successful aliens. We analyzed 2,195 mitochondrial base pairs, including Cytochrome b, Control Region and rRNA 12S, in 161 Italian and 27 African specimens and assessed the ancient invasive origin of Italian crested porcupine (Hystrix cristata) populations from Tunisia. Molecular coalescent-based Bayesian analyses proposed the Roman Age as a putative timeframe of introduction and suggested a retention of genetic diversity during the early phases of colonization. The characterization of the native African genetic background revealed the existence of two differentiated clades: a Mediterranean group and a Sub-Saharan one. Both standard population genetic and advanced molecular demography tools (Bayesian Skyline Plot) did not evidence a clear genetic signature of the expected increase in population size after introduction. Along with the genetic diversity retention during the bottlenecked steps of introduction, this finding could be better described by hypothesizing a multi-invasion event. Evidences of the ancient anthropogenic invasive origin of the Italian Hystrix cristata populations were clearly shown and the native African genetic background was preliminary described. A more complex pattern than a simple demographic exponential growth from a single propagule seems to have characterized this long-term invasion.

DEMOGRAPHIC CONSEQUENCES OF COALESCENCE IN SPORELING POPULATIONS OF MAZZAELLA LAMINARIOIDES (GIGARTINALES, RHODOPHYTA)(1).

PubMed

Santelices, B; Alvarado, J L

2008-06-01

Coalescing macroalgae are ecologically important members of intertidal and shallow subtidal communities. However, we still lack quantitative information on the demographic consequences of coalescence. Using demographic models developed for modular invertebrates, we studied the demography of settlement and early recruitment in the coalescing macroalga Mazzaella laminarioides (Bory) Fredericq. Permanently marked microscopic fields on laboratory-incubated and field-incubated plates were monitored regularly (at 15, 30, 45, and 60 d) using image analysis techniques to evaluate the relative importance of settler abundance, mortality, coalescence (fusion), and fission on the changes in size and numbers of recruits. On the plates, spores settled individually or in groups. Over time, spores in close proximity may coalesce, resulting in a mixture of unisporic and multisporic crusts. When new spores arrive, they may or may not coalesce with previously settled crusts. Coalescence and mortality reduce the number of sporelings, but coalescence increases the size of the sporelings, thereby reducing further probability of sporeling mortality. Crust fissions are negligible in frequency, while the frequency of coalescence increases from ∼25% after only 3 d, to ∼75% after 60 d. Thus, as a result of variable settlement, mortality, and coalescence, any area colonized by M. laminarioides would contain a mixture of crusts of different sizes, ages, and genetic constitution. The interactions between the above three processes create a more complex survivorship curve than the ones known for unitary organisms. © 2008 Phycological Society of America.

Effects of fullerene coalescence on the thermal conductivity of carbon nanopeapods

NASA Astrophysics Data System (ADS)

Li, Jiaqian; Shen, Haijun

2018-05-01

The heat conduction and its dependence on fullerene coalescence in carbon nanopeapods (CNPs) have been investigated by equilibrium molecular dynamics simulations. The effects of fullerene coalescence on the thermal conductivity of CNPs were discussed under different temperatures. It is shown that the thermal conductivity of the CNPs decreases with the coalescence of encapsulated fullerene molecules. The thermal transmission mechanism of the effect of fullerene coalescence was analysed by the mass transfer contribution, the relative contributions of phonon oscillation frequencies to total heat current and the phonon vibrational density of states (VDOS). The mass transfer in CNPs is mainly attributed to the motion of encapsulated fullerene molecule and it gets more restricted with the coalescence of the fullerene. It shows that the low-frequency phonon modes below 20 THz contribute mostly to thermal conductivity in CNPs. The analysis of VDOS demonstrates that the dominating contribution to heat transfer is from the inner fullerene chain. With the coalescence of fullerene, the interfacial heat transfer between the CNT and fullerene chain is strengthened; however, the heat conduction of the fullerene chain decreases more rapidly at the same time.

Genealogical Working Distributions for Bayesian Model Testing with Phylogenetic Uncertainty

PubMed Central

Baele, Guy; Lemey, Philippe; Suchard, Marc A.

2016-01-01

Marginal likelihood estimates to compare models using Bayes factors frequently accompany Bayesian phylogenetic inference. Approaches to estimate marginal likelihoods have garnered increased attention over the past decade. In particular, the introduction of path sampling (PS) and stepping-stone sampling (SS) into Bayesian phylogenetics has tremendously improved the accuracy of model selection. These sampling techniques are now used to evaluate complex evolutionary and population genetic models on empirical data sets, but considerable computational demands hamper their widespread adoption. Further, when very diffuse, but proper priors are specified for model parameters, numerical issues complicate the exploration of the priors, a necessary step in marginal likelihood estimation using PS or SS. To avoid such instabilities, generalized SS (GSS) has recently been proposed, introducing the concept of “working distributions” to facilitate—or shorten—the integration process that underlies marginal likelihood estimation. However, the need to fix the tree topology currently limits GSS in a coalescent-based framework. Here, we extend GSS by relaxing the fixed underlying tree topology assumption. To this purpose, we introduce a “working” distribution on the space of genealogies, which enables estimating marginal likelihoods while accommodating phylogenetic uncertainty. We propose two different “working” distributions that help GSS to outperform PS and SS in terms of accuracy when comparing demographic and evolutionary models applied to synthetic data and real-world examples. Further, we show that the use of very diffuse priors can lead to a considerable overestimation in marginal likelihood when using PS and SS, while still retrieving the correct marginal likelihood using both GSS approaches. The methods used in this article are available in BEAST, a powerful user-friendly software package to perform Bayesian evolutionary analyses. PMID:26526428

Molecular and morphological data reveal non-monophyly and speciation in imperiled freshwater mussels (Anodontoides and Strophitus)

USGS Publications Warehouse

Smith, Chase; Johnson, Nathan A.; Pfeiffer, John M.; Gangloff, Michael M.

2018-01-01

Accurate taxonomic placement is vital to conservation efforts considering many intrinsic biological characteristics of understudied species are inferred from closely related taxa. The rayed creekshell, Anodontoides radiatus (Conrad, 1834), exists in the Gulf of Mexico drainages from western Florida to Louisiana and has been petitioned for listing under the Endangered Species Act. We set out to resolve the evolutionary history of A. radiatus, primarily generic placement and species boundaries, using phylogenetic, morphometric, and geographic information. Our molecular matrix contained 3 loci: cytochrome c oxidase subunit I, NADH dehydrogenase subunit I, and the nuclear-encoded ribosomal internal transcribed spacer I. We employed maximum likelihood and Bayesian inference to estimate a phylogeny and test the monophyly of Anodontoides and Strophitus. We implemented two coalescent-based species delimitation models to test seven species models and evaluate species boundaries within A. radiatus. Concomitant to molecular data, we also employed linear morphometrics and geographic information to further evaluate species boundaries. Molecular and morphological evidence supports the inclusion of A. radiatus in the genus Strophitus, and we resurrect the binomial Strophitus radiatus to reflect their shared common ancestry. We also found strong support for polyphyly in Strophitus and advocate the resurrection of the genus Pseudodontoideus to represent ‘Strophitus’ connasaugaensis and ‘Strophitus’ subvexus. Strophitus radiatus exists in six well-supported clades that were distinguished as evolutionary independent lineages using Bayesian inference, maximum likelihood, and coalescent-based species delimitation models. Our integrative approach found evidence for as many as 4 evolutionary divergent clades within S. radiatus. Therefore, we formally describe two new species from the S. radiatus species complex (Strophitus williamsi and Strophitus pascagoulaensis) and recognize the potential for a third putative species (Strophitus sp. cf. pascagoulaensis). Our findings aid stakeholders in establishing conservation and management strategies for the members of Anodontoides, Strophitus, and Pseudodontoideus.

Phylodynamic Analysis of Clinical and Environmental Vibrio cholerae Isolates from Haiti Reveals Diversification Driven by Positive Selection

PubMed Central

Azarian, Taj; Ali, Afsar; Johnson, Judith A.; Mohr, David; Prosperi, Mattia; Veras, Nazle M.; Jubair, Mohammed; Strickland, Samantha L.; Rashid, Mohammad H.; Alam, Meer T.; Weppelmann, Thomas A.; Katz, Lee S.; Tarr, Cheryl L.; Colwell, Rita R.

2014-01-01

ABSTRACT Phylodynamic analysis of genome-wide single-nucleotide polymorphism (SNP) data is a powerful tool to investigate underlying evolutionary processes of bacterial epidemics. The method was applied to investigate a collection of 65 clinical and environmental isolates of Vibrio cholerae from Haiti collected between 2010 and 2012. Characterization of isolates recovered from environmental samples identified a total of four toxigenic V. cholerae O1 isolates, four non-O1/O139 isolates, and a novel nontoxigenic V. cholerae O1 isolate with the classical tcpA gene. Phylogenies of strains were inferred from genome-wide SNPs using coalescent-based demographic models within a Bayesian framework. A close phylogenetic relationship between clinical and environmental toxigenic V. cholerae O1 strains was observed. As cholera spread throughout Haiti between October 2010 and August 2012, the population size initially increased and then fluctuated over time. Selection analysis along internal branches of the phylogeny showed a steady accumulation of synonymous substitutions and a progressive increase of nonsynonymous substitutions over time, suggesting diversification likely was driven by positive selection. Short-term accumulation of nonsynonymous substitutions driven by selection may have significant implications for virulence, transmission dynamics, and even vaccine efficacy. PMID:25538191

A Three-Stage Colonization Model for the Peopling of the Americas

PubMed Central

Kitchen, Andrew; Miyamoto, Michael M.; Mulligan, Connie J.

2008-01-01

Background We evaluate the process by which the Americas were originally colonized and propose a three-stage model that integrates current genetic, archaeological, geological, and paleoecological data. Specifically, we analyze mitochondrial and nuclear genetic data by using complementary coalescent models of demographic history and incorporating non-genetic data to enhance the anthropological relevance of the analysis. Methodology/Findings Bayesian skyline plots, which provide dynamic representations of population size changes over time, indicate that Amerinds went through two stages of growth ≈40,000 and ≈15,000 years ago separated by a long period of population stability. Isolation-with-migration coalescent analyses, which utilize data from sister populations to estimate a divergence date and founder population sizes, suggest an Amerind population expansion starting ≈15,000 years ago. Conclusions/Significance These results support a model for the peopling of the New World in which Amerind ancestors diverged from the Asian gene pool prior to 40,000 years ago and experienced a gradual population expansion as they moved into Beringia. After a long period of little change in population size in greater Beringia, Amerinds rapidly expanded into the Americas ≈15,000 years ago either through an interior ice-free corridor or along the coast. This rapid colonization of the New World was achieved by a founder group with an effective population size of ≈1,000–5,400 individuals. Our model presents a detailed scenario for the timing and scale of the initial migration to the Americas, substantially refines the estimate of New World founders, and provides a unified theory for testing with future datasets and analytic methods. PMID:18270583

Molecular Epidemiology and Spatio-Temporal Dynamics of the H3N8 Equine Influenza Virus in South America

PubMed Central

Olguin Perglione, Cecilia; Golemba, Marcelo D.; Torres, Carolina; Barrandeguy, Maria

2016-01-01

Equine influenza virus (EIV) is considered the most important respiratory pathogen of horses as outbreaks of the disease lead to substantial economic losses. The H3N8 EIV has caused respiratory disease in horses across the world, including South American countries. Nucleotide and deduced amino acid sequences for the complete haemagglutinin gene of the H3N8 EIV detected in South America since 1963 were analyzed. Phylogenetic and Bayesian coalescent analyses were carried out to study the origin, the time of the most recent common ancestors (tMRCA), the demographic and the phylogeographic patterns of the H3N8 EIV. The phylogenetic analysis demonstrated that the H3N8 EIV detected in South America grouped in 5 well-supported monophyletic clades, each associated with strains of different origins. The tMRCA estimated for each group suggested that the virus was circulating in North America at least one year before its effective circulation in the South American population. Phylogenetic and coalescent analyses revealed a polyphyletic behavior of the viruses causing the outbreaks in South America between 1963 and 2012, possibly due to the introduction of at least 4 different EIVs through the international movement of horses. In addition, phylodynamic analysis suggested South America as the starting point of the spread of the H3N8 EIV in 1963 and showed migration links from the United States to South America in the subsequent EIV irruptions. Further, an increase in the relative genetic diversity was observed between 2006 and 2007 and a subsequent decline since 2009, probably due to the co-circulation of different lineages and as a result of the incorporation of the Florida clade 2 strain in vaccines, respectively. The observed data highlight the importance of epidemiological surveillance and the implementation of appropriate quarantine procedures to prevent outbreaks of the disease. PMID:27754468

Upper limits for gravitational radiation from supermassive coalescing binaries

NASA Technical Reports Server (NTRS)

Anderson, J. D.; Armstrong, J. W.; Lau, E. L.

1993-01-01

We report a search for waves from supermassive coalescing binaries using a 10.5 day Pioneer 10 data set taken in 1988. Depending on the time to coalescence, the initial frequency of the wave, and the length of the observing interval, a coalescing binary waveform appears in the tracking record either as a sinusoid, a 'chirp', or as a more complicated signal. We searched our data for coalescing binary waveforms in all three regimes. We successfully detected a (fortuitous) 'chirp' signal caused by the varying spin rate of the spacecraft; this nicely served as a calibration of the data quality and as a test of our analysis procedures on real data. We did not detect any signals of astronomical origin in the millihertz band to an upper limit of about 7 x 10 exp -15 (rms amplitude). This is the first time spacecraft Doppler data have been analyzed for coalescing binary waveforms, and the upper limits reported here are the best to date for any waveform in the millihertz band.

Pragmatic perspective on conservation genetics and demographic history of the last surviving population of Kashmir red deer (Cervus elaphus hanglu) in India.

PubMed

Mukesh; Kumar, Ved P; Sharma, Lalit K; Shukla, Malay; Sathyakumar, Sambandam

2015-01-01

The hangul (Cervus elaphus hanglu) is of great conservation concern because it represents the easternmost and only hope for an Asiatic survivor of the red deer species in the Indian subcontinent. Despite the rigorous conservation efforts of the Department of Wildlife Protection in Jammu & Kashmir, the hangul population has experienced a severe decline in numbers and range contraction in the past few decades. The hangul population once abundant in the past has largely become confined to the Dachigam landscape, with a recent population estimate of 218 individuals. We investigated the genetic variability and demographic history of the hangul population and found that it has shown a relatively low diversity estimates when compared to other red deer populations of the world. Neutrality tests, which are used to evaluate demographic effects, did not support population expansion, and the multimodal pattern of mismatch distribution indicated that the hangul population is under demographic equilibrium. Furthermore, the hangul population did not exhibit any signature of bottleneck footprints in the past, and Coalescent Bayesian Skyline plot analysis revealed that the population had not experienced any dramatic changes in the effective population size over the last several thousand years. We observed a strong evidence of sub-structuring in the population, wherein the majority of individuals were assigned to different clusters in Bayesian cluster analysis. Population viability analysis demonstrated insignificant changes in the mean population size, with a positive growth rate projected for the next hundred years. We discuss the phylogenetic status of hangul for the first time among the other red deer subspecies of the world and strongly recommend to upgrade hangul conservation status under IUCN that should be discrete from the other red deer subspecies of the world to draw more conservation attention from national and international bodies.

Reconstructing Past Admixture Processes from Local Genomic Ancestry Using Wavelet Transformation

PubMed Central

Sanderson, Jean; Sudoyo, Herawati; Karafet, Tatiana M.; Hammer, Michael F.; Cox, Murray P.

2015-01-01

Admixture between long-separated populations is a defining feature of the genomes of many species. The mosaic block structure of admixed genomes can provide information about past contact events, including the time and extent of admixture. Here, we describe an improved wavelet-based technique that better characterizes ancestry block structure from observed genomic patterns. principal components analysis is first applied to genomic data to identify the primary population structure, followed by wavelet decomposition to develop a new characterization of local ancestry information along the chromosomes. For testing purposes, this method is applied to human genome-wide genotype data from Indonesia, as well as virtual genetic data generated using genome-scale sequential coalescent simulations under a wide range of admixture scenarios. Time of admixture is inferred using an approximate Bayesian computation framework, providing robust estimates of both admixture times and their associated levels of uncertainty. Crucially, we demonstrate that this revised wavelet approach, which we have released as the R package adwave, provides improved statistical power over existing wavelet-based techniques and can be used to address a broad range of admixture questions. PMID:25852078

Population dynamics of American horseshoe crabs-historic climatic events and recent anthropogenic pressures

USGS Publications Warehouse

Faurby, S.; King, T.L.; Obst, M.; Hallerman, E.M.; Pertoldi, C.; Funch, P.

2010-01-01

Populations of the American horseshoe crab, Limulus polyphemus, have declined, but neither the causes nor the magnitude are fully understood. In order to evaluate historic demography, variation at 12 microsatellite DNA loci surveyed in 1218 L. polyphemus sampled from 28 localities was analysed with Bayesian coalescent-based methods. The analysis showed strong declines in population sizes throughout the species' distribution except in the geographically isolated southern-most population in Mexico, where a strong increase in population size was inferred. Analyses suggested that demographic changes in the core of the distribution occurred in association with the recolonization after the Ice Age and also by anthropogenic effects, such as the past overharvest of the species for fertilizer or the current use of the animals as bait for American eel (Anguilla rostrata) and whelk (Busycon spp.) fisheries. This study highlights the importance of considering both climatic changes and anthropogenic effects in efforts to understand population dynamics-a topic which is highly relevant in the ongoing assessments of the effects of climate change and overharvest. ?? 2010 Blackwell Publishing Ltd.

Population dynamics of American horseshoe crabs--historic climatic events and recent anthropogenic pressures.

PubMed

Faurby, Søren; King, Tim L; Obst, Matthias; Hallerman, Eric M; Pertoldi, Cino; Funch, Peter

2010-08-01

Populations of the American horseshoe crab, Limulus polyphemus, have declined, but neither the causes nor the magnitude are fully understood. In order to evaluate historic demography, variation at 12 microsatellite DNA loci surveyed in 1218 L. polyphemus sampled from 28 localities was analysed with Bayesian coalescent-based methods. The analysis showed strong declines in population sizes throughout the species' distribution except in the geographically isolated southern-most population in Mexico, where a strong increase in population size was inferred. Analyses suggested that demographic changes in the core of the distribution occurred in association with the recolonization after the Ice Age and also by anthropogenic effects, such as the past overharvest of the species for fertilizer or the current use of the animals as bait for American eel (Anguilla rostrata) and whelk (Busycon spp.) fisheries. This study highlights the importance of considering both climatic changes and anthropogenic effects in efforts to understand population dynamics--a topic which is highly relevant in the ongoing assessments of the effects of climate change and overharvest.

Filling phylogenetic gaps and the biogeographic relationships of the Octodontidae (Mammalia: Hystricognathi).

PubMed

Suárez-Villota, Elkin Y; González-Wevar, Claudio A; Gallardo, Milton H; Vásquez, Rodrigo A; Poulin, Elie

2016-12-01

Endemic to South America, octodontid rodents are remarkable by being the only mammal taxa where allotetraploidy has been documented. The taxon's extensive morpho-physiological radiation associated to niche shifts has allowed testing phylogeographic hypotheses. Using maximum likelihood and Bayesian inference analyses, applied to all nominal species of octodontids, phylogenetic reconstructions based on sequences of 12S rRNA and growth hormone receptor gene are presented. Species boundaries were determined by coalescent analyses and divergence times among taxa were estimated based on mutation rates. Two main clades associated to the Andean orogenesis were recognized. The essentially western clade comprises genera Aconaemys, Octodon, Spalacopus, and Octodontomys whereas the eastern one included genera Octomys, Pipanacoctomys, Salinoctomys, and Tympanoctomys. Genetic relationships, coalescent analyses, and genetic distance supported the specific status given to Octodon pacificus and that given to Pipanacoctomys aureus as a species of Tympanoctomys. However, these analyses failed to recognize Salinoctomys loschalchalerosorum as a valid taxon considering its position within the diversity of Tympanoctomys barrerae. Although the origin of genome duplication remains contentious, the coincidence of the basal clade split with distinctive modes of karyotypic evolution across the Andes emphasizes the role of physiographic barriers and westerlies in shaping different edaphological conditions, selective grounds, and concomitantly distinct adaptations within the octodontids. Copyright © 2016 Elsevier Inc. All rights reserved.

Are Antarctic minke whales unusually abundant because of 20th century whaling?

PubMed

Ruegg, Kristen C; Anderson, Eric C; Scott Baker, C; Vant, Murdoch; Jackson, Jennifer A; Palumbi, Stephen R

2010-01-01

Severe declines in megafauna worldwide illuminate the role of top predators in ecosystem structure. In the Antarctic, the Krill Surplus Hypothesis posits that the killing of more than 2 million large whales led to competitive release for smaller krill-eating species like the Antarctic minke whale. If true, the current size of the Antarctic minke whale population may be unusually high as an indirect result of whaling. Here, we estimate the long-term population size of the Antarctic minke whale prior to whaling by sequencing 11 nuclear genetic markers from 52 modern samples purchased in Japanese meat markets. We use coalescent simulations to explore the potential influence of population substructure and find that even though our samples are drawn from a limited geographic area, our estimate reflects ocean-wide genetic diversity. Using Bayesian estimates of the mutation rate and coalescent-based analyses of genetic diversity across loci, we calculate the long-term population size of the Antarctic minke whale to be 670,000 individuals (95% confidence interval: 374,000-1,150,000). Our estimate of long-term abundance is similar to, or greater than, contemporary abundance estimates, suggesting that managing Antarctic ecosystems under the assumption that Antarctic minke whales are unusually abundant is not warranted.

Pre-Whaling Genetic Diversity and Population Ecology in Eastern Pacific Gray Whales: Insights from Ancient DNA and Stable Isotopes

PubMed Central

Alter, S. Elizabeth; Newsome, Seth D.; Palumbi, Stephen R.

2012-01-01

Commercial whaling decimated many whale populations, including the eastern Pacific gray whale, but little is known about how population dynamics or ecology differed prior to these removals. Of particular interest is the possibility of a large population decline prior to whaling, as such a decline could explain the ∼5-fold difference between genetic estimates of prior abundance and estimates based on historical records. We analyzed genetic (mitochondrial control region) and isotopic information from modern and prehistoric gray whales using serial coalescent simulations and Bayesian skyline analyses to test for a pre-whaling decline and to examine prehistoric genetic diversity, population dynamics and ecology. Simulations demonstrate that significant genetic differences observed between ancient and modern samples could be caused by a large, recent population bottleneck, roughly concurrent with commercial whaling. Stable isotopes show minimal differences between modern and ancient gray whale foraging ecology. Using rejection-based Approximate Bayesian Computation, we estimate the size of the population bottleneck at its minimum abundance and the pre-bottleneck abundance. Our results agree with previous genetic studies suggesting the historical size of the eastern gray whale population was roughly three to five times its current size. PMID:22590499

Marangoni-flow-induced partial coalescence of a droplet on a liquid/air interface

NASA Astrophysics Data System (ADS)

Sun, Kai; Zhang, Peng; Che, Zhizhao; Wang, Tianyou

2018-02-01

The coalescence of a droplet and a liquid/air interface of lower surface tension was numerically studied by using the lattice Boltzmann phase-field method. The experimental phenomenon of droplet ejection observed by Blanchette et al. [Phys. Fluids 21, 072107 (2009), 10.1063/1.3177339] at sufficiently large surface tension differences was successfully reproduced for the first time. Furthermore, the emergence, disappearance, and re-emergence of "partial coalescence" with increasing surface tension difference was observed and explained. The re-emergence of partial coalescence under large surface tension differences is caused by the remarkable lifting motion of the Marangoni flow, which significantly retards the vertical collapse. Two different modes of partial coalescence were identified by the simulation, namely peak injection occurs at lower Ohnesorge numbers and bottom pinch-off at higher Ohnesorge numbers. By comparing the characteristic timescales of the upward Marangoni flow with that of the downward flow driven by capillary pressure, a criterion for the transition from partial to total coalescence was derived based on scaling analysis and numerically validated.

An analysis of shock coalescence including three-dimensional effects with application to sonic boom extrapolation. Ph.D. Thesis - George Washington Univ.

NASA Technical Reports Server (NTRS)

Darden, C. M.

1984-01-01

A method for analyzing shock coalescence which includes three dimensional effects was developed. The method is based on an extension of the axisymmetric solution, with asymmetric effects introduced through an additional set of governing equations, derived by taking the second circumferential derivative of the standard shock equations in the plane of symmetry. The coalescence method is consistent with and has been combined with a nonlinear sonic boom extrapolation program which is based on the method of characteristics. The extrapolation program, is able to extrapolate pressure signatures which include embedded shocks from an initial data line in the plane of symmetry at approximately one body length from the axis of the aircraft to the ground. The axisymmetric shock coalescence solution, the asymmetric shock coalescence solution, the method of incorporating these solutions into the extrapolation program, and the methods used to determine spatial derivatives needed in the coalescence solution are described. Results of the method are shown for a body of revolution at a small, positive angle of attack.

Hepatitis C Virus Diversification in Argentina: Comparative Analysis between the Large City of Buenos Aires and the Small Rural Town of O'Brien

PubMed Central

Golemba, Marcelo D.; Culasso, Andrés C. A.; Villamil, Federico G.; Bare, Patricia; Gadano, Adrián; Ridruejo, Ezequiel; Martinez, Alfredo; Di Lello, Federico A.; Campos, Rodolfo H.

2013-01-01

Background The estimated prevalence of HCV infection in Argentina is around 2%. However, higher rates of infection have been described in population studies of small urban and rural communities. The aim of this work was to compare the origin and diversification of HCV-1b in samples from two different epidemiological scenarios: Buenos Aires, a large cosmopolitan city, and O'Brien, a small rural town with a high prevalence of HCV infection. Patients and Methods The E1/E2 and NS5B regions of the viral genome from 83 patients infected with HCV-1b were sequenced. Phylogenetic analysis and Bayesian Coalescent methods were used to study the origin and diversification of HCV-1b in both patient populations. Results Samples from Buenos Aires showed a polyphyletic behavior with a tMRCA around 1887–1900 and a time of spread of infection approximately 60 years ago. In contrast, samples from ÓBrien showed a monophyletic behavior with a tMRCA around 1950–1960 and a time of spread of infection more recent than in Buenos Aires, around 20–30 years ago. Conclusion Phylogenetic and coalescence analysis revealed a different behavior in the epidemiological histories of Buenos Aires and ÓBrien. HCV infection in Buenos Aires shows a polyphyletic behavior and an exponential growth in two phases, whereas that in O'Brien shows a monophyletic cluster and an exponential growth in one single step with a more recent tMRCA. The polyphyletic origin and the probability of encountering susceptible individuals in a large cosmopolitan city like Buenos Aires are in agreement with a longer period of expansion. In contrast, in less populated areas such as O'Brien, the chances of HCV transmission are strongly restricted. Furthermore, the monophyletic character and the most recent time of emergence suggest that different HCV-1b ancestors (variants) that were in expansion in Buenos Aires had the opportunity to colonize and expand in O’Brien. PMID:24386322

A stereological analysis of ductile fracture by microvoid coalescence

DOE Office of Scientific and Technical Information (OSTI.GOV)

Steele, J.H., Jr.

A stereological analysis for ductile fracture by microvoid coalescence is presented based upon the model of Widgery and Knott which postulates that microvoids link with a propagating crack if they lie within a certain interaction distance of its plane. A 3- dimensional analytical expression for dimple density and shape is developed from this model using projected image relationships for a thin slab. Void nucleation and growth are incorporated into the analysis using numerical integration of the Rice-Tracey growth equation over the appropriate strain range. An evaluation of the stereological approach is given using tensile data from a spheroidized 1045 steelmore » to predict the effect of hydrostatic pressure upon the dimple density. The analysis, which is consistent with observed correlations between dimple density and second phase particle density, is shown to provide an estimate of dimple size and microroughness parameter used in local stain models for microvoid coalescence. 24 refs., 10 figs.« less

Characterization of Solids Deposited on the Modular Caustic-Side Solvent Extraction Unit (MCU) Strip Effluent (SE) Coalescer Media Removed in April 2015

DOE Office of Scientific and Technical Information (OSTI.GOV)

Fondeur, F. F.

On June 2015, Savannah River National Laboratory (SRNL) received a Strip Effluent (SE) coalescer (FLT-304) from MCU. That coalescer was first installed at MCU in late October 2014 and removed in April 2015. While processing approximately 48,700 gallons of strip solution, the pressure drop steadily increased linearly from 1 psi to near 16 psi (the administrative limit is 17 psi) with the total filtrate volume (2.1E-4 psi/gal of filtrate). The linear behavior is due to the combined effect of a constant deposition of material that starts from the closed-end to the mid-section of the coalescer reducing the available surface areamore » of the coalescer for fluid passage (linearly with filtrate volume) and the formation of a secondary emulsion (water in NG-CSSX) on the fibers of the coalescer media. Both effects reduced the coalescer porosity by at least 13% (after processing 48,700 gallons). Before the coalescer was removed, it was flushed with a 10 mM boric acid solution to reduce the dose level. To determine the nature of the deposited material, a physical and chemical analysis of the coalescer was conducted. Characterization of this coalescer revealed the adsorption of organic containing amines (secondary amides and primary amines), TiDG, degraded modifier (with no hydroxyl group), MaxCalix, and oxidized hydrocarbon (possibly from Isopar™L or from lubricant used at MCU) onto the coalescer media. The amide and amines are possibly from the decomposition of the suppressor (TiDG). The modifier and MaxCalix were the largest components of the deposited organic material, as determined from leaching the coalescer with dichloromethane. Both the Fourier-Transformed Infrared (FTIR) and Fourier-Transformed Hydrogen Nuclear Magnetic Resonance (FT-HNMR) results indicated that some of the modifier was degraded (missing their OH groups). The modifier was observed everywhere in the examined coalescer pieces (FTIR), while the TiDG and its decomposition products were observed at the entrance discs of the coalescer. A solvent trim (a cocktail of solvent components with a high concentration of modifier) was added to the solvent on 2/22/2015. It is believed that the trim did not mix completely with the solvent and that it was subsequently spread around the MCU components including the coalescers, where it may have deposited. Chronologically, the modifier, the TiDG’s decomposition products and silicates deposited on the entrance discs first and after the pressure drop increased significantly, parts of the coalescer media detached itself from the central porous steel mandrel and a significant amount of steel debris, mercury, titanium, and additional aluminum and silicates deposited on the coalescer.« less

A Gentle Introduction to Bayesian Analysis: Applications to Developmental Research

ERIC Educational Resources Information Center

van de Schoot, Rens; Kaplan, David; Denissen, Jaap; Asendorpf, Jens B.; Neyer, Franz J.; van Aken, Marcel A. G.

2014-01-01

Bayesian statistical methods are becoming ever more popular in applied and fundamental research. In this study a gentle introduction to Bayesian analysis is provided. It is shown under what circumstances it is attractive to use Bayesian estimation, and how to interpret properly the results. First, the ingredients underlying Bayesian methods are…

The origin and phylogeography of dog rabies virus

PubMed Central

Bourhy, Hervé; Reynes, Jean-Marc; Dunham, Eleca J.; Dacheux, Laurent; Larrous, Florence; Huong, Vu Thi Que; Xu, Gelin; Yan, Jiaxin; Miranda, Mary Elizabeth G.; Holmes, Edward C.

2012-01-01

Rabies is a progressively fatal and incurable viral encephalitis caused by a lyssavirus infection. Almost all of the 55 000 annual rabies deaths in humans result from infection with dog rabies viruses (RABV). Despite the importance of rabies for human health, little is known about the spread of RABV in dog populations, and patterns of biodiversity have only been studied in limited geographical space. To address these questions on a global scale, we sequenced 62 new isolates and performed an extensive comparative analysis of RABV gene sequence data, representing 192 isolates sampled from 55 countries. From this, we identified six clades of RABV in non-flying mammals, each of which has a distinct geographical distribution, most likely reflecting major physical barriers to gene flow. Indeed, a detailed analysis of phylogeographic structure revealed only limited viral movement among geographical localities. Using Bayesian coalescent methods we also reveal that the sampled lineages of canid RABV derive from a common ancestor that originated within the past 1500 years. Additionally, we found no evidence for either positive selection or widespread population bottlenecks during the global expansion of canid RABV. Overall, our study reveals that the stochastic processes of genetic drift and population subdivision are the most important factors shaping the global phylogeography of canid RABV. PMID:18931062

Extensive cryptic species diversity and fine-scale endemism in the marine red alga Portieria in the Philippines

PubMed Central

Payo, Dioli Ann; Leliaert, Frederik; Verbruggen, Heroen; D'hondt, Sofie; Calumpong, Hilconida P.; De Clerck, Olivier

2013-01-01

We investigated species diversity and distribution patterns of the marine red alga Portieria in the Philippine archipelago. Species boundaries were tested based on mitochondrial, plastid and nuclear encoded loci, using a general mixed Yule-coalescent (GMYC) model-based approach and a Bayesian multilocus species delimitation method. The outcome of the GMYC analysis of the mitochondrial encoded cox2-3 dataset was highly congruent with the multilocus analysis. In stark contrast with the current morphology-based assumption that the genus includes a single, widely distributed species in the Indo-West Pacific (Portieria hornemannii), DNA-based species delimitation resulted in the recognition of 21 species within the Philippines. Species distributions were found to be highly structured with most species restricted to island groups within the archipelago. These extremely narrow species ranges and high levels of intra-archipelagic endemism contrast with the wide-held belief that marine organisms generally have large geographical ranges and that endemism is at most restricted to the archipelagic level. Our results indicate that speciation in the marine environment may occur at spatial scales smaller than 100 km, comparable with some terrestrial systems. Our finding of fine-scale endemism has important consequences for marine conservation and management. PMID:23269854

Bayesian data analysis in population ecology: motivations, methods, and benefits

USGS Publications Warehouse

Dorazio, Robert

2016-01-01

During the 20th century ecologists largely relied on the frequentist system of inference for the analysis of their data. However, in the past few decades ecologists have become increasingly interested in the use of Bayesian methods of data analysis. In this article I provide guidance to ecologists who would like to decide whether Bayesian methods can be used to improve their conclusions and predictions. I begin by providing a concise summary of Bayesian methods of analysis, including a comparison of differences between Bayesian and frequentist approaches to inference when using hierarchical models. Next I provide a list of problems where Bayesian methods of analysis may arguably be preferred over frequentist methods. These problems are usually encountered in analyses based on hierarchical models of data. I describe the essentials required for applying modern methods of Bayesian computation, and I use real-world examples to illustrate these methods. I conclude by summarizing what I perceive to be the main strengths and weaknesses of using Bayesian methods to solve ecological inference problems.

Analysis of Skylab IV fluid mechanic science demonstration

NASA Technical Reports Server (NTRS)

Klett, M. G.; Bourgeois, S. V.

1975-01-01

Several science demonstrations performed on Skylab III and IV were concerned with the behavior of fluid drops free floating in microgravity. These demonstrations, with large liquid drops, included the oscillation, rotation, impact and coalescence, and air injection into the drops. Rayleigh's analysis of the oscillation of spherical drops of a liquid predicts accurately the effect of size and surface tension on the frequency of vibrated water globules in the Skylab demonstration. However, damping occurred much faster than predicted by Lamb's or Scriven's analyses of the damping time for spherical drops. The impact demonstrations indicated that a minimum velocity is necessary to overcome surface forces and effect a coalescence, but a precise criterion for the coalescence of liquids in low g could not be determined.

Ultrafine particle and fiber production in micro-gravity

NASA Technical Reports Server (NTRS)

Webb, George W.

1987-01-01

The technique of evaporation and condensation of material in an inert gas is investigated for the purpose of preparing ultrafine particles (of order 10 nm in diameter) with a narrow distribution of sizes. Gravity-driven convection increases the rate of coalescence of the particles, leading to larger sizes and a broader distribution. Analysis and experimental efforts to investigate coalescence of particles are presented. The possibility of reducing coalescence in microgravity is discussed. An experimental test in reduced gravity to be performed in a KC135 aircraft is described briefly.

The Bayesian New Statistics: Hypothesis testing, estimation, meta-analysis, and power analysis from a Bayesian perspective.

PubMed

Kruschke, John K; Liddell, Torrin M

2018-02-01

In the practice of data analysis, there is a conceptual distinction between hypothesis testing, on the one hand, and estimation with quantified uncertainty on the other. Among frequentists in psychology, a shift of emphasis from hypothesis testing to estimation has been dubbed "the New Statistics" (Cumming 2014). A second conceptual distinction is between frequentist methods and Bayesian methods. Our main goal in this article is to explain how Bayesian methods achieve the goals of the New Statistics better than frequentist methods. The article reviews frequentist and Bayesian approaches to hypothesis testing and to estimation with confidence or credible intervals. The article also describes Bayesian approaches to meta-analysis, randomized controlled trials, and power analysis.

Nuclear genomic sequences reveal that polar bears are an old and distinct bear lineage.

PubMed

Hailer, Frank; Kutschera, Verena E; Hallström, Björn M; Klassert, Denise; Fain, Steven R; Leonard, Jennifer A; Arnason, Ulfur; Janke, Axel

2012-04-20

Recent studies have shown that the polar bear matriline (mitochondrial DNA) evolved from a brown bear lineage since the late Pleistocene, potentially indicating rapid speciation and adaption to arctic conditions. Here, we present a high-resolution data set from multiple independent loci across the nuclear genomes of a broad sample of polar, brown, and black bears. Bayesian coalescent analyses place polar bears outside the brown bear clade and date the divergence much earlier, in the middle Pleistocene, about 600 (338 to 934) thousand years ago. This provides more time for polar bear evolution and confirms previous suggestions that polar bears carry introgressed brown bear mitochondrial DNA due to past hybridization. Our results highlight that multilocus genomic analyses are crucial for an accurate understanding of evolutionary history.

Effects of waveform model systematics on the interpretation of GW150914

NASA Astrophysics Data System (ADS)

Abbott, B. P.; Abbott, R.; Abbott, T. D.; Abernathy, M. R.; Acernese, F.; Ackley, K.; Adams, C.; Adams, T.; Addesso, P.; Adhikari, R. X.; Adya, V. B.; Affeldt, C.; Agathos, M.; Agatsuma, K.; Aggarwal, N.; Aguiar, O. D.; Aiello, L.; Ain, A.; Ajith, P.; Allen, B.; Allocca, A.; Altin, P. A.; Ananyeva, A.; Anderson, S. B.; Anderson, W. G.; Appert, S.; Arai, K.; Araya, M. C.; Areeda, J. S.; Arnaud, N.; Arun, K. G.; Ascenzi, S.; Ashton, G.; Ast, M.; Aston, S. M.; Astone, P.; Aufmuth, P.; Aulbert, C.; Avila-Alvarez, A.; Babak, S.; Bacon, P.; Bader, M. K. M.; Baker, P. T.; Baldaccini, F.; Ballardin, G.; Ballmer, S. W.; Barayoga, J. C.; E Barclay, S.; Barish, B. C.; Barker, D.; Barone, F.; Barr, B.; Barsotti, L.; Barsuglia, M.; Barta, D.; Bartlett, J.; Bartos, I.; Bassiri, R.; Basti, A.; Batch, J. C.; Baune, C.; Bavigadda, V.; Bazzan, M.; Beer, C.; Bejger, M.; Belahcene, I.; Belgin, M.; Bell, A. S.; Berger, B. K.; Bergmann, G.; Berry, C. P. L.; Bersanetti, D.; Bertolini, A.; Betzwieser, J.; Bhagwat, S.; Bhandare, R.; Bilenko, I. A.; Billingsley, G.; Billman, C. R.; Birch, J.; Birney, R.; Birnholtz, O.; Biscans, S.; Bisht, A.; Bitossi, M.; Biwer, C.; Bizouard, M. A.; Blackburn, J. K.; Blackman, J.; Blair, C. D.; Blair, D. G.; Blair, R. M.; Bloemen, S.; Bock, O.; Boer, M.; Bogaert, G.; Bohe, A.; Bondu, F.; Bonnand, R.; Boom, B. A.; Bork, R.; Boschi, V.; Bose, S.; Bouffanais, Y.; Bozzi, A.; Bradaschia, C.; Brady, P. R.; Braginsky, V. B.; Branchesi, M.; E Brau, J.; Briant, T.; Brillet, A.; Brinkmann, M.; Brisson, V.; Brockill, P.; E Broida, J.; Brooks, A. F.; Brown, D. A.; Brown, D. D.; Brown, N. M.; Brunett, S.; Buchanan, C. C.; Buikema, A.; Bulik, T.; Bulten, H. J.; Buonanno, A.; Buskulic, D.; Buy, C.; Byer, R. L.; Cabero, M.; Cadonati, L.; Cagnoli, G.; Cahillane, C.; Calderón Bustillo, J.; Callister, T. A.; Calloni, E.; Camp, J. B.; Cannon, K. C.; Cao, H.; Cao, J.; Capano, C. D.; Capocasa, E.; Carbognani, F.; Caride, S.; Casanueva Diaz, J.; Casentini, C.; Caudill, S.; Cavaglià, M.; Cavalier, F.; Cavalieri, R.; Cella, G.; Cepeda, C. B.; Cerboni Baiardi, L.; Cerretani, G.; Cesarini, E.; Chamberlin, S. J.; Chan, M.; Chao, S.; Charlton, P.; Chassande-Mottin, E.; Cheeseboro, B. D.; Chen, H. Y.; Chen, Y.; Cheng, H.-P.; Chincarini, A.; Chiummo, A.; Chmiel, T.; Cho, H. S.; Cho, M.; Chow, J. H.; Christensen, N.; Chu, Q.; Chua, A. J. K.; Chua, S.; Chung, S.; Ciani, G.; Clara, F.; Clark, J. A.; Cleva, F.; Cocchieri, C.; Coccia, E.; Cohadon, P.-F.; Colla, A.; Collette, C. G.; Cominsky, L.; Constancio, M., Jr.; Conti, L.; Cooper, S. J.; Corbitt, T. R.; Cornish, N.; Corsi, A.; Cortese, S.; Costa, C. A.; Coughlin, M. W.; Coughlin, S. B.; Coulon, J.-P.; Countryman, S. T.; Couvares, P.; Covas, P. B.; E Cowan, E.; Coward, D. M.; Cowart, M. J.; Coyne, D. C.; Coyne, R.; E Creighton, J. D.; Creighton, T. D.; Cripe, J.; Crowder, S. G.; Cullen, T. J.; Cumming, A.; Cunningham, L.; Cuoco, E.; Dal Canton, T.; Danilishin, S. L.; D'Antonio, S.; Danzmann, K.; Dasgupta, A.; Da Silva Costa, C. F.; Dattilo, V.; Dave, I.; Davier, M.; Davies, G. S.; Davis, D.; Daw, E. J.; Day, B.; Day, R.; De, S.; DeBra, D.; Debreczeni, G.; Degallaix, J.; De Laurentis, M.; Deléglise, S.; Del Pozzo, W.; Denker, T.; Dent, T.; Dergachev, V.; De Rosa, R.; DeRosa, R. T.; DeSalvo, R.; Devenson, J.; Devine, R. C.; Dhurandhar, S.; Díaz, M. C.; Di Fiore, L.; Di Giovanni, M.; Di Girolamo, T.; Di Lieto, A.; Di Pace, S.; Di Palma, I.; Di Virgilio, A.; Doctor, Z.; Dolique, V.; Donovan, F.; Dooley, K. L.; Doravari, S.; Dorrington, I.; Douglas, R.; Dovale Álvarez, M.; Downes, T. P.; Drago, M.; Drever, R. W. P.; Driggers, J. C.; Du, Z.; Ducrot, M.; E Dwyer, S.; Edo, T. B.; Edwards, M. C.; Effler, A.; Eggenstein, H.-B.; Ehrens, P.; Eichholz, J.; Eikenberry, S. S.; Eisenstein, R. A.; Essick, R. C.; Etienne, Z.; Etzel, T.; Evans, M.; Evans, T. M.; Everett, R.; Factourovich, M.; Fafone, V.; Fair, H.; Fairhurst, S.; Fan, X.; Farinon, S.; Farr, B.; Farr, W. M.; Fauchon-Jones, E. J.; Favata, M.; Fays, M.; Fehrmann, H.; Fejer, M. M.; Fernández Galiana, A.; Ferrante, I.; Ferreira, E. C.; Ferrini, F.; Fidecaro, F.; Fiori, I.; Fiorucci, D.; Fisher, R. P.; Flaminio, R.; Fletcher, M.; Fong, H.; Forsyth, S. S.; Fournier, J.-D.; Frasca, S.; Frasconi, F.; Frei, Z.; Freise, A.; Frey, R.; Frey, V.; Fries, E. M.; Fritschel, P.; Frolov, V. V.; Fulda, P.; Fyffe, M.; Gabbard, H.; Gadre, B. U.; Gaebel, S. M.; Gair, J. R.; Gammaitoni, L.; Gaonkar, S. G.; Garufi, F.; Gaur, G.; Gayathri, V.; Gehrels, N.; Gemme, G.; Genin, E.; Gennai, A.; George, J.; Gergely, L.; Germain, V.; Ghonge, S.; Ghosh, Abhirup; Ghosh, Archisman; Ghosh, S.; Giaime, J. A.; Giardina, K. D.; Giazotto, A.; Gill, K.; Glaefke, A.; Goetz, E.; Goetz, R.; Gondan, L.; González, G.; Gonzalez Castro, J. M.; Gopakumar, A.; Gorodetsky, M. L.; E Gossan, S.; Gosselin, M.; Gouaty, R.; Grado, A.; Graef, C.; Granata, M.; Grant, A.; Gras, S.; Gray, C.; Greco, G.; Green, A. C.; Groot, P.; Grote, H.; Grunewald, S.; Guidi, G. M.; Guo, X.; Gupta, A.; Gupta, M. K.; E Gushwa, K.; Gustafson, E. K.; Gustafson, R.; Hacker, J. J.; Hall, B. R.; Hall, E. D.; Hammond, G.; Haney, M.; Hanke, M. M.; Hanks, J.; Hanna, C.; Hannam, M. D.; Hanson, J.; Hardwick, T.; Harms, J.; Harry, G. M.; Harry, I. W.; Hart, M. J.; Hartman, M. T.; Haster, C.-J.; Haughian, K.; Healy, J.; Heidmann, A.; Heintze, M. C.; Heitmann, H.; Hello, P.; Hemming, G.; Hendry, M.; Heng, I. S.; Hennig, J.; Henry, J.; Heptonstall, A. W.; Heurs, M.; Hild, S.; Hoak, D.; Hofman, D.; Holt, K.; E Holz, D.; Hopkins, P.; Hough, J.; Houston, E. A.; Howell, E. J.; Hu, Y. M.; Huerta, E. A.; Huet, D.; Hughey, B.; Husa, S.; Huttner, S. H.; Huynh-Dinh, T.; Indik, N.; Ingram, D. R.; Inta, R.; Isa, H. N.; Isac, J.-M.; Isi, M.; Isogai, T.; Iyer, B. R.; Izumi, K.; Jacqmin, T.; Jani, K.; Jaranowski, P.; Jawahar, S.; Jiménez-Forteza, F.; Johnson, W. W.; Jones, D. I.; Jones, R.; Jonker, R. J. G.; Ju, L.; Junker, J.; Kalaghatgi, C. V.; Kalogera, V.; Kandhasamy, S.; Kang, G.; Kanner, J. B.; Karki, S.; Karvinen, K. S.; Kasprzack, M.; Katsavounidis, E.; Katzman, W.; Kaufer, S.; Kaur, T.; Kawabe, K.; Kéfélian, F.; Keitel, D.; Kelley, D. B.; Kennedy, R.; Key, J. S.; Khalili, F. Y.; Khan, I.; Khan, S.; Khan, Z.; Khazanov, E. A.; Kijbunchoo, N.; Kim, Chunglee; Kim, J. C.; Kim, Whansun; Kim, W.; Kim, Y.-M.; Kimbrell, S. J.; King, E. J.; King, P. J.; Kirchhoff, R.; Kissel, J. S.; Klein, B.; Kleybolte, L.; Klimenko, S.; Koch, P.; Koehlenbeck, S. M.; Koley, S.; Kondrashov, V.; Kontos, A.; Korobko, M.; Korth, W. Z.; Kowalska, I.; Kozak, D. B.; Krämer, C.; Kringel, V.; Krishnan, B.; Królak, A.; Kuehn, G.; Kumar, P.; Kumar, R.; Kuo, L.; Kutynia, A.; Lackey, B. D.; Landry, M.; Lang, R. N.; Lange, J.; Lantz, B.; Lanza, R. K.; Lartaux-Vollard, A.; Lasky, P. D.; Laxen, M.; Lazzarini, A.; Lazzaro, C.; Leaci, P.; Leavey, S.; Lebigot, E. O.; Lee, C. H.; Lee, H. K.; Lee, H. M.; Lee, K.; Lehmann, J.; Lenon, A.; Leonardi, M.; Leong, J. R.; Leroy, N.; Letendre, N.; Levin, Y.; Li, T. G. F.; Libson, A.; Littenberg, T. B.; Liu, J.; Lockerbie, N. A.; Lombardi, A. L.; London, L. T.; E Lord, J.; Lorenzini, M.; Loriette, V.; Lormand, M.; Losurdo, G.; Lough, J. D.; Lovelace, G.; Lück, H.; Lundgren, A. P.; Lynch, R.; Ma, Y.; Macfoy, S.; Machenschalk, B.; MacInnis, M.; Macleod, D. M.; Magaña-Sandoval, F.; Majorana, E.; Maksimovic, I.; Malvezzi, V.; Man, N.; Mandic, V.; Mangano, V.; Mansell, G. L.; Manske, M.; Mantovani, M.; Marchesoni, F.; Marion, F.; Márka, S.; Márka, Z.; Markosyan, A. S.; Maros, E.; Martelli, F.; Martellini, L.; Martin, I. W.; Martynov, D. V.; Mason, K.; Masserot, A.; Massinger, T. J.; Masso-Reid, M.; Mastrogiovanni, S.; Matichard, F.; Matone, L.; Mavalvala, N.; Mazumder, N.; McCarthy, R.; E McClelland, D.; McCormick, S.; McGrath, C.; McGuire, S. C.; McIntyre, G.; McIver, J.; McManus, D. J.; McRae, T.; McWilliams, S. T.; Meacher, D.; Meadors, G. D.; Meidam, J.; Melatos, A.; Mendell, G.; Mendoza-Gandara, D.; Mercer, R. A.; Merilh, E. L.; Merzougui, M.; Meshkov, S.; Messenger, C.; Messick, C.; Metzdorff, R.; Meyers, P. M.; Mezzani, F.; Miao, H.; Michel, C.; Middleton, H.; E Mikhailov, E.; Milano, L.; Miller, A. L.; Miller, A.; Miller, B. B.; Miller, J.; Millhouse, M.; Minenkov, Y.; Ming, J.; Mirshekari, S.; Mishra, C.; Mitra, S.; Mitrofanov, V. P.; Mitselmakher, G.; Mittleman, R.; Moggi, A.; Mohan, M.; Mohapatra, S. R. P.; Montani, M.; Moore, B. C.; Moore, C. J.; Moraru, D.; Moreno, G.; Morriss, S. R.; Mours, B.; Mow-Lowry, C. M.; Mueller, G.; Muir, A. W.; Mukherjee, Arunava; Mukherjee, D.; Mukherjee, S.; Mukund, N.; Mullavey, A.; Munch, J.; Muniz, E. A. M.; Murray, P. G.; Mytidis, A.; Napier, K.; Nardecchia, I.; Naticchioni, L.; Nelemans, G.; Nelson, T. J. N.; Neri, M.; Nery, M.; Neunzert, A.; Newport, J. M.; Newton, G.; Nguyen, T. T.; Nielsen, A. B.; Nissanke, S.; Nitz, A.; Noack, A.; Nocera, F.; Nolting, D.; Normandin, M. E. N.; Nuttall, L. K.; Oberling, J.; Ochsner, E.; Oelker, E.; Ogin, G. H.; Oh, J. J.; Oh, S. H.; Ohme, F.; Oliver, M.; Oppermann, P.; Oram, Richard J.; O'Reilly, B.; O'Shaughnessy, R.; Ottaway, D. J.; Overmier, H.; Owen, B. J.; E Pace, A.; Page, J.; Pai, A.; Pai, S. A.; Palamos, J. R.; Palashov, O.; Palomba, C.; Pal-Singh, A.; Pan, H.; Pankow, C.; Pannarale, F.; Pant, B. C.; Paoletti, F.; Paoli, A.; Papa, M. A.; Paris, H. R.; Parker, W.; Pascucci, D.; Pasqualetti, A.; Passaquieti, R.; Passuello, D.; Patricelli, B.; Pearlstone, B. L.; Pedraza, M.; Pedurand, R.; Pekowsky, L.; Pele, A.; Penn, S.; Perez, C. J.; Perreca, A.; Perri, L. M.; Pfeiffer, H. P.; Phelps, M.; Piccinni, O. J.; Pichot, M.; Piergiovanni, F.; Pierro, V.; Pillant, G.; Pinard, L.; Pinto, I. M.; Pitkin, M.; Poe, M.; Poggiani, R.; Popolizio, P.; Post, A.; Powell, J.; Prasad, J.; Pratt, J. W. W.; Predoi, V.; Prestegard, T.; Prijatelj, M.; Principe, M.; Privitera, S.; Prodi, G. A.; Prokhorov, L. G.; Puncken, O.; Punturo, M.; Puppo, P.; Pürrer, M.; Qi, H.; Qin, J.; Qiu, S.; Quetschke, V.; Quintero, E. A.; Quitzow-James, R.; Raab, F. J.; Rabeling, D. S.; Radkins, H.; Raffai, P.; Raja, S.; Rajan, C.; Rakhmanov, M.; Rapagnani, P.; Raymond, V.; Razzano, M.; Re, V.; Read, J.; Regimbau, T.; Rei, L.; Reid, S.; Reitze, D. H.; Rew, H.; Reyes, S. D.; Rhoades, E.; Ricci, F.; Riles, K.; Rizzo, M.; Robertson, N. A.; Robie, R.; Robinet, F.; Rocchi, A.; Rolland, L.; Rollins, J. G.; Roma, V. J.; Romano, J. D.; Romano, R.; Romie, J. H.; Rosińska, D.; Rowan, S.; Rüdiger, A.; Ruggi, P.; Ryan, K.; Sachdev, S.; Sadecki, T.; Sadeghian, L.; Sakellariadou, M.; Salconi, L.; Saleem, M.; Salemi, F.; Samajdar, A.; Sammut, L.; Sampson, L. M.; Sanchez, E. J.; Sandberg, V.; Sanders, J. R.; Sassolas, B.; Sathyaprakash, B. S.; Saulson, P. R.; Sauter, O.; Savage, R. L.; Sawadsky, A.; Schale, P.; Scheuer, J.; Schmidt, E.; Schmidt, J.; Schmidt, P.; Schnabel, R.; Schofield, R. M. S.; Schönbeck, A.; Schreiber, E.; Schuette, D.; Schutz, B. F.; Schwalbe, S. G.; Scott, J.; Scott, S. M.; Sellers, D.; Sengupta, A. S.; Sentenac, D.; Sequino, V.; Sergeev, A.; Setyawati, Y.; Shaddock, D. A.; Shaffer, T. J.; Shahriar, M. S.; Shapiro, B.; Shawhan, P.; Sheperd, A.; Shoemaker, D. H.; Shoemaker, D. M.; Siellez, K.; Siemens, X.; Sieniawska, M.; Sigg, D.; Silva, A. D.; Singer, A.; Singer, L. P.; Singh, A.; Singh, R.; Singhal, A.; Sintes, A. M.; Slagmolen, B. J. J.; Smith, B.; Smith, J. R.; E Smith, R. J.; Son, E. J.; Sorazu, B.; Sorrentino, F.; Souradeep, T.; Spencer, A. P.; Srivastava, A. K.; Staley, A.; Steinke, M.; Steinlechner, J.; Steinlechner, S.; Steinmeyer, D.; Stephens, B. C.; Stevenson, S. P.; Stone, R.; Strain, K. A.; Straniero, N.; Stratta, G.; E Strigin, S.; Sturani, R.; Stuver, A. L.; Summerscales, T. Z.; Sun, L.; Sunil, S.; Sutton, P. J.; Swinkels, B. L.; Szczepańczyk, M. J.; Tacca, M.; Talukder, D.; Tanner, D. B.; Tápai, M.; Taracchini, A.; Taylor, R.; Theeg, T.; Thomas, E. G.; Thomas, M.; Thomas, P.; Thorne, K. A.; Thrane, E.; Tippens, T.; Tiwari, S.; Tiwari, V.; Tokmakov, K. V.; Toland, K.; Tomlinson, C.; Tonelli, M.; Tornasi, Z.; Torrie, C. I.; Töyrä, D.; Travasso, F.; Traylor, G.; Trifirò, D.; Trinastic, J.; Tringali, M. C.; Trozzo, L.; Tse, M.; Tso, R.; Turconi, M.; Tuyenbayev, D.; Ugolini, D.; Unnikrishnan, C. S.; Urban, A. L.; Usman, S. A.; Vahlbruch, H.; Vajente, G.; Valdes, G.; van Bakel, N.; van Beuzekom, M.; van den Brand, J. F. J.; Van Den Broeck, C.; Vander-Hyde, D. C.; van der Schaaf, L.; van Heijningen, J. V.; van Veggel, A. A.; Vardaro, M.; Varma, V.; Vass, S.; Vasúth, M.; Vecchio, A.; Vedovato, G.; Veitch, J.; Veitch, P. J.; Venkateswara, K.; Venugopalan, G.; Verkindt, D.; Vetrano, F.; Viceré, A.; Viets, A. D.; Vinciguerra, S.; Vine, D. J.; Vinet, J.-Y.; Vitale, S.; Vo, T.; Vocca, H.; Vorvick, C.; Voss, D. V.; Vousden, W. D.; Vyatchanin, S. P.; Wade, A. R.; E Wade, L.; Wade, M.; Walker, M.; Wallace, L.; Walsh, S.; Wang, G.; Wang, H.; Wang, M.; Wang, Y.; Ward, R. L.; Warner, J.; Was, M.; Watchi, J.; Weaver, B.; Wei, L.-W.; Weinert, M.; Weinstein, A. J.; Weiss, R.; Wen, L.; Weßels, P.; Westphal, T.; Wette, K.; Whelan, J. T.; Whiting, B. F.; Whittle, C.; Williams, D.; Williams, R. D.; Williamson, A. R.; Willis, J. L.; Willke, B.; Wimmer, M. H.; Winkler, W.; Wipf, C. C.; Wittel, H.; Woan, G.; Woehler, J.; Worden, J.; Wright, J. L.; Wu, D. S.; Wu, G.; Yam, W.; Yamamoto, H.; Yancey, C. C.; Yap, M. J.; Yu, Hang; Yu, Haocun; Yvert, M.; Zadrożny, A.; Zangrando, L.; Zanolin, M.; Zendri, J.-P.; Zevin, M.; Zhang, L.; Zhang, M.; Zhang, T.; Zhang, Y.; Zhao, C.; Zhou, M.; Zhou, Z.; Zhu, S. J.; Zhu, X. J.; E Zucker, M.; Zweizig, J.; LIGO Scientific Collaboration; Virgo Collaboration; Boyle, M.; Chu, T.; Hemberger, D.; Hinder, I.; E Kidder, L.; Ossokine, S.; Scheel, M.; Szilagyi, B.; Teukolsky, S.; Vano Vinuales, A.

2017-05-01

Parameter estimates of GW150914 were obtained using Bayesian inference, based on three semi-analytic waveform models for binary black hole coalescences. These waveform models differ from each other in their treatment of black hole spins, and all three models make some simplifying assumptions, notably to neglect sub-dominant waveform harmonic modes and orbital eccentricity. Furthermore, while the models are calibrated to agree with waveforms obtained by full numerical solutions of Einstein’s equations, any such calibration is accurate only to some non-zero tolerance and is limited by the accuracy of the underlying phenomenology, availability, quality, and parameter-space coverage of numerical simulations. This paper complements the original analyses of GW150914 with an investigation of the effects of possible systematic errors in the waveform models on estimates of its source parameters. To test for systematic errors we repeat the original Bayesian analysis on mock signals from numerical simulations of a series of binary configurations with parameters similar to those found for GW150914. Overall, we find no evidence for a systematic bias relative to the statistical error of the original parameter recovery of GW150914 due to modeling approximations or modeling inaccuracies. However, parameter biases are found to occur for some configurations disfavored by the data of GW150914: for binaries inclined edge-on to the detector over a small range of choices of polarization angles, and also for eccentricities greater than  ˜0.05. For signals with higher signal-to-noise ratio than GW150914, or in other regions of the binary parameter space (lower masses, larger mass ratios, or higher spins), we expect that systematic errors in current waveform models may impact gravitational-wave measurements, making more accurate models desirable for future observations.

Is probabilistic bias analysis approximately Bayesian?

PubMed Central

MacLehose, Richard F.; Gustafson, Paul

2011-01-01

Case-control studies are particularly susceptible to differential exposure misclassification when exposure status is determined following incident case status. Probabilistic bias analysis methods have been developed as ways to adjust standard effect estimates based on the sensitivity and specificity of exposure misclassification. The iterative sampling method advocated in probabilistic bias analysis bears a distinct resemblance to a Bayesian adjustment; however, it is not identical. Furthermore, without a formal theoretical framework (Bayesian or frequentist), the results of a probabilistic bias analysis remain somewhat difficult to interpret. We describe, both theoretically and empirically, the extent to which probabilistic bias analysis can be viewed as approximately Bayesian. While the differences between probabilistic bias analysis and Bayesian approaches to misclassification can be substantial, these situations often involve unrealistic prior specifications and are relatively easy to detect. Outside of these special cases, probabilistic bias analysis and Bayesian approaches to exposure misclassification in case-control studies appear to perform equally well. PMID:22157311

Bayesian Mediation Analysis

ERIC Educational Resources Information Center

Yuan, Ying; MacKinnon, David P.

2009-01-01

In this article, we propose Bayesian analysis of mediation effects. Compared with conventional frequentist mediation analysis, the Bayesian approach has several advantages. First, it allows researchers to incorporate prior information into the mediation analysis, thus potentially improving the efficiency of estimates. Second, under the Bayesian…

Shear driven droplet shedding and coalescence on a superhydrophobic surface

NASA Astrophysics Data System (ADS)

Moghtadernejad, S.; Tembely, M.; Jadidi, M.; Esmail, N.; Dolatabadi, A.

2015-03-01

The interest on shedding and coalescence of sessile droplets arises from the importance of these phenomena in various scientific problems and industrial applications such as ice formation on wind turbine blades, power lines, nacelles, and aircraft wings. It is shown recently that one of the ways to reduce the probability of ice accretion on industrial components is using superhydrophobic coatings due to their low adhesion to water droplets. In this study, a combined experimental and numerical approach is used to investigate droplet shedding and coalescence phenomena under the influence of air shear flow on a superhydrophobic surface. Droplets with a size of 2 mm are subjected to various air speeds ranging from 5 to 90 m/s. A numerical simulation based on the Volume of Fluid method coupled with the Large Eddy Simulation turbulent model is carried out in conjunction with the validating experiments to shed more light on the coalescence of droplets and detachment phenomena through a detailed analysis of the aerodynamics forces and velocity vectors on the droplet and the streamlines around it. The results indicate a contrast in the mechanism of two-droplet coalescence and subsequent detachment with those related to the case of a single droplet shedding. At lower speeds, the two droplets coalesce by attracting each other with successive rebounds of the merged droplet on the substrate, while at higher speeds, the detachment occurs almost instantly after coalescence, with a detachment time decreasing exponentially with the air speed. It is shown that coalescence phenomenon assists droplet detachment from the superhydrophobic substrate at lower air speeds.

Prior approval: the growth of Bayesian methods in psychology.

PubMed

Andrews, Mark; Baguley, Thom

2013-02-01

Within the last few years, Bayesian methods of data analysis in psychology have proliferated. In this paper, we briefly review the history or the Bayesian approach to statistics, and consider the implications that Bayesian methods have for the theory and practice of data analysis in psychology.

Bayesian Divergence-Time Estimation with Genome-Wide SNP Data of Sea Catfishes (Ariidae) Supports Miocene Closure of the Panamanian Isthmus.

PubMed

Stange, Madlen; Sánchez-Villagra, Marcelo R; Salzburger, Walter; Matschiner, Michael

2018-01-27

The closure of the Isthmus of Panama has long been considered to be one of the best defined biogeographic calibration points for molecular divergence-time estimation. However, geological and biological evidence has recently cast doubt on the presumed timing of the initial isthmus closure around 3 Ma but has instead suggested the existence of temporary land bridges as early as the Middle or Late Miocene. The biological evidence supporting these earlier land bridges was based either on only few molecular markers or on concatenation of genome-wide sequence data, an approach that is known to result in potentially misleading branch lengths and divergence times, which could compromise the reliability of this evidence. To allow divergence-time estimation with genomic data using the more appropriate multi-species coalescent model, we here develop a new method combining the SNP-based Bayesian species-tree inference of the software SNAPP with a molecular clock model that can be calibrated with fossil or biogeographic constraints. We validate our approach with simulations and use our method to reanalyze genomic data of Neotropical army ants (Dorylinae) that previously supported divergence times of Central and South American populations before the isthmus closure around 3 Ma. Our reanalysis with the multi-species coalescent model shifts all of these divergence times to ages younger than 3 Ma, suggesting that the older estimates supporting the earlier existence of temporary land bridges were artifacts resulting at least partially from the use of concatenation. We then apply our method to a new RAD-sequencing data set of Neotropical sea catfishes (Ariidae) and calibrate their species tree with extensive information from the fossil record. We identify a series of divergences between groups of Caribbean and Pacific sea catfishes around 10 Ma, indicating that processes related to the emergence of the isthmus led to vicariant speciation already in the Late Miocene, millions of years before the final isthmus closure. © The Author(s) 2018. Published by Oxford University Press, on behalf of the Society of Systematic Biologists.

Bayesian Model Averaging for Propensity Score Analysis

ERIC Educational Resources Information Center

Kaplan, David; Chen, Jianshen

2013-01-01

The purpose of this study is to explore Bayesian model averaging in the propensity score context. Previous research on Bayesian propensity score analysis does not take into account model uncertainty. In this regard, an internally consistent Bayesian framework for model building and estimation must also account for model uncertainty. The…

The phylodynamics of the rabies virus in the Russian Federation

PubMed Central

Lukashev, Alexander N.; Poleshchuk, Elena M.; Dedkov, Vladimir G.; Tkachev, Sergey E.; Sidorov, Gennadiy N.; Karganova, Galina G.; Galkina, Irina V.; Shchelkanov, Mikhail Yu.; Shipulin, German A.

2017-01-01

Near complete rabies virus N gene sequences (1,110 nt) were determined for 82 isolates obtained from different regions of Russia between 2008 and 2016. These sequences were analyzed together with 108 representative GenBank sequences from 1977–2016 using the Bayesian coalescent approach. The timing of the major evolutionary events was estimated. Most of the isolates represented the steppe rabies virus group C, which was found over a vast geographic region from Central Russia to Mongolia and split into three groups (C0-C2) with discrete geographic prevalence. A single strain of the steppe rabies virus lineage was isolated in the far eastern part of Russia (Primorsky Krai), likely as a result of a recent anthropogenic introduction. For the first time the polar rabies virus group A2, previously reported in Alaska, was described in the northern part of European Russia and at the Franz Josef Land. Phylogenetic analysis suggested that all currently circulating rabies virus groups in the Russian Federation were introduced within the few last centuries, with most of the groups spreading in the 20th century. The dating of evolutionary events was highly concordant with the historical epidemiological data. PMID:28225771

Estimating diversifying selection and functional constraint in the presence of recombination.

PubMed

Wilson, Daniel J; McVean, Gilean

2006-03-01

Models of molecular evolution that incorporate the ratio of nonsynonymous to synonymous polymorphism (dN/dS ratio) as a parameter can be used to identify sites that are under diversifying selection or functional constraint in a sample of gene sequences. However, when there has been recombination in the evolutionary history of the sequences, reconstructing a single phylogenetic tree is not appropriate, and inference based on a single tree can give misleading results. In the presence of high levels of recombination, the identification of sites experiencing diversifying selection can suffer from a false-positive rate as high as 90%. We present a model that uses a population genetics approximation to the coalescent with recombination and use reversible-jump MCMC to perform Bayesian inference on both the dN/dS ratio and the recombination rate, allowing each to vary along the sequence. We demonstrate that the method has the power to detect variation in the dN/dS ratio and the recombination rate and does not suffer from a high false-positive rate. We use the method to analyze the porB gene of Neisseria meningitidis and verify the inferences using prior sensitivity analysis and model criticism techniques.

Estimating Diversifying Selection and Functional Constraint in the Presence of Recombination

PubMed Central

Wilson, Daniel J.; McVean, Gilean

2006-01-01

Models of molecular evolution that incorporate the ratio of nonsynonymous to synonymous polymorphism (dN/dS ratio) as a parameter can be used to identify sites that are under diversifying selection or functional constraint in a sample of gene sequences. However, when there has been recombination in the evolutionary history of the sequences, reconstructing a single phylogenetic tree is not appropriate, and inference based on a single tree can give misleading results. In the presence of high levels of recombination, the identification of sites experiencing diversifying selection can suffer from a false-positive rate as high as 90%. We present a model that uses a population genetics approximation to the coalescent with recombination and use reversible-jump MCMC to perform Bayesian inference on both the dN/dS ratio and the recombination rate, allowing each to vary along the sequence. We demonstrate that the method has the power to detect variation in the dN/dS ratio and the recombination rate and does not suffer from a high false-positive rate. We use the method to analyze the porB gene of Neisseria meningitidis and verify the inferences using prior sensitivity analysis and model criticism techniques. PMID:16387887

Measurements of the Young's modulus of hydroxide catalysis bonds, and the effect on thermal noise in ground-based gravitational wave detectors

NASA Astrophysics Data System (ADS)

Phelps, Margot; van Veggel, Anna-Maria; Hough, James; Messenger, Chris; Hughes, David; Cunningham, William; Haughian, Karen; Rowan, Sheila

2018-05-01

With the outstanding results from the detection and observation of gravitational waves from coalescing black holes and neutron star inspirals, it is essential that pathways to further improve the sensitivities of the LIGO and VIRGO detectors are explored. There are a number of factors that potentially limit the sensitivities of the detectors. One such factor is thermal noise, a component of which results from the mechanical loss in the bond material between the silica fibre suspensions and the test mass mirrors. To calculate its magnitude, the Young's modulus of the bond material has to be known with reasonable accuracy. In this paper we present a new combination of ultrasonic technology and Bayesian analysis to measure the Young's modulus of hydroxide catalysis bonds between fused silica substrates. Using this novel technique, we measure the bond Young's modulus to be 18.5 ±2.32.0 GPa . We show that by applying this value to thermal noise models of bonded test masses with suitable attachment geometries, a reduction in suspension thermal noise consistent with an overall design sensitivity improvement allows a factor of 5 increase in event rate to be achieved.

Bayesian analyses of time-interval data for environmental radiation monitoring.

PubMed

Luo, Peng; Sharp, Julia L; DeVol, Timothy A

2013-01-01

Time-interval (time difference between two consecutive pulses) analysis based on the principles of Bayesian inference was investigated for online radiation monitoring. Using experimental and simulated data, Bayesian analysis of time-interval data [Bayesian (ti)] was compared with Bayesian and a conventional frequentist analysis of counts in a fixed count time [Bayesian (cnt) and single interval test (SIT), respectively]. The performances of the three methods were compared in terms of average run length (ARL) and detection probability for several simulated detection scenarios. Experimental data were acquired with a DGF-4C system in list mode. Simulated data were obtained using Monte Carlo techniques to obtain a random sampling of the Poisson distribution. All statistical algorithms were developed using the R Project for statistical computing. Bayesian analysis of time-interval information provided a similar detection probability as Bayesian analysis of count information, but the authors were able to make a decision with fewer pulses at relatively higher radiation levels. In addition, for the cases with very short presence of the source (< count time), time-interval information is more sensitive to detect a change than count information since the source data is averaged by the background data over the entire count time. The relationships of the source time, change points, and modifications to the Bayesian approach for increasing detection probability are presented.

A SAS Interface for Bayesian Analysis with WinBUGS

ERIC Educational Resources Information Center

Zhang, Zhiyong; McArdle, John J.; Wang, Lijuan; Hamagami, Fumiaki

2008-01-01

Bayesian methods are becoming very popular despite some practical difficulties in implementation. To assist in the practical application of Bayesian methods, we show how to implement Bayesian analysis with WinBUGS as part of a standard set of SAS routines. This implementation procedure is first illustrated by fitting a multiple regression model…

A Gentle Introduction to Bayesian Analysis: Applications to Developmental Research

PubMed Central

van de Schoot, Rens; Kaplan, David; Denissen, Jaap; Asendorpf, Jens B; Neyer, Franz J; van Aken, Marcel AG

2014-01-01

Bayesian statistical methods are becoming ever more popular in applied and fundamental research. In this study a gentle introduction to Bayesian analysis is provided. It is shown under what circumstances it is attractive to use Bayesian estimation, and how to interpret properly the results. First, the ingredients underlying Bayesian methods are introduced using a simplified example. Thereafter, the advantages and pitfalls of the specification of prior knowledge are discussed. To illustrate Bayesian methods explained in this study, in a second example a series of studies that examine the theoretical framework of dynamic interactionism are considered. In the Discussion the advantages and disadvantages of using Bayesian statistics are reviewed, and guidelines on how to report on Bayesian statistics are provided. PMID:24116396

APPLICATION OF BAYESIAN MONTE CARLO ANALYSIS TO A LAGRANGIAN PHOTOCHEMICAL AIR QUALITY MODEL. (R824792)

EPA Science Inventory

Uncertainties in ozone concentrations predicted with a Lagrangian photochemical air quality model have been estimated using Bayesian Monte Carlo (BMC) analysis. Bayesian Monte Carlo analysis provides a means of combining subjective "prior" uncertainty estimates developed ...

Demographic Divergence History of Pied Flycatcher and Collared Flycatcher Inferred from Whole-Genome Re-sequencing Data

PubMed Central

Nadachowska-Brzyska, Krystyna; Burri, Reto; Olason, Pall I.; Kawakami, Takeshi; Smeds, Linnéa; Ellegren, Hans

2013-01-01

Profound knowledge of demographic history is a prerequisite for the understanding and inference of processes involved in the evolution of population differentiation and speciation. Together with new coalescent-based methods, the recent availability of genome-wide data enables investigation of differentiation and divergence processes at unprecedented depth. We combined two powerful approaches, full Approximate Bayesian Computation analysis (ABC) and pairwise sequentially Markovian coalescent modeling (PSMC), to reconstruct the demographic history of the split between two avian speciation model species, the pied flycatcher and collared flycatcher. Using whole-genome re-sequencing data from 20 individuals, we investigated 15 demographic models including different levels and patterns of gene flow, and changes in effective population size over time. ABC provided high support for recent (mode 0.3 my, range <0.7 my) species divergence, declines in effective population size of both species since their initial divergence, and unidirectional recent gene flow from pied flycatcher into collared flycatcher. The estimated divergence time and population size changes, supported by PSMC results, suggest that the ancestral species persisted through one of the glacial periods of middle Pleistocene and then split into two large populations that first increased in size before going through severe bottlenecks and expanding into their current ranges. Secondary contact appears to have been established after the last glacial maximum. The severity of the bottlenecks at the last glacial maximum is indicated by the discrepancy between current effective population sizes (20,000–80,000) and census sizes (5–50 million birds) of the two species. The recent divergence time challenges the supposition that avian speciation is a relatively slow process with extended times for intrinsic postzygotic reproductive barriers to evolve. Our study emphasizes the importance of using genome-wide data to unravel tangled demographic histories. Moreover, it constitutes one of the first examples of the inference of divergence history from genome-wide data in non-model species. PMID:24244198

Demographic divergence history of pied flycatcher and collared flycatcher inferred from whole-genome re-sequencing data.

PubMed

Nadachowska-Brzyska, Krystyna; Burri, Reto; Olason, Pall I; Kawakami, Takeshi; Smeds, Linnéa; Ellegren, Hans

2013-11-01

Profound knowledge of demographic history is a prerequisite for the understanding and inference of processes involved in the evolution of population differentiation and speciation. Together with new coalescent-based methods, the recent availability of genome-wide data enables investigation of differentiation and divergence processes at unprecedented depth. We combined two powerful approaches, full Approximate Bayesian Computation analysis (ABC) and pairwise sequentially Markovian coalescent modeling (PSMC), to reconstruct the demographic history of the split between two avian speciation model species, the pied flycatcher and collared flycatcher. Using whole-genome re-sequencing data from 20 individuals, we investigated 15 demographic models including different levels and patterns of gene flow, and changes in effective population size over time. ABC provided high support for recent (mode 0.3 my, range <0.7 my) species divergence, declines in effective population size of both species since their initial divergence, and unidirectional recent gene flow from pied flycatcher into collared flycatcher. The estimated divergence time and population size changes, supported by PSMC results, suggest that the ancestral species persisted through one of the glacial periods of middle Pleistocene and then split into two large populations that first increased in size before going through severe bottlenecks and expanding into their current ranges. Secondary contact appears to have been established after the last glacial maximum. The severity of the bottlenecks at the last glacial maximum is indicated by the discrepancy between current effective population sizes (20,000-80,000) and census sizes (5-50 million birds) of the two species. The recent divergence time challenges the supposition that avian speciation is a relatively slow process with extended times for intrinsic postzygotic reproductive barriers to evolve. Our study emphasizes the importance of using genome-wide data to unravel tangled demographic histories. Moreover, it constitutes one of the first examples of the inference of divergence history from genome-wide data in non-model species.

Absorption of charged particulate surfactants in microfluidics

NASA Astrophysics Data System (ADS)

Kong, Tiantian; Liu, Zhou; Yao, Xiaoxue; Liu, Yaming

2017-11-01

We use microfluidics to uncouple the generation of Pickering emulsion droplets and stability analysis against coalescence. By designing the microchannels, we control the packing time for charged particles arriving at the droplet interfaces, and subsequently test the droplet stability in a coalescence chamber. The critical particle coverage on interfaces that prevents coalescence are estimated by an adsorption model. We further investigate the dependence of the critical particle coverage on its properties such as particle sizes, surface charge densities, and bulk concentrations. Our studies are potentially beneficial to the applications involving particle-stabilized droplets including cosmetics, food products, and oil recovery. NSFC 11504238,JCYJ20160308092144035,2016A050503048.

Bayesian survival analysis in clinical trials: What methods are used in practice?

PubMed

Brard, Caroline; Le Teuff, Gwénaël; Le Deley, Marie-Cécile; Hampson, Lisa V

2017-02-01

Background Bayesian statistics are an appealing alternative to the traditional frequentist approach to designing, analysing, and reporting of clinical trials, especially in rare diseases. Time-to-event endpoints are widely used in many medical fields. There are additional complexities to designing Bayesian survival trials which arise from the need to specify a model for the survival distribution. The objective of this article was to critically review the use and reporting of Bayesian methods in survival trials. Methods A systematic review of clinical trials using Bayesian survival analyses was performed through PubMed and Web of Science databases. This was complemented by a full text search of the online repositories of pre-selected journals. Cost-effectiveness, dose-finding studies, meta-analyses, and methodological papers using clinical trials were excluded. Results In total, 28 articles met the inclusion criteria, 25 were original reports of clinical trials and 3 were re-analyses of a clinical trial. Most trials were in oncology (n = 25), were randomised controlled (n = 21) phase III trials (n = 13), and half considered a rare disease (n = 13). Bayesian approaches were used for monitoring in 14 trials and for the final analysis only in 14 trials. In the latter case, Bayesian survival analyses were used for the primary analysis in four cases, for the secondary analysis in seven cases, and for the trial re-analysis in three cases. Overall, 12 articles reported fitting Bayesian regression models (semi-parametric, n = 3; parametric, n = 9). Prior distributions were often incompletely reported: 20 articles did not define the prior distribution used for the parameter of interest. Over half of the trials used only non-informative priors for monitoring and the final analysis (n = 12) when it was specified. Indeed, no articles fitting Bayesian regression models placed informative priors on the parameter of interest. The prior for the treatment effect was based on historical data in only four trials. Decision rules were pre-defined in eight cases when trials used Bayesian monitoring, and in only one case when trials adopted a Bayesian approach to the final analysis. Conclusion Few trials implemented a Bayesian survival analysis and few incorporated external data into priors. There is scope to improve the quality of reporting of Bayesian methods in survival trials. Extension of the Consolidated Standards of Reporting Trials statement for reporting Bayesian clinical trials is recommended.

Population Genetic Structure of the Tropical Two-Wing Flyingfish (Exocoetus volitans)

PubMed Central

Lewallen, Eric A.; Bohonak, Andrew J.; Bonin, Carolina A.; van Wijnen, Andre J.; Pitman, Robert L.; Lovejoy, Nathan R.

2016-01-01

Delineating populations of pantropical marine fish is a difficult process, due to widespread geographic ranges and complex life history traits in most species. Exocoetus volitans, a species of two-winged flyingfish, is a good model for understanding large-scale patterns of epipelagic fish population structure because it has a circumtropical geographic range and completes its entire life cycle in the epipelagic zone. Buoyant pelagic eggs should dictate high local dispersal capacity in this species, although a brief larval phase, small body size, and short lifespan may limit the dispersal of individuals over large spatial scales. Based on these biological features, we hypothesized that E. volitans would exhibit statistically and biologically significant population structure defined by recognized oceanographic barriers. We tested this hypothesis by analyzing cytochrome b mtDNA sequence data (1106 bps) from specimens collected in the Pacific, Atlantic and Indian oceans (n = 266). AMOVA, Bayesian, and coalescent analytical approaches were used to assess and interpret population-level genetic variability. A parsimony-based haplotype network did not reveal population subdivision among ocean basins, but AMOVA revealed limited, statistically significant population structure between the Pacific and Atlantic Oceans (ΦST = 0.035, p<0.001). A spatially-unbiased Bayesian approach identified two circumtropical population clusters north and south of the Equator (ΦST = 0.026, p<0.001), a previously unknown dispersal barrier for an epipelagic fish. Bayesian demographic modeling suggested the effective population size of this species increased by at least an order of magnitude ~150,000 years ago, to more than 1 billion individuals currently. Thus, high levels of genetic similarity observed in E. volitans can be explained by high rates of gene flow, a dramatic and recent population expansion, as well as extensive and consistent dispersal throughout the geographic range of the species. PMID:27736863

Emerging Concepts of Data Integration in Pathogen Phylodynamics.

PubMed

Baele, Guy; Suchard, Marc A; Rambaut, Andrew; Lemey, Philippe

2017-01-01

Phylodynamics has become an increasingly popular statistical framework to extract evolutionary and epidemiological information from pathogen genomes. By harnessing such information, epidemiologists aim to shed light on the spatio-temporal patterns of spread and to test hypotheses about the underlying interaction of evolutionary and ecological dynamics in pathogen populations. Although the field has witnessed a rich development of statistical inference tools with increasing levels of sophistication, these tools initially focused on sequences as their sole primary data source. Integrating various sources of information, however, promises to deliver more precise insights in infectious diseases and to increase opportunities for statistical hypothesis testing. Here, we review how the emerging concept of data integration is stimulating new advances in Bayesian evolutionary inference methodology which formalize a marriage of statistical thinking and evolutionary biology. These approaches include connecting sequence to trait evolution, such as for host, phenotypic and geographic sampling information, but also the incorporation of covariates of evolutionary and epidemic processes in the reconstruction procedures. We highlight how a full Bayesian approach to covariate modeling and testing can generate further insights into sequence evolution, trait evolution, and population dynamics in pathogen populations. Specific examples demonstrate how such approaches can be used to test the impact of host on rabies and HIV evolutionary rates, to identify the drivers of influenza dispersal as well as the determinants of rabies cross-species transmissions, and to quantify the evolutionary dynamics of influenza antigenicity. Finally, we briefly discuss how data integration is now also permeating through the inference of transmission dynamics, leading to novel insights into tree-generative processes and detailed reconstructions of transmission trees. [Bayesian inference; birth–death models; coalescent models; continuous trait evolution; covariates; data integration; discrete trait evolution; pathogen phylodynamics.

Population Genetic Structure of the Tropical Two-Wing Flyingfish (Exocoetus volitans).

PubMed

Lewallen, Eric A; Bohonak, Andrew J; Bonin, Carolina A; van Wijnen, Andre J; Pitman, Robert L; Lovejoy, Nathan R

2016-01-01

Delineating populations of pantropical marine fish is a difficult process, due to widespread geographic ranges and complex life history traits in most species. Exocoetus volitans, a species of two-winged flyingfish, is a good model for understanding large-scale patterns of epipelagic fish population structure because it has a circumtropical geographic range and completes its entire life cycle in the epipelagic zone. Buoyant pelagic eggs should dictate high local dispersal capacity in this species, although a brief larval phase, small body size, and short lifespan may limit the dispersal of individuals over large spatial scales. Based on these biological features, we hypothesized that E. volitans would exhibit statistically and biologically significant population structure defined by recognized oceanographic barriers. We tested this hypothesis by analyzing cytochrome b mtDNA sequence data (1106 bps) from specimens collected in the Pacific, Atlantic and Indian oceans (n = 266). AMOVA, Bayesian, and coalescent analytical approaches were used to assess and interpret population-level genetic variability. A parsimony-based haplotype network did not reveal population subdivision among ocean basins, but AMOVA revealed limited, statistically significant population structure between the Pacific and Atlantic Oceans (ΦST = 0.035, p<0.001). A spatially-unbiased Bayesian approach identified two circumtropical population clusters north and south of the Equator (ΦST = 0.026, p<0.001), a previously unknown dispersal barrier for an epipelagic fish. Bayesian demographic modeling suggested the effective population size of this species increased by at least an order of magnitude ~150,000 years ago, to more than 1 billion individuals currently. Thus, high levels of genetic similarity observed in E. volitans can be explained by high rates of gene flow, a dramatic and recent population expansion, as well as extensive and consistent dispersal throughout the geographic range of the species.

Emerging Concepts of Data Integration in Pathogen Phylodynamics

PubMed Central

Baele, Guy; Suchard, Marc A.; Rambaut, Andrew; Lemey, Philippe

2017-01-01

Phylodynamics has become an increasingly popular statistical framework to extract evolutionary and epidemiological information from pathogen genomes. By harnessing such information, epidemiologists aim to shed light on the spatio-temporal patterns of spread and to test hypotheses about the underlying interaction of evolutionary and ecological dynamics in pathogen populations. Although the field has witnessed a rich development of statistical inference tools with increasing levels of sophistication, these tools initially focused on sequences as their sole primary data source. Integrating various sources of information, however, promises to deliver more precise insights in infectious diseases and to increase opportunities for statistical hypothesis testing. Here, we review how the emerging concept of data integration is stimulating new advances in Bayesian evolutionary inference methodology which formalize a marriage of statistical thinking and evolutionary biology. These approaches include connecting sequence to trait evolution, such as for host, phenotypic and geographic sampling information, but also the incorporation of covariates of evolutionary and epidemic processes in the reconstruction procedures. We highlight how a full Bayesian approach to covariate modeling and testing can generate further insights into sequence evolution, trait evolution, and population dynamics in pathogen populations. Specific examples demonstrate how such approaches can be used to test the impact of host on rabies and HIV evolutionary rates, to identify the drivers of influenza dispersal as well as the determinants of rabies cross-species transmissions, and to quantify the evolutionary dynamics of influenza antigenicity. Finally, we briefly discuss how data integration is now also permeating through the inference of transmission dynamics, leading to novel insights into tree-generative processes and detailed reconstructions of transmission trees. [Bayesian inference; birth–death models; coalescent models; continuous trait evolution; covariates; data integration; discrete trait evolution; pathogen phylodynamics. PMID:28173504

Tracing the spatio-temporal dynamics of endangered fin whales (Balaenoptera physalus) within baleen whale (Mysticeti) lineages: a mitogenomic perspective.

PubMed

Yu, Jihyun; Nam, Bo-Hye; Yoon, Joon; Kim, Eun Bae; Park, Jung Youn; Kim, Heebal; Yoon, Sook Hee

2017-12-01

To explore the spatio-temporal dynamics of endangered fin whales (Balaenoptera physalus) within the baleen whale (Mysticeti) lineages, we analyzed 148 published mitochondrial genome sequences of baleen whales. We used a Bayesian coalescent approach as well as Bayesian inferences and maximum likelihood methods. The results showed that the fin whales had a single maternal origin, and that there is a significant correlation between geographic location and evolution of global fin whales. The most recent common female ancestor of this species lived approximately 9.88 million years ago (Mya). Here, North Pacific fin whales first appeared about 7.48 Mya, followed by a subsequent divergence in Southern Hemisphere approximately 6.63 Mya and North Atlantic about 4.42 Mya. Relatively recently, approximately 1.76 and 1.42 Mya, there were two additional occurrences of North Pacific populations; one originated from the Southern Hemisphere and the other from an uncertain location. The evolutionary rate of this species was 1.002 × 10 -3 substitutions/site/My. Our Bayesian skyline plot illustrates that the fin whale population has the rapid expansion event since ~ 2.5 Mya, during the Quaternary glaciation stage. Additionally, this study indicates that the fin whale has a sister group relationship with humpback whale (Meganoptera novaeangliae) within the baleen whale lineages. Of the 16 genomic regions, NADH5 showed the most powerful signal for baleen whale phylogenetics. Interestingly, fin whales have 16 species-specific amino acid residues in eight mitochondrial genes: NADH2, COX2, COX3, ATPase6, ATPase8, NADH4, NADH5, and Cytb.

The Application of Bayesian Analysis to Issues in Developmental Research

ERIC Educational Resources Information Center

Walker, Lawrence J.; Gustafson, Paul; Frimer, Jeremy A.

2007-01-01

This article reviews the concepts and methods of Bayesian statistical analysis, which can offer innovative and powerful solutions to some challenging analytical problems that characterize developmental research. In this article, we demonstrate the utility of Bayesian analysis, explain its unique adeptness in some circumstances, address some…

A default Bayesian hypothesis test for mediation.

PubMed

Nuijten, Michèle B; Wetzels, Ruud; Matzke, Dora; Dolan, Conor V; Wagenmakers, Eric-Jan

2015-03-01

In order to quantify the relationship between multiple variables, researchers often carry out a mediation analysis. In such an analysis, a mediator (e.g., knowledge of a healthy diet) transmits the effect from an independent variable (e.g., classroom instruction on a healthy diet) to a dependent variable (e.g., consumption of fruits and vegetables). Almost all mediation analyses in psychology use frequentist estimation and hypothesis-testing techniques. A recent exception is Yuan and MacKinnon (Psychological Methods, 14, 301-322, 2009), who outlined a Bayesian parameter estimation procedure for mediation analysis. Here we complete the Bayesian alternative to frequentist mediation analysis by specifying a default Bayesian hypothesis test based on the Jeffreys-Zellner-Siow approach. We further extend this default Bayesian test by allowing a comparison to directional or one-sided alternatives, using Markov chain Monte Carlo techniques implemented in JAGS. All Bayesian tests are implemented in the R package BayesMed (Nuijten, Wetzels, Matzke, Dolan, & Wagenmakers, 2014).

A Tutorial in Bayesian Potential Outcomes Mediation Analysis.

PubMed

Miočević, Milica; Gonzalez, Oscar; Valente, Matthew J; MacKinnon, David P

2018-01-01

Statistical mediation analysis is used to investigate intermediate variables in the relation between independent and dependent variables. Causal interpretation of mediation analyses is challenging because randomization of subjects to levels of the independent variable does not rule out the possibility of unmeasured confounders of the mediator to outcome relation. Furthermore, commonly used frequentist methods for mediation analysis compute the probability of the data given the null hypothesis, which is not the probability of a hypothesis given the data as in Bayesian analysis. Under certain assumptions, applying the potential outcomes framework to mediation analysis allows for the computation of causal effects, and statistical mediation in the Bayesian framework gives indirect effects probabilistic interpretations. This tutorial combines causal inference and Bayesian methods for mediation analysis so the indirect and direct effects have both causal and probabilistic interpretations. Steps in Bayesian causal mediation analysis are shown in the application to an empirical example.

A Single Early Introduction of HIV-1 Subtype B into Central America Accounts for Most Current Cases

PubMed Central

Murillo, Wendy; Veras, Nazle; Prosperi, Mattia; de Rivera, Ivette Lorenzana; Paz-Bailey, Gabriela; Morales-Miranda, Sonia; Juarez, Sandra I.; Yang, Chunfu; DeVos, Joshua; Marín, José Pablo; Mild, Mattias; Albert, Jan

2013-01-01

Human immunodeficiency virus type 1 (HIV-1) variants show considerable geographical separation across the world, but there is limited information from Central America. We provide the first detailed investigation of the genetic diversity and molecular epidemiology of HIV-1 in six Central American countries. Phylogenetic analysis was performed on 625 HIV-1 pol gene sequences collected between 2002 and 2010 in Honduras, El Salvador, Nicaragua, Costa Rica, Panama, and Belize. Published sequences from neighboring countries (n = 57) and the rest of the world (n = 740) were included as controls. Maximum likelihood methods were used to explore phylogenetic relationships. Bayesian coalescence-based methods were used to time HIV-1 introductions. Nearly all (98.9%) Central American sequences were of subtype B. Phylogenetic analysis revealed that 437 (70%) sequences clustered within five significantly supported monophyletic clades formed essentially by Central American sequences. One clade contained 386 (62%) sequences from all six countries; the other four clades were smaller and more country specific, suggesting discrete subepidemics. The existence of one large well-supported Central American clade provides evidence that a single introduction of HIV-1 subtype B in Central America accounts for most current cases. An introduction during the early phase of the HIV-1 pandemic may explain its epidemiological success. Moreover, the smaller clades suggest a subsequent regional spread related to specific transmission networks within each country. PMID:23616665

Relating the microscopic rules in coalescence-fragmentation models to the cluster-size distribution

NASA Astrophysics Data System (ADS)

Ruszczycki, B.; Burnett, B.; Zhao, Z.; Johnson, N. F.

2009-11-01

Coalescence-fragmentation problems are now of great interest across the physical, biological, and social sciences. They are typically studied from the perspective of rate equations, at the heart of which are the rules used for coalescence and fragmentation. Here we discuss how changes in these microscopic rules affect the macroscopic cluster-size distribution which emerges from the solution to the rate equation. Our analysis elucidates the crucial role that the fragmentation rule can play in such dynamical grouping models. We focus our discussion on two well-known models whose fragmentation rules lie at opposite extremes. In particular, we provide a range of generalizations and new analytic results for the well-known model of social group formation developed by Eguíluz and Zimmermann, [Phys. Rev. Lett. 85, 5659 (2000)]. We develop analytic perturbation treatments of this original model, and extend the analytic analysis to the treatment of growing and declining populations.

A Bayesian approach to meta-analysis of plant pathology studies.

PubMed

Mila, A L; Ngugi, H K

2011-01-01

Bayesian statistical methods are used for meta-analysis in many disciplines, including medicine, molecular biology, and engineering, but have not yet been applied for quantitative synthesis of plant pathology studies. In this paper, we illustrate the key concepts of Bayesian statistics and outline the differences between Bayesian and classical (frequentist) methods in the way parameters describing population attributes are considered. We then describe a Bayesian approach to meta-analysis and present a plant pathological example based on studies evaluating the efficacy of plant protection products that induce systemic acquired resistance for the management of fire blight of apple. In a simple random-effects model assuming a normal distribution of effect sizes and no prior information (i.e., a noninformative prior), the results of the Bayesian meta-analysis are similar to those obtained with classical methods. Implementing the same model with a Student's t distribution and a noninformative prior for the effect sizes, instead of a normal distribution, yields similar results for all but acibenzolar-S-methyl (Actigard) which was evaluated only in seven studies in this example. Whereas both the classical (P = 0.28) and the Bayesian analysis with a noninformative prior (95% credibility interval [CRI] for the log response ratio: -0.63 to 0.08) indicate a nonsignificant effect for Actigard, specifying a t distribution resulted in a significant, albeit variable, effect for this product (CRI: -0.73 to -0.10). These results confirm the sensitivity of the analytical outcome (i.e., the posterior distribution) to the choice of prior in Bayesian meta-analyses involving a limited number of studies. We review some pertinent literature on more advanced topics, including modeling of among-study heterogeneity, publication bias, analyses involving a limited number of studies, and methods for dealing with missing data, and show how these issues can be approached in a Bayesian framework. Bayesian meta-analysis can readily include information not easily incorporated in classical methods, and allow for a full evaluation of competing models. Given the power and flexibility of Bayesian methods, we expect them to become widely adopted for meta-analysis of plant pathology studies.

Effective population size dynamics reveal impacts of historic climatic events and recent anthropogenic pressure in African elephants.

PubMed

Okello, J B A; Wittemyer, G; Rasmussen, H B; Arctander, P; Nyakaana, S; Douglas-Hamilton, I; Siegismund, H R

2008-09-01

Two hundred years of elephant hunting for ivory, peaking in 1970-1980s, caused local extirpations and massive population declines across Africa. The resulting genetic impacts on surviving populations have not been studied, despite the importance of understanding the evolutionary repercussions of such human-mediated events on this keystone species. Using Bayesian coalescent-based genetic methods to evaluate time-specific changes in effective population size, we analysed genetic variation in 20 highly polymorphic microsatellite loci from 400 elephants inhabiting the greater Samburu-Laikipia region of northern Kenya. This area experienced a decline of between 80% and 90% in the last few decades when ivory harvesting was rampant. The most significant change in effective population size, however, occurred approximately 2500 years ago during a mid-Holocene period of climatic drying in tropical Africa. Contrary to expectations, detailed analyses of four contemporary age-based cohorts showed that the peak poaching epidemic in the 1970s caused detectable temporary genetic impacts, with genetic diversity rebounding as juveniles surviving the poaching era became reproductively mature. This study demonstrates the importance of climatic history in shaping the distribution and genetic history of a keystone species and highlights the utility of coalescent-based demographic approaches in unravelling ancestral demographic events despite a lack of ancient samples. Unique insights into the genetic signature of mid-Holocene climatic change in Africa and effects of recent poaching pressure on elephants are discussed.

Bayesian structural equation modeling in sport and exercise psychology.

PubMed

Stenling, Andreas; Ivarsson, Andreas; Johnson, Urban; Lindwall, Magnus

2015-08-01

Bayesian statistics is on the rise in mainstream psychology, but applications in sport and exercise psychology research are scarce. In this article, the foundations of Bayesian analysis are introduced, and we will illustrate how to apply Bayesian structural equation modeling in a sport and exercise psychology setting. More specifically, we contrasted a confirmatory factor analysis on the Sport Motivation Scale II estimated with the most commonly used estimator, maximum likelihood, and a Bayesian approach with weakly informative priors for cross-loadings and correlated residuals. The results indicated that the model with Bayesian estimation and weakly informative priors provided a good fit to the data, whereas the model estimated with a maximum likelihood estimator did not produce a well-fitting model. The reasons for this discrepancy between maximum likelihood and Bayesian estimation are discussed as well as potential advantages and caveats with the Bayesian approach.

Bayesian Statistics for Biological Data: Pedigree Analysis

ERIC Educational Resources Information Center

Stanfield, William D.; Carlton, Matthew A.

2004-01-01

The use of Bayes' formula is applied to the biological problem of pedigree analysis to show that the Bayes' formula and non-Bayesian or "classical" methods of probability calculation give different answers. First year college students of biology can be introduced to the Bayesian statistics.

Ockham's razor and Bayesian analysis. [statistical theory for systems evaluation

NASA Technical Reports Server (NTRS)

Jefferys, William H.; Berger, James O.

1992-01-01

'Ockham's razor', the ad hoc principle enjoining the greatest possible simplicity in theoretical explanations, is presently shown to be justifiable as a consequence of Bayesian inference; Bayesian analysis can, moreover, clarify the nature of the 'simplest' hypothesis consistent with the given data. By choosing the prior probabilities of hypotheses, it becomes possible to quantify the scientific judgment that simpler hypotheses are more likely to be correct. Bayesian analysis also shows that a hypothesis with fewer adjustable parameters intrinsically possesses an enhanced posterior probability, due to the clarity of its predictions.

Markov Chain Monte Carlo Methods for Bayesian Data Analysis in Astronomy

NASA Astrophysics Data System (ADS)

Sharma, Sanjib

2017-08-01

Markov Chain Monte Carlo based Bayesian data analysis has now become the method of choice for analyzing and interpreting data in almost all disciplines of science. In astronomy, over the last decade, we have also seen a steady increase in the number of papers that employ Monte Carlo based Bayesian analysis. New, efficient Monte Carlo based methods are continuously being developed and explored. In this review, we first explain the basics of Bayesian theory and discuss how to set up data analysis problems within this framework. Next, we provide an overview of various Monte Carlo based methods for performing Bayesian data analysis. Finally, we discuss advanced ideas that enable us to tackle complex problems and thus hold great promise for the future. We also distribute downloadable computer software (available at https://github.com/sanjibs/bmcmc/ ) that implements some of the algorithms and examples discussed here.

Climate change underlies global demographic, genetic, and cultural transitions in pre-Columbian southern Peru.

PubMed

Fehren-Schmitz, Lars; Haak, Wolfgang; Mächtle, Bertil; Masch, Florian; Llamas, Bastien; Cagigao, Elsa Tomasto; Sossna, Volker; Schittek, Karsten; Isla Cuadrado, Johny; Eitel, Bernhard; Reindel, Markus

2014-07-01

Several archaeological studies in the Central Andes have pointed at the temporal coincidence of climatic fluctuations (both long- and short-term) and episodes of cultural transition and changes of socioeconomic structures throughout the pre-Columbian period. Although most scholars explain the connection between environmental and cultural changes by the impact of climatic alterations on the capacities of the ecosystems inhabited by pre-Columbian cultures, direct evidence for assumed demographic consequences is missing so far. In this study, we address directly the impact of climatic changes on the spatial population dynamics of the Central Andes. We use a large dataset of pre-Columbian mitochondrial DNA sequences from the northern Rio Grande de Nasca drainage (RGND) in southern Peru, dating from ∼840 BC to 1450 AD. Alternative demographic scenarios are tested using Bayesian serial coalescent simulations in an approximate Bayesian computational framework. Our results indicate migrations from the lower coastal valleys of southern Peru into the Andean highlands coincident with increasing climate variability at the end of the Nasca culture at ∼640 AD. We also find support for a back-migration from the highlands to the coast coincident with droughts in the southeastern Andean highlands and improvement of climatic conditions on the coast after the decline of the Wari and Tiwanaku empires (∼1200 AD), leading to a genetic homogenization in the RGND and probably southern Peru as a whole.

Climate change underlies global demographic, genetic, and cultural transitions in pre-Columbian southern Peru

PubMed Central

Fehren-Schmitz, Lars; Haak, Wolfgang; Mächtle, Bertil; Masch, Florian; Llamas, Bastien; Tomasto Cagigao, Elsa; Sossna, Volker; Schittek, Karsten; Isla Cuadrado, Johny; Eitel, Bernhard; Reindel, Markus

2014-01-01

Several archaeological studies in the Central Andes have pointed at the temporal coincidence of climatic fluctuations (both long- and short-term) and episodes of cultural transition and changes of socioeconomic structures throughout the pre-Columbian period. Although most scholars explain the connection between environmental and cultural changes by the impact of climatic alterations on the capacities of the ecosystems inhabited by pre-Columbian cultures, direct evidence for assumed demographic consequences is missing so far. In this study, we address directly the impact of climatic changes on the spatial population dynamics of the Central Andes. We use a large dataset of pre-Columbian mitochondrial DNA sequences from the northern Rio Grande de Nasca drainage (RGND) in southern Peru, dating from ∼840 BC to 1450 AD. Alternative demographic scenarios are tested using Bayesian serial coalescent simulations in an approximate Bayesian computational framework. Our results indicate migrations from the lower coastal valleys of southern Peru into the Andean highlands coincident with increasing climate variability at the end of the Nasca culture at ∼640 AD. We also find support for a back-migration from the highlands to the coast coincident with droughts in the southeastern Andean highlands and improvement of climatic conditions on the coast after the decline of the Wari and Tiwanaku empires (∼1200 AD), leading to a genetic homogenization in the RGND and probably southern Peru as a whole. PMID:24979787

Cryptic genetic diversity, population structure, and gene flow in the Mojave rattlesnake (Crotalus scutulatus).

PubMed

Schield, Drew R; Adams, Richard H; Card, Daren C; Corbin, Andrew B; Jezkova, Tereza; Hales, Nicole R; Meik, Jesse M; Perry, Blair W; Spencer, Carol L; Smith, Lydia L; García, Gustavo Campillo; Bouzid, Nassima M; Strickland, Jason L; Parkinson, Christopher L; Borja, Miguel; Castañeda-Gaytán, Gamaliel; Bryson, Robert W; Flores-Villela, Oscar A; Mackessy, Stephen P; Castoe, Todd A

2018-06-15

The Mojave rattlesnake (Crotalus scutulatus) inhabits deserts and arid grasslands of the western United States and Mexico. Despite considerable interest in its highly toxic venom and the recognition of two subspecies, no molecular studies have characterized range-wide genetic diversity and population structure or tested species limits within C. scutulatus. We used mitochondrial DNA and thousands of nuclear loci from double-digest restriction site associated DNA sequencing to infer population genetic structure throughout the range of C. scutulatus, and to evaluate divergence times and gene flow between populations. We find strong support for several divergent mitochondrial and nuclear clades of C. scutulatus, including splits coincident with two major phylogeographic barriers: the Continental Divide and the elevational increase associated with the Central Mexican Plateau. We apply Bayesian clustering, phylogenetic inference, and coalescent-based species delimitation to our nuclear genetic data to test hypotheses of population structure. We also performed demographic analyses to test hypotheses relating to population divergence and gene flow. Collectively, our results support the existence of four distinct lineages within C. scutulatus, and genetically defined populations do not correspond with currently recognized subspecies ranges. Finally, we use approximate Bayesian computation to test hypotheses of divergence among multiple rattlesnake species groups distributed across the Continental Divide, and find evidence for co-divergence at this boundary during the mid-Pleistocene. Copyright © 2018 Elsevier Inc. All rights reserved.

Is black-hole ringdown a memory of its progenitor?

PubMed

Kamaretsos, Ioannis; Hannam, Mark; Sathyaprakash, B S

2012-10-05

We perform an extensive numerical study of coalescing black-hole binaries to understand the gravitational-wave spectrum of quasinormal modes excited in the merged black hole. Remarkably, we find that the masses and spins of the progenitor are clearly encoded in the mode spectrum of the ringdown signal. Some of the mode amplitudes carry the signature of the binary's mass ratio, while others depend critically on the spins. Simulations of precessing binaries suggest that our results carry over to generic systems. Using Bayesian inference, we demonstrate that it is possible to accurately measure the mass ratio and a proper combination of spins even when the binary is itself invisible to a detector. Using a mapping of the binary masses and spins to the final black-hole spin allows us to further extract the spin components of the progenitor. Our results could have tremendous implications for gravitational astronomy by facilitating novel tests of general relativity using merging black holes.

Power in Bayesian Mediation Analysis for Small Sample Research

PubMed Central

Miočević, Milica; MacKinnon, David P.; Levy, Roy

2018-01-01

It was suggested that Bayesian methods have potential for increasing power in mediation analysis (Koopman, Howe, Hollenbeck, & Sin, 2015; Yuan & MacKinnon, 2009). This paper compares the power of Bayesian credibility intervals for the mediated effect to the power of normal theory, distribution of the product, percentile, and bias-corrected bootstrap confidence intervals at N≤ 200. Bayesian methods with diffuse priors have power comparable to the distribution of the product and bootstrap methods, and Bayesian methods with informative priors had the most power. Varying degrees of precision of prior distributions were also examined. Increased precision led to greater power only when N≥ 100 and the effects were small, N < 60 and the effects were large, and N < 200 and the effects were medium. An empirical example from psychology illustrated a Bayesian analysis of the single mediator model from prior selection to interpreting results. PMID:29662296

Power in Bayesian Mediation Analysis for Small Sample Research.

PubMed

Miočević, Milica; MacKinnon, David P; Levy, Roy

2017-01-01

It was suggested that Bayesian methods have potential for increasing power in mediation analysis (Koopman, Howe, Hollenbeck, & Sin, 2015; Yuan & MacKinnon, 2009). This paper compares the power of Bayesian credibility intervals for the mediated effect to the power of normal theory, distribution of the product, percentile, and bias-corrected bootstrap confidence intervals at N≤ 200. Bayesian methods with diffuse priors have power comparable to the distribution of the product and bootstrap methods, and Bayesian methods with informative priors had the most power. Varying degrees of precision of prior distributions were also examined. Increased precision led to greater power only when N≥ 100 and the effects were small, N < 60 and the effects were large, and N < 200 and the effects were medium. An empirical example from psychology illustrated a Bayesian analysis of the single mediator model from prior selection to interpreting results.

Bayesian methods including nonrandomized study data increased the efficiency of postlaunch RCTs.

PubMed

Schmidt, Amand F; Klugkist, Irene; Klungel, Olaf H; Nielen, Mirjam; de Boer, Anthonius; Hoes, Arno W; Groenwold, Rolf H H

2015-04-01

Findings from nonrandomized studies on safety or efficacy of treatment in patient subgroups may trigger postlaunch randomized clinical trials (RCTs). In the analysis of such RCTs, results from nonrandomized studies are typically ignored. This study explores the trade-off between bias and power of Bayesian RCT analysis incorporating information from nonrandomized studies. A simulation study was conducted to compare frequentist with Bayesian analyses using noninformative and informative priors in their ability to detect interaction effects. In simulated subgroups, the effect of a hypothetical treatment differed between subgroups (odds ratio 1.00 vs. 2.33). Simulations varied in sample size, proportions of the subgroups, and specification of the priors. As expected, the results for the informative Bayesian analyses were more biased than those from the noninformative Bayesian analysis or frequentist analysis. However, because of a reduction in posterior variance, informative Bayesian analyses were generally more powerful to detect an effect. In scenarios where the informative priors were in the opposite direction of the RCT data, type 1 error rates could be 100% and power 0%. Bayesian methods incorporating data from nonrandomized studies can meaningfully increase power of interaction tests in postlaunch RCTs. Copyright © 2015 Elsevier Inc. All rights reserved.

DNA barcoding of Iberian Peninsula and North Africa Tawny Owls Strix aluco suggests the Strait of Gibraltar as an important barrier for phylogeography.

PubMed

Doña, Jorge; Ruiz-Ruano, Francisco J; Jovani, Roger

2016-11-01

Eight subspecies have been proposed within the Tawny Owl (Strix aluco) species. However, recent molecular data have challenged this view, encouraging further work in this species complex. Here we reevaluated the taxonomic status between the North-Western African Tawny Owl, S. a. mauritanica, and its closest Iberian Tawny Owl population (from the S. a. sylvatica to S. a. aluco clade) separated by the Strait of Gibraltar. The Tawny Owl is a non-migratory and territorial species, and juvenile dispersal is restricted to a few kilometers around the natal site. This limited dispersal and the barrier imposed by the Strait of Gibraltar predicted a strong differentiation between the two populations. We tested this using DNA barcoding, Bayesian phylogenetic and species delimitation analysis. We found that an 81.1% of variation is due to the intergroups variation. In addition, the inter-intraspecific distances distribution revealed a barcoding gap among the two subspecies. Also, posterior probabilities and the P AB value allowed to reject the hypothesis that observed degree of distinctiveness is due to random coalescence processes. These findings clearly support the Strait of Gibraltar as an isolating barrier for this species. The subspecific status is confirmed and species status is even suggested for S. a. mauritanica.

Moving beyond qualitative evaluations of Bayesian models of cognition.

PubMed

Hemmer, Pernille; Tauber, Sean; Steyvers, Mark

2015-06-01

Bayesian models of cognition provide a powerful way to understand the behavior and goals of individuals from a computational point of view. Much of the focus in the Bayesian cognitive modeling approach has been on qualitative model evaluations, where predictions from the models are compared to data that is often averaged over individuals. In many cognitive tasks, however, there are pervasive individual differences. We introduce an approach to directly infer individual differences related to subjective mental representations within the framework of Bayesian models of cognition. In this approach, Bayesian data analysis methods are used to estimate cognitive parameters and motivate the inference process within a Bayesian cognitive model. We illustrate this integrative Bayesian approach on a model of memory. We apply the model to behavioral data from a memory experiment involving the recall of heights of people. A cross-validation analysis shows that the Bayesian memory model with inferred subjective priors predicts withheld data better than a Bayesian model where the priors are based on environmental statistics. In addition, the model with inferred priors at the individual subject level led to the best overall generalization performance, suggesting that individual differences are important to consider in Bayesian models of cognition.

A Preliminary Bayesian Analysis of Incomplete Longitudinal Data from a Small Sample: Methodological Advances in an International Comparative Study of Educational Inequality

ERIC Educational Resources Information Center

Hsieh, Chueh-An; Maier, Kimberly S.

2009-01-01

The capacity of Bayesian methods in estimating complex statistical models is undeniable. Bayesian data analysis is seen as having a range of advantages, such as an intuitive probabilistic interpretation of the parameters of interest, the efficient incorporation of prior information to empirical data analysis, model averaging and model selection.…

Historical and current introgression in a Mesoamerican hummingbird species complex: a biogeographic perspective

PubMed Central

Jiménez, Rosa Alicia

2016-01-01

The influence of geologic and Pleistocene glacial cycles might result in morphological and genetic complex scenarios in the biota of the Mesoamerican region. We tested whether berylline, blue-tailed and steely-blue hummingbirds, Amazilia beryllina, Amazilia cyanura and Amazilia saucerottei, show evidence of historical or current introgression as their plumage colour variation might suggest. We also analysed the role of past and present climatic events in promoting genetic introgression and species diversification. We collected mitochondrial DNA (mtDNA) sequence data and microsatellite loci scores for populations throughout the range of the three Amazilia species, as well as morphological and ecological data. Haplotype network, Bayesian phylogenetic and divergence time inference, historical demography, palaeodistribution modelling, and niche divergence tests were used to reconstruct the evolutionary history of this Amazilia species complex. An isolation-with-migration coalescent model and Bayesian assignment analysis were assessed to determine historical introgression and current genetic admixture. mtDNA haplotypes were geographically unstructured, with haplotypes from disparate areas interdispersed on a shallow tree and an unresolved haplotype network. Assignment analysis of the nuclear genome (nuDNA) supported three genetic groups with signs of genetic admixture, corresponding to: (1) A. beryllina populations located west of the Isthmus of Tehuantepec; (2) A. cyanura populations between the Isthmus of Tehuantepec and the Nicaraguan Depression (Nuclear Central America); and (3) A. saucerottei populations southeast of the Nicaraguan Depression. Gene flow and divergence time estimates, and demographic and palaeodistribution patterns suggest an evolutionary history of introgression mediated by Quaternary climatic fluctuations. High levels of gene flow were indicated by mtDNA and asymmetrical isolation-with-migration, whereas the microsatellite analyses found evidence for three genetic clusters with distributions corresponding to isolation by the Isthmus of Tehuantepec and the Nicaraguan Depression and signs of admixture. Historical levels of migration between genetically distinct groups estimated using microsatellites were higher than contemporary levels of migration. These results support the scenario of secondary contact and range contact during the glacial periods of the Pleistocene and strongly imply that the high levels of structure currently observed are a consequence of the limited dispersal of these hummingbirds across the isthmus and depression barriers. PMID:26788433

Informative Bayesian Type A uncertainty evaluation, especially applicable to a small number of observations

NASA Astrophysics Data System (ADS)

Cox, M.; Shirono, K.

2017-10-01

A criticism levelled at the Guide to the Expression of Uncertainty in Measurement (GUM) is that it is based on a mixture of frequentist and Bayesian thinking. In particular, the GUM’s Type A (statistical) uncertainty evaluations are frequentist, whereas the Type B evaluations, using state-of-knowledge distributions, are Bayesian. In contrast, making the GUM fully Bayesian implies, among other things, that a conventional objective Bayesian approach to Type A uncertainty evaluation for a number n of observations leads to the impractical consequence that n must be at least equal to 4, thus presenting a difficulty for many metrologists. This paper presents a Bayesian analysis of Type A uncertainty evaluation that applies for all n ≥slant 2 , as in the frequentist analysis in the current GUM. The analysis is based on assuming that the observations are drawn from a normal distribution (as in the conventional objective Bayesian analysis), but uses an informative prior based on lower and upper bounds for the standard deviation of the sampling distribution for the quantity under consideration. The main outcome of the analysis is a closed-form mathematical expression for the factor by which the standard deviation of the mean observation should be multiplied to calculate the required standard uncertainty. Metrological examples are used to illustrate the approach, which is straightforward to apply using a formula or look-up table.

Coalescent: an open-source and scalable framework for exact calculations in coalescent theory

PubMed Central

2012-01-01

Background Currently, there is no open-source, cross-platform and scalable framework for coalescent analysis in population genetics. There is no scalable GUI based user application either. Such a framework and application would not only drive the creation of more complex and realistic models but also make them truly accessible. Results As a first attempt, we built a framework and user application for the domain of exact calculations in coalescent analysis. The framework provides an API with the concepts of model, data, statistic, phylogeny, gene tree and recursion. Infinite-alleles and infinite-sites models are considered. It defines pluggable computations such as counting and listing all the ancestral configurations and genealogies and computing the exact probability of data. It can visualize a gene tree, trace and visualize the internals of the recursion algorithm for further improvement and attach dynamically a number of output processors. The user application defines jobs in a plug-in like manner so that they can be activated, deactivated, installed or uninstalled on demand. Multiple jobs can be run and their inputs edited. Job inputs are persisted across restarts and running jobs can be cancelled where applicable. Conclusions Coalescent theory plays an increasingly important role in analysing molecular population genetic data. Models involved are mathematically difficult and computationally challenging. An open-source, scalable framework that lets users immediately take advantage of the progress made by others will enable exploration of yet more difficult and realistic models. As models become more complex and mathematically less tractable, the need for an integrated computational approach is obvious. Object oriented designs, though has upfront costs, are practical now and can provide such an integrated approach. PMID:23033878

Micro- and macro-geographic scale effect on the molecular imprint of selection and adaptation in Norway spruce.

PubMed

Scalfi, Marta; Mosca, Elena; Di Pierro, Erica Adele; Troggio, Michela; Vendramin, Giovanni Giuseppe; Sperisen, Christoph; La Porta, Nicola; Neale, David B

2014-01-01

Forest tree species of temperate and boreal regions have undergone a long history of demographic changes and evolutionary adaptations. The main objective of this study was to detect signals of selection in Norway spruce (Picea abies [L.] Karst), at different sampling-scales and to investigate, accounting for population structure, the effect of environment on species genetic diversity. A total of 384 single nucleotide polymorphisms (SNPs) representing 290 genes were genotyped at two geographic scales: across 12 populations distributed along two altitudinal-transects in the Alps (micro-geographic scale), and across 27 populations belonging to the range of Norway spruce in central and south-east Europe (macro-geographic scale). At the macrogeographic scale, principal component analysis combined with Bayesian clustering revealed three major clusters, corresponding to the main areas of southern spruce occurrence, i.e. the Alps, Carpathians, and Hercynia. The populations along the altitudinal transects were not differentiated. To assess the role of selection in structuring genetic variation, we applied a Bayesian and coalescent-based F(ST)-outlier method and tested for correlations between allele frequencies and climatic variables using regression analyses. At the macro-geographic scale, the F(ST)-outlier methods detected together 11 F(ST)-outliers. Six outliers were detected when the same analyses were carried out taking into account the genetic structure. Regression analyses with population structure correction resulted in the identification of two (micro-geographic scale) and 38 SNPs (macro-geographic scale) significantly correlated with temperature and/or precipitation. Six of these loci overlapped with F(ST)-outliers, among them two loci encoding an enzyme involved in riboflavin biosynthesis and a sucrose synthase. The results of this study indicate a strong relationship between genetic and environmental variation at both geographic scales. It also suggests that an integrative approach combining different outlier detection methods and population sampling at different geographic scales is useful to identify loci potentially involved in adaptation.

Micro- and Macro-Geographic Scale Effect on the Molecular Imprint of Selection and Adaptation in Norway Spruce

PubMed Central

Scalfi, Marta; Mosca, Elena; Di Pierro, Erica Adele; Troggio, Michela; Vendramin, Giovanni Giuseppe; Sperisen, Christoph; La Porta, Nicola; Neale, David B.

2014-01-01

Forest tree species of temperate and boreal regions have undergone a long history of demographic changes and evolutionary adaptations. The main objective of this study was to detect signals of selection in Norway spruce (Picea abies [L.] Karst), at different sampling-scales and to investigate, accounting for population structure, the effect of environment on species genetic diversity. A total of 384 single nucleotide polymorphisms (SNPs) representing 290 genes were genotyped at two geographic scales: across 12 populations distributed along two altitudinal-transects in the Alps (micro-geographic scale), and across 27 populations belonging to the range of Norway spruce in central and south-east Europe (macro-geographic scale). At the macrogeographic scale, principal component analysis combined with Bayesian clustering revealed three major clusters, corresponding to the main areas of southern spruce occurrence, i.e. the Alps, Carpathians, and Hercynia. The populations along the altitudinal transects were not differentiated. To assess the role of selection in structuring genetic variation, we applied a Bayesian and coalescent-based F ST-outlier method and tested for correlations between allele frequencies and climatic variables using regression analyses. At the macro-geographic scale, the F ST-outlier methods detected together 11 F ST-outliers. Six outliers were detected when the same analyses were carried out taking into account the genetic structure. Regression analyses with population structure correction resulted in the identification of two (micro-geographic scale) and 38 SNPs (macro-geographic scale) significantly correlated with temperature and/or precipitation. Six of these loci overlapped with F ST-outliers, among them two loci encoding an enzyme involved in riboflavin biosynthesis and a sucrose synthase. The results of this study indicate a strong relationship between genetic and environmental variation at both geographic scales. It also suggests that an integrative approach combining different outlier detection methods and population sampling at different geographic scales is useful to identify loci potentially involved in adaptation. PMID:25551624

Ancient DNA Reveals Prehistoric Gene-Flow from Siberia in the Complex Human Population History of North East Europe

PubMed Central

Der Sarkissian, Clio; Balanovsky, Oleg; Brandt, Guido; Khartanovich, Valery; Buzhilova, Alexandra; Koshel, Sergey; Zaporozhchenko, Valery; Gronenborn, Detlef; Moiseyev, Vyacheslav; Kolpakov, Eugen; Shumkin, Vladimir; Alt, Kurt W.; Balanovska, Elena; Cooper, Alan; Haak, Wolfgang

2013-01-01

North East Europe harbors a high diversity of cultures and languages, suggesting a complex genetic history. Archaeological, anthropological, and genetic research has revealed a series of influences from Western and Eastern Eurasia in the past. While genetic data from modern-day populations is commonly used to make inferences about their origins and past migrations, ancient DNA provides a powerful test of such hypotheses by giving a snapshot of the past genetic diversity. In order to better understand the dynamics that have shaped the gene pool of North East Europeans, we generated and analyzed 34 mitochondrial genotypes from the skeletal remains of three archaeological sites in northwest Russia. These sites were dated to the Mesolithic and the Early Metal Age (7,500 and 3,500 uncalibrated years Before Present). We applied a suite of population genetic analyses (principal component analysis, genetic distance mapping, haplotype sharing analyses) and compared past demographic models through coalescent simulations using Bayesian Serial SimCoal and Approximate Bayesian Computation. Comparisons of genetic data from ancient and modern-day populations revealed significant changes in the mitochondrial makeup of North East Europeans through time. Mesolithic foragers showed high frequencies and diversity of haplogroups U (U2e, U4, U5a), a pattern observed previously in European hunter-gatherers from Iberia to Scandinavia. In contrast, the presence of mitochondrial DNA haplogroups C, D, and Z in Early Metal Age individuals suggested discontinuity with Mesolithic hunter-gatherers and genetic influx from central/eastern Siberia. We identified remarkable genetic dissimilarities between prehistoric and modern-day North East Europeans/Saami, which suggests an important role of post-Mesolithic migrations from Western Europe and subsequent population replacement/extinctions. This work demonstrates how ancient DNA can improve our understanding of human population movements across Eurasia. It contributes to the description of the spatio-temporal distribution of mitochondrial diversity and will be of significance for future reconstructions of the history of Europeans. PMID:23459685

Revisiting the time until fixation of a neutral mutant in a finite population - A coalescent theory approach.

PubMed

Greenbaum, Gili

2015-09-07

Evaluation of the time scale of the fixation of neutral mutations is crucial to the theoretical understanding of the role of neutral mutations in evolution. Diffusion approximations of the Wright-Fisher model are most often used to derive analytic formulations of genetic drift, as well as for the time scales of the fixation of neutral mutations. These approximations require a set of assumptions, most notably that genetic drift is a stochastic process in a continuous allele-frequency space, an assumption appropriate for large populations. Here equivalent approximations are derived using a coalescent theory approach which relies on a different set of assumptions than the diffusion approach, and adopts a discrete allele-frequency space. Solutions for the mean and variance of the time to fixation of a neutral mutation derived from the two approaches converge for large populations but slightly differ for small populations. A Markov chain analysis of the Wright-Fisher model for small populations is used to evaluate the solutions obtained, showing that both the mean and the variance are better approximated by the coalescent approach. The coalescence approximation represents a tighter upper-bound for the mean time to fixation than the diffusion approximation, while the diffusion approximation and coalescence approximation form an upper and lower bound, respectively, for the variance. The converging solutions and the small deviations of the two approaches strongly validate the use of diffusion approximations, but suggest that coalescent theory can provide more accurate approximations for small populations. Copyright © 2015 Elsevier Ltd. All rights reserved.

An Exploratory Study Examining the Feasibility of Using Bayesian Networks to Predict Circuit Analysis Understanding

ERIC Educational Resources Information Center

Chung, Gregory K. W. K.; Dionne, Gary B.; Kaiser, William J.

2006-01-01

Our research question was whether we could develop a feasible technique, using Bayesian networks, to diagnose gaps in student knowledge. Thirty-four college-age participants completed tasks designed to measure conceptual knowledge, procedural knowledge, and problem-solving skills related to circuit analysis. A Bayesian network was used to model…

Unravelling the genetic differentiation among varieties of the Neotropical savanna tree Hancornia speciosa Gomes.

PubMed

Collevatti, Rosane G; Rodrigues, Eduardo E; Vitorino, Luciana C; Lima-Ribeiro, Matheus S; Chaves, Lázaro J; Telles, Mariana P C

2018-04-20

Spatial distribution of species genetic diversity is often driven by geographical distance (isolation by distance) or environmental conditions (isolation by environment), especially under climate change scenarios such as Quaternary glaciations. Here, we used coalescent analyses coupled with ecological niche modelling (ENM), spatially explicit quantile regression analyses and the multiple matrix regression with randomization (MMRR) approach to unravel the patterns of genetic differentiation in the widely distributed Neotropical savanna tree, Hancornia speciosa (Apocynaceae). Due to its high morphological differentiation, the species was originally classified into six botanical varieties by Monachino, and has recently been recognized as only two varieties by Flora do Brasil 2020. Thus, H. speciosa is a good biological model for learning about evolution of phenotypic plasticity under genetic and ecological effects, and predicting their responses to changing environmental conditions. We sampled 28 populations (777 individuals) of Monachino's four varieties of H. speciosa and used seven microsatellite loci to genotype them. Bayesian clustering showed five distinct genetic groups (K = 5) with high admixture among Monachino's varieties, mainly among populations in the central area of the species geographical range. Genetic differentiation among Monachino's varieties was lower than the genetic differentiation among populations within varieties, with higher within-population inbreeding. A high historical connectivity among populations of the central Cerrado shown by coalescent analyses may explain the high admixture among varieties. In addition, areas of higher climatic suitability also presented higher genetic diversity in such a way that the wide historical refugium across central Brazil might have promoted the long-term connectivity among populations. Yet, FST was significantly related to geographic distances, but not to environmental distances, and coalescent analyses and ENM predicted a demographical scenario of quasi-stability through time. Our findings show that demographical history and isolation by distance, but not isolation by environment, drove genetic differentiation of populations. Finally, the genetic clusters do not support the two recently recognized botanical varieties of H. speciosa, but partially support Monachino's classification at least for the four sampled varieties, similar to morphological variation.

A comprehensive probabilistic analysis model of oil pipelines network based on Bayesian network

NASA Astrophysics Data System (ADS)

Zhang, C.; Qin, T. X.; Jiang, B.; Huang, C.

2018-02-01

Oil pipelines network is one of the most important facilities of energy transportation. But oil pipelines network accident may result in serious disasters. Some analysis models for these accidents have been established mainly based on three methods, including event-tree, accident simulation and Bayesian network. Among these methods, Bayesian network is suitable for probabilistic analysis. But not all the important influencing factors are considered and the deployment rule of the factors has not been established. This paper proposed a probabilistic analysis model of oil pipelines network based on Bayesian network. Most of the important influencing factors, including the key environment condition and emergency response are considered in this model. Moreover, the paper also introduces a deployment rule for these factors. The model can be used in probabilistic analysis and sensitive analysis of oil pipelines network accident.

Droplets on liquid surfaces: Dual equilibrium states and their energy barrier

NASA Astrophysics Data System (ADS)

Shabani, Roxana; Kumar, Ranganathan; Cho, Hyoung J.

2013-05-01

Floating aqueous droplets were formed at oil-air interface, and two stable configurations of (i) non-coalescent droplet and (ii) cap/bead droplet were observed. General solutions for energy and force analysis were obtained for both configurations and were shown to be in good agreement with the experimental observations. The energy barrier obtained for transition from configuration (i) to configuration (ii) was correlated to the droplet release height and the probability of non-coalescent droplet formation.

Crack Coalescence in Molded Gypsum and Carrara Marble

NASA Astrophysics Data System (ADS)

Wong, N.; Einstein, H. H.

2007-12-01

This research investigates the fracturing and coalescence behavior in prismatic laboratory-molded gypsum and Carrara marble specimens, which consist of either one or two pre-existing open flaws, under uniaxial compression. The tests are monitored by a high speed video system with a frame rate up to 24,000 frames/second. It allows one to precisely observe the cracking mechanisms, in particular if shear or tensile fracturing takes place. Seven crack types and nine crack coalescence categories are identified. The flaw inclination angle, the ligament length and the bridging angle between two flaws have different extents of influence on the coalescence patterns. For coplanar flaws, as the flaw inclination angle increases, there is a general trend of variation from shear coalescence to tensile coalescence. For stepped flaws, as the bridging angle changes from negative to small positive, and further up to large positive values, the coalescence generally progresses from categories of no coalescence, indirect coalescence to direct coalescence. For direct coalescence, it generally progresses from shear, mixed shear-tensile to tensile as the bridging angle increases. Some differences in fracturing and coalescence processes are observed in gypsum and marble, particularly the crack initiation in marble is preceded by the development of macroscopic white patches, but not in gypsum. Scanning Electron Microprobe (SEM) study reveals that the white patches consist of zones of microcracks (process zones).

Using SPM 12’s Second-Level Bayesian Inference Procedure for fMRI Analysis: Practical Guidelines for End Users

PubMed Central

Han, Hyemin; Park, Joonsuk

2018-01-01

Recent debates about the conventional traditional threshold used in the fields of neuroscience and psychology, namely P < 0.05, have spurred researchers to consider alternative ways to analyze fMRI data. A group of methodologists and statisticians have considered Bayesian inference as a candidate methodology. However, few previous studies have attempted to provide end users of fMRI analysis tools, such as SPM 12, with practical guidelines about how to conduct Bayesian inference. In the present study, we aim to demonstrate how to utilize Bayesian inference, Bayesian second-level inference in particular, implemented in SPM 12 by analyzing fMRI data available to public via NeuroVault. In addition, to help end users understand how Bayesian inference actually works in SPM 12, we examine outcomes from Bayesian second-level inference implemented in SPM 12 by comparing them with those from classical second-level inference. Finally, we provide practical guidelines about how to set the parameters for Bayesian inference and how to interpret the results, such as Bayes factors, from the inference. We also discuss the practical and philosophical benefits of Bayesian inference and directions for future research. PMID:29456498

An introduction to Bayesian statistics in health psychology.

PubMed

Depaoli, Sarah; Rus, Holly M; Clifton, James P; van de Schoot, Rens; Tiemensma, Jitske

2017-09-01

The aim of the current article is to provide a brief introduction to Bayesian statistics within the field of health psychology. Bayesian methods are increasing in prevalence in applied fields, and they have been shown in simulation research to improve the estimation accuracy of structural equation models, latent growth curve (and mixture) models, and hierarchical linear models. Likewise, Bayesian methods can be used with small sample sizes since they do not rely on large sample theory. In this article, we discuss several important components of Bayesian statistics as they relate to health-based inquiries. We discuss the incorporation and impact of prior knowledge into the estimation process and the different components of the analysis that should be reported in an article. We present an example implementing Bayesian estimation in the context of blood pressure changes after participants experienced an acute stressor. We conclude with final thoughts on the implementation of Bayesian statistics in health psychology, including suggestions for reviewing Bayesian manuscripts and grant proposals. We have also included an extensive amount of online supplementary material to complement the content presented here, including Bayesian examples using many different software programmes and an extensive sensitivity analysis examining the impact of priors.

Mechanism and simulation of droplet coalescence in molten steel

NASA Astrophysics Data System (ADS)

Ni, Bing; Zhang, Tao; Ni, Hai-qi; Luo, Zhi-guo

2017-11-01

Droplet coalescence in liquid steel was carefully investigated through observations of the distribution pattern of inclusions in solidified steel samples. The process of droplet coalescence was slow, and the critical Weber number ( We) was used to evaluate the coalescence or separation of droplets. The relationship between the collision parameter and the critical We indicated whether slow coalescence or bouncing of droplets occurred. The critical We was 5.5, which means that the droplets gradually coalesce when We ≤ 5.5, whereas they bounce when We > 5.5. For the carbonate wire feeding into liquid steel, a mathematical model implementing a combined computational fluid dynamics (CFD)-discrete element method (DEM) approach was developed to simulate the movement and coalescence of variably sized droplets in a bottom-argon-blowing ladle. In the CFD model, the flow field was solved on the premise that the fluid was a continuous medium. Meanwhile, the droplets were dispersed in the DEM model, and the coalescence criterion of the particles was added to simulate the collision- coalescence process of the particles. The numerical simulation results and observations of inclusion coalescence in steel samples are consistent.

Droplets coalescence at microchannel intersection chambers with different shapes

NASA Astrophysics Data System (ADS)

Liu, Zhaomiao; Wang, Xiang; Cao, Rentuo; Pang, Yan

2016-11-01

The influence of microchannel intersection chamber shape on droplets coalescence process is investigated in this study. Three kinds of chamber shapes (half-round, triangle and camber) are designed to realize head-on droplets coalescence. The coalescence processes are visualized with high-speed camera system and the internal flow patterns are resolved with micro-PIV system. Experimental analyses on droplets coalescence position, coalescence time and the critical conditions are discussed. Both direct coalescence and late coalescence can be observed in the camber junction while only the late coalescence is present for the half-round and the triangle junction. The critical capillary number Ca* varies for different working systems or intersection shapes. Ca* in the camber junction is larger than that in the other two junctions for each working system and it decreases with the increase of the viscosity ratios for each intersection shape. Moreover, the characteristics of the velocity fields for different coalescence cases are analyzed for in-depth understanding of the process. The authors do appreciate the financial support of No.11572013 of National Nature Scicence Funding of China.

A multiphase ion-transport analysis of the electrostatic disjoining pressure: implications for binary droplet coalescence

NASA Astrophysics Data System (ADS)

Mason, Lachlan; Gebauer, Felix; Bart, Hans-Jörg; Stevens, Geoffrey; Harvie, Dalton

2016-11-01

Understanding the physics of emulsion coalescence is critical for the robust simulation of industrial solvent extraction processes, in which loaded organic and raffinate phases are separated via the coalescence of dispersed droplets. At the droplet scale, predictive collision-outcome models require an accurate description of the repulsive surface forces arising from electrical-double-layer interactions. The conventional disjoining-pressure treatment of double-layer forces, however, relies on assumptions which do not hold generally for deformable droplet collisions: namely, low interfacial curvature and negligible advection of ion species. This study investigates the validity bounds of the disjoining pressure approximation for low-inertia droplet interactions. A multiphase ion-transport model, based on a coupling of droplet-scale Nernst-Planck and Navier-Stokes equations, predicts ion-concentration fields that are consistent with the equilibrium Boltzmann distribution; indicating that the disjoining-pressure approach is valid for both static and dynamic interactions in low-Reynolds-number settings. The present findings support the development of coalescence kernels for application in macro-scale population balance modelling.

Uncertainty aggregation and reduction in structure-material performance prediction

NASA Astrophysics Data System (ADS)

Hu, Zhen; Mahadevan, Sankaran; Ao, Dan

2018-02-01

An uncertainty aggregation and reduction framework is presented for structure-material performance prediction. Different types of uncertainty sources, structural analysis model, and material performance prediction model are connected through a Bayesian network for systematic uncertainty aggregation analysis. To reduce the uncertainty in the computational structure-material performance prediction model, Bayesian updating using experimental observation data is investigated based on the Bayesian network. It is observed that the Bayesian updating results will have large error if the model cannot accurately represent the actual physics, and that this error will be propagated to the predicted performance distribution. To address this issue, this paper proposes a novel uncertainty reduction method by integrating Bayesian calibration with model validation adaptively. The observation domain of the quantity of interest is first discretized into multiple segments. An adaptive algorithm is then developed to perform model validation and Bayesian updating over these observation segments sequentially. Only information from observation segments where the model prediction is highly reliable is used for Bayesian updating; this is found to increase the effectiveness and efficiency of uncertainty reduction. A composite rotorcraft hub component fatigue life prediction model, which combines a finite element structural analysis model and a material damage model, is used to demonstrate the proposed method.

A Two-Step Bayesian Approach for Propensity Score Analysis: Simulations and Case Study

ERIC Educational Resources Information Center

Kaplan, David; Chen, Jianshen

2012-01-01

A two-step Bayesian propensity score approach is introduced that incorporates prior information in the propensity score equation and outcome equation without the problems associated with simultaneous Bayesian propensity score approaches. The corresponding variance estimators are also provided. The two-step Bayesian propensity score is provided for…

Evolution of the human immunodeficiency virus envelope gene is dominated by purifying selection.

PubMed

Edwards, C T T; Holmes, E C; Pybus, O G; Wilson, D J; Viscidi, R P; Abrams, E J; Phillips, R E; Drummond, A J

2006-11-01

The evolution of the human immunodeficiency virus (HIV-1) during chronic infection involves the rapid, continuous turnover of genetic diversity. However, the role of natural selection, relative to random genetic drift, in governing this process is unclear. We tested a stochastic model of genetic drift using partial envelope sequences sampled longitudinally in 28 infected children. In each case the Bayesian posterior (empirical) distribution of coalescent genealogies was estimated using Markov chain Monte Carlo methods. Posterior predictive simulation was then used to generate a null distribution of genealogies assuming neutrality, with the null and empirical distributions compared using four genealogy-based summary statistics sensitive to nonneutral evolution. Because both null and empirical distributions were generated within a coalescent framework, we were able to explicitly account for the confounding influence of demography. From the distribution of corrected P-values across patients, we conclude that empirical genealogies are more asymmetric than expected if evolution is driven by mutation and genetic drift only, with an excess of low-frequency polymorphisms in the population. This indicates that although drift may still play an important role, natural selection has a strong influence on the evolution of HIV-1 envelope. A negative relationship between effective population size and substitution rate indicates that as the efficacy of selection increases, a smaller proportion of mutations approach fixation in the population. This suggests the presence of deleterious mutations. We therefore conclude that intrahost HIV-1 evolution in envelope is dominated by purifying selection against low-frequency deleterious mutations that do not reach fixation.

Prior elicitation and Bayesian analysis of the Steroids for Corneal Ulcers Trial.

PubMed

See, Craig W; Srinivasan, Muthiah; Saravanan, Somu; Oldenburg, Catherine E; Esterberg, Elizabeth J; Ray, Kathryn J; Glaser, Tanya S; Tu, Elmer Y; Zegans, Michael E; McLeod, Stephen D; Acharya, Nisha R; Lietman, Thomas M

2012-12-01

To elicit expert opinion on the use of adjunctive corticosteroid therapy in bacterial corneal ulcers. To perform a Bayesian analysis of the Steroids for Corneal Ulcers Trial (SCUT), using expert opinion as a prior probability. The SCUT was a placebo-controlled trial assessing visual outcomes in patients receiving topical corticosteroids or placebo as adjunctive therapy for bacterial keratitis. Questionnaires were conducted at scientific meetings in India and North America to gauge expert consensus on the perceived benefit of corticosteroids as adjunct treatment. Bayesian analysis, using the questionnaire data as a prior probability and the primary outcome of SCUT as a likelihood, was performed. For comparison, an additional Bayesian analysis was performed using the results of the SCUT pilot study as a prior distribution. Indian respondents believed there to be a 1.21 Snellen line improvement, and North American respondents believed there to be a 1.24 line improvement with corticosteroid therapy. The SCUT primary outcome found a non-significant 0.09 Snellen line benefit with corticosteroid treatment. The results of the Bayesian analysis estimated a slightly greater benefit than did the SCUT primary analysis (0.19 lines verses 0.09 lines). Indian and North American experts had similar expectations on the effectiveness of corticosteroids in bacterial corneal ulcers; that corticosteroids would markedly improve visual outcomes. Bayesian analysis produced results very similar to those produced by the SCUT primary analysis. The similarity in result is likely due to the large sample size of SCUT and helps validate the results of SCUT.

Careful with Those Priors: A Note on Bayesian Estimation in Two-Parameter Logistic Item Response Theory Models

ERIC Educational Resources Information Center

Marcoulides, Katerina M.

2018-01-01

This study examined the use of Bayesian analysis methods for the estimation of item parameters in a two-parameter logistic item response theory model. Using simulated data under various design conditions with both informative and non-informative priors, the parameter recovery of Bayesian analysis methods were examined. Overall results showed that…

A bayesian approach to classification criteria for spectacled eiders

USGS Publications Warehouse

Taylor, B.L.; Wade, P.R.; Stehn, R.A.; Cochrane, J.F.

1996-01-01

To facilitate decisions to classify species according to risk of extinction, we used Bayesian methods to analyze trend data for the Spectacled Eider, an arctic sea duck. Trend data from three independent surveys of the Yukon-Kuskokwim Delta were analyzed individually and in combination to yield posterior distributions for population growth rates. We used classification criteria developed by the recovery team for Spectacled Eiders that seek to equalize errors of under- or overprotecting the species. We conducted both a Bayesian decision analysis and a frequentist (classical statistical inference) decision analysis. Bayesian decision analyses are computationally easier, yield basically the same results, and yield results that are easier to explain to nonscientists. With the exception of the aerial survey analysis of the 10 most recent years, both Bayesian and frequentist methods indicated that an endangered classification is warranted. The discrepancy between surveys warrants further research. Although the trend data are abundance indices, we used a preliminary estimate of absolute abundance to demonstrate how to calculate extinction distributions using the joint probability distributions for population growth rate and variance in growth rate generated by the Bayesian analysis. Recent apparent increases in abundance highlight the need for models that apply to declining and then recovering species.

CytoBayesJ: software tools for Bayesian analysis of cytogenetic radiation dosimetry data.

PubMed

Ainsbury, Elizabeth A; Vinnikov, Volodymyr; Puig, Pedro; Maznyk, Nataliya; Rothkamm, Kai; Lloyd, David C

2013-08-30

A number of authors have suggested that a Bayesian approach may be most appropriate for analysis of cytogenetic radiation dosimetry data. In the Bayesian framework, probability of an event is described in terms of previous expectations and uncertainty. Previously existing, or prior, information is used in combination with experimental results to infer probabilities or the likelihood that a hypothesis is true. It has been shown that the Bayesian approach increases both the accuracy and quality assurance of radiation dose estimates. New software entitled CytoBayesJ has been developed with the aim of bringing Bayesian analysis to cytogenetic biodosimetry laboratory practice. CytoBayesJ takes a number of Bayesian or 'Bayesian like' methods that have been proposed in the literature and presents them to the user in the form of simple user-friendly tools, including testing for the most appropriate model for distribution of chromosome aberrations and calculations of posterior probability distributions. The individual tools are described in detail and relevant examples of the use of the methods and the corresponding CytoBayesJ software tools are given. In this way, the suitability of the Bayesian approach to biological radiation dosimetry is highlighted and its wider application encouraged by providing a user-friendly software interface and manual in English and Russian. Copyright © 2013 Elsevier B.V. All rights reserved.

Bayesian data analysis in observational comparative effectiveness research: rationale and examples.

PubMed

Olson, William H; Crivera, Concetta; Ma, Yi-Wen; Panish, Jessica; Mao, Lian; Lynch, Scott M

2013-11-01

Many comparative effectiveness research and patient-centered outcomes research studies will need to be observational for one or both of two reasons: first, randomized trials are expensive and time-consuming; and second, only observational studies can answer some research questions. It is generally recognized that there is a need to increase the scientific validity and efficiency of observational studies. Bayesian methods for the design and analysis of observational studies are scientifically valid and offer many advantages over frequentist methods, including, importantly, the ability to conduct comparative effectiveness research/patient-centered outcomes research more efficiently. Bayesian data analysis is being introduced into outcomes studies that we are conducting. Our purpose here is to describe our view of some of the advantages of Bayesian methods for observational studies and to illustrate both realized and potential advantages by describing studies we are conducting in which various Bayesian methods have been or could be implemented.

Using Bayesian analysis in repeated preclinical in vivo studies for a more effective use of animals.

PubMed

Walley, Rosalind; Sherington, John; Rastrick, Joe; Detrait, Eric; Hanon, Etienne; Watt, Gillian

2016-05-01

Whilst innovative Bayesian approaches are increasingly used in clinical studies, in the preclinical area Bayesian methods appear to be rarely used in the reporting of pharmacology data. This is particularly surprising in the context of regularly repeated in vivo studies where there is a considerable amount of data from historical control groups, which has potential value. This paper describes our experience with introducing Bayesian analysis for such studies using a Bayesian meta-analytic predictive approach. This leads naturally either to an informative prior for a control group as part of a full Bayesian analysis of the next study or using a predictive distribution to replace a control group entirely. We use quality control charts to illustrate study-to-study variation to the scientists and describe informative priors in terms of their approximate effective numbers of animals. We describe two case studies of animal models: the lipopolysaccharide-induced cytokine release model used in inflammation and the novel object recognition model used to screen cognitive enhancers, both of which show the advantage of a Bayesian approach over the standard frequentist analysis. We conclude that using Bayesian methods in stable repeated in vivo studies can result in a more effective use of animals, either by reducing the total number of animals used or by increasing the precision of key treatment differences. This will lead to clearer results and supports the "3Rs initiative" to Refine, Reduce and Replace animals in research. Copyright © 2016 John Wiley & Sons, Ltd. Copyright © 2016 John Wiley & Sons, Ltd.

Bayesian linkage and segregation analysis: factoring the problem.

PubMed

Matthysse, S

2000-01-01

Complex segregation analysis and linkage methods are mathematical techniques for the genetic dissection of complex diseases. They are used to delineate complex modes of familial transmission and to localize putative disease susceptibility loci to specific chromosomal locations. The computational problem of Bayesian linkage and segregation analysis is one of integration in high-dimensional spaces. In this paper, three available techniques for Bayesian linkage and segregation analysis are discussed: Markov Chain Monte Carlo (MCMC), importance sampling, and exact calculation. The contribution of each to the overall integration will be explicitly discussed.

Development and comparison of Bayesian modularization method in uncertainty assessment of hydrological models

NASA Astrophysics Data System (ADS)

Li, L.; Xu, C.-Y.; Engeland, K.

2012-04-01

With respect to model calibration, parameter estimation and analysis of uncertainty sources, different approaches have been used in hydrological models. Bayesian method is one of the most widely used methods for uncertainty assessment of hydrological models, which incorporates different sources of information into a single analysis through Bayesian theorem. However, none of these applications can well treat the uncertainty in extreme flows of hydrological models' simulations. This study proposes a Bayesian modularization method approach in uncertainty assessment of conceptual hydrological models by considering the extreme flows. It includes a comprehensive comparison and evaluation of uncertainty assessments by a new Bayesian modularization method approach and traditional Bayesian models using the Metropolis Hasting (MH) algorithm with the daily hydrological model WASMOD. Three likelihood functions are used in combination with traditional Bayesian: the AR (1) plus Normal and time period independent model (Model 1), the AR (1) plus Normal and time period dependent model (Model 2) and the AR (1) plus multi-normal model (Model 3). The results reveal that (1) the simulations derived from Bayesian modularization method are more accurate with the highest Nash-Sutcliffe efficiency value, and (2) the Bayesian modularization method performs best in uncertainty estimates of entire flows and in terms of the application and computational efficiency. The study thus introduces a new approach for reducing the extreme flow's effect on the discharge uncertainty assessment of hydrological models via Bayesian. Keywords: extreme flow, uncertainty assessment, Bayesian modularization, hydrological model, WASMOD

A Primer on Bayesian Analysis for Experimental Psychopathologists

PubMed Central

Krypotos, Angelos-Miltiadis; Blanken, Tessa F.; Arnaudova, Inna; Matzke, Dora; Beckers, Tom

2016-01-01

The principal goals of experimental psychopathology (EPP) research are to offer insights into the pathogenic mechanisms of mental disorders and to provide a stable ground for the development of clinical interventions. The main message of the present article is that those goals are better served by the adoption of Bayesian statistics than by the continued use of null-hypothesis significance testing (NHST). In the first part of the article we list the main disadvantages of NHST and explain why those disadvantages limit the conclusions that can be drawn from EPP research. Next, we highlight the advantages of Bayesian statistics. To illustrate, we then pit NHST and Bayesian analysis against each other using an experimental data set from our lab. Finally, we discuss some challenges when adopting Bayesian statistics. We hope that the present article will encourage experimental psychopathologists to embrace Bayesian statistics, which could strengthen the conclusions drawn from EPP research. PMID:28748068

Testing students' e-learning via Facebook through Bayesian structural equation modeling.

PubMed

Salarzadeh Jenatabadi, Hashem; Moghavvemi, Sedigheh; Wan Mohamed Radzi, Che Wan Jasimah Bt; Babashamsi, Parastoo; Arashi, Mohammad

2017-01-01

Learning is an intentional activity, with several factors affecting students' intention to use new learning technology. Researchers have investigated technology acceptance in different contexts by developing various theories/models and testing them by a number of means. Although most theories/models developed have been examined through regression or structural equation modeling, Bayesian analysis offers more accurate data analysis results. To address this gap, the unified theory of acceptance and technology use in the context of e-learning via Facebook are re-examined in this study using Bayesian analysis. The data (S1 Data) were collected from 170 students enrolled in a business statistics course at University of Malaya, Malaysia, and tested with the maximum likelihood and Bayesian approaches. The difference between the two methods' results indicates that performance expectancy and hedonic motivation are the strongest factors influencing the intention to use e-learning via Facebook. The Bayesian estimation model exhibited better data fit than the maximum likelihood estimator model. The results of the Bayesian and maximum likelihood estimator approaches are compared and the reasons for the result discrepancy are deliberated.

Testing students’ e-learning via Facebook through Bayesian structural equation modeling

PubMed Central

Moghavvemi, Sedigheh; Wan Mohamed Radzi, Che Wan Jasimah Bt; Babashamsi, Parastoo; Arashi, Mohammad

2017-01-01

Learning is an intentional activity, with several factors affecting students’ intention to use new learning technology. Researchers have investigated technology acceptance in different contexts by developing various theories/models and testing them by a number of means. Although most theories/models developed have been examined through regression or structural equation modeling, Bayesian analysis offers more accurate data analysis results. To address this gap, the unified theory of acceptance and technology use in the context of e-learning via Facebook are re-examined in this study using Bayesian analysis. The data (S1 Data) were collected from 170 students enrolled in a business statistics course at University of Malaya, Malaysia, and tested with the maximum likelihood and Bayesian approaches. The difference between the two methods’ results indicates that performance expectancy and hedonic motivation are the strongest factors influencing the intention to use e-learning via Facebook. The Bayesian estimation model exhibited better data fit than the maximum likelihood estimator model. The results of the Bayesian and maximum likelihood estimator approaches are compared and the reasons for the result discrepancy are deliberated. PMID:28886019

Origin and Evolution of the Unique Hepatitis C Virus Circulating Recombinant Form 2k/1b

PubMed Central

Thomas, Xiomara V.; Koekkoek, Sylvie M.; Schinkel, Janke; Molenkamp, Richard; van de Laar, Thijs J.; Takebe, Yutaka; Tanaka, Yasuhito; Mizokami, Masashi; Rambaut, Andrew

2012-01-01

Since its initial identification in St. Petersburg, Russia, the recombinant hepatitis C virus (HCV) 2k/1b has been isolated from several countries throughout Eurasia. The 2k/1b strain is the only recombinant HCV to have spread widely, raising questions about the epidemiological background in which it first appeared. In order to further understand the circumstances by which HCV recombinants might be formed and spread, we estimated the date of the recombination event that generated the 2k/1b strain using a Bayesian phylogenetic approach. Our study incorporates newly isolated 2k/1b strains from Amsterdam, The Netherlands, and has employed a hierarchical Bayesian framework to combine information from different genomic regions. We estimate that 2k/1b originated sometime between 1923 and 1956, substantially before the first detection of the strain in 1999. The timescale and the geographic spread of 2k/1b suggest that it originated in the former Soviet Union at about the time that the world's first centralized national blood transfusion and storage service was being established. We also reconstructed the epidemic history of 2k/1b using coalescent theory-based methods, matching patterns previously reported for other epidemic HCV subtypes. This study demonstrates the practicality of jointly estimating dates of recombination from flanking regions of the breakpoint and further illustrates that rare genetic-exchange events can be particularly informative about the underlying epidemiological processes. PMID:22114341

Bayesian Population Genomic Inference of Crossing Over and Gene Conversion

PubMed Central

Padhukasahasram, Badri; Rannala, Bruce

2011-01-01

Meiotic recombination is a fundamental cellular mechanism in sexually reproducing organisms and its different forms, crossing over and gene conversion both play an important role in shaping genetic variation in populations. Here, we describe a coalescent-based full-likelihood Markov chain Monte Carlo (MCMC) method for jointly estimating the crossing-over, gene-conversion, and mean tract length parameters from population genomic data under a Bayesian framework. Although computationally more expensive than methods that use approximate likelihoods, the relative efficiency of our method is expected to be optimal in theory. Furthermore, it is also possible to obtain a posterior sample of genealogies for the data using this method. We first check the performance of the new method on simulated data and verify its correctness. We also extend the method for inference under models with variable gene-conversion and crossing-over rates and demonstrate its ability to identify recombination hotspots. Then, we apply the method to two empirical data sets that were sequenced in the telomeric regions of the X chromosome of Drosophila melanogaster. Our results indicate that gene conversion occurs more frequently than crossing over in the su-w and su-s gene sequences while the local rates of crossing over as inferred by our program are not low. The mean tract lengths for gene-conversion events are estimated to be ∼70 bp and 430 bp, respectively, for these data sets. Finally, we discuss ideas and optimizations for reducing the execution time of our algorithm. PMID:21840857

Speciation at the Mogollon Rim in the Arizona Mountain Kingsnake (Lampropeltis pyromelana).

PubMed

Burbrink, Frank T; Yao, Helen; Ingrasci, Matthew; Bryson, Robert W; Guiher, Timothy J; Ruane, Sara

2011-09-01

Studies of speciation and taxon delimitation are usually decoupled. Combining these methods provides a stronger theoretical ground for recognizing new taxa and understanding processes of speciation. Using coalescent methods, we examine speciation, post-speciation population demographics, and taxon delimitation in the Arizona Mountain Kingsnake (Lampropeltis pyromelana), a species restricted to high elevations in southwestern United States and northern Mexico (SW). These methods provide a solid foundation for understanding how biogeographic barriers operate at the regional scale in the SW. Bayesian species delimitation methods, using three loci from samples of L. pyromelana taken throughout their range, show strong support for the existence of two species that are separated by low elevation habitats found between the Colorado Plateau/ Mogollon Rim and the Sierra Madre Occidental. Our results suggest an allopatric mode of speciation given the near absence of gene flow over time, which resulted in two lineages of unequal population sizes. Speciation likely occurred prior to the Pleistocene, during the aridification of the SW and/or the uplift of the Colorado Plateau, and while these species occupy similar high-elevation niches, they are isolated by xeric conditions found in the intervening low deserts. Furthermore, post-speciation demographics suggest that populations of both lineages were not negatively impacted by climate change throughout the Pleistocene. Finally, our results suggest that at least for this group, where divergence is old and gene flow is low, Bayesian species delimitation performs well. Copyright © 2011 Elsevier Inc. All rights reserved.

Delimiting cryptic pathogen species causing apple Valsa canker with multilocus data

PubMed Central

Wang, Xuli; Zang, Rui; Yin, Zhiyuan; Kang, Zhensheng; Huang, Lili

2014-01-01

Fungal diseases are posing tremendous threats to global economy and food safety. Among them, Valsa canker, caused by fungi of Valsa and their Cytospora anamorphs, has been a serious threat to fruit and forest trees and is one of the most destructive diseases of apple in East Asia, particularly. Accurate and robust delimitation of pathogen species is not only essential for the development of effective disease control programs, but also will advance our understanding of the emergence of plant diseases. However, species delimitation is especially difficult in Valsa because of the high variability of morphological traits and in many cases the lack of the teleomorph. In this study, we delimitated species boundary for pathogens causing apple Valsa canker with a multifaceted approach. Based on three independent loci, the internal transcribed spacer (ITS), β-tubulin (Btu), and translation elongation factor-1 alpha (EF1α), we inferred gene trees with both maximum likelihood and Bayesian methods, estimated species tree with Bayesian multispecies coalescent approaches, and validated species tree with Bayesian species delimitation. Through divergence time estimation and ancestral host reconstruction, we tested the possible underlying mechanisms for fungal speciation and host-range change. Our results proved that two varieties of the former morphological species V. mali represented two distinct species, V. mali and V. pyri, which diverged about 5 million years ago, much later than the divergence of their preferred hosts, excluding a scenario of fungi–host co-speciation. The marked different thermal preferences and contrasting pathogenicity in cross-inoculation suggest ecological divergences between the two species. Apple was the most likely ancestral host for both V. mali and V. pyri. Host-range expansion led to the occurrence of V. pyri on both pear and apple. Our results also represent an example in which ITS data might underestimate species diversity. PMID:24834333

An experimental study on the coalescence process of binary droplets in oil under ultrasonic standing waves.

PubMed

Luo, Xiaoming; Cao, Juhang; He, Limin; Wang, Hongping; Yan, Haipeng; Qin, Yahua

2017-01-01

The coalescence process of binary droplets in oil under ultrasonic standing waves was investigated with high-speed photography. Three motion models of binary droplets in coalescence process were illustrated: (1) slight translational oscillation; (2) sinusoidal translational oscillation; (3) migration along with acoustic streaming. To reveal the droplets coalescence mechanisms, the influence of main factors (such as acoustic intensity, droplet size, viscosity and interfacial tension, etc) on the motion and coalescence of binary droplets was studied under ultrasonic standing waves. Results indicate that the shortest coalescence time is achieved when binary droplets show sinusoidal translational oscillation. The corresponding acoustic intensity in this case is the optimum acoustic intensity. Under the optimum acoustic intensity, drop size decrease will bring about coalescence time decrease by enhancing the binary droplets oscillation. Moreover, there is an optimum interfacial tension to achieve the shortest coalescence time. Copyright © 2016 Elsevier B.V. All rights reserved.

Gene flow and hybridization between numerically imbalanced populations of two duck species on the subantarctic island of South Georgia.

PubMed

McCracken, Kevin G; Wilson, Robert E; Martin, Anthony R

2013-01-01

Hybridization is common between species of animals, particularly in waterfowl (Anatidae). One factor shown to promote hybridization is restricted mate choice, which can occur when 2 species occur in sympatry but one is rare. According to the Hubbs principle, or "desperation hypothesis," the rarer species is more likely to mate with heterospecifics. We report the second of 2 independent examples of hybridization between 2 species of ducks inhabiting island ecosystems in the Subantarctic and South Atlantic Ocean. Yellow-billed pintails (Anas georgica) and speckled teal (Anas flavirostris) are abundant in continental South America, where they are sympatric and coexist in mixed flocks. But on South Georgia, an isolated island in the Subantarctic, the pintail population of approximately 6000 pairs outnumbers a small breeding population of speckled teal 300∶1. Using 6 genetic loci (mtDNA and 5 nuclear introns) and Bayesian assignment tests coupled with coalescent analyses, we identified hybrid-origin speckled teal alleles in 2 pintails on South Georgia. While it is unclear whether introgression has also occurred into the speckled teal population, our data suggest that this hybridization was not a recent event, but occurred some time ago. We also failed to identify unequivocal evidence of introgression in a much larger sample of pintails and speckled teal from Argentina using a 3-population "Isolation-with-Migration" coalescent analysis. Combined with parallel findings of hybridization between these same 2 duck species in the Falkland Islands, where population ratios are reversed and pintails are outnumbered by speckled teal 1:10, our results provide further support for the desperation hypothesis, which predicts that scarcity in one population and abundance of another will often lead to hybridization. While the South Georgia pintail population appears to be thriving, it's possible that low density of conspecific mates and inverse density dependence (Allee effect) may be one factor limiting the reproductive output of the speckled teal population, and this situation may persist unless speckled teal increase in abundance on South Georgia.

Ultraviolet to Infrared SED (Spectral Energy Distribution) Analysis of Nearby Late-Stage Mergers

NASA Astrophysics Data System (ADS)

Weiner, Aaron S.; Smith, Howard A.; Ashby, Matthew; Martínez-Galarza, Juan Rafael; Ramos Padilla, Andres; Hung, Chao-Ling; Dietrich, Jeremy; Lanz, Lauranne; Hayward, Christopher; Rosenthal, Lee; Willner, Steven; Zezas, Andreas

2018-01-01

We present an analysis of the fundamental properties of nearby merging galaxies based on an in-depth analysis of their spectral energy distributions. The Late-Stage Interacting Galaxy Sample (LSIGS) cross-correlates the Revised IRAS-FSC Redshift Catalogue (Wang et al. 2014) with Galaxy Zoo (Lintott et al. 2008, 2011). LSIGS builds on and extends SIGS (Spitzer Interacting Galaxy Sample; Lanz et al. 2013, Brassington et al. 2015) in two ways. First it enlarges the sample considerably to 453 systems, increasing the statistical power of the analysis significantly. Second, it includes galaxies in the most advanced merger stage, during coalescence, filling a gap in the SIGS sample. We present full ultraviolet (UV) to far-infrared (FIR) aperture photometry for 50 galaxies in this sample, 40 of which are late-stage mergers, selecting based on availability of both UV and SPIRE observations. These have subsequently been fit and analyzed by CIGALE (Code Investigating Galaxy Emission; Burgarella 2005) in order to retrieve key physical properties of the galaxies including star-formation rate (SFR), AGN fraction, dust luminosity, bolometric luminosity, and stellar and gas mass. We use this same analysis on hydrodynamical simulations created with GADGET-3 and using SUNRISE for the radiative transfer. Using the observations in conjunction with the simulations, CIGALE fits the simulated values accurately for fAGN>0.3. Additionally galaxies in the midst of coalescence have significantly increased sSFR compared to both early and late-stage mergers, while finding that the gas mass and alpha significantly increase from early stage mergers to those in coalescence. Furthermore, we find a linear anti-correlation between alpha and both the log(60/100μm) flux, and, more interestingly, the compactness. Lastly we bring forth the idea of using the best fit age of the oldest stars and the folding time of the stellar population, τmain, in conjunction to predict the likelihood of a galaxy being in a late-stage merger or in the midst of coalescence.

[Bayesian statistics in medicine -- part II: main applications and inference].

PubMed

Montomoli, C; Nichelatti, M

2008-01-01

Bayesian statistics is not only used when one is dealing with 2-way tables, but it can be used for inferential purposes. Using the basic concepts presented in the first part, this paper aims to give a simple overview of Bayesian methods by introducing its foundation (Bayes' theorem) and then applying this rule to a very simple practical example; whenever possible, the elementary processes at the basis of analysis are compared to those of frequentist (classical) statistical analysis. The Bayesian reasoning is naturally connected to medical activity, since it appears to be quite similar to a diagnostic process.

Prior Elicitation and Bayesian Analysis of the Steroids for Corneal Ulcers Trial

PubMed Central

See, Craig W.; Srinivasan, Muthiah; Saravanan, Somu; Oldenburg, Catherine E.; Esterberg, Elizabeth J.; Ray, Kathryn J.; Glaser, Tanya S.; Tu, Elmer Y.; Zegans, Michael E.; McLeod, Stephen D.; Acharya, Nisha R.; Lietman, Thomas M.

2013-01-01

Purpose To elicit expert opinion on the use of adjunctive corticosteroid therapy in bacterial corneal ulcers. To perform a Bayesian analysis of the Steroids for Corneal Ulcers Trial (SCUT), using expert opinion as a prior probability. Methods The SCUT was a placebo-controlled trial assessing visual outcomes in patients receiving topical corticosteroids or placebo as adjunctive therapy for bacterial keratitis. Questionnaires were conducted at scientific meetings in India and North America to gauge expert consensus on the perceived benefit of corticosteroids as adjunct treatment. Bayesian analysis, using the questionnaire data as a prior probability and the primary outcome of SCUT as a likelihood, was performed. For comparison, an additional Bayesian analysis was performed using the results of the SCUT pilot study as a prior distribution. Results Indian respondents believed there to be a 1.21 Snellen line improvement, and North American respondents believed there to be a 1.24 line improvement with corticosteroid therapy. The SCUT primary outcome found a non-significant 0.09 Snellen line benefit with corticosteroid treatment. The results of the Bayesian analysis estimated a slightly greater benefit than did the SCUT primary analysis (0.19 lines verses 0.09 lines). Conclusion Indian and North American experts had similar expectations on the effectiveness of corticosteroids in bacterial corneal ulcers; that corticosteroids would markedly improve visual outcomes. Bayesian analysis produced results very similar to those produced by the SCUT primary analysis. The similarity in result is likely due to the large sample size of SCUT and helps validate the results of SCUT. PMID:23171211

A Gibbs sampler for Bayesian analysis of site-occupancy data

USGS Publications Warehouse

Dorazio, Robert M.; Rodriguez, Daniel Taylor

2012-01-01

1. A Bayesian analysis of site-occupancy data containing covariates of species occurrence and species detection probabilities is usually completed using Markov chain Monte Carlo methods in conjunction with software programs that can implement those methods for any statistical model, not just site-occupancy models. Although these software programs are quite flexible, considerable experience is often required to specify a model and to initialize the Markov chain so that summaries of the posterior distribution can be estimated efficiently and accurately. 2. As an alternative to these programs, we develop a Gibbs sampler for Bayesian analysis of site-occupancy data that include covariates of species occurrence and species detection probabilities. This Gibbs sampler is based on a class of site-occupancy models in which probabilities of species occurrence and detection are specified as probit-regression functions of site- and survey-specific covariate measurements. 3. To illustrate the Gibbs sampler, we analyse site-occupancy data of the blue hawker, Aeshna cyanea (Odonata, Aeshnidae), a common dragonfly species in Switzerland. Our analysis includes a comparison of results based on Bayesian and classical (non-Bayesian) methods of inference. We also provide code (based on the R software program) for conducting Bayesian and classical analyses of site-occupancy data.

RECONSTRUCTING EXPOSURE SCENARIOS USING DOSE BIOMARKERS - AN APPLICATION OF BAYESIAN UNCERTAINTY ANALYSIS

EPA Science Inventory

We use Bayesian uncertainty analysis to explore how to estimate pollutant exposures from biomarker concentrations. The growing number of national databases with exposure data makes such an analysis possible. They contain datasets of pharmacokinetic biomarkers for many polluta...

Electromigration Mechanism of Failure in Flip-Chip Solder Joints Based on Discrete Void Formation.

PubMed

Chang, Yuan-Wei; Cheng, Yin; Helfen, Lukas; Xu, Feng; Tian, Tian; Scheel, Mario; Di Michiel, Marco; Chen, Chih; Tu, King-Ning; Baumbach, Tilo

2017-12-20

In this investigation, SnAgCu and SN100C solders were electromigration (EM) tested, and the 3D laminography imaging technique was employed for in-situ observation of the microstructure evolution during testing. We found that discrete voids nucleate, grow and coalesce along the intermetallic compound/solder interface during EM testing. A systematic analysis yields quantitative information on the number, volume, and growth rate of voids, and the EM parameter of DZ*. We observe that fast intrinsic diffusion in SnAgCu solder causes void growth and coalescence, while in the SN100C solder this coalescence was not significant. To deduce the current density distribution, finite-element models were constructed on the basis of the laminography images. The discrete voids do not change the global current density distribution, but they induce the local current crowding around the voids: this local current crowding enhances the lateral void growth and coalescence. The correlation between the current density and the probability of void formation indicates that a threshold current density exists for the activation of void formation. There is a significant increase in the probability of void formation when the current density exceeds half of the maximum value.

A zero-gravity demonstration of the collision and coalescence of water droplets

NASA Technical Reports Server (NTRS)

Hung, R. J.; Vaughan, O. H.; Smith, R. E.

1974-01-01

The mechanics of the collision and coalescence of liquid droplets is one of the main research areas in the fields of nuclear physics, astrophysics, meteorology and fluid mechanics. The crew members on the Skylab 3 and 4 missions were requested to perform demonstrations of the collision and coalescence of water droplets under the low gravity environment at orbital altitude. In Skylab 4 two water droplets with equal volumes, 30 cu cm each, were used. A dark colored droplet (contaminated with grape drink) moving with a velocity of 3.14 cm/sec collided with a stationary pink colored droplet (contaminated with strawberry drink) and coalescence occurred. Theoretical models are proposed to study the various stages of the collision-coalescence processes. Special considerations are concentrated in the investigation of the bounce-coalescence and coalescence-instability processes. The surface tension of the coalesced droplets was calculated to be 52 dynes/cm in perfect agreement with laboratory measurements made after the flight using a reproduction of the liquids.

Coalescence-Induced Jumping of Multiple Condensate Droplets on Hierarchical Superhydrophobic Surfaces

PubMed Central

Chen, Xuemei; Patel, Ravi S.; Weibel, Justin A.; Garimella, Suresh V.

2016-01-01

Coalescence-induced jumping of condensate droplets from a superhydrophobic surface with hierarchical micro/nanoscale roughness is quantitatively characterized. Experimental observations show that the condensate droplet jumping is induced by coalescence of multiple droplets of different sizes, and that the coalesced droplet trajectories typically deviate from the surface normal. A depth-from-defocus image processing technique is developed to track the out-of-plane displacement of the jumping droplets, so as to accurately measure the droplet size and velocity. The results demonstrate that the highest jumping velocity is achieved when two droplets coalesce. The jumping velocity decreases gradually with an increase in the number of coalescing droplets, despite the greater potential surface energy released upon coalescence. A general theoretical model that accounts for viscous dissipation, surface adhesion, line tension, the initial droplet wetting states, and the number and sizes of the coalescing droplets is developed to explain the trends of droplet jumping velocity observed in the experiments. PMID:26725512

Theoretical Coalescence: A Method to Develop Qualitative Theory: The Example of Enduring.

PubMed

Morse, Janice M

Qualitative research is frequently context bound, lacks generalizability, and is limited in scope. The purpose of this article was to describe a method, theoretical coalescence, that provides a strategy for analyzing complex, high-level concepts and for developing generalizable theory. Theoretical coalescence is a method of theoretical expansion, inductive inquiry, of theory development, that uses data (rather than themes, categories, and published extracts of data) as the primary source for analysis. Here, using the development of the lay concept of enduring as an example, I explore the scientific development of the concept in multiple settings over many projects and link it within the Praxis Theory of Suffering. As comprehension emerges when conducting theoretical coalescence, it is essential that raw data from various different situations be available for reinterpretation/reanalysis and comparison to identify the essential features of the concept. The concept is then reconstructed, with additional inquiry that builds description, and evidence is conducted and conceptualized to create a more expansive concept and theory. By utilizing apparently diverse data sets from different contexts that are linked by certain characteristics, the essential features of the concept emerge. Such inquiry is divergent and less bound by context yet purposeful, logical, and with significant pragmatic implications for practice in nursing and beyond our discipline. Theoretical coalescence is a means by which qualitative inquiry is broadened to make an impact, to accommodate new theoretical shifts and concepts, and to make qualitative research applied and accessible in new ways.

Theoretical Coalescence: A Method to Develop Qualitative Theory

PubMed Central

Morse, Janice M.

2018-01-01

Background Qualitative research is frequently context bound, lacks generalizability, and is limited in scope. Objectives The purpose of this article was to describe a method, theoretical coalescence, that provides a strategy for analyzing complex, high-level concepts and for developing generalizable theory. Theoretical coalescence is a method of theoretical expansion, inductive inquiry, of theory development, that uses data (rather than themes, categories, and published extracts of data) as the primary source for analysis. Here, using the development of the lay concept of enduring as an example, I explore the scientific development of the concept in multiple settings over many projects and link it within the Praxis Theory of Suffering. Methods As comprehension emerges when conducting theoretical coalescence, it is essential that raw data from various different situations be available for reinterpretation/reanalysis and comparison to identify the essential features of the concept. The concept is then reconstructed, with additional inquiry that builds description, and evidence is conducted and conceptualized to create a more expansive concept and theory. Results By utilizing apparently diverse data sets from different contexts that are linked by certain characteristics, the essential features of the concept emerge. Such inquiry is divergent and less bound by context yet purposeful, logical, and with significant pragmatic implications for practice in nursing and beyond our discipline. Conclusion Theoretical coalescence is a means by which qualitative inquiry is broadened to make an impact, to accommodate new theoretical shifts and concepts, and to make qualitative research applied and accessible in new ways. PMID:29360688

Theory of peak coalescence in Fourier transform ion cyclotron resonance mass spectrometry.

PubMed

Boldin, Ivan A; Nikolaev, Eugene N

2009-10-01

Peak coalescence, i.e. the merging of two close peaks in a Fourier transform ion cyclotron resonance (FTICR) mass spectrum at a high number of ions, plays an important role in various FTICR experiments. In order to describe the coalescence phenomenon we would like to propose a new theory of motion for ion clouds with close mass-to-charge ratios, driven by a uniform magnetic field and Coulomb interactions between the clouds. We describe the motion of the ion clouds in terms of their averaged drift motion in crossed magnetic and electric fields. The ion clouds are considered to be of constant size and their motion is studied in two dimensions. The theory deals with the first-order approximation of the equations of motion in relation to dm/m, where dm is the mass difference and m is the mass of a single ion. The analysis was done for an arbitrary inter-cloud interaction potential, which makes it possible to analyze finite-size ion clouds of any shape. The final analytical expression for the condition of the onset of coalescence is found for the case of uniformly charged spheres. An algorithm for finding this condition for an arbitrary interaction potential is proposed. The critical number of ions for the peak coalescence to take place is shown to depend quadratically on the magnetic field strength and to be proportional to the cyclotron radius and inversely proportional to the ion masses. Copyright (c) 2009 John Wiley & Sons, Ltd.

Bayesian Factor Analysis as a Variable Selection Problem: Alternative Priors and Consequences

PubMed Central

Lu, Zhao-Hua; Chow, Sy-Miin; Loken, Eric

2016-01-01

Factor analysis is a popular statistical technique for multivariate data analysis. Developments in the structural equation modeling framework have enabled the use of hybrid confirmatory/exploratory approaches in which factor loading structures can be explored relatively flexibly within a confirmatory factor analysis (CFA) framework. Recently, a Bayesian structural equation modeling (BSEM) approach (Muthén & Asparouhov, 2012) has been proposed as a way to explore the presence of cross-loadings in CFA models. We show that the issue of determining factor loading patterns may be formulated as a Bayesian variable selection problem in which Muthén and Asparouhov’s approach can be regarded as a BSEM approach with ridge regression prior (BSEM-RP). We propose another Bayesian approach, denoted herein as the Bayesian structural equation modeling with spike and slab prior (BSEM-SSP), which serves as a one-stage alternative to the BSEM-RP. We review the theoretical advantages and disadvantages of both approaches and compare their empirical performance relative to two modification indices-based approaches and exploratory factor analysis with target rotation. A teacher stress scale data set (Byrne, 2012; Pettegrew & Wolf, 1982) is used to demonstrate our approach. PMID:27314566

Application of a data-mining method based on Bayesian networks to lesion-deficit analysis

NASA Technical Reports Server (NTRS)

Herskovits, Edward H.; Gerring, Joan P.

2003-01-01

Although lesion-deficit analysis (LDA) has provided extensive information about structure-function associations in the human brain, LDA has suffered from the difficulties inherent to the analysis of spatial data, i.e., there are many more variables than subjects, and data may be difficult to model using standard distributions, such as the normal distribution. We herein describe a Bayesian method for LDA; this method is based on data-mining techniques that employ Bayesian networks to represent structure-function associations. These methods are computationally tractable, and can represent complex, nonlinear structure-function associations. When applied to the evaluation of data obtained from a study of the psychiatric sequelae of traumatic brain injury in children, this method generates a Bayesian network that demonstrates complex, nonlinear associations among lesions in the left caudate, right globus pallidus, right side of the corpus callosum, right caudate, and left thalamus, and subsequent development of attention-deficit hyperactivity disorder, confirming and extending our previous statistical analysis of these data. Furthermore, analysis of simulated data indicates that methods based on Bayesian networks may be more sensitive and specific for detecting associations among categorical variables than methods based on chi-square and Fisher exact statistics.

Divergence and codon usage bias of Betanodavirus, a neurotropic pathogen in fish.

PubMed

He, Mei; Teng, Chun-Bo

2015-02-01

Betanodavirus is a small bipartite RNA virus of global economical significance that can cause severe neurological disorders to an increasing number of marine fish species. Herein, to further the understanding of the evolution of betanodavirus, Bayesian coalescent analyses were conducted to the time-stamped entire coding sequences of their RNA polymerase and coat protein genes. Similar moderate nucleotide substitution rates were then estimated for the two genes. According to age calculations, the divergence of the two genes into the four genotypes initiated nearly simultaneously at ∼700 years ago, despite the different scenarios, whereas the seven analyzed chimeric isolates might be the outcomes of a single genetic reassortment event taking place in the early 1980s in Southern Europe. Furthermore, codon usage bias analyses indicated that each gene had influences in addition to mutational bias and codon choice of betanodavirus was not completely complied with that of fish host. Copyright © 2014 Elsevier Inc. All rights reserved.

Holarctic genetic structure and range dynamics in the woolly mammoth

PubMed Central

Palkopoulou, Eleftheria; Dalén, Love; Lister, Adrian M.; Vartanyan, Sergey; Sablin, Mikhail; Sher, Andrei; Edmark, Veronica Nyström; Brandström, Mikael D.; Germonpré, Mietje; Barnes, Ian; Thomas, Jessica A.

2013-01-01

Ancient DNA analyses have provided enhanced resolution of population histories in many Pleistocene taxa. However, most studies are spatially restricted, making inference of species-level biogeographic histories difficult. Here, we analyse mitochondrial DNA (mtDNA) variation in the woolly mammoth from across its Holarctic range to reconstruct its history over the last 200 thousand years (kyr). We identify a previously undocumented major mtDNA lineage in Europe, which was replaced by another major mtDNA lineage 32–34 kyr before present (BP). Coalescent simulations provide support for demographic expansions at approximately 121 kyr BP, suggesting that the previous interglacial was an important driver for demography and intraspecific genetic divergence. Furthermore, our results suggest an expansion into Eurasia from America around 66 kyr BP, coinciding with the first exposure of the Bering Land Bridge during the Late Pleistocene. Bayesian inference indicates Late Pleistocene demographic stability until 20–15 kyr BP, when a severe population size decline occurred. PMID:24026825

Diagnostic accuracy of a bayesian latent group analysis for the detection of malingering-related poor effort.

PubMed

Ortega, Alonso; Labrenz, Stephan; Markowitsch, Hans J; Piefke, Martina

2013-01-01

In the last decade, different statistical techniques have been introduced to improve assessment of malingering-related poor effort. In this context, we have recently shown preliminary evidence that a Bayesian latent group model may help to optimize classification accuracy using a simulation research design. In the present study, we conducted two analyses. Firstly, we evaluated how accurately this Bayesian approach can distinguish between participants answering in an honest way (honest response group) and participants feigning cognitive impairment (experimental malingering group). Secondly, we tested the accuracy of our model in the differentiation between patients who had real cognitive deficits (cognitively impaired group) and participants who belonged to the experimental malingering group. All Bayesian analyses were conducted using the raw scores of a visual recognition forced-choice task (2AFC), the Test of Memory Malingering (TOMM, Trial 2), and the Word Memory Test (WMT, primary effort subtests). The first analysis showed 100% accuracy for the Bayesian model in distinguishing participants of both groups with all effort measures. The second analysis showed outstanding overall accuracy of the Bayesian model when estimates were obtained from the 2AFC and the TOMM raw scores. Diagnostic accuracy of the Bayesian model diminished when using the WMT total raw scores. Despite, overall diagnostic accuracy can still be considered excellent. The most plausible explanation for this decrement is the low performance in verbal recognition and fluency tasks of some patients of the cognitively impaired group. Additionally, the Bayesian model provides individual estimates, p(zi |D), of examinees' effort levels. In conclusion, both high classification accuracy levels and Bayesian individual estimates of effort may be very useful for clinicians when assessing for effort in medico-legal settings.

Scaling laws and dynamics of bubble coalescence

NASA Astrophysics Data System (ADS)

Anthony, Christopher R.; Kamat, Pritish M.; Thete, Sumeet S.; Munro, James P.; Lister, John R.; Harris, Michael T.; Basaran, Osman A.

2017-08-01

The coalescence of bubbles and drops plays a central role in nature and industry. During coalescence, two bubbles or drops touch and merge into one as the neck connecting them grows from microscopic to macroscopic scales. The hydrodynamic singularity that arises when two bubbles or drops have just touched and the flows that ensue have been studied thoroughly when two drops coalesce in a dynamically passive outer fluid. In this paper, the coalescence of two identical and initially spherical bubbles, which are idealized as voids that are surrounded by an incompressible Newtonian liquid, is analyzed by numerical simulation. This problem has recently been studied (a) experimentally using high-speed imaging and (b) by asymptotic analysis in which the dynamics is analyzed by determining the growth of a hole in the thin liquid sheet separating the two bubbles. In the latter, advantage is taken of the fact that the flow in the thin sheet of nonconstant thickness is governed by a set of one-dimensional, radial extensional flow equations. While these studies agree on the power law scaling of the variation of the minimum neck radius with time, they disagree with respect to the numerical value of the prefactors in the scaling laws. In order to reconcile these differences and also provide insights into the dynamics that are difficult to probe by either of the aforementioned approaches, simulations are used to access both earlier times than has been possible in the experiments and also later times when asymptotic analysis is no longer applicable. Early times and extremely small length scales are attained in the new simulations through the use of a truncated domain approach. Furthermore, it is shown by direct numerical simulations in which the flow within the bubbles is also determined along with the flow exterior to them that idealizing the bubbles as passive voids has virtually no effect on the scaling laws relating minimum neck radius and time.

A Six Nuclear Gene Phylogeny of Citrus (Rutaceae) Taking into Account Hybridization and Lineage Sorting

PubMed Central

Keremane, Manjunath L.; Lee, Richard F.; Maureira-Butler, Ivan J.; Roose, Mikeal L.

2013-01-01

Background Genus Citrus (Rutaceae) comprises many important cultivated species that generally hybridize easily. Phylogenetic study of a group showing extensive hybridization is challenging. Since the genus Citrus has diverged recently (4–12 Ma), incomplete lineage sorting of ancestral polymorphisms is also likely to cause discrepancies among genes in phylogenetic inferences. Incongruence of gene trees is observed and it is essential to unravel the processes that cause inconsistencies in order to understand the phylogenetic relationships among the species. Methodology and Principal Findings (1) We generated phylogenetic trees using haplotype sequences of six low copy nuclear genes. (2) Published simple sequence repeat data were re-analyzed to study population structure and the results were compared with the phylogenetic trees constructed using sequence data and coalescence simulations. (3) To distinguish between hybridization and incomplete lineage sorting, we developed and utilized a coalescence simulation approach. In other studies, species trees have been inferred despite the possibility of hybridization having occurred and used to generate null distributions of the effect of lineage sorting alone (by coalescent simulation). Since this is problematic, we instead generate these distributions directly from observed gene trees. Of the six trees generated, we used the most resolved three to detect hybrids. We found that 11 of 33 samples appear to be affected by historical hybridization. Analysis of the remaining three genes supported the conclusions from the hybrid detection test. Conclusions We have identified or confirmed probable hybrid origins for several Citrus cultivars using three different approaches–gene phylogenies, population structure analysis and coalescence simulation. Hybridization and incomplete lineage sorting were identified primarily based on differences among gene phylogenies with reference to null expectations via coalescence simulations. We conclude that identifying hybridization as a frequent cause of incongruence among gene trees is critical to correctly infer the phylogeny among species of Citrus. PMID:23874615

The Scirtothrips dorsalis Species Complex: Endemism and Invasion in a Global Pest

PubMed Central

Dickey, Aaron M.; Kumar, Vivek; Hoddle, Mark S.; Funderburk, Joe E.; Morgan, J. Kent; Jara-Cavieres, Antonella; Shatters, Robert G. Jr.; Osborne, Lance S.; McKenzie, Cindy L.

2015-01-01

Invasive arthropods pose unique management challenges in various environments, the first of which is correct identification. This apparently mundane task is particularly difficult if multiple species are morphologically indistinguishable but accurate identification can be determined with DNA barcoding provided an adequate reference set is available. Scirtothrips dorsalis is a highly polyphagous plant pest with a rapidly expanding global distribution and this species, as currently recognized, may be comprised of cryptic species. Here we report the development of a comprehensive DNA barcode library for S. dorsalis and seven nuclear markers via next-generation sequencing for identification use within the complex. We also report the delimitation of nine cryptic species and two morphologically distinguishable species comprising the S. dorsalis species complex using histogram analysis of DNA barcodes, Bayesian phylogenetics, and the multi-species coalescent. One member of the complex, here designated the South Asia 1 cryptic species, is highly invasive, polyphagous, and likely the species implicated in tospovirus transmission. Two other species, South Asia 2, and East Asia 1 are also highly polyphagous and appear to be at an earlier stage of global invasion. The remaining members of the complex are regionally endemic, varying in their pest status and degree of polyphagy. In addition to patterns of invasion and endemism, our results provide a framework both for identifying members of the complex based on their DNA barcode, and for future species delimiting efforts. PMID:25893251

Hiding deep in the trees: discovery of divergent mitochondrial lineages in Malagasy chameleons of the Calumma nasutum group

PubMed Central

Gehring, Philip-Sebastian; Tolley, Krystal A; Eckhardt, Falk Sebastian; Townsend, Ted M; Ziegler, Thomas; Ratsoavina, Fanomezana; Glaw, Frank; Vences, Miguel

2012-01-01

We conducted a comprehensive molecular phylogenetic study for a group of chameleons from Madagascar (Chamaeleonidae: Calumma nasutum group, comprising seven nominal species) to examine the genetic and species diversity in this widespread genus. Based on DNA sequences of the mitochondrial gene (ND2) from 215 specimens, we reconstructed the phylogeny using a Bayesian approach. Our results show deep divergences among several unnamed mitochondrial lineages that are difficult to identify morphologically. We evaluated lineage diversification using a number of statistical phylogenetic methods (general mixed Yule-coalescent model; SpeciesIdentifier; net p-distances) to objectively delimit lineages that we here consider as operational taxonomic units (OTUs), and for which the taxonomic status remains largely unknown. In addition, we compared molecular and morphological differentiation in detail for one particularly diverse clade (the C. boettgeri complex) from northern Madagascar. To assess the species boundaries within this group we used an integrative taxonomic approach, combining evidence from two independent molecular markers (ND2 and CMOS), together with genital and other external morphological characters, and conclude that some of the newly discovered OTUs are separate species (confirmed candidate species, CCS), while others should best be considered as deep conspecific lineages (DCLs). Our analysis supports a total of 33 OTUs, of which seven correspond to described species, suggesting that the taxonomy of the C. nasutum group is in need of revision. PMID:22957155

Diversification of Rice Yellow Mottle Virus and Related Viruses Spans the History of Agriculture from the Neolithic to the Present

PubMed Central

Fargette, Denis; Pinel-Galzi, Agnès; Sérémé, Drissa; Lacombe, Séverine; Hébrard, Eugénie; Traoré, Oumar; Konaté, Gnissa

2008-01-01

The mechanisms of evolution of plant viruses are being unraveled, yet the timescale of their evolution remains an enigma. To address this critical issue, the divergence time of plant viruses at the intra- and inter-specific levels was assessed. The time of the most recent common ancestor (TMRCA) of Rice yellow mottle virus (RYMV; genus Sobemovirus) was calculated by a Bayesian coalescent analysis of the coat protein sequences of 253 isolates collected between 1966 and 2006 from all over Africa. It is inferred that RYMV diversified approximately 200 years ago in Africa, i.e., centuries after rice was domesticated or introduced, and decades before epidemics were reported. The divergence time of sobemoviruses and viruses of related genera was subsequently assessed using the age of RYMV under a relaxed molecular clock for calibration. The divergence time between sobemoviruses and related viruses was estimated to be approximately 9,000 years, that between sobemoviruses and poleroviruses approximately 5,000 years, and that among sobemoviruses approximately 3,000 years. The TMRCA of closely related pairs of sobemoviruses, poleroviruses, and luteoviruses was approximately 500 years, which is a measure of the time associated with plant virus speciation. It is concluded that the diversification of RYMV and related viruses has spanned the history of agriculture, from the Neolithic age to the present. PMID:18704169

Non-toxigenic environmental Vibrio cholerae O1 strain from Haiti provides evidence of pre-pandemic cholera in Hispaniola.

PubMed

Azarian, Taj; Ali, Afsar; Johnson, Judith A; Jubair, Mohammad; Cella, Eleonora; Ciccozzi, Massimo; Nolan, David J; Farmerie, William; Rashid, Mohammad H; Sinha-Ray, Shrestha; Alam, Meer T; Morris, J Glenn; Salemi, Marco

2016-10-27

Vibrio cholerae is ubiquitous in aquatic environments, with environmental toxigenic V. cholerae O1 strains serving as a source for recurrent cholera epidemics and pandemic disease. However, a number of questions remain about long-term survival and evolution of V. cholerae strains within these aquatic environmental reservoirs. Through monitoring of the Haitian aquatic environment following the 2010 cholera epidemic, we isolated two novel non-toxigenic (ctxA/B-negative) Vibrio cholerae O1. These two isolates underwent whole-genome sequencing and were investigated through comparative genomics and Bayesian coalescent analysis. These isolates cluster in the evolutionary tree with strains responsible for clinical cholera, possessing genomic components of 6 th and 7 th pandemic lineages, and diverge from "modern" cholera strains around 1548 C.E. [95% HPD: 1532-1555]. Vibrio Pathogenicity Island (VPI)-1 was present; however, SXT/R391-family ICE and VPI-2 were absent. Rugose phenotype conversion and vibriophage resistance evidenced adaption for persistence in aquatic environments. The identification of V. cholerae O1 strains in the Haitian environment, which predate the first reported cholera pandemic in 1817, broadens our understanding of the history of pandemics. It also raises the possibility that these and similar environmental strains could acquire virulence genes from the 2010 Haitian epidemic clone, including the cholera toxin producing CTXϕ.

Chronology of the last glacial maximum in the upper Bear River Basin, Utah

USGS Publications Warehouse

Laabs, B.J.C.; Munroe, Jeffrey S.; Rosenbaum, J.G.; Refsnider, K.A.; Mickelson, D.M.; Singer, B.S.; Caffee, M.W.

2007-01-01

The headwaters of the Bear River drainage were occupied during the Last Glacial Maximum (LGM) by outlet glaciers of the Western Uinta Ice Field, an extensive ice mass (???685 km2) that covered the western slope of the Uinta Mountains. A well-preserved sequence of latero-frontal moraines in the drainage indicates that outlet glaciers advanced beyond the mountain front and coalesced on the piedmont. Glacial deposits in the Bear River drainage provide a unique setting where both 10Be cosmogenic surface-exposure dating of moraine boulders and 14C dating of sediment in Bear Lake downstream of the glaciated area set age limits on the timing of glaciation. Limiting 14C ages of glacial flour in Bear Lake (corrected to calendar years using CALIB 5.0) indicate that ice advance began at 32 ka and culminated at about 24 ka. Based on a Bayesian statistical analysis of cosmogenic surface-exposure ages from two areas on the terminal moraine complex, the Bear River glacier began its final retreat at about 18.7 to 18.1 ka, approximately coincident with the start of deglaciation elsewhere in the central Rocky Mountains and many other alpine glacial localities worldwide. Unlike valleys of the southwestern Uinta Mountains, deglaciation of the Bear River drainage began prior to the hydrologie fall of Lake Bonneville from the Provo shoreline at about 16 ka. ?? 2007 Regents of the University of Colorado.

Coalescence preference in densely packed microbubbles

DOE PAGES

Kim, Yeseul; Lim, Su Jin; Gim, Bopil; ...

2015-01-13

A bubble merged from two parent bubbles with different size tends to be placed closer to the larger parent. This phenomenon is known as the coalescence preference. Here we demonstrate that the coalescence preference can be blocked inside a densely packed cluster of bubbles. We utilized high-speed high-resolution X-ray microscopy to clearly visualize individual coalescence events inside densely packed microbubbles with a local packing fraction of ~40%. Thus, the surface energy release theory predicts an exponent of 5 in a relation between the relative coalescence position and the parent size ratio, whereas our observation for coalescence in densely packed microbubblesmore » shows a different exponent of 2. We believe that this result would be important to understand the reality of coalescence dynamics in a variety of packing situations of soft matter.« less

Coalescence preference in densely packed microbubbles

DOE Office of Scientific and Technical Information (OSTI.GOV)

Kim, Yeseul; Lim, Su Jin; Gim, Bopil

A bubble merged from two parent bubbles with different size tends to be placed closer to the larger parent. This phenomenon is known as the coalescence preference. Here we demonstrate that the coalescence preference can be blocked inside a densely packed cluster of bubbles. We utilized high-speed high-resolution X-ray microscopy to clearly visualize individual coalescence events inside densely packed microbubbles with a local packing fraction of ~40%. Thus, the surface energy release theory predicts an exponent of 5 in a relation between the relative coalescence position and the parent size ratio, whereas our observation for coalescence in densely packed microbubblesmore » shows a different exponent of 2. We believe that this result would be important to understand the reality of coalescence dynamics in a variety of packing situations of soft matter.« less

Acoustic emission characterization of microcracking in laboratory-scale hydraulic fracturing tests

DOE Office of Scientific and Technical Information (OSTI.GOV)

Hampton, Jesse; Gutierrez, Marte; Matzar, Luis

Understanding microcracking near coalesced fracture generation is critically important for hydrocarbon and geothermal reservoir characterization as well as damage evaluation in civil engineering structures. Dense and sometimes random microcracking near coalesced fracture formation alters the mechanical properties of the nearby virgin material. Individual microcrack characterization is also significant in quantifying the material changes near the fracture faces (i.e. damage). Acoustic emission (AE) monitoring and analysis provide unique information regarding the microcracking process temporally, and information concerning the source characterization of individual microcracks can be extracted. In this context, laboratory hydraulic fracture tests were carried out while monitoring the AEs frommore » several piezoelectric transducers. In-depth post-processing of the AE event data was performed for the purpose of understanding the individual source mechanisms. Several source characterization techniques including moment tensor inversion, event parametric analysis, and volumetric deformation analysis were adopted. Post-test fracture characterization through coring, slicing and micro-computed tomographic imaging was performed to determine the coalesced fracture location and structure. Distinct differences in fracture characteristics were found spatially in relation to the openhole injection interval. Individual microcrack AE analysis showed substantial energy reduction emanating spatially from the injection interval. Lastly, it was quantitatively observed that the recorded AE signals provided sufficient information to generalize the damage radiating spatially away from the injection wellbore.« less

Acoustic emission characterization of microcracking in laboratory-scale hydraulic fracturing tests

DOE PAGES

Hampton, Jesse; Gutierrez, Marte; Matzar, Luis; ...

2018-06-11

Understanding microcracking near coalesced fracture generation is critically important for hydrocarbon and geothermal reservoir characterization as well as damage evaluation in civil engineering structures. Dense and sometimes random microcracking near coalesced fracture formation alters the mechanical properties of the nearby virgin material. Individual microcrack characterization is also significant in quantifying the material changes near the fracture faces (i.e. damage). Acoustic emission (AE) monitoring and analysis provide unique information regarding the microcracking process temporally, and information concerning the source characterization of individual microcracks can be extracted. In this context, laboratory hydraulic fracture tests were carried out while monitoring the AEs frommore » several piezoelectric transducers. In-depth post-processing of the AE event data was performed for the purpose of understanding the individual source mechanisms. Several source characterization techniques including moment tensor inversion, event parametric analysis, and volumetric deformation analysis were adopted. Post-test fracture characterization through coring, slicing and micro-computed tomographic imaging was performed to determine the coalesced fracture location and structure. Distinct differences in fracture characteristics were found spatially in relation to the openhole injection interval. Individual microcrack AE analysis showed substantial energy reduction emanating spatially from the injection interval. Lastly, it was quantitatively observed that the recorded AE signals provided sufficient information to generalize the damage radiating spatially away from the injection wellbore.« less

Field-Controlled Electrical Switch with Liquid Metal.

PubMed

Wissman, James; Dickey, Michael D; Majidi, Carmel

2017-12-01

When immersed in an electrolyte, droplets of Ga-based liquid metal (LM) alloy can be manipulated in ways not possible with conventional electrocapillarity or electrowetting. This study demonstrates how LM electrochemistry can be exploited to coalesce and separate droplets under moderate voltages of ~1-10 V. This novel approach to droplet interaction can be explained with a theory that accounts for oxidation and reduction as well as fluidic instabilities. Based on simulations and experimental analysis, this study finds that droplet separation is governed by a unique limit-point instability that arises from gradients in bipolar electrochemical reactions that lead to gradients in interfacial tension. The LM coalescence and separation are used to create a field-programmable electrical switch. As with conventional relays or flip-flop latch circuits, the system can transition between bistable (separated or coalesced) states, making it useful for memory storage, logic, and shape-programmable circuitry using entirely liquids instead of solid-state materials.

The impact of using informative priors in a Bayesian cost-effectiveness analysis: an application of endovascular versus open surgical repair for abdominal aortic aneurysms in high-risk patients.

PubMed

McCarron, C Elizabeth; Pullenayegum, Eleanor M; Thabane, Lehana; Goeree, Ron; Tarride, Jean-Eric

2013-04-01

Bayesian methods have been proposed as a way of synthesizing all available evidence to inform decision making. However, few practical applications of the use of Bayesian methods for combining patient-level data (i.e., trial) with additional evidence (e.g., literature) exist in the cost-effectiveness literature. The objective of this study was to compare a Bayesian cost-effectiveness analysis using informative priors to a standard non-Bayesian nonparametric method to assess the impact of incorporating additional information into a cost-effectiveness analysis. Patient-level data from a previously published nonrandomized study were analyzed using traditional nonparametric bootstrap techniques and bivariate normal Bayesian models with vague and informative priors. Two different types of informative priors were considered to reflect different valuations of the additional evidence relative to the patient-level data (i.e., "face value" and "skeptical"). The impact of using different distributions and valuations was assessed in a sensitivity analysis. Models were compared in terms of incremental net monetary benefit (INMB) and cost-effectiveness acceptability frontiers (CEAFs). The bootstrapping and Bayesian analyses using vague priors provided similar results. The most pronounced impact of incorporating the informative priors was the increase in estimated life years in the control arm relative to what was observed in the patient-level data alone. Consequently, the incremental difference in life years originally observed in the patient-level data was reduced, and the INMB and CEAF changed accordingly. The results of this study demonstrate the potential impact and importance of incorporating additional information into an analysis of patient-level data, suggesting this could alter decisions as to whether a treatment should be adopted and whether more information should be acquired.

Investigations on the droplet distributions in the atomization of kerosene jets in supersonic crossflows

DOE Office of Scientific and Technical Information (OSTI.GOV)

Wu, Liyin; Wang, Zhen-guo, E-mail: wangzhenguo-wzg@163.com; Li, Qinglian

2015-09-07

Phase Doppler anemometry was applied to investigate the atomization processes of a kerosene jet injected into Ma = 1.86 crossflow. Physical behaviors, such as breakup and coalescence, are reproduced through the analysis of the spatial distribution of kerosene droplets' size. It is concluded that Sauter mean diameter distribution shape transforms into “I” type from “C” type as the atomization development. Simultaneously, the breakup of large droplets and the coalescence of small droplets can be observed throughout the whole atomization process.

The PyCBC search for binary black hole coalescences in Advanced LIGO's first observing run

NASA Astrophysics Data System (ADS)

Willis, Joshua; LIGO Scientific Collaboration

2017-01-01

Advanced LIGO's first observing run saw the first detections of binary black hole coalescences. We describe the PyCBC matched filter analysis, and the results of that search for binary systems with total mass up to 100 solar masses. This is a matched filter search for general-relativistic signals from binary black hole systems. Two signals, GW150914 and GW151226, were identified with very high significance, and a third possible signal, LVT151012, was found, though at much lower significance. Supported by NSF award PHY-1506254.

Single-Case Time Series with Bayesian Analysis: A Practitioner's Guide.

ERIC Educational Resources Information Center

Jones, W. Paul

2003-01-01

This article illustrates a simplified time series analysis for use by the counseling researcher practitioner in single-case baseline plus intervention studies with a Bayesian probability analysis to integrate findings from replications. The C statistic is recommended as a primary analysis tool with particular relevance in the context of actual…

Daniel Goodman’s empirical approach to Bayesian statistics

USGS Publications Warehouse

Gerrodette, Tim; Ward, Eric; Taylor, Rebecca L.; Schwarz, Lisa K.; Eguchi, Tomoharu; Wade, Paul; Himes Boor, Gina

2016-01-01

Bayesian statistics, in contrast to classical statistics, uses probability to represent uncertainty about the state of knowledge. Bayesian statistics has often been associated with the idea that knowledge is subjective and that a probability distribution represents a personal degree of belief. Dr. Daniel Goodman considered this viewpoint problematic for issues of public policy. He sought to ground his Bayesian approach in data, and advocated the construction of a prior as an empirical histogram of “similar” cases. In this way, the posterior distribution that results from a Bayesian analysis combined comparable previous data with case-specific current data, using Bayes’ formula. Goodman championed such a data-based approach, but he acknowledged that it was difficult in practice. If based on a true representation of our knowledge and uncertainty, Goodman argued that risk assessment and decision-making could be an exact science, despite the uncertainties. In his view, Bayesian statistics is a critical component of this science because a Bayesian analysis produces the probabilities of future outcomes. Indeed, Goodman maintained that the Bayesian machinery, following the rules of conditional probability, offered the best legitimate inference from available data. We give an example of an informative prior in a recent study of Steller sea lion spatial use patterns in Alaska.

Robust Bayesian Factor Analysis

ERIC Educational Resources Information Center

Hayashi, Kentaro; Yuan, Ke-Hai

2003-01-01

Bayesian factor analysis (BFA) assumes the normal distribution of the current sample conditional on the parameters. Practical data in social and behavioral sciences typically have significant skewness and kurtosis. If the normality assumption is not attainable, the posterior analysis will be inaccurate, although the BFA depends less on the current…

Bayesian Meta-Analysis of Coefficient Alpha

ERIC Educational Resources Information Center

Brannick, Michael T.; Zhang, Nanhua

2013-01-01

The current paper describes and illustrates a Bayesian approach to the meta-analysis of coefficient alpha. Alpha is the most commonly used estimate of the reliability or consistency (freedom from measurement error) for educational and psychological measures. The conventional approach to meta-analysis uses inverse variance weights to combine…

Analyzing small data sets using Bayesian estimation: the case of posttraumatic stress symptoms following mechanical ventilation in burn survivors

PubMed Central

van de Schoot, Rens; Broere, Joris J.; Perryck, Koen H.; Zondervan-Zwijnenburg, Mariëlle; van Loey, Nancy E.

2015-01-01

Background The analysis of small data sets in longitudinal studies can lead to power issues and often suffers from biased parameter values. These issues can be solved by using Bayesian estimation in conjunction with informative prior distributions. By means of a simulation study and an empirical example concerning posttraumatic stress symptoms (PTSS) following mechanical ventilation in burn survivors, we demonstrate the advantages and potential pitfalls of using Bayesian estimation. Methods First, we show how to specify prior distributions and by means of a sensitivity analysis we demonstrate how to check the exact influence of the prior (mis-) specification. Thereafter, we show by means of a simulation the situations in which the Bayesian approach outperforms the default, maximum likelihood and approach. Finally, we re-analyze empirical data on burn survivors which provided preliminary evidence of an aversive influence of a period of mechanical ventilation on the course of PTSS following burns. Results Not suprisingly, maximum likelihood estimation showed insufficient coverage as well as power with very small samples. Only when Bayesian analysis, in conjunction with informative priors, was used power increased to acceptable levels. As expected, we showed that the smaller the sample size the more the results rely on the prior specification. Conclusion We show that two issues often encountered during analysis of small samples, power and biased parameters, can be solved by including prior information into Bayesian analysis. We argue that the use of informative priors should always be reported together with a sensitivity analysis. PMID:25765534

Analyzing small data sets using Bayesian estimation: the case of posttraumatic stress symptoms following mechanical ventilation in burn survivors.

PubMed

van de Schoot, Rens; Broere, Joris J; Perryck, Koen H; Zondervan-Zwijnenburg, Mariëlle; van Loey, Nancy E

2015-01-01

Background : The analysis of small data sets in longitudinal studies can lead to power issues and often suffers from biased parameter values. These issues can be solved by using Bayesian estimation in conjunction with informative prior distributions. By means of a simulation study and an empirical example concerning posttraumatic stress symptoms (PTSS) following mechanical ventilation in burn survivors, we demonstrate the advantages and potential pitfalls of using Bayesian estimation. Methods : First, we show how to specify prior distributions and by means of a sensitivity analysis we demonstrate how to check the exact influence of the prior (mis-) specification. Thereafter, we show by means of a simulation the situations in which the Bayesian approach outperforms the default, maximum likelihood and approach. Finally, we re-analyze empirical data on burn survivors which provided preliminary evidence of an aversive influence of a period of mechanical ventilation on the course of PTSS following burns. Results : Not suprisingly, maximum likelihood estimation showed insufficient coverage as well as power with very small samples. Only when Bayesian analysis, in conjunction with informative priors, was used power increased to acceptable levels. As expected, we showed that the smaller the sample size the more the results rely on the prior specification. Conclusion : We show that two issues often encountered during analysis of small samples, power and biased parameters, can be solved by including prior information into Bayesian analysis. We argue that the use of informative priors should always be reported together with a sensitivity analysis.

Bayesian dose-response analysis for epidemiological studies with complex uncertainty in dose estimation.

PubMed

Kwon, Deukwoo; Hoffman, F Owen; Moroz, Brian E; Simon, Steven L

2016-02-10

Most conventional risk analysis methods rely on a single best estimate of exposure per person, which does not allow for adjustment for exposure-related uncertainty. Here, we propose a Bayesian model averaging method to properly quantify the relationship between radiation dose and disease outcomes by accounting for shared and unshared uncertainty in estimated dose. Our Bayesian risk analysis method utilizes multiple realizations of sets (vectors) of doses generated by a two-dimensional Monte Carlo simulation method that properly separates shared and unshared errors in dose estimation. The exposure model used in this work is taken from a study of the risk of thyroid nodules among a cohort of 2376 subjects who were exposed to fallout from nuclear testing in Kazakhstan. We assessed the performance of our method through an extensive series of simulations and comparisons against conventional regression risk analysis methods. When the estimated doses contain relatively small amounts of uncertainty, the Bayesian method using multiple a priori plausible draws of dose vectors gave similar results to the conventional regression-based methods of dose-response analysis. However, when large and complex mixtures of shared and unshared uncertainties are present, the Bayesian method using multiple dose vectors had significantly lower relative bias than conventional regression-based risk analysis methods and better coverage, that is, a markedly increased capability to include the true risk coefficient within the 95% credible interval of the Bayesian-based risk estimate. An evaluation of the dose-response using our method is presented for an epidemiological study of thyroid disease following radiation exposure. Copyright © 2015 John Wiley & Sons, Ltd.

The Importance of Proving the Null

ERIC Educational Resources Information Center

Gallistel, C. R.

2009-01-01

Null hypotheses are simple, precise, and theoretically important. Conventional statistical analysis cannot support them; Bayesian analysis can. The challenge in a Bayesian analysis is to formulate a suitably vague alternative, because the vaguer the alternative is (the more it spreads out the unit mass of prior probability), the more the null is…

Genetic history of hepatitis C virus in Venezuela: high diversity and long time of evolution of HCV genotype 2.

PubMed

Sulbarán, Maria Z; Di Lello, Federico A; Sulbarán, Yoneira; Cosson, Clarisa; Loureiro, Carmen L; Rangel, Héctor R; Cantaloube, Jean F; Campos, Rodolfo H; Moratorio, Gonzalo; Cristina, Juan; Pujol, Flor H

2010-12-13

The subtype diversity of the hepatitis C virus (HCV) genotypes is unknown in Venezuela. Partial sequencing of the NS5B region was performed in 310 isolates circulating in patients from 1995 to 2007. In the samples collected between 2005 and 2007, HCV genotype 1 (G1) was the most common genotype (63%), composed as expected of mainly G1a and G1b. G2 was the second most common genotype (33%), being G2a almost absent and G2j the most frequent subtype. Sequence analysis of the core region confirmed the subtype assignment performed within the NS5b region in 63 isolates. The complete genome sequence of G2j was obtained. G2j has been described in France, Canada and Burkina Fasso, but it was not found in Martinique, where several subtypes of G2 circulate in the general population. Bayesian coalescence analysis indicated a most recent common ancestor (MRCA) of G2j around 1785, before the introduction of G1b (1869) and G1a (1922). While HCV G1a and G1b experienced a growth reduction since 1990, coincident with the time when blood testing was implemented in Venezuela, HCV G2j did not seem to reach growth equilibrium during this period. Assuming the introduction of G2j from Africa during the slave trade, the high frequency of G2j found in Venezuela could suggest: 1- the introduction of African ethnic groups different from the ones introduced to Martinique or 2- the occurrence of a founder effect. This study represents an in-depth analysis of the subtype diversity of HCV in Venezuela, which is still unexplored in the Americas and deserves further studies.

HTLV-1aA introduction into Brazil and its association with the trans-Atlantic slave trade.

PubMed

Amoussa, Adjile Edjide Roukiyath; Wilkinson, Eduan; Giovanetti, Marta; de Almeida Rego, Filipe Ferreira; Araujo, Thessika Hialla A; de Souza Gonçalves, Marilda; de Oliveira, Tulio; Alcantara, Luiz Carlos Junior

2017-03-01

Human T-lymphotropic virus (HTLV) is an endemic virus in some parts of the world, with Africa being home to most of the viral genetic diversity. In Brazil, HTLV-1 is endemic amongst Japanese and African immigrant populations. Multiple introductions of the virus in Brazil from other epidemic foci were hypothesized. The long terminal repeat (LTR) region of HTLV-1 was used to infer the origin of the virus in Brazil, using phylogenetic analysis. LTR sequences were obtained from the HTLV-1 database (http://htlv1db.bahia.fiocruz.br). Sequences were aligned and maximum-likelihood and Bayesian tree topologies were inferred. Brazilian specific clusters were identified and molecular-clock and coalescent models were used to estimate each cluster's time to the most recent common ancestor (tMRCA). Three Brazilian clusters were identified with a posterior probability ranged from 0.61 to 0.99. Molecular clock analysis of these three clusters dated back their respective tMRCAs between the year 1499 and the year 1668. Additional analysis also identified a close association between Brazilian sequences and new sequences from South Africa. Our results support the hypothesis of a multiple introductions of HTLV-1 into Brazil, with the majority of introductions occurring in the post-Colombian period. Our results further suggest that HTLV-1 introduction into Brazil was facilitated by the trans-Atlantic slave trade from endemic areas of Africa. The close association between southern African and Brazilian sequences also suggested that greater numbers of the southern African Bantu population might also have been part of the slave trade than previously thought. Copyright © 2016. Published by Elsevier B.V.

Bayesian selection of misspecified models is overconfident and may cause spurious posterior probabilities for phylogenetic trees.

PubMed

Yang, Ziheng; Zhu, Tianqi

2018-02-20

The Bayesian method is noted to produce spuriously high posterior probabilities for phylogenetic trees in analysis of large datasets, but the precise reasons for this overconfidence are unknown. In general, the performance of Bayesian selection of misspecified models is poorly understood, even though this is of great scientific interest since models are never true in real data analysis. Here we characterize the asymptotic behavior of Bayesian model selection and show that when the competing models are equally wrong, Bayesian model selection exhibits surprising and polarized behaviors in large datasets, supporting one model with full force while rejecting the others. If one model is slightly less wrong than the other, the less wrong model will eventually win when the amount of data increases, but the method may become overconfident before it becomes reliable. We suggest that this extreme behavior may be a major factor for the spuriously high posterior probabilities for evolutionary trees. The philosophical implications of our results to the application of Bayesian model selection to evaluate opposing scientific hypotheses are yet to be explored, as are the behaviors of non-Bayesian methods in similar situations.

Bayesian Analysis of Nonlinear Structural Equation Models with Nonignorable Missing Data

ERIC Educational Resources Information Center

Lee, Sik-Yum

2006-01-01

A Bayesian approach is developed for analyzing nonlinear structural equation models with nonignorable missing data. The nonignorable missingness mechanism is specified by a logistic regression model. A hybrid algorithm that combines the Gibbs sampler and the Metropolis-Hastings algorithm is used to produce the joint Bayesian estimates of…

Bayesian Data-Model Fit Assessment for Structural Equation Modeling

ERIC Educational Resources Information Center

Levy, Roy

2011-01-01

Bayesian approaches to modeling are receiving an increasing amount of attention in the areas of model construction and estimation in factor analysis, structural equation modeling (SEM), and related latent variable models. However, model diagnostics and model criticism remain relatively understudied aspects of Bayesian SEM. This article describes…

Bayesian Posterior Odds Ratios: Statistical Tools for Collaborative Evaluations

ERIC Educational Resources Information Center

Hicks, Tyler; Rodríguez-Campos, Liliana; Choi, Jeong Hoon

2018-01-01

To begin statistical analysis, Bayesians quantify their confidence in modeling hypotheses with priors. A prior describes the probability of a certain modeling hypothesis apart from the data. Bayesians should be able to defend their choice of prior to a skeptical audience. Collaboration between evaluators and stakeholders could make their choices…

Evolutionary dynamics of methicillin-resistant Staphylococcus aureus within a healthcare system.

PubMed

Hsu, Li-Yang; Harris, Simon R; Chlebowicz, Monika A; Lindsay, Jodi A; Koh, Tse-Hsien; Krishnan, Prabha; Tan, Thean-Yen; Hon, Pei-Yun; Grubb, Warren B; Bentley, Stephen D; Parkhill, Julian; Peacock, Sharon J; Holden, Matthew T G

2015-04-23

In the past decade, several countries have seen gradual replacement of endemic multi-resistant healthcare-associated methicillin-resistant Staphylococcus aureus (MRSA) with clones that are more susceptible to antibiotic treatment. One example is Singapore, where MRSA ST239, the dominant clone since molecular profiling of MRSA began in the mid-1980s, has been replaced by ST22 isolates belonging to EMRSA-15, a recently emerged pandemic lineage originating from Europe. We investigated the population structure of MRSA in Singaporean hospitals spanning three decades, using whole genome sequencing. Applying Bayesian phylogenetic methods we report that prior to the introduction of ST22, the ST239 MRSA population in Singapore originated from multiple introductions from the surrounding region; it was frequently transferred within the healthcare system resulting in a heterogeneous hospital population. Following the introduction of ST22 around the beginning of the millennium, this clone spread rapidly through Singaporean hospitals, supplanting the endemic ST239 population. Coalescent analysis revealed that although the genetic diversity of ST239 initially decreased as ST22 became more dominant, from 2007 onwards the genetic diversity of ST239 began to increase once more, which was not associated with the emergence of a sub-clone of ST239. Comparative genomic analysis of the accessory genome of the extant ST239 population identified that the Arginine Catabolic Mobile Element arose multiple times, thereby introducing genes associated with enhanced skin colonization into this population. Our results clearly demonstrate that, alongside clinical practice and antibiotic usage, competition between clones also has an important role in driving the evolution of nosocomial pathogen populations.

Molecular diversity and evolutionary history of rabies virus strains circulating in the Balkans.

PubMed

McElhinney, L M; Marston, D A; Freuling, C M; Cragg, W; Stankov, S; Lalosevic, D; Lalosevic, V; Müller, T; Fooks, A R

2011-09-01

Molecular studies of European classical rabies viruses (RABV) have revealed a number of geographically clustered lineages. To study the diversity of Balkan RABV, partial nucleoprotein (N) gene sequences were analysed from a unique panel of isolates (n = 210), collected from various hosts between 1972 and 2006. All of the Balkan isolates grouped within the European/Middle East Lineage, with the majority most closely related to East European strains. A number of RABV from Bosnia & Herzegovina and Montenegro, collected between 1986 and 2006, grouped with the West European strains, believed to be responsible for the rabies epizootic that spread throughout Europe in the latter half of the 20th Century. In contrast, no Serbian RABV belonged to this sublineage. However, a distinct group of Serbian fox RABV provided further evidence for the southwards wildlife-mediated movement of rabies from Hungary, Romania and Serbia into Bulgaria. To determine the optimal region for evolutionary analysis, partial, full and concatenated N-gene and glycoprotein (G) gene sequences were compared. Whilst both the divergence times and evolutionary rates were similar irrespective of genomic region, the 95 % highest probability density (HPD) limits were significantly reduced for full N-gene and concatenated NG-gene sequences compared with partial gene sequences. Bayesian coalescent analysis estimated the date of the most common recent ancestor of the Balkan RABV to be 1885 (95 % HPD, 1852-1913), and skyline plots suggested an expansion of the local viral population in 1980-1990, which coincides with the observed emergence of fox rabies in the region.

Species-Level Phylogeny and Polyploid Relationships in Hordeum (Poaceae) Inferred by Next-Generation Sequencing and In Silico Cloning of Multiple Nuclear Loci.

PubMed

Brassac, Jonathan; Blattner, Frank R

2015-09-01

Polyploidization is an important speciation mechanism in the barley genus Hordeum. To analyze evolutionary changes after allopolyploidization, knowledge of parental relationships is essential. One chloroplast and 12 nuclear single-copy loci were amplified by polymerase chain reaction (PCR) in all Hordeum plus six out-group species. Amplicons from each of 96 individuals were pooled, sheared, labeled with individual-specific barcodes and sequenced in a single run on a 454 platform. Reference sequences were obtained by cloning and Sanger sequencing of all loci for nine supplementary individuals. The 454 reads were assembled into contigs representing the 13 loci and, for polyploids, also homoeologues. Phylogenetic analyses were conducted for all loci separately and for a concatenated data matrix of all loci. For diploid taxa, a Bayesian concordance analysis and a coalescent-based dated species tree was inferred from all gene trees. Chloroplast matK was used to determine the maternal parent in allopolyploid taxa. The relative performance of different multilocus analyses in the presence of incomplete lineage sorting and hybridization was also assessed. The resulting multilocus phylogeny reveals for the first time species phylogeny and progenitor-derivative relationships of all di- and polyploid Hordeum taxa within a single analysis. Our study proves that it is possible to obtain a multilocus species-level phylogeny for di- and polyploid taxa by combining PCR with next-generation sequencing, without cloning and without creating a heavy load of sequence data. © The Author(s) 2015. Published by Oxford University Press, on behalf of the Society of Systematic Biologists.

Development and comparison in uncertainty assessment based Bayesian modularization method in hydrological modeling

NASA Astrophysics Data System (ADS)

Li, Lu; Xu, Chong-Yu; Engeland, Kolbjørn

2013-04-01

SummaryWith respect to model calibration, parameter estimation and analysis of uncertainty sources, various regression and probabilistic approaches are used in hydrological modeling. A family of Bayesian methods, which incorporates different sources of information into a single analysis through Bayes' theorem, is widely used for uncertainty assessment. However, none of these approaches can well treat the impact of high flows in hydrological modeling. This study proposes a Bayesian modularization uncertainty assessment approach in which the highest streamflow observations are treated as suspect information that should not influence the inference of the main bulk of the model parameters. This study includes a comprehensive comparison and evaluation of uncertainty assessments by our new Bayesian modularization method and standard Bayesian methods using the Metropolis-Hastings (MH) algorithm with the daily hydrological model WASMOD. Three likelihood functions were used in combination with standard Bayesian method: the AR(1) plus Normal model independent of time (Model 1), the AR(1) plus Normal model dependent on time (Model 2) and the AR(1) plus Multi-normal model (Model 3). The results reveal that the Bayesian modularization method provides the most accurate streamflow estimates measured by the Nash-Sutcliffe efficiency and provide the best in uncertainty estimates for low, medium and entire flows compared to standard Bayesian methods. The study thus provides a new approach for reducing the impact of high flows on the discharge uncertainty assessment of hydrological models via Bayesian method.

Bayesian correction for covariate measurement error: A frequentist evaluation and comparison with regression calibration.

PubMed

Bartlett, Jonathan W; Keogh, Ruth H

2018-06-01

Bayesian approaches for handling covariate measurement error are well established and yet arguably are still relatively little used by researchers. For some this is likely due to unfamiliarity or disagreement with the Bayesian inferential paradigm. For others a contributory factor is the inability of standard statistical packages to perform such Bayesian analyses. In this paper, we first give an overview of the Bayesian approach to handling covariate measurement error, and contrast it with regression calibration, arguably the most commonly adopted approach. We then argue why the Bayesian approach has a number of statistical advantages compared to regression calibration and demonstrate that implementing the Bayesian approach is usually quite feasible for the analyst. Next, we describe the closely related maximum likelihood and multiple imputation approaches and explain why we believe the Bayesian approach to generally be preferable. We then empirically compare the frequentist properties of regression calibration and the Bayesian approach through simulation studies. The flexibility of the Bayesian approach to handle both measurement error and missing data is then illustrated through an analysis of data from the Third National Health and Nutrition Examination Survey.

Enhancing the Modeling of PFOA Pharmacokinetics with Bayesian Analysis

EPA Science Inventory

The detail sufficient to describe the pharmacokinetics (PK) for perfluorooctanoic acid (PFOA) and the methods necessary to combine information from multiple data sets are both subjects of ongoing investigation. Bayesian analysis provides tools to accommodate these goals. We exa...

Bayesian statistics: estimating plant demographic parameters

Treesearch

James S. Clark; Michael Lavine

2001-01-01

There are times when external information should be brought tobear on an ecological analysis. experiments are never conducted in a knowledge-free context. The inference we draw from an observation may depend on everything else we know about the process. Bayesian analysis is a method that brings outside evidence into the analysis of experimental and observational data...

Spatial Dependence and Heterogeneity in Bayesian Factor Analysis: A Cross-National Investigation of Schwartz Values

ERIC Educational Resources Information Center

Stakhovych, Stanislav; Bijmolt, Tammo H. A.; Wedel, Michel

2012-01-01

In this article, we present a Bayesian spatial factor analysis model. We extend previous work on confirmatory factor analysis by including geographically distributed latent variables and accounting for heterogeneity and spatial autocorrelation. The simulation study shows excellent recovery of the model parameters and demonstrates the consequences…

Bayesian Structural Equation Modeling: A More Flexible Representation of Substantive Theory

ERIC Educational Resources Information Center

Muthen, Bengt; Asparouhov, Tihomir

2012-01-01

This article proposes a new approach to factor analysis and structural equation modeling using Bayesian analysis. The new approach replaces parameter specifications of exact zeros with approximate zeros based on informative, small-variance priors. It is argued that this produces an analysis that better reflects substantive theories. The proposed…

BCM: toolkit for Bayesian analysis of Computational Models using samplers.

PubMed

Thijssen, Bram; Dijkstra, Tjeerd M H; Heskes, Tom; Wessels, Lodewyk F A

2016-10-21

Computational models in biology are characterized by a large degree of uncertainty. This uncertainty can be analyzed with Bayesian statistics, however, the sampling algorithms that are frequently used for calculating Bayesian statistical estimates are computationally demanding, and each algorithm has unique advantages and disadvantages. It is typically unclear, before starting an analysis, which algorithm will perform well on a given computational model. We present BCM, a toolkit for the Bayesian analysis of Computational Models using samplers. It provides efficient, multithreaded implementations of eleven algorithms for sampling from posterior probability distributions and for calculating marginal likelihoods. BCM includes tools to simplify the process of model specification and scripts for visualizing the results. The flexible architecture allows it to be used on diverse types of biological computational models. In an example inference task using a model of the cell cycle based on ordinary differential equations, BCM is significantly more efficient than existing software packages, allowing more challenging inference problems to be solved. BCM represents an efficient one-stop-shop for computational modelers wishing to use sampler-based Bayesian statistics.

Divergent evolutionary processes associated with colonization of offshore islands.

PubMed

Martínková, Natália; Barnett, Ross; Cucchi, Thomas; Struchen, Rahel; Pascal, Marine; Pascal, Michel; Fischer, Martin C; Higham, Thomas; Brace, Selina; Ho, Simon Y W; Quéré, Jean-Pierre; O'Higgins, Paul; Excoffier, Laurent; Heckel, Gerald; Hoelzel, A Rus; Dobney, Keith M; Searle, Jeremy B

2013-10-01

Oceanic islands have been a test ground for evolutionary theory, but here, we focus on the possibilities for evolutionary study created by offshore islands. These can be colonized through various means and by a wide range of species, including those with low dispersal capabilities. We use morphology, modern and ancient sequences of cytochrome b (cytb) and microsatellite genotypes to examine colonization history and evolutionary change associated with occupation of the Orkney archipelago by the common vole (Microtus arvalis), a species found in continental Europe but not in Britain. Among possible colonization scenarios, our results are most consistent with human introduction at least 5100 bp (confirmed by radiocarbon dating). We used approximate Bayesian computation of population history to infer the coast of Belgium as the possible source and estimated the evolutionary timescale using a Bayesian coalescent approach. We showed substantial morphological divergence of the island populations, including a size increase presumably driven by selection and reduced microsatellite variation likely reflecting founder events and genetic drift. More surprisingly, our results suggest that a recent and widespread cytb replacement event in the continental source area purged cytb variation there, whereas the ancestral diversity is largely retained in the colonized islands as a genetic 'ark'. The replacement event in the continental M. arvalis was probably triggered by anthropogenic causes (land-use change). Our studies illustrate that small offshore islands can act as field laboratories for studying various evolutionary processes over relatively short timescales, informing about the mainland source area as well as the island. © 2013 John Wiley & Sons Ltd.

Coalescence-induced jumping of nanoscale droplets on super-hydrophobic surfaces

NASA Astrophysics Data System (ADS)

Liang, Zhi; Keblinski, Pawel; Nanoscale Science; Engineering Center Team

The coalescence-induced jumping of tens of microns size droplets on super-hydrophobic surfaces has been observed in both experiments and simulations. However, whether the coalescence-induced jumping would occur for smaller, particularly nanoscale droplets, is an open question. Using molecular dynamics simulations, we demonstrate that in spite of the large internal viscous dissipation, coalescence of two nanoscale droplets on a super-hydrophobic surface can result in a jumping of the coalesced droplet from the surface with a speed of a few m/s. Similar to the coalescence-induced jumping of microscale droplets, we observe that the bridge between the coalescing nano-droplets expands and impacts the solid surface, which leads to an acceleration of the coalesced droplet by the pressure force from the solid surface. We observe that the jumping velocity decreases with the droplet size and its ratio to the inertial-capillary velocity is a constant of about 0.126, which is close to the minimum value of 0.111 predicted by continuum-level modeling of Enright et al. [R. Enright, N. Miljkovic, J. Sprittles, K. Nolan, R. Mitchell, and E. N. Wang, ACS Nano 8, 10352 (2014)].

Effect of electrolytes on bubble coalescence in columns observed with visualization techniques.

PubMed

Aguilera, María Eugenia; Ojeda, Antonieta; Rondón, Carolina; López De Ramos, Aura

2002-10-01

Bubble coalescence and the effect of electrolytes on this phenomenon have been previously studied. This interfacial phenomenon has attracted attention for reactor design/operation and enhanced oil recovery. Predicting bubble coalescence may help prevent low yields in reactors and predict crude oil recovery. Because of the importance of bubble coalescence, the objectives of this work were to improve the accuracy of measuring the percentage of coalescing bubbles and to observe the interfacial gas-liquid behavior. An experimental setup was designed and constructed. Bubble interactions were monitored with a visualization setup. The percentage of air bubble coalescence was 100% in distilled water, about 50% in 0.1 M sodium chloride (NaCl) aqueous solution, and 0% in 0.145 M NaCl aqueous solution. A reduction of the contact gas-liquid area was observed in distillate water. The volume of the resulting bubble was the sum of the original bubble volumes. Repulsion of bubbles was observed in NaCl solutions exceeding 0.07 M. The percentage of bubble coalescence diminishes as the concentration of NaCl chloride increases. High-speed video recording is an accurate technique to measure the percentage of bubble coalescence, and represents an important advance in gas-liquid interfacial studies.

Coalescence driven self-organization of growing nanodroplets around a microcap

NASA Astrophysics Data System (ADS)

Dyett, Brendan; Hao, Hao; Lohse, Detlef; Zhang, Xuehua

The coalescence between growing droplets is important for the surface coverage and spatial arrangements of droplets on surfaces. In this work, total internal reflection fluorescence (TIRF) microscopy is utilized to in-situ investigate the formation of nanodroplets around the rim of a polymer microcap, with sub-micron spatial and millisecond temporal resolution. We observe that the coalescence among droplets occurs frequently during their growth by solvent exchange. Our experimental results show that the position of the droplet from two merged droplets is related to the size of the parent droplets. The position of the coalesced droplet and the ratio of parent droplet sizes obey a scaling law, reflecting a coalescence preference based on the size inequality. As a result of droplet coalescence, the angles between the centroids of two neighbouring droplets increase with time, obeying a nearly symmetrical arrangement of droplets at various time intervals. The evolution of the position and number from coalescence of growing droplets is modelled. The mechanism for coalescence driven self-organization of growing droplets is general, applicable to microcaps of different sizes and droplets of different liquids. The understanding from this work may be valuable for positioning nanodroplets by nucleation and growth without using templates.

Coalescence driven self-organization of growing nanodroplets around a microcap.

PubMed

Dyett, Brendan; Hao, Hao; Lohse, Detlef; Zhang, Xuehua

2018-04-04

The coalescence between growing droplets is important for the surface coverage and spatial arrangements of droplets on surfaces. In this work, total internal reflection fluorescence (TIRF) microscopy is utilized to in situ investigate the formation of nanodroplets around the rim of a polymer microcap, with sub-micron spatial and millisecond temporal resolution. We observe that the coalescence among droplets occurs frequently during their growth by solvent exchange. Our experimental results show that the position of the droplet from two merged droplets is related to the size of the parent droplets. The position of the coalesced droplet and the ratio of parent droplet sizes obey a scaling law, reflecting a coalescence preference based on the size inequality. As a result of droplet coalescence, the angles between the centroids of two neighbouring droplets increase with time, obeying a nearly symmetrical arrangement of droplets at various time intervals. The evolution of the position and number from coalescence of growing droplets is modelled. The mechanism for coalescence driven self-organization of growing droplets is general, applicable to microcaps of different sizes and droplets of different liquids. The understanding from this work may be valuable for positioning nanodroplets by nucleation and growth without using templates.

Optofluidic droplet coalescence on a microfluidic chip

NASA Astrophysics Data System (ADS)

Jung, Jin Ho; Lee, Kyung Heon; Lee, Kang Soo; Cho, Hyunjun; Ha, Byung Hang; Destgeer, Ghulam; Sung, Hyung Jin

2013-11-01

Coalescence is the procedure that two or more droplets fuse during contact to form a larger droplet. Optofluidic droplet coalescence on a microfluidic chip was demonstrated with theoretical and experimental approaches. Droplets were produced in a T-junction geometry and their velocities and sizes were adjusted by flow rate. In order to bring them in a direct contact of coalescence, optical gradient force was used to trap the droplets. A theoretical modeling of the coalescence was derived by combining the optical force and drag force on the droplet. The analytical expression of the optical force on a sphere droplet was employed to estimate the trapping efficiency in the ray optics regime. The drag force acting on the droplet was calculated in terms of the fluid velocity, viscosity and the geometrical parameters of a microfluidic channel. The droplet coalescence was conducted in a microfluidic setup equipped with a 1064 CW laser, focusing optics, a syringe pump, a custom-made stage and a sCMOS camera. The droplets were successfully coalesced using the optical gradient force. The experimental data of coalescence were in good agreement with the prediction. This work was supported by the Creative Research Initiatives program (No.2013-003364) of the National Research Foundation of Korea (MSIP).

When do species-tree and concatenated estimates disagree? An empirical analysis with higher-level scincid lizard phylogeny.

PubMed

Lambert, Shea M; Reeder, Tod W; Wiens, John J

2015-01-01

Simulation studies suggest that coalescent-based species-tree methods are generally more accurate than concatenated analyses. However, these species-tree methods remain impractical for many large datasets. Thus, a critical but unresolved issue is when and why concatenated and coalescent species-tree estimates will differ. We predict such differences for branches in concatenated trees that are short, weakly supported, and have conflicting gene trees. We test these predictions in Scincidae, the largest lizard family, with data from 10 nuclear genes for 17 ingroup taxa and 44 genes for 12 taxa. We support our initial predictions, andsuggest that simply considering uncertainty in concatenated trees may sometimes encompass the differences between these methods. We also found that relaxed-clock concatenated trees can be surprisingly similar to the species-tree estimate. Remarkably, the coalescent species-tree estimates had slightly lower support values when based on many more genes (44 vs. 10) and a small (∼30%) reduction in taxon sampling. Thus, taxon sampling may be more important than gene sampling when applying species-tree methods to deep phylogenetic questions. Finally, our coalescent species-tree estimates tentatively support division of Scincidae into three monophyletic subfamilies, a result otherwise found only in concatenated analyses with extensive species sampling. Copyright © 2014 Elsevier Inc. All rights reserved.

On the use of higher order wave forms in the search for gravitational waves emitted by compact binary coalescences

NASA Astrophysics Data System (ADS)

McKechan, David J. A.

2010-11-01

This thesis concerns the use, in gravitational wave data analysis, of higher order wave form models of the gravitational radiation emitted by compact binary coalescences. We begin with an introductory chapter that includes an overview of the theory of general relativity, gravitational radiation and ground-based interferometric gravitational wave detectors. We then discuss, in Chapter 2, the gravitational waves emitted by compact binary coalescences, with an explanation of higher order waveforms and how they differ from leading order waveforms we also introduce the post-Newtonian formalism. In Chapter 3 the method and results of a gravitational wave search for low mass compact binary coalescences using a subset of LIGO's 5th science run data are presented and in the subsequent chapter we examine how one could use higher order waveforms in such analyses. We follow the development of a new search algorithm that incorporates higher order waveforms with promising results for detection efficiency and parameter estimation. In Chapter 5, a new method of windowing time-domain waveforms that offers benefit to gravitational wave searches is presented. The final chapter covers the development of a game designed as an outreach project to raise public awareness and understanding of the search for gravitational waves.

Morphology and Evolution of Sublimation Pits on Pluto

NASA Astrophysics Data System (ADS)

Abu-Hashmeh, N.; Conrad, J. W.; Nimmo, F.; Moore, J. M.; Stern, A.; Olkin, C.; Weaver, H. A., Jr.; Ennico Smith, K.; Young, L. A.

2017-12-01

Pluto's Sputnik Planitia region hosts a geologically young surface of nitrogen ice that exhibits striking pitted terrain (Moore et al., Science 351, 2016). These pits are most likely formed by sublimation due to incident sunlight, similar to the southern polar cap of Mars (Byrne and Ingersoll, Science 299, 2003); however, their evolution over time has resulted in unique morphological characteristics. Motivated by this, we used the high-resolution mosaic strips captured by New Horizons' Long Range Reconnaissance Imager (LORRI) to map sublimation pits in the southernmost region of Sputnik Planitia. Statistical data shows pit orientations appearing North-South dominant; their morphology also indicates extensional evolution along the major axis caused by further sublimation and contact-coalescence processes. Qualitative analysis of the region yielded indications of an evolutionary path for individual pits that coalesce into each other and exhibit an elongated end-stage. Additionally, densely-pitted regions generally appear to correlate with regions containing longer pits, implying that coalescence may be an important process for elongation. We also model the evolution geometry through competing effects of diffusion (viscous relaxation) and retreat (sublimation) (Buhler and Ingersoll, LPSC Abstract #1746, 2017). The model demonstrates single-pit and coalescing-pit evolutions that influence overall length, as well as a potential ability for the pit center to move in space while the pit morphology evolves.

Bayesian Analysis of Longitudinal Data Using Growth Curve Models

ERIC Educational Resources Information Center

Zhang, Zhiyong; Hamagami, Fumiaki; Wang, Lijuan Lijuan; Nesselroade, John R.; Grimm, Kevin J.

2007-01-01

Bayesian methods for analyzing longitudinal data in social and behavioral research are recommended for their ability to incorporate prior information in estimating simple and complex models. We first summarize the basics of Bayesian methods before presenting an empirical example in which we fit a latent basis growth curve model to achievement data…

Introduction to Bayesian statistical approaches to compositional analyses of transgenic crops 1. Model validation and setting the stage.

PubMed

Harrison, Jay M; Breeze, Matthew L; Harrigan, George G

2011-08-01

Statistical comparisons of compositional data generated on genetically modified (GM) crops and their near-isogenic conventional (non-GM) counterparts typically rely on classical significance testing. This manuscript presents an introduction to Bayesian methods for compositional analysis along with recommendations for model validation. The approach is illustrated using protein and fat data from two herbicide tolerant GM soybeans (MON87708 and MON87708×MON89788) and a conventional comparator grown in the US in 2008 and 2009. Guidelines recommended by the US Food and Drug Administration (FDA) in conducting Bayesian analyses of clinical studies on medical devices were followed. This study is the first Bayesian approach to GM and non-GM compositional comparisons. The evaluation presented here supports a conclusion that a Bayesian approach to analyzing compositional data can provide meaningful and interpretable results. We further describe the importance of method validation and approaches to model checking if Bayesian approaches to compositional data analysis are to be considered viable by scientists involved in GM research and regulation. Copyright © 2011 Elsevier Inc. All rights reserved.

Bayesian analysis of rare events

NASA Astrophysics Data System (ADS)

Straub, Daniel; Papaioannou, Iason; Betz, Wolfgang

2016-06-01

In many areas of engineering and science there is an interest in predicting the probability of rare events, in particular in applications related to safety and security. Increasingly, such predictions are made through computer models of physical systems in an uncertainty quantification framework. Additionally, with advances in IT, monitoring and sensor technology, an increasing amount of data on the performance of the systems is collected. This data can be used to reduce uncertainty, improve the probability estimates and consequently enhance the management of rare events and associated risks. Bayesian analysis is the ideal method to include the data into the probabilistic model. It ensures a consistent probabilistic treatment of uncertainty, which is central in the prediction of rare events, where extrapolation from the domain of observation is common. We present a framework for performing Bayesian updating of rare event probabilities, termed BUS. It is based on a reinterpretation of the classical rejection-sampling approach to Bayesian analysis, which enables the use of established methods for estimating probabilities of rare events. By drawing upon these methods, the framework makes use of their computational efficiency. These methods include the First-Order Reliability Method (FORM), tailored importance sampling (IS) methods and Subset Simulation (SuS). In this contribution, we briefly review these methods in the context of the BUS framework and investigate their applicability to Bayesian analysis of rare events in different settings. We find that, for some applications, FORM can be highly efficient and is surprisingly accurate, enabling Bayesian analysis of rare events with just a few model evaluations. In a general setting, BUS implemented through IS and SuS is more robust and flexible.

Application of parametric equations of motion to study the resonance coalescence in H2(+).

PubMed

Kalita, Dhruba J; Gupta, Ashish K

2012-12-07

Recently, occurrence of coalescence point was reported in H(2)(+) undergoing multiphoton dissociation in strong laser field. We have applied parametric equations of motion and smooth exterior scaling method to study the coalescence phenomenon of H(2)(+). The advantage of this method is that one can easily trace the different states that are changing as the field parameters change. It was reported earlier that in the parameter space, only two bound states coalesce [R. Lefebvre, O. Atabek, M. Sindelka, and N. Moiseyev, Phys. Rev. Lett. 103, 123003 (2009)]. However, it is found that increasing the accuracy of the calculation leads to the coalescence between resonance states originating from the bound and the continuum states. We have also reported many other coalescence points.

Multi-body coalescence in Pickering emulsions

NASA Astrophysics Data System (ADS)

Wu, Tong; Wang, Haitao; Jing, Benxin; Liu, Fang; Burns, Peter C.; Na, Chongzheng

2015-01-01

Particle-stabilized Pickering emulsions have shown unusual behaviours such as the formation of non-spherical droplets and the sudden halt of coalescence between individual droplets. Here we report another unusual behaviour of Pickering emulsions—the simultaneous coalescence of multiple droplets in a single event. Using latex particles, silica particles and carbon nanotubes as model stabilizers, we show that multi-body coalescence can occur in both water-in-oil and oil-in-water emulsions. The number of droplets involved in the nth coalscence event equals four times the corresponding number of the tetrahedral sequence in close packing. Furthermore, coalescence is promoted by repulsive latex and silica particles but inhibited by attractive carbon nanotubes. The revelation of multi-body coalescence is expected to help better understand Pickering emulsions in natural systems and improve their designs in engineering applications.

A guide to Bayesian model selection for ecologists

USGS Publications Warehouse

Hooten, Mevin B.; Hobbs, N.T.

2015-01-01

The steady upward trend in the use of model selection and Bayesian methods in ecological research has made it clear that both approaches to inference are important for modern analysis of models and data. However, in teaching Bayesian methods and in working with our research colleagues, we have noticed a general dissatisfaction with the available literature on Bayesian model selection and multimodel inference. Students and researchers new to Bayesian methods quickly find that the published advice on model selection is often preferential in its treatment of options for analysis, frequently advocating one particular method above others. The recent appearance of many articles and textbooks on Bayesian modeling has provided welcome background on relevant approaches to model selection in the Bayesian framework, but most of these are either very narrowly focused in scope or inaccessible to ecologists. Moreover, the methodological details of Bayesian model selection approaches are spread thinly throughout the literature, appearing in journals from many different fields. Our aim with this guide is to condense the large body of literature on Bayesian approaches to model selection and multimodel inference and present it specifically for quantitative ecologists as neutrally as possible. We also bring to light a few important and fundamental concepts relating directly to model selection that seem to have gone unnoticed in the ecological literature. Throughout, we provide only a minimal discussion of philosophy, preferring instead to examine the breadth of approaches as well as their practical advantages and disadvantages. This guide serves as a reference for ecologists using Bayesian methods, so that they can better understand their options and can make an informed choice that is best aligned with their goals for inference.

BATSE gamma-ray burst line search. 2: Bayesian consistency methodology

NASA Technical Reports Server (NTRS)

Band, D. L.; Ford, L. A.; Matteson, J. L.; Briggs, M.; Paciesas, W.; Pendleton, G.; Preece, R.; Palmer, D.; Teegarden, B.; Schaefer, B.

1994-01-01

We describe a Bayesian methodology to evaluate the consistency between the reported Ginga and Burst and Transient Source Experiment (BATSE) detections of absorption features in gamma-ray burst spectra. Currently no features have been detected by BATSE, but this methodology will still be applicable if and when such features are discovered. The Bayesian methodology permits the comparison of hypotheses regarding the two detectors' observations and makes explicit the subjective aspects of our analysis (e.g., the quantification of our confidence in detector performance). We also present non-Bayesian consistency statistics. Based on preliminary calculations of line detectability, we find that both the Bayesian and non-Bayesian techniques show that the BATSE and Ginga observations are consistent given our understanding of these detectors.

Application of Bayesian Approach in Cancer Clinical Trial

PubMed Central

Bhattacharjee, Atanu

2014-01-01

The application of Bayesian approach in clinical trials becomes more useful over classical method. It is beneficial from design to analysis phase. The straight forward statement is possible to obtain through Bayesian about the drug treatment effect. Complex computational problems are simple to handle with Bayesian techniques. The technique is only feasible to performing presence of prior information of the data. The inference is possible to establish through posterior estimates. However, some limitations are present in this method. The objective of this work was to explore the several merits and demerits of Bayesian approach in cancer research. The review of the technique will be helpful for the clinical researcher involved in the oncology to explore the limitation and power of Bayesian techniques. PMID:29147387

Coalescence preference and droplet size inequality during fluid phase segregation

NASA Astrophysics Data System (ADS)

Roy, Sutapa

2018-02-01

Using molecular dynamics simulations and scaling arguments, we investigate the coalescence preference dynamics of liquid droplets in a phase-segregating off-critical, single-component fluid. It is observed that the preferential distance of the product drop from its larger parent, during a coalescence event, gets smaller for large parent size inequality. The relative coalescence position exhibits a power-law dependence on the parent size ratio with an exponent q ≃ 3.1 . This value of q is in strong contrast with earlier reports 2.1 and 5.1 in the literature. The dissimilarity is explained by considering the underlying coalescence mechanisms.

How to interpret the results of medical time series data analysis: Classical statistical approaches versus dynamic Bayesian network modeling.

PubMed

Onisko, Agnieszka; Druzdzel, Marek J; Austin, R Marshall

2016-01-01

Classical statistics is a well-established approach in the analysis of medical data. While the medical community seems to be familiar with the concept of a statistical analysis and its interpretation, the Bayesian approach, argued by many of its proponents to be superior to the classical frequentist approach, is still not well-recognized in the analysis of medical data. The goal of this study is to encourage data analysts to use the Bayesian approach, such as modeling with graphical probabilistic networks, as an insightful alternative to classical statistical analysis of medical data. This paper offers a comparison of two approaches to analysis of medical time series data: (1) classical statistical approach, such as the Kaplan-Meier estimator and the Cox proportional hazards regression model, and (2) dynamic Bayesian network modeling. Our comparison is based on time series cervical cancer screening data collected at Magee-Womens Hospital, University of Pittsburgh Medical Center over 10 years. The main outcomes of our comparison are cervical cancer risk assessments produced by the three approaches. However, our analysis discusses also several aspects of the comparison, such as modeling assumptions, model building, dealing with incomplete data, individualized risk assessment, results interpretation, and model validation. Our study shows that the Bayesian approach is (1) much more flexible in terms of modeling effort, and (2) it offers an individualized risk assessment, which is more cumbersome for classical statistical approaches.

Spatiotemporal Bayesian analysis of Lyme disease in New York state, 1990-2000.

PubMed

Chen, Haiyan; Stratton, Howard H; Caraco, Thomas B; White, Dennis J

2006-07-01

Mapping ordinarily increases our understanding of nontrivial spatial and temporal heterogeneities in disease rates. However, the large number of parameters required by the corresponding statistical models often complicates detailed analysis. This study investigates the feasibility of a fully Bayesian hierarchical regression approach to the problem and identifies how it outperforms two more popular methods: crude rate estimates (CRE) and empirical Bayes standardization (EBS). In particular, we apply a fully Bayesian approach to the spatiotemporal analysis of Lyme disease incidence in New York state for the period 1990-2000. These results are compared with those obtained by CRE and EBS in Chen et al. (2005). We show that the fully Bayesian regression model not only gives more reliable estimates of disease rates than the other two approaches but also allows for tractable models that can accommodate more numerous sources of variation and unknown parameters.

Asymptotic Distributions of Coalescence Times and Ancestral Lineage Numbers for Populations with Temporally Varying Size

PubMed Central

Chen, Hua; Chen, Kun

2013-01-01

The distributions of coalescence times and ancestral lineage numbers play an essential role in coalescent modeling and ancestral inference. Both exact distributions of coalescence times and ancestral lineage numbers are expressed as the sum of alternating series, and the terms in the series become numerically intractable for large samples. More computationally attractive are their asymptotic distributions, which were derived in Griffiths (1984) for populations with constant size. In this article, we derive the asymptotic distributions of coalescence times and ancestral lineage numbers for populations with temporally varying size. For a sample of size n, denote by Tm the mth coalescent time, when m + 1 lineages coalesce into m lineages, and An(t) the number of ancestral lineages at time t back from the current generation. Similar to the results in Griffiths (1984), the number of ancestral lineages, An(t), and the coalescence times, Tm, are asymptotically normal, with the mean and variance of these distributions depending on the population size function, N(t). At the very early stage of the coalescent, when t → 0, the number of coalesced lineages n − An(t) follows a Poisson distribution, and as m → n, n(n−1)Tm/2N(0) follows a gamma distribution. We demonstrate the accuracy of the asymptotic approximations by comparing to both exact distributions and coalescent simulations. Several applications of the theoretical results are also shown: deriving statistics related to the properties of gene genealogies, such as the time to the most recent common ancestor (TMRCA) and the total branch length (TBL) of the genealogy, and deriving the allele frequency spectrum for large genealogies. With the advent of genomic-level sequencing data for large samples, the asymptotic distributions are expected to have wide applications in theoretical and methodological development for population genetic inference. PMID:23666939

Asymptotic distributions of coalescence times and ancestral lineage numbers for populations with temporally varying size.

PubMed

Chen, Hua; Chen, Kun

2013-07-01

The distributions of coalescence times and ancestral lineage numbers play an essential role in coalescent modeling and ancestral inference. Both exact distributions of coalescence times and ancestral lineage numbers are expressed as the sum of alternating series, and the terms in the series become numerically intractable for large samples. More computationally attractive are their asymptotic distributions, which were derived in Griffiths (1984) for populations with constant size. In this article, we derive the asymptotic distributions of coalescence times and ancestral lineage numbers for populations with temporally varying size. For a sample of size n, denote by Tm the mth coalescent time, when m + 1 lineages coalesce into m lineages, and An(t) the number of ancestral lineages at time t back from the current generation. Similar to the results in Griffiths (1984), the number of ancestral lineages, An(t), and the coalescence times, Tm, are asymptotically normal, with the mean and variance of these distributions depending on the population size function, N(t). At the very early stage of the coalescent, when t → 0, the number of coalesced lineages n - An(t) follows a Poisson distribution, and as m → n, $$n\\left(n-1\\right){T}_{m}/2N\\left(0\\right)$$ follows a gamma distribution. We demonstrate the accuracy of the asymptotic approximations by comparing to both exact distributions and coalescent simulations. Several applications of the theoretical results are also shown: deriving statistics related to the properties of gene genealogies, such as the time to the most recent common ancestor (TMRCA) and the total branch length (TBL) of the genealogy, and deriving the allele frequency spectrum for large genealogies. With the advent of genomic-level sequencing data for large samples, the asymptotic distributions are expected to have wide applications in theoretical and methodological development for population genetic inference.

Bayesian Inference for Functional Dynamics Exploring in fMRI Data.

PubMed

Guo, Xuan; Liu, Bing; Chen, Le; Chen, Guantao; Pan, Yi; Zhang, Jing

2016-01-01

This paper aims to review state-of-the-art Bayesian-inference-based methods applied to functional magnetic resonance imaging (fMRI) data. Particularly, we focus on one specific long-standing challenge in the computational modeling of fMRI datasets: how to effectively explore typical functional interactions from fMRI time series and the corresponding boundaries of temporal segments. Bayesian inference is a method of statistical inference which has been shown to be a powerful tool to encode dependence relationships among the variables with uncertainty. Here we provide an introduction to a group of Bayesian-inference-based methods for fMRI data analysis, which were designed to detect magnitude or functional connectivity change points and to infer their functional interaction patterns based on corresponding temporal boundaries. We also provide a comparison of three popular Bayesian models, that is, Bayesian Magnitude Change Point Model (BMCPM), Bayesian Connectivity Change Point Model (BCCPM), and Dynamic Bayesian Variable Partition Model (DBVPM), and give a summary of their applications. We envision that more delicate Bayesian inference models will be emerging and play increasingly important roles in modeling brain functions in the years to come.

Bayesian Factor Analysis When Only a Sample Covariance Matrix Is Available

ERIC Educational Resources Information Center

Hayashi, Kentaro; Arav, Marina

2006-01-01

In traditional factor analysis, the variance-covariance matrix or the correlation matrix has often been a form of inputting data. In contrast, in Bayesian factor analysis, the entire data set is typically required to compute the posterior estimates, such as Bayes factor loadings and Bayes unique variances. We propose a simple method for computing…

A menu-driven software package of Bayesian nonparametric (and parametric) mixed models for regression analysis and density estimation.

PubMed

Karabatsos, George

2017-02-01

Most of applied statistics involves regression analysis of data. In practice, it is important to specify a regression model that has minimal assumptions which are not violated by data, to ensure that statistical inferences from the model are informative and not misleading. This paper presents a stand-alone and menu-driven software package, Bayesian Regression: Nonparametric and Parametric Models, constructed from MATLAB Compiler. Currently, this package gives the user a choice from 83 Bayesian models for data analysis. They include 47 Bayesian nonparametric (BNP) infinite-mixture regression models; 5 BNP infinite-mixture models for density estimation; and 31 normal random effects models (HLMs), including normal linear models. Each of the 78 regression models handles either a continuous, binary, or ordinal dependent variable, and can handle multi-level (grouped) data. All 83 Bayesian models can handle the analysis of weighted observations (e.g., for meta-analysis), and the analysis of left-censored, right-censored, and/or interval-censored data. Each BNP infinite-mixture model has a mixture distribution assigned one of various BNP prior distributions, including priors defined by either the Dirichlet process, Pitman-Yor process (including the normalized stable process), beta (two-parameter) process, normalized inverse-Gaussian process, geometric weights prior, dependent Dirichlet process, or the dependent infinite-probits prior. The software user can mouse-click to select a Bayesian model and perform data analysis via Markov chain Monte Carlo (MCMC) sampling. After the sampling completes, the software automatically opens text output that reports MCMC-based estimates of the model's posterior distribution and model predictive fit to the data. Additional text and/or graphical output can be generated by mouse-clicking other menu options. This includes output of MCMC convergence analyses, and estimates of the model's posterior predictive distribution, for selected functionals and values of covariates. The software is illustrated through the BNP regression analysis of real data.

Phylogenomic analysis of a rapid radiation of misfit fishes (Syngnathiformes) using ultraconserved elements.

PubMed

Longo, S J; Faircloth, B C; Meyer, A; Westneat, M W; Alfaro, M E; Wainwright, P C

2017-08-01

Phylogenetics is undergoing a revolution as large-scale molecular datasets reveal unexpected but repeatable rearrangements of clades that were previously thought to be disparate lineages. One of the most unusual clades of fishes that has been found using large-scale molecular datasets is an expanded Syngnathiformes including traditional long-snouted syngnathiform lineages (Aulostomidae, Centriscidae, Fistulariidae, Solenostomidae, Syngnathidae), as well as a diverse set of largely benthic-associated fishes (Callionymoidei, Dactylopteridae, Mullidae, Pegasidae) that were previously dispersed across three orders. The monophyly of this surprising clade of fishes has been upheld by recent studies utilizing both nuclear and mitogenomic data, but the relationships among major lineages within Syngnathiformes remain ambiguous; previous analyses have inconsistent topologies and are plagued by low support at deep divergences between the major lineages. In this study, we use a dataset of ultraconserved elements (UCEs) to conduct the first phylogenomic study of Syngnathiformes. UCEs have been effective markers for resolving deep phylogenetic relationships in fishes and, combined with increased taxon sampling, we expected UCEs to resolve problematic syngnathiform relationships. Overall, UCEs were effective at resolving relationships within Syngnathiformes at a range of evolutionary timescales. We find consistent support for the monophyly of traditional long-snouted syngnathiform lineages (Aulostomidae, Centriscidae, Fistulariidae, Solenostomidae, Syngnathidae), which better agrees with morphological hypotheses than previously published topologies from molecular data. This result was supported by all Bayesian and maximum likelihood analyses, was robust to differences in matrix completeness and potential sources of bias, and was highly supported in coalescent-based analyses in ASTRAL when matrices were filtered to contain the most phylogenetically informative loci. While Bayesian and maximum likelihood analyses found support for a benthic-associated clade (Callionymidae, Dactylopteridae, Mullidae, and Pegasidae) as sister to the long-snouted clade, this result was not replicated in the ASTRAL analyses. The base of our phylogeny is characterized by short internodes separating major syngnathiform lineages and is consistent with the hypothesis of an ancient rapid radiation at the base of Syngnathiformes. Syngnathiformes therefore present an exciting opportunity to study patterns of morphological variation and functional innovation arising from rapid but ancient radiation. Copyright © 2017 Elsevier Inc. All rights reserved.

Coalescent histories for caterpillar-like families.

PubMed

Rosenberg, Noah A

2013-01-01

A coalescent history is an assignment of branches of a gene tree to branches of a species tree on which coalescences in the gene tree occur. The number of coalescent histories for a pair consisting of a labeled gene tree topology and a labeled species tree topology is important in gene tree probability computations, and more generally, in studying evolutionary possibilities for gene trees on species trees. Defining the Tr-caterpillar-like family as a sequence of n-taxon trees constructed by replacing the r-taxon subtree of n-taxon caterpillars by a specific r-taxon labeled topology Tr, we examine the number of coalescent histories for caterpillar-like families with matching gene tree and species tree labeled topologies. For each Tr with size r≤8, we compute the number of coalescent histories for n-taxon trees in the Tr-caterpillar-like family. Next, as n→∞, we find that the limiting ratio of the numbers of coalescent histories for the Tr family and caterpillars themselves is correlated with the number of labeled histories for Tr. The results support a view that large numbers of coalescent histories occur when a tree has both a relatively balanced subtree and a high tree depth, contributing to deeper understanding of the combinatorics of gene trees and species trees.

Recent results and persisting problems in modeling flow induced coalescence

DOE Office of Scientific and Technical Information (OSTI.GOV)

Fortelný, I., E-mail: fortelny@imc.cas.cz, E-mail: juza@imc.cas.cz; Jza, J., E-mail: fortelny@imc.cas.cz, E-mail: juza@imc.cas.cz

2014-05-15

The contribution summarizes recent results of description of the flow induced coalescence in immiscible polymer blends and addresses problems that call for which solving. The theory of coalescence based on the switch between equations for matrix drainage between spherical or deformed droplets provides a good agreement with more complicated modeling and available experimental data for probability, P{sub c}, that the collision of droplets will be followed by their fusion. A new equation for description of the matrix drainage between deformed droplets, applicable to the whole range of viscosity ratios, p, of the droplets and matrixes, is proposed. The theory facilitatesmore » to consider the effect of the matrix elasticity on coalescence. P{sub c} decreases with the matrix relaxation time but this decrease is not pronounced for relaxation times typical of most commercial polymers. Modeling of the flow induced coalescence in concentrated systems is needed for prediction of the dependence of coalescence rate on volume fraction of droplets. The effect of the droplet anisometry on P{sub c} should be studied for better understanding the coalescence in flow field with high and moderate deformation rates. A reliable description of coalescence in mixing and processing devices requires proper modeling of complex flow fields.« less

Numerical analysis of deposition frequency for successive droplets coalescence dynamics

NASA Astrophysics Data System (ADS)

Cheng, Xiaoding; Zhu, Yunlong; Zhang, Lei; Zhang, Dingyi; Ku, Tao

2018-04-01

A pseudopotential based multi-relaxation-time lattice Boltzmann model is employed to investigate the dynamic behaviors of successive droplets' impact and coalescence on a solid surface. The effects of deposition frequency on the morphology of the formed line are investigated with a zero receding contact angle by analyzing the droplet-to-droplet coalescence dynamics. Two collision modes (in-phase mode and out-of-phase mode) between the pre-deposited bead and the subsequent droplet are identified depending on the deposition frequency. A uniform line can be obtained at the optimal droplet spacing in the in-phase mode (Δt* < 1.875). However, a scalloped line pattern is formed in the out-of-phase mode (Δt* > 1.875). It is found that decreasing the droplet spacing or advancing contact angle can improve the smoothness of line in the out-of-phase mode. Furthermore, the effects of deposition frequency on the morphology of the formed lines are validated to be applicable to cases with a finite receding contact angle.

Fully Bayesian inference for structural MRI: application to segmentation and statistical analysis of T2-hypointensities.

PubMed

Schmidt, Paul; Schmid, Volker J; Gaser, Christian; Buck, Dorothea; Bührlen, Susanne; Förschler, Annette; Mühlau, Mark

2013-01-01

Aiming at iron-related T2-hypointensity, which is related to normal aging and neurodegenerative processes, we here present two practicable approaches, based on Bayesian inference, for preprocessing and statistical analysis of a complex set of structural MRI data. In particular, Markov Chain Monte Carlo methods were used to simulate posterior distributions. First, we rendered a segmentation algorithm that uses outlier detection based on model checking techniques within a Bayesian mixture model. Second, we rendered an analytical tool comprising a Bayesian regression model with smoothness priors (in the form of Gaussian Markov random fields) mitigating the necessity to smooth data prior to statistical analysis. For validation, we used simulated data and MRI data of 27 healthy controls (age: [Formula: see text]; range, [Formula: see text]). We first observed robust segmentation of both simulated T2-hypointensities and gray-matter regions known to be T2-hypointense. Second, simulated data and images of segmented T2-hypointensity were analyzed. We found not only robust identification of simulated effects but also a biologically plausible age-related increase of T2-hypointensity primarily within the dentate nucleus but also within the globus pallidus, substantia nigra, and red nucleus. Our results indicate that fully Bayesian inference can successfully be applied for preprocessing and statistical analysis of structural MRI data.

Bayesian Exploratory Factor Analysis

PubMed Central

Conti, Gabriella; Frühwirth-Schnatter, Sylvia; Heckman, James J.; Piatek, Rémi

2014-01-01

This paper develops and applies a Bayesian approach to Exploratory Factor Analysis that improves on ad hoc classical approaches. Our framework relies on dedicated factor models and simultaneously determines the number of factors, the allocation of each measurement to a unique factor, and the corresponding factor loadings. Classical identification criteria are applied and integrated into our Bayesian procedure to generate models that are stable and clearly interpretable. A Monte Carlo study confirms the validity of the approach. The method is used to produce interpretable low dimensional aggregates from a high dimensional set of psychological measurements. PMID:25431517

Recursions for the exchangeable partition function of the seedbank coalescent.

PubMed

Kurt, Noemi; Rafler, Mathias

2017-04-01

For the seedbank coalescent with mutation under the infinite alleles assumption, which describes the gene genealogy of a population with a strong seedbank effect subject to mutations, we study the distribution of the final partition with mutation. This generalizes the coalescent with freeze by Dong et al. (2007) to coalescents where ancestral lineages are blocked from coalescing. We derive an implicit recursion which we show to have a unique solution and give an interpretation in terms of absorption problems of a random walk. Moreover, we derive recursions for the distribution of the number of blocks in the final partition. Copyright © 2017 Elsevier Inc. All rights reserved.

Short time dynamics of water coalescence on a flat water pool

DOE Office of Scientific and Technical Information (OSTI.GOV)

Lim, Su Jin; Gim, Bopil; Fezzaa, Kamel

2016-12-01

Coalescence is an important hydrodynamic event that frequently takes place in nature as well as in industry. Here we provide an experimental study on short time dynamics of water coalescence, particularly when a water droplet comes in contact with a flat water surface, by utilizing high-resolution high-penetration ultrafast X-ray microscopy. Our results demonstrate a possibility that an extreme curvature difference between a drop and a flat surface can significantly modify the hydrodynamics of water coalescence, which is unexpected in the existing theory. We suggest a plausible explanation for why coalescence can be modified by an extreme curvature difference.

Characteristic time scales of coalescence of silver nanocomposite and nanoparticle films induced by continuous wave laser irradiation

DOE Office of Scientific and Technical Information (OSTI.GOV)

Paeng, Dongwoo; Grigoropoulos, Costas P., E-mail: cgrigoro@berkeley.edu; Lee, Daeho

2014-08-18

In-situ optical probing has been performed to analyze and compare the characteristic coalescence time scales of silver ion-doped polyvinylalcohol nanocomposite (Ag-PVA NC) and polyvinylpyrrolidone-capped silver nanoparticle (Ag-PVP NP) films subjected to continuous wave laser irradiation. The Ag-PVA NC yielded conductive metallic patterns by photothermal reduction of PVA, formation of nanoparticles from silver ions and their subsequent coalescence. On the other hand, Ag-PVP NP thin films produced conductive patterns through only coalescence of nanoparticles. Upon laser irradiation, Ag-PVA NC and Ag-PVP NP films exhibited different coalescence characteristics.

An investigation of bubble coalescence and post-rupture oscillation in non-ionic surfactant solutions using high-speed cinematography.

PubMed

Bournival, G; Ata, S; Karakashev, S I; Jameson, G J

2014-01-15

Most processes involving bubbling in a liquid require small bubbles to maximise mass/energy transfer. A common method to prevent bubbles from coalescing is by the addition of surfactants. In order to get an insight into the coalescence process, capillary bubbles were observed using a high speed cinematography. Experiments were performed in solutions of 1-pentanol, 4-methyl-2-pentanol, tri(propylene glycol) methyl ether, and poly(propylene glycol) for which information such as the coalescence time and the deformation of the resultant bubble upon coalescence was extracted. It is shown in this study that the coalescence time increases with surfactant concentration until the appearance of a plateau. The increase in coalescence time with surfactant concentration could not be attributed only to surface elasticity. The oscillation of the resultant bubble was characterised by the damping of the oscillation. The results suggested that a minimum elasticity is required to achieve an increased damping and considerable diffusion has a detrimental effect on the dynamic response of the bubble, thereby reducing the damping. Copyright © 2013 Elsevier Inc. All rights reserved.

2D Bayesian automated tilted-ring fitting of disc galaxies in large H I galaxy surveys: 2DBAT

NASA Astrophysics Data System (ADS)

Oh, Se-Heon; Staveley-Smith, Lister; Spekkens, Kristine; Kamphuis, Peter; Koribalski, Bärbel S.

2018-01-01

We present a novel algorithm based on a Bayesian method for 2D tilted-ring analysis of disc galaxy velocity fields. Compared to the conventional algorithms based on a chi-squared minimization procedure, this new Bayesian-based algorithm suffers less from local minima of the model parameters even with highly multimodal posterior distributions. Moreover, the Bayesian analysis, implemented via Markov Chain Monte Carlo sampling, only requires broad ranges of posterior distributions of the parameters, which makes the fitting procedure fully automated. This feature will be essential when performing kinematic analysis on the large number of resolved galaxies expected to be detected in neutral hydrogen (H I) surveys with the Square Kilometre Array and its pathfinders. The so-called 2D Bayesian Automated Tilted-ring fitter (2DBAT) implements Bayesian fits of 2D tilted-ring models in order to derive rotation curves of galaxies. We explore 2DBAT performance on (a) artificial H I data cubes built based on representative rotation curves of intermediate-mass and massive spiral galaxies, and (b) Australia Telescope Compact Array H I data from the Local Volume H I Survey. We find that 2DBAT works best for well-resolved galaxies with intermediate inclinations (20° < i < 70°), complementing 3D techniques better suited to modelling inclined galaxies.

Applying Bayesian Modeling and Receiver Operating Characteristic Methodologies for Test Utility Analysis

ERIC Educational Resources Information Center

Wang, Qiu; Diemer, Matthew A.; Maier, Kimberly S.

2013-01-01

This study integrated Bayesian hierarchical modeling and receiver operating characteristic analysis (BROCA) to evaluate how interest strength (IS) and interest differentiation (ID) predicted low–socioeconomic status (SES) youth's interest-major congruence (IMC). Using large-scale Kuder Career Search online-assessment data, this study fit three…

Metrics for evaluating performance and uncertainty of Bayesian network models

Treesearch

Bruce G. Marcot

2012-01-01

This paper presents a selected set of existing and new metrics for gauging Bayesian network model performance and uncertainty. Selected existing and new metrics are discussed for conducting model sensitivity analysis (variance reduction, entropy reduction, case file simulation); evaluating scenarios (influence analysis); depicting model complexity (numbers of model...

Monte Carlo Algorithms for a Bayesian Analysis of the Cosmic Microwave Background

NASA Technical Reports Server (NTRS)

Jewell, Jeffrey B.; Eriksen, H. K.; ODwyer, I. J.; Wandelt, B. D.; Gorski, K.; Knox, L.; Chu, M.

2006-01-01

A viewgraph presentation on the review of Bayesian approach to Cosmic Microwave Background (CMB) analysis, numerical implementation with Gibbs sampling, a summary of application to WMAP I and work in progress with generalizations to polarization, foregrounds, asymmetric beams, and 1/f noise is given.

Bayesian analysis of rare events

DOE Office of Scientific and Technical Information (OSTI.GOV)

Straub, Daniel, E-mail: straub@tum.de; Papaioannou, Iason; Betz, Wolfgang

2016-06-01

In many areas of engineering and science there is an interest in predicting the probability of rare events, in particular in applications related to safety and security. Increasingly, such predictions are made through computer models of physical systems in an uncertainty quantification framework. Additionally, with advances in IT, monitoring and sensor technology, an increasing amount of data on the performance of the systems is collected. This data can be used to reduce uncertainty, improve the probability estimates and consequently enhance the management of rare events and associated risks. Bayesian analysis is the ideal method to include the data into themore » probabilistic model. It ensures a consistent probabilistic treatment of uncertainty, which is central in the prediction of rare events, where extrapolation from the domain of observation is common. We present a framework for performing Bayesian updating of rare event probabilities, termed BUS. It is based on a reinterpretation of the classical rejection-sampling approach to Bayesian analysis, which enables the use of established methods for estimating probabilities of rare events. By drawing upon these methods, the framework makes use of their computational efficiency. These methods include the First-Order Reliability Method (FORM), tailored importance sampling (IS) methods and Subset Simulation (SuS). In this contribution, we briefly review these methods in the context of the BUS framework and investigate their applicability to Bayesian analysis of rare events in different settings. We find that, for some applications, FORM can be highly efficient and is surprisingly accurate, enabling Bayesian analysis of rare events with just a few model evaluations. In a general setting, BUS implemented through IS and SuS is more robust and flexible.« less

Implementing informative priors for heterogeneity in meta-analysis using meta-regression and pseudo data.

PubMed

Rhodes, Kirsty M; Turner, Rebecca M; White, Ian R; Jackson, Dan; Spiegelhalter, David J; Higgins, Julian P T

2016-12-20

Many meta-analyses combine results from only a small number of studies, a situation in which the between-study variance is imprecisely estimated when standard methods are applied. Bayesian meta-analysis allows incorporation of external evidence on heterogeneity, providing the potential for more robust inference on the effect size of interest. We present a method for performing Bayesian meta-analysis using data augmentation, in which we represent an informative conjugate prior for between-study variance by pseudo data and use meta-regression for estimation. To assist in this, we derive predictive inverse-gamma distributions for the between-study variance expected in future meta-analyses. These may serve as priors for heterogeneity in new meta-analyses. In a simulation study, we compare approximate Bayesian methods using meta-regression and pseudo data against fully Bayesian approaches based on importance sampling techniques and Markov chain Monte Carlo (MCMC). We compare the frequentist properties of these Bayesian methods with those of the commonly used frequentist DerSimonian and Laird procedure. The method is implemented in standard statistical software and provides a less complex alternative to standard MCMC approaches. An importance sampling approach produces almost identical results to standard MCMC approaches, and results obtained through meta-regression and pseudo data are very similar. On average, data augmentation provides closer results to MCMC, if implemented using restricted maximum likelihood estimation rather than DerSimonian and Laird or maximum likelihood estimation. The methods are applied to real datasets, and an extension to network meta-analysis is described. The proposed method facilitates Bayesian meta-analysis in a way that is accessible to applied researchers. © 2016 The Authors. Statistics in Medicine Published by John Wiley & Sons Ltd. © 2016 The Authors. Statistics in Medicine Published by John Wiley & Sons Ltd.

Improved inference in Bayesian segmentation using Monte Carlo sampling: application to hippocampal subfield volumetry.

PubMed

Iglesias, Juan Eugenio; Sabuncu, Mert Rory; Van Leemput, Koen

2013-10-01

Many segmentation algorithms in medical image analysis use Bayesian modeling to augment local image appearance with prior anatomical knowledge. Such methods often contain a large number of free parameters that are first estimated and then kept fixed during the actual segmentation process. However, a faithful Bayesian analysis would marginalize over such parameters, accounting for their uncertainty by considering all possible values they may take. Here we propose to incorporate this uncertainty into Bayesian segmentation methods in order to improve the inference process. In particular, we approximate the required marginalization over model parameters using computationally efficient Markov chain Monte Carlo techniques. We illustrate the proposed approach using a recently developed Bayesian method for the segmentation of hippocampal subfields in brain MRI scans, showing a significant improvement in an Alzheimer's disease classification task. As an additional benefit, the technique also allows one to compute informative "error bars" on the volume estimates of individual structures. Copyright © 2013 Elsevier B.V. All rights reserved.

Improved Inference in Bayesian Segmentation Using Monte Carlo Sampling: Application to Hippocampal Subfield Volumetry

PubMed Central

Iglesias, Juan Eugenio; Sabuncu, Mert Rory; Leemput, Koen Van

2013-01-01

Many segmentation algorithms in medical image analysis use Bayesian modeling to augment local image appearance with prior anatomical knowledge. Such methods often contain a large number of free parameters that are first estimated and then kept fixed during the actual segmentation process. However, a faithful Bayesian analysis would marginalize over such parameters, accounting for their uncertainty by considering all possible values they may take. Here we propose to incorporate this uncertainty into Bayesian segmentation methods in order to improve the inference process. In particular, we approximate the required marginalization over model parameters using computationally efficient Markov chain Monte Carlo techniques. We illustrate the proposed approach using a recently developed Bayesian method for the segmentation of hippocampal subfields in brain MRI scans, showing a significant improvement in an Alzheimer’s disease classification task. As an additional benefit, the technique also allows one to compute informative “error bars” on the volume estimates of individual structures. PMID:23773521

Age estimation by assessment of pulp chamber volume: a Bayesian network for the evaluation of dental evidence.

PubMed

Sironi, Emanuele; Taroni, Franco; Baldinotti, Claudio; Nardi, Cosimo; Norelli, Gian-Aristide; Gallidabino, Matteo; Pinchi, Vilma

2017-11-14

The present study aimed to investigate the performance of a Bayesian method in the evaluation of dental age-related evidence collected by means of a geometrical approximation procedure of the pulp chamber volume. Measurement of this volume was based on three-dimensional cone beam computed tomography images. The Bayesian method was applied by means of a probabilistic graphical model, namely a Bayesian network. Performance of that method was investigated in terms of accuracy and bias of the decisional outcomes. Influence of an informed elicitation of the prior belief of chronological age was also studied by means of a sensitivity analysis. Outcomes in terms of accuracy were adequate with standard requirements for forensic adult age estimation. Findings also indicated that the Bayesian method does not show a particular tendency towards under- or overestimation of the age variable. Outcomes of the sensitivity analysis showed that results on estimation are improved with a ration elicitation of the prior probabilities of age.

Coalescence-Induced Jumping of Nanodroplets on Textured Surfaces.

PubMed

Gao, Shan; Liao, Quanwen; Liu, Wei; Liu, Zhichun

2018-01-04

Conducting experimental studies on nanoscale droplet coalescence using traditional microscopes is a challenging research topic, and views differ as to whether the spontaneous removal can occur in the coalescing nanodroplets. Here, a molecular dynamics simulation is carried out to investigate the coalescence process of two equally sized nanodroplets. On the basis of atomic coordinates, we compute the liquid bridge radii for various cases, which is described by a power law of spreading time, and these nanodroplets undergo coalescence in the inertially limited-viscous regime. Moreover, coalescence-induced jumping is also possible for the nanodroplets, and the attraction force between surface and water molecules plays a crucial role in this process, where the merged nanodroplets prefer to jump away from those surfaces with lower attraction force. When the solid-liquid interaction intensity and surface structure parameters are varied, the attraction force is shown to decrease with decreasing surface wettability intensity and solid fraction.

Hybrid-Lambda: simulation of multiple merger and Kingman gene genealogies in species networks and species trees.

PubMed

Zhu, Sha; Degnan, James H; Goldstien, Sharyn J; Eldon, Bjarki

2015-09-15

There has been increasing interest in coalescent models which admit multiple mergers of ancestral lineages; and to model hybridization and coalescence simultaneously. Hybrid-Lambda is a software package that simulates gene genealogies under multiple merger and Kingman's coalescent processes within species networks or species trees. Hybrid-Lambda allows different coalescent processes to be specified for different populations, and allows for time to be converted between generations and coalescent units, by specifying a population size for each population. In addition, Hybrid-Lambda can generate simulated datasets, assuming the infinitely many sites mutation model, and compute the F ST statistic. As an illustration, we apply Hybrid-Lambda to infer the time of subdivision of certain marine invertebrates under different coalescent processes. Hybrid-Lambda makes it possible to investigate biogeographic concordance among high fecundity species exhibiting skewed offspring distribution.

Surfactant effect on drop coalescence and film drainage hydrodynamics

NASA Astrophysics Data System (ADS)

Weheliye, Weheliye; Chinaud, Maxime; Voulgaropoulos, Victor; Angeli, Panagiota

2015-11-01

Coalescence of a drop on an aqueous-organic interface is studied in two test geometries A rectangular acrylic vessel and a Hele-Shaw cell (two parallel plates placed 2mm apart) are investigated for the experiments. Time resolved Particle Image Velocimetry (PIV) measurements provide information on the hydrodynamics during the bouncing stage of the droplet and on the vortices generated at the bulk fluid after the droplet has coalesced. The velocity field inside the droplet during its coalescence is presented. By localizing the rupture point of the coalescence in the quasi two dimensional cell, the film drainage dynamics are discussed by acquiring its flow velocity by PIV measurements with a straddling camera. The effect of surface tension forces in the coalescence of the droplet is investigated by introducing surface active agents at various concentrations extending on both sides of the critical micelle concentration.

Coalescence of Fluid-Driven Fractures

NASA Astrophysics Data System (ADS)

O'Keeffe, Niall; Zheng, Zhong; Huppert, Herbert; Linden, Paul

2017-11-01

We present an experimental study on the coalescence of two in-plane fluid-driven penny-shaped fractures in a brittle elastic medium. Initially, two fluid-driven fractures propagate independently of each other in the same plane. Then when the radial extent of each fracture reaches a certain distance the fractures begin to interact and coalesce. This coalescence forms a bridge between the fractures and then, in an intermediate period following the contact of the two fractures, most growth is observed to focus along this bridge, perpendicular to the line connecting the injection sources. We analyse the growth and shape of this bridge at various stages after coalescence and the transitions between different stages of growth. We also investigate the influence of the injection rate, the distance between two injection points, the viscosity of the fluid and the Young's modulus of the elastic medium on the coalescence of the fractures.

The detachment of particles from coalescing bubble pairs.

PubMed

Ata, Seher

2009-10-15

This paper is concerned with the detachment of particles from coalescing bubble pairs. Two bubbles were generated at adjacent capillaries and coated with hydrophobic glass particles of mean diameter 66 microm. The bubbles were then positioned next to each other until the thin liquid film between them ruptured. The particles that dropped from the bubble surface during the coalescence process were collected and measured. The coalescence process was very vigorous and observations showed that particles detached from the bubble surfaces as a result of the oscillations caused by coalescence. The attached particles themselves and, to some extent the presence of the surfactant had a damping affect on the bubble oscillation, which played a decisive role on the particle detachment phenomena. The behaviour of particles on the surfaces of the bubbles during coalescence was described, and implications of results for the flotation process were discussed.

Next Steps in Bayesian Structural Equation Models: Comments on, Variations of, and Extensions to Muthen and Asparouhov (2012)

ERIC Educational Resources Information Center

Rindskopf, David

2012-01-01

Muthen and Asparouhov (2012) made a strong case for the advantages of Bayesian methodology in factor analysis and structural equation models. I show additional extensions and adaptations of their methods and show how non-Bayesians can take advantage of many (though not all) of these advantages by using interval restrictions on parameters. By…

A Bayesian Approach to Person Fit Analysis in Item Response Theory Models. Research Report.

ERIC Educational Resources Information Center

Glas, Cees A. W.; Meijer, Rob R.

A Bayesian approach to the evaluation of person fit in item response theory (IRT) models is presented. In a posterior predictive check, the observed value on a discrepancy variable is positioned in its posterior distribution. In a Bayesian framework, a Markov Chain Monte Carlo procedure can be used to generate samples of the posterior distribution…

Bayesian Latent Class Analysis Tutorial.

PubMed

Li, Yuelin; Lord-Bessen, Jennifer; Shiyko, Mariya; Loeb, Rebecca

2018-01-01

This article is a how-to guide on Bayesian computation using Gibbs sampling, demonstrated in the context of Latent Class Analysis (LCA). It is written for students in quantitative psychology or related fields who have a working knowledge of Bayes Theorem and conditional probability and have experience in writing computer programs in the statistical language R . The overall goals are to provide an accessible and self-contained tutorial, along with a practical computation tool. We begin with how Bayesian computation is typically described in academic articles. Technical difficulties are addressed by a hypothetical, worked-out example. We show how Bayesian computation can be broken down into a series of simpler calculations, which can then be assembled together to complete a computationally more complex model. The details are described much more explicitly than what is typically available in elementary introductions to Bayesian modeling so that readers are not overwhelmed by the mathematics. Moreover, the provided computer program shows how Bayesian LCA can be implemented with relative ease. The computer program is then applied in a large, real-world data set and explained line-by-line. We outline the general steps in how to extend these considerations to other methodological applications. We conclude with suggestions for further readings.

"Contrasting patterns of selection at Pinus pinaster Ait. Drought stress candidate genes as revealed by genetic differentiation analyses".

PubMed

Eveno, Emmanuelle; Collada, Carmen; Guevara, M Angeles; Léger, Valérie; Soto, Alvaro; Díaz, Luis; Léger, Patrick; González-Martínez, Santiago C; Cervera, M Teresa; Plomion, Christophe; Garnier-Géré, Pauline H

2008-02-01

The importance of natural selection for shaping adaptive trait differentiation among natural populations of allogamous tree species has long been recognized. Determining the molecular basis of local adaptation remains largely unresolved, and the respective roles of selection and demography in shaping population structure are actively debated. Using a multilocus scan that aims to detect outliers from simulated neutral expectations, we analyzed patterns of nucleotide diversity and genetic differentiation at 11 polymorphic candidate genes for drought stress tolerance in phenotypically contrasted Pinus pinaster Ait. populations across its geographical range. We compared 3 coalescent-based methods: 2 frequentist-like, including 1 approach specifically developed for biallelic single nucleotide polymorphisms (SNPs) here and 1 Bayesian. Five genes showed outlier patterns that were robust across methods at the haplotype level for 2 of them. Two genes presented higher F(ST) values than expected (PR-AGP4 and erd3), suggesting that they could have been affected by the action of diversifying selection among populations. In contrast, 3 genes presented lower F(ST) values than expected (dhn-1, dhn2, and lp3-1), which could represent signatures of homogenizing selection among populations. A smaller proportion of outliers were detected at the SNP level suggesting the potential functional significance of particular combinations of sites in drought-response candidate genes. The Bayesian method appeared robust to low sample sizes, flexible to assumptions regarding migration rates, and powerful for detecting selection at the haplotype level, but the frequentist-like method adapted to SNPs was more efficient for the identification of outlier SNPs showing low differentiation. Population-specific effects estimated in the Bayesian method also revealed populations with lower immigration rates, which could have led to favorable situations for local adaptation. Outlier patterns are discussed in relation to the different genes' putative involvement in drought tolerance responses, from published results in transcriptomics and association mapping in P. pinaster and other related species. These genes clearly constitute relevant candidates for future association studies in P. pinaster.

Travelling to the south: Phylogeographic spatial diffusion model in Monttea aphylla (Plantaginaceae), an endemic plant of the Monte Desert

PubMed Central

Cosacov, Andrea; Ferreiro, Gabriela; Johnson, Leigh A.; Sérsic, Alicia N.

2017-01-01

Effects of Pleistocene climatic oscillations on plant phylogeographic patterns are relatively well studied in forest, savanna and grassland biomes, but such impacts remain less explored on desert regions of the world, especially in South America. Here, we performed a phylogeographical study of Monttea aphylla, an endemic species of the Monte Desert, to understand the evolutionary history of vegetation communities inhabiting the South American Arid Diagonal. We obtained sequences of three chloroplast (trnS–trnfM, trnH–psbA and trnQ–rps16) and one nuclear (ITS) intergenic spacers from 272 individuals of 34 localities throughout the range of the species. Population genetic and Bayesian coalescent analyses were performed to infer genealogical relationships among haplotypes, population genetic structure, and demographic history of the study species. Timing of demographic events was inferred using Bayesian Skyline Plot and the spatio-temporal patterns of lineage diversification was reconstructed using Bayesian relaxed diffusion models. Palaeo-distribution models (PDM) were performed through three different timescales to validate phylogeographical patterns. Twenty-five and 22 haplotypes were identified in the cpDNA and nDNA data, respectively. that clustered into two main genealogical lineages following a latitudinal pattern, the northern and the southern Monte (south of 35° S). The northern Monte showed two lineages of high genetic structure, and more relative stable demography than the southern Monte that retrieved three groups with little phylogenetic structure and a strong signal of demographic expansion that would have started during the Last Interglacial period (ca. 120 Ka). The PDM and diffusion models analyses agreed in the southeast direction of the range expansion. Differential effect of climatic oscillations across the Monte phytogeographic province was observed in Monttea aphylla lineages. In northern Monte, greater genetic structure and more relative stable demography resulted from a more stable climate than in the southern Monte. Pleistocene glaciations drastically decreased the species area in the southern Monte, which expanded in a southeastern direction to the new available areas during the interglacial periods. PMID:28582433

Bayesian multimodel inference for dose-response studies

USGS Publications Warehouse

Link, W.A.; Albers, P.H.

2007-01-01

Statistical inference in dose?response studies is model-based: The analyst posits a mathematical model of the relation between exposure and response, estimates parameters of the model, and reports conclusions conditional on the model. Such analyses rarely include any accounting for the uncertainties associated with model selection. The Bayesian inferential system provides a convenient framework for model selection and multimodel inference. In this paper we briefly describe the Bayesian paradigm and Bayesian multimodel inference. We then present a family of models for multinomial dose?response data and apply Bayesian multimodel inferential methods to the analysis of data on the reproductive success of American kestrels (Falco sparveriuss) exposed to various sublethal dietary concentrations of methylmercury.

Wetting and Coalescence of Drops of Self-Healing Agents on Electrospun Nanofiber Mats.

PubMed

An, Seongpil; Kim, Yong Il; Lee, Min Wook; Yarin, Alexander L; Yoon, Sam S

2017-10-10

Here we study experimentally the behavior of liquid healing agents released in vascular core-shell nanofiber mats used in self-healing engineered materials. It is shown that wettability-driven spreading of liquid drops is accompanied by the imbibition into the nanofiber matrix, and its laws deviate from those known for spreading on an intact surface. We also explore coalescence of the released drops on nanofiber mats, in particular, coalescence of drops of resin monomer and cure important for self-healing. The coalescence process is also affected by the imbibition into the pores of an underlying nanofiber mat. A theoretical model is developed to account for the imbibition effect on drop coalescence.

Bayesian B-spline mapping for dynamic quantitative traits.

PubMed

Xing, Jun; Li, Jiahan; Yang, Runqing; Zhou, Xiaojing; Xu, Shizhong

2012-04-01

Owing to their ability and flexibility to describe individual gene expression at different time points, random regression (RR) analyses have become a popular procedure for the genetic analysis of dynamic traits whose phenotypes are collected over time. Specifically, when modelling the dynamic patterns of gene expressions in the RR framework, B-splines have been proved successful as an alternative to orthogonal polynomials. In the so-called Bayesian B-spline quantitative trait locus (QTL) mapping, B-splines are used to characterize the patterns of QTL effects and individual-specific time-dependent environmental errors over time, and the Bayesian shrinkage estimation method is employed to estimate model parameters. Extensive simulations demonstrate that (1) in terms of statistical power, Bayesian B-spline mapping outperforms the interval mapping based on the maximum likelihood; (2) for the simulated dataset with complicated growth curve simulated by B-splines, Legendre polynomial-based Bayesian mapping is not capable of identifying the designed QTLs accurately, even when higher-order Legendre polynomials are considered and (3) for the simulated dataset using Legendre polynomials, the Bayesian B-spline mapping can find the same QTLs as those identified by Legendre polynomial analysis. All simulation results support the necessity and flexibility of B-spline in Bayesian mapping of dynamic traits. The proposed method is also applied to a real dataset, where QTLs controlling the growth trajectory of stem diameters in Populus are located.

Phylogenetic Relationships and Species Delimitation in Pinus Section Trifoliae Inferrred from Plastid DNA

PubMed Central

Hernández-León, Sergio; Gernandt, David S.; Pérez de la Rosa, Jorge A.; Jardón-Barbolla, Lev

2013-01-01

Recent diversification followed by secondary contact and hybridization may explain complex patterns of intra- and interspecific morphological and genetic variation in the North American hard pines (Pinus section Trifoliae), a group of approximately 49 tree species distributed in North and Central America and the Caribbean islands. We concatenated five plastid DNA markers for an average of 3.9 individuals per putative species and assessed the suitability of the five regions as DNA bar codes for species identification, species delimitation, and phylogenetic reconstruction. The ycf1 gene accounted for the greatest proportion of the alignment (46.9%), the greatest proportion of variable sites (74.9%), and the most unique sequences (75 haplotypes). Phylogenetic analysis recovered clades corresponding to subsections Australes, Contortae, and Ponderosae. Sequences for 23 of the 49 species were monophyletic and sequences for another 9 species were paraphyletic. Morphologically similar species within subsections usually grouped together, but there were exceptions consistent with incomplete lineage sorting or introgression. Bayesian relaxed molecular clock analyses indicated that all three subsections diversified relatively recently during the Miocene. The general mixed Yule-coalescent method gave a mixed model estimate of only 22 or 23 evolutionary entities for the plastid sequences, which corresponds to less than half the 49 species recognized based on morphological species assignments. Including more unique haplotypes per species may result in higher estimates, but low mutation rates, recent diversification, and large effective population sizes may limit the effectiveness of this method to detect evolutionary entities. PMID:23936218

Identifying predictors of time-inhomogeneous viral evolutionary processes.

PubMed

Bielejec, Filip; Baele, Guy; Rodrigo, Allen G; Suchard, Marc A; Lemey, Philippe

2016-07-01

Various factors determine the rate at which mutations are generated and fixed in viral genomes. Viral evolutionary rates may vary over the course of a single persistent infection and can reflect changes in replication rates and selective dynamics. Dedicated statistical inference approaches are required to understand how the complex interplay of these processes shapes the genetic diversity and divergence in viral populations. Although evolutionary models accommodating a high degree of complexity can now be formalized, adequately informing these models by potentially sparse data, and assessing the association of the resulting estimates with external predictors, remains a major challenge. In this article, we present a novel Bayesian evolutionary inference method, which integrates multiple potential predictors and tests their association with variation in the absolute rates of synonymous and non-synonymous substitutions along the evolutionary history. We consider clinical and virological measures as predictors, but also changes in population size trajectories that are simultaneously inferred using coalescent modelling. We demonstrate the potential of our method in an application to within-host HIV-1 sequence data sampled throughout the infection of multiple patients. While analyses of individual patient populations lack statistical power, we detect significant evidence for an abrupt drop in non-synonymous rates in late stage infection and a more gradual increase in synonymous rates over the course of infection in a joint analysis across all patients. The former is predicted by the immune relaxation hypothesis while the latter may be in line with increasing replicative fitness during the asymptomatic stage.

The space of ultrametric phylogenetic trees.

PubMed

Gavryushkin, Alex; Drummond, Alexei J

2016-08-21

The reliability of a phylogenetic inference method from genomic sequence data is ensured by its statistical consistency. Bayesian inference methods produce a sample of phylogenetic trees from the posterior distribution given sequence data. Hence the question of statistical consistency of such methods is equivalent to the consistency of the summary of the sample. More generally, statistical consistency is ensured by the tree space used to analyse the sample. In this paper, we consider two standard parameterisations of phylogenetic time-trees used in evolutionary models: inter-coalescent interval lengths and absolute times of divergence events. For each of these parameterisations we introduce a natural metric space on ultrametric phylogenetic trees. We compare the introduced spaces with existing models of tree space and formulate several formal requirements that a metric space on phylogenetic trees must possess in order to be a satisfactory space for statistical analysis, and justify them. We show that only a few known constructions of the space of phylogenetic trees satisfy these requirements. However, our results suggest that these basic requirements are not enough to distinguish between the two metric spaces we introduce and that the choice between metric spaces requires additional properties to be considered. Particularly, that the summary tree minimising the square distance to the trees from the sample might be different for different parameterisations. This suggests that further fundamental insight is needed into the problem of statistical consistency of phylogenetic inference methods. Copyright © 2016 The Authors. Published by Elsevier Ltd.. All rights reserved.

Meiotic gene-conversion rate and tract length variation in the human genome.

PubMed

Padhukasahasram, Badri; Rannala, Bruce

2013-02-27

Meiotic recombination occurs in the form of two different mechanisms called crossing-over and gene-conversion and both processes have an important role in shaping genetic variation in populations. Although variation in crossing-over rates has been studied extensively using sperm-typing experiments, pedigree studies and population genetic approaches, our knowledge of variation in gene-conversion parameters (ie, rates and mean tract lengths) remains far from complete. To explore variability in population gene-conversion rates and its relationship to crossing-over rate variation patterns, we have developed and validated using coalescent simulations a comprehensive Bayesian full-likelihood method that can jointly infer crossing-over and gene-conversion rates as well as tract lengths from population genomic data under general variable rate models with recombination hotspots. Here, we apply this new method to SNP data from multiple human populations and attempt to characterize for the first time the fine-scale variation in gene-conversion parameters along the human genome. We find that the estimated ratio of gene-conversion to crossing-over rates varies considerably across genomic regions as well as between populations. However, there is a great degree of uncertainty associated with such estimates. We also find substantial evidence for variation in the mean conversion tract length. The estimated tract lengths did not show any negative relationship with the local heterozygosity levels in our analysis.European Journal of Human Genetics advance online publication, 27 February 2013; doi:10.1038/ejhg.2013.30.

Phylogenetic relationships and species delimitation in pinus section trifoliae inferrred from plastid DNA.

PubMed

Hernández-León, Sergio; Gernandt, David S; Pérez de la Rosa, Jorge A; Jardón-Barbolla, Lev

2013-01-01

Recent diversification followed by secondary contact and hybridization may explain complex patterns of intra- and interspecific morphological and genetic variation in the North American hard pines (Pinus section Trifoliae), a group of approximately 49 tree species distributed in North and Central America and the Caribbean islands. We concatenated five plastid DNA markers for an average of 3.9 individuals per putative species and assessed the suitability of the five regions as DNA bar codes for species identification, species delimitation, and phylogenetic reconstruction. The ycf1 gene accounted for the greatest proportion of the alignment (46.9%), the greatest proportion of variable sites (74.9%), and the most unique sequences (75 haplotypes). Phylogenetic analysis recovered clades corresponding to subsections Australes, Contortae, and Ponderosae. Sequences for 23 of the 49 species were monophyletic and sequences for another 9 species were paraphyletic. Morphologically similar species within subsections usually grouped together, but there were exceptions consistent with incomplete lineage sorting or introgression. Bayesian relaxed molecular clock analyses indicated that all three subsections diversified relatively recently during the Miocene. The general mixed Yule-coalescent method gave a mixed model estimate of only 22 or 23 evolutionary entities for the plastid sequences, which corresponds to less than half the 49 species recognized based on morphological species assignments. Including more unique haplotypes per species may result in higher estimates, but low mutation rates, recent diversification, and large effective population sizes may limit the effectiveness of this method to detect evolutionary entities.

Magnetic merging in colliding flux tubes

NASA Technical Reports Server (NTRS)

Zweibel, Ellen G.; Rhoads, James E.

1995-01-01

We develop an analytical theory of reconnection between colliding, twisted magnetic flux tubes. Our analysis is restricted to direct collisions between parallel tubes and is based on the collision dynamics worked out by Bogdan (1984). We show that there is a range of collision velocities for which neutral point reconnection of the Parker-Sweet type can occur, and a smaller range for which reconnection leads to coalescence. Mean velocities within the solar convection zone are probably significantly greater than the upper limit for coalescence. This suggests that the majority of flux tube collisions do not result in merging, unless the frictional coupling of the tubes to the background flow is extremely strong.

Bayesian inference for psychology. Part II: Example applications with JASP.

PubMed

Wagenmakers, Eric-Jan; Love, Jonathon; Marsman, Maarten; Jamil, Tahira; Ly, Alexander; Verhagen, Josine; Selker, Ravi; Gronau, Quentin F; Dropmann, Damian; Boutin, Bruno; Meerhoff, Frans; Knight, Patrick; Raj, Akash; van Kesteren, Erik-Jan; van Doorn, Johnny; Šmíra, Martin; Epskamp, Sacha; Etz, Alexander; Matzke, Dora; de Jong, Tim; van den Bergh, Don; Sarafoglou, Alexandra; Steingroever, Helen; Derks, Koen; Rouder, Jeffrey N; Morey, Richard D

2018-02-01

Bayesian hypothesis testing presents an attractive alternative to p value hypothesis testing. Part I of this series outlined several advantages of Bayesian hypothesis testing, including the ability to quantify evidence and the ability to monitor and update this evidence as data come in, without the need to know the intention with which the data were collected. Despite these and other practical advantages, Bayesian hypothesis tests are still reported relatively rarely. An important impediment to the widespread adoption of Bayesian tests is arguably the lack of user-friendly software for the run-of-the-mill statistical problems that confront psychologists for the analysis of almost every experiment: the t-test, ANOVA, correlation, regression, and contingency tables. In Part II of this series we introduce JASP ( http://www.jasp-stats.org ), an open-source, cross-platform, user-friendly graphical software package that allows users to carry out Bayesian hypothesis tests for standard statistical problems. JASP is based in part on the Bayesian analyses implemented in Morey and Rouder's BayesFactor package for R. Armed with JASP, the practical advantages of Bayesian hypothesis testing are only a mouse click away.

Applying Bayesian statistics to the study of psychological trauma: A suggestion for future research.

PubMed

Yalch, Matthew M

2016-03-01

Several contemporary researchers have noted the virtues of Bayesian methods of data analysis. Although debates continue about whether conventional or Bayesian statistics is the "better" approach for researchers in general, there are reasons why Bayesian methods may be well suited to the study of psychological trauma in particular. This article describes how Bayesian statistics offers practical solutions to the problems of data non-normality, small sample size, and missing data common in research on psychological trauma. After a discussion of these problems and the effects they have on trauma research, this article explains the basic philosophical and statistical foundations of Bayesian statistics and how it provides solutions to these problems using an applied example. Results of the literature review and the accompanying example indicates the utility of Bayesian statistics in addressing problems common in trauma research. Bayesian statistics provides a set of methodological tools and a broader philosophical framework that is useful for trauma researchers. Methodological resources are also provided so that interested readers can learn more. (c) 2016 APA, all rights reserved).

Bayesian Network Meta-Analysis for Unordered Categorical Outcomes with Incomplete Data

ERIC Educational Resources Information Center

Schmid, Christopher H.; Trikalinos, Thomas A.; Olkin, Ingram

2014-01-01

We develop a Bayesian multinomial network meta-analysis model for unordered (nominal) categorical outcomes that allows for partially observed data in which exact event counts may not be known for each category. This model properly accounts for correlations of counts in mutually exclusive categories and enables proper comparison and ranking of…

A Comparison of Imputation Methods for Bayesian Factor Analysis Models

ERIC Educational Resources Information Center

Merkle, Edgar C.

2011-01-01

Imputation methods are popular for the handling of missing data in psychology. The methods generally consist of predicting missing data based on observed data, yielding a complete data set that is amiable to standard statistical analyses. In the context of Bayesian factor analysis, this article compares imputation under an unrestricted…

Modeling Associations among Multivariate Longitudinal Categorical Variables in Survey Data: A Semiparametric Bayesian Approach

ERIC Educational Resources Information Center

Tchumtchoua, Sylvie; Dey, Dipak K.

2012-01-01

This paper proposes a semiparametric Bayesian framework for the analysis of associations among multivariate longitudinal categorical variables in high-dimensional data settings. This type of data is frequent, especially in the social and behavioral sciences. A semiparametric hierarchical factor analysis model is developed in which the…

Bayesian Meta-Analysis of Cronbach's Coefficient Alpha to Evaluate Informative Hypotheses

ERIC Educational Resources Information Center

Okada, Kensuke

2015-01-01

This paper proposes a new method to evaluate informative hypotheses for meta-analysis of Cronbach's coefficient alpha using a Bayesian approach. The coefficient alpha is one of the most widely used reliability indices. In meta-analyses of reliability, researchers typically form specific informative hypotheses beforehand, such as "alpha of…

Assessment of Matrix Multiplication Learning with a Rule-Based Analytical Model--"A Bayesian Network Representation"

ERIC Educational Resources Information Center

Zhang, Zhidong

2016-01-01

This study explored an alternative assessment procedure to examine learning trajectories of matrix multiplication. It took rule-based analytical and cognitive task analysis methods specifically to break down operation rules for a given matrix multiplication. Based on the analysis results, a hierarchical Bayesian network, an assessment model,…

Using Discrete Loss Functions and Weighted Kappa for Classification: An Illustration Based on Bayesian Network Analysis

ERIC Educational Resources Information Center

Zwick, Rebecca; Lenaburg, Lubella

2009-01-01

In certain data analyses (e.g., multiple discriminant analysis and multinomial log-linear modeling), classification decisions are made based on the estimated posterior probabilities that individuals belong to each of several distinct categories. In the Bayesian network literature, this type of classification is often accomplished by assigning…

Application of Multiple Imputation for Missing Values in Three-Way Three-Mode Multi-Environment Trial Data

PubMed Central

Tian, Ting; McLachlan, Geoffrey J.; Dieters, Mark J.; Basford, Kaye E.

2015-01-01

It is a common occurrence in plant breeding programs to observe missing values in three-way three-mode multi-environment trial (MET) data. We proposed modifications of models for estimating missing observations for these data arrays, and developed a novel approach in terms of hierarchical clustering. Multiple imputation (MI) was used in four ways, multiple agglomerative hierarchical clustering, normal distribution model, normal regression model, and predictive mean match. The later three models used both Bayesian analysis and non-Bayesian analysis, while the first approach used a clustering procedure with randomly selected attributes and assigned real values from the nearest neighbour to the one with missing observations. Different proportions of data entries in six complete datasets were randomly selected to be missing and the MI methods were compared based on the efficiency and accuracy of estimating those values. The results indicated that the models using Bayesian analysis had slightly higher accuracy of estimation performance than those using non-Bayesian analysis but they were more time-consuming. However, the novel approach of multiple agglomerative hierarchical clustering demonstrated the overall best performances. PMID:26689369

Application of Multiple Imputation for Missing Values in Three-Way Three-Mode Multi-Environment Trial Data.

PubMed

Tian, Ting; McLachlan, Geoffrey J; Dieters, Mark J; Basford, Kaye E

2015-01-01

It is a common occurrence in plant breeding programs to observe missing values in three-way three-mode multi-environment trial (MET) data. We proposed modifications of models for estimating missing observations for these data arrays, and developed a novel approach in terms of hierarchical clustering. Multiple imputation (MI) was used in four ways, multiple agglomerative hierarchical clustering, normal distribution model, normal regression model, and predictive mean match. The later three models used both Bayesian analysis and non-Bayesian analysis, while the first approach used a clustering procedure with randomly selected attributes and assigned real values from the nearest neighbour to the one with missing observations. Different proportions of data entries in six complete datasets were randomly selected to be missing and the MI methods were compared based on the efficiency and accuracy of estimating those values. The results indicated that the models using Bayesian analysis had slightly higher accuracy of estimation performance than those using non-Bayesian analysis but they were more time-consuming. However, the novel approach of multiple agglomerative hierarchical clustering demonstrated the overall best performances.

A lattice Boltzmann simulation of coalescence-induced droplet jumping on superhydrophobic surfaces with randomly distributed structures

NASA Astrophysics Data System (ADS)

Zhang, Li-Zhi; Yuan, Wu-Zhi

2018-04-01

The motion of coalescence-induced condensate droplets on superhydrophobic surface (SHS) has attracted increasing attention in energy-related applications. Previous researches were focused on regularly rough surfaces. Here a new approach, a mesoscale lattice Boltzmann method (LBM), is proposed and used to model the dynamic behavior of coalescence-induced droplet jumping on SHS with randomly distributed rough structures. A Fast Fourier Transformation (FFT) method is used to generate non-Gaussian randomly distributed rough surfaces with the skewness (Sk), kurtosis (K) and root mean square (Rq) obtained from real surfaces. Three typical spreading states of coalesced droplets are observed through LBM modeling on various rough surfaces, which are found to significantly influence the jumping ability of coalesced droplet. The coalesced droplets spreading in Cassie state or in composite state will jump off the rough surfaces, while the ones spreading in Wenzel state would eventually remain on the rough surfaces. It is demonstrated that the rough surfaces with smaller Sks, larger Rqs and a K at 3.0 are beneficial to coalescence-induced droplet jumping. The new approach gives more detailed insights into the design of SHS.

On spatial coalescents with multiple mergers in two dimensions.

PubMed

Heuer, Benjamin; Sturm, Anja

2013-08-01

We consider the genealogy of a sample of individuals taken from a spatially structured population when the variance of the offspring distribution is relatively large. The space is structured into discrete sites of a graph G. If the population size at each site is large, spatial coalescents with multiple mergers, so called spatial Λ-coalescents, for which ancestral lines migrate in space and coalesce according to some Λ-coalescent mechanism, are shown to be appropriate approximations to the genealogy of a sample of individuals. We then consider as the graph G the two dimensional torus with side length 2L+1 and show that as L tends to infinity, and time is rescaled appropriately, the partition structure of spatial Λ-coalescents of individuals sampled far enough apart converges to the partition structure of a non-spatial Kingman coalescent. From a biological point of view this means that in certain circumstances both the spatial structure as well as larger variances of the underlying offspring distribution are harder to detect from the sample. However, supplemental simulations show that for moderately large L the different structure is still evident. Copyright © 2012 Elsevier Inc. All rights reserved.

Coalescence preference in dense packing of bubbles

NASA Astrophysics Data System (ADS)

Kim, Yeseul; Gim, Bopil; Gim, Bopil; Weon, Byung Mook

2015-11-01

Coalescence preference is the tendency that a merged bubble from the contact of two original bubbles (parent) tends to be near to the bigger parent. Here, we show that the coalescence preference can be blocked by densely packing of neighbor bubbles. We use high-speed high-resolution X-ray microscopy to clearly visualize individual coalescence phenomenon which occurs in micro scale seconds and inside dense packing of microbubbles with a local packing fraction of ~40%. Previous theory and experimental evidence predict a power of -5 between the relative coalescence position and the parent size. However, our new observation for coalescence preference in densely packed microbubbles shows a different power of -2. We believe that this result may be important to understand coalescence dynamics in dense packing of soft matter. This work (NRF-2013R1A22A04008115) was supported by Mid-career Researcher Program through NRF grant funded by the MEST and also was supported by Ministry of Science, ICT and Future Planning (2009-0082580) and by Basic Science Research Program through the National Research Foundation of Korea (NRF) funded by the Ministry and Education, Science and Technology (NRF-2012R1A6A3A04039257).

Approximate string matching algorithms for limited-vocabulary OCR output correction

NASA Astrophysics Data System (ADS)

Lasko, Thomas A.; Hauser, Susan E.

2000-12-01

Five methods for matching words mistranslated by optical character recognition to their most likely match in a reference dictionary were tested on data from the archives of the National Library of Medicine. The methods, including an adaptation of the cross correlation algorithm, the generic edit distance algorithm, the edit distance algorithm with a probabilistic substitution matrix, Bayesian analysis, and Bayesian analysis on an actively thinned reference dictionary were implemented and their accuracy rates compared. Of the five, the Bayesian algorithm produced the most correct matches (87%), and had the advantage of producing scores that have a useful and practical interpretation.

Bayesian conditional-independence modeling of the AIDS epidemic in England and Wales

NASA Astrophysics Data System (ADS)

Gilks, Walter R.; De Angelis, Daniela; Day, Nicholas E.

We describe the use of conditional-independence modeling, Bayesian inference and Markov chain Monte Carlo, to model and project the HIV-AIDS epidemic in homosexual/bisexual males in England and Wales. Complexity in this analysis arises through selectively missing data, indirectly observed underlying processes, and measurement error. Our emphasis is on presentation and discussion of the concepts, not on the technicalities of this analysis, which can be found elsewhere [D. De Angelis, W.R. Gilks, N.E. Day, Bayesian projection of the the acquired immune deficiency syndrome epidemic (with discussion), Applied Statistics, in press].

Time-varying nonstationary multivariate risk analysis using a dynamic Bayesian copula

NASA Astrophysics Data System (ADS)

Sarhadi, Ali; Burn, Donald H.; Concepción Ausín, María.; Wiper, Michael P.

2016-03-01

A time-varying risk analysis is proposed for an adaptive design framework in nonstationary conditions arising from climate change. A Bayesian, dynamic conditional copula is developed for modeling the time-varying dependence structure between mixed continuous and discrete multiattributes of multidimensional hydrometeorological phenomena. Joint Bayesian inference is carried out to fit the marginals and copula in an illustrative example using an adaptive, Gibbs Markov Chain Monte Carlo (MCMC) sampler. Posterior mean estimates and credible intervals are provided for the model parameters and the Deviance Information Criterion (DIC) is used to select the model that best captures different forms of nonstationarity over time. This study also introduces a fully Bayesian, time-varying joint return period for multivariate time-dependent risk analysis in nonstationary environments. The results demonstrate that the nature and the risk of extreme-climate multidimensional processes are changed over time under the impact of climate change, and accordingly the long-term decision making strategies should be updated based on the anomalies of the nonstationary environment.

Bayesian model reduction and empirical Bayes for group (DCM) studies

PubMed Central

Friston, Karl J.; Litvak, Vladimir; Oswal, Ashwini; Razi, Adeel; Stephan, Klaas E.; van Wijk, Bernadette C.M.; Ziegler, Gabriel; Zeidman, Peter

2016-01-01

This technical note describes some Bayesian procedures for the analysis of group studies that use nonlinear models at the first (within-subject) level – e.g., dynamic causal models – and linear models at subsequent (between-subject) levels. Its focus is on using Bayesian model reduction to finesse the inversion of multiple models of a single dataset or a single (hierarchical or empirical Bayes) model of multiple datasets. These applications of Bayesian model reduction allow one to consider parametric random effects and make inferences about group effects very efficiently (in a few seconds). We provide the relatively straightforward theoretical background to these procedures and illustrate their application using a worked example. This example uses a simulated mismatch negativity study of schizophrenia. We illustrate the robustness of Bayesian model reduction to violations of the (commonly used) Laplace assumption in dynamic causal modelling and show how its recursive application can facilitate both classical and Bayesian inference about group differences. Finally, we consider the application of these empirical Bayesian procedures to classification and prediction. PMID:26569570

Evolution of the viral hemorrhagic septicemia virus: divergence, selection and origin.

PubMed

He, Mei; Yan, Xue-Chun; Liang, Yang; Sun, Xiao-Wen; Teng, Chun-Bo

2014-08-01

Viral hemorrhagic septicemia virus (VHSV) is an economically significant rhabdovirus that affects an increasing number of freshwater and marine fish species. Extensive studies have been conducted on the molecular epizootiology, genetic diversity, and phylogeny of VHSV. However, there are discrepancies between the reported estimates of the nucleotide substitution rate for the G gene and the divergence times for the genotypes. Herein, Bayesian coalescent analyses were conducted to the time-stamped entire coding sequences of the six VHSV genes. Rate estimates based on the G gene indicated that the marine genotypes/subtypes might not all evolve slower than their major European freshwater counterpart. Age calculations on the six genes revealed that the first bifurcation event of the analyzed isolates might have taken place within the last 300 years, which was much younger than previously thought. Selection analyses suggested that two codons of the G gene might be positively selected. Surveys of codon usage bias showed that the P, M and NV genes exhibited genotype-specific variations. Furthermore, we proposed that VHSV originated from the Pacific Northwest of North America. Copyright © 2014 Elsevier Inc. All rights reserved.

Multi-locus phylogeny and divergence time estimates of Enallagma damselflies (Odonata: Coenagrionidae).

PubMed

Callahan, Melissa S; McPeek, Mark A

2016-01-01

Reconstructing evolutionary patterns of species and populations provides a framework for asking questions about the impacts of climate change. Here we use a multilocus dataset to estimate gene trees under maximum likelihood and Bayesian models to obtain a robust estimate of relationships for a genus of North American damselflies, Enallagma. Using a relaxed molecular clock, we estimate the divergence times for this group. Furthermore, to account for the fact that gene tree analyses can overestimate ages of population divergences, we use a multi-population coalescent model to gain a more accurate estimate of divergence times. We also infer diversification rates using a method that allows for variation in diversification rate through time and among lineages. Our results reveal a complex evolutionary history of Enallagma, in which divergence events both predate and occur during Pleistocene climate fluctuations. There is also evidence of diversification rate heterogeneity across the tree. These divergence time estimates provide a foundation for addressing the relative significance of historical climatic events in the diversification of this genus. Copyright © 2015 Elsevier Inc. All rights reserved.

Dirichlet Process Gaussian-mixture model: An application to localizing coalescing binary neutron stars with gravitational-wave observations

NASA Astrophysics Data System (ADS)

Del Pozzo, W.; Berry, C. P. L.; Ghosh, A.; Haines, T. S. F.; Singer, L. P.; Vecchio, A.

2018-06-01

We reconstruct posterior distributions for the position (sky area and distance) of a simulated set of binary neutron-star gravitational-waves signals observed with Advanced LIGO and Advanced Virgo. We use a Dirichlet Process Gaussian-mixture model, a fully Bayesian non-parametric method that can be used to estimate probability density functions with a flexible set of assumptions. The ability to reliably reconstruct the source position is important for multimessenger astronomy, as recently demonstrated with GW170817. We show that for detector networks comparable to the early operation of Advanced LIGO and Advanced Virgo, typical localization volumes are ˜104-105 Mpc3 corresponding to ˜102-103 potential host galaxies. The localization volume is a strong function of the network signal-to-noise ratio, scaling roughly ∝ϱnet-6. Fractional localizations improve with the addition of further detectors to the network. Our Dirichlet Process Gaussian-mixture model can be adopted for localizing events detected during future gravitational-wave observing runs, and used to facilitate prompt multimessenger follow-up.

Near Full-Length Characterization and Population Dynamics of the Human Immunodeficiency Virus Type I Circulating Recombinant Form 42 (CRF42_BF) in Luxembourg.

PubMed

Struck, Daniel; Roman, François; De Landtsheer, Sébastien; Servais, Jean-Yves; Lambert, Christine; Masquelier, Cécile; Venard, Véronique; Ruelle, Jean; Nijhuis, Monique; Schmit, Jean-Claude; Seguin-Devaux, Carole

2015-05-01

A new recombinant form representing a mosaic of HIV-1 subtype B and F1 and designated as CRF42_BF was identified in Luxembourg. We confirmed the inedited nature of CRF42_BF by near full-length genome characterization and retrieved a possible ancestor originating from Brazil. The demographic history of CRF42_BF in Luxembourg using Bayesian coalescent-based methods was investigated. The exponential phase of the logistic growth happened in a very short time period of approximately 5 months associated with a high mean rate of population growth of 15.02 new infections per year. However, CRF42_BF was not characterized by either a higher ex vivo replication capacity in peripheral blood mononuclear cells (PBMCs) or a higher ex vivo transmission efficiency from monocyte-derived dendritic cells to PBMCs as compared to B and F1 viruses. These data do not support a high pathogenic potential of CFR42_BF but rather an initial bursting spread of the recombinant probably due to a more favorable transmission route.

The tale of a modern animal plague: Tracing the evolutionary history and determining the time-scale for foot and mouth disease virus

DOE Office of Scientific and Technical Information (OSTI.GOV)

Tully, Damien C.; Fares, Mario A.

2008-12-20

Despite significant advances made in the understanding of its epidemiology, foot and mouth disease virus (FMDV) is among the most unexpected agricultural devastating plagues. While the disease manifests itself as seven immunologically distinct strains their origin, population dynamics, migration patterns and divergence times remain unknown. Herein we have assembled a comprehensive data set of gene sequences representing the global diversity of the disease and inferred the time-scale and evolutionary history for FMDV. Serotype-specific rates of evolution and divergence times were estimated using a Bayesian coalescent framework. We report that an ancient precursor FMDV gave rise to two major diversification eventsmore » spanning a relatively short interval of time. This radiation event is estimated to have taken place towards the end of the 17th and the beginning of the 18th century giving us the present circulating Euro-Asiatic and South African viral strains. Furthermore our results hint that Europe acted as a possible hub for the disease from where it successfully dispersed elsewhere via exploration and trading routes.« less

A Pragmatic Bayesian Perspective on Correlation Analysis. The exoplanetary gravity - stellar activity case

NASA Astrophysics Data System (ADS)

Figueira, P.; Faria, J. P.; Adibekyan, V. Zh.; Oshagh, M.; Santos, N. C.

2016-11-01

We apply the Bayesian framework to assess the presence of a correlation between two quantities. To do so, we estimate the probability distribution of the parameter of interest, ρ, characterizing the strength of the correlation. We provide an implementation of these ideas and concepts using python programming language and the pyMC module in a very short (˜ 130 lines of code, heavily commented) and user-friendly program. We used this tool to assess the presence and properties of the correlation between planetary surface gravity and stellar activity level as measured by the log(R^' }_{ {HK}}) indicator. The results of the Bayesian analysis are qualitatively similar to those obtained via p-value analysis, and support the presence of a correlation in the data. The results are more robust in their derivation and more informative, revealing interesting features such as asymmetric posterior distributions or markedly different credible intervals, and allowing for a deeper exploration. We encourage the reader interested in this kind of problem to apply our code to his/her own scientific problems. The full understanding of what the Bayesian framework is can only be gained through the insight that comes by handling priors, assessing the convergence of Monte Carlo runs, and a multitude of other practical problems. We hope to contribute so that Bayesian analysis becomes a tool in the toolkit of researchers, and they understand by experience its advantages and limitations.

Comparison of nonwoven fiberglass and stainless steel microfiber media in aerosol coalescence filtration

NASA Astrophysics Data System (ADS)

Manzo, Gabriel

Coalescing filters are used to remove small liquid droplets from air streams. They have numerous industrial applications including dehumidification, cabin air filtration, compressed air filtration, metal working, CCV, and agriculture. In compressed air systems, oils used for lubrication of compressor parts can aerosolize into the main air stream causing potential contamination concerns for downstream applications. In many systems, humid air can present problems to sensitive equipment and sensors. As the humid air cools, small water drops condense and can disrupt components that need to be kept dry. Fibrous nonwoven filter media are commonly used to coalesce small drops into larger drops for easier removal. The coalescing performance of a medium is dependent upon several parameters including permeability, porosity, and wettability. In many coalescing filters, glass fibers are used. In this work, the properties of steel fiber media are measured to see how these properties compare to glass fiber media. Steel fiber media has different permeability, porosity and wettability to oil and water than fiber glass media. These differences can impact coalescence performance. The impact of these differences in properties on coalescence filtration performance was evaluated in a coalescence test apparatus. The overall coalescence performance of the steel and glass nonwoven fiber media are compared using a filtration efficiency and filtration index. In many cases, the stainless steel media performed comparably to fiber glass media with efficiencies near 90%. Since stainless steel media had lower pressure drops than fiber glass media, its filtration index values were significantly higher. Broader impact of this work is the use of stainless steel fiber media as an alternative to fiber glass media in applications where aerosol filtration is needed to protect the environment or sensitive equipment and sensors.

Bayesian analysis of time-series data under case-crossover designs: posterior equivalence and inference.

PubMed

Li, Shi; Mukherjee, Bhramar; Batterman, Stuart; Ghosh, Malay

2013-12-01

Case-crossover designs are widely used to study short-term exposure effects on the risk of acute adverse health events. While the frequentist literature on this topic is vast, there is no Bayesian work in this general area. The contribution of this paper is twofold. First, the paper establishes Bayesian equivalence results that require characterization of the set of priors under which the posterior distributions of the risk ratio parameters based on a case-crossover and time-series analysis are identical. Second, the paper studies inferential issues under case-crossover designs in a Bayesian framework. Traditionally, a conditional logistic regression is used for inference on risk-ratio parameters in case-crossover studies. We consider instead a more general full likelihood-based approach which makes less restrictive assumptions on the risk functions. Formulation of a full likelihood leads to growth in the number of parameters proportional to the sample size. We propose a semi-parametric Bayesian approach using a Dirichlet process prior to handle the random nuisance parameters that appear in a full likelihood formulation. We carry out a simulation study to compare the Bayesian methods based on full and conditional likelihood with the standard frequentist approaches for case-crossover and time-series analysis. The proposed methods are illustrated through the Detroit Asthma Morbidity, Air Quality and Traffic study, which examines the association between acute asthma risk and ambient air pollutant concentrations. © 2013, The International Biometric Society.

Determination of the coalescence temperature of latexes by environmental scanning electron microscopy.

PubMed

Gonzalez, Edurne; Tollan, Christopher; Chuvilin, Andrey; Barandiaran, Maria J; Paulis, Maria

2012-08-01

A new methodology for quantitative characterization of the coalescence process of waterborne polymer dispersion (latex) particles by environmental scanning electron microscopy (ESEM) is proposed. The experimental setup has been developed to provide reproducible latex monolayer depositions, optimized contrast of the latex particles, and a reliable readout of the sample temperature. Quantification of the coalescence process under dry conditions has been performed by image processing based on evaluation of the image autocorrelation function. As a proof of concept the coalescence of two latexes with known and differing glass transition temperatures has been measured. It has been shown that a reproducibility of better than 1.5 °C can be obtained for the measurement of the coalescence temperature.

Bubble coalescence in a Newtonian fluid

NASA Astrophysics Data System (ADS)

Garg, Vishrut; Basaran, Osman

2017-11-01

Bubble coalescence plays a central role in the hydrodynamics of gas-liquid systems such as bubble column reactors, spargers, and foams. Two bubbles approaching each other at velocity V coalesce when the thin film between them ruptures, which is often the rate-limiting step. Experimental studies of this system are difficult, and recent works provide conflicting results on the effect of V on coalescence times. We simulate the head-on approach of two bubbles of equal radii R in an incompressible Newtonian fluid (density ρ, viscosity μ, and surface tension σ) by solving numerically the free boundary problem comprised of the Navier Stokes and continuity equations. Simulations are made challenging by the existence of highly disparate lengthscales, i.e. film thickness and drop radii, which are resolved by using the method of elliptic mesh generation. For a given liquid, the bubbles are shown to coalesce for all velocities below a critical value. The effects of Ohnesorge number Oh = μ /√{ ρσR } on coalescence time and critical velocity are also investigated.

Gene tree rooting methods give distributions that mimic the coalescent process.

PubMed

Tian, Yuan; Kubatko, Laura S

2014-01-01

Multi-locus phylogenetic inference is commonly carried out via models that incorporate the coalescent process to model the possibility that incomplete lineage sorting leads to incongruence between gene trees and the species tree. An interesting question that arises in this context is whether data "fit" the coalescent model. Previous work (Rosenfeld et al., 2012) has suggested that rooting of gene trees may account for variation in empirical data that has been previously attributed to the coalescent process. We examine this possibility using simulated data. We show that, in the case of four taxa, the distribution of gene trees observed from rooting estimated gene trees with either the molecular clock or with outgroup rooting can be closely matched by the distribution predicted by the coalescent model with specific choices of species tree branch lengths. We apply commonly-used coalescent-based methods of species tree inference to assess their performance in these situations. Copyright © 2013 Elsevier Inc. All rights reserved.

Pareto genealogies arising from a Poisson branching evolution model with selection.

PubMed

Huillet, Thierry E

2014-02-01

We study a class of coalescents derived from a sampling procedure out of N i.i.d. Pareto(α) random variables, normalized by their sum, including β-size-biasing on total length effects (β < α). Depending on the range of α we derive the large N limit coalescents structure, leading either to a discrete-time Poisson-Dirichlet (α, -β) Ξ-coalescent (α ε[0, 1)), or to a family of continuous-time Beta (2 - α, α - β)Λ-coalescents (α ε[1, 2)), or to the Kingman coalescent (α ≥ 2). We indicate that this class of coalescent processes (and their scaling limits) may be viewed as the genealogical processes of some forward in time evolving branching population models including selection effects. In such constant-size population models, the reproduction step, which is based on a fitness-dependent Poisson Point Process with scaling power-law(α) intensity, is coupled to a selection step consisting of sorting out the N fittest individuals issued from the reproduction step.

Minimal-assumption inference from population-genomic data

NASA Astrophysics Data System (ADS)

Weissman, Daniel; Hallatschek, Oskar

Samples of multiple complete genome sequences contain vast amounts of information about the evolutionary history of populations, much of it in the associations among polymorphisms at different loci. Current methods that take advantage of this linkage information rely on models of recombination and coalescence, limiting the sample sizes and populations that they can analyze. We introduce a method, Minimal-Assumption Genomic Inference of Coalescence (MAGIC), that reconstructs key features of the evolutionary history, including the distribution of coalescence times, by integrating information across genomic length scales without using an explicit model of recombination, demography or selection. Using simulated data, we show that MAGIC's performance is comparable to PSMC' on single diploid samples generated with standard coalescent and recombination models. More importantly, MAGIC can also analyze arbitrarily large samples and is robust to changes in the coalescent and recombination processes. Using MAGIC, we show that the inferred coalescence time histories of samples of multiple human genomes exhibit inconsistencies with a description in terms of an effective population size based on single-genome data.

Liquid Marble Coalescence and Triggered Microreaction Driven by Acoustic Levitation.

PubMed

Chen, Zhen; Zang, Duyang; Zhao, Liang; Qu, Mengfei; Li, Xu; Li, Xiaoguang; Li, Lixin; Geng, Xingguo

2017-06-27

Liquid marbles show promising potential for application in the microreactor field. Control of the coalescence between two or among multiple liquid marbles is critical; however, the successful merging of two isolated marbles is difficult because of their mechanically robust particle shells. In this work, the coalescence of multiple liquid marbles was achieved via acoustic levitation. The dynamic behaviors of the liquid marbles were monitored by a high-speed camera. Driven by the sound field, the liquid marbles moved toward each other, collided, and eventually coalesced into a larger single marble. The underlying mechanisms of this process were probed via sound field simulation and acoustic radiation pressure calculation. The results indicated that the pressure gradient on the liquid marble surface favors the formation of a liquid bridge between the liquid marbles, resulting in their coalescence. A preliminary indicator reaction was induced by the coalescence of dual liquid marbles, which suggests that expected chemical reactions can be successfully triggered with multiple reagents contained in isolated liquid marbles via acoustic levitation.

The roles of history and ecology in chloroplast phylogeographic patterns of the bird-dispersed plant parasite Phoradendron californicum (Viscaceae) in the Sonoran Desert.

PubMed

Lira-Noriega, Andrés; Toro-Núñez, Oscar; Oaks, Jamie R; Mort, Mark E

2015-01-01

• A recurrent explanation for phylogeographic discontinuities in the Baja California Peninsula and the Sonoran Desert Region has been the association of vicariant events with Pliocene and Pleistocene seaway breaks. Nevertheless, despite its relevance for plant dispersal, other explanations such as ecological and paleoclimatic factors have received little attention. Here, we analyzed the role of several of these factors to describe the phylogeographic patterns of the desert mistletoe, Phoradendron californicum.• Using noncoding chloroplast regions, we assess the marginal probability of 19 a priori hypotheses related to geological and ecological factors to predict the cpDNA variation in P. californicum using a Bayesian coalescent framework. Complementarily, we used the macrofossil record and niche model projections on Last Glacial Maximum climatic conditions for hosts, mistletoe, and a bird specialist to interpret phylogeographic patterns.• Genealogical reconstructions revealed five clades, which suggest a combination of cryptic divergence, long-distance seed dispersal, and isolating postdivergence events. Bayesian hypothesis test favored a series of Pliocene and Pleistocene geological events related to the formation of the Baja California Peninsula and seaways across the peninsula as the most supported explanation for this genealogical pattern. However, age estimates, niche projections, and fossil records show dynamic host-mistletoe interactions and evidence of host races, indicating that ecological and geological factors have been interacting during the formation and structuring of phylogeographic divergence.• Variation in cpDNA across the species range results from the interplay of vicariant events, past climatic oscillations, and more dynamic factors related to ecological processes at finer temporal and spatial scales. © 2015 Botanical Society of America, Inc.

The conquering of North America: dated phylogenetic and biogeographic inference of migratory behavior in bee hummingbirds.

PubMed

Licona-Vera, Yuyini; Ornelas, Juan Francisco

2017-06-05

Geographical and temporal patterns of diversification in bee hummingbirds (Mellisugini) were assessed with respect to the evolution of migration, critical for colonization of North America. We generated a dated multilocus phylogeny of the Mellisugini based on a dense sampling using Bayesian inference, maximum-likelihood and maximum parsimony methods, and reconstructed the ancestral states of distributional areas in a Bayesian framework and migratory behavior using maximum parsimony, maximum-likelihood and re-rooting methods. All phylogenetic analyses confirmed monophyly of the Mellisugini and the inclusion of Atthis, Calothorax, Doricha, Eulidia, Mellisuga, Microstilbon, Myrmia, Tilmatura, and Thaumastura. Mellisugini consists of two clades: (1) South American species (including Tilmatura dupontii), and (2) species distributed in North and Central America and the Caribbean islands. The second clade consists of four subclades: Mexican (Calothorax, Doricha) and Caribbean (Archilochus, Calliphlox, Mellisuga) sheartails, Calypte, and Selasphorus (incl. Atthis). Coalescent-based dating places the origin of the Mellisugini in the mid-to-late Miocene, with crown ages of most subclades in the early Pliocene, and subsequent species splits in the Pleistocene. Bee hummingbirds reached western North America by the end of the Miocene and the ancestral mellisuginid (bee hummingbirds) was reconstructed as sedentary, with four independent gains of migratory behavior during the evolution of the Mellisugini. Early colonization of North America and subsequent evolution of migration best explained biogeographic and diversification patterns within the Mellisugini. The repeated evolution of long-distance migration by different lineages was critical for the colonization of North America, contributing to the radiation of bee hummingbirds. Comparative phylogeography is needed to test whether the repeated evolution of migration resulted from northward expansion of southern sedentary populations.

The Bayesian approach to reporting GSR analysis results: some first-hand experiences

NASA Astrophysics Data System (ADS)

Charles, Sebastien; Nys, Bart

2010-06-01

The use of Bayesian principles in the reporting of forensic findings has been a matter of interest for some years. Recently, also the GSR community is gradually exploring the advantages of this method, or rather approach, for writing reports. Since last year, our GSR group is adapting reporting procedures to the use of Bayesian principles. The police and magistrates find the reports more directly accessible and useful in their part of the criminal investigation. In the lab we find that, through applying the Bayesian principles, unnecessary analyses can be eliminated and thus time can be freed on the instruments.

Bayesian Analysis of Multidimensional Item Response Theory Models: A Discussion and Illustration of Three Response Style Models

ERIC Educational Resources Information Center

Leventhal, Brian C.; Stone, Clement A.

2018-01-01

Interest in Bayesian analysis of item response theory (IRT) models has grown tremendously due to the appeal of the paradigm among psychometricians, advantages of these methods when analyzing complex models, and availability of general-purpose software. Possible models include models which reflect multidimensionality due to designed test structure,…

Symptoms of Depression and Challenging Behaviours in People with Intellectual Disability: A Bayesian Analysis. Brief Report

ERIC Educational Resources Information Center

Tsiouris, John; Mann, Rachel; Patti, Paul; Sturmey, Peter

2004-01-01

Clinicians need to know the likelihood of a condition given a positive or negative diagnostic test. In this study a Bayesian analysis of the Clinical Behavior Checklist for Persons with Intellectual Disabilities (CBCPID) to predict depression in people with intellectual disability was conducted. The CBCPID was administered to 92 adults with…

Bayesian analysis of heterogeneous treatment effects for patient-centered outcomes research.

PubMed

Henderson, Nicholas C; Louis, Thomas A; Wang, Chenguang; Varadhan, Ravi

2016-01-01

Evaluation of heterogeneity of treatment effect (HTE) is an essential aspect of personalized medicine and patient-centered outcomes research. Our goal in this article is to promote the use of Bayesian methods for subgroup analysis and to lower the barriers to their implementation by describing the ways in which the companion software beanz can facilitate these types of analyses. To advance this goal, we describe several key Bayesian models for investigating HTE and outline the ways in which they are well-suited to address many of the commonly cited challenges in the study of HTE. Topics highlighted include shrinkage estimation, model choice, sensitivity analysis, and posterior predictive checking. A case study is presented in which we demonstrate the use of the methods discussed.

Enhancements of Bayesian Blocks; Application to Large Light Curve Databases

NASA Technical Reports Server (NTRS)

Scargle, Jeff

2015-01-01

Bayesian Blocks are optimal piecewise linear representations (step function fits) of light-curves. The simple algorithm implementing this idea, using dynamic programming, has been extended to include more data modes and fitness metrics, multivariate analysis, and data on the circle (Studies in Astronomical Time Series Analysis. VI. Bayesian Block Representations, Scargle, Norris, Jackson and Chiang 2013, ApJ, 764, 167), as well as new results on background subtraction and refinement of the procedure for precise timing of transient events in sparse data. Example demonstrations will include exploratory analysis of the Kepler light curve archive in a search for "star-tickling" signals from extraterrestrial civilizations. (The Cepheid Galactic Internet, Learned, Kudritzki, Pakvasa1, and Zee, 2008, arXiv: 0809.0339; Walkowicz et al., in progress).

Estimating size and scope economies in the Portuguese water sector using the Bayesian stochastic frontier analysis.

PubMed

Carvalho, Pedro; Marques, Rui Cunha

2016-02-15

This study aims to search for economies of size and scope in the Portuguese water sector applying Bayesian and classical statistics to make inference in stochastic frontier analysis (SFA). This study proves the usefulness and advantages of the application of Bayesian statistics for making inference in SFA over traditional SFA which just uses classical statistics. The resulting Bayesian methods allow overcoming some problems that arise in the application of the traditional SFA, such as the bias in small samples and skewness of residuals. In the present case study of the water sector in Portugal, these Bayesian methods provide more plausible and acceptable results. Based on the results obtained we found that there are important economies of output density, economies of size, economies of vertical integration and economies of scope in the Portuguese water sector, pointing out to the huge advantages in undertaking mergers by joining the retail and wholesale components and by joining the drinking water and wastewater services. Copyright © 2015 Elsevier B.V. All rights reserved.

Mass Transfer And Hydraulic Testing Of The V-05 And V-10 Contactors With The Next Generation Solvent

DOE Office of Scientific and Technical Information (OSTI.GOV)

Herman, D. T.; Duignan, M. R.; Williams, M. R.

The Modular Caustic Side Solvent Extraction (CSSX) Unit (MCU) facility is actively pursuing the transition from the current BOBCalixC6 based solvent to the Next Generation Solvent (NGS)-MCU solvent. To support this integration of NGS into the MCU facilities, Savannah River Remediation (SRR) requested that Savannah River National Laboratory (SRNL) perform testing of a blend of the NGS (MaxCalix based solvent) with the current solvent (BOBCalixC6 based solvent) for the removal of cesium (Cs) from the liquid salt waste stream. This testing differs from prior testing by utilizing a blend of BOBCalixC6 based solvent and the NGS with the full (0.05more » M) concentration of the MaxCalix as well as a new suppressor, tris(3,7dimethyloctyl) guanidine. Single stage tests were conducted using the full size V-05 and V-10 centrifugal contactors installed at SRNL. These tests were designed to determine the mass transfer and hydraulic characteristics with the NGS solvent blended with the projected heel of the BOBCalixC6 based solvent that will exist in MCU at time of transition. The test program evaluated the amount of organic carryover and the droplet size of the organic carryover phases using several analytical methods. Stage efficiency and mass distribution ratios were determined by measuring Cs concentration in the aqueous and organic phases during single contactor testing. The nominal cesium distribution ratio, D(Cs) measured for extraction ranged from 37-60. The data showed greater than 96% stage efficiency for extraction. No significant differences were noted for operations at 4, 8 or 12 gpm aqueous salt simulant feed flow rates. The first scrub test (contact with weak caustic solution) yielded average scrub D(Cs) values of 3.3 to 5.2 and the second scrub test produced an average value of 1.8 to 2.3. For stripping behavior, the “first stage” D Cs) values ranged from 0.04 to 0.08. The efficiency of the low flow (0.27 gpm aqueous) was calculated to be 82.7%. The Spreadsheet Algorithm for Stagewise Solvent Extraction (SASSE) predicted equivalent DF for MCU from this testing is greater than 3,500 assuming 95% efficiency during extraction and 80% efficiency during scrub and strip. Hydraulically, the system performed very well in all tests. Target flows were easily obtained and stable throughout testing. Though some issues were encountered with plugging in the coalescer, they were not related to the solvent. No hydraulic upsets due to the solvent were experienced during any of the tests conducted. The first extraction coalescer element used in testing developed high pressure drop that made it difficult to maintain the target flow rates. Analysis showed an accumulation of sodium aluminosilicate solids. The coalescer was replaced with one from the same manufacturer’s lot and pressure drop was no longer an issue. Concentrations of Isopar™ L and Modifier were measured using semi-volatile organic analysis (SVOA) and high performance liquid chromatography (HPLC) to determine the amount of solvent carryover. For low-flow (0.27 gpm aqueous) conditions in stripping, SVOA measured the Isopar™ L post-contactor concentration to be 25 mg/L, HPLC measured 39 mg/L of Modifier. For moderate-flow (0.54 gpm aqueous) conditions, SVOA measured the Isopar™ L postcontactor to be ~69 mg/L, while the HPLC measured 56 mg/L for Modifier. For high-flow (0.8 gpm aqueous) conditions, SVOA measured the Isopar™ L post-contactor to be 39 mg/L. The post-coalescer (pre-decanter) measurements by SVOA for Isopar™ L were all less than the analysis detection limit of 10 mg/L. The HPLC measured 18, 22 and 20 mg/L Modifier for the low, medium, and high-low rates respectively. In extraction, the quantity of pre-coalescer Isopar™ L carryover measured by SVOA was ~280-410 mg/L at low flow (4 gpm aqueous), ~400-450 mg/L at moderate flow (8 gpm aqueous), and ~480 mg/L at high flow (12 gpm aqueous). The amount of post coalescer (pre-decanter) Isopar™ L carryover measured by SVOA was less than 45 mg/L for all flow rates. HPLC results for Modifier were 182, 217 and 222 mg/L for the post-contactor low, medium and high flow rates. The post-coalescer (pre-decanter) samples were measured to contain 12, 10 and 22 mg/L Modifier for the low, medium, and high flow rates. The carryover results and droplet size measurements were used to determine the decanter performance utilizing the decanter model developed by the ARES Corporation. Results show for the targeted salt flow rate of approximately 8 gpm, that over 93% of the solvent carryover from stripping is predicted to be recovered and over 96% solvent carryover from extraction is predicted to be recovered. This translates to a predicted solvent carryover of <3 ppm from stripping and <20 ppm solvent carryover from extraction. This projected performance at MCU is expected to be well within the operating limits and the historical performance for the baseline BOBCalixC6 based solvent. Droplet-size data obtained by MicroTrac™ S3400 analyzer consistently shows that the droplet size post-oalescer is significantly greater than the post-contactor or pre-coalescer samples. Increased flow rates did not show a consistent impact to the droplet size results. For the extraction testing, droplet size analysis showed that the post-contactor and pre-coalescer samples were essentially the same. The mean droplet sizes post-coalescer were less than the mean droplet sizes pre-coalescer with a very slight upward trend in the mean droplet size as the flow rate was increased. This result is probably due to the method of sampling. The larger post-coalescer drops immediately rise to the surface after leaving the coalescer element. The downstream sampling point was horizontally in-line with the element and therefore would only capture those organic droplets well mixed in the flowing aqueous stream.« less

Efficient Bayesian hierarchical functional data analysis with basis function approximations using Gaussian-Wishart processes.

PubMed

Yang, Jingjing; Cox, Dennis D; Lee, Jong Soo; Ren, Peng; Choi, Taeryon

2017-12-01

Functional data are defined as realizations of random functions (mostly smooth functions) varying over a continuum, which are usually collected on discretized grids with measurement errors. In order to accurately smooth noisy functional observations and deal with the issue of high-dimensional observation grids, we propose a novel Bayesian method based on the Bayesian hierarchical model with a Gaussian-Wishart process prior and basis function representations. We first derive an induced model for the basis-function coefficients of the functional data, and then use this model to conduct posterior inference through Markov chain Monte Carlo methods. Compared to the standard Bayesian inference that suffers serious computational burden and instability in analyzing high-dimensional functional data, our method greatly improves the computational scalability and stability, while inheriting the advantage of simultaneously smoothing raw observations and estimating the mean-covariance functions in a nonparametric way. In addition, our method can naturally handle functional data observed on random or uncommon grids. Simulation and real studies demonstrate that our method produces similar results to those obtainable by the standard Bayesian inference with low-dimensional common grids, while efficiently smoothing and estimating functional data with random and high-dimensional observation grids when the standard Bayesian inference fails. In conclusion, our method can efficiently smooth and estimate high-dimensional functional data, providing one way to resolve the curse of dimensionality for Bayesian functional data analysis with Gaussian-Wishart processes. © 2017, The International Biometric Society.

Void growth and coalescence in irradiated copper under deformation

NASA Astrophysics Data System (ADS)

Barrioz, P. O.; Hure, J.; Tanguy, B.

2018-04-01

A decrease of fracture toughness of irradiated materials is usually observed, as reported for austenitic stainless steels in Light Water Reactors (LWRs) or copper alloys for fusion applications. For a wide range of applications (e.g. structural steels irradiated at low homologous temperature), void growth and coalescence fracture mechanism has been shown to be still predominant. As a consequence, a comprehensive study of the effects of irradiation-induced hardening mechanisms on void growth and coalescence in irradiated materials is required. The effects of irradiation on ductile fracture mechanisms - void growth to coalescence - are assessed in this study based on model experiments. Pure copper thin tensile samples have been irradiated with protons up to 0.01 dpa. Micron-scale holes drilled through the thickness of these samples subjected to uniaxial loading conditions allow a detailed description of void growth and coalescence. In this study, experimental data show that physical mechanisms of micron-scale void growth and coalescence are similar between the unirradiated and irradiated copper. However, an acceleration of void growth is observed in the later case, resulting in earlier coalescence, which is consistent with the decrease of fracture toughness reported in irradiated materials. These results are qualitatively reproduced with numerical simulations accounting for irradiation macroscopic hardening and decrease of strain-hardening capability.

Inhibition of bubble coalescence: effects of salt concentration and speed of approach.

PubMed

Del Castillo, Lorena A; Ohnishi, Satomi; Horn, Roger G

2011-04-01

Bubble coalescence experiments have been performed using a sliding bubble apparatus, in which mm-sized bubbles in an aqueous electrolyte solution without added surfactant rose toward an air meniscus at different speeds obtained by varying the inclination of a closed glass cylinder containing the liquid. The coalescence times of single bubbles contacting the meniscus were monitored using a high speed camera. Results clearly show that stability against coalescence of colliding air bubbles is influenced by both the salt concentration and the approach speed of the bubbles. Contrary to the widespread belief that bubbles in pure water are unstable, we demonstrate that bubbles formed in highly purified water and colliding with the meniscus at very slow approach speeds can survive for minutes or even hours. At higher speeds, bubbles in water only survive for a few seconds, and at still higher speeds they coalesce instantly. Addition of a simple electrolyte (KCl) removes the low-speed stability and shifts the transition between transient stability and instant coalescence to higher approach speeds. At high electrolyte concentration no bubbles were observed to coalesce instantly. These observations are consistent with recent results of Yaminsky et al. (Langmuir 26 (2010) 8061) and the transitions between different regions of behavior are in semi-quantitative agreement with Yaminsky's model. Copyright © 2010 Elsevier Inc. All rights reserved.

A Three-Stage Mechanistic Model for Solidification Cracking During Welding of Steel

NASA Astrophysics Data System (ADS)

Aucott, L.; Huang, D.; Dong, H. B.; Wen, S. W.; Marsden, J.; Rack, A.; Cocks, A. C. F.

2018-03-01

A three-stage mechanistic model for solidification cracking during TIG welding of steel is proposed from in situ synchrotron X-ray imaging of solidification cracking and subsequent analysis of fracture surfaces. Stage 1—Nucleation of inter-granular hot cracks: cracks nucleate inter-granularly in sub-surface where maximum volumetric strain is localized and volume fraction of liquid is less than 0.1; the crack nuclei occur at solute-enriched liquid pockets which remain trapped in increasingly impermeable semi-solid skeleton. Stage 2—Coalescence of cracks via inter-granular fracture: as the applied strain increases, cracks coalesce through inter-granular fracture; the coalescence path is preferential to the direction of the heat source and propagates through the grain boundaries to solidifying dendrites. Stage 3—Propagation through inter-dendritic hot tearing: inter-dendritic hot tearing occurs along the boundaries between solidifying columnar dendrites with higher liquid fraction. It is recommended that future solidification cracking criterion shall be based on the application of multiphase mechanics and fracture mechanics to the failure of semi-solid materials.

Bayesian Group Bridge for Bi-level Variable Selection.

PubMed

Mallick, Himel; Yi, Nengjun

2017-06-01

A Bayesian bi-level variable selection method (BAGB: Bayesian Analysis of Group Bridge) is developed for regularized regression and classification. This new development is motivated by grouped data, where generic variables can be divided into multiple groups, with variables in the same group being mechanistically related or statistically correlated. As an alternative to frequentist group variable selection methods, BAGB incorporates structural information among predictors through a group-wise shrinkage prior. Posterior computation proceeds via an efficient MCMC algorithm. In addition to the usual ease-of-interpretation of hierarchical linear models, the Bayesian formulation produces valid standard errors, a feature that is notably absent in the frequentist framework. Empirical evidence of the attractiveness of the method is illustrated by extensive Monte Carlo simulations and real data analysis. Finally, several extensions of this new approach are presented, providing a unified framework for bi-level variable selection in general models with flexible penalties.

Bayesian analysis of CCDM models

NASA Astrophysics Data System (ADS)

Jesus, J. F.; Valentim, R.; Andrade-Oliveira, F.

2017-09-01

Creation of Cold Dark Matter (CCDM), in the context of Einstein Field Equations, produces a negative pressure term which can be used to explain the accelerated expansion of the Universe. In this work we tested six different spatially flat models for matter creation using statistical criteria, in light of SNe Ia data: Akaike Information Criterion (AIC), Bayesian Information Criterion (BIC) and Bayesian Evidence (BE). These criteria allow to compare models considering goodness of fit and number of free parameters, penalizing excess of complexity. We find that JO model is slightly favoured over LJO/ΛCDM model, however, neither of these, nor Γ = 3αH0 model can be discarded from the current analysis. Three other scenarios are discarded either because poor fitting or because of the excess of free parameters. A method of increasing Bayesian evidence through reparameterization in order to reducing parameter degeneracy is also developed.

Alveolar ridge preservation after tooth extraction: a Bayesian Network meta-analysis of grafting materials efficacy on prevention of bone height and width reduction.

PubMed

Iocca, Oreste; Farcomeni, Alessio; Pardiñas Lopez, Simon; Talib, Huzefa S

2017-01-01

To conduct a traditional meta-analysis and a Bayesian Network meta-analysis to synthesize the information coming from randomized controlled trials on different socket grafting materials and combine the resulting indirect evidence in order to make inferences on treatments that have not been compared directly. RCTs were identified for inclusion in the systematic review and subsequent statistical analysis. Bone height and width remodelling were selected as the chosen summary measures for comparison. First, a series of pairwise meta-analyses were performed and overall mean difference (MD) in mm with 95% CI was calculated between grafted versus non-grafted sockets. Then, a Bayesian Network meta-analysis was performed to draw indirect conclusions on which grafting materials can be considered most likely the best compared to the others. From the six included studies, seven comparisons were obtained. Traditional meta-analysis showed statistically significant results in favour of grafting the socket compared to no-graft both for height (MD 1.02, 95% CI 0.44-1.59, p value < 0.001) than for width (MD 1.52 95% CI 1.18-1.86, p value <0.000001) remodelling. Bayesian Network meta-analysis allowed to obtain a rank of intervention efficacy. On the basis of the results of the present analysis, socket grafting seems to be more favourable than unassisted socket healing. Moreover, Bayesian Network meta-analysis indicates that freeze-dried bone graft plus membrane is the most likely effective in the reduction of bone height remodelling. Autologous bone marrow resulted the most likely effective when width remodelling was considered. Studies with larger samples and less risk of bias should be conducted in the future in order to further strengthen the results of this analysis. © 2016 John Wiley & Sons A/S. Published by John Wiley & Sons Ltd.

A Bayesian Analysis of a Randomized Clinical Trial Comparing Antimetabolite Therapies for Non-Infectious Uveitis.

PubMed

Browne, Erica N; Rathinam, Sivakumar R; Kanakath, Anuradha; Thundikandy, Radhika; Babu, Manohar; Lietman, Thomas M; Acharya, Nisha R

2017-02-01

To conduct a Bayesian analysis of a randomized clinical trial (RCT) for non-infectious uveitis using expert opinion as a subjective prior belief. A RCT was conducted to determine which antimetabolite, methotrexate or mycophenolate mofetil, is more effective as an initial corticosteroid-sparing agent for the treatment of intermediate, posterior, and pan-uveitis. Before the release of trial results, expert opinion on the relative effectiveness of these two medications was collected via online survey. Members of the American Uveitis Society executive committee were invited to provide an estimate for the relative decrease in efficacy with a 95% credible interval (CrI). A prior probability distribution was created from experts' estimates. A Bayesian analysis was performed using the constructed expert prior probability distribution and the trial's primary outcome. A total of 11 of the 12 invited uveitis specialists provided estimates. Eight of 11 experts (73%) believed mycophenolate mofetil is more effective. The group prior belief was that the odds of treatment success for patients taking mycophenolate mofetil were 1.4-fold the odds of those taking methotrexate (95% CrI 0.03-45.0). The odds of treatment success with mycophenolate mofetil compared to methotrexate was 0.4 from the RCT (95% confidence interval 0.1-1.2) and 0.7 (95% CrI 0.2-1.7) from the Bayesian analysis. A Bayesian analysis combining expert belief with the trial's result did not indicate preference for one drug. However, the wide credible interval leaves open the possibility of a substantial treatment effect. This suggests clinical equipoise necessary to allow a larger, more definitive RCT.

Kinetic aspects of emulsion stabilization by surfactants: a microfluidic analysis.

PubMed

Baret, Jean-Christophe; Kleinschmidt, Felix; El Harrak, Abdeslam; Griffiths, Andrew D

2009-06-02

In classical emulsification processes, surfactants play two roles: first, they reduce the interfacial tension, facilitating droplet deformation and rupture, and second, they reduce droplet coalescence. Here, we use a microfluidic emulsification system to completely uncouple these two processes, allowing stabilization against coalescence to be studied quantitatively and independently of droplet formation. We demonstrate that, in addition to the classical effect of stabilization by an increase of surfactant concentration, the dynamics of adsorption of surfactant at the water-oil interface is a key element for droplet stabilization. Microfluidic emulsification devices can therefore be tailored to improve emulsification while decreasing the concentration of surfactant by increasing the time before the droplets first come into contact.

Impacts of Non-Divergence-Free Flows on the Coalescence of Initially Distant Buoyant Scalars on a Turbulent Free Surface

NASA Astrophysics Data System (ADS)

Pratt, K.; Crimaldi, J. P.

2016-02-01

Lagrangian Coherent Structures (LCS) have been shown to play a predictive role in the coalescence of initially distant scalars in incompressible flows. Buoyant scalars on the free surface of a 3D incompressible turbulent fluid, however, are advected by a 2D compressible velocity field, resulting in scalar distributions that differ from those seen in a 2D incompressible flow. Our research uses both numerical and experimental approaches to investigate the coalescence of two initially distant reactive scalars to infer the impact of non-divergence-free behavior on buoyant scalar coalescence. Preliminary numerical results, utilizing incompressible and compressible chaotic 2D models, indicate that non-divergence-free behavior increases the likelihood of scalar coalescence and therefore enhances any interactions or reactions between the scalars. In addition, the shape and distribution of LCS is altered in compressible flows, which may explain the increased likelihood of scalar coalescence. Experimentally, we have constructed a 60 X 60 X 60 cm tank that generates three-dimensional turbulence via random pulsing of 36 jets on the tank bottom. Buoyant fluorescent red and green particles are used to quantify coalescence. Through the addition of a thin surfactant film on the free surface, results for incompressible flow cases are also obtained and directly compared to the compressible results. From these results, we hope to elucidate the role of free-surface flow on the coalescence of initially distant buoyant scalars, and extend these results to oceanic mixing problems, such as the transport of phytoplankton blooms and oil spills.

Bayesian Correlation Analysis for Sequence Count Data

PubMed Central

Lau, Nelson; Perkins, Theodore J.

2016-01-01

Evaluating the similarity of different measured variables is a fundamental task of statistics, and a key part of many bioinformatics algorithms. Here we propose a Bayesian scheme for estimating the correlation between different entities’ measurements based on high-throughput sequencing data. These entities could be different genes or miRNAs whose expression is measured by RNA-seq, different transcription factors or histone marks whose expression is measured by ChIP-seq, or even combinations of different types of entities. Our Bayesian formulation accounts for both measured signal levels and uncertainty in those levels, due to varying sequencing depth in different experiments and to varying absolute levels of individual entities, both of which affect the precision of the measurements. In comparison with a traditional Pearson correlation analysis, we show that our Bayesian correlation analysis retains high correlations when measurement confidence is high, but suppresses correlations when measurement confidence is low—especially for entities with low signal levels. In addition, we consider the influence of priors on the Bayesian correlation estimate. Perhaps surprisingly, we show that naive, uniform priors on entities’ signal levels can lead to highly biased correlation estimates, particularly when different experiments have widely varying sequencing depths. However, we propose two alternative priors that provably mitigate this problem. We also prove that, like traditional Pearson correlation, our Bayesian correlation calculation constitutes a kernel in the machine learning sense, and thus can be used as a similarity measure in any kernel-based machine learning algorithm. We demonstrate our approach on two RNA-seq datasets and one miRNA-seq dataset. PMID:27701449

Online Variational Bayesian Filtering-Based Mobile Target Tracking in Wireless Sensor Networks

PubMed Central

Zhou, Bingpeng; Chen, Qingchun; Li, Tiffany Jing; Xiao, Pei

2014-01-01

The received signal strength (RSS)-based online tracking for a mobile node in wireless sensor networks (WSNs) is investigated in this paper. Firstly, a multi-layer dynamic Bayesian network (MDBN) is introduced to characterize the target mobility with either directional or undirected movement. In particular, it is proposed to employ the Wishart distribution to approximate the time-varying RSS measurement precision's randomness due to the target movement. It is shown that the proposed MDBN offers a more general analysis model via incorporating the underlying statistical information of both the target movement and observations, which can be utilized to improve the online tracking capability by exploiting the Bayesian statistics. Secondly, based on the MDBN model, a mean-field variational Bayesian filtering (VBF) algorithm is developed to realize the online tracking of a mobile target in the presence of nonlinear observations and time-varying RSS precision, wherein the traditional Bayesian filtering scheme cannot be directly employed. Thirdly, a joint optimization between the real-time velocity and its prior expectation is proposed to enable online velocity tracking in the proposed online tacking scheme. Finally, the associated Bayesian Cramer–Rao Lower Bound (BCRLB) analysis and numerical simulations are conducted. Our analysis unveils that, by exploiting the potential state information via the general MDBN model, the proposed VBF algorithm provides a promising solution to the online tracking of a mobile node in WSNs. In addition, it is shown that the final tracking accuracy linearly scales with its expectation when the RSS measurement precision is time-varying. PMID:25393784

Model-based Bayesian inference for ROC data analysis

NASA Astrophysics Data System (ADS)

Lei, Tianhu; Bae, K. Ty

2013-03-01

This paper presents a study of model-based Bayesian inference to Receiver Operating Characteristics (ROC) data. The model is a simple version of general non-linear regression model. Different from Dorfman model, it uses a probit link function with a covariate variable having zero-one two values to express binormal distributions in a single formula. Model also includes a scale parameter. Bayesian inference is implemented by Markov Chain Monte Carlo (MCMC) method carried out by Bayesian analysis Using Gibbs Sampling (BUGS). Contrast to the classical statistical theory, Bayesian approach considers model parameters as random variables characterized by prior distributions. With substantial amount of simulated samples generated by sampling algorithm, posterior distributions of parameters as well as parameters themselves can be accurately estimated. MCMC-based BUGS adopts Adaptive Rejection Sampling (ARS) protocol which requires the probability density function (pdf) which samples are drawing from be log concave with respect to the targeted parameters. Our study corrects a common misconception and proves that pdf of this regression model is log concave with respect to its scale parameter. Therefore, ARS's requirement is satisfied and a Gaussian prior which is conjugate and possesses many analytic and computational advantages is assigned to the scale parameter. A cohort of 20 simulated data sets and 20 simulations from each data set are used in our study. Output analysis and convergence diagnostics for MCMC method are assessed by CODA package. Models and methods by using continuous Gaussian prior and discrete categorical prior are compared. Intensive simulations and performance measures are given to illustrate our practice in the framework of model-based Bayesian inference using MCMC method.

Systemic antibiotics in the treatment of aggressive periodontitis. A systematic review and a Bayesian Network meta-analysis.

PubMed

Rabelo, Cleverton Correa; Feres, Magda; Gonçalves, Cristiane; Figueiredo, Luciene C; Faveri, Marcelo; Tu, Yu-Kang; Chambrone, Leandro

2015-07-01

The aim of this study was to assess the effect of systemic antibiotic therapy on the treatment of aggressive periodontitis (AgP). This study was conducted and reported in accordance with the PRISMA statement. The MEDLINE, EMBASE and CENTRAL databases were searched up to June 2014 for randomized clinical trials comparing the treatment of subjects with AgP with either scaling and root planing (SRP) alone or associated with systemic antibiotics. Bayesian network meta-analysis was prepared using the Bayesian random-effects hierarchical models and the outcomes reported at 6-month post-treatment. Out of 350 papers identified, 14 studies were eligible. Greater gain in clinical attachment (CA) (mean difference [MD]: 1.08 mm; p < 0.0001) and reduction in probing depth (PD) (MD: 1.05 mm; p < 0.00001) were observed for SRP + metronidazole (Mtz), and for SRP + Mtz + amoxicillin (Amx) (MD: 0.45 mm, MD: 0.53 mm, respectively; p < 0.00001) than SRP alone/placebo. Bayesian network meta-analysis showed additional benefits in CA gain and PD reduction when SRP was associated with systemic antibiotics. SRP plus systemic antibiotics led to an additional clinical effect compared with SRP alone in the treatment of AgP. Of the antibiotic protocols available for inclusion into the Bayesian network meta-analysis, Mtz and Mtz/Amx provided to the most beneficial outcomes. © 2015 John Wiley & Sons A/S. Published by John Wiley & Sons Ltd.

Evaluating allopolyploid origins in strawberries (Fragaria) using haplotypes generated from target capture sequencing.

PubMed

Kamneva, Olga K; Syring, John; Liston, Aaron; Rosenberg, Noah A

2017-08-04

Hybridization is observed in many eukaryotic lineages and can lead to the formation of polyploid species. The study of hybridization and polyploidization faces challenges both in data generation and in accounting for population-level phenomena such as coalescence processes in phylogenetic analysis. Genus Fragaria is one example of a set of plant taxa in which a range of ploidy levels is observed across species, but phylogenetic origins are unknown. Here, using 20 diploid and polyploid Fragaria species, we combine approaches from NGS data analysis and phylogenetics to infer evolutionary origins of polyploid strawberries, taking into account coalescence processes. We generate haplotype sequences for 257 low-copy nuclear markers assembled from Illumina target capture sequence data. We then identify putative hybridization events by analyzing gene tree topologies, and further test predicted hybridizations in a coalescence framework. This approach confirms the allopolyploid ancestry of F. chiloensis and F. virginiana, and provides new allopolyploid ancestry hypotheses for F. iturupensis, F. moschata, and F. orientalis. Evidence of gene flow between diploids F. bucharica and F. vesca is also detected, suggesting that it might be appropriate to consider these groups as conspecifics. This study is one of the first in which target capture sequencing followed by computational deconvolution of individual haplotypes is used for tracing origins of polyploid taxa. The study also provides new perspectives on the evolutionary history of Fragaria.

Bayesian model reduction and empirical Bayes for group (DCM) studies.

PubMed

Friston, Karl J; Litvak, Vladimir; Oswal, Ashwini; Razi, Adeel; Stephan, Klaas E; van Wijk, Bernadette C M; Ziegler, Gabriel; Zeidman, Peter

2016-03-01

This technical note describes some Bayesian procedures for the analysis of group studies that use nonlinear models at the first (within-subject) level - e.g., dynamic causal models - and linear models at subsequent (between-subject) levels. Its focus is on using Bayesian model reduction to finesse the inversion of multiple models of a single dataset or a single (hierarchical or empirical Bayes) model of multiple datasets. These applications of Bayesian model reduction allow one to consider parametric random effects and make inferences about group effects very efficiently (in a few seconds). We provide the relatively straightforward theoretical background to these procedures and illustrate their application using a worked example. This example uses a simulated mismatch negativity study of schizophrenia. We illustrate the robustness of Bayesian model reduction to violations of the (commonly used) Laplace assumption in dynamic causal modelling and show how its recursive application can facilitate both classical and Bayesian inference about group differences. Finally, we consider the application of these empirical Bayesian procedures to classification and prediction. Copyright © 2015 The Authors. Published by Elsevier Inc. All rights reserved.

Electron acceleration via magnetic island coalescence

NASA Astrophysics Data System (ADS)

Shinohara, I.; Yumura, T.; Tanaka, K. G.; Fujimoto, M.

2009-06-01

Electron acceleration via fast magnetic island coalescence that happens as quick magnetic reconnection triggering (QMRT) proceeds has been studied. We have carried out a three-dimensional full kinetic simulation of the Harris current sheet with a large enough simulation run for two magnetic islands coalescence. Due to the strong inductive electric field associated with the non-linear evolution of the lower-hybrid-drift instability and the magnetic island coalescence process observed in the non-linear stage of the collisionless tearing mode, electrons are significantly accelerated at around the neutral sheet and the subsequent X-line. The accelerated meandering electrons generated by the non-linear evolution of the lower-hybrid-drift instability are resulted in QMRT, and QMRT leads to fast magnetic island coalescence. As a whole, the reconnection triggering and its transition to large-scale structure work as an effective electron accelerator.

Characterization of solids deposited on the modular caustic-side solvent extraction unit (MCU) coalescer media removed in May and October 2014

DOE Office of Scientific and Technical Information (OSTI.GOV)

Fondeur, F. F.

During routine maintenance, the coalescers utilized in the Modular Caustic-Side Solvent Extraction Unit (MCU) processing of Salt Batch 6 and a portion of Salt Batch 7 were sampled and submitted to the Savannah River National Laboratory (SRNL) for characterization, for the purpose of identifying solid phase constituents that may be accumulating in these coalescers. Specifically, two samples were received and characterized: A decontaminated salt solution (DSS) coalescer sample and a strip effluent (SE) coalescer sample. Aliquots of the samples were analyzed by XRD, Fourier Transform Infrared (FTIR) Spectroscopy, SEM, and EDS. Other aliquots of the samples were leached in acidmore » solution, and the leachates were analyzed by ICP-AES. In addition, modeling was performed to provide a basis for comparison of the analytical results.« less

Inference of Epidemiological Dynamics Based on Simulated Phylogenies Using Birth-Death and Coalescent Models

PubMed Central

Boskova, Veronika; Bonhoeffer, Sebastian; Stadler, Tanja

2014-01-01

Quantifying epidemiological dynamics is crucial for understanding and forecasting the spread of an epidemic. The coalescent and the birth-death model are used interchangeably to infer epidemiological parameters from the genealogical relationships of the pathogen population under study, which in turn are inferred from the pathogen genetic sequencing data. To compare the performance of these widely applied models, we performed a simulation study. We simulated phylogenetic trees under the constant rate birth-death model and the coalescent model with a deterministic exponentially growing infected population. For each tree, we re-estimated the epidemiological parameters using both a birth-death and a coalescent based method, implemented as an MCMC procedure in BEAST v2.0. In our analyses that estimate the growth rate of an epidemic based on simulated birth-death trees, the point estimates such as the maximum a posteriori/maximum likelihood estimates are not very different. However, the estimates of uncertainty are very different. The birth-death model had a higher coverage than the coalescent model, i.e. contained the true value in the highest posterior density (HPD) interval more often (2–13% vs. 31–75% error). The coverage of the coalescent decreases with decreasing basic reproductive ratio and increasing sampling probability of infecteds. We hypothesize that the biases in the coalescent are due to the assumption of deterministic rather than stochastic population size changes. Both methods performed reasonably well when analyzing trees simulated under the coalescent. The methods can also identify other key epidemiological parameters as long as one of the parameters is fixed to its true value. In summary, when using genetic data to estimate epidemic dynamics, our results suggest that the birth-death method will be less sensitive to population fluctuations of early outbreaks than the coalescent method that assumes a deterministic exponentially growing infected population. PMID:25375100

Maritime Transportation Risk Assessment of Tianjin Port with Bayesian Belief Networks.

PubMed

Zhang, Jinfen; Teixeira, Ângelo P; Guedes Soares, C; Yan, Xinping; Liu, Kezhong

2016-06-01

This article develops a Bayesian belief network model for the prediction of accident consequences in the Tianjin port. The study starts with a statistical analysis of historical accident data of six years from 2008 to 2013. Then a Bayesian belief network is constructed to express the dependencies between the indicator variables and accident consequences. The statistics and expert knowledge are synthesized in the Bayesian belief network model to obtain the probability distribution of the consequences. By a sensitivity analysis, several indicator variables that have influence on the consequences are identified, including navigational area, ship type and time of the day. The results indicate that the consequences are most sensitive to the position where the accidents occurred, followed by time of day and ship length. The results also reflect that the navigational risk of the Tianjin port is at the acceptable level, despite that there is more room of improvement. These results can be used by the Maritime Safety Administration to take effective measures to enhance maritime safety in the Tianjin port. © 2016 Society for Risk Analysis.

Risk Assessment for Mobile Systems Through a Multilayered Hierarchical Bayesian Network.

PubMed

Li, Shancang; Tryfonas, Theo; Russell, Gordon; Andriotis, Panagiotis

2016-08-01

Mobile systems are facing a number of application vulnerabilities that can be combined together and utilized to penetrate systems with devastating impact. When assessing the overall security of a mobile system, it is important to assess the security risks posed by each mobile applications (apps), thus gaining a stronger understanding of any vulnerabilities present. This paper aims at developing a three-layer framework that assesses the potential risks which apps introduce within the Android mobile systems. A Bayesian risk graphical model is proposed to evaluate risk propagation in a layered risk architecture. By integrating static analysis, dynamic analysis, and behavior analysis in a hierarchical framework, the risks and their propagation through each layer are well modeled by the Bayesian risk graph, which can quantitatively analyze risks faced to both apps and mobile systems. The proposed hierarchical Bayesian risk graph model offers a novel way to investigate the security risks in mobile environment and enables users and administrators to evaluate the potential risks. This strategy allows to strengthen both app security as well as the security of the entire system.

Embedding the results of focussed Bayesian fusion into a global context

NASA Astrophysics Data System (ADS)

Sander, Jennifer; Heizmann, Michael

2014-05-01

Bayesian statistics offers a well-founded and powerful fusion methodology also for the fusion of heterogeneous information sources. However, except in special cases, the needed posterior distribution is not analytically derivable. As consequence, Bayesian fusion may cause unacceptably high computational and storage costs in practice. Local Bayesian fusion approaches aim at reducing the complexity of the Bayesian fusion methodology significantly. This is done by concentrating the actual Bayesian fusion on the potentially most task relevant parts of the domain of the Properties of Interest. Our research on these approaches is motivated by an analogy to criminal investigations where criminalists pursue clues also only locally. This publication follows previous publications on a special local Bayesian fusion technique called focussed Bayesian fusion. Here, the actual calculation of the posterior distribution gets completely restricted to a suitably chosen local context. By this, the global posterior distribution is not completely determined. Strategies for using the results of a focussed Bayesian analysis appropriately are needed. In this publication, we primarily contrast different ways of embedding the results of focussed Bayesian fusion explicitly into a global context. To obtain a unique global posterior distribution, we analyze the application of the Maximum Entropy Principle that has been shown to be successfully applicable in metrology and in different other areas. To address the special need for making further decisions subsequently to the actual fusion task, we further analyze criteria for decision making under partial information.

Phylogeny of sipunculan worms: A combined analysis of four gene regions and morphology.

PubMed

Schulze, Anja; Cutler, Edward B; Giribet, Gonzalo

2007-01-01

The intra-phyletic relationships of sipunculan worms were analyzed based on DNA sequence data from four gene regions and 58 morphological characters. Initially we analyzed the data under direct optimization using parsimony as optimality criterion. An implied alignment resulting from the direct optimization analysis was subsequently utilized to perform a Bayesian analysis with mixed models for the different data partitions. For this we applied a doublet model for the stem regions of the 18S rRNA. Both analyses support monophyly of Sipuncula and most of the same clades within the phylum. The analyses differ with respect to the relationships among the major groups but whereas the deep nodes in the direct optimization analysis generally show low jackknife support, they are supported by 100% posterior probability in the Bayesian analysis. Direct optimization has been useful for handling sequences of unequal length and generating conservative phylogenetic hypotheses whereas the Bayesian analysis under mixed models provided high resolution in the basal nodes of the tree.

DOE Office of Scientific and Technical Information (OSTI.GOV)

Lü, B.; Münger, E. P.; Sarakinos, K.

The morphology and physical properties of thin films deposited by vapor condensation on solid surfaces are predominantly set by the processes of island nucleation, growth, and coalescence. When deposition is performed using pulsed vapor fluxes, three distinct nucleation regimes are known to exist depending on the temporal profile of the flux. These regimes can be accessed by tuning deposition conditions; however, their effect on film microstructure becomes marginal when coalescence sets in and erases morphological features obtained during nucleation. By preventing coalescence from being completed, these nucleation regimes can be used to control microstructure evolution and thus access a largermore » palette of film morphological features. Recently, we derived the quantitative criterion to stop coalescence during continuous metal vapor flux deposition on insulating surfaces—which typically yields 3-dimensional growth—by describing analytically the competition between island growth by atomic incorporation and the coalescence rate of islands [Lü et al., Appl. Phys. Lett. 105, 163107 (2014)]. Here, we develop the analytical framework for entering a coalescence-free growth regime for metal vapor deposition on insulating substrates using pulsed vapor fluxes, showing that there exist three distinct criteria for suppressing coalescence that correspond to the three nucleation regimes of pulsed vapor flux deposition. The theoretical framework developed herein is substantiated by kinetic Monte Carlo growth simulations. Our findings highlight the possibility of using atomistic nucleation theory for pulsed vapor deposition to control morphology of thin films beyond the point of island density saturation.« less

Assessment of partial coalescence in whippable oil-in-water food emulsions.

PubMed

Petrut, Raul Flaviu; Danthine, Sabine; Blecker, Christophe

2016-03-01

Partial coalescence influences to a great extent the properties of final food products such as ice cream and whipped toppings. In return, the partial coalescence occurrence and development are conditioned, in such systems, by the emulsion's intrinsic properties (e.g. solid fat content, fat crystal shape and size), formulation (e.g. protein content, surfactants presence) and extrinsic factors (e.g. cooling rate, shearing). A set of methods is available for partial coalescence investigation and quantification. These methods are critically reviewed in this paper, balancing the weaknesses of the methods in terms of structure alteration (for turbidity, dye dilution, etc.) and assumptions made for mathematical models (for particle size determination) with their advantages (good repeatability, high sensitivity, etc.). With the methods proposed in literature, the partial coalescence investigations can be conducted quantitatively and/or qualitatively. Good correlation were observed between some of the quantitative methods such as dye dilution, calorimetry, fat particle size; while a poor correlation was found in the case of solvent extraction method with other quantitative methods. The most suitable way for partial coalescence quantification was implied to be the fat particle size method, which would give results with a high degree of confidence if used in combination with a microscopic technique for the confirmation of partial coalescence as the main destabilization mechanism. Copyright © 2015 Elsevier B.V. All rights reserved.

Bayesian models: A statistical primer for ecologists

USGS Publications Warehouse

Hobbs, N. Thompson; Hooten, Mevin B.

2015-01-01

Bayesian modeling has become an indispensable tool for ecological research because it is uniquely suited to deal with complexity in a statistically coherent way. This textbook provides a comprehensive and accessible introduction to the latest Bayesian methods—in language ecologists can understand. Unlike other books on the subject, this one emphasizes the principles behind the computations, giving ecologists a big-picture understanding of how to implement this powerful statistical approach.Bayesian Models is an essential primer for non-statisticians. It begins with a definition of probability and develops a step-by-step sequence of connected ideas, including basic distribution theory, network diagrams, hierarchical models, Markov chain Monte Carlo, and inference from single and multiple models. This unique book places less emphasis on computer coding, favoring instead a concise presentation of the mathematical statistics needed to understand how and why Bayesian analysis works. It also explains how to write out properly formulated hierarchical Bayesian models and use them in computing, research papers, and proposals.This primer enables ecologists to understand the statistical principles behind Bayesian modeling and apply them to research, teaching, policy, and management.Presents the mathematical and statistical foundations of Bayesian modeling in language accessible to non-statisticiansCovers basic distribution theory, network diagrams, hierarchical models, Markov chain Monte Carlo, and moreDeemphasizes computer coding in favor of basic principlesExplains how to write out properly factored statistical expressions representing Bayesian models

Divorcing the Late Upper Palaeolithic demographic histories of mtDNA haplogroups M1 and U6 in Africa

PubMed Central

2012-01-01

Background A Southwest Asian origin and dispersal to North Africa in the Early Upper Palaeolithic era has been inferred in previous studies for mtDNA haplogroups M1 and U6. Both haplogroups have been proposed to show similar geographic patterns and shared demographic histories. Results We report here 24 M1 and 33 U6 new complete mtDNA sequences that allow us to refine the existing phylogeny of these haplogroups. The resulting phylogenetic information was used to genotype a further 131 M1 and 91 U6 samples to determine the geographic spread of their sub-clades. No southwest Asian specific clades for M1 or U6 were discovered. U6 and M1 frequencies in North Africa, the Middle East and Europe do not follow similar patterns, and their sub-clade divisions do not appear to be compatible with their shared history reaching back to the Early Upper Palaeolithic. The Bayesian Skyline Plots testify to non-overlapping phases of expansion, and the haplogroups’ phylogenies suggest that there are U6 sub-clades that expanded earlier than those in M1. Some M1 and U6 sub-clades could be linked with certain events. For example, U6a1 and M1b, with their coalescent ages of ~20,000–22,000 years ago and earliest inferred expansion in northwest Africa, could coincide with the flourishing of the Iberomaurusian industry, whilst U6b and M1b1 appeared at the time of the Capsian culture. Conclusions Our high-resolution phylogenetic dissection of both haplogroups and coalescent time assessments suggest that the extant main branching pattern of both haplogroups arose and diversified in the mid-later Upper Palaeolithic, with some sub-clades concomitantly with the expansion of the Iberomaurusian industry. Carriers of these maternal lineages have been later absorbed into and diversified further during the spread of Afro-Asiatic languages in North and East Africa. PMID:23206491

mtDNA variation predicts population size in humans and reveals a major Southern Asian chapter in human prehistory.

PubMed

Atkinson, Quentin D; Gray, Russell D; Drummond, Alexei J

2008-02-01

The relative timing and size of regional human population growth following our expansion from Africa remain unknown. Human mitochondrial DNA (mtDNA) diversity carries a legacy of our population history. Given a set of sequences, we can use coalescent theory to estimate past population size through time and draw inferences about human population history. However, recent work has challenged the validity of using mtDNA diversity to infer species population sizes. Here we use Bayesian coalescent inference methods, together with a global data set of 357 human mtDNA coding-region sequences, to infer human population sizes through time across 8 major geographic regions. Our estimates of relative population sizes show remarkable concordance with the contemporary regional distribution of humans across Africa, Eurasia, and the Americas, indicating that mtDNA diversity is a good predictor of population size in humans. Plots of population size through time show slow growth in sub-Saharan Africa beginning 143-193 kya, followed by a rapid expansion into Eurasia after the emergence of the first non-African mtDNA lineages 50-70 kya. Outside Africa, the earliest and fastest growth is inferred in Southern Asia approximately 52 kya, followed by a succession of growth phases in Northern and Central Asia (approximately 49 kya), Australia (approximately 48 kya), Europe (approximately 42 kya), the Middle East and North Africa (approximately 40 kya), New Guinea (approximately 39 kya), the Americas (approximately 18 kya), and a second expansion in Europe (approximately 10-15 kya). Comparisons of relative regional population sizes through time suggest that between approximately 45 and 20 kya most of humanity lived in Southern Asia. These findings not only support the use of mtDNA data for estimating human population size but also provide a unique picture of human prehistory and demonstrate the importance of Southern Asia to our recent evolutionary past.

Semiparametric Thurstonian Models for Recurrent Choices: A Bayesian Analysis

ERIC Educational Resources Information Center

Ansari, Asim; Iyengar, Raghuram

2006-01-01

We develop semiparametric Bayesian Thurstonian models for analyzing repeated choice decisions involving multinomial, multivariate binary or multivariate ordinal data. Our modeling framework has multiple components that together yield considerable flexibility in modeling preference utilities, cross-sectional heterogeneity and parameter-driven…

Deep Learning Neural Networks and Bayesian Neural Networks in Data Analysis

NASA Astrophysics Data System (ADS)

Chernoded, Andrey; Dudko, Lev; Myagkov, Igor; Volkov, Petr

2017-10-01

Most of the modern analyses in high energy physics use signal-versus-background classification techniques of machine learning methods and neural networks in particular. Deep learning neural network is the most promising modern technique to separate signal and background and now days can be widely and successfully implemented as a part of physical analysis. In this article we compare Deep learning and Bayesian neural networks application as a classifiers in an instance of top quark analysis.

A Bayesian test for Hardy–Weinberg equilibrium of biallelic X-chromosomal markers

PubMed Central

Puig, X; Ginebra, J; Graffelman, J

2017-01-01

The X chromosome is a relatively large chromosome, harboring a lot of genetic information. Much of the statistical analysis of X-chromosomal information is complicated by the fact that males only have one copy. Recently, frequentist statistical tests for Hardy–Weinberg equilibrium have been proposed specifically for dealing with markers on the X chromosome. Bayesian test procedures for Hardy–Weinberg equilibrium for the autosomes have been described, but Bayesian work on the X chromosome in this context is lacking. This paper gives the first Bayesian approach for testing Hardy–Weinberg equilibrium with biallelic markers at the X chromosome. Marginal and joint posterior distributions for the inbreeding coefficient in females and the male to female allele frequency ratio are computed, and used for statistical inference. The paper gives a detailed account of the proposed Bayesian test, and illustrates it with data from the 1000 Genomes project. In that implementation, a novel approach to tackle multiple testing from a Bayesian perspective through posterior predictive checks is used. PMID:28900292

Genes with minimal phylogenetic information are problematic for coalescent analyses when gene tree estimation is biased.

PubMed

Xi, Zhenxiang; Liu, Liang; Davis, Charles C

2015-11-01

The development and application of coalescent methods are undergoing rapid changes. One little explored area that bears on the application of gene-tree-based coalescent methods to species tree estimation is gene informativeness. Here, we investigate the accuracy of these coalescent methods when genes have minimal phylogenetic information, including the implementation of the multilocus bootstrap approach. Using simulated DNA sequences, we demonstrate that genes with minimal phylogenetic information can produce unreliable gene trees (i.e., high error in gene tree estimation), which may in turn reduce the accuracy of species tree estimation using gene-tree-based coalescent methods. We demonstrate that this problem can be alleviated by sampling more genes, as is commonly done in large-scale phylogenomic analyses. This applies even when these genes are minimally informative. If gene tree estimation is biased, however, gene-tree-based coalescent analyses will produce inconsistent results, which cannot be remedied by increasing the number of genes. In this case, it is not the gene-tree-based coalescent methods that are flawed, but rather the input data (i.e., estimated gene trees). Along these lines, the commonly used program PhyML has a tendency to infer one particular bifurcating topology even though it is best represented as a polytomy. We additionally corroborate these findings by analyzing the 183-locus mammal data set assembled by McCormack et al. (2012) using ultra-conserved elements (UCEs) and flanking DNA. Lastly, we demonstrate that when employing the multilocus bootstrap approach on this 183-locus data set, there is no strong conflict between species trees estimated from concatenation and gene-tree-based coalescent analyses, as has been previously suggested by Gatesy and Springer (2014). Copyright © 2015 Elsevier Inc. All rights reserved.

Phase Structure and Properties of a Biodegradable Block Copolymer Coalesced from It's Crystalline Inclusion Compound Formed with alpha-Cyclodextrin

NASA Astrophysics Data System (ADS)

Shuai, Xintao; Wei, Min; Probeni, Francis; Bullions, Todd A.; Shin, I. Daniel; Tonelli, Alan E.

2002-03-01

A well-defined biodegradable block copolymer of poly(epsilon caprolactone) (PCL) and poly(L-lactic acid) (PLLA) was synthesized and characterized and then included as a guest in an inclusion compound (IC) formed with the host alpha-cyclodextrin (CD). The PCL-b-PLLA block copolymer was subsequently coalesced from it's CD-IC crystals by either treatment with hot water (50 C) or an aqueous amylase solution at 25 C. The coalesced PCL-b-PLLA was examined by FTIR, DSC, TGA, and WAXD and was found to be much more homogeneosly organized, with much less segregation and crystallinity of the PCL and PLLA microphases. The morpholgy, crystallization kinetics, thermal behavior, and biodegradability of the coalesced PCL-b-PLLA block copolymer was studied by comparison to similar observations made on as-synthesized PCL-b-PLLA, PCL and PLLA homopolymers, and their solution-cast blend. The PCL and PLLA blocks are found to be more intimately mixed, with less phase segregation, in the coalesced diblock copolymer, and this leads to homogeneous bulk crystallization, which is not observed for the as-synthesized diblock copolymer. The coalesced PCL-b-PLLA was also found to be more quickly biodegraded (lipase from Rhizopus arrhizus)than the as-synthesized PCL-b-PLLA or the physical blend of PCL and PLLA homopolymers. Overall, the coalescence of the inherently phase segregated diblock copolymer PCL-b-PLLA results in a small amount of compact, chain-extended PCL and PLLA crystals embedded in an amorphous phase, largely consisting of well-mixed PCL and PLLA blocks. Thus, we have demonstrated that it is possible to control the morpholgy of a biodegradable diblock copolymer, thereby significantly modifying it's properties, by coalescence from it's CD-IC crystals.

Dynamics of gas cell coalescence during baking expansion of leavened dough.

PubMed

Miś, Antoni; Nawrocka, Agnieszka; Lamorski, Krzysztof; Dziki, Dariusz

2018-01-01

The investigation of the dynamics of gas cell coalescence, i.e. a phenomenon that deteriorates the homogeneity of the cellular structure of bread crumb, was carried out performing simultaneously measurements of the dough volume, pressure, and viscosity. It was demonstrated that, during the baking expansion of chemically leavened wheat flour dough, the maximum growth rate of the gas cell radius determined from the ratio of pressure exerted by the expanded dough to its viscosity was on average four-fold lower than that calculated from volume changes in the gas phase of the dough. Such a high discrepancy was interpreted as a result of the course of coalescence, and a formula for determination of its rate was developed. The coalescence rate in the initial baking expansion phase had negative values, indicating nucleation of newly formed gas cells, which increased the number of gas cells even by 8%. In the next baking expansion phase, the coalescence rate started to exhibit positive values, reflecting dominance of the coalescence phenomenon over nucleation. The maximum coalescence rates indicate that, during the period of the most intensive dough expansion, the number of gas cells decreased by 2-3% within one second. At the end of the formation of bread crumb, the number of the gas cells declined by 55-67% in comparison with the initial value. The correctness of the results was positively verified using X-ray micro-computed tomography. The developed method can be a useful tool for more profound exploration of the coalescence phenomenon at various stages of evolution of the cellular structure and its determinants, which may contribute to future development of more effective methods for improving the texture and sensory quality of bread crumb. Copyright © 2017 Elsevier Ltd. All rights reserved.

Predicting nuclear gene coalescence from mitochondrial data: the three-times rule.

PubMed

Palumbi, S R; Cipriano, F; Hare, M P

2001-05-01

Coalescence theory predicts when genetic drift at nuclear loci will result in fixation of sequence differences to produce monophyletic gene trees. However, the theory is difficult to apply to particular taxa because it hinges on genetically effective population size, which is generally unknown. Neutral theory also predicts that evolution of monophyly will be four times slower in nuclear than in mitochondrial genes primarily because genetic drift is slower at nuclear loci. Variation in mitochondrial DNA (mtDNA) within and between species has been studied extensively, but can these mtDNA data be used to predict coalescence in nuclear loci? Comparison of neutral theories of coalescence of mitochondrial and nuclear loci suggests a simple rule of thumb. The "three-times rule" states that, on average, most nuclear loci will be monophyletic when the branch length leading to the mtDNA sequences of a species is three times longer than the average mtDNA sequence diversity observed within that species. A test using mitochondrial and nuclear intron data from seven species of whales and dolphins suggests general agreement with predictions of the three-times rule. We define the coalescence ratio as the mitochondrial branch length for a species divided by intraspecific mtDNA diversity. We show that species with high coalescence ratios show nuclear monophyly, whereas species with low ratios have polyphyletic nuclear gene trees. As expected, species with intermediate coalescence ratios show a variety of patterns. Especially at very high or low coalescence ratios, the three-times rule predicts nuclear gene patterns that can help detect the action of selection. The three-times rule may be useful as an empirical benchmark for evaluating evolutionary processes occurring at multiple loci.

Uncertainty Analysis and Parameter Estimation For Nearshore Hydrodynamic Models

NASA Astrophysics Data System (ADS)

Ardani, S.; Kaihatu, J. M.

2012-12-01

Numerical models represent deterministic approaches used for the relevant physical processes in the nearshore. Complexity of the physics of the model and uncertainty involved in the model inputs compel us to apply a stochastic approach to analyze the robustness of the model. The Bayesian inverse problem is one powerful way to estimate the important input model parameters (determined by apriori sensitivity analysis) and can be used for uncertainty analysis of the outputs. Bayesian techniques can be used to find the range of most probable parameters based on the probability of the observed data and the residual errors. In this study, the effect of input data involving lateral (Neumann) boundary conditions, bathymetry and off-shore wave conditions on nearshore numerical models are considered. Monte Carlo simulation is applied to a deterministic numerical model (the Delft3D modeling suite for coupled waves and flow) for the resulting uncertainty analysis of the outputs (wave height, flow velocity, mean sea level and etc.). Uncertainty analysis of outputs is performed by random sampling from the input probability distribution functions and running the model as required until convergence to the consistent results is achieved. The case study used in this analysis is the Duck94 experiment, which was conducted at the U.S. Army Field Research Facility at Duck, North Carolina, USA in the fall of 1994. The joint probability of model parameters relevant for the Duck94 experiments will be found using the Bayesian approach. We will further show that, by using Bayesian techniques to estimate the optimized model parameters as inputs and applying them for uncertainty analysis, we can obtain more consistent results than using the prior information for input data which means that the variation of the uncertain parameter will be decreased and the probability of the observed data will improve as well. Keywords: Monte Carlo Simulation, Delft3D, uncertainty analysis, Bayesian techniques, MCMC

Automated Bayesian model development for frequency detection in biological time series.

PubMed

Granqvist, Emma; Oldroyd, Giles E D; Morris, Richard J

2011-06-24

A first step in building a mathematical model of a biological system is often the analysis of the temporal behaviour of key quantities. Mathematical relationships between the time and frequency domain, such as Fourier Transforms and wavelets, are commonly used to extract information about the underlying signal from a given time series. This one-to-one mapping from time points to frequencies inherently assumes that both domains contain the complete knowledge of the system. However, for truncated, noisy time series with background trends this unique mapping breaks down and the question reduces to an inference problem of identifying the most probable frequencies. In this paper we build on the method of Bayesian Spectrum Analysis and demonstrate its advantages over conventional methods by applying it to a number of test cases, including two types of biological time series. Firstly, oscillations of calcium in plant root cells in response to microbial symbionts are non-stationary and noisy, posing challenges to data analysis. Secondly, circadian rhythms in gene expression measured over only two cycles highlights the problem of time series with limited length. The results show that the Bayesian frequency detection approach can provide useful results in specific areas where Fourier analysis can be uninformative or misleading. We demonstrate further benefits of the Bayesian approach for time series analysis, such as direct comparison of different hypotheses, inherent estimation of noise levels and parameter precision, and a flexible framework for modelling the data without pre-processing. Modelling in systems biology often builds on the study of time-dependent phenomena. Fourier Transforms are a convenient tool for analysing the frequency domain of time series. However, there are well-known limitations of this method, such as the introduction of spurious frequencies when handling short and noisy time series, and the requirement for uniformly sampled data. Biological time series often deviate significantly from the requirements of optimality for Fourier transformation. In this paper we present an alternative approach based on Bayesian inference. We show the value of placing spectral analysis in the framework of Bayesian inference and demonstrate how model comparison can automate this procedure.

Automated Bayesian model development for frequency detection in biological time series

PubMed Central

2011-01-01

Background A first step in building a mathematical model of a biological system is often the analysis of the temporal behaviour of key quantities. Mathematical relationships between the time and frequency domain, such as Fourier Transforms and wavelets, are commonly used to extract information about the underlying signal from a given time series. This one-to-one mapping from time points to frequencies inherently assumes that both domains contain the complete knowledge of the system. However, for truncated, noisy time series with background trends this unique mapping breaks down and the question reduces to an inference problem of identifying the most probable frequencies. Results In this paper we build on the method of Bayesian Spectrum Analysis and demonstrate its advantages over conventional methods by applying it to a number of test cases, including two types of biological time series. Firstly, oscillations of calcium in plant root cells in response to microbial symbionts are non-stationary and noisy, posing challenges to data analysis. Secondly, circadian rhythms in gene expression measured over only two cycles highlights the problem of time series with limited length. The results show that the Bayesian frequency detection approach can provide useful results in specific areas where Fourier analysis can be uninformative or misleading. We demonstrate further benefits of the Bayesian approach for time series analysis, such as direct comparison of different hypotheses, inherent estimation of noise levels and parameter precision, and a flexible framework for modelling the data without pre-processing. Conclusions Modelling in systems biology often builds on the study of time-dependent phenomena. Fourier Transforms are a convenient tool for analysing the frequency domain of time series. However, there are well-known limitations of this method, such as the introduction of spurious frequencies when handling short and noisy time series, and the requirement for uniformly sampled data. Biological time series often deviate significantly from the requirements of optimality for Fourier transformation. In this paper we present an alternative approach based on Bayesian inference. We show the value of placing spectral analysis in the framework of Bayesian inference and demonstrate how model comparison can automate this procedure. PMID:21702910

Fluorescence correlation spectroscopy directly monitors coalescence during nanoparticle preparation.

PubMed

Schaeffel, David; Staff, Roland Hinrich; Butt, Hans-Juergen; Landfester, Katharina; Crespy, Daniel; Koynov, Kaloian

2012-11-14

Dual color fluorescence cross-correlation spectroscopy (DC FCCS) experiments were conducted to study the coalescence and aggregation during the formation of nanoparticles. To assess the generality of the method, three completely different processes were selected to prepare the nanoparticles. Polymeric nanoparticles were formed either by solvent evaporation from emulsion nanodroplets of polymer solutions or by miniemulsion polymerization. Inorganic nanocapsules were formed by polycondensation of alkoxysilanes at the interface of nanodroplets. In all cases, DC FCCS provided fast and unambiguous information about the occurrence of coalescence and thus a deeper insight into the mechanism of nanoparticle formation. In particular, it was found that coalescence played a minor role for the emulsion-solvent evaporation process and the miniemulsion polymerization, whereas substantial coalescence was detected during the formation of the inorganic nanocapsules. These findings demonstrate that DC FCCS is a powerful tool for monitoring nanoparticles genesis.

Bayesian ensemble refinement by replica simulations and reweighting.

PubMed

Hummer, Gerhard; Köfinger, Jürgen

2015-12-28

We describe different Bayesian ensemble refinement methods, examine their interrelation, and discuss their practical application. With ensemble refinement, the properties of dynamic and partially disordered (bio)molecular structures can be characterized by integrating a wide range of experimental data, including measurements of ensemble-averaged observables. We start from a Bayesian formulation in which the posterior is a functional that ranks different configuration space distributions. By maximizing this posterior, we derive an optimal Bayesian ensemble distribution. For discrete configurations, this optimal distribution is identical to that obtained by the maximum entropy "ensemble refinement of SAXS" (EROS) formulation. Bayesian replica ensemble refinement enhances the sampling of relevant configurations by imposing restraints on averages of observables in coupled replica molecular dynamics simulations. We show that the strength of the restraints should scale linearly with the number of replicas to ensure convergence to the optimal Bayesian result in the limit of infinitely many replicas. In the "Bayesian inference of ensembles" method, we combine the replica and EROS approaches to accelerate the convergence. An adaptive algorithm can be used to sample directly from the optimal ensemble, without replicas. We discuss the incorporation of single-molecule measurements and dynamic observables such as relaxation parameters. The theoretical analysis of different Bayesian ensemble refinement approaches provides a basis for practical applications and a starting point for further investigations.

Bayesian ensemble refinement by replica simulations and reweighting

NASA Astrophysics Data System (ADS)

Hummer, Gerhard; Köfinger, Jürgen

2015-12-01

We describe different Bayesian ensemble refinement methods, examine their interrelation, and discuss their practical application. With ensemble refinement, the properties of dynamic and partially disordered (bio)molecular structures can be characterized by integrating a wide range of experimental data, including measurements of ensemble-averaged observables. We start from a Bayesian formulation in which the posterior is a functional that ranks different configuration space distributions. By maximizing this posterior, we derive an optimal Bayesian ensemble distribution. For discrete configurations, this optimal distribution is identical to that obtained by the maximum entropy "ensemble refinement of SAXS" (EROS) formulation. Bayesian replica ensemble refinement enhances the sampling of relevant configurations by imposing restraints on averages of observables in coupled replica molecular dynamics simulations. We show that the strength of the restraints should scale linearly with the number of replicas to ensure convergence to the optimal Bayesian result in the limit of infinitely many replicas. In the "Bayesian inference of ensembles" method, we combine the replica and EROS approaches to accelerate the convergence. An adaptive algorithm can be used to sample directly from the optimal ensemble, without replicas. We discuss the incorporation of single-molecule measurements and dynamic observables such as relaxation parameters. The theoretical analysis of different Bayesian ensemble refinement approaches provides a basis for practical applications and a starting point for further investigations.

Making Sense of a Negative Clinical Trial Result: A Bayesian Analysis of a Clinical Trial of Lorazepam and Diazepam for Pediatric Status Epilepticus.

PubMed

Chamberlain, Daniel B; Chamberlain, James M

2017-01-01

We demonstrate the application of a Bayesian approach to a recent negative clinical trial result. A Bayesian analysis of such a trial can provide a more useful interpretation of results and can incorporate previous evidence. This was a secondary analysis of the efficacy and safety results of the Pediatric Seizure Study, a randomized clinical trial of lorazepam versus diazepam for pediatric status epilepticus. We included the published results from the only prospective pediatric study of status in a Bayesian hierarchic model, and we performed sensitivity analyses on the amount of pooling between studies. We evaluated 3 summary analyses for the results: superiority, noninferiority (margin <-10%), and practical equivalence (within ±10%). Consistent with the original study's classic analysis of study results, we did not demonstrate superiority of lorazepam over diazepam. There is a 95% probability that the true efficacy of lorazepam is in the range of 66% to 80%. For both the efficacy and safety outcomes, there was greater than 95% probability that lorazepam is noninferior to diazepam, and there was greater than 90% probability that the 2 medications are practically equivalent. The results were largely driven by the current study because of the sample sizes of our study (n=273) and the previous pediatric study (n=61). Because Bayesian analysis estimates the probability of one or more hypotheses, such an approach can provide more useful information about the meaning of the results of a negative trial outcome. In the case of pediatric status epilepticus, it is highly likely that lorazepam is noninferior and practically equivalent to diazepam. Copyright © 2016 American College of Emergency Physicians. Published by Elsevier Inc. All rights reserved.

A Bayesian Analysis of a Randomized Clinical Trial Comparing Antimetabolite Therapies for Non-Infectious Uveitis

PubMed Central

Browne, Erica N; Rathinam, Sivakumar R; Kanakath, Anuradha; Thundikandy, Radhika; Babu, Manohar; Lietman, Thomas M; Acharya, Nisha R

2017-01-01

Purpose To conduct a Bayesian analysis of a randomized clinical trial (RCT) for non-infectious uveitis using expert opinion as a subjective prior belief. Methods A RCT was conducted to determine which antimetabolite, methotrexate or mycophenolate mofetil, is more effective as an initial corticosteroid-sparing agent for the treatment of intermediate, posterior, and pan- uveitis. Before the release of trial results, expert opinion on the relative effectiveness of these two medications was collected via online survey. Members of the American Uveitis Society executive committee were invited to provide an estimate for the relative decrease in efficacy with a 95% credible interval (CrI). A prior probability distribution was created from experts’ estimates. A Bayesian analysis was performed using the constructed expert prior probability distribution and the trial’s primary outcome. Results 11 of 12 invited uveitis specialists provided estimates. Eight of 11 experts (73%) believed mycophenolate mofetil is more effective. The group prior belief was that the odds of treatment success for patients taking mycophenolate mofetil were 1.4-fold the odds of those taking methotrexate (95% CrI 0.03 – 45.0). The odds of treatment success with mycophenolate mofetil compared to methotrexate was 0.4 from the RCT (95% confidence interval 0.1–1.2) and 0.7 (95% CrI 0.2–1.7) from the Bayesian analysis. Conclusions A Bayesian analysis combining expert belief with the trial’s result did not indicate preference for one drug. However, the wide credible interval leaves open the possibility of a substantial treatment effect. This suggests clinical equipoise necessary to allow a larger, more definitive RCT. PMID:27982726

Accounting for Uncertainty in Gene Tree Estimation: Summary-Coalescent Species Tree Inference in a Challenging Radiation of Australian Lizards.

PubMed

Blom, Mozes P K; Bragg, Jason G; Potter, Sally; Moritz, Craig

2017-05-01

Accurate gene tree inference is an important aspect of species tree estimation in a summary-coalescent framework. Yet, in empirical studies, inferred gene trees differ in accuracy due to stochastic variation in phylogenetic signal between targeted loci. Empiricists should, therefore, examine the consistency of species tree inference, while accounting for the observed heterogeneity in gene tree resolution of phylogenomic data sets. Here, we assess the impact of gene tree estimation error on summary-coalescent species tree inference by screening ${\\sim}2000$ exonic loci based on gene tree resolution prior to phylogenetic inference. We focus on a phylogenetically challenging radiation of Australian lizards (genus Cryptoblepharus, Scincidae) and explore effects on topology and support. We identify a well-supported topology based on all loci and find that a relatively small number of high-resolution gene trees can be sufficient to converge on the same topology. Adding gene trees with decreasing resolution produced a generally consistent topology, and increased confidence for specific bipartitions that were poorly supported when using a small number of informative loci. This corroborates coalescent-based simulation studies that have highlighted the need for a large number of loci to confidently resolve challenging relationships and refutes the notion that low-resolution gene trees introduce phylogenetic noise. Further, our study also highlights the value of quantifying changes in nodal support across locus subsets of increasing size (but decreasing gene tree resolution). Such detailed analyses can reveal anomalous fluctuations in support at some nodes, suggesting the possibility of model violation. By characterizing the heterogeneity in phylogenetic signal among loci, we can account for uncertainty in gene tree estimation and assess its effect on the consistency of the species tree estimate. We suggest that the evaluation of gene tree resolution should be incorporated in the analysis of empirical phylogenomic data sets. This will ultimately increase our confidence in species tree estimation using summary-coalescent methods and enable us to exploit genomic data for phylogenetic inference. [Coalescence; concatenation; Cryptoblepharus; exon capture; gene tree; phylogenomics; species tree.]. © The authors 2016. Published by Oxford University Press, on behalf of the Society of Systematic Biologists. All rights reserved. For permissions, please e-mail: journals.permission@oup.com.

Coalescence growth mechanism of ultrafine metal particles

NASA Astrophysics Data System (ADS)

Kasukabe, S.

1990-01-01

Ultrafine particles produced by a gas-evaporation technique show clear-cut crystal habits. The convection of an inert gas makes distinct growth zones in a metal smoke. The coalescence stages of hexagonal plates and multiply twinned particles are observed in the outer zone of a smoke. A model of the coalescence growth of particles with different crystal habits is proposed. Size distributions can be calculated by counting the ratio of the number of collisions by using the effective cross section of collisions and the existence probability of the volume of a particle. This simulation model makes clear the effect on the growth rate of coalescence growth derived from crystal habit.

Prevention of nanoparticle coalescence under high-temperature annealing.

PubMed

Mizuno, Mikihisa; Sasaki, Yuichi; Yu, Andrew C C; Inoue, Makoto

2004-12-21

An effective method of employing 3-aminopropyldimethylethoxysilane linker molecules to stabilize 4.4 nm FePt nanoparticle monolayer films on a SiO2 substrate as well as to prevent coalescence of the particles under 800 degrees C annealing is reported. As-deposited FePt nanoparticle films in chemically disordered face-centered-cubic phase transform to mostly chemically ordered L1 0 structure after annealing, while the nanoparticles are free from serious coalescence. The method may fulfill the pressing need to prevent nanoparticle coalescence under high-temperature annealing for the development of FePt nanoparticle based products, such as ultrahigh-density magnetic recording media and novel memory devices.

Generalized Boltzmann-Type Equations for Aggregation in Gases

NASA Astrophysics Data System (ADS)

Adzhiev, S. Z.; Vedenyapin, V. V.; Volkov, Yu. A.; Melikhov, I. V.

2017-12-01

The coalescence and fragmentation of particles in a dispersion system are investigated by applying kinetic theory methods, namely, by generalizing the Boltzmann kinetic equation to coalescence and fragmentation processes. Dynamic equations for the particle concentrations in the system are derived using the kinetic equations of motion. For particle coalescence and fragmentation, equations for the particle momentum, coordinate, and mass distribution functions are obtained and the coalescence and fragmentation coefficients are calculated. The equilibrium mass and velocity distribution functions of the particles in the dispersion system are found in the approximation of an active terminal group (Becker-Döring-type equation). The transition to a continuum description is performed.

Coalescence of Drops of a Power-law Fluid

NASA Astrophysics Data System (ADS)

Kamat, Pritish; Thete, Sumeet; Basaran, Osman

2014-11-01

Drop coalescence is crucial in a host of industrial, household, and natural processes that involve dispersions. Coalescence is a rate-controlling process in breaking emulsions and strongly influences drop-size-distributions in sprays. In a continuum approach, coalescence begins by the formation of a microscopic, non-slender bridge connecting the two drops. Indefinitely large axial curvature at the neck results in local lowering of pressure that drives fluid from the bulk of the drops toward the neck, thereby causing the bridge radius r (t) and height z (t) to increase in time t. The coalescence of Newtonian drops in air has heretofore been thoroughly studied. Here, we extend these earlier studies by analyzing the coalescence of drops of power-law fluids because many fluids encountered in real applications, including cosmetic creams, shampoos, grease, and paint, exhibit power-law (deformation-rate thinning) rheology. On account of the non-slender geometry of the liquid bridge connecting the two drops (z << r) , we analyze the resulting free surface flow problem by numerical simulation. Among other results, we present and discuss the nature of flows and scaling behaviors for r and z as functions of the initial viscosity and power-law index (0 < n <= 1) .

Assessment of parametric uncertainty for groundwater reactive transport modeling,

USGS Publications Warehouse

Shi, Xiaoqing; Ye, Ming; Curtis, Gary P.; Miller, Geoffery L.; Meyer, Philip D.; Kohler, Matthias; Yabusaki, Steve; Wu, Jichun

2014-01-01

The validity of using Gaussian assumptions for model residuals in uncertainty quantification of a groundwater reactive transport model was evaluated in this study. Least squares regression methods explicitly assume Gaussian residuals, and the assumption leads to Gaussian likelihood functions, model parameters, and model predictions. While the Bayesian methods do not explicitly require the Gaussian assumption, Gaussian residuals are widely used. This paper shows that the residuals of the reactive transport model are non-Gaussian, heteroscedastic, and correlated in time; characterizing them requires using a generalized likelihood function such as the formal generalized likelihood function developed by Schoups and Vrugt (2010). For the surface complexation model considered in this study for simulating uranium reactive transport in groundwater, parametric uncertainty is quantified using the least squares regression methods and Bayesian methods with both Gaussian and formal generalized likelihood functions. While the least squares methods and Bayesian methods with Gaussian likelihood function produce similar Gaussian parameter distributions, the parameter distributions of Bayesian uncertainty quantification using the formal generalized likelihood function are non-Gaussian. In addition, predictive performance of formal generalized likelihood function is superior to that of least squares regression and Bayesian methods with Gaussian likelihood function. The Bayesian uncertainty quantification is conducted using the differential evolution adaptive metropolis (DREAM(zs)) algorithm; as a Markov chain Monte Carlo (MCMC) method, it is a robust tool for quantifying uncertainty in groundwater reactive transport models. For the surface complexation model, the regression-based local sensitivity analysis and Morris- and DREAM(ZS)-based global sensitivity analysis yield almost identical ranking of parameter importance. The uncertainty analysis may help select appropriate likelihood functions, improve model calibration, and reduce predictive uncertainty in other groundwater reactive transport and environmental modeling.

Genetic History of Hepatitis C Virus in Venezuela: High Diversity and Long Time of Evolution of HCV Genotype 2

PubMed Central

Sulbarán, Maria Z.; Di Lello, Federico A.; Sulbarán, Yoneira; Cosson, Clarisa; Loureiro, Carmen L.; Rangel, Héctor R.; Cantaloube, Jean F.; Campos, Rodolfo H.; Moratorio, Gonzalo; Cristina, Juan; Pujol, Flor H.

2010-01-01

Background The subtype diversity of the hepatitis C virus (HCV) genotypes is unknown in Venezuela. Methodology/Principal Findings Partial sequencing of the NS5B region was performed in 310 isolates circulating in patients from 1995 to 2007. In the samples collected between 2005 and 2007, HCV genotype 1 (G1) was the most common genotype (63%), composed as expected of mainly G1a and G1b. G2 was the second most common genotype (33%), being G2a almost absent and G2j the most frequent subtype. Sequence analysis of the core region confirmed the subtype assignment performed within the NS5b region in 63 isolates. The complete genome sequence of G2j was obtained. G2j has been described in France, Canada and Burkina Fasso, but it was not found in Martinique, where several subtypes of G2 circulate in the general population. Bayesian coalescence analysis indicated a most recent common ancestor (MRCA) of G2j around 1785, before the introduction of G1b (1869) and G1a (1922). While HCV G1a and G1b experienced a growth reduction since 1990, coincident with the time when blood testing was implemented in Venezuela, HCV G2j did not seem to reach growth equilibrium during this period. Conclusions/Significance Assuming the introduction of G2j from Africa during the slave trade, the high frequency of G2j found in Venezuela could suggest: 1- the introduction of African ethnic groups different from the ones introduced to Martinique or 2- the occurrence of a founder effect. This study represents an in-depth analysis of the subtype diversity of HCV in Venezuela, which is still unexplored in the Americas and deserves further studies. PMID:21179440

A Bayesian Multinomial Probit MODEL FOR THE ANALYSIS OF PANEL CHOICE DATA.

PubMed

Fong, Duncan K H; Kim, Sunghoon; Chen, Zhe; DeSarbo, Wayne S

2016-03-01

A new Bayesian multinomial probit model is proposed for the analysis of panel choice data. Using a parameter expansion technique, we are able to devise a Markov Chain Monte Carlo algorithm to compute our Bayesian estimates efficiently. We also show that the proposed procedure enables the estimation of individual level coefficients for the single-period multinomial probit model even when the available prior information is vague. We apply our new procedure to consumer purchase data and reanalyze a well-known scanner panel dataset that reveals new substantive insights. In addition, we delineate a number of advantageous features of our proposed procedure over several benchmark models. Finally, through a simulation analysis employing a fractional factorial design, we demonstrate that the results from our proposed model are quite robust with respect to differing factors across various conditions.

Predictive distributions for between-study heterogeneity and simple methods for their application in Bayesian meta-analysis

PubMed Central

Turner, Rebecca M; Jackson, Dan; Wei, Yinghui; Thompson, Simon G; Higgins, Julian P T

2015-01-01

Numerous meta-analyses in healthcare research combine results from only a small number of studies, for which the variance representing between-study heterogeneity is estimated imprecisely. A Bayesian approach to estimation allows external evidence on the expected magnitude of heterogeneity to be incorporated. The aim of this paper is to provide tools that improve the accessibility of Bayesian meta-analysis. We present two methods for implementing Bayesian meta-analysis, using numerical integration and importance sampling techniques. Based on 14 886 binary outcome meta-analyses in the Cochrane Database of Systematic Reviews, we derive a novel set of predictive distributions for the degree of heterogeneity expected in 80 settings depending on the outcomes assessed and comparisons made. These can be used as prior distributions for heterogeneity in future meta-analyses. The two methods are implemented in R, for which code is provided. Both methods produce equivalent results to standard but more complex Markov chain Monte Carlo approaches. The priors are derived as log-normal distributions for the between-study variance, applicable to meta-analyses of binary outcomes on the log odds-ratio scale. The methods are applied to two example meta-analyses, incorporating the relevant predictive distributions as prior distributions for between-study heterogeneity. We have provided resources to facilitate Bayesian meta-analysis, in a form accessible to applied researchers, which allow relevant prior information on the degree of heterogeneity to be incorporated. © 2014 The Authors. Statistics in Medicine published by John Wiley & Sons Ltd. PMID:25475839

A fully Bayesian before-after analysis of permeable friction course (PFC) pavement wet weather safety.

PubMed

Buddhavarapu, Prasad; Smit, Andre F; Prozzi, Jorge A

2015-07-01

Permeable friction course (PFC), a porous hot-mix asphalt, is typically applied to improve wet weather safety on high-speed roadways in Texas. In order to warrant expensive PFC construction, a statistical evaluation of its safety benefits is essential. Generally, the literature on the effectiveness of porous mixes in reducing wet-weather crashes is limited and often inconclusive. In this study, the safety effectiveness of PFC was evaluated using a fully Bayesian before-after safety analysis. First, two groups of road segments overlaid with PFC and non-PFC material were identified across Texas; the non-PFC or reference road segments selected were similar to their PFC counterparts in terms of site specific features. Second, a negative binomial data generating process was assumed to model the underlying distribution of crash counts of PFC and reference road segments to perform Bayesian inference on the safety effectiveness. A data-augmentation based computationally efficient algorithm was employed for a fully Bayesian estimation. The statistical analysis shows that PFC is not effective in reducing wet weather crashes. It should be noted that the findings of this study are in agreement with the existing literature, although these studies were not based on a fully Bayesian statistical analysis. Our study suggests that the safety effectiveness of PFC road surfaces, or any other safety infrastructure, largely relies on its interrelationship with the road user. The results suggest that the safety infrastructure must be properly used to reap the benefits of the substantial investments. Copyright © 2015 Elsevier Ltd. All rights reserved.

A fully Bayesian method for jointly fitting instrumental calibration and X-ray spectral models

DOE Office of Scientific and Technical Information (OSTI.GOV)

Xu, Jin; Yu, Yaming; Van Dyk, David A.

2014-10-20

Owing to a lack of robust principled methods, systematic instrumental uncertainties have generally been ignored in astrophysical data analysis despite wide recognition of the importance of including them. Ignoring calibration uncertainty can cause bias in the estimation of source model parameters and can lead to underestimation of the variance of these estimates. We previously introduced a pragmatic Bayesian method to address this problem. The method is 'pragmatic' in that it introduced an ad hoc technique that simplified computation by neglecting the potential information in the data for narrowing the uncertainty for the calibration product. Following that work, we use amore » principal component analysis to efficiently represent the uncertainty of the effective area of an X-ray (or γ-ray) telescope. Here, however, we leverage this representation to enable a principled, fully Bayesian method that coherently accounts for the calibration uncertainty in high-energy spectral analysis. In this setting, the method is compared with standard analysis techniques and the pragmatic Bayesian method. The advantage of the fully Bayesian method is that it allows the data to provide information not only for estimation of the source parameters but also for the calibration product—here the effective area, conditional on the adopted spectral model. In this way, it can yield more accurate and efficient estimates of the source parameters along with valid estimates of their uncertainty. Provided that the source spectrum can be accurately described by a parameterized model, this method allows rigorous inference about the effective area by quantifying which possible curves are most consistent with the data.« less

Bayesian Techniques for Plasma Theory to Bridge the Gap Between Space and Lab Plasmas

NASA Astrophysics Data System (ADS)

Crabtree, Chris; Ganguli, Gurudas; Tejero, Erik

2017-10-01

We will show how Bayesian techniques provide a general data analysis methodology that is better suited to investigate phenomena that require a nonlinear theory for an explanation. We will provide short examples of how Bayesian techniques have been successfully used in the radiation belts to provide precise nonlinear spectral estimates of whistler mode chorus and how these techniques have been verified in laboratory plasmas. We will demonstrate how Bayesian techniques allow for the direct competition of different physical theories with data acting as the necessary arbitrator. This work is supported by the Naval Research Laboratory base program and by the National Aeronautics and Space Administration under Grant No. NNH15AZ90I.

Bayesian just-so stories in psychology and neuroscience.

PubMed

Bowers, Jeffrey S; Davis, Colin J

2012-05-01

According to Bayesian theories in psychology and neuroscience, minds and brains are (near) optimal in solving a wide range of tasks. We challenge this view and argue that more traditional, non-Bayesian approaches are more promising. We make 3 main arguments. First, we show that the empirical evidence for Bayesian theories in psychology is weak. This weakness relates to the many arbitrary ways that priors, likelihoods, and utility functions can be altered in order to account for the data that are obtained, making the models unfalsifiable. It further relates to the fact that Bayesian theories are rarely better at predicting data compared with alternative (and simpler) non-Bayesian theories. Second, we show that the empirical evidence for Bayesian theories in neuroscience is weaker still. There are impressive mathematical analyses showing how populations of neurons could compute in a Bayesian manner but little or no evidence that they do. Third, we challenge the general scientific approach that characterizes Bayesian theorizing in cognitive science. A common premise is that theories in psychology should largely be constrained by a rational analysis of what the mind ought to do. We question this claim and argue that many of the important constraints come from biological, evolutionary, and processing (algorithmic) considerations that have no adaptive relevance to the problem per se. In our view, these factors have contributed to the development of many Bayesian "just so" stories in psychology and neuroscience; that is, mathematical analyses of cognition that can be used to explain almost any behavior as optimal. 2012 APA, all rights reserved.

Evaluation of a Partial Genome Screening of Two Asthma Susceptibility Regions Using Bayesian Network Based Bayesian Multilevel Analysis of Relevance

PubMed Central

Antal, Péter; Kiszel, Petra Sz.; Gézsi, András; Hadadi, Éva; Virág, Viktor; Hajós, Gergely; Millinghoffer, András; Nagy, Adrienne; Kiss, András; Semsei, Ágnes F.; Temesi, Gergely; Melegh, Béla; Kisfali, Péter; Széll, Márta; Bikov, András; Gálffy, Gabriella; Tamási, Lilla; Falus, András; Szalai, Csaba

2012-01-01

Genetic studies indicate high number of potential factors related to asthma. Based on earlier linkage analyses we selected the 11q13 and 14q22 asthma susceptibility regions, for which we designed a partial genome screening study using 145 SNPs in 1201 individuals (436 asthmatic children and 765 controls). The results were evaluated with traditional frequentist methods and we applied a new statistical method, called Bayesian network based Bayesian multilevel analysis of relevance (BN-BMLA). This method uses Bayesian network representation to provide detailed characterization of the relevance of factors, such as joint significance, the type of dependency, and multi-target aspects. We estimated posteriors for these relations within the Bayesian statistical framework, in order to estimate the posteriors whether a variable is directly relevant or its association is only mediated. With frequentist methods one SNP (rs3751464 in the FRMD6 gene) provided evidence for an association with asthma (OR = 1.43(1.2–1.8); p = 3×10−4). The possible role of the FRMD6 gene in asthma was also confirmed in an animal model and human asthmatics. In the BN-BMLA analysis altogether 5 SNPs in 4 genes were found relevant in connection with asthma phenotype: PRPF19 on chromosome 11, and FRMD6, PTGER2 and PTGDR on chromosome 14. In a subsequent step a partial dataset containing rhinitis and further clinical parameters was used, which allowed the analysis of relevance of SNPs for asthma and multiple targets. These analyses suggested that SNPs in the AHNAK and MS4A2 genes were indirectly associated with asthma. This paper indicates that BN-BMLA explores the relevant factors more comprehensively than traditional statistical methods and extends the scope of strong relevance based methods to include partial relevance, global characterization of relevance and multi-target relevance. PMID:22432035

Coalescent Processes with Skewed Offspring Distributions and Nonequilibrium Demography.

PubMed

Matuszewski, Sebastian; Hildebrandt, Marcel E; Achaz, Guillaume; Jensen, Jeffrey D

2018-01-01

Nonequilibrium demography impacts coalescent genealogies leaving detectable, well-studied signatures of variation. However, similar genomic footprints are also expected under models of large reproductive skew, posing a serious problem when trying to make inference. Furthermore, current approaches consider only one of the two processes at a time, neglecting any genomic signal that could arise from their simultaneous effects, preventing the possibility of jointly inferring parameters relating to both offspring distribution and population history. Here, we develop an extended Moran model with exponential population growth, and demonstrate that the underlying ancestral process converges to a time-inhomogeneous psi-coalescent. However, by applying a nonlinear change of time scale-analogous to the Kingman coalescent-we find that the ancestral process can be rescaled to its time-homogeneous analog, allowing the process to be simulated quickly and efficiently. Furthermore, we derive analytical expressions for the expected site-frequency spectrum under the time-inhomogeneous psi-coalescent, and develop an approximate-likelihood framework for the joint estimation of the coalescent and growth parameters. By means of extensive simulation, we demonstrate that both can be estimated accurately from whole-genome data. In addition, not accounting for demography can lead to serious biases in the inferred coalescent model, with broad implications for genomic studies ranging from ecology to conservation biology. Finally, we use our method to analyze sequence data from Japanese sardine populations, and find evidence of high variation in individual reproductive success, but few signs of a recent demographic expansion. Copyright © 2018 by the Genetics Society of America.

Dynamic measurements and simulations of airborne picolitre-droplet coalescence in holographic optical tweezers

DOE Office of Scientific and Technical Information (OSTI.GOV)

Bzdek, Bryan R.; Reid, Jonathan P., E-mail: j.p.reid@bristol.ac.uk; Collard, Liam

We report studies of the coalescence of pairs of picolitre aerosol droplets manipulated with holographic optical tweezers, probing the shape relaxation dynamics following coalescence by simultaneously monitoring the intensity of elastic backscattered light (EBL) from the trapping laser beam (time resolution on the order of 100 ns) while recording high frame rate camera images (time resolution <10 μs). The goals of this work are to: resolve the dynamics of droplet coalescence in holographic optical traps; assign the origin of key features in the time-dependent EBL intensity; and validate the use of the EBL alone to precisely determine droplet surface tensionmore » and viscosity. For low viscosity droplets, two sequential processes are evident: binary coalescence first results from the overlap of the optical traps on the time scale of microseconds followed by the recapture of the composite droplet in an optical trap on the time scale of milliseconds. As droplet viscosity increases, the relaxation in droplet shape eventually occurs on the same time scale as recapture, resulting in a convoluted evolution of the EBL intensity that inhibits quantitative determination of the relaxation time scale. Droplet coalescence was simulated using a computational framework to validate both experimental approaches. The results indicate that time-dependent monitoring of droplet shape from the EBL intensity allows for robust determination of properties such as surface tension and viscosity. Finally, the potential of high frame rate imaging to examine the coalescence of dissimilar viscosity droplets is discussed.« less

Flocculation and coalescence of droplets in oil-in-water emulsions formed with highly hydrolysed whey proteins as influenced by starch.

PubMed

Ye, Aiqian; Hemar, Yacine; Singh, Harjinder

2004-10-10

The effects of added unmodified amylopectin starch, modified amylopectin starch and amylose starch on the formation and properties of emulsions (4 wt.% corn oil) made with an extensively hydrolysed commercial whey protein (WPH) product under a range of conditions were examined. The rate of coalescence was calculated based on the changes in the droplet size of the emulsions during storage at 20 degrees C. The rates of creaming and coalescence in emulsions containing amylopectin starches were enhanced with increasing concentration of the starches during storage for up to 7 days. At a given starch concentration, the rate of coalescence was higher in the emulsions containing modified amylopectin starch than in those containing unmodified amylopectin starch, whereas it was lowest in the emulsions containing amylose starch. All emulsions containing unmodified and modified amylopectin starches showed flocculation of oil droplets by a depletion mechanism. However, flocculation was not observed in the emulsions containing amylose starch. The extent of flocculation was considered to correlate with the rate of coalescence of oil droplets. The different rates of coalescence could be explained on the basis of the strength of the depletion potential, which was dependent on the molecular weight and the radius of gyration of the starches. At high levels of starch addition (>1.5%), the rate of coalescence decreased gradually, apparently because of the high viscosity of the aqueous phase caused by the starch.

Asymptotic Properties of the Number of Matching Coalescent Histories for Caterpillar-Like Families of Species Trees.

PubMed

Disanto, Filippo; Rosenberg, Noah A

2016-01-01

Coalescent histories provide lists of species tree branches on which gene tree coalescences can take place, and their enumerative properties assist in understanding the computational complexity of calculations central in the study of gene trees and species trees. Here, we solve an enumerative problem left open by Rosenberg (IEEE/ACM Transactions on Computational Biology and Bioinformatics 10: 1253-1262, 2013) concerning the number of coalescent histories for gene trees and species trees with a matching labeled topology that belongs to a generic caterpillar-like family. By bringing a generating function approach to the study of coalescent histories, we prove that for any caterpillar-like family with seed tree t , the sequence (h n ) n ≥ 0 describing the number of matching coalescent histories of the n th tree of the family grows asymptotically as a constant multiple of the Catalan numbers. Thus, h n  ∼ β t c n , where the asymptotic constant β t > 0 depends on the shape of the seed tree t. The result extends a claim demonstrated only for seed trees with at most eight taxa to arbitrary seed trees, expanding the set of cases for which detailed enumerative properties of coalescent histories can be determined. We introduce a procedure that computes from t the constant β t as well as the algebraic expression for the generating function of the sequence (h n ) n ≥ 0 .

A Two-Step Bayesian Approach for Propensity Score Analysis: Simulations and Case Study.

PubMed

Kaplan, David; Chen, Jianshen

2012-07-01

A two-step Bayesian propensity score approach is introduced that incorporates prior information in the propensity score equation and outcome equation without the problems associated with simultaneous Bayesian propensity score approaches. The corresponding variance estimators are also provided. The two-step Bayesian propensity score is provided for three methods of implementation: propensity score stratification, weighting, and optimal full matching. Three simulation studies and one case study are presented to elaborate the proposed two-step Bayesian propensity score approach. Results of the simulation studies reveal that greater precision in the propensity score equation yields better recovery of the frequentist-based treatment effect. A slight advantage is shown for the Bayesian approach in small samples. Results also reveal that greater precision around the wrong treatment effect can lead to seriously distorted results. However, greater precision around the correct treatment effect parameter yields quite good results, with slight improvement seen with greater precision in the propensity score equation. A comparison of coverage rates for the conventional frequentist approach and proposed Bayesian approach is also provided. The case study reveals that credible intervals are wider than frequentist confidence intervals when priors are non-informative.

Robust Bayesian Analysis of Heavy-tailed Stochastic Volatility Models using Scale Mixtures of Normal Distributions

PubMed Central

Abanto-Valle, C. A.; Bandyopadhyay, D.; Lachos, V. H.; Enriquez, I.

2009-01-01

A Bayesian analysis of stochastic volatility (SV) models using the class of symmetric scale mixtures of normal (SMN) distributions is considered. In the face of non-normality, this provides an appealing robust alternative to the routine use of the normal distribution. Specific distributions examined include the normal, student-t, slash and the variance gamma distributions. Using a Bayesian paradigm, an efficient Markov chain Monte Carlo (MCMC) algorithm is introduced for parameter estimation. Moreover, the mixing parameters obtained as a by-product of the scale mixture representation can be used to identify outliers. The methods developed are applied to analyze daily stock returns data on S&P500 index. Bayesian model selection criteria as well as out-of- sample forecasting results reveal that the SV models based on heavy-tailed SMN distributions provide significant improvement in model fit as well as prediction to the S&P500 index data over the usual normal model. PMID:20730043

Bayesian Analysis of the Association between Family-Level Factors and Siblings' Dental Caries.

PubMed

Wen, A; Weyant, R J; McNeil, D W; Crout, R J; Neiswanger, K; Marazita, M L; Foxman, B

2017-07-01

We conducted a Bayesian analysis of the association between family-level socioeconomic status and smoking and the prevalence of dental caries among siblings (children from infant to 14 y) among children living in rural and urban Northern Appalachia using data from the Center for Oral Health Research in Appalachia (COHRA). The observed proportion of siblings sharing caries was significantly different from predicted assuming siblings' caries status was independent. Using a Bayesian hierarchical model, we found the inclusion of a household factor significantly improved the goodness of fit. Other findings showed an inverse association between parental education and siblings' caries and a positive association between households with smokers and siblings' caries. Our study strengthens existing evidence suggesting that increased parental education and decreased parental cigarette smoking are associated with reduced childhood caries in the household. Our results also demonstrate the value of a Bayesian approach, which allows us to include household as a random effect, thereby providing more accurate estimates than obtained using generalized linear mixed models.

Bayesian generalized least squares regression with application to log Pearson type 3 regional skew estimation

NASA Astrophysics Data System (ADS)

Reis, D. S.; Stedinger, J. R.; Martins, E. S.

2005-10-01

This paper develops a Bayesian approach to analysis of a generalized least squares (GLS) regression model for regional analyses of hydrologic data. The new approach allows computation of the posterior distributions of the parameters and the model error variance using a quasi-analytic approach. Two regional skew estimation studies illustrate the value of the Bayesian GLS approach for regional statistical analysis of a shape parameter and demonstrate that regional skew models can be relatively precise with effective record lengths in excess of 60 years. With Bayesian GLS the marginal posterior distribution of the model error variance and the corresponding mean and variance of the parameters can be computed directly, thereby providing a simple but important extension of the regional GLS regression procedures popularized by Tasker and Stedinger (1989), which is sensitive to the likely values of the model error variance when it is small relative to the sampling error in the at-site estimator.

Bayesian Estimation of the True Prevalence and of the Diagnostic Test Sensitivity and Specificity of Enteropathogenic Yersinia in Finnish Pig Serum Samples.

PubMed

Vilar, M J; Ranta, J; Virtanen, S; Korkeala, H

2015-01-01

Bayesian analysis was used to estimate the pig's and herd's true prevalence of enteropathogenic Yersinia in serum samples collected from Finnish pig farms. The sensitivity and specificity of the diagnostic test were also estimated for the commercially available ELISA which is used for antibody detection against enteropathogenic Yersinia. The Bayesian analysis was performed in two steps; the first step estimated the prior true prevalence of enteropathogenic Yersinia with data obtained from a systematic review of the literature. In the second step, data of the apparent prevalence (cross-sectional study data), prior true prevalence (first step), and estimated sensitivity and specificity of the diagnostic methods were used for building the Bayesian model. The true prevalence of Yersinia in slaughter-age pigs was 67.5% (95% PI 63.2-70.9). The true prevalence of Yersinia in sows was 74.0% (95% PI 57.3-82.4). The estimates of sensitivity and specificity values of the ELISA were 79.5% and 96.9%.

A Bayesian Approach to a Multiple-Group Latent Class-Profile Analysis: The Timing of Drinking Onset and Subsequent Drinking Behaviors among U.S. Adolescents

ERIC Educational Resources Information Center

Chung, Hwan; Anthony, James C.

2013-01-01

This article presents a multiple-group latent class-profile analysis (LCPA) by taking a Bayesian approach in which a Markov chain Monte Carlo simulation is employed to achieve more robust estimates for latent growth patterns. This article describes and addresses a label-switching problem that involves the LCPA likelihood function, which has…

Bayesian Logic Programs for Plan Recognition and Machine Reading

DTIC Science & Technology

2012-12-01

models is that they can handle both uncertainty and structured/ relational data. As a result, they are widely used in domains like social network...data. As a result, they are widely used in domains like social net- work analysis, biological data analysis, and natural language processing. Bayesian...the Story Understanding data set. (b) The logical representation of the observations. (c) The set of ground rules obtained from logical abduction

Distribution Grid Integration Costs Under High PV Penetrations Workshop |

Science.gov Websites

grids. These distribution grid integration costs are one component of a complete cost-benefit analysis . Engaging stakeholders to coalesce around transparent and mutually acceptable frameworks for cost-benefit -voltage only). In particular, there was be a focus on methods most appropriate for cost-benefit analysis

Phylotranscriptomic analysis of the origin and early diversification of land plants

PubMed Central

Wickett, Norman J.; Mirarab, Siavash; Nguyen, Nam; Warnow, Tandy; Carpenter, Eric; Matasci, Naim; Ayyampalayam, Saravanaraj; Barker, Michael S.; Burleigh, J. Gordon; Gitzendanner, Matthew A.; Ruhfel, Brad R.; Wafula, Eric; Graham, Sean W.; Mathews, Sarah; Melkonian, Michael; Soltis, Douglas E.; Soltis, Pamela S.; Miles, Nicholas W.; Rothfels, Carl J.; Pokorny, Lisa; Shaw, A. Jonathan; DeGironimo, Lisa; Stevenson, Dennis W.; Surek, Barbara; Villarreal, Juan Carlos; Roure, Béatrice; Philippe, Hervé; dePamphilis, Claude W.; Chen, Tao; Deyholos, Michael K.; Baucom, Regina S.; Kutchan, Toni M.; Augustin, Megan M.; Wang, Jun; Zhang, Yong; Tian, Zhijian; Yan, Zhixiang; Wu, Xiaolei; Sun, Xiao; Wong, Gane Ka-Shu; Leebens-Mack, James

2014-01-01

Reconstructing the origin and evolution of land plants and their algal relatives is a fundamental problem in plant phylogenetics, and is essential for understanding how critical adaptations arose, including the embryo, vascular tissue, seeds, and flowers. Despite advances in molecular systematics, some hypotheses of relationships remain weakly resolved. Inferring deep phylogenies with bouts of rapid diversification can be problematic; however, genome-scale data should significantly increase the number of informative characters for analyses. Recent phylogenomic reconstructions focused on the major divergences of plants have resulted in promising but inconsistent results. One limitation is sparse taxon sampling, likely resulting from the difficulty and cost of data generation. To address this limitation, transcriptome data for 92 streptophyte taxa were generated and analyzed along with 11 published plant genome sequences. Phylogenetic reconstructions were conducted using up to 852 nuclear genes and 1,701,170 aligned sites. Sixty-nine analyses were performed to test the robustness of phylogenetic inferences to permutations of the data matrix or to phylogenetic method, including supermatrix, supertree, and coalescent-based approaches, maximum-likelihood and Bayesian methods, partitioned and unpartitioned analyses, and amino acid versus DNA alignments. Among other results, we find robust support for a sister-group relationship between land plants and one group of streptophyte green algae, the Zygnematophyceae. Strong and robust support for a clade comprising liverworts and mosses is inconsistent with a widely accepted view of early land plant evolution, and suggests that phylogenetic hypotheses used to understand the evolution of fundamental plant traits should be reevaluated. PMID:25355905

Accurate quantification of within- and between-host HBV evolutionary rates requires explicit transmission chain modelling.

PubMed

Vrancken, Bram; Suchard, Marc A; Lemey, Philippe

2017-07-01

Analyses of virus evolution in known transmission chains have the potential to elucidate the impact of transmission dynamics on the viral evolutionary rate and its difference within and between hosts. Lin et al. (2015, Journal of Virology , 89/7: 3512-22) recently investigated the evolutionary history of hepatitis B virus in a transmission chain and postulated that the 'colonization-adaptation-transmission' model can explain the differential impact of transmission on synonymous and non-synonymous substitution rates. Here, we revisit this dataset using a full probabilistic Bayesian phylogenetic framework that adequately accounts for the non-independence of sequence data when estimating evolutionary parameters. Examination of the transmission chain data under a flexible coalescent prior reveals a general inconsistency between the estimated timings and clustering patterns and the known transmission history, highlighting the need to incorporate host transmission information in the analysis. Using an explicit genealogical transmission chain model, we find strong support for a transmission-associated decrease of the overall evolutionary rate. However, in contrast to the initially reported larger transmission effect on non-synonymous substitution rate, we find a similar decrease in both non-synonymous and synonymous substitution rates that cannot be adequately explained by the colonization-adaptation-transmission model. An alternative explanation may involve a transmission/establishment advantage of hepatitis B virus variants that have accumulated fewer within-host substitutions, perhaps by spending more time in the covalently closed circular DNA state between each round of viral replication. More generally, this study illustrates that ignoring phylogenetic relationships can lead to misleading evolutionary estimates.

Historical and Contemporary DNA Indicate Fisher Decline and Isolation Occurred Prior to the European Settlement of California

PubMed Central

Tucker, Jody M.; Schwartz, Michael K.; Truex, Richard L.; Pilgrim, Kristine L.; Allendorf, Fred W.

2012-01-01

Establishing if species contractions were the result of natural phenomena or human induced landscape changes is essential for managing natural populations. Fishers (Martes pennanti) in California occur in two geographically and genetically isolated populations in the northwestern mountains and southern Sierra Nevada. Their isolation is hypothesized to have resulted from a decline in abundance and distribution associated with European settlement in the 1800s. However, there is little evidence to establish that fisher occupied the area between the two extant populations at that time. We analyzed 10 microsatellite loci from 275 contemporary and 21 historical fisher samples (1880–1920) to evaluate the demographic history of fisher in California. We did not find any evidence of a recent (post-European) bottleneck in the northwestern population. In the southern Sierra Nevada, genetic subdivision within the population strongly influenced bottleneck tests. After accounting for genetic subdivision, we found a bottleneck signal only in the northern and central portions of the southern Sierra Nevada, indicating that the southernmost tip of these mountains may have acted as a refugium for fisher during the anthropogenic changes of the late 19th and early 20th centuries. Using a coalescent-based Bayesian analysis, we detected a 90% decline in effective population size and dated the time of decline to over a thousand years ago. We hypothesize that fisher distribution in California contracted to the two current population areas pre-European settlement, and that portions of the southern Sierra Nevada subsequently experienced another more recent bottleneck post-European settlement. PMID:23300783

Spatiotemporal dynamics of influenza A(H1N1)pdm09 in Brazil during the pandemic and post-pandemic periods.

PubMed

Manito, Alessandra C B; Gräf, Tiago; Lunge, Vagner R; Ikuta, Nilo

2017-06-15

Influenza A(H1N1)pdm09 was responsible for the first global flu pandemic in 21st century affecting all the world. In Brazil, A(H1N1)pdm09 is still circulating as a seasonal virus, causing deaths every year. Nevertheless, the viral diffusion process that yearly seeds new influenza strains in the country was not investigated yet. The aim of the current study was to describe the phylodynamics and phylogeography of influenza A(H1N1)pdm09 in Brazil between 2009 and 2014. Neuraminidase sequences from Brazil and other regions of the World were retrieved and analyzed. Bayesian phylogeographic and phylodynamic model approaches were used to reconstruct the spatiotemporal and demographic history of influenza A(H1N1)pdm09 in Brazil (divided in subtropical and tropical regions) and related countries. Our analyses reveal that new influenza A(H1N1)pdm09 lineages are seeded in Brazil in almost each year and the main sources of viral diversity are North America, Europe and East Asia. The phylogeographic asymmetric model also revealed that Brazil, mainly the subtropical region, seeds viral lineages into other countries. Coalescent analysis of the compiled dataset reconstructed the peak of viral transmissions in the winter months of Southern hemisphere. The results presented in this study can be informative to public health, guide intervention strategies and in the understanding of flu virus migration, which helps to predict antigenic drift and consequently the developing of new vaccines. Copyright © 2017 Elsevier B.V. All rights reserved.

Detection of different reconnection regions from kinetic simulations during island coalescence after asymmetric magnetic reconnection

NASA Astrophysics Data System (ADS)

Cazzola, Emanuele; Berchem, Jean; Innocenti, Maria Elena; Goldman, Martin V.; Newman, David L.; Zhou, Meng; Lapenta, Giovanni

2017-04-01

In this work we present new results from fully kinetic simulations of the magnetic islands coalescence dynamics after asymmetric magnetic reconnection. In a previous work, we have shown that three different reconnection regions can be identified when a new frame of reference based on the local magnetic field is set. These regions were marked as X, D and M whether they describe, respectively, a traditional X-line event, an event between two diverging islands or an event between two merging islands [1, 2]. The results shown here extend the previous analysis to a more realistic regime, including a remarkable temperature transition across the current sheet. In particular, regions X, D, and M are also observed within this new regime, featuring yet new interesting characteristics. Special attention is given to the particles agyrotropic and anisotropic behavior as fundamental signatures for the detection of these regions with satellites. These results are timely for the ongoing MMS mission, whose data from the magnetopause crossing are presently being analyzed. In fact, data revealed that an intense flux-ropes activity takes place in this region of the magnetosphere, which makes the presence of this set of reconnection regions highly expected. [1] Cazzola, E., et al. "On the electron dynamics during island coalescence in asymmetric magnetic reconnection." Physics of Plasmas (1994-present) 22.9 (2015): 092901. [2] Cazzola, E., et al. "On the electron agyrotropy during rapid asymmetric magnetic island coalescence in presence of a guide field." Geophysical Research Letters 43.15 (2016): 7840-7849.

Bayesian Models for Astrophysical Data Using R, JAGS, Python, and Stan

NASA Astrophysics Data System (ADS)

Hilbe, Joseph M.; de Souza, Rafael S.; Ishida, Emille E. O.

2017-05-01

This comprehensive guide to Bayesian methods in astronomy enables hands-on work by supplying complete R, JAGS, Python, and Stan code, to use directly or to adapt. It begins by examining the normal model from both frequentist and Bayesian perspectives and then progresses to a full range of Bayesian generalized linear and mixed or hierarchical models, as well as additional types of models such as ABC and INLA. The book provides code that is largely unavailable elsewhere and includes details on interpreting and evaluating Bayesian models. Initial discussions offer models in synthetic form so that readers can easily adapt them to their own data; later the models are applied to real astronomical data. The consistent focus is on hands-on modeling, analysis of data, and interpretations that address scientific questions. A must-have for astronomers, its concrete approach will also be attractive to researchers in the sciences more generally.

Applying species-tree analyses to deep phylogenetic histories: challenges and potential suggested from a survey of empirical phylogenetic studies.

PubMed

Lanier, Hayley C; Knowles, L Lacey

2015-02-01

Coalescent-based methods for species-tree estimation are becoming a dominant approach for reconstructing species histories from multi-locus data, with most of the studies examining these methodologies focused on recently diverged species. However, deeper phylogenies, such as the datasets that comprise many Tree of Life (ToL) studies, also exhibit gene-tree discordance. This discord may also arise from the stochastic sorting of gene lineages during the speciation process (i.e., reflecting the random coalescence of gene lineages in ancestral populations). It remains unknown whether guidelines regarding methodologies and numbers of loci established by simulation studies at shallow tree depths translate into accurate species relationships for deeper phylogenetic histories. We address this knowledge gap and specifically identify the challenges and limitations of species-tree methods that account for coalescent variance for deeper phylogenies. Using simulated data with characteristics informed by empirical studies, we evaluate both the accuracy of estimated species trees and the characteristics associated with recalcitrant nodes, with a specific focus on whether coalescent variance is generally responsible for the lack of resolution. By determining the proportion of coalescent genealogies that support a particular node, we demonstrate that (1) species-tree methods account for coalescent variance at deep nodes and (2) mutational variance - not gene-tree discord arising from the coalescent - posed the primary challenge for accurate reconstruction across the tree. For example, many nodes were accurately resolved despite predicted discord from the random coalescence of gene lineages and nodes with poor support were distributed across a range of depths (i.e., they were not restricted to a particular recent divergences). Given their broad taxonomic scope and large sampling of taxa, deep level phylogenies pose several potential methodological complications including difficulties with MCMC convergence and estimation of requisite population genetic parameters for coalescent-based approaches. Despite these difficulties, the findings generally support the utility of species-tree analyses for the estimation of species relationships throughout the ToL. We discuss strategies for successful application of species-tree approaches to deep phylogenies. Copyright © 2014 Elsevier Inc. All rights reserved.

Destabilization of Oil-in-Water Emulsions Formed Using Highly Hydrolyzed Whey Proteins.

PubMed

Agboola; Singh; Munro; Dalgleish; Singh

1998-01-19

Oil-in-water emulsions (4 wt % soy oil) were prepared with 0.5-5 wt % whey protein hydrolysate (WPH) (27% degree of hydrolysis), in a two-stage homogenizer using various first-stage pressures of 10.3, 20.6, and 34.3 MPa and a constant second-stage pressure of 3.4 MPa. Destabilization studies on the emulsions were carried out for up to 24 h, using both laser light scattering and confocal laser microscopy. It was found that emulsions formed with <2% WPH showed oiling off and coalescence at all homogenization pressures. Emulsions formed with 2, 3, and 4% WPH showed coalescence and creaming only, while slight flocculation but no creaming occurred in emulsions formed with 5% WPH. Furthermore, the apparent rate of coalescence increased with homogenization pressure but decreased with WPH concentration. In contrast, the surface concentration of WPH increased with the WPH concentration in the emulsions but decreased with homogenization pressure. Analysis of WPH by high-performance liquid chromatography showed an increase in the concentration of high molecular weight peptides at the droplet surface compared to the WPH solution. This was considered very important for the stability of these oil-in-water emulsions.

Toward an ecological analysis of Bayesian inferences: how task characteristics influence responses

PubMed Central

Hafenbrädl, Sebastian; Hoffrage, Ulrich

2015-01-01

In research on Bayesian inferences, the specific tasks, with their narratives and characteristics, are typically seen as exchangeable vehicles that merely transport the structure of the problem to research participants. In the present paper, we explore whether, and possibly how, task characteristics that are usually ignored influence participants’ responses in these tasks. We focus on both quantitative dimensions of the tasks, such as their base rates, hit rates, and false-alarm rates, as well as qualitative characteristics, such as whether the task involves a norm violation or not, whether the stakes are high or low, and whether the focus is on the individual case or on the numbers. Using a data set of 19 different tasks presented to 500 different participants who provided a total of 1,773 responses, we analyze these responses in two ways: first, on the level of the numerical estimates themselves, and second, on the level of various response strategies, Bayesian and non-Bayesian, that might have produced the estimates. We identified various contingencies, and most of the task characteristics had an influence on participants’ responses. Typically, this influence has been stronger when the numerical information in the tasks was presented in terms of probabilities or percentages, compared to natural frequencies – and this effect cannot be fully explained by a higher proportion of Bayesian responses when natural frequencies were used. One characteristic that did not seem to influence participants’ response strategy was the numerical value of the Bayesian solution itself. Our exploratory study is a first step toward an ecological analysis of Bayesian inferences, and highlights new avenues for future research. PMID:26300791

Hip fracture in the elderly: a re-analysis of the EPIDOS study with causal Bayesian networks.

PubMed

Caillet, Pascal; Klemm, Sarah; Ducher, Michel; Aussem, Alexandre; Schott, Anne-Marie

2015-01-01

Hip fractures commonly result in permanent disability, institutionalization or death in elderly. Existing hip-fracture predicting tools are underused in clinical practice, partly due to their lack of intuitive interpretation. By use of a graphical layer, Bayesian network models could increase the attractiveness of fracture prediction tools. Our aim was to study the potential contribution of a causal Bayesian network in this clinical setting. A logistic regression was performed as a standard control approach to check the robustness of the causal Bayesian network approach. EPIDOS is a multicenter study, conducted in an ambulatory care setting in five French cities between 1992 and 1996 and updated in 2010. The study included 7598 women aged 75 years or older, in which fractures were assessed quarterly during 4 years. A causal Bayesian network and a logistic regression were performed on EPIDOS data to describe major variables involved in hip fractures occurrences. Both models had similar association estimations and predictive performances. They detected gait speed and mineral bone density as variables the most involved in the fracture process. The causal Bayesian network showed that gait speed and bone mineral density were directly connected to fracture and seem to mediate the influence of all the other variables included in our model. The logistic regression approach detected multiple interactions involving psychotropic drug use, age and bone mineral density. Both approaches retrieved similar variables as predictors of hip fractures. However, Bayesian network highlighted the whole web of relation between the variables involved in the analysis, suggesting a possible mechanism leading to hip fracture. According to the latter results, intervention focusing concomitantly on gait speed and bone mineral density may be necessary for an optimal prevention of hip fracture occurrence in elderly people.

Bayesian flood forecasting methods: A review

NASA Astrophysics Data System (ADS)

Han, Shasha; Coulibaly, Paulin

2017-08-01

Over the past few decades, floods have been seen as one of the most common and largely distributed natural disasters in the world. If floods could be accurately forecasted in advance, then their negative impacts could be greatly minimized. It is widely recognized that quantification and reduction of uncertainty associated with the hydrologic forecast is of great importance for flood estimation and rational decision making. Bayesian forecasting system (BFS) offers an ideal theoretic framework for uncertainty quantification that can be developed for probabilistic flood forecasting via any deterministic hydrologic model. It provides suitable theoretical structure, empirically validated models and reasonable analytic-numerical computation method, and can be developed into various Bayesian forecasting approaches. This paper presents a comprehensive review on Bayesian forecasting approaches applied in flood forecasting from 1999 till now. The review starts with an overview of fundamentals of BFS and recent advances in BFS, followed with BFS application in river stage forecasting and real-time flood forecasting, then move to a critical analysis by evaluating advantages and limitations of Bayesian forecasting methods and other predictive uncertainty assessment approaches in flood forecasting, and finally discusses the future research direction in Bayesian flood forecasting. Results show that the Bayesian flood forecasting approach is an effective and advanced way for flood estimation, it considers all sources of uncertainties and produces a predictive distribution of the river stage, river discharge or runoff, thus gives more accurate and reliable flood forecasts. Some emerging Bayesian forecasting methods (e.g. ensemble Bayesian forecasting system, Bayesian multi-model combination) were shown to overcome limitations of single model or fixed model weight and effectively reduce predictive uncertainty. In recent years, various Bayesian flood forecasting approaches have been developed and widely applied, but there is still room for improvements. Future research in the context of Bayesian flood forecasting should be on assimilation of various sources of newly available information and improvement of predictive performance assessment methods.

Applications of Bayesian Procrustes shape analysis to ensemble radar reflectivity nowcast verification

NASA Astrophysics Data System (ADS)

Fox, Neil I.; Micheas, Athanasios C.; Peng, Yuqiang

2016-07-01

This paper introduces the use of Bayesian full Procrustes shape analysis in object-oriented meteorological applications. In particular, the Procrustes methodology is used to generate mean forecast precipitation fields from a set of ensemble forecasts. This approach has advantages over other ensemble averaging techniques in that it can produce a forecast that retains the morphological features of the precipitation structures and present the range of forecast outcomes represented by the ensemble. The production of the ensemble mean avoids the problems of smoothing that result from simple pixel or cell averaging, while producing credible sets that retain information on ensemble spread. Also in this paper, the full Bayesian Procrustes scheme is used as an object verification tool for precipitation forecasts. This is an extension of a previously presented Procrustes shape analysis based verification approach into a full Bayesian format designed to handle the verification of precipitation forecasts that match objects from an ensemble of forecast fields to a single truth image. The methodology is tested on radar reflectivity nowcasts produced in the Warning Decision Support System - Integrated Information (WDSS-II) by varying parameters in the K-means cluster tracking scheme.

Bayesian analysis of non-homogeneous Markov chains: application to mental health data.

PubMed

Sung, Minje; Soyer, Refik; Nhan, Nguyen

2007-07-10

In this paper we present a formal treatment of non-homogeneous Markov chains by introducing a hierarchical Bayesian framework. Our work is motivated by the analysis of correlated categorical data which arise in assessment of psychiatric treatment programs. In our development, we introduce a Markovian structure to describe the non-homogeneity of transition patterns. In doing so, we introduce a logistic regression set-up for Markov chains and incorporate covariates in our model. We present a Bayesian model using Markov chain Monte Carlo methods and develop inference procedures to address issues encountered in the analyses of data from psychiatric treatment programs. Our model and inference procedures are implemented to some real data from a psychiatric treatment study. Copyright 2006 John Wiley & Sons, Ltd.

A FAST BAYESIAN METHOD FOR UPDATING AND FORECASTING HOURLY OZONE LEVELS

EPA Science Inventory

A Bayesian hierarchical space-time model is proposed by combining information from real-time ambient AIRNow air monitoring data, and output from a computer simulation model known as the Community Multi-scale Air Quality (Eta-CMAQ) forecast model. A model validation analysis shows...

Uncertainty estimation of a complex water quality model: The influence of Box-Cox transformation on Bayesian approaches and comparison with a non-Bayesian method

NASA Astrophysics Data System (ADS)

Freni, Gabriele; Mannina, Giorgio

In urban drainage modelling, uncertainty analysis is of undoubted necessity. However, uncertainty analysis in urban water-quality modelling is still in its infancy and only few studies have been carried out. Therefore, several methodological aspects still need to be experienced and clarified especially regarding water quality modelling. The use of the Bayesian approach for uncertainty analysis has been stimulated by its rigorous theoretical framework and by the possibility of evaluating the impact of new knowledge on the modelling predictions. Nevertheless, the Bayesian approach relies on some restrictive hypotheses that are not present in less formal methods like the Generalised Likelihood Uncertainty Estimation (GLUE). One crucial point in the application of Bayesian method is the formulation of a likelihood function that is conditioned by the hypotheses made regarding model residuals. Statistical transformations, such as the use of Box-Cox equation, are generally used to ensure the homoscedasticity of residuals. However, this practice may affect the reliability of the analysis leading to a wrong uncertainty estimation. The present paper aims to explore the influence of the Box-Cox equation for environmental water quality models. To this end, five cases were considered one of which was the “real” residuals distributions (i.e. drawn from available data). The analysis was applied to the Nocella experimental catchment (Italy) which is an agricultural and semi-urbanised basin where two sewer systems, two wastewater treatment plants and a river reach were monitored during both dry and wet weather periods. The results show that the uncertainty estimation is greatly affected by residual transformation and a wrong assumption may also affect the evaluation of model uncertainty. The use of less formal methods always provide an overestimation of modelling uncertainty with respect to Bayesian method but such effect is reduced if a wrong assumption is made regarding the residuals distribution. If residuals are not normally distributed, the uncertainty is over-estimated if Box-Cox transformation is not applied or non-calibrated parameter is used.

From nucleation to coalescence of Cu2O islands during in situ oxidation of Cu(001)

NASA Astrophysics Data System (ADS)

Yang, J. C.; Evan, D.; Tropia, L.

2002-07-01

The nucleation, growth, and coalescence of Cu2O islands due to oxidation of Cu(001) films were visualized by in situ ultrahigh-vacuum transmission electron microscopy. We have previously demonstrated that the nucleation and initial growth of copper oxides is dominated by oxygen surface diffusion. These surface models have been extended to quantitatively represent the coalescence behavior of copper oxidation in the framework of the Johnson-Mehl-Avrami-Kolmogorov theory. An excellent agreement exists between the experimental data of nucleation to coalescence with the surface model. The implication could be an alternate paradigm for passivation and oxidation, since classic theories assume uniform film growth.

Propagation of population pharmacokinetic information using a Bayesian approach: comparison with meta-analysis.

PubMed

Dokoumetzidis, Aristides; Aarons, Leon

2005-08-01

We investigated the propagation of population pharmacokinetic information across clinical studies by applying Bayesian techniques. The aim was to summarize the population pharmacokinetic estimates of a study in appropriate statistical distributions in order to use them as Bayesian priors in consequent population pharmacokinetic analyses. Various data sets of simulated and real clinical data were fitted with WinBUGS, with and without informative priors. The posterior estimates of fittings with non-informative priors were used to build parametric informative priors and the whole procedure was carried on in a consecutive manner. The posterior distributions of the fittings with informative priors where compared to those of the meta-analysis fittings of the respective combinations of data sets. Good agreement was found, for the simulated and experimental datasets when the populations were exchangeable, with the posterior distribution from the fittings with the prior to be nearly identical to the ones estimated with meta-analysis. However, when populations were not exchangeble an alternative parametric form for the prior, the natural conjugate prior, had to be used in order to have consistent results. In conclusion, the results of a population pharmacokinetic analysis may be summarized in Bayesian prior distributions that can be used consecutively with other analyses. The procedure is an alternative to meta-analysis and gives comparable results. It has the advantage that it is faster than the meta-analysis, due to the large datasets used with the latter and can be performed when the data included in the prior are not actually available.

A Development of Nonstationary Regional Frequency Analysis Model with Large-scale Climate Information: Its Application to Korean Watershed

NASA Astrophysics Data System (ADS)

Kim, Jin-Young; Kwon, Hyun-Han; Kim, Hung-Soo

2015-04-01

The existing regional frequency analysis has disadvantages in that it is difficult to consider geographical characteristics in estimating areal rainfall. In this regard, this study aims to develop a hierarchical Bayesian model based nonstationary regional frequency analysis in that spatial patterns of the design rainfall with geographical information (e.g. latitude, longitude and altitude) are explicitly incorporated. This study assumes that the parameters of Gumbel (or GEV distribution) are a function of geographical characteristics within a general linear regression framework. Posterior distribution of the regression parameters are estimated by Bayesian Markov Chain Monte Carlo (MCMC) method, and the identified functional relationship is used to spatially interpolate the parameters of the distributions by using digital elevation models (DEM) as inputs. The proposed model is applied to derive design rainfalls over the entire Han-river watershed. It was found that the proposed Bayesian regional frequency analysis model showed similar results compared to L-moment based regional frequency analysis. In addition, the model showed an advantage in terms of quantifying uncertainty of the design rainfall and estimating the area rainfall considering geographical information. Finally, comprehensive discussion on design rainfall in the context of nonstationary will be presented. KEYWORDS: Regional frequency analysis, Nonstationary, Spatial information, Bayesian Acknowledgement This research was supported by a grant (14AWMP-B082564-01) from Advanced Water Management Research Program funded by Ministry of Land, Infrastructure and Transport of Korean government.

Identification of specialists and abundance-occupancy relationships among intestinal bacteria of Aves, Mammalia, and Actinopterygii

EPA Science Inventory

The coalescence of next generation DNA sequencing methods, ecological perspectives, and bioinformatics analysis tools is rapidly advancing our understanding of the evolution and function of vertebrate-associated bacterial communities. Delineating host-microbial associations has a...

Coalescence of Spheromaks,

DTIC Science & Technology

1981-07-01

the fact that the toroidal field coil must link both the main and refueling plasma rings raises questions concerninq the practicality of repeated...also thread the main plasma ring .) The analysis of Ref. 17 also assumes axisymmetric reconnection and plasma incompressibility. We will see 5 that we

Pathway analysis of high-throughput biological data within a Bayesian network framework.

PubMed

Isci, Senol; Ozturk, Cengizhan; Jones, Jon; Otu, Hasan H

2011-06-15

Most current approaches to high-throughput biological data (HTBD) analysis either perform individual gene/protein analysis or, gene/protein set enrichment analysis for a list of biologically relevant molecules. Bayesian Networks (BNs) capture linear and non-linear interactions, handle stochastic events accounting for noise, and focus on local interactions, which can be related to causal inference. Here, we describe for the first time an algorithm that models biological pathways as BNs and identifies pathways that best explain given HTBD by scoring fitness of each network. Proposed method takes into account the connectivity and relatedness between nodes of the pathway through factoring pathway topology in its model. Our simulations using synthetic data demonstrated robustness of our approach. We tested proposed method, Bayesian Pathway Analysis (BPA), on human microarray data regarding renal cell carcinoma (RCC) and compared our results with gene set enrichment analysis. BPA was able to find broader and more specific pathways related to RCC. Accompanying BPA software (BPAS) package is freely available for academic use at http://bumil.boun.edu.tr/bpa.

Molecular phylogenetics reveals convergent evolution in lower Congo River spiny eels.

PubMed

Alter, S Elizabeth; Brown, Bianca; Stiassny, Melanie L J

2015-10-15

The lower Congo River (LCR) is a region of exceptional species diversity and endemism in the Congo basin, including numerous species of spiny eels (genus Mastacembelus). Four of these exhibit distinctive phenotypes characterized by greatly reduced optic globes deeply embedded into the head (cryptophthalmia) and reduced (or absent) melanin pigmentation, among other characteristics. A strikingly similar cryptophthalmic phenotype is also found in members of a number of unrelated fish families, strongly suggesting the possibility of convergent evolution. However, little is known about the evolutionary processes that shaped diversification in LCR Mastacembelus, their biogeographic origins, or when colonization of the LCR occurred. We sequenced mitochondrial and nuclear genes from Mastacembelus species collected in the lower Congo River, and compared them with other African species and Asian representatives as outgroups. We analyzed the sequence data using Maximum Likelihood and Bayesian phylogenetic inference. Bayesian and Maximum Likelihood phylogenetic analyses, and Bayesian coalescent methods for species tree reconstruction, reveal that endemic LCR spiny eels derive from two independent origins, clearly demonstrating convergent evolution of the cryptophthalmic phenotype. Mastacembelus crassus, M. aviceps, and M. simbi form a clade, allied to species found in southern, eastern and central Africa. Unexpectedly, M. brichardi and brachyrhinus fall within a clade otherwise endemic to Lake Tanganikya (LT) ca. 1500 km east of the LCR. Divergence dating suggests the ages of these two clades of LCR endemics differ markedly. The age of the crassus group is estimated at ~4 Myr while colonization of the LCR by the brichardi-brachyrhinus progenitor was considerably more recent, dated at ~0.5 Myr. The phylogenetic framework of spiny eels presented here, the first to include LCR species, demonstrates that cryptophthalmia and associated traits evolved at least twice in Mastacembelus: once in M. brichardi and at least once in the M. crassus clade. Timing of diversification is broadly consistent with the onset of modern high-energy flow conditions in the LCR and with previous studies of endemic cichlids. The close genetic relationship between M. brichardi and M. brachyrhinus is particularly notable given the extreme difference in phenotype between these species, and additional work is needed to better understand the evolutionary history of diversification in this clade. The findings presented here demonstrate strong, multi-trait convergence in LCR spiny eels, suggesting that extreme selective pressures have shaped numerous phenotypic attributes of the endemic species of this region.

Non-Coalescence Effects in Microgravity

NASA Technical Reports Server (NTRS)

Neitzel, G. Paul

1998-01-01

Non-coalescence of two bodies of the same liquid and the suppression of contact between liquid drops and solid surfaces is being studied through a pair of parallel investigations being conducted at the Georgia Institute of Technology and the Microgravity Research and Support (MARS) Center in Naples, Italy. Both non-coalescence and contact suppression are achieved by exploiting the mechanism of thermocapillary convection to drive a lubricating film of surrounding gas (air) into the space between the two liquid free surfaces (non-coalescence) or between the drop free surface and the solid (contact suppression). Earlier experiments performed included flow-visualization experiments in both axisymmetric and (nearly) two-dimensional geometries and quantitative measurements of film thickness in the contact-suppression case in both geometries. Work done in the second year has focused on obtaining quantitative results relating to the effects of variable air pressure, development of analytical and numerical models of non-coalescing droplets and to pursuing potential applications of these self-lubricated systems.

Interactions Forces and the Flow-Induced Coalescence of Drops and Bubbles

NASA Technical Reports Server (NTRS)

Leal, L. Gary; Israelachvili, J.

2004-01-01

In order to accomplish the proposed macroscale experimental goals, we designed and built a pair of miniaturized computer-controlled four-roll mills, similar but much smaller than the 4-roll mill that had been develop earlier in Prof. Leal's group for studies of drop deformation and breakup. This unique experimental facility allows for controlled experiments on the breakup and coalescence of very small drops in the size range of 20-200 micrometers in diameter for a wide variety of flows and under a wide range of flow conditions including time-dependent flows, etc. The small size of this device is necessary for coalescence studies, since coalescence occurs in viscous fluids at capillary numbers that are large enough to be experimentally accessible only for drops that are smaller than approximately 100_m in diameter. Using these miniaturized 4-roll mills, we have obtained the first quantitative data (so far as we are aware) on the flow-induced coalescence process.

Confinement of Screw Dislocations to Predetermined Lateral Positions in (0001) 4H-SiC Epilayers Using Homoepitaxial Web Growth

NASA Technical Reports Server (NTRS)

Neudeck, Philip G.; Spry, Andrew J.; Trunek, Andrew J.; Powell, J. Anthony; Beheim, Glenn M.

2002-01-01

This paper reports initial demonstration of a cantilevered homoepitaxial growth process that places screw dislocations at predetermined lateral positions in on-axis 4H-SiC mesa epilayers. Thin cantilevers were grown extending toward the interior of hollow pre-growth mesa shapes etched into an on-axis 4H-SiC wafer, eventually completely coalescing to form roofed cavities. Each completely coalesced cavity exhibited either: 1) a screw dislocation growth spiral located exactly where final cantilever coalescence occurred, or 2) no growth spiral. The fact that growth spirals are not observed at any other position except the central coalescence point suggests that substrate screw dislocations, initially surrounded by the hollow portion of the pre-growth mesa shape, are relocated to the final coalescence point of the webbed epilayer roof. Molten potassium hydroxide etch studies revealed that properly grown webbed cantilevers exhibited no etch pits, confirming the superior crystal quality of the cantilevers.

The Genealogical Consequences of Fecundity Variance Polymorphism

PubMed Central

Taylor, Jesse E.

2009-01-01

The genealogical consequences of within-generation fecundity variance polymorphism are studied using coalescent processes structured by genetic backgrounds. I show that these processes have three distinctive features. The first is that the coalescent rates within backgrounds are not jointly proportional to the infinitesimal variance, but instead depend only on the frequencies and traits of genotypes containing each allele. Second, the coalescent processes at unlinked loci are correlated with the genealogy at the selected locus; i.e., fecundity variance polymorphism has a genomewide impact on genealogies. Third, in diploid models, there are infinitely many combinations of fecundity distributions that have the same diffusion approximation but distinct coalescent processes; i.e., in this class of models, ancestral processes and allele frequency dynamics are not in one-to-one correspondence. Similar properties are expected to hold in models that allow for heritable variation in other traits that affect the coalescent effective population size, such as sex ratio or fecundity and survival schedules. PMID:19433628

A Bayesian method for using simulator data to enhance human error probabilities assigned by existing HRA methods

DOE PAGES

Groth, Katrina M.; Smith, Curtis L.; Swiler, Laura P.

2014-04-05

In the past several years, several international agencies have begun to collect data on human performance in nuclear power plant simulators [1]. This data provides a valuable opportunity to improve human reliability analysis (HRA), but there improvements will not be realized without implementation of Bayesian methods. Bayesian methods are widely used in to incorporate sparse data into models in many parts of probabilistic risk assessment (PRA), but Bayesian methods have not been adopted by the HRA community. In this article, we provide a Bayesian methodology to formally use simulator data to refine the human error probabilities (HEPs) assigned by existingmore » HRA methods. We demonstrate the methodology with a case study, wherein we use simulator data from the Halden Reactor Project to update the probability assignments from the SPAR-H method. The case study demonstrates the ability to use performance data, even sparse data, to improve existing HRA methods. Furthermore, this paper also serves as a demonstration of the value of Bayesian methods to improve the technical basis of HRA.« less

Balance of baryon number in the quark coalescence model

NASA Astrophysics Data System (ADS)

Bialas, A.; Rafelski, J.

2006-02-01

The charge and baryon balance functions are studied in the coalescence hadronization mechanism of quark-gluon plasma. Assuming that in the plasma phase the qqbar pairs form uncorrelated clusters whose decay is also uncorrelated, one can understand the observed small width of the charge balance function in the Gaussian approximation. The coalescence model predicts even smaller width of the baryon-antibaryon balance function: σBBbar /σ+ - =√{ 2 / 3 }.

A dual-core double emulsion platform for osmolarity-controlled microreactor triggered by coalescence of encapsulated droplets.

PubMed

Guan, Xuewei; Hou, Likai; Ren, Yukun; Deng, Xiaokang; Lang, Qi; Jia, Yankai; Hu, Qingming; Tao, Ye; Liu, Jiangwei; Jiang, Hongyuan

2016-05-01

Droplet-based microfluidics has provided a means to generate multi-core double emulsions, which are versatile platforms for microreactors in materials science, synthetic biology, and chemical engineering. To provide new opportunities for double emulsion platforms, here, we report a glass capillary microfluidic approach to first fabricate osmolarity-responsive Water-in-Oil-in-Water (W/O/W) double emulsion containing two different inner droplets/cores and to then trigger the coalescence between the encapsulated droplets precisely. To achieve this, we independently control the swelling speed and size of each droplet in the dual-core double emulsion by controlling the osmotic pressure between the inner droplets and the collection solutions. When the inner two droplets in one W/O/W double emulsion swell to the same size and reach the instability of the oil film interface between the inner droplets, core-coalescence happens and this coalescence process can be controlled precisely. This microfluidic methodology enables the generation of highly monodisperse dual-core double emulsions and the osmolarity-controlled swelling behavior provides new stimuli to trigger the coalescence between the encapsulated droplets. Such swelling-caused core-coalescence behavior in dual-core double emulsion establishes a novel microreactor for nanoliter-scale reactions, which can protect reaction materials and products from being contaminated or released.

A dual-core double emulsion platform for osmolarity-controlled microreactor triggered by coalescence of encapsulated droplets

PubMed Central

Guan, Xuewei; Hou, Likai; Ren, Yukun; Deng, Xiaokang; Lang, Qi; Jia, Yankai; Hu, Qingming; Tao, Ye; Liu, Jiangwei; Jiang, Hongyuan

2016-01-01

Droplet-based microfluidics has provided a means to generate multi-core double emulsions, which are versatile platforms for microreactors in materials science, synthetic biology, and chemical engineering. To provide new opportunities for double emulsion platforms, here, we report a glass capillary microfluidic approach to first fabricate osmolarity-responsive Water-in-Oil-in-Water (W/O/W) double emulsion containing two different inner droplets/cores and to then trigger the coalescence between the encapsulated droplets precisely. To achieve this, we independently control the swelling speed and size of each droplet in the dual-core double emulsion by controlling the osmotic pressure between the inner droplets and the collection solutions. When the inner two droplets in one W/O/W double emulsion swell to the same size and reach the instability of the oil film interface between the inner droplets, core-coalescence happens and this coalescence process can be controlled precisely. This microfluidic methodology enables the generation of highly monodisperse dual-core double emulsions and the osmolarity-controlled swelling behavior provides new stimuli to trigger the coalescence between the encapsulated droplets. Such swelling-caused core-coalescence behavior in dual-core double emulsion establishes a novel microreactor for nanoliter-scale reactions, which can protect reaction materials and products from being contaminated or released. PMID:27279935

Estimating trace-suspect match probabilities for singleton Y-STR haplotypes using coalescent theory.

PubMed

Andersen, Mikkel Meyer; Caliebe, Amke; Jochens, Arne; Willuweit, Sascha; Krawczak, Michael

2013-02-01

Estimation of match probabilities for singleton haplotypes of lineage markers, i.e. for haplotypes observed only once in a reference database augmented by a suspect profile, is an important problem in forensic genetics. We compared the performance of four estimators of singleton match probabilities for Y-STRs, namely the count estimate, both with and without Brenner's so-called 'kappa correction', the surveying estimate, and a previously proposed, but rarely used, coalescent-based approach implemented in the BATWING software. Extensive simulation with BATWING of the underlying population history, haplotype evolution and subsequent database sampling revealed that the coalescent-based approach is characterized by lower bias and lower mean squared error than the uncorrected count estimator and the surveying estimator. Moreover, in contrast to the two count estimators, both the surveying and the coalescent-based approach exhibited a good correlation between the estimated and true match probabilities. However, although its overall performance is thus better than that of any other recognized method, the coalescent-based estimator is still computation-intense on the verge of general impracticability. Its application in forensic practice therefore will have to be limited to small reference databases, or to isolated cases of particular interest, until more powerful algorithms for coalescent simulation have become available. Copyright © 2012 Elsevier Ireland Ltd. All rights reserved.

Lateral vegetation growth rates exert control on coastal foredune hummockiness and coalescing time

NASA Astrophysics Data System (ADS)

Goldstein, Evan B.; Moore, Laura J.; Durán Vinent, Orencio

2017-08-01

Coastal foredunes form along sandy, low-sloped coastlines and range in shape from continuous dune ridges to hummocky features, which are characterized by alongshore-variable dune crest elevations. Initially scattered dune-building plants and species that grow slowly in the lateral direction have been implicated as a cause of foredune hummockiness. Our goal in this work is to explore how the initial configuration of vegetation and vegetation growth characteristics control the development of hummocky coastal dunes including the maximum hummockiness of a given dune field. We find that given sufficient time and absent external forcing, hummocky foredunes coalesce to form continuous dune ridges. Model results yield a predictive rule for the timescale of coalescing and the height of the coalesced dune that depends on initial plant dispersal and two parameters that control the lateral and vertical growth of vegetation, respectively. Our findings agree with previous observational and conceptual work - whether or not hummockiness will be maintained depends on the timescale of coalescing relative to the recurrence interval of high-water events that reset dune building in low areas between hummocks. Additionally, our model reproduces the observed tendency for foredunes to be hummocky along the southeast coast of the US where lateral vegetation growth rates are slower and thus coalescing times are likely longer.

Data Envelopment Analysis in the Presence of Measurement Error: Case Study from the National Database of Nursing Quality Indicators® (NDNQI®)

PubMed Central

Gajewski, Byron J.; Lee, Robert; Dunton, Nancy

2012-01-01

Data Envelopment Analysis (DEA) is the most commonly used approach for evaluating healthcare efficiency (Hollingsworth, 2008), but a long-standing concern is that DEA assumes that data are measured without error. This is quite unlikely, and DEA and other efficiency analysis techniques may yield biased efficiency estimates if it is not realized (Gajewski, Lee, Bott, Piamjariyakul and Taunton, 2009; Ruggiero, 2004). We propose to address measurement error systematically using a Bayesian method (Bayesian DEA). We will apply Bayesian DEA to data from the National Database of Nursing Quality Indicators® (NDNQI®) to estimate nursing units’ efficiency. Several external reliability studies inform the posterior distribution of the measurement error on the DEA variables. We will discuss the case of generalizing the approach to situations where an external reliability study is not feasible. PMID:23328796

Prevalence of cryptic species in morphologically uniform taxa - fast speciation and evolutionary radiation in Asian toads.

PubMed

Liu, Zuyao; Chen, Guoling; Zhu, Tianqi; Zeng, Zhaochi; Lyu, Zhitong; Wang, Jian; Messenger, Kevin; Greenberg, Anthony J; Guo, Zixiao; Yang, Ziheng; Shi, Suhua; Wang, Yingyong

2018-06-16

Diversity and distributions of cryptic species have long been a vexing issue. Identification of species boundaries is made difficult by the lack of obvious morphological differences. Here, we investigate the cryptic diversity and evolutionary history of an underappreciated group of Asian frog species (Megophrys) to explore the pattern and dynamic of amphibian cryptic species. We sequenced four mitochondrial genes and five nuclear genes and delineated species using multiple approaches, combining DNA and mating-call data. A Bayesian species tree was generated to estimate divergence times and to reconstruct ancestral ranges. Macroevolutionary analyses and hybridization tests were conducted to explore the evolutionary dynamics of this cryptic group. Our phylogenies support the current subgenera. We revealed 43 cryptic species, 158% higher than previously thought. The species-delimitation results were further confirmed by mating-call data and morphological divergence. We found that these Asian frogss entered China from the Sunda Shelf 48 Mya, followed by an ancient radiation event during middle Miocene. We confirmed the efficiency of the multispecies coalescent model for delimitation of species with low morphological diversity. Species diversity of Megophrys is severely underappreciated, and species distributions have been misestimated as a result. Copyright © 2018. Published by Elsevier Inc.

Evolution and dispersal of St. Louis encephalitis virus in the Americas.

PubMed

Auguste, Albert J; Pybus, Oliver G; Carrington, Christine V F

2009-07-01

Using a Bayesian coalescent approach on a dataset of 73 envelope gene sequences we estimated substitution rates and dates of divergence for St. Louis encephalitis virus (SLEV) in the Americas. We found significant rate heterogeneity among lineages, such that "relaxed" molecular clock models were much better supported than a strict molecular clock. The mean substitution rate estimated for all SLEV was 4.1x10(-4)substitutions/site/year (95% HPD 2.5-5.7)-higher than previous estimates that relied on the less well-suited strict clock. Mean substitution rates for individual lineages varied from 3.7x10(-4) to 7.2x10(-4)substitutions/site/year. For the first time we also assessed the magnitude and direction of viral gene flow within the Americas. The overall direction of gene flow during the period represented by the phylogeny is from South to North, and the region between 15 degrees N and 30 degrees N latitude appears to be the major source of virus for the rest of North America, which is consistent with migratory birds returning to their northern breeding grounds having acquired infection while wintering in the region of the Gulf of Mexico.

Fermentation broth components influence droplet coalescence and hinder advanced biofuel recovery during fermentation.

PubMed

Heeres, Arjan S; Schroën, Karin; Heijnen, Joseph J; van der Wielen, Luuk A M; Cuellar, Maria C

2015-08-01

Developments in synthetic biology enabled the microbial production of long chain hydrocarbons, which can be used as advanced biofuels in aviation or transportation. Currently, these fuels are not economically competitive due to their production costs. The current process offers room for improvement: by utilizing lignocellulosic feedstock, increasing microbial yields, and using cheaper process technology. Gravity separation is an example of the latter, for which droplet growth by coalescence is crucial. The aim of this study was to study the effect of fermentation broth components on droplet coalescence. Droplet coalescence was measured using two setups: a microfluidic chip and regular laboratory scale stirred vessel (2 L). Some fermentation broth components had a large impact on droplet coalescence. Especially components present in hydrolysed cellulosic biomass and mannoproteins from the yeast cell wall retard coalescence. To achieve a technically feasible gravity separation that can be integrated with the fermentation, the negative effects of these components on coalescence should be minimized. This could be achieved by redesign of the fermentation medium or adjusting the fermentation conditions, aiming to minimize the release of surface active components by the microorganisms. This way, another step can be made towards economically feasible advanced biofuel production. © 2015 The Authors. Biotechnology Journal published by Wiley-VCH Verlag GmbH & Co. KGaA, Weinheim. This is an open access article under the terms of the Creative Commons Attribution-Non-Commercial-NoDerivs Licence, which permits use and distribution in any medium, provided the original work is properly cited, the use is non-commercial and no modifications or adaptations are made.

Electrohydrodynamic coalescence of droplets using an embedded potential flow model

NASA Astrophysics Data System (ADS)

Garzon, M.; Gray, L. J.; Sethian, J. A.

2018-03-01

The coalescence, and subsequent satellite formation, of two inviscid droplets is studied numerically. The initial drops are taken to be of equal and different sizes, and simulations have been carried out with and without the presence of an electrical field. The main computational challenge is the tracking of a free surface that changes topology. Coupling level set and boundary integral methods with an embedded potential flow model, we seamlessly compute through these singular events. As a consequence, the various coalescence modes that appear depending upon the relative ratio of the parent droplets can be studied. Computations of first stage pinch-off, second stage pinch-off, and complete engulfment are analyzed and compared to recent numerical studies and laboratory experiments. Specifically, we study the evolution of bridge radii and the related scaling laws, the minimum drop radii evolution from coalescence to satellite pinch-off, satellite sizes, and the upward stretching of the near cylindrical protrusion at the droplet top. Clear evidence of partial coalescence self-similarity is presented for parent droplet ratios between 1.66 and 4. This has been possible due to the fact that computational initial conditions only depend upon the mother droplet size, in contrast with laboratory experiments where the difficulty in establishing the same initial physical configuration is well known. The presence of electric forces changes the coalescence patterns, and it is possible to control the satellite droplet size by tuning the electrical field intensity. All of the numerical results are in very good agreement with recent laboratory experiments for water droplet coalescence.

Bayesian approach for counting experiment statistics applied to a neutrino point source analysis

NASA Astrophysics Data System (ADS)

Bose, D.; Brayeur, L.; Casier, M.; de Vries, K. D.; Golup, G.; van Eijndhoven, N.

2013-12-01

In this paper we present a model independent analysis method following Bayesian statistics to analyse data from a generic counting experiment and apply it to the search for neutrinos from point sources. We discuss a test statistic defined following a Bayesian framework that will be used in the search for a signal. In case no signal is found, we derive an upper limit without the introduction of approximations. The Bayesian approach allows us to obtain the full probability density function for both the background and the signal rate. As such, we have direct access to any signal upper limit. The upper limit derivation directly compares with a frequentist approach and is robust in the case of low-counting observations. Furthermore, it allows also to account for previous upper limits obtained by other analyses via the concept of prior information without the need of the ad hoc application of trial factors. To investigate the validity of the presented Bayesian approach, we have applied this method to the public IceCube 40-string configuration data for 10 nearby blazars and we have obtained a flux upper limit, which is in agreement with the upper limits determined via a frequentist approach. Furthermore, the upper limit obtained compares well with the previously published result of IceCube, using the same data set.

Comparing interval estimates for small sample ordinal CFA models

PubMed Central

Natesan, Prathiba

2015-01-01

Robust maximum likelihood (RML) and asymptotically generalized least squares (AGLS) methods have been recommended for fitting ordinal structural equation models. Studies show that some of these methods underestimate standard errors. However, these studies have not investigated the coverage and bias of interval estimates. An estimate with a reasonable standard error could still be severely biased. This can only be known by systematically investigating the interval estimates. The present study compares Bayesian, RML, and AGLS interval estimates of factor correlations in ordinal confirmatory factor analysis models (CFA) for small sample data. Six sample sizes, 3 factor correlations, and 2 factor score distributions (multivariate normal and multivariate mildly skewed) were studied. Two Bayesian prior specifications, informative and relatively less informative were studied. Undercoverage of confidence intervals and underestimation of standard errors was common in non-Bayesian methods. Underestimated standard errors may lead to inflated Type-I error rates. Non-Bayesian intervals were more positive biased than negatively biased, that is, most intervals that did not contain the true value were greater than the true value. Some non-Bayesian methods had non-converging and inadmissible solutions for small samples and non-normal data. Bayesian empirical standard error estimates for informative and relatively less informative priors were closer to the average standard errors of the estimates. The coverage of Bayesian credibility intervals was closer to what was expected with overcoverage in a few cases. Although some Bayesian credibility intervals were wider, they reflected the nature of statistical uncertainty that comes with the data (e.g., small sample). Bayesian point estimates were also more accurate than non-Bayesian estimates. The results illustrate the importance of analyzing coverage and bias of interval estimates, and how ignoring interval estimates can be misleading. Therefore, editors and policymakers should continue to emphasize the inclusion of interval estimates in research. PMID:26579002

Comparing interval estimates for small sample ordinal CFA models.

PubMed

Natesan, Prathiba

2015-01-01

Robust maximum likelihood (RML) and asymptotically generalized least squares (AGLS) methods have been recommended for fitting ordinal structural equation models. Studies show that some of these methods underestimate standard errors. However, these studies have not investigated the coverage and bias of interval estimates. An estimate with a reasonable standard error could still be severely biased. This can only be known by systematically investigating the interval estimates. The present study compares Bayesian, RML, and AGLS interval estimates of factor correlations in ordinal confirmatory factor analysis models (CFA) for small sample data. Six sample sizes, 3 factor correlations, and 2 factor score distributions (multivariate normal and multivariate mildly skewed) were studied. Two Bayesian prior specifications, informative and relatively less informative were studied. Undercoverage of confidence intervals and underestimation of standard errors was common in non-Bayesian methods. Underestimated standard errors may lead to inflated Type-I error rates. Non-Bayesian intervals were more positive biased than negatively biased, that is, most intervals that did not contain the true value were greater than the true value. Some non-Bayesian methods had non-converging and inadmissible solutions for small samples and non-normal data. Bayesian empirical standard error estimates for informative and relatively less informative priors were closer to the average standard errors of the estimates. The coverage of Bayesian credibility intervals was closer to what was expected with overcoverage in a few cases. Although some Bayesian credibility intervals were wider, they reflected the nature of statistical uncertainty that comes with the data (e.g., small sample). Bayesian point estimates were also more accurate than non-Bayesian estimates. The results illustrate the importance of analyzing coverage and bias of interval estimates, and how ignoring interval estimates can be misleading. Therefore, editors and policymakers should continue to emphasize the inclusion of interval estimates in research.

A Bayesian Missing Data Framework for Generalized Multiple Outcome Mixed Treatment Comparisons

ERIC Educational Resources Information Center

Hong, Hwanhee; Chu, Haitao; Zhang, Jing; Carlin, Bradley P.

2016-01-01

Bayesian statistical approaches to mixed treatment comparisons (MTCs) are becoming more popular because of their flexibility and interpretability. Many randomized clinical trials report multiple outcomes with possible inherent correlations. Moreover, MTC data are typically sparse (although richer than standard meta-analysis, comparing only two…

Multi-Scale Validation of a Nanodiamond Drug Delivery System and Multi-Scale Engineering Education

ERIC Educational Resources Information Center

Schwalbe, Michelle Kristin

2010-01-01

This dissertation has two primary concerns: (i) evaluating the uncertainty and prediction capabilities of a nanodiamond drug delivery model using Bayesian calibration and bias correction, and (ii) determining conceptual difficulties of multi-scale analysis from an engineering education perspective. A Bayesian uncertainty quantification scheme…

Bayesian Adaptive Lasso for Ordinal Regression with Latent Variables

ERIC Educational Resources Information Center

Feng, Xiang-Nan; Wu, Hao-Tian; Song, Xin-Yuan

2017-01-01

We consider an ordinal regression model with latent variables to investigate the effects of observable and latent explanatory variables on the ordinal responses of interest. Each latent variable is characterized by correlated observed variables through a confirmatory factor analysis model. We develop a Bayesian adaptive lasso procedure to conduct…

IMPLICATIONS OF USING ROBUST BAYESIAN ANALYSIS TO REPRESENT DIVERSE SOURCES OF UNCERTAINTY IN INTEGRATED ASSESSMENT

EPA Science Inventory

In our previous research, we showed that robust Bayesian methods can be used in environmental modeling to define a set of probability distributions for key parameters that captures the effects of expert disagreement, ambiguity, or ignorance. This entire set can then be update...

Pig Data and Bayesian Inference on Multinomial Probabilities

ERIC Educational Resources Information Center

Kern, John C.

2006-01-01

Bayesian inference on multinomial probabilities is conducted based on data collected from the game Pass the Pigs[R]. Prior information on these probabilities is readily available from the instruction manual, and is easily incorporated in a Dirichlet prior. Posterior analysis of the scoring probabilities quantifies the discrepancy between empirical…

Bayesian inference of the number of factors in gene-expression analysis: application to human virus challenge studies.

PubMed

Chen, Bo; Chen, Minhua; Paisley, John; Zaas, Aimee; Woods, Christopher; Ginsburg, Geoffrey S; Hero, Alfred; Lucas, Joseph; Dunson, David; Carin, Lawrence

2010-11-09

Nonparametric Bayesian techniques have been developed recently to extend the sophistication of factor models, allowing one to infer the number of appropriate factors from the observed data. We consider such techniques for sparse factor analysis, with application to gene-expression data from three virus challenge studies. Particular attention is placed on employing the Beta Process (BP), the Indian Buffet Process (IBP), and related sparseness-promoting techniques to infer a proper number of factors. The posterior density function on the model parameters is computed using Gibbs sampling and variational Bayesian (VB) analysis. Time-evolving gene-expression data are considered for respiratory syncytial virus (RSV), Rhino virus, and influenza, using blood samples from healthy human subjects. These data were acquired in three challenge studies, each executed after receiving institutional review board (IRB) approval from Duke University. Comparisons are made between several alternative means of per-forming nonparametric factor analysis on these data, with comparisons as well to sparse-PCA and Penalized Matrix Decomposition (PMD), closely related non-Bayesian approaches. Applying the Beta Process to the factor scores, or to the singular values of a pseudo-SVD construction, the proposed algorithms infer the number of factors in gene-expression data. For real data the "true" number of factors is unknown; in our simulations we consider a range of noise variances, and the proposed Bayesian models inferred the number of factors accurately relative to other methods in the literature, such as sparse-PCA and PMD. We have also identified a "pan-viral" factor of importance for each of the three viruses considered in this study. We have identified a set of genes associated with this pan-viral factor, of interest for early detection of such viruses based upon the host response, as quantified via gene-expression data.

Metis: A Pure Metropolis Markov Chain Monte Carlo Bayesian Inference Library

DOE Office of Scientific and Technical Information (OSTI.GOV)

Bates, Cameron Russell; Mckigney, Edward Allen

The use of Bayesian inference in data analysis has become the standard for large scienti c experiments [1, 2]. The Monte Carlo Codes Group(XCP-3) at Los Alamos has developed a simple set of algorithms currently implemented in C++ and Python to easily perform at-prior Markov Chain Monte Carlo Bayesian inference with pure Metropolis sampling. These implementations are designed to be user friendly and extensible for customization based on speci c application requirements. This document describes the algorithmic choices made and presents two use cases.

CRAFT (complete reduction to amplitude frequency table)--robust and time-efficient Bayesian approach for quantitative mixture analysis by NMR.

PubMed

Krishnamurthy, Krish

2013-12-01

The intrinsic quantitative nature of NMR is increasingly exploited in areas ranging from complex mixture analysis (as in metabolomics and reaction monitoring) to quality assurance/control. Complex NMR spectra are more common than not, and therefore, extraction of quantitative information generally involves significant prior knowledge and/or operator interaction to characterize resonances of interest. Moreover, in most NMR-based metabolomic experiments, the signals from metabolites are normally present as a mixture of overlapping resonances, making quantification difficult. Time-domain Bayesian approaches have been reported to be better than conventional frequency-domain analysis at identifying subtle changes in signal amplitude. We discuss an approach that exploits Bayesian analysis to achieve a complete reduction to amplitude frequency table (CRAFT) in an automated and time-efficient fashion - thus converting the time-domain FID to a frequency-amplitude table. CRAFT uses a two-step approach to FID analysis. First, the FID is digitally filtered and downsampled to several sub FIDs, and secondly, these sub FIDs are then modeled as sums of decaying sinusoids using the Bayesian approach. CRAFT tables can be used for further data mining of quantitative information using fingerprint chemical shifts of compounds of interest and/or statistical analysis of modulation of chemical quantity in a biological study (metabolomics) or process study (reaction monitoring) or quality assurance/control. The basic principles behind this approach as well as results to evaluate the effectiveness of this approach in mixture analysis are presented. Copyright © 2013 John Wiley & Sons, Ltd.

Containing Revolutionary Islam: Reassessing the Problem and the Approach

DTIC Science & Technology

2017-03-01

2011), xx. 83 Russ Rodgers, Fundamentals of Islamic Asymmetric Warfare: A Documentary Analysis of the Principles of Muhammad (Lewiston, NY: Edwin...have not yet effectively coalesced or managed to spark the greater revolution they seek. They remain fragmented, choosing divergent activities in...Libertarian Rebuttal. Auburn, AL: Ludwig von Mises Institute, 2015. Rodgers, Russ. Fundamentals of Islamic Asymmetric Warfare: A Documentary Analysis

Microstructural Evolution of HSLA ISO 3183 X80M (API 5L X80) Friction Stir Welded Joints

NASA Astrophysics Data System (ADS)

Hermenegildo, Tahiana F. C.; Santos, Tiago F. A.; Torres, Edwar A.; Afonso, Conrado R. M.; Ramirez, Antonio J.

2018-03-01

Evaluation was made of friction stir welded joints, identifying conditions that resulted in satisfactory welded joints free from defects and with microstructural characteristics that provided good mechanical properties. Microstructural characterization and cooling curve analysis of the joints with lower and higher heat inputs evidenced deformation below and above the non-recrystallization temperature (Tnr) and dynamic recrystallization during microstructural evolution. Microscopy analyses showed acicular ferrite, bainitic ferrite, and coalesced bainite microstructures in the stir zone of the cold weld (lower heat input), while the stir zone of the hot weld (higher heat input) contained bainitic ferrite, acicular ferrite, coalesced bainite, martensite, and dispersed carbides. Granular bainite and dispersed carbides were observed in all the heat affected zones. Analysis of the microstructural transformations, together with the thermal history of the joints, showed that the variable that had the greatest influence on the morphology of the bainite (granular bainite/bainitic ferrite) was the deformation temperature.

Non-Coalescence Effects in Microgravity

NASA Technical Reports Server (NTRS)

Neitzel, G. Paul

1997-01-01

Non-coalescence of two bodies of the same liquid and the suppression of contact between liquid drops and solid surfaces is being studied through a pair of parallel investigations being conducted at the Georgia Institute of Technology and the Microgravity Research and Support (MARS) Center in Naples, Italy. Both non-coalescence and contact suppression are achieved by exploiting the mechanism of thermocapillary convection to drive a lubricating film of surrounding gas (air) into the space between the two liquid free surfaces (non-coalescence) or between the drop free surface and the solid (contact suppression). Experiments performed to date include flow visualization experiments in both axisymmetric and (nearly) two-dimensional geometries and quantitative measurements of film thickness in the contact-suppression case in both geometries.

Bayesian coronal seismology

NASA Astrophysics Data System (ADS)

Arregui, Iñigo

2018-01-01

In contrast to the situation in a laboratory, the study of the solar atmosphere has to be pursued without direct access to the physical conditions of interest. Information is therefore incomplete and uncertain and inference methods need to be employed to diagnose the physical conditions and processes. One of such methods, solar atmospheric seismology, makes use of observed and theoretically predicted properties of waves to infer plasma and magnetic field properties. A recent development in solar atmospheric seismology consists in the use of inversion and model comparison methods based on Bayesian analysis. In this paper, the philosophy and methodology of Bayesian analysis are first explained. Then, we provide an account of what has been achieved so far from the application of these techniques to solar atmospheric seismology and a prospect of possible future extensions.

Bayesian evidence computation for model selection in non-linear geoacoustic inference problems.

PubMed

Dettmer, Jan; Dosso, Stan E; Osler, John C

2010-12-01

This paper applies a general Bayesian inference approach, based on Bayesian evidence computation, to geoacoustic inversion of interface-wave dispersion data. Quantitative model selection is carried out by computing the evidence (normalizing constants) for several model parameterizations using annealed importance sampling. The resulting posterior probability density estimate is compared to estimates obtained from Metropolis-Hastings sampling to ensure consistent results. The approach is applied to invert interface-wave dispersion data collected on the Scotian Shelf, off the east coast of Canada for the sediment shear-wave velocity profile. Results are consistent with previous work on these data but extend the analysis to a rigorous approach including model selection and uncertainty analysis. The results are also consistent with core samples and seismic reflection measurements carried out in the area.

A Bayesian Approach for Evaluation of Determinants of Health System Efficiency Using Stochastic Frontier Analysis and Beta Regression.

PubMed

Şenel, Talat; Cengiz, Mehmet Ali

2016-01-01

In today's world, Public expenditures on health are one of the most important issues for governments. These increased expenditures are putting pressure on public budgets. Therefore, health policy makers have focused on the performance of their health systems and many countries have introduced reforms to improve the performance of their health systems. This study investigates the most important determinants of healthcare efficiency for OECD countries using second stage approach for Bayesian Stochastic Frontier Analysis (BSFA). There are two steps in this study. First we measure 29 OECD countries' healthcare efficiency by BSFA using the data from the OECD Health Database. At second stage, we expose the multiple relationships between the healthcare efficiency and characteristics of healthcare systems across OECD countries using Bayesian beta regression.

Aminoglycoside Therapy Manager: An Advanced Computer Program for Decision Support for Drug Dosing and Therapeutic Monitoring

PubMed Central

Lenert, Leslie; Lurie, Jon; Coleman, Robert; Klosterman, Heidrun; Blaschke, Terrence

1990-01-01

In this paper, we will describe an advanced drug dosing program, Aminoglycoside Therapy Manager that reasons using Bayesian pharmacokinetic modeling and symbolic modeling of patient status and drug response. Our design is similar to the design of the Digitalis Therapy Advisor program, but extends previous work by incorporating a Bayesian pharmacokinetic model, a “meta-level” analysis of drug concentrations to identify sampling errors and changes in pharmacokinetics, and including the results of the “meta-level” analysis in reasoning for dosing and therapeutic monitoring recommendations. The program is user friendly and runs on low cost general-purpose hardware. Validation studies show that the program is as accurate in predicting future drug concentrations as an expert using commercial Bayesian forecasting software.

Applications of Bayesian spectrum representation in acoustics

NASA Astrophysics Data System (ADS)

Botts, Jonathan M.

This dissertation utilizes a Bayesian inference framework to enhance the solution of inverse problems where the forward model maps to acoustic spectra. A Bayesian solution to filter design inverts a acoustic spectra to pole-zero locations of a discrete-time filter model. Spatial sound field analysis with a spherical microphone array is a data analysis problem that requires inversion of spatio-temporal spectra to directions of arrival. As with many inverse problems, a probabilistic analysis results in richer solutions than can be achieved with ad-hoc methods. In the filter design problem, the Bayesian inversion results in globally optimal coefficient estimates as well as an estimate the most concise filter capable of representing the given spectrum, within a single framework. This approach is demonstrated on synthetic spectra, head-related transfer function spectra, and measured acoustic reflection spectra. The Bayesian model-based analysis of spatial room impulse responses is presented as an analogous problem with equally rich solution. The model selection mechanism provides an estimate of the number of arrivals, which is necessary to properly infer the directions of simultaneous arrivals. Although, spectrum inversion problems are fairly ubiquitous, the scope of this dissertation has been limited to these two and derivative problems. The Bayesian approach to filter design is demonstrated on an artificial spectrum to illustrate the model comparison mechanism and then on measured head-related transfer functions to show the potential range of application. Coupled with sampling methods, the Bayesian approach is shown to outperform least-squares filter design methods commonly used in commercial software, confirming the need for a global search of the parameter space. The resulting designs are shown to be comparable to those that result from global optimization methods, but the Bayesian approach has the added advantage of a filter length estimate within the same unified framework. The application to reflection data is useful for representing frequency-dependent impedance boundaries in finite difference acoustic simulations. Furthermore, since the filter transfer function is a parametric model, it can be modified to incorporate arbitrary frequency weighting and account for the band-limited nature of measured reflection spectra. Finally, the model is modified to compensate for dispersive error in the finite difference simulation, from the filter design process. Stemming from the filter boundary problem, the implementation of pressure sources in finite difference simulation is addressed in order to assure that schemes properly converge. A class of parameterized source functions is proposed and shown to offer straightforward control of residual error in the simulation. Guided by the notion that the solution to be approximated affects the approximation error, sources are designed which reduce residual dispersive error to the size of round-off errors. The early part of a room impulse response can be characterized by a series of isolated plane waves. Measured with an array of microphones, plane waves map to a directional response of the array or spatial intensity map. Probabilistic inversion of this response results in estimates of the number and directions of image source arrivals. The model-based inversion is shown to avoid ambiguities associated with peak-finding or inspection of the spatial intensity map. For this problem, determining the number of arrivals in a given frame is critical for properly inferring the state of the sound field. This analysis is effectively compression of the spatial room response, which is useful for analysis or encoding of the spatial sound field. Parametric, model-based formulations of these problems enhance the solution in all cases, and a Bayesian interpretation provides a principled approach to model comparison and parameter estimation. v

Bayesian Sensitivity Analysis of Statistical Models with Missing Data

PubMed Central

ZHU, HONGTU; IBRAHIM, JOSEPH G.; TANG, NIANSHENG

2013-01-01

Methods for handling missing data depend strongly on the mechanism that generated the missing values, such as missing completely at random (MCAR) or missing at random (MAR), as well as other distributional and modeling assumptions at various stages. It is well known that the resulting estimates and tests may be sensitive to these assumptions as well as to outlying observations. In this paper, we introduce various perturbations to modeling assumptions and individual observations, and then develop a formal sensitivity analysis to assess these perturbations in the Bayesian analysis of statistical models with missing data. We develop a geometric framework, called the Bayesian perturbation manifold, to characterize the intrinsic structure of these perturbations. We propose several intrinsic influence measures to perform sensitivity analysis and quantify the effect of various perturbations to statistical models. We use the proposed sensitivity analysis procedure to systematically investigate the tenability of the non-ignorable missing at random (NMAR) assumption. Simulation studies are conducted to evaluate our methods, and a dataset is analyzed to illustrate the use of our diagnostic measures. PMID:24753718

An efficient Bayesian meta-analysis approach for studying cross-phenotype genetic associations

PubMed Central

Majumdar, Arunabha; Haldar, Tanushree; Bhattacharya, Sourabh; Witte, John S.

2018-01-01

Simultaneous analysis of genetic associations with multiple phenotypes may reveal shared genetic susceptibility across traits (pleiotropy). For a locus exhibiting overall pleiotropy, it is important to identify which specific traits underlie this association. We propose a Bayesian meta-analysis approach (termed CPBayes) that uses summary-level data across multiple phenotypes to simultaneously measure the evidence of aggregate-level pleiotropic association and estimate an optimal subset of traits associated with the risk locus. This method uses a unified Bayesian statistical framework based on a spike and slab prior. CPBayes performs a fully Bayesian analysis by employing the Markov Chain Monte Carlo (MCMC) technique Gibbs sampling. It takes into account heterogeneity in the size and direction of the genetic effects across traits. It can be applied to both cohort data and separate studies of multiple traits having overlapping or non-overlapping subjects. Simulations show that CPBayes can produce higher accuracy in the selection of associated traits underlying a pleiotropic signal than the subset-based meta-analysis ASSET. We used CPBayes to undertake a genome-wide pleiotropic association study of 22 traits in the large Kaiser GERA cohort and detected six independent pleiotropic loci associated with at least two phenotypes. This includes a locus at chromosomal region 1q24.2 which exhibits an association simultaneously with the risk of five different diseases: Dermatophytosis, Hemorrhoids, Iron Deficiency, Osteoporosis and Peripheral Vascular Disease. We provide an R-package ‘CPBayes’ implementing the proposed method. PMID:29432419

Coalescent: an open-science framework for importance sampling in coalescent theory.

PubMed

Tewari, Susanta; Spouge, John L

2015-01-01

Background. In coalescent theory, computer programs often use importance sampling to calculate likelihoods and other statistical quantities. An importance sampling scheme can exploit human intuition to improve statistical efficiency of computations, but unfortunately, in the absence of general computer frameworks on importance sampling, researchers often struggle to translate new sampling schemes computationally or benchmark against different schemes, in a manner that is reliable and maintainable. Moreover, most studies use computer programs lacking a convenient user interface or the flexibility to meet the current demands of open science. In particular, current computer frameworks can only evaluate the efficiency of a single importance sampling scheme or compare the efficiencies of different schemes in an ad hoc manner. Results. We have designed a general framework (http://coalescent.sourceforge.net; language: Java; License: GPLv3) for importance sampling that computes likelihoods under the standard neutral coalescent model of a single, well-mixed population of constant size over time following infinite sites model of mutation. The framework models the necessary core concepts, comes integrated with several data sets of varying size, implements the standard competing proposals, and integrates tightly with our previous framework for calculating exact probabilities. For a given dataset, it computes the likelihood and provides the maximum likelihood estimate of the mutation parameter. Well-known benchmarks in the coalescent literature validate the accuracy of the framework. The framework provides an intuitive user interface with minimal clutter. For performance, the framework switches automatically to modern multicore hardware, if available. It runs on three major platforms (Windows, Mac and Linux). Extensive tests and coverage make the framework reliable and maintainable. Conclusions. In coalescent theory, many studies of computational efficiency consider only effective sample size. Here, we evaluate proposals in the coalescent literature, to discover that the order of efficiency among the three importance sampling schemes changes when one considers running time as well as effective sample size. We also describe a computational technique called "just-in-time delegation" available to improve the trade-off between running time and precision by constructing improved importance sampling schemes from existing ones. Thus, our systems approach is a potential solution to the "2(8) programs problem" highlighted by Felsenstein, because it provides the flexibility to include or exclude various features of similar coalescent models or importance sampling schemes.

A Bayesian Approach for Nonlinear Structural Equation Models with Dichotomous Variables Using Logit and Probit Links

ERIC Educational Resources Information Center

Lee, Sik-Yum; Song, Xin-Yuan; Cai, Jing-Heng

2010-01-01

Analysis of ordered binary and unordered binary data has received considerable attention in social and psychological research. This article introduces a Bayesian approach, which has several nice features in practical applications, for analyzing nonlinear structural equation models with dichotomous data. We demonstrate how to use the software…

Bayesian Statistics in Educational Research: A Look at the Current State of Affairs

ERIC Educational Resources Information Center

König, Christoph; van de Schoot, Rens

2018-01-01

The ability of a scientific discipline to build cumulative knowledge depends on its predominant method of data analysis. A steady accumulation of knowledge requires approaches which allow researchers to consider results from comparable prior research. Bayesian statistics is especially relevant for establishing a cumulative scientific discipline,…

Bayesian Finite Mixtures for Nonlinear Modeling of Educational Data.

ERIC Educational Resources Information Center

Tirri, Henry; And Others

A Bayesian approach for finding latent classes in data is discussed. The approach uses finite mixture models to describe the underlying structure in the data and demonstrate that the possibility of using full joint probability models raises interesting new prospects for exploratory data analysis. The concepts and methods discussed are illustrated…

Bayesian Analysis of Structural Equation Models with Nonlinear Covariates and Latent Variables

ERIC Educational Resources Information Center

Song, Xin-Yuan; Lee, Sik-Yum

2006-01-01

In this article, we formulate a nonlinear structural equation model (SEM) that can accommodate covariates in the measurement equation and nonlinear terms of covariates and exogenous latent variables in the structural equation. The covariates can come from continuous or discrete distributions. A Bayesian approach is developed to analyze the…

Evidence of major genes affecting stress response in rainbow trout using Bayesian methods of complex segregation analysis

USDA-ARS?s Scientific Manuscript database

As a first step towards the genetic mapping of quantitative trait loci (QTL) affecting stress response variation in rainbow trout, we performed complex segregation analyses (CSA) fitting mixed inheritance models of plasma cortisol using Bayesian methods in large full-sib families of rainbow trout. ...

A Hierarchical Bayesian Procedure for Two-Mode Cluster Analysis

ERIC Educational Resources Information Center

DeSarbo, Wayne S.; Fong, Duncan K. H.; Liechty, John; Saxton, M. Kim

2004-01-01

This manuscript introduces a new Bayesian finite mixture methodology for the joint clustering of row and column stimuli/objects associated with two-mode asymmetric proximity, dominance, or profile data. That is, common clusters are derived which partition both the row and column stimuli/objects simultaneously into the same derived set of clusters.…

Exact Bayesian p-values for a test of independence in a 2 × 2 contingency table with missing data.

PubMed

Lin, Yan; Lipsitz, Stuart R; Sinha, Debajyoti; Fitzmaurice, Garrett; Lipshultz, Steven

2017-01-01

Altham (Altham PME. Exact Bayesian analysis of a 2 × 2 contingency table, and Fisher's "exact" significance test. J R Stat Soc B 1969; 31: 261-269) showed that a one-sided p-value from Fisher's exact test of independence in a 2 × 2 contingency table is equal to the posterior probability of negative association in the 2 × 2 contingency table under a Bayesian analysis using an improper prior. We derive an extension of Fisher's exact test p-value in the presence of missing data, assuming the missing data mechanism is ignorable (i.e., missing at random or completely at random). Further, we propose Bayesian p-values for a test of independence in a 2 × 2 contingency table with missing data using alternative priors; we also present results from a simulation study exploring the Type I error rate and power of the proposed exact test p-values. An example, using data on the association between blood pressure and a cardiac enzyme, is presented to illustrate the methods.

Bayesian randomized clinical trials: From fixed to adaptive design.

PubMed

Yin, Guosheng; Lam, Chi Kin; Shi, Haolun

2017-08-01

Randomized controlled studies are the gold standard for phase III clinical trials. Using α-spending functions to control the overall type I error rate, group sequential methods are well established and have been dominating phase III studies. Bayesian randomized design, on the other hand, can be viewed as a complement instead of competitive approach to the frequentist methods. For the fixed Bayesian design, the hypothesis testing can be cast in the posterior probability or Bayes factor framework, which has a direct link to the frequentist type I error rate. Bayesian group sequential design relies upon Bayesian decision-theoretic approaches based on backward induction, which is often computationally intensive. Compared with the frequentist approaches, Bayesian methods have several advantages. The posterior predictive probability serves as a useful and convenient tool for trial monitoring, and can be updated at any time as the data accrue during the trial. The Bayesian decision-theoretic framework possesses a direct link to the decision making in the practical setting, and can be modeled more realistically to reflect the actual cost-benefit analysis during the drug development process. Other merits include the possibility of hierarchical modeling and the use of informative priors, which would lead to a more comprehensive utilization of information from both historical and longitudinal data. From fixed to adaptive design, we focus on Bayesian randomized controlled clinical trials and make extensive comparisons with frequentist counterparts through numerical studies. Copyright © 2017 Elsevier Inc. All rights reserved.

Coalescence of repelling colloidal droplets: a route to monodisperse populations.

PubMed

Roger, Kevin; Botet, Robert; Cabane, Bernard

2013-05-14

Populations of droplets or particles dispersed in a liquid may evolve through Brownian collisions, aggregation, and coalescence. We have found a set of conditions under which these populations evolve spontaneously toward a narrow size distribution. The experimental system consists of poly(methyl methacrylate) (PMMA) nanodroplets dispersed in a solvent (acetone) + nonsolvent (water) mixture. These droplets carry electrical charges, located on the ionic end groups of the macromolecules. We used time-resolved small angle X-ray scattering to determine their size distribution. We find that the droplets grow through coalescence events: the average radius (R) increases logarithmically with elapsed time while the relative width σR/(R) of the distribution decreases as the inverse square root of (R). We interpret this evolution as resulting from coalescence events that are hindered by ionic repulsions between droplets. We generalize this evolution through a simulation of the Smoluchowski kinetic equation, with a kernel that takes into account the interactions between droplets. In the case of vanishing or attractive interactions, all droplet encounters lead to coalescence. The corresponding kernel leads to the well-known "self-preserving" particle distribution of the coalescence process, where σR/(R) increases to a plateau value. However, for droplets that interact through long-range ionic repulsions, "large + small" droplet encounters are more successful at coalescence than "large + large" encounters. We show that the corresponding kernel leads to a particular scaling of the droplet-size distribution-known as the "second-scaling law" in the theory of critical phenomena, where σR/(R) decreases as 1/√(R) and becomes independent of the initial distribution. We argue that this scaling explains the narrow size distributions of colloidal dispersions that have been synthesized through aggregation processes.

Advanced pediatric mastoiditis with and without intracranial complications.

PubMed

Zevallos, Jose P; Vrabec, Jeffrey T; Williamson, Robert A; Giannoni, Carla; Larrier, Deidre; Sulek, Marcelle; Friedman, Ellen M; Oghalai, John S

2009-08-01

Recently, several groups have noticed an increase in cases of advanced pediatric mastoiditis and intracranial complications. The objective of this study was to review the bacteriology of advanced mastoiditis in pediatric patients, with the hypothesis that a difference in bacteriology might explain the development of an intracranial complication. Retrospective chart review. All pediatric patients with coalescent mastoiditis requiring surgery treated at a tertiary care children's hospital between 2002 and 2007 were reviewed. Every patient included was treated either with mastoidectomy alone (for coalescent mastoiditis without an intracranial complication) or with transtemporal craniotomy (for coalescent mastoiditis with an intracranial complication). All patients had surgical specimens sent for pathology, Gram stain, and aerobic and anaerobic cultures. One hundred eight pediatric patients with coalescent mastoiditis were identified: 58 (53%) presented with coalescent mastoiditis alone, 17 (16%) presented with coalescent mastoiditis and an intracranial complication, and 33 (31%) were excluded because they were treated with myringotomy and tubes alone, had incomplete data, or had an unclear diagnosis. Streptococcus pneumoniae was the most commonly cultured organism in patients with and without intracranial complications. Anaerobic isolates were present in 29.4% of patients with intracranial complications and 5.7% of patients without intracranial complications (P = .015). Nearly a quarter of pediatric patients with coalescent mastoiditis presented with a simultaneous intracranial complication. There was an increased incidence of anaerobic organisms in patients with intracranial complications compared to those without, indicating the importance of culture and antibiotic coverage appropriate for anaerobes. This series demonstrates the role of aggressive surgical management and close collaboration with the infectious disease service for long-term intravenous antibiotic therapy in treating pediatric patients with advanced mastoiditis.

Critical Void Volume Fraction fc at Void Coalescence for S235JR Steel at Low Initial Stress Triaxiality

NASA Astrophysics Data System (ADS)

Grzegorz Kossakowski, Paweł; Wciślik, Wiktor

2017-10-01

The paper is concerned with the nucleation, growth and coalescence of microdefects in the form of voids in S235JR steel. The material is known to be one of the basic steel grades commonly used in the construction industry. The theory and methods of damage mechanics were applied to determine and describe the failure mechanisms that occur when the material undergoes deformation. Until now, engineers have generally employed the Gurson-Tvergaard- Needleman model. This material model based on damage mechanics is well suited to define and analyze failure processes taking place in the microstructure of S235JR steel. It is particularly important to determine the critical void volume fraction fc , which is one of the basic parameters of the Gurson-Tvergaard-Needleman material model. As the critical void volume fraction fc refers to the failure stage, it is determined from the data collected for the void coalescence phase. A case of multi-axial stresses is considered taking into account the effects of spatial stress state. In this study, the parameter of stress triaxiality η was used to describe the failure phenomena. Cylindrical tensile specimens with a circumferential notch were analysed to obtain low values of initial stress triaxiality (η = 0.556 of the range) in order to determine the critical void volume fraction fc . It is essential to emphasize how unique the method applied is and how different it is from the other more common methods involving parameter calibration, i.e. curve-fitting methods. The critical void volume fraction fc at void coalescence was established through digital image analysis of surfaces of S235JR steel, which involved studying real, physical results obtained directly from the material tested.

Colonization and diversification of aquatic insects on three Macaronesian archipelagos using 59 nuclear loci derived from a draft genome.

PubMed

Rutschmann, Sereina; Detering, Harald; Simon, Sabrina; Funk, David H; Gattolliat, Jean-Luc; Hughes, Samantha J; Raposeiro, Pedro M; DeSalle, Rob; Sartori, Michel; Monaghan, Michael T

2017-02-01

The study of processes driving diversification requires a fully sampled and well resolved phylogeny, although a lack of phylogenetic markers remains a limitation for many non-model groups. Multilocus approaches to the study of recent diversification provide a powerful means to study the evolutionary process, but their application remains restricted because multiple unlinked loci with suitable variation for phylogenetic or coalescent analysis are not available for most non-model taxa. Here we identify novel, putative single-copy nuclear DNA (nDNA) phylogenetic markers to study the colonization and diversification of an aquatic insect species complex, Cloeon dipterum L. 1761 (Ephemeroptera: Baetidae), in Macaronesia. Whole-genome sequencing data from one member of the species complex were used to identify 59 nDNA loci (32,213 base pairs), followed by Sanger sequencing of 29 individuals sampled from 13 islands of three Macaronesian archipelagos. Multispecies coalescent analyses established six putative species. Three island species formed a monophyletic clade, with one species occurring on the Azores, Europe and North America. Ancestral state reconstruction indicated at least two colonization events from the mainland (to the Canaries, respectively Azores) and one within the archipelago (between Madeira and the Canaries). Random subsets of the 59 loci showed a positive linear relationship between number of loci and node support. In contrast, node support in the multispecies coalescent tree was negatively correlated with mean number of phylogenetically informative sites per locus, suggesting a complex relationship between tree resolution and marker variability. Our approach highlights the value of combining genomics, coalescent-based phylogeography, species delimitation, and phylogenetic reconstruction to resolve recent diversification events in an archipelago species complex. Copyright © 2016 Elsevier Inc. All rights reserved.

Coalescence Effects on Neutron Production in High Energy Nucleus-Nucleus Collisions

DTIC Science & Technology

2001-08-01

25/Jun/2001 THESIS 1 4. TITLE AND SUBTITLE 5a. CONTRACT NUMBER COALESCENCE EFFECTS ON NEUTRON PRODUCTION IN HIGH- ENERGY NUCLEUS-NUCLEUS COLLISIONS 5b... Energy Nucleus-Nucleus Collisions." I have examined the final copy of this thesis for form and content and recommend that it be accepted in partial...School COALESCENCE EFFECTS ON NEUTRON PRODUCTION IN HIGH ENERGY NUCLEUS-NUCLEUS COLLISIONS A Thesis Presented for the Master of Science Degree The

Phase segregation due to simultaneous migration and coalescence

NASA Technical Reports Server (NTRS)

Davis, Robert H.; Wang, Hua; Hawker, Debra

1994-01-01

Ground-based modeling and experiments have been performed on the interaction and coalescence of drops leading to macroscopic phase separation. The focus has been on gravity-induced motion, with research also initiated on thermocapillary motion of drops. The drop size distribution initially shifts toward larger drops with time due to coalescence, and then a back towards smaller drops due to the larger preferentially settling out. As a consequence, the phase separation rate initially increases with time and then decreases.

Lattice-Boltzmann simulation of coalescence-driven island coarsening

USGS Publications Warehouse

Basagaoglu, H.; Green, C.T.; Meakin, P.; McCoy, B.J.

2004-01-01

The first-order phase separation in a thin fluid film was simulated using a two-dimensional lattice-Boltzman model (LBM) with fluid-fluid interactions. The effects of the domain size on the intermediate asymptotic island size distribution were also discussed. It was observed that the overall process is dominated by coalescence which is independent of island mass. The results show that the combined effects of growth, coalescence, and Ostwald ripening control the phase transition process in the LBM simulations.

Viscosity Measurement Using Drop Coalescence in Microgravity

NASA Technical Reports Server (NTRS)

Antar, Basil N.; Ethridge, Edwin C.; Maxwell, Daniel; Curreri, Peter A. (Technical Monitor)

2002-01-01

We present in here validation studies of a new method for application in microgravity environment which measures the viscosity of highly viscous undercooled liquids using drop coalescence. The method has the advantage of avoiding heterogeneous nucleation at container walls caused by crystallization of undercooled liquids during processing. Homogeneous nucleation can also be avoided due to the rapidity of the measurement using this method. The technique relies on measurements from experiments conducted in near zero gravity environment as well as highly accurate analytical formulation for the coalescence process. The viscosity of the liquid is determined by allowing the computed free surface shape relaxation time to be adjusted in response to the measured free surface velocity for two coalescing drops. Results are presented from two sets of validation experiments for the method which were conducted on board aircraft flying parabolic trajectories. In these tests the viscosity of a highly viscous liquid, namely glycerin, was determined at different temperatures using the drop coalescence method described in here. The experiments measured the free surface velocity of two glycerin drops coalescing under the action of surface tension alone in low gravity environment using high speed photography. The liquid viscosity was determined by adjusting the computed free surface velocity values to the measured experimental data. The results of these experiments were found to agree reasonably well with the known viscosity for the test liquid used.

Exoplanet Biosignatures: Future Directions

PubMed Central

Bains, William; Cronin, Leroy; DasSarma, Shiladitya; Danielache, Sebastian; Domagal-Goldman, Shawn; Kacar, Betul; Kiang, Nancy Y.; Lenardic, Adrian; Reinhard, Christopher T.; Moore, William; Schwieterman, Edward W.; Shkolnik, Evgenya L.; Smith, Harrison B.

2018-01-01

Abstract We introduce a Bayesian method for guiding future directions for detection of life on exoplanets. We describe empirical and theoretical work necessary to place constraints on the relevant likelihoods, including those emerging from better understanding stellar environment, planetary climate and geophysics, geochemical cycling, the universalities of physics and chemistry, the contingencies of evolutionary history, the properties of life as an emergent complex system, and the mechanisms driving the emergence of life. We provide examples for how the Bayesian formalism could guide future search strategies, including determining observations to prioritize or deciding between targeted searches or larger lower resolution surveys to generate ensemble statistics and address how a Bayesian methodology could constrain the prior probability of life with or without a positive detection. Key Words: Exoplanets—Biosignatures—Life detection—Bayesian analysis. Astrobiology 18, 779–824. PMID:29938538

Population forecasts for Bangladesh, using a Bayesian methodology.

PubMed

Mahsin, Md; Hossain, Syed Shahadat

2012-12-01

Population projection for many developing countries could be quite a challenging task for the demographers mostly due to lack of availability of enough reliable data. The objective of this paper is to present an overview of the existing methods for population forecasting and to propose an alternative based on the Bayesian statistics, combining the formality of inference. The analysis has been made using Markov Chain Monte Carlo (MCMC) technique for Bayesian methodology available with the software WinBUGS. Convergence diagnostic techniques available with the WinBUGS software have been applied to ensure the convergence of the chains necessary for the implementation of MCMC. The Bayesian approach allows for the use of observed data and expert judgements by means of appropriate priors, and a more realistic population forecasts, along with associated uncertainty, has been possible.