Phylogeography on the rocks: The contribution of current and historical factors in shaping the genetic structure of Chthamalus montagui (Crustacea, Cirripedia)

PubMed Central

Pannacciulli, Federica G.; de Guttry, Christian; Achituv, Yair

2017-01-01

The model marine broadcast-spawner barnacle Chthamalus montagui was investigated to understand its genetic structure and quantify levels of population divergence, and to make inference on historical demography in terms of time of divergence and changes in population size. We collected specimens from rocky shores of the north-east Atlantic Ocean (4 locations), Mediterranean Sea (8) and Black Sea (1). The 312 sequences 537 bp) of the mitochondrial cytochrome c oxidase I allowed to detect 130 haplotypes. High within-location genetic variability was recorded, with haplotype diversity ranging between h = 0.750 and 0.967. Parameters of genetic divergence, haplotype network and Bayesian assignment analysis were consistent in rejecting the hypothesis of panmixia. C. montagui is genetically structured in three geographically discrete populations, which corresponded to north-eastern Atlantic Ocean, western-central Mediterranean Sea, and Aegean Sea-Black Sea. These populations are separated by two main effective barriers to gene flow located at the Almeria-Oran Front and in correspondence of the Cyclades Islands. According to the ‘isolation with migration’ model, adjacent population pairs diverged during the early to middle Pleistocene transition, a period in which geological events provoked significant changes in the structure and composition of palaeocommunities. Mismatch distributions, neutrality tests and Bayesian skyline plots showed past population expansions, which started approximately in the Mindel-Riss interglacial, in which ecological conditions were favourable for temperate species and calcium-uptaking marine organisms. PMID:28594840

Accounting for rate variation among lineages in comparative demographic analyses.

PubMed

Hope, Andrew G; Ho, Simon Y W; Malaney, Jason L; Cook, Joseph A; Talbot, Sandra L

2014-09-01

Genetic analyses of contemporary populations can be used to estimate the demographic histories of species within an ecological community. Comparison of these demographic histories can shed light on community responses to past climatic events. However, species experience different rates of molecular evolution, and this presents a major obstacle to comparative demographic analyses. We address this problem by using a Bayesian relaxed-clock method to estimate the relative evolutionary rates of 22 small mammal taxa distributed across northwestern North America. We found that estimates of the relative molecular substitution rate for each taxon were consistent across the range of sampling schemes that we compared. Using three different reference rates, we rescaled the relative rates so that they could be used to estimate absolute evolutionary timescales. Accounting for rate variation among taxa led to temporal shifts in our skyline-plot estimates of demographic history, highlighting both uniform and idiosyncratic evolutionary responses to directional climate trends for distinct ecological subsets of the small mammal community. Our approach can be used in evolutionary analyses of populations from multiple species, including comparative demographic studies. © 2014 The Author(s). Evolution © 2014 The Society for the Study of Evolution.

The Impact of the Tree Prior on Molecular Dating of Data Sets Containing a Mixture of Inter- and Intraspecies Sampling.

PubMed

Ritchie, Andrew M; Lo, Nathan; Ho, Simon Y W

2017-05-01

In Bayesian phylogenetic analyses of genetic data, prior probability distributions need to be specified for the model parameters, including the tree. When Bayesian methods are used for molecular dating, available tree priors include those designed for species-level data, such as the pure-birth and birth-death priors, and coalescent-based priors designed for population-level data. However, molecular dating methods are frequently applied to data sets that include multiple individuals across multiple species. Such data sets violate the assumptions of both the speciation and coalescent-based tree priors, making it unclear which should be chosen and whether this choice can affect the estimation of node times. To investigate this problem, we used a simulation approach to produce data sets with different proportions of within- and between-species sampling under the multispecies coalescent model. These data sets were then analyzed under pure-birth, birth-death, constant-size coalescent, and skyline coalescent tree priors. We also explored the ability of Bayesian model testing to select the best-performing priors. We confirmed the applicability of our results to empirical data sets from cetaceans, phocids, and coregonid whitefish. Estimates of node times were generally robust to the choice of tree prior, but some combinations of tree priors and sampling schemes led to large differences in the age estimates. In particular, the pure-birth tree prior frequently led to inaccurate estimates for data sets containing a mixture of inter- and intraspecific sampling, whereas the birth-death and skyline coalescent priors produced stable results across all scenarios. Model testing provided an adequate means of rejecting inappropriate tree priors. Our results suggest that tree priors do not strongly affect Bayesian molecular dating results in most cases, even when severely misspecified. However, the choice of tree prior can be significant for the accuracy of dating results in the case of data sets with mixed inter- and intraspecies sampling. [Bayesian phylogenetic methods; model testing; molecular dating; node time; tree prior.]. © 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.

Short communication: phylodynamics analysis of the human immunodeficiency virus type 1 envelope gene in mother and child pairs.

PubMed

Santos, Luciane Amorim; Gray, Rebecca R; Monteiro-Cunha, Joana Paixão; Strazza, Evandra; Kashima, Simone; Santos, Edson de Souza; Araújo, Thessika Hialla Almeida; Gonçalves, Marilda de Souza; Salemi, Marco; Alcantara, Luiz Carlos Junior

2015-09-01

Characterizing the impact of HIV transmission routes on viral genetic diversity can improve the understanding of the mechanisms of virus evolution and adaptation. HIV vertical transmission can occur in utero, during delivery, or while breastfeeding. The present study investigated the phylodynamics of the HIV-1 env gene in mother-to-child transmission by analyzing one chronically infected pair from Brazil and three acutely infected pairs from Zambia, with three to five time points. Sequences from 25 clones from each sample were obtained and aligned using Clustal X. ML trees were constructed in PhyML using the best evolutionary model. Bayesian analyses testing the relaxed and strict molecular clock were performed using BEAST and a Bayesian Skyline Plot (BSP) was construed. The genetic variability of previously described epitopes was investigated and compared between each individual time point and between mother and child sequences. The relaxed molecular clock was the best-fitted model for all datasets. The tree topologies did not show differentiation in the evolutionary dynamics of the virus circulating in the mother from the viral population in the child. In the BSP, the effective population size was more constant in time in the chronically infected patients while in the acute patients it was possible to detect bottlenecks. The genetic variability within viral epitopes recognized by the human immune system was considerably higher among the chronically infected pair in comparison with acutely infected pairs. These results contribute to a better understanding of HIV-1 evolutionary dynamics in mother-to-child transmission.

Glaciation Effects on the Phylogeographic Structure of Oligoryzomys longicaudatus (Rodentia: Sigmodontinae) in the Southern Andes

PubMed Central

Palma, R. Eduardo; Boric-Bargetto, Dusan; Torres-Pérez, Fernando; Hernández, Cristián E.; Yates, Terry L.

2012-01-01

The long-tailed pygmy rice rat Oligoryzomys longicaudatus (Sigmodontinae), the major reservoir of Hantavirus in Chile and Patagonian Argentina, is widely distributed in the Mediterranean, Temperate and Patagonian Forests of Chile, as well as in adjacent areas in southern Argentina. We used molecular data to evaluate the effects of the last glacial event on the phylogeographic structure of this species. We examined if historical Pleistocene events had affected genetic variation and spatial distribution of this species along its distributional range. We sampled 223 individuals representing 47 localities along the species range, and sequenced the hypervariable domain I of the mtDNA control region. Aligned sequences were analyzed using haplotype network, Bayesian population structure and demographic analyses. Analysis of population structure and the haplotype network inferred three genetic clusters along the distribution of O. longicaudatus that mostly agreed with the three major ecogeographic regions in Chile: Mediterranean, Temperate Forests and Patagonian Forests. Bayesian Skyline Plots showed constant population sizes through time in all three clusters followed by an increase after and during the Last Glacial Maximum (LGM; between 26,000–13,000 years ago). Neutrality tests and the “g” parameter also suggest that populations of O. longicaudatus experienced demographic expansion across the species entire range. Past climate shifts have influenced population structure and lineage variation of O. longicaudatus. This species remained in refugia areas during Pleistocene times in southern Temperate Forests (and adjacent areas in Patagonia). From these refugia, O. longicaudatus experienced demographic expansions into Patagonian Forests and central Mediterranean Chile using glacial retreats. PMID:22396751

Reconstructing the history of a fragmented and heavily exploited red deer population using ancient and contemporary DNA.

PubMed

Rosvold, Jørgen; Røed, Knut H; Hufthammer, Anne Karin; Andersen, Reidar; Stenøien, Hans K

2012-09-26

Red deer (Cervus elaphus) have been an important human resource for millennia, experiencing intensive human influence through habitat alterations, hunting and translocation of animals. In this study we investigate a time series of ancient and contemporary DNA from Norwegian red deer spanning about 7,000 years. Our main aim was to investigate how increasing agricultural land use, hunting pressure and possibly human mediated translocation of animals have affected the genetic diversity on a long-term scale. We obtained mtDNA (D-loop) sequences from 73 ancient specimens. These show higher genetic diversity in ancient compared to extant samples, with the highest diversity preceding the onset of agricultural intensification in the Early Iron Age. Using standard diversity indices, Bayesian skyline plot and approximate Bayesian computation, we detected a population reduction which was more prolonged than, but not as severe as, historic documents indicate. There are signs of substantial changes in haplotype frequencies primarily due to loss of haplotypes through genetic drift. There is no indication of human mediated translocations into the Norwegian population. All the Norwegian sequences show a western European origin, from which the Norwegian lineage diverged approximately 15,000 years ago. Our results provide direct insight into the effects of increasing habitat fragmentation and human hunting pressure on genetic diversity and structure of red deer populations. They also shed light on the northward post-glacial colonisation process of red deer in Europe and suggest increased precision in inferring past demographic events when including both ancient and contemporary DNA.

Glaciation effects on the phylogeographic structure of Oligoryzomys longicaudatus (Rodentia: Sigmodontinae) in the southern Andes.

PubMed

Palma, R Eduardo; Boric-Bargetto, Dusan; Torres-Pérez, Fernando; Hernández, Cristián E; Yates, Terry L

2012-01-01

The long-tailed pygmy rice rat Oligoryzomys longicaudatus (Sigmodontinae), the major reservoir of Hantavirus in Chile and Patagonian Argentina, is widely distributed in the Mediterranean, Temperate and Patagonian Forests of Chile, as well as in adjacent areas in southern Argentina. We used molecular data to evaluate the effects of the last glacial event on the phylogeographic structure of this species. We examined if historical Pleistocene events had affected genetic variation and spatial distribution of this species along its distributional range. We sampled 223 individuals representing 47 localities along the species range, and sequenced the hypervariable domain I of the mtDNA control region. Aligned sequences were analyzed using haplotype network, bayesian population structure and demographic analyses. Analysis of population structure and the haplotype network inferred three genetic clusters along the distribution of O. longicaudatus that mostly agreed with the three major ecogeographic regions in Chile: Mediterranean, Temperate Forests and Patagonian Forests. Bayesian Skyline Plots showed constant population sizes through time in all three clusters followed by an increase after and during the Last Glacial Maximum (LGM; between 26,000-13,000 years ago). Neutrality tests and the "g" parameter also suggest that populations of O. longicaudatus experienced demographic expansion across the species entire range. Past climate shifts have influenced population structure and lineage variation of O. longicaudatus. This species remained in refugia areas during Pleistocene times in southern Temperate Forests (and adjacent areas in Patagonia). From these refugia, O. longicaudatus experienced demographic expansions into Patagonian Forests and central Mediterranean Chile using glacial retreats.

A topographic index to quantify the effect of mesoscale and form on site productivity

Treesearch

W. Henry McNab

1992-01-01

Landform is related to environmental factorsthat affectsite productivity in mountainous areas. I devised a simple index of landform and tested this index as a predictor of site index ín the Blue Ridge physiographic province. The landform index is the mean of eight slope gradients from plot center to skyline. A preliminary test indicated that the index was...

The second molecular epidemiological study of HIV infection in Mongolia between 2010 and 2016.

PubMed

Jagdagsuren, Davaalkham; Hayashida, Tsunefusa; Takano, Misao; Gombo, Erdenetuya; Zayasaikhan, Setsen; Kanayama, Naomi; Tsuchiya, Kiyoto; Oka, Shinichi

2017-01-01

Our previous 2005-2009 molecular epidemiological study in Mongolia identified a hot spot of HIV-1 transmission in men who have sex with men (MSM). To control the infection, we collaborated with NGOs to promote safer sex and HIV testing since mid-2010. In this study, we carried out the second molecular epidemiological survey between 2010 and 2016 to determine the status of HIV-1 infection in Mongolia. The study included 143 new cases of HIV-1 infection. Viral RNA was extracted from stocked plasma samples and sequenced for the pol and the env regions using the Sanger method. Near-full length sequencing using MiSeq was performed in 3 patients who were suspected to be infected with recombinant HIV-1. Phylogenetic analysis was performed using the neighbor-joining method and Bayesian Markov chain Monte Carlo method. MSM was the main transmission route in the previous and current studies. However, heterosexual route showed a significant increase in recent years. Phylogenetic analysis documented three taxa; Mongolian B, Korean B, and CRF51_01B, though the former two were also observed in the previous study. CRF51_01B, which originated from Singapore and Malaysia, was confirmed by near-full length sequencing. Although these strains were mainly detected in MSM, they were also found in increasing numbers of heterosexual males and females. Bayesian phylogenetic analysis estimated transmission of CRF51_01B into Mongolia around early 2000s. An extended Bayesian skyline plot showed a rapid increase in the effective population size of Mongolian B cluster around 2004 and that of CRF51_01B cluster around 2011. HIV-1 infection might expand to the general population in Mongolia. Our study documented a new cluster of HIV-1 transmission, enhancing our understanding of the epidemiological status of HIV-1 in Mongolia.

Evolutionary analysis of rubella viruses in mainland China during 2010–2012: endemic circulation of genotype 1E and introductions of genotype 2B

PubMed Central

Zhu, Zhen; Rivailler, Pierre; Abernathy, Emily; Cui, Aili; Zhang, Yan; Mao, Naiyin; Xu, Songtao; Zhou, Shujie; Lei, Yue; Wang, Yan; Zheng, Huanying; He, Jilan; Chen, Ying; Li, Chongshan; Bo, Fang; Zhao, Chunfang; Chen, Meng; Lu, Peishan; Li, Fangcai; Gu, Suyi; Gao, Hui; Guo, Yu; Chen, Hui; Feng, Daxing; Wang, Shuang; Tang, Xiaomin; Lei, Yake; Feng, Yan; Deng, Lili; Gong, Tian; Fan, Lixia; Xu, Wenbo; Icenogle, Joseph; Chen, Xia; Tian, Hong; Ma, Yan; Liu, Leng; Liu, Li; Liu, Jianfeng; Fu, Hong; Yang, Yuying; Ma, Yujie; Zhao, Hua; Huang, Fang; Hu, Ying; Zhang, Hong; Tian, Xiaoling; Du, Hui; Ma, Xuemin; Zhang, Zhenying; Xu, Jin; Zhou, Jianhui; Ye, Xufang; Li, Jing; Lu, Yiyu; Liu, Wei; Zhang, Yanni; Zhao, Shengcang; Ba, Zhuoma

2015-01-01

Rubella remains a significant burden in mainland China. In this report, 667 viruses collected in 24 of 31 provinces of mainland China during 2010–2012 were sequenced and analyzed, significantly extending previous reports on limited numbers of viruses collected before 2010. Only viruses of genotypes 1E and 2B were found. Genotype 1E viruses were found in all 24 provinces. Genotype 1E viruses were likely introduced into mainland China around 1997 and endemic transmission of primarily one lineage became established. Viruses reported here from 2010–2012 are largely in a single cluster within this lineage. Genotype 2B viruses were rarely detected in China prior to 2010. This report documents a previously undetected 2B lineage, which likely became endemic in eastern provinces of China between 2010 and 2012. Bayesian analyses were performed to estimate the evolutionary rates and dates of appearance of the genotype 1E and 2B viral linages in China. A skyline plot of viral population diversity did not provide evidence of reduction of diversity as a result of vaccination, but should be useful as a baseline for such reductions as vaccination programs for rubella become widespread in mainland China. PMID:25613734

Demographic response of cutlassfish (Trichiurus japonicus and T. nanhaiensis) to fluctuating palaeo-climate and regional oceanographic conditions in the China seas.

PubMed

He, Lijun; Zhang, Aibing; Weese, David; Li, Shengfa; Li, Jiansheng; Zhang, Jing

2014-09-16

Glacial cycles of the Quaternary have heavily influenced the demographic history of various species. To test the evolutionary impact of palaeo-geologic and climatic events on the demographic history of marine taxa from the coastal Western Pacific, we investigated the population structure and demographic history of two economically important fish (Trichiurus japonicus and T. nanhaiensis) that inhabit the continental shelves of the East China and northern South China Seas using the mitochondrial cytochrome b sequences and Bayesian Skyline Plot analyses. A molecular rate of 2.03% per million years, calibrated to the earliest flooding of the East China Sea shelf (70-140 kya), revealed a strong correlation between population sizes and primary production. Furthermore, comparison of the demographic history of T. japonicus populations from the East China and South China Seas provided evidence of the postglacial development of the Changjiang (Yangtze River) Delta. In the South China Sea, interspecific comparisons between T. japonicus and T. nanhaiensis indicated possible evolutionary responses to changes in palaeo-productivity that were influenced by East Asian winter monsoons. This study not only provides insight into the demographic history of cutlassfish but also reveals potential clues regarding the historic productivity and regional oceanographic conditions of the Western Pacific marginal seas.

Demographic response of cutlassfish (Trichiurus japonicus and T. nanhaiensis) to fluctuating palaeo-climate and regional oceanographic conditions in the China seas

PubMed Central

He, Lijun; Zhang, Aibing; Weese, David; Li, Shengfa; Li, Jiansheng; Zhang, Jing

2014-01-01

Glacial cycles of the Quaternary have heavily influenced the demographic history of various species. To test the evolutionary impact of palaeo-geologic and climatic events on the demographic history of marine taxa from the coastal Western Pacific, we investigated the population structure and demographic history of two economically important fish (Trichiurus japonicus and T. nanhaiensis) that inhabit the continental shelves of the East China and northern South China Seas using the mitochondrial cytochrome b sequences and Bayesian Skyline Plot analyses. A molecular rate of 2.03% per million years, calibrated to the earliest flooding of the East China Sea shelf (70–140 kya), revealed a strong correlation between population sizes and primary production. Furthermore, comparison of the demographic history of T. japonicus populations from the East China and South China Seas provided evidence of the postglacial development of the Changjiang (Yangtze River) Delta. In the South China Sea, interspecific comparisons between T. japonicus and T. nanhaiensis indicated possible evolutionary responses to changes in palaeo-productivity that were influenced by East Asian winter monsoons. This study not only provides insight into the demographic history of cutlassfish but also reveals potential clues regarding the historic productivity and regional oceanographic conditions of the Western Pacific marginal seas. PMID:25223336

Multilocus Analyses Reveal Postglacial Demographic Shrinkage of Juniperus morrisonicola (Cupressaceae), a Dominant Alpine Species in Taiwan

PubMed Central

Chiu, Chi-Te; Huang, Chao-Li; Hung, Kuo-Hsiang; Chiang, Tzen-Yuh

2016-01-01

Postglacial climate changes alter geographical distributions and diversity of species. Such ongoing changes often force species to migrate along the latitude/altitude. Altitudinal gradients represent assemblage of environmental, especially climatic, variable factors that influence the plant distributions. Global warming that triggered upward migrations has therefore impacted the alpine plants on an island. In this study, we examined the genetic structure of Juniperus morrisonicola, a dominant alpine species in Taiwan, and inferred historical, demographic dynamics based on multilocus analyses. Lower levels of genetic diversity in north indicated that populations at higher latitudes were vulnerable to climate change, possibly related to historical alpine glaciers. Neither organellar DNA nor nuclear genes displayed geographical subdivisions, indicating that populations were likely interconnected before migrating upward to isolated mountain peaks, providing low possibilities of seed/pollen dispersal across mountain ranges. Bayesian skyline plots suggested steady population growth of J. morrisonicola followed by recent demographic contraction. In contrast, most lower-elevation plants experienced recent demographic expansion as a result of global warming. The endemic alpine conifer may have experienced dramatic climate changes over the alternation of glacial and interglacial periods, as indicated by a trend showing decreasing genetic diversity with the altitudinal gradient, plus a fact of upward migration. PMID:27561108

Evolutionary analysis of rubella viruses in mainland China during 2010-2012: endemic circulation of genotype 1E and introductions of genotype 2B.

PubMed

Zhu, Zhen; Rivailler, Pierre; Abernathy, Emily; Cui, Aili; Zhang, Yan; Mao, Naiyin; Xu, Songtao; Zhou, Shujie; Lei, Yue; Wang, Yan; Zheng, Huanying; He, Jilan; Chen, Ying; Li, Chongshan; Bo, Fang; Zhao, Chunfang; Chen, Meng; Lu, Peishan; Li, Fangcai; Gu, Suyi; Gao, Hui; Guo, Yu; Chen, Hui; Feng, Daxing; Wang, Shuang; Tang, Xiaomin; Lei, Yake; Feng, Yan; Deng, Lili; Gong, Tian; Fan, Lixia; Xu, Wenbo; Icenogle, Joseph

2015-01-23

Rubella remains a significant burden in mainland China. In this report, 667 viruses collected in 24 of 31 provinces of mainland China during 2010-2012 were sequenced and analyzed, significantly extending previous reports on limited numbers of viruses collected before 2010. Only viruses of genotypes 1E and 2B were found. Genotype 1E viruses were found in all 24 provinces. Genotype 1E viruses were likely introduced into mainland China around 1997 and endemic transmission of primarily one lineage became established. Viruses reported here from 2010-2012 are largely in a single cluster within this lineage. Genotype 2B viruses were rarely detected in China prior to 2010. This report documents a previously undetected 2B lineage, which likely became endemic in eastern provinces of China between 2010 and 2012. Bayesian analyses were performed to estimate the evolutionary rates and dates of appearance of the genotype 1E and 2B viral linages in China. A skyline plot of viral population diversity did not provide evidence of reduction of diversity as a result of vaccination, but should be useful as a baseline for such reductions as vaccination programs for rubella become widespread in mainland China.

Multilocus Analyses Reveal Postglacial Demographic Shrinkage of Juniperus morrisonicola (Cupressaceae), a Dominant Alpine Species in Taiwan.

PubMed

Huang, Chi-Chun; Hsu, Tsai-Wen; Wang, Hao-Ven; Liu, Zin-Huang; Chen, Yi-Yen; Chiu, Chi-Te; Huang, Chao-Li; Hung, Kuo-Hsiang; Chiang, Tzen-Yuh

2016-01-01

Postglacial climate changes alter geographical distributions and diversity of species. Such ongoing changes often force species to migrate along the latitude/altitude. Altitudinal gradients represent assemblage of environmental, especially climatic, variable factors that influence the plant distributions. Global warming that triggered upward migrations has therefore impacted the alpine plants on an island. In this study, we examined the genetic structure of Juniperus morrisonicola, a dominant alpine species in Taiwan, and inferred historical, demographic dynamics based on multilocus analyses. Lower levels of genetic diversity in north indicated that populations at higher latitudes were vulnerable to climate change, possibly related to historical alpine glaciers. Neither organellar DNA nor nuclear genes displayed geographical subdivisions, indicating that populations were likely interconnected before migrating upward to isolated mountain peaks, providing low possibilities of seed/pollen dispersal across mountain ranges. Bayesian skyline plots suggested steady population growth of J. morrisonicola followed by recent demographic contraction. In contrast, most lower-elevation plants experienced recent demographic expansion as a result of global warming. The endemic alpine conifer may have experienced dramatic climate changes over the alternation of glacial and interglacial periods, as indicated by a trend showing decreasing genetic diversity with the altitudinal gradient, plus a fact of upward migration.

Updated Three-Stage Model for the Peopling of the Americas

PubMed Central

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

2008-01-01

Background We re-assess support for our three stage model for the peopling of the Americas in light of a recent report that identified nine non-Native American mitochondrial genome sequences that should not have been included in our initial analysis. Removal of these sequences results in the elimination of an early (i.e. ∼40,000 years ago) expansion signal we had proposed for the proto-Amerind population. Methodology/Findings Bayesian skyline plot analysis of a new dataset of Native American mitochondrial coding genomes confirms the absence of an early expansion signal for the proto-Amerind population and allows us to reduce the variation around our estimate of the New World founder population size. In addition, genetic variants that define New World founder haplogroups are used to estimate the amount of time required between divergence of proto-Amerinds from the Asian gene pool and expansion into the New World. Conclusions/Significance The period of population isolation required for the generation of New World mitochondrial founder haplogroup-defining genetic variants makes the existence of three stages of colonization a logical conclusion. Thus, our three stage model remains an important and useful working hypothesis for researchers interested in the peopling of the Americas and the processes of colonization. PMID:18797500

The Endemic Insular and Peninsular Species Chaetodipus spinatus (Mammalia, Heteromyidae) Breaks Patterns for Baja California

PubMed Central

Álvarez-Castañeda, Sergio Ticul; Murphy, Robert W.

2014-01-01

The Baja California peninsula is the second longest, most geographically isolated peninsula on Earth. Its physiography and the presence of many surrounding islands has facilitated studies of the underlying patterns and drivers of genetic structuring for a wide spectrum of organisms. Chaetodipus spinatus is endemic to the region and occurs on 12 associated islands, including 10 in the Gulf of California and two in the Pacific Ocean. This distribution makes it a model species for evaluating natural historical barriers. We test hypotheses associated with the relationship between the range of the species, patterns in other species, and its relationship to Pleistocene-Holocene climatic changes. We analyzed sequence data from mtDNA genes encoding cytochrome b (Cytb) and cytochrome c oxidase subunits I (COI) and III (COIII) in 26 populations including all 12 islands. The matrilineal genealogy, statistical parsimony network and Bayesian skyline plot indicated an origin of C. spinatus in the southern part of the peninsula. Our analyses detected several differences from the common pattern of peninsular animals: no mid-peninsula break exists, Isla Carmen hosts the most divergent population, the population on an ancient southern Midriff island does not differ from peninsular populations, and a mtDNA peninsular discordance occurs near Loreto. PMID:25542029

Pleistocene climate changes shaped the population structure of Partamona seridoensis (Apidae, Meliponini), an endemic stingless bee from the Neotropical dry forest

PubMed Central

Ferreira, Kátia Maria; Carvalho, Airton Torres; Martins, Celso Feitosa; Fernandes, Carlo Rivero; Del Lama, Marco Antonio

2017-01-01

Partamona seridoensis is an endemic stingless bee from the Caatinga, a Neotropical dry forest in northeastern Brazil. Like other stingless bees, this species plays an important ecological role as a pollinator. The aim of the present study was to investigate the genetic structure and evolutionary history of P. seridoensis across its current geographic range. Workers from 84 nests from 17 localities were analyzed for COI and Cytb genic regions. The population structure tests (Bayesian phylogenetic inference, AMOVA and haplotype network) consistently characterized two haplogroups (northwestern and eastern), with little gene flow between them, generating a high differentiation between them as well as among the populations within each haplogroup. The Mantel test revealed no isolation by distance. No evidence of a potential geographic barrier in the present that could explain the diversification between the P. seridoensis haplogroups was found. However, Pleistocene climatic changes may explain this differentiation, since the initial time for the P. seridoensis lineages diversification took place during the mid-Pleistocene, specifically the interglacial period, when the biota is presumed to have been more associated with dry conditions and had more restricted, fragmented geographical distribution. This event may have driven diversification by isolating the two haplogroups. Otherwise, the climatic changes in the late Pleistocene must not have drastically affected the population dynamics of P. seridoensis, since the Bayesian Skyline Plot did not reveal any substantial fluctuation in effective population size in either haplogroup. Considering its importance and the fact that it is an endemic bee from a very threatened Neotropical dry forest, the results herein could be useful to the development of conservation strategies for P. seridoensis. PMID:28410408

Extinction and recolonization of maritime Antarctica in the limpet Nacella concinna (Strebel, 1908) during the last glacial cycle: toward a model of Quaternary biogeography in shallow Antarctic invertebrates.

PubMed

González-Wevar, C A; Saucède, T; Morley, S A; Chown, S L; Poulin, E

2013-10-01

Quaternary glaciations in Antarctica drastically modified geographical ranges and population sizes of marine benthic invertebrates and thus affected the amount and distribution of intraspecific genetic variation. Here, we present new genetic information in the Antarctic limpet Nacella concinna, a dominant Antarctic benthic species along shallow ice-free rocky ecosystems. We examined the patterns of genetic diversity and structure in this broadcast spawner along maritime Antarctica and from the peri-Antarctic island of South Georgia. Genetic analyses showed that N. concinna represents a single panmictic unit in maritime Antarctic. Low levels of genetic diversity characterized this population; its median-joining haplotype network revealed a typical star-like topology with a short genealogy and a dominant haplotype broadly distributed. As previously reported with nuclear markers, we detected significant genetic differentiation between South Georgia Island and maritime Antarctica populations. Higher levels of genetic diversity, a more expanded genealogy and the presence of more private haplotypes support the hypothesis of glacial persistence in this peri-Antarctic island. Bayesian Skyline plot and mismatch distribution analyses recognized an older demographic history in South Georgia. Approximate Bayesian computations did not support the persistence of N. concinna along maritime Antarctica during the last glacial period, but indicated the resilience of the species in peri-Antarctic refugia (South Georgia Island). We proposed a model of Quaternary Biogeography for Antarctic marine benthic invertebrates with shallow and narrow bathymetric ranges including (i) extinction of maritime Antarctic populations during glacial periods; (ii) persistence of populations in peri-Antarctic refugia; and (iii) recolonization of maritime Antarctica following the deglaciation process. © 2013 John Wiley & Sons Ltd.

Comparative phylogeography highlights the double-edged sword of climate change faced by arctic- and alpine-adapted mammals.

PubMed

Lanier, Hayley C; Gunderson, Aren M; Weksler, Marcelo; Fedorov, Vadim B; Olson, Link E

2015-01-01

Recent studies suggest that alpine and arctic organisms may have distinctly different phylogeographic histories from temperate or tropical taxa, with recent range contraction into interglacial refugia as opposed to post-glacial expansion out of refugia. We use a combination of phylogeographic inference, demographic reconstructions, and hierarchical Approximate Bayesian Computation to test for phylodemographic concordance among five species of alpine-adapted small mammals in eastern Beringia. These species (Collared Pikas, Hoary Marmots, Brown Lemmings, Arctic Ground Squirrels, and Singing Voles) vary in specificity to alpine and boreal-tundra habitat but share commonalities (e.g., cold tolerance and nunatak survival) that might result in concordant responses to Pleistocene glaciations. All five species contain a similar phylogeographic disjunction separating eastern and Beringian lineages, which we show to be the result of simultaneous divergence. Genetic diversity is similar within each haplogroup for each species, and there is no support for a post-Pleistocene population expansion in eastern lineages relative to those from Beringia. Bayesian skyline plots for four of the five species do not support Pleistocene population contraction. Brown Lemmings show evidence of late Quaternary demographic expansion without subsequent population decline. The Wrangell-St. Elias region of eastern Alaska appears to be an important zone of recent secondary contact for nearctic alpine mammals. Despite differences in natural history and ecology, similar phylogeographic histories are supported for all species, suggesting that these, and likely other, alpine- and arctic-adapted taxa are already experiencing population and/or range declines that are likely to synergistically accelerate in the face of rapid climate change. Climate change may therefore be acting as a double-edged sword that erodes genetic diversity within populations but promotes divergence and the generation of biodiversity.

Pleistocene climate changes shaped the population structure of Partamona seridoensis (Apidae, Meliponini), an endemic stingless bee from the Neotropical dry forest.

PubMed

Miranda, Elder Assis; Ferreira, Kátia Maria; Carvalho, Airton Torres; Martins, Celso Feitosa; Fernandes, Carlo Rivero; Del Lama, Marco Antonio

2017-01-01

Partamona seridoensis is an endemic stingless bee from the Caatinga, a Neotropical dry forest in northeastern Brazil. Like other stingless bees, this species plays an important ecological role as a pollinator. The aim of the present study was to investigate the genetic structure and evolutionary history of P. seridoensis across its current geographic range. Workers from 84 nests from 17 localities were analyzed for COI and Cytb genic regions. The population structure tests (Bayesian phylogenetic inference, AMOVA and haplotype network) consistently characterized two haplogroups (northwestern and eastern), with little gene flow between them, generating a high differentiation between them as well as among the populations within each haplogroup. The Mantel test revealed no isolation by distance. No evidence of a potential geographic barrier in the present that could explain the diversification between the P. seridoensis haplogroups was found. However, Pleistocene climatic changes may explain this differentiation, since the initial time for the P. seridoensis lineages diversification took place during the mid-Pleistocene, specifically the interglacial period, when the biota is presumed to have been more associated with dry conditions and had more restricted, fragmented geographical distribution. This event may have driven diversification by isolating the two haplogroups. Otherwise, the climatic changes in the late Pleistocene must not have drastically affected the population dynamics of P. seridoensis, since the Bayesian Skyline Plot did not reveal any substantial fluctuation in effective population size in either haplogroup. Considering its importance and the fact that it is an endemic bee from a very threatened Neotropical dry forest, the results herein could be useful to the development of conservation strategies for P. seridoensis.

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.

Comparative Phylogeography Highlights the Double-Edged Sword of Climate Change Faced by Arctic- and Alpine-Adapted Mammals

PubMed Central

Lanier, Hayley C.; Gunderson, Aren M.; Weksler, Marcelo; Fedorov, Vadim B.; Olson, Link E.

2015-01-01

Recent studies suggest that alpine and arctic organisms may have distinctly different phylogeographic histories from temperate or tropical taxa, with recent range contraction into interglacial refugia as opposed to post-glacial expansion out of refugia. We use a combination of phylogeographic inference, demographic reconstructions, and hierarchical Approximate Bayesian Computation to test for phylodemographic concordance among five species of alpine-adapted small mammals in eastern Beringia. These species (Collared Pikas, Hoary Marmots, Brown Lemmings, Arctic Ground Squirrels, and Singing Voles) vary in specificity to alpine and boreal-tundra habitat but share commonalities (e.g., cold tolerance and nunatak survival) that might result in concordant responses to Pleistocene glaciations. All five species contain a similar phylogeographic disjunction separating eastern and Beringian lineages, which we show to be the result of simultaneous divergence. Genetic diversity is similar within each haplogroup for each species, and there is no support for a post-Pleistocene population expansion in eastern lineages relative to those from Beringia. Bayesian skyline plots for four of the five species do not support Pleistocene population contraction. Brown Lemmings show evidence of late Quaternary demographic expansion without subsequent population decline. The Wrangell-St. Elias region of eastern Alaska appears to be an important zone of recent secondary contact for nearctic alpine mammals. Despite differences in natural history and ecology, similar phylogeographic histories are supported for all species, suggesting that these, and likely other, alpine- and arctic-adapted taxa are already experiencing population and/or range declines that are likely to synergistically accelerate in the face of rapid climate change. Climate change may therefore be acting as a double-edged sword that erodes genetic diversity within populations but promotes divergence and the generation of biodiversity. PMID:25734275

Tracing the epidemic history of hepatitis C virus genotypes in Saudi Arabia.

PubMed

Khan, Anis; Al Balwi, Mohammed; AlAyyar, Latifah; AlAbdulkareem, Ibrahim; Albekairy, Abdulkareem; Aljumah, Abdulrahman

2017-08-01

HCV genotype 4 is highly prevalent in many Middle Eastern countries, yet little is known about the genotype's epidemic history at the subtype-level in this region. To address the dearth of data from Saudi Arabia (SA) we genotyped 230 HCV isolates in the core/E- and NS5B-region and analyzed using Bayesian phylogenetic approaches. HCV genotype 4 (HCV/4) was positive in 61.7% (142/230) of isolates belonging to 7 different subtypes with the predominance of 4d (73/142; 51.4%) followed by 4a (51/142; 35.9%). Phylogenetic analysis also revealed a distinct epidemiological cluster of HCV/4d for Saudi Arabia. HCV/1 appeared as the second most prevalent genotype positive in 31.3% (72/230) of isolates with the predominance of 1b (53/72; 73.6%) followed by 1a (16/72; 22.2%), and 1g (3/72; 4.1%). A small proportion of isolates belonged to HCV/3a (12/230; 5.2%), and HCV/2a (4/230; 1.7%). We estimate that the genotype 4 common ancestor existed around 1935 (1850-1985). Genotype 4 originated plausibly in Central Africa and multiple subtypes disseminated across African borders since ~1970, including subtype 4d which dominates current HCV infections in Saudi Arabia. The Bayesian skyline plot (BSP) analysis showed that genotype 4d entered the Saudi population in 1900. The effective number of HCV infections grew gradually until the second half of the 1950s and more rapidly until the early-80s through the use of imported blood units and blood products. Subsequently, the rate of HCV infection in the Saudi Arabian population was stabilized through effective screening of blood and infection control measures. Copyright © 2017 Elsevier B.V. All rights reserved.

Inferring the global phylodynamics of influenza A/H3N2 viruses in Taiwan.

PubMed

Gong, Yu-Nong; Tsao, Kuo-Chien; Chen, Guang-Wu

2018-02-20

Influenza A/H3N2 viruses are characterized by highly mutated RNA genomes. In this study, we focused on tracing the phylodynamics of Taiwanese strains over the past four decades. All Taiwanese H3N2 HA1 sequences and references were downloaded from public database. A Bayesian skyline plot (BSP) and phylogenetic tree were used to analyze the evolutionary history, and Bayesian phylogeographic analysis was applied to predict the spatiotemporal migrations of influenza outbreaks. Genetic diversity was found to have peaked near the summer of 2009 in BSP, in addition to the two earlier reported ones in summer of 2005 and 2007. We predicted their spatiotemporal migrations and found the summer epidemic of 2005 from Korea, and 2007 and 2009 from the Western United States. BSP also predicted an elevated genetic diversity in 2015-2017. Quasispecies were found over approximately 20% of the strains included in this time span. In addition, a first-time seen N31S mutation was noted in Taiwan in 2016-2017. We comprehensively investigated the evolutionary history of Taiwanese strains in 1979-2017. An epidemic caution could thus be raised if genetic diversity was found to have peaked. An example showed a newly-discovered cluster in 2016-2017 strains featuring a mutation N31S together with HA-160 quasispecies. Phylogeographic analysis, moreover, provided useful insights in tracing the possible source and migrations of these epidemics around the world. We demonstrated that Asian destinations including Taiwan were the immediate followers, while U.S. continent was predicted the origin of two summer epidemics in 2007 and 2009. Copyright © 2018. Published by Elsevier B.V.

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.

Phylodynamics of classical swine fever virus with emphasis on Ecuadorian strains.

PubMed

Garrido Haro, A D; Barrera Valle, M; Acosta, A; J Flores, F

2018-06-01

Classic swine fever virus (CSFV) is a Pestivirus from the Flaviviridae family that affects pigs worldwide and is endemic in several Latin American countries. However, there are still some countries in the region, including Ecuador, for which CSFV molecular information is lacking. To better understand the epidemiology of CSFV in the Americas, sequences from CSFVs from Ecuador were generated and a phylodynamic analysis of the virus was performed. Sequences for the full-length glycoprotein E2 gene of twenty field isolates were obtained and, along with sequences from strains previously described in the Americas and from the most representative strains worldwide, were used to analyse the phylodynamics of the virus. Bayesian methods were used to test several molecular clock and demographic models. A calibrated ultrametric tree and a Bayesian skyline were constructed, and codons associated with positive selection involving immune scape were detected. The best model according to Bayes factors was the strict molecular clock and Bayesian skyline model, which shows that CSFV has an evolution rate of 3.2 × 10 -4 substitutions per site per year. The model estimates the origin of CSFV in the mid-1500s. There is a strong spatial structure for CSFV in the Americas, indicating that the virus is moving mainly through neighbouring countries. The genetic diversity of CSFV has increased constantly since its appearance, with a slight decrease in mid-twentieth century, which coincides, with eradication campaigns in North America. Even though there is no evidence of strong directional evolution of the E2 gene in CSFV, codons 713, 761, 762 and 975 appear to be selected positively and could be related to virulence or pathogenesis. These results reveal how CSFV has spread and evolved since it first appeared in the Americas and provide important information for attaining the goal of eradication of this virus in Latin America. © 2018 Blackwell Verlag GmbH.

Honeybees use the skyline in orientation.

PubMed

Towne, William F; Ritrovato, Antoinette E; Esposto, Antonina; Brown, Duncan F

2017-07-01

In view-based navigation, animals acquire views of the landscape from various locations and then compare the learned views with current views in order to orient in certain directions or move toward certain destinations. One landscape feature of great potential usefulness in view-based navigation is the skyline, the silhouette of terrestrial objects against the sky, as it is distant, relatively stable and easy to detect. The skyline has been shown to be important in the view-based navigation of ants, but no flying insect has yet been shown definitively to use the skyline in this way. Here, we show that honeybees do indeed orient using the skyline. A feeder was surrounded with an artificial replica of the natural skyline there, and the bees' departures toward the nest were recorded from above with a video camera under overcast skies (to eliminate celestial cues). When the artificial skyline was rotated, the bees' departures were rotated correspondingly, showing that the bees oriented by the artificial skyline alone. We discuss these findings in the context of the likely importance of the skyline in long-range homing in bees, the likely importance of altitude in using the skyline, the likely role of ultraviolet light in detecting the skyline, and what we know about the bees' ability to resolve skyline features. © 2017. Published by The Company of Biologists Ltd.

Application of a fast skyline computation algorithm for serendipitous searching problems

NASA Astrophysics Data System (ADS)

Koizumi, Kenichi; Hiraki, Kei; Inaba, Mary

2018-02-01

Skyline computation is a method of extracting interesting entries from a large population with multiple attributes. These entries, called skyline or Pareto optimal entries, are known to have extreme characteristics that cannot be found by outlier detection methods. Skyline computation is an important task for characterizing large amounts of data and selecting interesting entries with extreme features. When the population changes dynamically, the task of calculating a sequence of skyline sets is called continuous skyline computation. This task is known to be difficult to perform for the following reasons: (1) information of non-skyline entries must be stored since they may join the skyline in the future; (2) the appearance or disappearance of even a single entry can change the skyline drastically; (3) it is difficult to adopt a geometric acceleration algorithm for skyline computation tasks with high-dimensional datasets. Our new algorithm called jointed rooted-tree (JR-tree) manages entries using a rooted tree structure. JR-tree delays extend the tree to deep levels to accelerate tree construction and traversal. In this study, we presented the difficulties in extracting entries tagged with a rare label in high-dimensional space and the potential of fast skyline computation in low-latency cell identification technology.

Past and future demographic dynamics of alpine species: limited genetic consequences despite dramatic range contraction in a plant from the Spanish Sierra Nevada.

PubMed

Blanco-Pastor, J L; Fernández-Mazuecos, M; Vargas, P

2013-08-01

Anthropogenic global climate change is expected to cause severe range contractions among alpine plants. Alpine areas in the Mediterranean region are of special concern because of the high abundance of endemic species with narrow ranges. This study combined species distribution models, population structure analyses and Bayesian skyline plots to trace the past and future distribution and diversity of Linaria glacialis, an endangered narrow endemic species that inhabits summits of Sierra Nevada (Spain). The results showed that: (i) the habitat of this alpine-Mediterranean species in Sierra Nevada suffered little changes during glacial and interglacial stages of late Quaternary; (ii) climatic oscillations in the last millennium (Medieval Warm Period and Little Ice Age) moderately affected the demographic trends of L. glacialis; (iii) future warming conditions will cause severe range contractions; and (iv) genetic diversity will not diminish at the same pace as the distribution range. As a consequence of the low population structure of this species, genetic impoverishment in the alpine zones of Sierra Nevada should be limited during range contraction. We conclude that maintenance of large effective population sizes via high mutation rates and high levels of gene flow may promote the resilience of alpine plant species when confronted with global warming. © 2013 John Wiley & Sons Ltd.

Landscape genetics indicate recently increased habitat fragmentation in African forest-associated chafers.

PubMed

Eberle, Jonas; Rödder, Dennis; Beckett, Marc; Ahrens, Dirk

2017-05-01

Today, indigenous forests cover less than 0.6% of South Africa's land surface and are highly fragmented. Most forest relicts are very small and typically occur in fire-protected gorges along the eastern Great Escarpment. Yet, they hold a unique and valuable fauna with high endemism and ancient phylogenetic lineages, fostered by long-term climatic stability and complex microclimates. Despite numerous studies on southern African vegetation cover, the current state of knowledge about the natural extension of indigenous forests is rather fragmentary. We use an integrated approach of population-level phylogeography and climatic niche modeling of forest-associated chafer species to assess connectivity and extent of forest habitats since the last glacial maximum. Current and past species distribution models ascertained potential fluctuations of forest distribution and supported a much wider potential current extension of forests based on climatic data. Considerable genetic admixture of mitochondrial and nuclear DNA among many populations and an increase in mean population mutation rate in Extended Bayesian Skyline Plots of all species indicated more extended or better connected forests in the recent past (<5 kya). Genetic isolation of certain populations, as revealed by population differentiation statistics (GST'), as well as landscape connectivity statistics and habitat succession scenarios suggests considerable loss of habitat connectivity. As major anthropogenic influence is likely, conservational actions need to be considered. © 2017 John Wiley & Sons Ltd.

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

Mitogenomes from Egyptian Cattle Breeds: New Clues on the Origin of Haplogroup Q and the Early Spread of Bos taurus from the Near East.

PubMed

Olivieri, Anna; Gandini, Francesca; Achilli, Alessandro; Fichera, Alessandro; Rizzi, Ermanno; Bonfiglio, Silvia; Battaglia, Vincenza; Brandini, Stefania; De Gaetano, Anna; El-Beltagi, Ahmed; Lancioni, Hovirag; Agha, Saif; Semino, Ornella; Ferretti, Luca; Torroni, Antonio

2015-01-01

Genetic studies support the scenario that Bos taurus domestication occurred in the Near East during the Neolithic transition about 10 thousand years (ky) ago, with the likely exception of a minor secondary event in Italy. However, despite the proven effectiveness of whole mitochondrial genome data in providing valuable information concerning the origin of taurine cattle, until now no population surveys have been carried out at the level of mitogenomes in local breeds from the Near East or surrounding areas. Egypt is in close geographic and cultural proximity to the Near East, in particular the Nile Delta region, and was one of the first neighboring areas to adopt the Neolithic package. Thus, a survey of mitogenome variation of autochthonous taurine breeds from the Nile Delta region might provide new insights on the early spread of cattle rearing outside the Near East. Using Illumina high-throughput sequencing we characterized the mitogenomes from two cattle breeds, Menofi (N = 17) and Domiaty (N = 14), from the Nile Delta region. Phylogenetic and Bayesian analyses were subsequently performed. Phylogenetic analyses of the 31 mitogenomes confirmed the prevalence of haplogroup T1, similar to most African cattle breeds, but showed also high frequencies for haplogroups T2, T3 and Q1, and an extremely high haplotype diversity, while Bayesian skyline plots pointed to a main episode of population growth ~12.5 ky ago. Comparisons of Nile Delta mitogenomes with those from other geographic areas revealed that (i) most Egyptian mtDNAs are probably direct local derivatives from the founder domestic herds which first arrived from the Near East and the extent of gene flow from and towards the Nile Delta region was limited after the initial founding event(s); (ii) haplogroup Q1 was among these founders, thus proving that it underwent domestication in the Near East together with the founders of the T clades.

Mitogenomes from Egyptian Cattle Breeds: New Clues on the Origin of Haplogroup Q and the Early Spread of Bos taurus from the Near East

PubMed Central

Olivieri, Anna; Gandini, Francesca; Achilli, Alessandro; Fichera, Alessandro; Rizzi, Ermanno; Bonfiglio, Silvia; Battaglia, Vincenza; Brandini, Stefania; De Gaetano, Anna; El-Beltagi, Ahmed; Lancioni, Hovirag; Agha, Saif; Semino, Ornella; Ferretti, Luca; Torroni, Antonio

2015-01-01

Background Genetic studies support the scenario that Bos taurus domestication occurred in the Near East during the Neolithic transition about 10 thousand years (ky) ago, with the likely exception of a minor secondary event in Italy. However, despite the proven effectiveness of whole mitochondrial genome data in providing valuable information concerning the origin of taurine cattle, until now no population surveys have been carried out at the level of mitogenomes in local breeds from the Near East or surrounding areas. Egypt is in close geographic and cultural proximity to the Near East, in particular the Nile Delta region, and was one of the first neighboring areas to adopt the Neolithic package. Thus, a survey of mitogenome variation of autochthonous taurine breeds from the Nile Delta region might provide new insights on the early spread of cattle rearing outside the Near East. Methodology Using Illumina high-throughput sequencing we characterized the mitogenomes from two cattle breeds, Menofi (N = 17) and Domiaty (N = 14), from the Nile Delta region. Phylogenetic and Bayesian analyses were subsequently performed. Conclusions Phylogenetic analyses of the 31 mitogenomes confirmed the prevalence of haplogroup T1, similar to most African cattle breeds, but showed also high frequencies for haplogroups T2, T3 and Q1, and an extremely high haplotype diversity, while Bayesian skyline plots pointed to a main episode of population growth ~12.5 ky ago. Comparisons of Nile Delta mitogenomes with those from other geographic areas revealed that (i) most Egyptian mtDNAs are probably direct local derivatives from the founder domestic herds which first arrived from the Near East and the extent of gene flow from and towards the Nile Delta region was limited after the initial founding event(s); (ii) haplogroup Q1 was among these founders, thus proving that it underwent domestication in the Near East together with the founders of the T clades. PMID:26513361

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.

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.

Skyline: an open source document editor for creating and analyzing targeted proteomics experiments.

PubMed

MacLean, Brendan; Tomazela, Daniela M; Shulman, Nicholas; Chambers, Matthew; Finney, Gregory L; Frewen, Barbara; Kern, Randall; Tabb, David L; Liebler, Daniel C; MacCoss, Michael J

2010-04-01

Skyline is a Windows client application for targeted proteomics method creation and quantitative data analysis. It is open source and freely available for academic and commercial use. The Skyline user interface simplifies the development of mass spectrometer methods and the analysis of data from targeted proteomics experiments performed using selected reaction monitoring (SRM). Skyline supports using and creating MS/MS spectral libraries from a wide variety of sources to choose SRM filters and verify results based on previously observed ion trap data. Skyline exports transition lists to and imports the native output files from Agilent, Applied Biosystems, Thermo Fisher Scientific and Waters triple quadrupole instruments, seamlessly connecting mass spectrometer output back to the experimental design document. The fast and compact Skyline file format is easily shared, even for experiments requiring many sample injections. A rich array of graphs displays results and provides powerful tools for inspecting data integrity as data are acquired, helping instrument operators to identify problems early. The Skyline dynamic report designer exports tabular data from the Skyline document model for in-depth analysis with common statistical tools. Single-click, self-updating web installation is available at http://proteome.gs.washington.edu/software/skyline. This web site also provides access to instructional videos, a support board, an issues list and a link to the source code project.

Mitochondrial DNA analyses revealed low genetic diversity in the endangered Indian wild ass Equus hemionus khur.

PubMed

Khaire, Devendra; Atkulwar, Ashwin; Farah, Sameera; Baig, Mumtaz

2017-09-01

The Indian wild ass Equus hemionus khur, belonging to ass-like equid branch, inhabits the dry and arid desert of the Little Rann of Kutch, Gujarat. The E. h. khur is the sole survivor of Asiatic wild ass species/subspecies in South Asia. To provide first ever insights into the genetic diversity, phylogeny, and demography of the endangered Indian wild ass, we sampled 52 free-ranging individuals from the Little Rann of Kutch by using a non-invasive methodology. The sequencing of 230 bp in cytochrome b (Cyt b) and displacement loop (D-loop) region revealed that current ∼4000 extant population of Indian wild ass harbours low genetic diversity. Phylogenetic analyses confirmed that E. h. khur, E. h. onager, and E. h. kulan belong to a single strict monophyletic clade. Therefore, we suggest the delimitation of the five E. hemionus subspecies in vogue to a single species E. hemionus. The application of molecular clock confirmed that the Asiatic wild ass had undergone diversification 0.65 Million years ago. Demographic measurements assessed using a Bayesian skyline plot demonstrated decline in the maternal effective population size of the Indian wild ass during different periods; these periods coincided with the origin and rise of the Indus civilization in the northwest of the Indian subcontinent during the Neolithic. In conclusion, maintaining high genetic diversity in the existing isolated population of 4000 Indian wild asses inhabiting the wild ass sanctuary is important compared with subspecies preservation alone.

Skyline: an open source document editor for creating and analyzing targeted proteomics experiments

PubMed Central

MacLean, Brendan; Tomazela, Daniela M.; Shulman, Nicholas; Chambers, Matthew; Finney, Gregory L.; Frewen, Barbara; Kern, Randall; Tabb, David L.; Liebler, Daniel C.; MacCoss, Michael J.

2010-01-01

Summary: Skyline is a Windows client application for targeted proteomics method creation and quantitative data analysis. It is open source and freely available for academic and commercial use. The Skyline user interface simplifies the development of mass spectrometer methods and the analysis of data from targeted proteomics experiments performed using selected reaction monitoring (SRM). Skyline supports using and creating MS/MS spectral libraries from a wide variety of sources to choose SRM filters and verify results based on previously observed ion trap data. Skyline exports transition lists to and imports the native output files from Agilent, Applied Biosystems, Thermo Fisher Scientific and Waters triple quadrupole instruments, seamlessly connecting mass spectrometer output back to the experimental design document. The fast and compact Skyline file format is easily shared, even for experiments requiring many sample injections. A rich array of graphs displays results and provides powerful tools for inspecting data integrity as data are acquired, helping instrument operators to identify problems early. The Skyline dynamic report designer exports tabular data from the Skyline document model for in-depth analysis with common statistical tools. Availability: Single-click, self-updating web installation is available at http://proteome.gs.washington.edu/software/skyline. This web site also provides access to instructional videos, a support board, an issues list and a link to the source code project. Contact: brendanx@u.washington.edu Supplementary information: Supplementary data are available at Bioinformatics online. PMID:20147306

A hydraulic assist for a manual skyline lock

Treesearch

Cleveland J. Biller

1977-01-01

A hydraulic locking mechanism was designed to replace the manual skyline lock on a small standing skyline with gravity carriage. It improved the efficiency of the operation by reducing setup and takedown times and reduced the hazard to the crew.

48. VIEW OF SKYLINE DRIVE FROM THE ROCKY PEAK OF ...

Library of Congress Historic Buildings Survey, Historic Engineering Record, Historic Landscapes Survey

48. VIEW OF SKYLINE DRIVE FROM THE ROCKY PEAK OF STONY MAN MOUNTAIN (EL. 4,011). LOOKING NORTHEAST. STONY MAN OVERLOOK VISIBLE IN THE DISTANCE. - Skyline Drive, From Front Royal, VA to Rockfish Gap, VA , Luray, Page County, VA

Conceptions of Height and Verticality in the History of Skyscrapers and Skylines

NASA Astrophysics Data System (ADS)

Maslovskaya, Oksana; Ignatov, Grigoriy

2018-03-01

The main goal of this article is to reveal the significance of height and verticality history of skyscrapers and skylines. The objectives are as follows: 1. trace the origin of design concepts related to skyscraper; 2. discuss the perceived experience of the cultural aspects of skyscrapers and skylines; 3. describe the differences and similarities of the profiles of with comparable skylines. The methodology of study is designed to explore the perceived theory and principals of skyscraper and skyline development phenomenon and its key features. The skyscraper reveals an assertive creative form of vertical design. Skyscraper construction also relates to the origin of ancient cultural symbolism as the dominant vertical element as the main features of an ordered space. The historical idea of height reaches back to the earliest civilization such as the Tower of Babel. Philosophical approaches of elements of such post-structuralism have been included in studying of skyscraper phenomenon. The analysis of skyscraper and their resulting skyline are examined to show the connection to their origins with their concepts of height and verticality. From the historical perspective, cities with skyscrapers and a skyline turn out to be an assertive manifestation of common ideas of height and verticality.

Skyline Harvesting in Appalachia

Treesearch

J. N. Kochenderfer; G. W. Wendel

1978-01-01

The URUS, a small standing skyline system, was tested in the Appalachian Mountains of north-central West Virginia. Some problems encountered with this small, mobile system are discussed. From the results of this test and observation of skyline systems used in the western United States, the authors suggest some machine characteristics that would be desirable for use in...

Genetic structure and demographic inference of the regular sea urchin Sterechinus neumayeri (Meissner, 1900) in the Southern Ocean: The role of the last glaciation.

PubMed

Díaz, Angie; Gérard, Karin; González-Wevar, Claudio; Maturana, Claudia; Féral, Jean-Pierre; David, Bruno; Saucède, Thomas; Poulin, Elie

2018-01-01

One of the most relevant characteristics of the extant Southern Ocean fauna is its resiliency to survive glacial processes of the Quaternary. These climatic events produced catastrophic habitat reductions and forced some marine benthic species to move, adapt or go extinct. The marine benthic species inhabiting the Antarctic upper continental shelf faced the Quaternary glaciations with different strategies that drastically modified population sizes and thus affected the amount and distribution of intraspecific genetic variation. Here we present new genetic information for the most conspicuous regular sea urchin of the Antarctic continental shelf, Sterechinus neumayeri. We studied the patterns of genetic diversity and structure in this broadcast-spawner across three Antarctic regions: Antarctic Peninsula, the Weddell Sea and Adélie Land in East Antarctica. Genetic analyses based on mitochondrial and nuclear markers suggested that S. neumayeri is a single genetic unit around the Antarctic continent. The species is characterized by low levels of genetic diversity and exhibits a typical star-like haplotype genealogy that supports the hypothesis of a single in situ refugium. Based on two mutation rates standardized for this genus, the Bayesian Skyline plot analyses detected a rapid demographic expansion after the Last Glacial Maximum. We propose a scenario of rapid postglacial expansion and recolonization of Antarctic shallow areas from a less ice-impacted refugium where the species survived the LGM. Considering the patterns of genetic diversity and structure recorded in the species, this refugium was probably located in East Antarctica.

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.

Diversification in the South American Pampas: the genetic and morphological variation of the widespread Petunia axillaris complex (Solanaceae).

PubMed

Turchetto, Caroline; Fagundes, Nelson J R; Segatto, Ana L A; Kuhlemeier, Cris; Solís Neffa, Viviana G; Speranza, Pablo R; Bonatto, Sandro L; Freitas, Loreta B

2014-02-01

Understanding the spatiotemporal distribution of genetic variation and the ways in which this distribution is connected to the ecological context of natural populations is fundamental for understanding the nature and mode of intraspecific and, ultimately, interspecific differentiation. The Petunia axillaris complex is endemic to the grasslands of southern South America and includes three subspecies: P. a. axillaris, P. a. parodii and P. a. subandina. These subspecies are traditionally delimited based on both geography and floral morphology, although the latter is highly variable. Here, we determined the patterns of genetic (nuclear and cpDNA), morphological and ecological (bioclimatic) variation of a large number of P. axillaris populations and found that they are mostly coincident with subspecies delimitation. The nuclear data suggest that the subspecies are likely independent evolutionary units, and their morphological differences may be associated with local adaptations to diverse climatic and/or edaphic conditions and population isolation. The demographic dynamics over time estimated by skyline plot analyses showed different patterns for each subspecies in the last 100 000 years, which is compatible with a divergence time between 35 000 and 107 000 years ago between P. a. axillaris and P. a. parodii, as estimated with the IMa program. Coalescent simulation tests using Approximate Bayesian Computation do not support previous suggestions of extensive gene flow between P. a. axillaris and P. a. parodii in their contact zone. © 2013 John Wiley & Sons Ltd.

Genetic structure and demographic inference of the regular sea urchin Sterechinus neumayeri (Meissner, 1900) in the Southern Ocean: The role of the last glaciation

PubMed Central

Gérard, Karin; González-Wevar, Claudio; Maturana, Claudia; Féral, Jean-Pierre; David, Bruno; Saucède, Thomas; Poulin, Elie

2018-01-01

One of the most relevant characteristics of the extant Southern Ocean fauna is its resiliency to survive glacial processes of the Quaternary. These climatic events produced catastrophic habitat reductions and forced some marine benthic species to move, adapt or go extinct. The marine benthic species inhabiting the Antarctic upper continental shelf faced the Quaternary glaciations with different strategies that drastically modified population sizes and thus affected the amount and distribution of intraspecific genetic variation. Here we present new genetic information for the most conspicuous regular sea urchin of the Antarctic continental shelf, Sterechinus neumayeri. We studied the patterns of genetic diversity and structure in this broadcast-spawner across three Antarctic regions: Antarctic Peninsula, the Weddell Sea and Adélie Land in East Antarctica. Genetic analyses based on mitochondrial and nuclear markers suggested that S. neumayeri is a single genetic unit around the Antarctic continent. The species is characterized by low levels of genetic diversity and exhibits a typical star-like haplotype genealogy that supports the hypothesis of a single in situ refugium. Based on two mutation rates standardized for this genus, the Bayesian Skyline plot analyses detected a rapid demographic expansion after the Last Glacial Maximum. We propose a scenario of rapid postglacial expansion and recolonization of Antarctic shallow areas from a less ice-impacted refugium where the species survived the LGM. Considering the patterns of genetic diversity and structure recorded in the species, this refugium was probably located in East Antarctica. PMID:29874287

Postglacial recolonization at a snail's pace (Trochulus villosus): confronting competing refugia hypotheses using model selection.

PubMed

Dépraz, A; Cordellier, M; Hausser, J; Pfenninger, M

2008-05-01

The localization of Last Glacial Maximum (LGM) refugia is crucial information to understand a species' history and predict its reaction to future climate changes. However, many phylogeographical studies often lack sampling designs intensive enough to precisely localize these refugia. The hairy land snail Trochulus villosus has a small range centred on Switzerland, which could be intensively covered by sampling 455 individuals from 52 populations. Based on mitochondrial DNA sequences (COI and 16S), we identified two divergent lineages with distinct geographical distributions. Bayesian skyline plots suggested that both lineages expanded at the end of the LGM. To find where the origin populations were located, we applied the principles of ancestral character reconstruction and identified a candidate refugium for each mtDNA lineage: the French Jura and Central Switzerland, both ice-free during the LGM. Additional refugia, however, could not be excluded, as suggested by the microsatellite analysis of a population subset. Modelling the LGM niche of T. villosus, we showed that suitable climatic conditions were expected in the inferred refugia, but potentially also in the nunataks of the alpine ice shield. In a model selection approach, we compared several alternative recolonization scenarios by estimating the Akaike information criterion for their respective maximum-likelihood migration rates. The 'two refugia' scenario received by far the best support given the distribution of genetic diversity in T. villosus populations. Provided that fine-scale sampling designs and various analytical approaches are combined, it is possible to refine our necessary understanding of species responses to environmental changes.

Molecular insights into the colonization and chromosomal diversification of Madeiran house mice.

PubMed

Förster, D W; Gündüz, I; Nunes, A C; Gabriel, S; Ramalhinho, M G; Mathias, M L; Britton-Davidian, J; Searle, J B

2009-11-01

The colonization history of Madeiran house mice was investigated by analysing the complete mitochondrial (mt) D-loop sequences of 156 mice from the island of Madeira and mainland Portugal, extending on previous studies. The numbers of mtDNA haplotypes from Madeira and mainland Portugal were substantially increased (17 and 14 new haplotypes respectively), and phylogenetic analysis confirmed the previously reported link between the Madeiran archipelago and northern Europe. Sequence analysis revealed the presence of four mtDNA lineages in mainland Portugal, of which one was particularly common and widespread (termed the 'Portugal Main Clade'). There was no support for population bottlenecks during the formation of the six Robertsonian chromosome races on the island of Madeira, and D-loop sequence variation was not found to be structured according to karyotype. The colonization time of the Madeiran archipelago by Mus musculus domesticus was approached using two molecular dating methods (mismatch distribution and Bayesian skyline plot). Time estimates based on D-loop sequence variation at mainland sites (including previously published data from France and Turkey) were evaluated in the context of the zooarchaeological record of M. m. domesticus. A range of values for mutation rate (mu) and number of mouse generations per year was considered in these analyses because of the uncertainty surrounding these two parameters. The colonization of Portugal and Madeira by house mice is discussed in the context of the best-supported parameter values. In keeping with recent studies, our results suggest that mutation rate estimates based on interspecific divergence lead to gross overestimates concerning the timing of recent within-species events.

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.

Climate Is Not All: Evidence From Phylogeography of Rhodiola fastigiata (Crassulaceae) and Comparison to Its Closest Relatives.

PubMed

Zhang, Jian-Qiang; Zhong, Da-Lv; Song, Wei-Jie; Zhu, Ruo-Wei; Sun, Wei-Yue

2018-01-01

How geological events and climate oscillations in the Pleistocene glaciation shaped the geographic distribution of genetic variation of species on the Qinghai-Tibetan Plateau (QTP) and its adjacent areas has been extensively studied. However, little studies have investigated whether closely related species in the same genus with similar physiological and life history traits responded similarly to the glacial climatic oscillations. If this is not the case, we would expect that the population histories of studied species were not driven by extrinsic environmental changes alone. Here we conducted a phylogeographic study of a succulent alpine plant Rhodiola fastigiata , using sequences from chloroplast genome and nrITS region, as well as ecological niche modeling. The results of R. fastigiata were compared to other congeneric species that have been studied, especially to R. alsia and R. crenulata . We found that for both markers, two geographic groups could be revealed, corresponding to the QTP plateau and the Hengduan Mountains, respectively, indicating isolated refugia in those two areas. The two groups diverged 1.23 Mya during the Pleistocene. We detected no significant population expansion by mismatch distribution analysis and Bayesian Skyline Plot. We found that even these similar species with similar physiological and life history traits have had different demographic histories in the Quaternary glacial periods. Our comparative phylogeographic study sheds new lights into phylogeographic research that extrinsic environmental changes are not the only factor that can drive population demography, and other factors, such as coevolved interactions between plants and their specialized pathogens, that probably played a role need to be examined with more case studies.

Genetic Diversity in Endangered Guizhou Snub-Nosed Monkeys (Rhinopithecus brelichi): Contrasting Results from Microsatellite and Mitochondrial DNA Data

PubMed Central

Kolleck, Jakob; Yang, Mouyu; Zinner, Dietmar; Roos, Christian

2013-01-01

To evaluate the conservation status of a species or population it is necessary to gain insight into its ecological requirements, reproduction, genetic population structure, and overall genetic diversity. In our study we examined the genetic diversity of Rhinopithecus brelichi by analyzing microsatellite data and compared them with already existing data derived from mitochondrial DNA, which revealed that R. brelichi exhibits the lowest mitochondrial diversity of all so far studied Rhinopithecus species. In contrast, the genetic diversity of nuclear DNA is high and comparable to other Rhinopithecus species, i.e. the examined microsatellite loci are similarly highly polymorphic as in other species of the genus. An explanation for these differences in mitochondrial and nuclear genetic diversity could be a male biased dispersal. Females most likely stay within their natal band and males migrate between bands, thus mitochondrial DNA will not be exchanged between bands but nuclear DNA via males. A Bayesian Skyline Plot based on mitochondrial DNA sequences shows a strong decrease of the female effective population size (Nef) starting about 3,500 to 4,000 years ago, which concurs with the increasing human population in the area and respective expansion of agriculture. Given that we found no indication for a loss of nuclear DNA diversity in R. brelichi it seems that this factor does not represent the most prominent conservation threat for the long-term survival of the species. Conservation efforts should therefore focus more on immediate threats such as development of tourism and habitat destruction. PMID:24009761

Phylodynamic and Genetic Diversity of Canine Parvovirus Type 2c in Taiwan

PubMed Central

Chiang, Shu-Yun; Wu, Hung-Yi; Lin, Jih-Hui; Chiou, Ming-Tang; Lin, Chao-Nan

2017-01-01

Canine parvovirus type 2c (CPV-2c) emerged in 2000 and is known for causing a more severe disease than other CPV-2 variants in puppies. In 2015, the emerging CPV-2c variant was isolated in Taiwan and it subsequently became the predominant variant. To trace the evolution of Taiwanese CPV-2c, we compared complete VP2 genes of CPV-2c from Taiwan and sequences obtained from GenBank. The evolutionary rate of CPV-2c was estimated to be 4.586 × 10−4 substitutions per site per year (95% highest posterior density (HPD) was 3.284–6.076 × 10−4). The time to the most recent common ancestor (TMRCA) dated to 1990 (95% HPD: 1984–1996) and 2011 (95% HPD: 2010–2013) for the CPV-2c variant and Taiwanese isolates, respectively. The CPV-2c variant isolated from Taiwan was clustered with CPV-2c from China. This phylogenetic clade began to branch off in approximately 2010 (95% HPD was 3.823–6.497). Notably, two unique mutations of Taiwanese CPV-2c were found, Q383R and P410L. In summary, this is the first report on the genome evolution of CPV-2c in Taiwan, revealing that this CPV-2c variant shares a common evolutionary origin with strains from China. The demographic history inferred by the Bayesian skyline plot showed that the effective population of CPV-2c increased until 2006 and then slowly declined until 2011. PMID:29236084

A Bayesian CUSUM plot: Diagnosing quality of treatment.

PubMed

Rosthøj, Steen; Jacobsen, Rikke-Line

2017-12-01

To present a CUSUM plot based on Bayesian diagnostic reasoning displaying evidence in favour of "healthy" rather than "sick" quality of treatment (QOT), and to demonstrate a technique using Kaplan-Meier survival curves permitting application to case series with ongoing follow-up. For a case series with known final outcomes: Consider each case a diagnostic test of good versus poor QOT (expected vs. increased failure rates), determine the likelihood ratio (LR) of the observed outcome, convert LR to weight taking log to base 2, and add up weights sequentially in a plot showing how many times odds in favour of good QOT have been doubled. For a series with observed survival times and an expected survival curve: Divide the curve into time intervals, determine "healthy" and specify "sick" risks of failure in each interval, construct a "sick" survival curve, determine the LR of survival or failure at the given observation times, convert to weights, and add up. The Bayesian plot was applied retrospectively to 39 children with acute lymphoblastic leukaemia with completed follow-up, using Nordic collaborative results as reference, showing equal odds between good and poor QOT. In the ongoing treatment trial, with 22 of 37 children still at risk for event, QOT has been monitored with average survival curves as reference, odds so far favoring good QOT 2:1. QOT in small patient series can be assessed with a Bayesian CUSUM plot, retrospectively when all treatment outcomes are known, but also in ongoing series with unfinished follow-up. © 2017 John Wiley & Sons, Ltd.

Operational test of the prototype peewee yarder.

Treesearch

Charles N. Mann; Ronald W. Mifflin

1979-01-01

An operational test of a small, prototype running skyline yarder was conducted early in 1978. Test results indicate that this yarder concept promises a low cost, high performance system for harvesting small logs where skyline methods are indicated. Timber harvest by thinning took place on 12 uphill and 2 downhill skyline roads, and clearcut harvesting was performed on...

The SKYTOWER and SKYMOBILE programs for locating and designing skyline harvest units.

Treesearch

R.H. Twito; R.J. McGaughey; S.E. Reutebuch

1988-01-01

PLANS, a software package for integrated timber-harvest planning, uses digital terrain models to provide the topographic data needed to fit harvest and transportation designs to specific terrain. SKYTOWER and SKYMOBILE are integral programs in the PLANS package and are used to design the timber-harvest units for skyline systems. SKYTOWER determines skyline payloads and...

Evolutionary Dynamics of West Nile Virus in the United States, 1999–2011: Phylogeny, Selection Pressure and Evolutionary Time-Scale Analysis

PubMed Central

Chancey, Caren; Ball, Christopher; Akolkar, Namita; Land, Kevin J.; Winkelman, Valerie; Stramer, Susan L.; Kramer, Laura D.; Rios, Maria

2013-01-01

West Nile virus (WNV), an arbovirus maintained in a bird-mosquito enzootic cycle, can infect other vertebrates including humans. WNV was first reported in the US in 1999 where, to date, three genotypes belonging to WNV lineage I have been described (NY99, WN02, SW/WN03). We report here the WNV sequences obtained from two birds, one mosquito, and 29 selected human samples acquired during the US epidemics from 2006–2011 and our examination of the evolutionary dynamics in the open-reading frame of WNV isolates reported from 1999–2011. Maximum-likelihood and Bayesian methods were used to perform the phylogenetic analyses and selection pressure analyses were conducted with the HyPhy package. Phylogenetic analysis identified human WNV isolates within the main WNV genotypes that have circulated in the US. Within genotype SW/WN03, we have identified a cluster with strains derived from blood donors and birds from Idaho and North Dakota collected during 2006–2007, termed here MW/WN06. Using different codon-based and branch-site selection models, we detected a number of codons subjected to positive pressure in WNV genes. The mean nucleotide substitution rate for WNV isolates obtained from humans was calculated to be 5.06×10−4 substitutions/site/year (s/s/y). The Bayesian skyline plot shows that after a period of high genetic variability following the introduction of WNV into the US, the WNV population appears to have reached genetic stability. The establishment of WNV in the US represents a unique opportunity to understand how an arbovirus adapts and evolves in a naïve environment. We describe a novel, well-supported cluster of WNV formed by strains collected from humans and birds from Idaho and North Dakota. Adequate genetic surveillance is essential to public health since new mutants could potentially affect viral pathogenesis, decrease performance of diagnostic assays, and negatively impact the efficacy of vaccines and the development of specific therapies. PMID:23738027

Phylogeography of the sandy beach amphipod Haustorioides japonicus along the Sea of Japan: Paleogeographical signatures of cryptic regional divergences

NASA Astrophysics Data System (ADS)

Takada, Yoshitake; Sakuma, Kay; Fujii, Tetsuo; Kojima, Shigeaki

2018-01-01

Recent findings of genetic breaks within apparently continuous marine populations challenge the traditional vicariance paradigm in population genetics. Such "invisible" boundaries are sometimes associated with potential geographic barriers that have forced divergence of an ancestral population, habitat discontinuities, biogeographic disjunctions due to environmental gradients, or a combination of these factors. To explore the factors that influence the genetic population structure of apparently continuous populations along the Sea of Japan, the sandy beach amphipod Haustorioides japonicus was examined. We sampled a total of 300 individuals of H. japonicus from the coast of Japan, and obtained partial sequences of the mitochondrial COI gene. The sequences from 19 local populations were clustered into five groups (Northwestern Pacific, Northern, Central, Southern Sea of Japan, and East China Sea) based on a spatial genetic mixture analysis and a minimum-spanning network. AMOVA and pairwise Fst tests further supported the significant divergence of the five groups. Phylogenetic analysis revealed the relationship among the haplotypes of H. japonicus and outgroups, which inferred the northward range expansion of the species. A relaxed molecular-clock Bayesian analysis inferred the early-to middle-Pleistocene divergence of the populations. Among the five clusters, the Central Sea of Japan showed the highest values for genetic diversity indices indicating the existence of a relatively stable and large population there. The hypothesis is also supported by Bayesian Skyline Plots that showed sudden population expansion for all the clusters except for Central Sea of Japan. The present study shows genetic boundaries between the Sea of Japan and the neighboring seas, probably due to geographic isolation during the Pleistocene glacial periods. We further found divergence between the populations along the apparently continuous coast of the Sea of Japan. Historical changes in the geographic range of H. japonicus in relation to sandy beach habitat availability, account for the genetic breaks among the three populations in the Sea of Japan. The present results infer that the past geographic events influenced the population formation of H. japonicus.

Molecular evolution of respiratory syncytial virus subgroup A genotype NA1 and ON1 attachment glycoprotein (G) gene in central Vietnam.

PubMed

Yoshihara, Keisuke; Le, Minh Nhat; Nagasawa, Koo; Tsukagoshi, Hiroyuki; Nguyen, Hien Anh; Toizumi, Michiko; Moriuchi, Hiroyuki; Hashizume, Masahiro; Ariyoshi, Koya; Dang, Duc Anh; Kimura, Hirokazu; Yoshida, Lay-Myint

2016-11-01

We performed molecular evolutionary analyses of the G gene C-terminal 3rd hypervariable region of RSV-A genotypes NA1 and ON1 strains from the paediatric acute respiratory infection patients in central Vietnam during the 2010-2012 study period. Time-scaled phylogenetic analyses were performed using Bayesian Markov Chain Monte Carlo (MCMC) method, and pairwise distances (p-distances) were calculated. Bayesian Skyline Plot (BSP) was constructed to analyze the time-trend relative genetic diversity of central Vietnam RSV-A strains. We also estimated the N-glycosylation sites within G gene hypervariable region. Amino acid substitutions under positive and negative selection pressure were examined using Conservative Single Likelihood Ancestor Counting (SLAC), Fixed Effects Likelihood (FEL), Internal Fixed Effects Likelihood (IFEL) and Mixed Effects Model for Episodic Diversifying Selection (MEME) models. The majority of central Vietnam ON1 strains detected in 2012 were classified into lineage 1 with few positively selected substitutions. As for the Vietnamese NA1 strains, four lineages were circulating during the study period with a few positive selection sites. Shifting patterns of the predominantly circulating NA1 lineage were observed in each year during the investigation period. Median p-distance of central Vietnam NA1 strains was wider (p-distance=0.028) than that of ON1 (p-distance=0.012). The molecular evolutionary rate of central Vietnam ON1 strains was estimated to be 2.55×10 -2 (substitutions/site/year) and was faster than NA1 (7.12×10 -3 (substitutions/site/year)). Interestingly, the evolutionary rates of both genotypes ON1 and NA1 strains from central Vietnam were faster than the global strains respectively. Furthermore, the shifts of N-glycosylation pattern within the G gene 3rd hypervariable region of Vietnamese NA1 strains were observed in each year. BSP analysis indicated the rapid growth of RSV-A effective population size in early 2012. These results suggested that the molecular evolution of RSV-A G gene detected in central Vietnam was fast with unique evolutionary dynamics. Copyright © 2016 Elsevier B.V. All rights reserved.

An analysis of running skyline load path.

Treesearch

Ward W. Carson; Charles N. Mann

1971-01-01

This paper is intended for those who wish to prepare an algorithm to determine the load path of a running skyline. The mathematics of a simplified approach to this running skyline design problem are presented. The approach employs assumptions which reduce the complexity of the problem to the point where it can be solved on desk-top computers of limited capacities. The...

Panorama: A Targeted Proteomics Knowledge Base

PubMed Central

2015-01-01

Panorama is a web application for storing, sharing, analyzing, and reusing targeted assays created and refined with Skyline,1 an increasingly popular Windows client software tool for targeted proteomics experiments. Panorama allows laboratories to store and organize curated results contained in Skyline documents with fine-grained permissions, which facilitates distributed collaboration and secure sharing of published and unpublished data via a web-browser interface. It is fully integrated with the Skyline workflow and supports publishing a document directly to a Panorama server from the Skyline user interface. Panorama captures the complete Skyline document information content in a relational database schema. Curated results published to Panorama can be aggregated and exported as chromatogram libraries. These libraries can be used in Skyline to pick optimal targets in new experiments and to validate peak identification of target peptides. Panorama is open-source and freely available. It is distributed as part of LabKey Server,2 an open source biomedical research data management system. Laboratories and organizations can set up Panorama locally by downloading and installing the software on their own servers. They can also request freely hosted projects on https://panoramaweb.org, a Panorama server maintained by the Department of Genome Sciences at the University of Washington. PMID:25102069

Registration of Panoramic/Fish-Eye Image Sequence and LiDAR Points Using Skyline Features

PubMed Central

Zhu, Ningning; Jia, Yonghong; Ji, Shunping

2018-01-01

We propose utilizing a rigorous registration model and a skyline-based method for automatic registration of LiDAR points and a sequence of panoramic/fish-eye images in a mobile mapping system (MMS). This method can automatically optimize original registration parameters and avoid the use of manual interventions in control point-based registration methods. First, the rigorous registration model between the LiDAR points and the panoramic/fish-eye image was built. Second, skyline pixels from panoramic/fish-eye images and skyline points from the MMS’s LiDAR points were extracted, relying on the difference in the pixel values and the registration model, respectively. Third, a brute force optimization method was used to search for optimal matching parameters between skyline pixels and skyline points. In the experiments, the original registration method and the control point registration method were used to compare the accuracy of our method with a sequence of panoramic/fish-eye images. The result showed: (1) the panoramic/fish-eye image registration model is effective and can achieve high-precision registration of the image and the MMS’s LiDAR points; (2) the skyline-based registration method can automatically optimize the initial attitude parameters, realizing a high-precision registration of a panoramic/fish-eye image and the MMS’s LiDAR points; and (3) the attitude correction values of the sequences of panoramic/fish-eye images are different, and the values must be solved one by one. PMID:29883431

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

Platform-independent and label-free quantitation of proteomic data using MS1 extracted ion chromatograms in skyline: application to protein acetylation and phosphorylation.

PubMed

Schilling, Birgit; Rardin, Matthew J; MacLean, Brendan X; Zawadzka, Anna M; Frewen, Barbara E; Cusack, Michael P; Sorensen, Dylan J; Bereman, Michael S; Jing, Enxuan; Wu, Christine C; Verdin, Eric; Kahn, C Ronald; Maccoss, Michael J; Gibson, Bradford W

2012-05-01

Despite advances in metabolic and postmetabolic labeling methods for quantitative proteomics, there remains a need for improved label-free approaches. This need is particularly pressing for workflows that incorporate affinity enrichment at the peptide level, where isobaric chemical labels such as isobaric tags for relative and absolute quantitation and tandem mass tags may prove problematic or where stable isotope labeling with amino acids in cell culture labeling cannot be readily applied. Skyline is a freely available, open source software tool for quantitative data processing and proteomic analysis. We expanded the capabilities of Skyline to process ion intensity chromatograms of peptide analytes from full scan mass spectral data (MS1) acquired during HPLC MS/MS proteomic experiments. Moreover, unlike existing programs, Skyline MS1 filtering can be used with mass spectrometers from four major vendors, which allows results to be compared directly across laboratories. The new quantitative and graphical tools now available in Skyline specifically support interrogation of multiple acquisitions for MS1 filtering, including visual inspection of peak picking and both automated and manual integration, key features often lacking in existing software. In addition, Skyline MS1 filtering displays retention time indicators from underlying MS/MS data contained within the spectral library to ensure proper peak selection. The modular structure of Skyline also provides well defined, customizable data reports and thus allows users to directly connect to existing statistical programs for post hoc data analysis. To demonstrate the utility of the MS1 filtering approach, we have carried out experiments on several MS platforms and have specifically examined the performance of this method to quantify two important post-translational modifications: acetylation and phosphorylation, in peptide-centric affinity workflows of increasing complexity using mouse and human models.

Platform-independent and Label-free Quantitation of Proteomic Data Using MS1 Extracted Ion Chromatograms in Skyline

PubMed Central

Schilling, Birgit; Rardin, Matthew J.; MacLean, Brendan X.; Zawadzka, Anna M.; Frewen, Barbara E.; Cusack, Michael P.; Sorensen, Dylan J.; Bereman, Michael S.; Jing, Enxuan; Wu, Christine C.; Verdin, Eric; Kahn, C. Ronald; MacCoss, Michael J.; Gibson, Bradford W.

2012-01-01

Despite advances in metabolic and postmetabolic labeling methods for quantitative proteomics, there remains a need for improved label-free approaches. This need is particularly pressing for workflows that incorporate affinity enrichment at the peptide level, where isobaric chemical labels such as isobaric tags for relative and absolute quantitation and tandem mass tags may prove problematic or where stable isotope labeling with amino acids in cell culture labeling cannot be readily applied. Skyline is a freely available, open source software tool for quantitative data processing and proteomic analysis. We expanded the capabilities of Skyline to process ion intensity chromatograms of peptide analytes from full scan mass spectral data (MS1) acquired during HPLC MS/MS proteomic experiments. Moreover, unlike existing programs, Skyline MS1 filtering can be used with mass spectrometers from four major vendors, which allows results to be compared directly across laboratories. The new quantitative and graphical tools now available in Skyline specifically support interrogation of multiple acquisitions for MS1 filtering, including visual inspection of peak picking and both automated and manual integration, key features often lacking in existing software. In addition, Skyline MS1 filtering displays retention time indicators from underlying MS/MS data contained within the spectral library to ensure proper peak selection. The modular structure of Skyline also provides well defined, customizable data reports and thus allows users to directly connect to existing statistical programs for post hoc data analysis. To demonstrate the utility of the MS1 filtering approach, we have carried out experiments on several MS platforms and have specifically examined the performance of this method to quantify two important post-translational modifications: acetylation and phosphorylation, in peptide-centric affinity workflows of increasing complexity using mouse and human models. PMID:22454539

Phylogeny and population dynamics of respiratory syncytial virus (Rsv) A and B.

PubMed

Martinelli, Marianna; Frati, Elena Rosanna; Zappa, Alessandra; Ebranati, Erika; Bianchi, Silvia; Pariani, Elena; Amendola, Antonella; Zehender, Gianguglielmo; Tanzi, Elisabetta

2014-08-30

Respiratory syncytial virus (RSV) is a major cause of lower respiratory tract infections in infants and young children. RSV is characterised by high variability, especially in the G glycoprotein, which may play a significant role in RSV pathogenicity by allowing immune evasion. To reconstruct the origin and phylodynamic history of RSV, we evaluated the genetic diversity and evolutionary dynamics of RSV A and RSV B isolated from children under 3 years old infected in Italy from 2006 to 2012. Phylogenetic analysis revealed that most of the RSV A sequences clustered with the NA1 genotype, and RSV B sequences were included in the Buenos Aires genotype. The mean evolutionary rates for RSV A and RSV B were estimated to be 2.1 × 10(-3) substitutions (subs)/site/year and 3.03 × 10(-3) subs/site/year, respectively. The time of most recent common ancestor for the tree root went back to the 1940s (95% highest posterior density-HPD: 1927-1951) for RSV A and the 1950s (95%HPD: 1951-1960) for RSV B. The RSV A Bayesian skyline plot (BSP) showed a decrease in transmission events ending in about 2005, when a sharp growth restored the original viral population size. RSV B BSP showed a similar trend. Site-specific selection analysis identified 10 codons under positive selection in RSV A sequences and only one site in RSV B sequences. Although RSV remains difficult to control due to its antigenic diversity, it is important to monitor changes in its coding sequences, to permit the identification of future epidemic strains and to implement vaccine and therapy strategies. Copyright © 2014 Elsevier B.V. All rights reserved.

Rubella epidemic caused by genotype 1E rubella viruses in Beijing, China, in 2007–2011

PubMed Central

2013-01-01

Background A series of different rubella vaccination strategies were implemented to control rubella and prevent congenital rubella virus infection in Beijing, China. The rubella vaccine was available in 1995 in Beijing, and was introduced into the Beijing immunization program (vaccine recipients at their own expense vaccination) in 2000, and was introduced into the National Expanded Program on Immunization (vaccine recipients free vaccination) in 2006. Rubella virological surveillance started in Beijing in 2007. Results The reported rubella incidence rate has decreased dramatically due to the introduction of the vaccine in Beijing since 1995. However, rubella epidemics occurred regardless in 2001 and 2007. The incidence rate among the floating population has gradually increased since 2002, reaching 2 or more times that in the permanent resident population. The peak age of rubella cases gradually changed from <15 years of age to adults after 2005. Phylogenetic analysis was performed and a phylogenetic tree was constructed based on the World Health Organization standard sequence window for rubella virus isolates. All Beijing rubella virus isolates belong to genotype 1E/cluster1 and were clustered interspersed with viruses from other provinces in China. The effective number of infections indicated by a Bayesian skyline plot remained constant from 2007 to 2011. Conclusions The proportion of rubella cases among the floating population has increased significantly in Beijing since 2002, and the disease burden gradually shifted to the older age group (15- to 39-year olds), which has become a major group with rubella infection since 2006. Genotype 1E rubella virus continuously caused a rubella epidemic in Beijing in 2007–2011 and was the predominant virus, and all Beijing genotype 1E viruses belong to cluster 1, which is also widely circulated throughout the country. PMID:23596982

HIV-1 subtype A gag variability and epitope evolution.

PubMed

Abidi, Syed Hani; Kalish, Marcia L; Abbas, Farhat; Rowland-Jones, Sarah; Ali, Syed

2014-01-01

The aim of this study was to examine the course of time-dependent evolution of HIV-1 subtype A on a global level, especially with respect to the dynamics of immunogenic HIV gag epitopes. We used a total of 1,893 HIV-1 subtype A gag sequences representing a timeline from 1985 through 2010, and 19 different countries in Africa, Europe and Asia. The phylogenetic relationship of subtype A gag and its epidemic dynamics was analysed through a Maximum Likelihood tree and Bayesian Skyline plot, genomic variability was measured in terms of G → A substitutions and Shannon entropy, and the time-dependent evolution of HIV subtype A gag epitopes was examined. Finally, to confirm observations on globally reported HIV subtype A sequences, we analysed the gag epitope data from our Kenyan, Pakistani, and Afghan cohorts, where both cohort-specific gene epitope variability and HLA restriction profiles of gag epitopes were examined. The most recent common ancestor of the HIV subtype A epidemic was estimated to be 1956 ± 1. A period of exponential growth began about 1980 and lasted for approximately 7 years, stabilized for 15 years, declined for 2-3 years, then stabilized again from about 2004. During the course of evolution, a gradual increase in genomic variability was observed that peaked in 2005-2010. We observed that the number of point mutations and novel epitopes in gag also peaked concurrently during 2005-2010. It appears that as the HIV subtype A epidemic spread globally, changing population immunogenetic pressures may have played a role in steering immune-evolution of this subtype in new directions. This trend is apparent in the genomic variability and epitope diversity of HIV-1 subtype A gag sequences.

Population structure analysis of the neglected parasite Thelazia callipaeda revealed high genetic diversity in Eastern Asia isolates.

PubMed

Zhang, Xi; Shi, Ya Li; Han, Lu Lu; Xiong, Chen; Yi, Shi Qi; Jiang, Peng; Wang, Zeng Xian; Shen, Ji Long; Cui, Jing; Wang, Zhong Quan

2018-01-01

Thelazia callipaeda is the causative agent of thelaziasis in canids, felids and humans. However, the population genetic structure regarding this parasite remains unclear. In this study, we first explored the genetic variation of 32 T. callipaeda clinical isolates using the following multi-molecular markers: cox1, cytb, 12S rDNA, ITS1 and 18S rDNA. The isolates were collected from 13 patients from 11 geographical locations in China. Next, the population structure of T. callipaeda from Europe and other Asian countries was analyzed using the cox1 sequences collected during this study and from the GenBank database. In general, the Chinese clinical isolates of T. callipaeda expressed high genetic diversity. Based on the cox1 gene, a total of 21 haplotypes were identified. One only circulated in European countries (Hap1), while the other 20 haplotypes were dispersed in Korea, Japan and China. There were five nucleotide positions in the cox1 sequences that were confirmed as invariable among individuals from Europe and Asia, but the sequences were distinct between these two regions. Population differences between Europe and Asian countries were greater than those among China, Korea and Japan. The T. callipaeda populations from Europe and Asia should be divided into two separate sub-populations. These two groups started to diverge during the middle Pleistocene. Neutrality tests, mismatch distribution and Bayesian skyline plot (BSP) analysis all rejected possible population expansion of T. callipaeda. The Asian population of T. callipaeda has a high level of genetic diversity, but further studies should be performed to explore the biology, ecology and epidemiology of T. callipaeda.

Rubella epidemic caused by genotype 1E rubella viruses in Beijing, China, in 2007-2011.

PubMed

Chen, Meng; Zhu, Zhen; Liu, Donglei; Huang, Guohong; Huang, Fang; Wu, Jiang; Zhang, Tiegang; Xu, Wenbo; Pang, Xinghuo

2013-04-18

A series of different rubella vaccination strategies were implemented to control rubella and prevent congenital rubella virus infection in Beijing, China. The rubella vaccine was available in 1995 in Beijing, and was introduced into the Beijing immunization program (vaccine recipients at their own expense vaccination) in 2000, and was introduced into the National Expanded Program on Immunization (vaccine recipients free vaccination) in 2006. Rubella virological surveillance started in Beijing in 2007. The reported rubella incidence rate has decreased dramatically due to the introduction of the vaccine in Beijing since 1995. However, rubella epidemics occurred regardless in 2001 and 2007. The incidence rate among the floating population has gradually increased since 2002, reaching 2 or more times that in the permanent resident population. The peak age of rubella cases gradually changed from <15 years of age to adults after 2005. Phylogenetic analysis was performed and a phylogenetic tree was constructed based on the World Health Organization standard sequence window for rubella virus isolates. All Beijing rubella virus isolates belong to genotype 1E/cluster1 and were clustered interspersed with viruses from other provinces in China. The effective number of infections indicated by a Bayesian skyline plot remained constant from 2007 to 2011. The proportion of rubella cases among the floating population has increased significantly in Beijing since 2002, and the disease burden gradually shifted to the older age group (15- to 39-year olds), which has become a major group with rubella infection since 2006. Genotype 1E rubella virus continuously caused a rubella epidemic in Beijing in 2007-2011 and was the predominant virus, and all Beijing genotype 1E viruses belong to cluster 1, which is also widely circulated throughout the country.

Contrasting responses to a climate regime change by sympatric, ice-dependent predators.

PubMed

Younger, Jane L; van den Hoff, John; Wienecke, Barbara; Hindell, Mark; Miller, Karen J

2016-03-15

Models that predict changes in the abundance and distribution of fauna under future climate change scenarios often assume that ecological niche and habitat availability are the major determinants of species' responses to climate change. However, individual species may have very different capacities to adapt to environmental change, as determined by intrinsic factors such as their dispersal ability, genetic diversity, generation time and rate of evolution. These intrinsic factors are usually excluded from forecasts of species' abundance and distribution changes. We aimed to determine the importance of these factors by comparing the impact of the most recent climate regime change, the late Pleistocene glacial-interglacial transition, on two sympatric, ice-dependent meso-predators, the emperor penguin (Aptenodytes forsteri) and Weddell seal (Leptonychotes weddellii). We reconstructed the population trend of emperor penguins and Weddell seals in East Antarctica over the past 75,000 years using mitochondrial DNA sequences and an extended Bayesian skyline plot method. We also assessed patterns of contemporary population structure and genetic diversity. Despite their overlapping distributions and shared dependence on sea ice, our genetic data revealed very different responses to climate warming between these species. The emperor penguin population grew rapidly following the glacial-interglacial transition, but the size of the Weddell seal population did not change. The expansion of emperor penguin numbers during the warm Holocene may have been facilitated by their higher dispersal ability and gene flow among colonies, and fine-scale differences in preferred foraging locations. The vastly different climate change responses of two sympatric ice-dependent predators suggests that differing adaptive capacities and/or fine-scale niche differences can play a major role in species' climate change responses, and that adaptive capacity should be considered alongside niche and distribution in future species forecasts.

Phylogeographic patterns of Lygus pratensis (Hemiptera: Miridae): Evidence for weak genetic structure and recent expansion in northwest China.

PubMed

Zhang, Li-Juan; Cai, Wan-Zhi; Luo, Jun-Yu; Zhang, Shuai; Wang, Chun-Yi; Lv, Li-Min; Zhu, Xiang-Zhen; Wang, Li; Cui, Jin-Jie

2017-01-01

Lygus pratensis (L.) is an important cotton pest in China, especially in the northwest region. Nymphs and adults cause serious quality and yield losses. However, the genetic structure and geographic distribution of L. pratensis is not well known. We analyzed genetic diversity, geographical structure, gene flow, and population dynamics of L. pratensis in northwest China using mitochondrial and nuclear sequence datasets to study phylogeographical patterns and demographic history. L. pratensis (n = 286) were collected at sites across an area spanning 2,180,000 km2, including the Xinjiang and Gansu-Ningxia regions. Populations in the two regions could be distinguished based on mitochondrial criteria but the overall genetic structure was weak. The nuclear dataset revealed a lack of diagnostic genetic structure across sample areas. Phylogenetic analysis indicated a lack of population level monophyly that may have been caused by incomplete lineage sorting. The Mantel test showed a significant correlation between genetic and geographic distances among the populations based on the mtDNA data. However the nuclear dataset did not show significant correlation. A high level of gene flow among populations was indicated by migration analysis; human activities may have also facilitated insect movement. The availability of irrigation water and ample cotton hosts makes the Xinjiang region well suited for L. pratensis reproduction. Bayesian skyline plot analysis, star-shaped network, and neutrality tests all indicated that L. pratensis has experienced recent population expansion. Climatic changes and extensive areas occupied by host plants have led to population expansion of L. pratensis. In conclusion, the present distribution and phylogeographic pattern of L. pratensis was influenced by climate, human activities, and availability of plant hosts.

Demographic History of Indigenous Populations in Mesoamerica Based on mtDNA Sequence Data

PubMed Central

González-Martín, Antonio; Gorostiza, Amaya; Regalado-Liu, Lucía; Arroyo-Peña, Sergio; Tirado, Sergio; Nuño-Arana, Ismael; Rubi-Castellanos, Rodrigo; Sandoval, Karla; Coble, Michael D.; Rangel-Villalobos, Héctor

2015-01-01

The genetic characterization of Native American groups provides insights into their history and demographic events. We sequenced the mitochondrial D-loop region (control region) of 520 samples from eight Mexican indigenous groups. In addition to an analysis of the genetic diversity, structure and genetic relationship between 28 Native American populations, we applied Bayesian skyline methodology for a deeper insight into the history of Mesoamerica. AMOVA tests applying cultural, linguistic and geographic criteria were performed. MDS plots showed a central cluster of Oaxaca and Maya populations, whereas those from the North and West were located on the periphery. Demographic reconstruction indicates higher values of the effective number of breeding females (Nef) in Central Mesoamerica during the Preclassic period, whereas this pattern moves toward the Classic period for groups in the North and West. Conversely, Nef minimum values are distributed either in the Lithic period (i.e. founder effects) or in recent periods (i.e. population declines). The Mesomerican regions showed differences in population fluctuation as indicated by the maximum Inter-Generational Rate (IGRmax): i) Center-South from the lithic period until the Preclassic; ii) West from the beginning of the Preclassic period until early Classic; iii) North characterized by a wide range of temporal variation from the Lithic to the Preclassic. Our findings are consistent with the genetic variations observed between central, South and Southeast Mesoamerica and the North-West region that are related to differences in genetic drift, structure, and temporal survival strategies (agriculture versus hunter-gathering, respectively). Interestingly, although the European contact had a major negative demographic impact, we detect a previous decline in Mesoamerica that had begun a few hundred years before. PMID:26292226

Population structure analysis of the neglected parasite Thelazia callipaeda revealed high genetic diversity in Eastern Asia isolates

PubMed Central

Zhang, Xi; Shi, Ya Li; Han, Lu Lu; Xiong, Chen; Yi, Shi Qi; Jiang, Peng; Wang, Zeng Xian; Shen, Ji Long; Wang, Zhong Quan

2018-01-01

Background Thelazia callipaeda is the causative agent of thelaziasis in canids, felids and humans. However, the population genetic structure regarding this parasite remains unclear. Methodology/principal findings In this study, we first explored the genetic variation of 32 T. callipaeda clinical isolates using the following multi-molecular markers: cox1, cytb, 12S rDNA, ITS1 and 18S rDNA. The isolates were collected from 13 patients from 11 geographical locations in China. Next, the population structure of T. callipaeda from Europe and other Asian countries was analyzed using the cox1 sequences collected during this study and from the GenBank database. In general, the Chinese clinical isolates of T. callipaeda expressed high genetic diversity. Based on the cox1 gene, a total of 21 haplotypes were identified. One only circulated in European countries (Hap1), while the other 20 haplotypes were dispersed in Korea, Japan and China. There were five nucleotide positions in the cox1 sequences that were confirmed as invariable among individuals from Europe and Asia, but the sequences were distinct between these two regions. Population differences between Europe and Asian countries were greater than those among China, Korea and Japan. The T. callipaeda populations from Europe and Asia should be divided into two separate sub-populations. These two groups started to diverge during the middle Pleistocene. Neutrality tests, mismatch distribution and Bayesian skyline plot (BSP) analysis all rejected possible population expansion of T. callipaeda. Conclusions The Asian population of T. callipaeda has a high level of genetic diversity, but further studies should be performed to explore the biology, ecology and epidemiology of T. callipaeda. PMID:29324738

Molecular data and ecological niche modelling reveal the Pleistocene history of a semi-aquatic bug (Microvelia douglasi douglasi) in East Asia.

PubMed

Ye, Zhen; Zhu, Gengping; Chen, Pingping; Zhang, Danli; Bu, Wenjun

2014-06-01

This study investigated the Pleistocene history of a semi-aquatic bug, Microvelia douglasi douglasi Scott, 1874 (Hemiptera: Veliidae) in East Asia. We used M. douglasi douglasi as a model species to explore the effects of historical climatic fluctuations on montane semi-aquatic invertebrate species. Two hypotheses were developed using ecological niche models (ENMs). First, we hypothesized that M. douglasi douglasi persisted in suitable habitats in southern Guizhou, southern Yunnan, Hainan, Taiwan and southeast China during the LIG. After that, the populations expanded (Hypothesis 1). As the spatial prediction in the LGM was significantly larger than in the LIG, we then hypothesized that the population expanded during the LIG to LGM transition (Hypothesis 2). We tested these hypotheses using mitochondrial data (COI+COII) and nuclear data (ITS1+5.8S+ITS2). Young lineages, relatively deep splits, lineage differentiation among mountain ranges in central, south and southwest China and high genetic diversities were observed in these suitable habitats. Evidence of mismatch distributions and neutrality tests indicate that a population expansion occurred in the late Pleistocene. The Bayesian skyline plot (BSP) revealed an unusual population expansion that likely happened during the cooling transition between LIG and LGM. The results of genetic data were mostly consistent with the spatial predictions from ENM, a finding that can profoundly improve phylogeographic research. The ecological requirements of M. douglasi douglasi, together with the geographical heterogeneity and climatic fluctuations of Pleistocene in East Asia, could have shaped this unusual demographic history. Our study contributes to our knowledge of semi-aquatic bug/invertebrate responses to Pleistocene climatic fluctuations in East Asia. © 2014 John Wiley & Sons Ltd.

Ancient DNA from Giant Panda (Ailuropoda melanoleuca) of South-Western China Reveals Genetic Diversity Loss during the Holocene

PubMed Central

Barlow, Axel; Cooper, Alan; Hou, Xin-Dong; Ji, Xue-Ping; Zhong, Bo-Jian; Liu, Hong; Flynn, Lawrence J.; Yuan, Jun-Xia; Wang, Li-Rui; Basler, Nikolas; Westbury, Michael V.; Hofreiter, Michael; Lai, Xu-Long

2018-01-01

The giant panda was widely distributed in China and south-eastern Asia during the middle to late Pleistocene, prior to its habitat becoming rapidly reduced in the Holocene. While conservation reserves have been established and population numbers of the giant panda have recently increased, the interpretation of its genetic diversity remains controversial. Previous analyses, surprisingly, have indicated relatively high levels of genetic diversity raising issues concerning the efficiency and usefulness of reintroducing individuals from captive populations. However, due to a lack of DNA data from fossil specimens, it is unknown whether genetic diversity was even higher prior to the most recent population decline. We amplified complete cytb and 12s rRNA, partial 16s rRNA and ND1, and control region sequences from the mitochondrial genomes of two Holocene panda specimens. We estimated genetic diversity and population demography by analyzing the ancient mitochondrial DNA sequences alongside those from modern giant pandas, as well as from other members of the bear family (Ursidae). Phylogenetic analyses show that one of the ancient haplotypes is sister to all sampled modern pandas and the second ancient individual is nested among the modern haplotypes, suggesting that genetic diversity may indeed have been higher earlier during the Holocene. Bayesian skyline plot analysis supports this view and indicates a slight decline in female effective population size starting around 6000 years B.P., followed by a recovery around 2000 years ago. Therefore, while the genetic diversity of the giant panda has been affected by recent habitat contraction, it still harbors substantial genetic diversity. Moreover, while its still low population numbers require continued conservation efforts, there seem to be no immediate threats from the perspective of genetic evolutionary potential. PMID:29642393

Ancient DNA from Giant Panda (Ailuropoda melanoleuca) of South-Western China Reveals Genetic Diversity Loss during the Holocene.

PubMed

Sheng, Gui-Lian; Barlow, Axel; Cooper, Alan; Hou, Xin-Dong; Ji, Xue-Ping; Jablonski, Nina G; Zhong, Bo-Jian; Liu, Hong; Flynn, Lawrence J; Yuan, Jun-Xia; Wang, Li-Rui; Basler, Nikolas; Westbury, Michael V; Hofreiter, Michael; Lai, Xu-Long

2018-04-06

The giant panda was widely distributed in China and south-eastern Asia during the middle to late Pleistocene, prior to its habitat becoming rapidly reduced in the Holocene. While conservation reserves have been established and population numbers of the giant panda have recently increased, the interpretation of its genetic diversity remains controversial. Previous analyses, surprisingly, have indicated relatively high levels of genetic diversity raising issues concerning the efficiency and usefulness of reintroducing individuals from captive populations. However, due to a lack of DNA data from fossil specimens, it is unknown whether genetic diversity was even higher prior to the most recent population decline. We amplified complete cyt b and 12s rRNA, partial 16s rRNA and ND1 , and control region sequences from the mitochondrial genomes of two Holocene panda specimens. We estimated genetic diversity and population demography by analyzing the ancient mitochondrial DNA sequences alongside those from modern giant pandas, as well as from other members of the bear family (Ursidae). Phylogenetic analyses show that one of the ancient haplotypes is sister to all sampled modern pandas and the second ancient individual is nested among the modern haplotypes, suggesting that genetic diversity may indeed have been higher earlier during the Holocene. Bayesian skyline plot analysis supports this view and indicates a slight decline in female effective population size starting around 6000 years B.P., followed by a recovery around 2000 years ago. Therefore, while the genetic diversity of the giant panda has been affected by recent habitat contraction, it still harbors substantial genetic diversity. Moreover, while its still low population numbers require continued conservation efforts, there seem to be no immediate threats from the perspective of genetic evolutionary potential.

Genetic Variation of the Endangered Neotropical Catfish Steindachneridion scriptum (Siluriformes: Pimelodidae)

PubMed Central

Paixão, Rômulo V.; Ribolli, Josiane; Zaniboni-Filho, Evoy

2018-01-01

Steindachneridion scriptum is an important species as a resource for fisheries and aquaculture; it is currently threatened and has a reduced occurrence in South America. The damming of rivers, overfishing, and contamination of freshwater environments are the main impacts on the maintenance of this species. We accessed the genetic diversity and structure of S. scriptum using the DNA barcode and control region (D-loop) sequences of 43 individuals from the Upper Uruguay River Basin (UUR) and 10 sequences from the Upper Paraná River Basin (UPR), which were obtained from GenBank. S. scriptum from the UUR and the UPR were assigned in two distinct molecular operational taxonomic units (MOTUs) with higher inter-specific K2P distance than the optimum threshold (OT = 0.0079). The COI Intra-MOTU distances of S. scriptum specimens from the UUR ranged from 0.0000 to 0.0100. The control region indicated a high number of haplotypes and low nucleotide diversity, compatible with a new population in recent expansion process. Genetic structure was observed, with high differentiation between UUR and UPR basins, identified by BAPS, haplotype network, AMOVA (FST = 0.78, p < 0.05) and Mantel test. S. scriptum from the UUR showed a slight differentiation (FST = 0.068, p < 0.05), but not isolation-by-distance. Negative values of Tajima’s D and Fu’s Fs suggest recent demographic oscillations. The Bayesian skyline plot analysis indicated possible population expansion from beginning 2,500 years ago and a recent reduction in the population size. Low nucleotide diversity, spatial population structure, and the reduction of effective population size should be considered for the planning of strategies aimed at the conservation and rehabilitation of this important fisheries resource. PMID:29520295

Phylogenetic and nucleotide sequence analysis of influenza A (H1N1) HA and NA genes of strains isolated from Saudi Arabia.

PubMed

Al-Qahtani, Ahmed Ali; Mubin, Muhammad; Dela Cruz, Damian M; Althawadi, Sahar Isa; Ul Rehman, Muhammad Shah Nawaz; Bohol, Marie Fe F; Al-Ahdal, Mohammed N

2017-01-30

In early 2009, a novel influenza A (H1N1) virus appeared in Mexico and rapidly disseminated worldwide. Little is known about the phylogeny and evolutionary dynamics of the H1N1 strain found in Saudi Arabia. Nucleotide sequencing and bioinformatics analyses were used to study molecular variation between the virus isolates. In this report, 72 hemagglutinin (HA) and 45 neuraminidase (NA) H1N1 virus gene sequences, isolated in 2009 from various regions of Saudi Arabia, were analyzed. Genetic characterization indicated that viruses from two different clades, 6 and 7, were circulating in the region, with clade 7, the most widely circulating H1N1 clade globally in 2009, being predominant. Sequence analysis of the HA and NA genes revealed a high degree of sequence identity with the corresponding genes from viruses circulating in the South East Asia region and with the A/California/7/2009 strain. New mutations in the HA gene of pandemic H1N1 (pH1N1) viruses, that could alter viral fitness, were identified. Relaxed-clock and Bayesian Skyline Plot analyses, based on the isolates used in this study and closely related globally representative strains, indicated marginally higher substitution rates than the type strain (5.14×10-3 and 4.18×10-3 substitutions/nucleotide/year in the HA and NA genes, respectively). The Saudi isolates were antigenically homogeneous and closely related to the prototype vaccine strain A/California/7/2009. The antigenic site of the HA gene had acquired novel mutations in some isolates, making continued monitoring of these viruses vital for the identification of potentially highly virulent and drug resistant variants.

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

Postglacial range shift and demographic expansion of the marine intertidal snail Batillaria attramentaria

PubMed Central

Ho, Phuong-Thao; Kwan, Ye-Seul; Kim, Boa; Won, Yong-Jin

2015-01-01

To address the impacts of past climate changes, particularly since the last glacial period, on the history of the distribution and demography of marine species, we investigated the evolutionary and demographic responses of the intertidal batillariid gastropod, Batillaria attramentaria, to these changes, using the snail as a model species in the northwest Pacific. We applied phylogeographic and divergence population genetic approaches to mitochondrial COI sequences from B. attramentaria. To cover much of its distributional range, 197 individuals collected throughout Korea and 507 publically available sequences (mostly from Japan) were used. Finally, a Bayesian skyline plot (BSP) method was applied to reconstruct the demographic history of this species. We found four differentiated geographic groups around Korea, confirming the presence of two distinct, geographically subdivided haplogroups on the Japanese coastlines along the bifurcated routes of the warm Tsushima and Kuroshio Currents. These two haplogroups were estimated to have begun to split approximately 400,000 years ago. Population divergence analysis supported the hypothesis that the Yellow Sea was populated by a northward range expansion of a small fraction of founders that split from a southern ancestral population since the last glacial maximum (LGM: 26,000–19,000 years ago), when the southern area became re-submerged. BSP analyses on six geographically and genetically defined groups in Korea and Japan consistently demonstrated that each group has exponentially increased approximately since the LGM. This study resolved the phylogeography of B. attramentaria as a series of events connected over space and time; while paleoceanographic conditions determining the connectivity of neighboring seas in East Asia are responsible for the vicariance of this species, the postglacial sea-level rise and warming temperatures have played a crucial role in rapid range shifts and broad demographic expansions of its populations. PMID:25691968

Genetic Structure and Demographic History Reveal Migration of the Diamondback Moth Plutella xylostella (Lepidoptera: Plutellidae) from the Southern to Northern Regions of China

PubMed Central

Wei, Shu-Jun; Shi, Bao-Cai; Gong, Ya-Jun; Jin, Gui-Hua; Chen, Xue-Xin; Meng, Xiang-Feng

2013-01-01

The diamondback moth Plutella xylostella (Linnaeus) (Lepidoptera: Plutellidae) is one of the most destructive insect pests of cruciferous plants worldwide. Biological, ecological and genetic studies have indicated that this moth is migratory in many regions around the world. Although outbreaks of this pest occur annually in China and cause heavy damage, little is known concerning its migration. To better understand its migration pattern, we investigated the population genetic structure and demographic history of the diamondback moth by analyzing 27 geographical populations across China using four mitochondrial genes and nine microsatellite loci. The results showed that high haplotype diversity and low nucleotide diversity occurred in the diamondback moth populations, a finding that is typical for migratory species. No genetic differentiation among all populations and no correlation between genetic and geographical distance were found. However, pairwise analysis of the mitochondrial genes has indicated that populations from the southern region were more differentiated than those from the northern region. Gene flow analysis revealed that the effective number of migrants per generation into populations of the northern region is very high, whereas that into populations of the southern region is quite low. Neutrality testing, mismatch distribution and Bayesian Skyline Plot analyses based on mitochondrial genes all revealed that deviation from Hardy-Weinberg equilibrium and sudden expansion of the effective population size were present in populations from the northern region but not in those from the southern region. In conclusion, all our analyses strongly demonstrated that the diamondback moth migrates within China from the southern to northern regions with rare effective migration in the reverse direction. Our research provides a successful example of using population genetic approaches to resolve the seasonal migration of insects. PMID:23565158

Analysis of terrain map matching using multisensing techniques for applications to autonomous vehicle navigation

NASA Technical Reports Server (NTRS)

Page, Lance; Shen, C. N.

1991-01-01

This paper describes skyline-based terrain matching, a new method for locating the vantage point of laser range-finding measurements on a global map previously prepared by satellite or aerial mapping. Skylines can be extracted from the range-finding measurements and modelled from the global map, and are represented in parametric, cylindrical form with azimuth angle as the independent variable. The three translational parameters of the vantage point are determined with a three-dimensional matching of these two sets of skylines.

3. ENVIRONMENT, FROM NORTH, SHOWING RICHMOND SKYLINE, BRIDGE DECK AND ...

Library of Congress Historic Buildings Survey, Historic Engineering Record, Historic Landscapes Survey

3. ENVIRONMENT, FROM NORTH, SHOWING RICHMOND SKYLINE, BRIDGE DECK AND ROADWAY, AND NORTH APPROACH - Fifth Street Viaduct, Spanning Bacon's Quarter Branch Valley on Fifth Street, Richmond, Independent City, VA

Tsugaru Iwaki Skyline, Japan

NASA Image and Video Library

2018-05-03

The Tsugaru Iwaki Skyline is a toll road in northern Japan, which partially ascends Mount Iwaki stratovolcano, and is notable for its steep gradient and 69 hairpin turns. The road ascends 806 meters over an average gradient of 8.66%, with some sections going up to 10%. The Tsugaru Iwaki Skyline has been considered one of the most dangerous mountain roads in the world. (Wikipedia) The image was acquired May 26, 2015, and is located at 40.6 degrees north, 140.3 degrees east. https://photojournal.jpl.nasa.gov/catalog/PIA22385

Limiting Index Sort: A New Non-Dominated Sorting Algorithm and its Comparison to the State-of-the-Art

DTIC Science & Technology

2010-05-01

Skyline Algorithms 2.2.1 Block-Nested Loops A simple way to find the skyline is to use the block-nested loops ( BNL ) algorithm [3], which is the algorithm...by an NDS member are discarded. After every individual has been compared with the NDS, the NDS is the dataset’s skyline. In the best case for BNL ...SFS) algorithm [4] is a variation on BNL that first introduces the idea of initially ordering the individuals by a monotonically increasing scoring

77 FR 15118 - Buy American Exceptions Under the American Recovery and Reinvestment Act of 2009

Federal Register 2010, 2011, 2012, 2013, 2014

2012-03-14

... heat pumps for the Skyline Crest Sustainability Upgrade project. FOR FURTHER INFORMATION CONTACT... Skyline Crest Sustainability Upgrade project. The exception was granted by HUD on the basis that the...

Enhanced HIV-1 surveillance using molecular epidemiology to study and monitor HIV-1 outbreaks among intravenous drug users (IDUs) in Athens and Bucharest.

PubMed

Paraskevis, Dimitrios; Paraschiv, Simona; Sypsa, Vana; Nikolopoulos, Georgios; Tsiara, Chryssa; Magiorkinis, Gkikas; Psichogiou, Mina; Flampouris, Andreas; Mardarescu, Mariana; Niculescu, Iulia; Batan, Ionelia; Malliori, Meni; Otelea, Dan; Hatzakis, Angelos

2015-10-01

A significant increase in HIV-1 diagnoses was reported among Injecting Drug Users (IDUs) in the Athens (17-fold) and Bucharest (9-fold) metropolitan areas starting 2011. Molecular analyses were conducted on HIV-1 sequences from IDUs comprising 51% and 20% of the diagnosed cases among IDUs during 2011-2013 for Greece and Romania, respectively. Phylodynamic analyses were performed using the newly developed birth-death serial skyline model which allows estimating of important epidemiological parameters, as implemented in BEAST programme. Most infections (>90%) occurred within four and three IDU local transmission networks in Athens and Bucharest, respectively. For all Romanian clusters, the viral strains originated from local circulating strains, whereas in Athens, the local strains seeded only two of the four sub-outbreaks. Birth-death skyline plots suggest a more explosive nature for sub-outbreaks in Bucharest than in Athens. In Athens, two sub-outbreaks had been controlled (Re<1.0) by 2013 and two appeared to be endemic (Re∼1). In Bucharest one outbreak continued to expand (Re>1.0) and two had been controlled (Re<1.0). The lead times were shorter for the outbreak in Athens than in Bucharest. Enhanced molecular surveillance proved useful to gain information about the origin, causal pathways, dispersal patterns and transmission dynamics of the outbreaks that can be useful in a public health setting. Copyright © 2015 Elsevier B.V. All rights reserved.

ensembleBMA: An R Package for Probabilistic Forecasting using Ensembles and Bayesian Model Averaging

DTIC Science & Technology

2007-08-15

library is used to allow addition of the legend and map outline to the plot. > bluescale <- function(n) hsv (4/6, s = seq(from = 1 /8, to = 1 , length = n...v = 1 ) > plotBMAforecast( probFreeze290104, lon=srftGridData$lon, lat =srftGridData$ lat , type="image", col=bluescale(100)) > title("Probability of...probPrecip130103) # used to determine zlim in plots [ 1 ] 0.02832709 0.99534860 > plotBMAforecast( probPrecip130103[,Ŕ"], lon=prcpGridData$lon, lat

Block 2. Photograph represents general view taken from the north/west ...

Library of Congress Historic Buildings Survey, Historic Engineering Record, Historic Landscapes Survey

Block 2. Photograph represents general view taken from the north/west region of the May D & F Tower. Photograph shows the main public gathering space for Skyline Park and depicts a light feature and an “Information” sign - Skyline Park, 1500-1800 Arapaho Street, Denver, Denver County, CO

Toyota/Skyline Technical Education Network. Cooperative Demonstration Program. Final Performance Report.

ERIC Educational Resources Information Center

Skyline Coll., San Bruno, CA.

A joint project was conducted between Toyota Motor Sales and Skyline College (in the San Francisco, California, area) to create an automotive technician training program that would serve the needs of working adults. During the project, a model high technology curriculum suitable for adults was developed, the quality of instruction available for…

A Skyline Plugin for Pathway-Centric Data Browsing

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

Degan, Michael G.; Ryadinskiy, Lillian; Fujimoto, Grant M.

For targeted proteomics to be broadly adopted in biological laboratories as a routine experimental protocol, wet-bench biologists must be able to approach SRM assay design in the same way they approach biological experimental design. Most often, biological hypotheses are envisioned in a set of protein interactions, networks and pathways. We present a plugin for the popular Skyline tool that presents public mass spectrometry data in a pathway-centric view to assist users in browsing available data and determining how to design quantitative experiments. Selected proteins and their underlying mass spectra are imported to Skyline for further assay design (transition selection). Themore » same plugin can be used for hypothesis-drive DIA data analysis, again utilizing the pathway view to help narrow down the set of proteins which will be investigated. The plugin is backed by the PNNL Biodiversity Library, a corpus of 3 million peptides from >100 organisms, and the draft human proteome. Users can upload personal data to the plugin to use the pathway navigation prior to importing their own data into Skyline.« less

A Skyline Plugin for Pathway-Centric Data Browsing

NASA Astrophysics Data System (ADS)

Degan, Michael G.; Ryadinskiy, Lillian; Fujimoto, Grant M.; Wilkins, Christopher S.; Lichti, Cheryl F.; Payne, Samuel H.

2016-11-01

For targeted proteomics to be broadly adopted in biological laboratories as a routine experimental protocol, wet-bench biologists must be able to approach selected reaction monitoring (SRM) and parallel reaction monitoring (PRM) assay design in the same way they approach biological experimental design. Most often, biological hypotheses are envisioned in a set of protein interactions, networks, and pathways. We present a plugin for the popular Skyline tool that presents public mass spectrometry data in a pathway-centric view to assist users in browsing available data and determining how to design quantitative experiments. Selected proteins and their underlying mass spectra are imported to Skyline for further assay design (transition selection). The same plugin can be used for hypothesis-driven data-independent acquisition (DIA) data analysis, again utilizing the pathway view to help narrow down the set of proteins that will be investigated. The plugin is backed by the Pacific Northwest National Laboratory (PNNL) Biodiversity Library, a corpus of 3 million peptides from >100 organisms, and the draft human proteome. Users can upload personal data to the plugin to use the pathway navigation prior to importing their own data into Skyline.

Spectral Skyline Separation: Extended Landmark Databases and Panoramic Imaging

PubMed Central

Differt, Dario; Möller, Ralf

2016-01-01

Evidence from behavioral experiments suggests that insects use the skyline as a cue for visual navigation. However, changes of lighting conditions, over hours, days or possibly seasons, significantly affect the appearance of the sky and ground objects. One possible solution to this problem is to extract the “skyline” by an illumination-invariant classification of the environment into two classes, ground objects and sky. In a previous study (Insect models of illumination-invariant skyline extraction from UV (ultraviolet) and green channels), we examined the idea of using two different color channels available for many insects (UV and green) to perform this segmentation. We found out that for suburban scenes in temperate zones, where the skyline is dominated by trees and artificial objects like houses, a “local” UV segmentation with adaptive thresholds applied to individual images leads to the most reliable classification. Furthermore, a “global” segmentation with fixed thresholds (trained on an image dataset recorded over several days) using UV-only information is only slightly worse compared to using both the UV and green channel. In this study, we address three issues: First, to enhance the limited range of environments covered by the dataset collected in the previous study, we gathered additional data samples of skylines consisting of minerals (stones, sand, earth) as ground objects. We could show that also for mineral-rich environments, UV-only segmentation achieves a quality comparable to multi-spectral (UV and green) segmentation. Second, we collected a wide variety of ground objects to examine their spectral characteristics under different lighting conditions. On the one hand, we found that the special case of diffusely-illuminated minerals increases the difficulty to reliably separate ground objects from the sky. On the other hand, the spectral characteristics of this collection of ground objects covers well with the data collected in the skyline databases, increasing, due to the increased variety of ground objects, the validity of our findings for novel environments. Third, we collected omnidirectional images, as often used for visual navigation tasks, of skylines using an UV-reflective hyperbolic mirror. We could show that “local” separation techniques can be adapted to the use of panoramic images by splitting the image into segments and finding individual thresholds for each segment. Contrarily, this is not possible for ‘global’ separation techniques. PMID:27690053

Harvesting costs and environmental impacts associated with skyline yarding shelterwood harvests and thinning in Appalachian hardwoods

Treesearch

J. E. Baumgras; C. B. LeDoux; J. R. Sherar

1993-01-01

To evaluate the potential for moderating the visual impact and soil disturbance associated with timber harvesting on steep-slope hardwood sites, thinning and shelterwood harvests were conducted with a skyline yarding system. Operations were monitored to document harvesting production, residual stand damage, soil disturbance, and visual quality. Yarding costs for...

Skyline Gathers K-12 Together Under One Roof.

ERIC Educational Resources Information Center

American School Board Journal, 1968

1968-01-01

Skyline School is a flexible and economical elementary and high school design for 400 pupils. The library, a large resource center serving all ages, and the administration offices are accented by landscaped courts. There are two instructional material centers per grade grouping of K-6 and 7-12. Grades 1-6 surround the kindergarten, which has…

Hardwood silviculture and skyline yarding on steep slopes: economic and environmental impacts

Treesearch

John E. Baumgras; Chris B. LeDoux

1995-01-01

Ameliorating the visual and environmental impact associated with harvesting hardwoods on steep slopes will require the efficient use of skyline yarding along with silvicultural alternatives to clearcutting. In evaluating the effects of these alternatives on harvesting revenue, results of field studies and computer simulations were used to estimate costs and revenue for...

Molecular epidemiology and phylogenetic analysis of Hepatitis B virus in a group of migrants in Italy.

PubMed

Villano, Umbertina; Lo Presti, Alessandra; Equestre, Michele; Cella, Eleonora; Pisani, Giulio; Giovanetti, Marta; Bruni, Roberto; Tritarelli, Elena; Amicosante, Massimo; Grifoni, Alba; Scarcella, Carmelo; El-Hamad, Issa; Pezzoli, Maria Chiara; Angeletti, Silvia; Silvia, Angeletti; Ciccaglione, Anna Rita; Ciccozzi, Massimo

2015-07-25

Hepatitis B virus infection (HBV) is widespread and it is considered a major health problem worldwide. The global distribution of HBV varies significantly between countries and between regions of the world. Among the many factors contributing to the changing epidemiology of viral hepatitis, the movement of people within and between countries is a potentially important one. In Italy, the number of migrant individuals has been increasing during the past 25 years. HBV genotype D has been found throughout the world, although its highest prevalence is in the Mediterranean area, the Middle East and southern Asia. We describe the molecular epidemiology of HBV in a chronically infected population of migrants (living in Italy), by using the phylogenetic analysis. HBV-DNA was amplified and sequenced from 43 HBV chronically infected patients. Phylogenetic and evolutionary analysis were performed using both maximum Likelihood and Bayesian methods. Of the 43 HBV S gene isolates from migrants, 25 (58.1 %) were classified as D genotype. Maximum Likelihood analysis showed an intermixing between Moldavian and foreigners sequences mostly respect to Italian ones. Italian sequences clustered mostly together in a main clade separately from all others. The estimation of the time of the tree's root gave a mean value of 17 years ago, suggesting the origin of the tree back to 1992 year. The skyline plot showed that the number of infections softly increased until the early 2005s, after which reached a plateau. Comparing phylogenetic data to the migrants date of arrival in Italy, it should be possible that migrants arrived in Italy yet infected from their country of origin. In conclusion, this is the first paper where phylogenetic analysis and genetic evolution has been used to characterize HBV sub genotypes D1 circulation in a selected and homogenous group of migrants coming from a restricted area of Balkans and to approximately define the period of infection besides the migration date.

A New Phylogeographic Pattern of Endemic Bufo bankorensis in Taiwan Island Is Attributed to the Genetic Variation of Populations

PubMed Central

Yu, Teng-Lang; Lin, Hung-Du; Weng, Ching-Feng

2014-01-01

Aim To comprehend the phylogeographic patterns of genetic variation in anurans at Taiwan Island, this study attempted to examine (1) the existence of various geological barriers (Central Mountain Ranges, CMRs); and (2) the genetic variation of Bufo bankorensis using mtDNA sequences among populations located in different regions of Taiwan, characterized by different climates and existing under extreme conditions when compared available sequences of related species B. gargarizans of mainland China. Methodology/Principal Findings Phylogenetic analyses of the dataset with mitochondrial DNA (mtDNA) D-loop gene (348 bp) recovered a close relationship between B. bankorensis and B. gargarizans, identified three distinct lineages. Furthermore, the network of mtDNA D-loop gene (564 bp) amplified (279 individuals, 27 localities) from Taiwan Island indicated three divergent clades within B. bankorensis (Clade W, E and S), corresponding to the geography, thereby verifying the importance of the CMRs and Kaoping River drainage as major biogeographic barriers. Mismatch distribution analysis, neutrality tests and Bayesian skyline plots revealed that a significant population expansion occurred for the total population and Clade W, with horizons dated to approximately 0.08 and 0.07 Mya, respectively. These results suggest that the population expansion of Taiwan Island species B. bankorensis might have resulted from the release of available habitat in post-glacial periods, the genetic variation on mtDNA showing habitat selection, subsequent population dispersal, and co-distribution among clades. Conclusions The multiple origins (different clades) of B. bankorensis mtDNA sequences were first evident in this study. The divergent genetic clades found within B. bankorensis could be independent colonization by previously diverged lineages; inferring B. bankorensis originated from B. gargarizans of mainland China, then dispersal followed by isolation within Taiwan Island. Highly divergent clades between W and E of B. bankorensis, implies that the CMRs serve as a genetic barrier and separated the whole island into the western and eastern phylogroups. PMID:24853679

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

The Near East as a cradle of biodiversity: A phylogeography of banded newts (genus Ommatotriton) reveals extensive inter- and intraspecific genetic differentiation.

PubMed

van Riemsdijk, Isolde; Arntzen, Jan W; Bogaerts, Sergé; Franzen, Michael; Litvinchuk, Spartak N; Olgun, Kurtuluş; Wielstra, Ben

2017-09-01

The banded newt (genus Ommatotriton) is widely distributed in the Near East (Anatolia, Caucasus and the Levant) - an understudied region from the perspective of phylogeography. The genus is polytypic, but the number of species included and the phylogenetic relationships between them are not settled. We sequenced two mitochondrial and two nuclear DNA markers throughout the range of Ommatotriton. For mtDNA we constructed phylogenetic trees, estimated divergence times using fossil calibration, and investigated changes in effective population size with Bayesian skyline plots and mismatch analyses. For nuDNA we constructed phylogenetic trees and haplotype networks. Species trees were constructed for all markers and nuDNA only. Species distribution models were projected on current and Last Glacial Maximum climate layers. We confirm the presence of three Ommatotriton species: O. nesterovi, O. ophryticus and O. vittatus. These species are genetically distinct and their most recent common ancestor was dated at ∼25Ma (Oligocene). No evidence of recent gene flow between species was found. The species show deep intraspecific genetic divergence, represented by geographically structured clades, with crown nodes of species dated ∼8-13Ma (Miocene to Early Quaternary); evidence of long-term in situ evolution and survival in multiple glacial refugia. While a species tree based on nuDNA suggested a sister species relationship between O. vittatus and O. ophryticus, when mtDNA was included, phylogenetic relationships were unresolved, and we refrain from accepting a particular phylogenetic hypothesis at this stage. While species distribution models suggest reduced and fragmented ranges during the Last Glacial Maximum, we found no evidence for strong population bottlenecks. We discuss our results in the light of other phylogeographic studies from the Near East. Our study underlines the important role of the Near East in generating and sustaining biodiversity. Copyright © 2017 Elsevier Inc. All rights reserved.

Rubella epidemics and genotypic distribution of the rubella virus in Shandong Province, China, in 1999-2010.

PubMed

Wang, Changyin; Zhu, Zhen; Xu, Qing; Xu, Aiqiang; Fang, Xueqiang; Song, Lizhi; Li, Weixiu; Xiong, Ping; Xu, Wenbo

2012-01-01

The rubella vaccine was introduced into the immunization program in 1995 in the Shandong province, China. A series of different rubella vaccination strategies were implemented at different stages of measles control in Shandong province. The average reported incidence rate of rubella cases remained at a low level in Shandong province after 1999. However, rubella epidemics occurred repeatedly in 2001/2002, 2006, and 2008/2009. The age of the onset of rubella cases gradually increased during 1999-2010, which showed that most cases were found among the 10 years old in 1999 and among the 17 years old in 2010. Phylogenetic analysis was performed and a phylogenetic tree was constructed based on the World Health Organization standard sequence window for rubella virus isolates. All rubella viruses isolated in Shandong province were divided into 4 genotypes: 1E, 1F, 2A, and 2B. Genotype 1E viruses accounted for the majority (79%) of all these viruses. The similarity of nucleotide and amino acid sequences among genotype 1E viruses was 98.2-100% and 99.1-100%, respectively. All Shandong genotype 1E strains, differed from international genotype 1E strains, belonged to cluster 1 and interdigitated with the viruses from other provinces in mainland China. The effective number of infections indicated by a bayesian skyline plot remained constant from 2001 to 2009. The gradual shift of disease burden to an older age group occurred after a rubella-containing vaccine was introduced into the childhood immunization schedule in 1995 in Shandong province. Four genotypes, including 1E, 1F, 2A, and 2B, were found in Shandong province during 2000-2009. Genotype 1E, rather than genotype 1F, became the predominant genotype circulating in Shandong province from 2001. All Shandong genotype 1E viruses belong to the genotype 1E/cluster 1; they have constantly circulated, and co-evolved and co-circulated, with those from other provinces.

Evaluation of a Phylogenetic Marker Based on Genomic Segment B of Infectious Bursal Disease Virus: Facilitating a Feasible Incorporation of this Segment to the Molecular Epidemiology Studies for this Viral Agent.

PubMed

Alfonso-Morales, Abdulahi; Rios, Liliam; Martínez-Pérez, Orlando; Dolz, Roser; Valle, Rosa; Perera, Carmen L; Bertran, Kateri; Frías, Maria T; Ganges, Llilianne; Díaz de Arce, Heidy; Majó, Natàlia; Núñez, José I; Pérez, Lester J

2015-01-01

Infectious bursal disease (IBD) is a highly contagious and acute viral disease, which has caused high mortality rates in birds and considerable economic losses in different parts of the world for more than two decades and it still represents a considerable threat to poultry. The current study was designed to rigorously measure the reliability of a phylogenetic marker included into segment B. This marker can facilitate molecular epidemiology studies, incorporating this segment of the viral genome, to better explain the links between emergence, spreading and maintenance of the very virulent IBD virus (vvIBDV) strains worldwide. Sequences of the segment B gene from IBDV strains isolated from diverse geographic locations were obtained from the GenBank Database; Cuban sequences were obtained in the current work. A phylogenetic marker named B-marker was assessed by different phylogenetic principles such as saturation of substitution, phylogenetic noise and high consistency. This last parameter is based on the ability of B-marker to reconstruct the same topology as the complete segment B of the viral genome. From the results obtained from B-marker, demographic history for both main lineages of IBDV regarding segment B was performed by Bayesian skyline plot analysis. Phylogenetic analysis for both segments of IBDV genome was also performed, revealing the presence of a natural reassortant strain with segment A from vvIBDV strains and segment B from non-vvIBDV strains within Cuban IBDV population. This study contributes to a better understanding of the emergence of vvIBDV strains, describing molecular epidemiology of IBDV using the state-of-the-art methodology concerning phylogenetic reconstruction. This study also revealed the presence of a novel natural reassorted strain as possible manifest of change in the genetic structure and stability of the vvIBDV strains. Therefore, it highlights the need to obtain information about both genome segments of IBDV for molecular epidemiology studies.

Whole mitochondrial genome sequencing of domestic horses reveals incorporation of extensive wild horse diversity during domestication

PubMed Central

2011-01-01

Background DNA target enrichment by micro-array capture combined with high throughput sequencing technologies provides the possibility to obtain large amounts of sequence data (e.g. whole mitochondrial DNA genomes) from multiple individuals at relatively low costs. Previously, whole mitochondrial genome data for domestic horses (Equus caballus) were limited to only a few specimens and only short parts of the mtDNA genome (especially the hypervariable region) were investigated for larger sample sets. Results In this study we investigated whole mitochondrial genomes of 59 domestic horses from 44 breeds and a single Przewalski horse (Equus przewalski) using a recently described multiplex micro-array capture approach. We found 473 variable positions within the domestic horses, 292 of which are parsimony-informative, providing a well resolved phylogenetic tree. Our divergence time estimate suggests that the mitochondrial genomes of modern horse breeds shared a common ancestor around 93,000 years ago and no later than 38,000 years ago. A Bayesian skyline plot (BSP) reveals a significant population expansion beginning 6,000-8,000 years ago with an ongoing exponential growth until the present, similar to other domestic animal species. Our data further suggest that a large sample of wild horse diversity was incorporated into the domestic population; specifically, at least 46 of the mtDNA lineages observed in domestic horses (73%) already existed before the beginning of domestication about 5,000 years ago. Conclusions Our study provides a window into the maternal origins of extant domestic horses and confirms that modern domestic breeds present a wide sample of the mtDNA diversity found in ancestral, now extinct, wild horse populations. The data obtained allow us to detect a population expansion event coinciding with the beginning of domestication and to estimate both the minimum number of female horses incorporated into the domestic gene pool and the time depth of the domestic horse mtDNA gene pool. PMID:22082251

The spread of hepatitis C virus genotype 1a in North America: a retrospective phylogenetic study.

PubMed

Joy, Jeffrey B; McCloskey, Rosemary M; Nguyen, Thuy; Liang, Richard H; Khudyakov, Yury; Olmstead, Andrea; Krajden, Mel; Ward, John W; Harrigan, P Richard; Montaner, Julio S G; Poon, Art F Y

2016-06-01

The timing of the initial spread of hepatitis C virus genotype 1a in North America is controversial. In particular, how and when hepatitis C virus reached extraordinary prevalence in specific demographic groups remains unclear. We quantified, using all available hepatitis C virus sequence data and phylodynamic methods, the timing of the spread of hepatitis C virus genotype 1a in North America. We screened 45 316 publicly available sequences of hepatitis C virus genotype 1a for location and genotype, and then did phylogenetic analyses of available North American sequences from five hepatitis C virus genes (E1, E2, NS2, NS4B, NS5B), with an emphasis on including as many sequences with early collection dates as possible. We inferred the historical population dynamics of this epidemic for all five gene regions using Bayesian skyline plots. Most of the spread of genotype 1a in North America occurred before 1965, and the hepatitis C virus epidemic has undergone relatively little expansion since then. The effective population size of the North American epidemic stabilised around 1960. These results were robust across all five gene regions analysed, although analyses of each gene separately show substantial variation in estimates of the timing of the early exponential growth, ranging roughly from 1940 for NS2, to 1965 for NS4B. The expansion of genotype 1a before 1965 suggests that nosocomial or iatrogenic factors rather than past sporadic behavioural risk (ie, experimentation with injection drug use, unsafe tattooing, high risk sex, travel to high endemic areas) were key contributors to the hepatitis C virus epidemic in North America. Our results might reduce stigmatisation around screening and diagnosis, potentially increasing rates of screening and treatment for hepatitis C virus. The Canadian Institutes of Health Research, Michael Smith Foundation for Health Research, and BC Centre for Excellence in HIV/AIDS. Copyright © 2016 Elsevier Ltd. All rights reserved.

Evolving in the highlands: the case of the Neotropical Lerma live-bearing Poeciliopsis infans (Woolman, 1894) (Cyprinodontiformes: Poeciliidae) in Central Mexico.

PubMed

Beltrán-López, Rosa Gabriela; Domínguez-Domínguez, Omar; Pérez-Rodríguez, Rodolfo; Piller, Kyle; Doadrio, Ignacio

2018-04-20

Volcanic and tectonic activities in conjunction with Quaternary climate are the main events that shaped the geographical distribution of genetic variation of many lineages. Poeciliopsis infans is the only poeciliid species that was able to colonize the temperate highlands of central Mexico. We inferred the phylogenetic relationships, biogeographic history, and historical demography in the widespread Neotropical species P. infans and correlated this with geological events and the Quaternary glacial-interglacial climate in the highlands of central Mexico, using the mitochondrial genes Cytochrome b and Cytochrome oxidase I and two nuclear loci, Rhodopsin and ribosomal protein S7. Populations of P. infans were recovered in two well-differentiated clades. The maximum genetic distances between the two clades were 3.3% for cytb, and 1.9% for coxI. The divergence of the two clades occurred ca. 2.83 Myr. Ancestral area reconstruction revealed a complex biogeographical history for P. infans. The Bayesian Skyline Plot showed a demographic decline, although more visible for clade A, and more recently showed a population expansion in the last 0.025 Myr. Finally, the habitat suitability modelling showed that during the LIG, clade B had more areas with high probabilities of presence in comparison to clade A, whereas for the LGM, clade A showed more areas with high probabilities of presence in comparisons to clade B. Poeciliopsis infans has had a complex evolutionary and biogeographic history, which, as in other co-distributed freshwater fishes, seems to be linked to the volcanic and tectonic activities during the Pliocene or early Pleistocene. Populations of P. infans distributed in lowlands showed a higher level of genetic diversity than populations distributed in highlands, which could be linked to more stable and higher temperatures in lowland areas. The fluctuations in population size through time are in agreement with the continuous fluctuations of the climate of central Mexico.

Data set for phylogenetic tree and RAMPAGE Ramachandran plot analysis of SODs in Gossypium raimondii and G. arboreum.

PubMed

Wang, Wei; Xia, Minxuan; Chen, Jie; Deng, Fenni; Yuan, Rui; Zhang, Xiaopei; Shen, Fafu

2016-12-01

The data presented in this paper is supporting the research article "Genome-Wide Analysis of Superoxide Dismutase Gene Family in Gossypium raimondii and G. arboreum" [1]. In this data article, we present phylogenetic tree showing dichotomy with two different clusters of SODs inferred by the Bayesian method of MrBayes (version 3.2.4), "Bayesian phylogenetic inference under mixed models" [2], Ramachandran plots of G. raimondii and G. arboreum SODs, the protein sequence used to generate 3D sructure of proteins and the template accession via SWISS-MODEL server, "SWISS-MODEL: modelling protein tertiary and quaternary structure using evolutionary information." [3] and motif sequences of SODs identified by InterProScan (version 4.8) with the Pfam database, "Pfam: the protein families database" [4].

Skyline Wide Educational Plan (SWEP) Product Evaluation Report: Educational Goals for the Future (1980's). SWEP Evaluation Report No. 2.

ERIC Educational Resources Information Center

Burns, Robert J.

The major purpose of this evaluation report is to scrutinize the Skyline Wide Educational Plan (SWEP) research methods and analytical schemes and to communicate the project's constituency priorities relative to the educational programs and processes of the future. A Delphi technique was used as the primary mechanism for gathering and scrutinizing…

Tree damage from skyline logging in a western larch/Douglas-fir stand

Treesearch

Robert E. Benson; Michael J. Gonsior

1981-01-01

Damage to shelterwood leave trees and to understory trees in shelterwood and clearcut logging units logged with skyline yarders was measured, and related to stand conditions, harvesting specifications, and yarding system-terrain interactions. About 23 percent of the marked leave trees in the shelterwood units were killed in logging, and about 10 percent had moderate to...

Secure Skyline Queries on Cloud Platform.

PubMed

Liu, Jinfei; Yang, Juncheng; Xiong, Li; Pei, Jian

2017-04-01

Outsourcing data and computation to cloud server provides a cost-effective way to support large scale data storage and query processing. However, due to security and privacy concerns, sensitive data (e.g., medical records) need to be protected from the cloud server and other unauthorized users. One approach is to outsource encrypted data to the cloud server and have the cloud server perform query processing on the encrypted data only. It remains a challenging task to support various queries over encrypted data in a secure and efficient way such that the cloud server does not gain any knowledge about the data, query, and query result. In this paper, we study the problem of secure skyline queries over encrypted data. The skyline query is particularly important for multi-criteria decision making but also presents significant challenges due to its complex computations. We propose a fully secure skyline query protocol on data encrypted using semantically-secure encryption. As a key subroutine, we present a new secure dominance protocol, which can be also used as a building block for other queries. Finally, we provide both serial and parallelized implementations and empirically study the protocols in terms of efficiency and scalability under different parameter settings, verifying the feasibility of our proposed solutions.

Camera Geolocation From Mountain Images

DTIC Science & Technology

2015-09-17

be reliably extracted from query images. However, in real-life scenarios the skyline in a query image may be blurred or invisible , due to occlusions...extracted from multiple mountain ridges is critical to reliably geolocating challenging real-world query images with blurred or invisible mountain skylines...Buddemeier, A. Bissacco, F. Brucher, T. Chua, H. Neven, and J. Yagnik, “Tour the world: building a web -scale landmark recognition engine,” in Proc. of

Secure Skyline Queries on Cloud Platform

PubMed Central

Liu, Jinfei; Yang, Juncheng; Xiong, Li; Pei, Jian

2017-01-01

Outsourcing data and computation to cloud server provides a cost-effective way to support large scale data storage and query processing. However, due to security and privacy concerns, sensitive data (e.g., medical records) need to be protected from the cloud server and other unauthorized users. One approach is to outsource encrypted data to the cloud server and have the cloud server perform query processing on the encrypted data only. It remains a challenging task to support various queries over encrypted data in a secure and efficient way such that the cloud server does not gain any knowledge about the data, query, and query result. In this paper, we study the problem of secure skyline queries over encrypted data. The skyline query is particularly important for multi-criteria decision making but also presents significant challenges due to its complex computations. We propose a fully secure skyline query protocol on data encrypted using semantically-secure encryption. As a key subroutine, we present a new secure dominance protocol, which can be also used as a building block for other queries. Finally, we provide both serial and parallelized implementations and empirically study the protocols in terms of efficiency and scalability under different parameter settings, verifying the feasibility of our proposed solutions. PMID:28883710

Modeling fatigue.

PubMed

Sumner, Walton; Xu, Jin Zhong

2002-01-01

The American Board of Family Practice is developing a patient simulation program to evaluate diagnostic and management skills. The simulator must give temporally and physiologically reasonable answers to symptom questions such as "Have you been tired?" A three-step process generates symptom histories. In the first step, the simulator determines points in time where it should calculate instantaneous symptom status. In the second step, a Bayesian network implementing a roughly physiologic model of the symptom generates a value on a severity scale at each sampling time. Positive, zero, and negative values represent increased, normal, and decreased status, as applicable. The simulator plots these values over time. In the third step, another Bayesian network inspects this plot and reports how the symptom changed over time. This mechanism handles major trends, multiple and concurrent symptom causes, and gradually effective treatments. Other temporal insights, such as observations about short-term symptom relief, require complimentary mechanisms.

Mountain Logging Symposium Proceedings Held in West Virginia on Jun 5-7, 1984

DTIC Science & Technology

1984-06-07

and board" analysis ( Lysons and Mann 1967) provided a method to make skyline payload determination feasible using topographic maps or field run... Lysons , Hilton H.; Mann, Charles N. Skyline tension and deflection handbook. Res. Pap. PNW-39. Portland, OR: U.S. Department of Agriculture, Forest...those described by Mifflin and Lysons (1978)and Miyata (1980). The estimated cost for the Clearwater Yarder and a four-man crew was $48.27 per

Skyline Wide Educational Plan (SWEP) Planning Project. Volume 2 -- Appendices. Combined Quarterly Report No. 4 (April 1 to June 30, 1974) and Final Report (July 1973 to August 1974).

ERIC Educational Resources Information Center

Dallas Independent School District, TX. Dept. of Research and Evaluation.

This volume consists of a number of appendixes containing data and analyses that were compiled to aid administrators of the Skyline Wide Educational Plan (SWEP) in their efforts to develop a comprehensive secondary school plan for the Dallas-Fort Worth metroplex in the 1970's. Much of the volume is devoted to various facility considerations…

Molecular insights into the historic demography of bowhead whales: understanding the evolutionary basis of contemporary management practices

PubMed Central

Phillips, C D; Hoffman, J I; George, J C; Suydam, R S; Huebinger, R M; Patton, J C; Bickham, J W

2013-01-01

Patterns of genetic variation observed within species reflect evolutionary histories that include signatures of past demography. Understanding the demographic component of species' history is fundamental to informed management because changes in effective population size affect response to environmental change and evolvability, the strength of genetic drift, and maintenance of genetic variability. Species experiencing anthropogenic population reductions provide valuable case studies for understanding the genetic response to demographic change because historic changes in the census size are often well documented. A classic example is the bowhead whale, Balaena mysticetus, which experienced dramatic population depletion due to commercial whaling in the late 19th and early 20th centuries. Consequently, we analyzed a large multi-marker dataset of bowhead whales using a variety of analytical methods, including extended Bayesian skyline analysis and approximate Bayesian computation, to characterize genetic signatures of both ancient and contemporary demographic histories. No genetic signature of recent population depletion was recovered through any analysis incorporating realistic mutation assumptions, probably due to the combined influences of long generation time, short bottleneck duration, and the magnitude of population depletion. In contrast, a robust signal of population expansion was detected around 70,000 years ago, followed by a population decline around 15,000 years ago. The timing of these events coincides to a historic glacial period and the onset of warming at the end of the last glacial maximum, respectively. By implication, climate driven long-term variation in Arctic Ocean productivity, rather than recent anthropogenic disturbance, appears to have been the primary driver of historic bowhead whale demography. PMID:23403722

Emerging Coxsackievirus A6 Causing Hand, Foot and Mouth Disease, Vietnam

PubMed Central

Anh, Nguyen To; Nhu, Le Nguyen Truc; Van, Hoang Minh Tu; Hong, Nguyen Thi Thu; Thanh, Tran Tan; Hang, Vu Thi Ty; Ny, Nguyen Thi Han; Nguyet, Lam Anh; Phuong, Tran Thi Lan; Nhan, Le Nguyen Thanh; Hung, Nguyen Thanh; Khanh, Truong Huu; Tuan, Ha Manh; Viet, Ho Lu; Nam, Nguyen Tran; Viet, Do Chau; Qui, Phan Tu; Wills, Bridget; Sabanathan, Sarawathy; Chau, Nguyen Van Vinh; Thwaites, Louise; Rogier van Doorn, H.; Thwaites, Guy; Rabaa, Maia A.

2018-01-01

Hand, foot and mouth disease (HFMD) is a major public health issue in Asia and has global pandemic potential. Coxsackievirus A6 (CV-A6) was detected in 514/2,230 (23%) of HFMD patients admitted to 3 major hospitals in southern Vietnam during 2011–2015. Of these patients, 93 (18%) had severe HFMD. Phylogenetic analysis of 98 genome sequences revealed they belonged to cluster A and had been circulating in Vietnam for 2 years before emergence. CV-A6 movement among localities within Vietnam occurred frequently, whereas viral movement across international borders appeared rare. Skyline plots identified fluctuations in the relative genetic diversity of CV-A6 corresponding to large CV-A6–associated HFMD outbreaks worldwide. These data show that CV-A6 is an emerging pathogen and emphasize the necessity of active surveillance and understanding the mechanisms that shape the pathogen evolution and emergence, which is essential for development and implementation of intervention strategies. PMID:29553326

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

La Russa, D

Purpose: The purpose of this project is to develop a robust method of parameter estimation for a Poisson-based TCP model using Bayesian inference. Methods: Bayesian inference was performed using the PyMC3 probabilistic programming framework written in Python. A Poisson-based TCP regression model that accounts for clonogen proliferation was fit to observed rates of local relapse as a function of equivalent dose in 2 Gy fractions for a population of 623 stage-I non-small-cell lung cancer patients. The Slice Markov Chain Monte Carlo sampling algorithm was used to sample the posterior distributions, and was initiated using the maximum of the posterior distributionsmore » found by optimization. The calculation of TCP with each sample step required integration over the free parameter α, which was performed using an adaptive 24-point Gauss-Legendre quadrature. Convergence was verified via inspection of the trace plot and posterior distribution for each of the fit parameters, as well as with comparisons of the most probable parameter values with their respective maximum likelihood estimates. Results: Posterior distributions for α, the standard deviation of α (σ), the average tumour cell-doubling time (Td), and the repopulation delay time (Tk), were generated assuming α/β = 10 Gy, and a fixed clonogen density of 10{sup 7} cm−{sup 3}. Posterior predictive plots generated from samples from these posterior distributions are in excellent agreement with the observed rates of local relapse used in the Bayesian inference. The most probable values of the model parameters also agree well with maximum likelihood estimates. Conclusion: A robust method of performing Bayesian inference of TCP data using a complex TCP model has been established.« less

Geological and climatic changes in quaternary shaped the evolutionary history of Calibrachoa heterophylla, an endemic South-Atlantic species of petunia

PubMed Central

2013-01-01

Background The glacial and interglacial cycles that characterized the Quaternary greatly affected the distribution and genetic diversity of plants. In the Neotropics, few phylogeographic studies have focused on coastal species outside of the Atlantic Rainforest. Climatic and sea level changes during the Quaternary played an important role in the evolutionary history of many organisms found in coastal regions. To contribute to a better understanding of plant evolution in this environment in Southern South America, we focused on Calibrachoa heterophylla (Solanaceae), an endemic and vulnerable wild petunia species from the South Atlantic Coastal Plain (SACP). Results We assessed DNA sequences from two cpDNA intergenic spacers and analyzed them using a phylogeographic approach. The present phylogeographic study reveals the influence of complex geologic and climatic events on patterns of genetic diversification. The results indicate that C. heterophylla originated inland and subsequently colonized the SACP; the data show that the inland haplogroup is more ancient than the coastal one and that the inland was not affected by sea level changes in the Quaternary. The major diversification of C. heterophylla that occurred after 0.4 Myr was linked to sea level oscillations in the Quaternary, and any diversification that occurred before this time was obscured by marine transgressions that occurred before the coastal sand barrier’s formation. Results of the Bayesian skyline plot showed a recent population expansion detected in C. heterophylla seems to be related to an increase in temperature and humidity that occurred at the beginning of the Holocene. Conclusions The geographic clades have been formed when the coastal plain was deeply dissected by paleochannels and these correlate very well with the distributional limits of the clades. The four major sea transgressions formed a series of four sand barriers parallel to the coast that progressively increased the availability of coastal areas after the regressions and that may have promoted the geographic structuring of genetic diversity observed today. The recent population expansion for the entire species may be linked with the event of marine regression after the most recent sea transgression at ~5 kya. PMID:23987105

Rubella Epidemics and Genotypic Distribution of the Rubella Virus in Shandong Province, China, in 1999–2010

PubMed Central

Xu, Qing; Xu, Aiqiang; Fang, Xueqiang; Song, Lizhi; Li, Weixiu; Xiong, Ping; Xu, Wenbo

2012-01-01

Background The rubella vaccine was introduced into the immunization program in 1995 in the Shandong province, China. A series of different rubella vaccination strategies were implemented at different stages of measles control in Shandong province. Methodology/Principal Findings The average reported incidence rate of rubella cases remained at a low level in Shandong province after 1999. However, rubella epidemics occurred repeatedly in 2001/2002, 2006, and 2008/2009. The age of the onset of rubella cases gradually increased during 1999–2010, which showed that most cases were found among the 10 years old in 1999 and among the 17 years old in 2010. Phylogenetic analysis was performed and a phylogenetic tree was constructed based on the World Health Organization standard sequence window for rubella virus isolates. All rubella viruses isolated in Shandong province were divided into 4 genotypes: 1E, 1F, 2A, and 2B. Genotype 1E viruses accounted for the majority (79%) of all these viruses. The similarity of nucleotide and amino acid sequences among genotype 1E viruses was 98.2–100% and 99.1–100%, respectively. All Shandong genotype 1E strains, differed from international genotype 1E strains, belonged to cluster 1 and interdigitated with the viruses from other provinces in mainland China. The effective number of infections indicated by a Bayesian skyline plot remained constant from 2001 to 2009. Conclusions/Significance The gradual shift of disease burden to an older age group occurred after a rubella-containing vaccine was introduced into the childhood immunization schedule in 1995 in Shandong province. Four genotypes, including 1E, 1F, 2A, and 2B, were found in Shandong province during 2000–2009. Genotype 1E, rather than genotype 1F, became the predominant genotype circulating in Shandong province from 2001. All Shandong genotype 1E viruses belong to the genotype 1E/cluster 1; they have constantly circulated, and co-evolved and co-circulated, with those from other provinces. PMID:22911874

Evolution of foot-and-mouth disease virus serotype A capsid coding (P1) region on a timescale of three decades in an endemic context.

PubMed

Das, Biswajit; Mohapatra, Jajati K; Pande, Veena; Subramaniam, Saravanan; Sanyal, Aniket

2016-07-01

Three decades-long (1977-2013) evolutionary trend of the capsid coding (P1) region of foot-and-mouth disease virus (FMDV) serotype A isolated in India was analysed. The exclusive presence of genotype 18 since 2001 and the dominance of the VP3(59)-deletion group of genotype 18 was evident in the recent years. Clade 18c was found to be currently the only active one among the three clades (18a, 18b and 18c) identified in the deletion group. The rate of evolution of the Indian isolates at the capsid region was found to be 4.96×10(-3)substitutions/site/year. The timescale analysis predicted the most recent common ancestor to have existed during 1962 for Indian FMDV serotype A and around 1998 for the deletion group. The evolutionary pattern of serotype A in India appears to be homogeneous as no spatial or temporal structure was observed. Bayesian skyline plots indicate a sharp decline in the effective number of infections after 2008, which might be a result of mass vaccination or inherent loss of virus fitness. Analyses of variability at 38 known antigenically critical positions in a countrywide longitudinal data set suggested that the substitutions neither followed any specific trend nor remained fixed for a long period since frequent reversions and convergence was noticed. A maximum of 6 different amino acid residues was seen in the gene pool at any antigenically critical site over the decades, suggesting a limited combination of residues being responsible for the observed antigenic variation. Evidence of positive selection at some of the antigenically critical residues and the structurally proximal positions suggest a possible role of pre-existing immunity in the host population in driving evolution. The VP1 C-terminus neither revealed variability nor positive selection, suggesting the possibility that this stretch does not contribute to the antigenic variation and adaptation under immune selection. Copyright © 2016 Elsevier B.V. All rights reserved.

Evaluation of a Phylogenetic Marker Based on Genomic Segment B of Infectious Bursal Disease Virus: Facilitating a Feasible Incorporation of this Segment to the Molecular Epidemiology Studies for this Viral Agent

PubMed Central

Martínez-Pérez, Orlando; Dolz, Roser; Valle, Rosa; Perera, Carmen L.; Bertran, Kateri; Frías, Maria T.; Ganges, Llilianne; Díaz de Arce, Heidy; Majó, Natàlia; Núñez, José I.; Pérez, Lester J.

2015-01-01

Background Infectious bursal disease (IBD) is a highly contagious and acute viral disease, which has caused high mortality rates in birds and considerable economic losses in different parts of the world for more than two decades and it still represents a considerable threat to poultry. The current study was designed to rigorously measure the reliability of a phylogenetic marker included into segment B. This marker can facilitate molecular epidemiology studies, incorporating this segment of the viral genome, to better explain the links between emergence, spreading and maintenance of the very virulent IBD virus (vvIBDV) strains worldwide. Methodology/Principal Findings Sequences of the segment B gene from IBDV strains isolated from diverse geographic locations were obtained from the GenBank Database; Cuban sequences were obtained in the current work. A phylogenetic marker named B-marker was assessed by different phylogenetic principles such as saturation of substitution, phylogenetic noise and high consistency. This last parameter is based on the ability of B-marker to reconstruct the same topology as the complete segment B of the viral genome. From the results obtained from B-marker, demographic history for both main lineages of IBDV regarding segment B was performed by Bayesian skyline plot analysis. Phylogenetic analysis for both segments of IBDV genome was also performed, revealing the presence of a natural reassortant strain with segment A from vvIBDV strains and segment B from non-vvIBDV strains within Cuban IBDV population. Conclusions/Significance This study contributes to a better understanding of the emergence of vvIBDV strains, describing molecular epidemiology of IBDV using the state-of-the-art methodology concerning phylogenetic reconstruction. This study also revealed the presence of a novel natural reassorted strain as possible manifest of change in the genetic structure and stability of the vvIBDV strains. Therefore, it highlights the need to obtain information about both genome segments of IBDV for molecular epidemiology studies. PMID:25946336

Bayesian Estimation of Fish Disease Prevalence from Pooled Samples Incorporating Sensitivity and Specificity

NASA Astrophysics Data System (ADS)

Williams, Christopher J.; Moffitt, Christine M.

2003-03-01

An important emerging issue in fisheries biology is the health of free-ranging populations of fish, particularly with respect to the prevalence of certain pathogens. For many years, pathologists focused on captive populations and interest was in the presence or absence of certain pathogens, so it was economically attractive to test pooled samples of fish. Recently, investigators have begun to study individual fish prevalence from pooled samples. Estimation of disease prevalence from pooled samples is straightforward when assay sensitivity and specificity are perfect, but this assumption is unrealistic. Here we illustrate the use of a Bayesian approach for estimating disease prevalence from pooled samples when sensitivity and specificity are not perfect. We also focus on diagnostic plots to monitor the convergence of the Gibbs-sampling-based Bayesian analysis. The methods are illustrated with a sample data set.

Extract useful knowledge from agro-hydrological simulations data for decision making

NASA Astrophysics Data System (ADS)

Gascuel-odoux, C.; Bouadi, T.; Cordier, M.; Quiniou, R.

2013-12-01

In recent years, models have been developed and used to test the effect of scenarios and help stakeholders in decision making. Agro-hydrological models have guided agricultural water management by testing the effect of landscape structure and farming system changes on water quantity and quality. Such models generate a large amount of data but few are stored and are often not customized for stakeholders, so that a great amount of information is lost from the simulation process or not transformed in a usable format. A first approach, already published (Trepos et al., 2012), has been developed to identify object oriented tree patterns, that represent surface flow and pollutant pathways from plot to plot, involved in water pollution by herbicides. A simulation model (Gascuel-odoux et al., 2009) predicted herbicide transfer rate, defined as the proportion of applied herbicide that reaches water courses. The predictions were used as a set of learning examples for symbolic learning techniques to induce rules based on qualitative and quantitative attributes and explain two extreme classes in transfer rate. Two automatic symbolic learning techniques were used: the inductive logic programming approach to induce spatial tree patterns, and an attribute-value method to induce aggregated attributes of the trees. A visualization interface allows the users to identify rules explaining contamination and mitigation measures improving the current situation. A second approach has been recently developed to analyse directly the simulated data (Bouadi et al, submitted). A data warehouse called N-catch has been built to store and manage simulation data from the agro-hydrological model TNT2 (Beaujouan et al., 2002). 44 output key simulated variables are stored per plot and at a daily time step on a 50 squared km area, i.e, 8 GB of storage size. After identifying the set of multileveled dimensions integrating hierarchical structures and relationships among related dimension levels, N-Catch has been designed using the open source Business Intelligence Platform Pentaho. We show how to use online analytical processing (OLAP) to access and exploit, intuitively and quickly, the multidimensional and aggregated data from the N-Catch data warehouse. We illustrate how the data warehouse can be used to explore spatio-temporal dimensions efficiently and to discover new knowledge at multiple levels of simulation. OLAP tool can be used to synthesize environmental information and understand nitrogen emissions in water bodies by generating comparative and personalized views of historical data. This DWH is currently extended with data mining or information retrieval methods as Skyline queries to perform advanced analyses (Bouadi et al., 2012). Bouadi et al. N-Catch: A Data Warehouse for Multilevel Analysis of Simulated Nitrogen Data from an Agro-hydrological Model. Submitted. Bouadi et al., 2012) Bouadi, T., Cordier, M., and Quiniou, R. (2012). Incremental computation of skyline queries with dynamic preferences. In DEXA (1), pages 219-233. Trepos et al. 2012. Mining simulation data by rule induction to determine critical source areas of stream water pollution by herbicides. Computers and Electronics in Agriculture 86, 75-88.

[Bayesian approach for the cost-effectiveness evaluation of healthcare technologies].

PubMed

Berchialla, Paola; Gregori, Dario; Brunello, Franco; Veltri, Andrea; Petrinco, Michele; Pagano, Eva

2009-01-01

The development of Bayesian statistical methods for the assessment of the cost-effectiveness of health care technologies is reviewed. Although many studies adopt a frequentist approach, several authors have advocated the use of Bayesian methods in health economics. Emphasis has been placed on the advantages of the Bayesian approach, which include: (i) the ability to make more intuitive and meaningful inferences; (ii) the ability to tackle complex problems, such as allowing for the inclusion of patients who generate no cost, thanks to the availability of powerful computational algorithms; (iii) the importance of a full use of quantitative and structural prior information to produce realistic inferences. Much literature comparing the cost-effectiveness of two treatments is based on the incremental cost-effectiveness ratio. However, new methods are arising with the purpose of decision making. These methods are based on a net benefits approach. In the present context, the cost-effectiveness acceptability curves have been pointed out to be intrinsically Bayesian in their formulation. They plot the probability of a positive net benefit against the threshold cost of a unit increase in efficacy.A case study is presented in order to illustrate the Bayesian statistics in the cost-effectiveness analysis. Emphasis is placed on the cost-effectiveness acceptability curves. Advantages and disadvantages of the method described in this paper have been compared to frequentist methods and discussed.

Use of airborne lidar data to improve plant species richness and diversity monitoring in lowland and mountain forests

PubMed Central

Durrieu, Sylvie; Gosselin, Frédéric; Herpigny, Basile

2017-01-01

We explored the potential of airborne laser scanner (ALS) data to improve Bayesian models linking biodiversity indicators of the understory vegetation to environmental factors. Biodiversity was studied at plot level and models were built to investigate species abundance for the most abundant plants found on each study site, and for ecological group richness based on light preference. The usual abiotic explanatory factors related to climate, topography and soil properties were used in the models. ALS data, available for two contrasting study sites, were used to provide biotic factors related to forest structure, which was assumed to be a key driver of understory biodiversity. Several ALS variables were found to have significant effects on biodiversity indicators. However, the responses of biodiversity indicators to forest structure variables, as revealed by the Bayesian model outputs, were shown to be dependent on the abiotic environmental conditions characterizing the study areas. Lower responses were observed on the lowland site than on the mountainous site. In the latter, shade-tolerant and heliophilous species richness was impacted by vegetation structure indicators linked to light penetration through the canopy. However, to reveal the full effects of forest structure on biodiversity indicators, forest structure would need to be measured over much wider areas than the plot we assessed. It seems obvious that the forest structure surrounding the field plots can impact biodiversity indicators measured at plot level. Various scales were found to be relevant depending on: the biodiversity indicators that were modelled, and the ALS variable. Finally, our results underline the utility of lidar data in abundance and richness models to characterize forest structure with variables that are difficult to measure in the field, either due to their nature or to the size of the area they relate to. PMID:28902920

DISPAQ: Distributed Profitable-Area Query from Big Taxi Trip Data.

PubMed

Putri, Fadhilah Kurnia; Song, Giltae; Kwon, Joonho; Rao, Praveen

2017-09-25

One of the crucial problems for taxi drivers is to efficiently locate passengers in order to increase profits. The rapid advancement and ubiquitous penetration of Internet of Things (IoT) technology into transportation industries enables us to provide taxi drivers with locations that have more potential passengers (more profitable areas) by analyzing and querying taxi trip data. In this paper, we propose a query processing system, called Distributed Profitable-Area Query ( DISPAQ ) which efficiently identifies profitable areas by exploiting the Apache Software Foundation's Spark framework and a MongoDB database. DISPAQ first maintains a profitable-area query index (PQ-index) by extracting area summaries and route summaries from raw taxi trip data. It then identifies candidate profitable areas by searching the PQ-index during query processing. Then, it exploits a Z-Skyline algorithm, which is an extension of skyline processing with a Z-order space filling curve, to quickly refine the candidate profitable areas. To improve the performance of distributed query processing, we also propose local Z-Skyline optimization, which reduces the number of dominant tests by distributing killer profitable areas to each cluster node. Through extensive evaluation with real datasets, we demonstrate that our DISPAQ system provides a scalable and efficient solution for processing profitable-area queries from huge amounts of big taxi trip data.

DISPAQ: Distributed Profitable-Area Query from Big Taxi Trip Data †

PubMed Central

Putri, Fadhilah Kurnia; Song, Giltae; Rao, Praveen

2017-01-01

One of the crucial problems for taxi drivers is to efficiently locate passengers in order to increase profits. The rapid advancement and ubiquitous penetration of Internet of Things (IoT) technology into transportation industries enables us to provide taxi drivers with locations that have more potential passengers (more profitable areas) by analyzing and querying taxi trip data. In this paper, we propose a query processing system, called Distributed Profitable-Area Query (DISPAQ) which efficiently identifies profitable areas by exploiting the Apache Software Foundation’s Spark framework and a MongoDB database. DISPAQ first maintains a profitable-area query index (PQ-index) by extracting area summaries and route summaries from raw taxi trip data. It then identifies candidate profitable areas by searching the PQ-index during query processing. Then, it exploits a Z-Skyline algorithm, which is an extension of skyline processing with a Z-order space filling curve, to quickly refine the candidate profitable areas. To improve the performance of distributed query processing, we also propose local Z-Skyline optimization, which reduces the number of dominant tests by distributing killer profitable areas to each cluster node. Through extensive evaluation with real datasets, we demonstrate that our DISPAQ system provides a scalable and efficient solution for processing profitable-area queries from huge amounts of big taxi trip data. PMID:28946679

LiDAR based prediction of forest biomass using hierarchical models with spatially varying coefficients

Treesearch

Chad Babcock; Andrew O. Finley; John B. Bradford; Randy Kolka; Richard Birdsey; Michael G. Ryan

2015-01-01

Many studies and production inventory systems have shown the utility of coupling covariates derived from Light Detection and Ranging (LiDAR) data with forest variables measured on georeferenced inventory plots through regression models. The objective of this study was to propose and assess the use of a Bayesian hierarchical modeling framework that accommodates both...

Proliferation of East Antarctic Adélie penguins in response to historical deglaciation.

PubMed

Younger, Jane; Emmerson, Louise; Southwell, Colin; Lelliott, Patrick; Miller, Karen

2015-11-18

Major, long-term environmental changes are projected in the Southern Ocean and these are likely to have impacts for marine predators such as the Adélie penguin (Pygoscelis adeliae). Decadal monitoring studies have provided insight into the short-term environmental sensitivities of Adélie penguin populations, particularly to sea ice changes. However, given the long-term nature of projected climate change, it is also prudent to consider the responses of populations to environmental change over longer time scales. We investigated the population trajectory of Adélie penguins during the last glacial-interglacial transition to determine how the species was affected by climate warming over millennia. We focussed our study on East Antarctica, which is home to 30 % of the global population of Adélie penguins. Using mitochondrial DNA from extant colonies, we reconstructed the population trend of Adélie penguins in East Antarctica over the past 22,000 years using an extended Bayesian skyline plot method. To determine the relationship of East Antarctic Adélie penguins with populations elsewhere in Antarctica we constructed a phylogeny using mitochondrial DNA sequences. We found that the Adélie penguin population expanded 135-fold from approximately 14,000 years ago. The population growth was coincident with deglaciation in East Antarctica and, therefore, an increase in ice-free ground suitable for Adélie penguin nesting. Our phylogenetic analysis indicated that East Antarctic Adélie penguins share a common ancestor with Adélie penguins from the Antarctic Peninsula and Scotia Arc, with an estimated age of 29,000 years ago, in the midst of the last glacial period. This finding suggests that extant colonies in East Antarctica, the Scotia Arc and the Antarctic Peninsula were founded from a single glacial refuge. While changes in sea ice conditions are a critical driver of Adélie penguin population success over decadal and yearly timescales, deglaciation appears to have been the key driver of population change over millennia. This suggests that environmental drivers of population trends over thousands of years may differ to drivers over years or decades, highlighting the need to consider millennial-scale trends alongside contemporary data for the forecasting of species' abundance and distribution changes under future climate change scenarios.

Nonparametric Bayesian Context Learning for Buried Threat Detection

DTIC Science & Technology

2012-01-01

scans of field-collected GPR data collected on dirt (top) and gravel (bottom) lanes at an Eastern US test site. . . . . . . . . . 47 2.11 Plot of ...partition the data into M components, they differ in the information used to partition the data. First, approaches that as- sume independence of observations...and the advantages and disadvantages of using each are discussed. Furthermore, the merits of incorporating spatial information are also highlighted

Rapid Assessment of Contaminants and Interferences in Mass Spectrometry Data Using Skyline

NASA Astrophysics Data System (ADS)

Rardin, Matthew J.

2018-04-01

Proper sample preparation in proteomic workflows is essential to the success of modern mass spectrometry experiments. Complex workflows often require reagents which are incompatible with MS analysis (e.g., detergents) necessitating a variety of sample cleanup procedures. Efforts to understand and mitigate sample contamination are a continual source of disruption with respect to both time and resources. To improve the ability to rapidly assess sample contamination from a diverse array of sources, I developed a molecular library in Skyline for rapid extraction of contaminant precursor signals using MS1 filtering. This contaminant template library is easily managed and can be modified for a diverse array of mass spectrometry sample preparation workflows. Utilization of this template allows rapid assessment of sample integrity and indicates potential sources of contamination. [Figure not available: see fulltext.

The impact of warming on greenhouse gas fluxes: an experimental comparison which reveals the varied response of ecosystems to climate change.

NASA Astrophysics Data System (ADS)

Stockdale, James; Ineson, Philip

2016-04-01

Modelled predictions of the response of terrestrial systems to climate change are highly variable, yet the response of net ecosystem exchange (NEE) is a vital ecosystem behaviour to understand due to its inherent feedback to the carbon cycle. The establishment and subsequent monitoring of replicated experimental manipulations are a direct method to reveal these responses, yet are difficult to achieve as they typically resource-heavy and labour intensive. We actively manipulated the temperature at three agricultural grasslands in southern England and deployed novel 'SkyLine' systems, recently developed at the University of York, to continuously monitor GHG fluxes. Each 'SkyLine' is a low-cost and fully autonomous technology yet produces fluxes at a near-continuous temporal frequency and across a wide spatial area. The results produced by 'SkyLine' enable the detail response of each system to increased temperature over diurnal and seasonal timescales. Unexpected differences in NEE are shown between superficially similar ecosystems which, upon investigation, suggest that interactions between a variety of environmental variables are key and that knowledge of pre-existing environmental conditions help to predict a systems response to future climate. For example, the prevailing hydrological conditions at each site appear to affect its response to changing temperature. The high-frequency data shown here, combined with the fully-replicated experimental design reveal complex interactions which must be understood to improve predictions of ecosystem response to a changing climate.

Data-Independent MS/MS Quantification of Neuropeptides for Determination of Putative Feeding-Related Neurohormones in Microdialysate

PubMed Central

2015-01-01

Food consumption is an important behavior that is regulated by an intricate array of neuropeptides (NPs). Although many feeding-related NPs have been identified in mammals, precise mechanisms are unclear and difficult to study in mammals, as current methods are not highly multiplexed and require extensive a priori knowledge about analytes. New advances in data-independent acquisition (DIA) MS/MS and the open-source quantification software Skyline have opened up the possibility to identify hundreds of compounds and quantify them from a single DIA MS/MS run. An untargeted DIA MSE quantification method using Skyline software for multiplexed, discovery-driven quantification was developed and found to produce linear calibration curves for peptides at physiologically relevant concentrations using a protein digest as internal standard. By using this method, preliminary relative quantification of the crab Cancer borealis neuropeptidome (<2 kDa, 137 peptides from 18 families) was possible in microdialysates from 8 replicate feeding experiments. Of these NPs, 55 were detected with an average mass error below 10 ppm. The time-resolved profiles of relative concentration changes for 6 are shown, and there is great potential for the use of this method in future experiments to aid in correlation of NP changes with behavior. This work presents an unbiased approach to winnowing candidate NPs related to a behavior of interest in a functionally relevant manner, and demonstrates the success of such a UPLC-MSE quantification method using the open source software Skyline. PMID:25552291

Data-independent MS/MS quantification of neuropeptides for determination of putative feeding-related neurohormones in microdialysate.

PubMed

Schmerberg, Claire M; Liang, Zhidan; Li, Lingjun

2015-01-21

Food consumption is an important behavior that is regulated by an intricate array of neuropeptides (NPs). Although many feeding-related NPs have been identified in mammals, precise mechanisms are unclear and difficult to study in mammals, as current methods are not highly multiplexed and require extensive a priori knowledge about analytes. New advances in data-independent acquisition (DIA) MS/MS and the open-source quantification software Skyline have opened up the possibility to identify hundreds of compounds and quantify them from a single DIA MS/MS run. An untargeted DIA MS(E) quantification method using Skyline software for multiplexed, discovery-driven quantification was developed and found to produce linear calibration curves for peptides at physiologically relevant concentrations using a protein digest as internal standard. By using this method, preliminary relative quantification of the crab Cancer borealis neuropeptidome (<2 kDa, 137 peptides from 18 families) was possible in microdialysates from 8 replicate feeding experiments. Of these NPs, 55 were detected with an average mass error below 10 ppm. The time-resolved profiles of relative concentration changes for 6 are shown, and there is great potential for the use of this method in future experiments to aid in correlation of NP changes with behavior. This work presents an unbiased approach to winnowing candidate NPs related to a behavior of interest in a functionally relevant manner, and demonstrates the success of such a UPLC-MS(E) quantification method using the open source software Skyline.

RadVel: General toolkit for modeling Radial Velocities

NASA Astrophysics Data System (ADS)

Fulton, Benjamin J.; Petigura, Erik A.; Blunt, Sarah; Sinukoff, Evan

2018-01-01

RadVel models Keplerian orbits in radial velocity (RV) time series. The code is written in Python with a fast Kepler's equation solver written in C. It provides a framework for fitting RVs using maximum a posteriori optimization and computing robust confidence intervals by sampling the posterior probability density via Markov Chain Monte Carlo (MCMC). RadVel can perform Bayesian model comparison and produces publication quality plots and LaTeX tables.

iSEDfit: Bayesian spectral energy distribution modeling of galaxies

NASA Astrophysics Data System (ADS)

Moustakas, John

2017-08-01

iSEDfit uses Bayesian inference to extract the physical properties of galaxies from their observed broadband photometric spectral energy distribution (SED). In its default mode, the inputs to iSEDfit are the measured photometry (fluxes and corresponding inverse variances) and a measurement of the galaxy redshift. Alternatively, iSEDfit can be used to estimate photometric redshifts from the input photometry alone. After the priors have been specified, iSEDfit calculates the marginalized posterior probability distributions for the physical parameters of interest, including the stellar mass, star-formation rate, dust content, star formation history, and stellar metallicity. iSEDfit also optionally computes K-corrections and produces multiple "quality assurance" (QA) plots at each stage of the modeling procedure to aid in the interpretation of the prior parameter choices and subsequent fitting results. The software is distributed as part of the impro IDL suite.

Characterization of a Saccharomyces cerevisiae fermentation process for production of a therapeutic recombinant protein using a multivariate Bayesian approach.

PubMed

Fu, Zhibiao; Baker, Daniel; Cheng, Aili; Leighton, Julie; Appelbaum, Edward; Aon, Juan

2016-05-01

The principle of quality by design (QbD) has been widely applied to biopharmaceutical manufacturing processes. Process characterization is an essential step to implement the QbD concept to establish the design space and to define the proven acceptable ranges (PAR) for critical process parameters (CPPs). In this study, we present characterization of a Saccharomyces cerevisiae fermentation process using risk assessment analysis, statistical design of experiments (DoE), and the multivariate Bayesian predictive approach. The critical quality attributes (CQAs) and CPPs were identified with a risk assessment. The statistical model for each attribute was established using the results from the DoE study with consideration given to interactions between CPPs. Both the conventional overlapping contour plot and the multivariate Bayesian predictive approaches were used to establish the region of process operating conditions where all attributes met their specifications simultaneously. The quantitative Bayesian predictive approach was chosen to define the PARs for the CPPs, which apply to the manufacturing control strategy. Experience from the 10,000 L manufacturing scale process validation, including 64 continued process verification batches, indicates that the CPPs remain under a state of control and within the established PARs. The end product quality attributes were within their drug substance specifications. The probability generated with the Bayesian approach was also used as a tool to assess CPP deviations. This approach can be extended to develop other production process characterization and quantify a reliable operating region. © 2016 American Institute of Chemical Engineers Biotechnol. Prog., 32:799-812, 2016. © 2016 American Institute of Chemical Engineers.

Evaluating impacts using a BACI design, ratios, and a Bayesian approach with a focus on restoration.

PubMed

Conner, Mary M; Saunders, W Carl; Bouwes, Nicolaas; Jordan, Chris

2015-10-01

Before-after-control-impact (BACI) designs are an effective method to evaluate natural and human-induced perturbations on ecological variables when treatment sites cannot be randomly chosen. While effect sizes of interest can be tested with frequentist methods, using Bayesian Markov chain Monte Carlo (MCMC) sampling methods, probabilities of effect sizes, such as a ≥20 % increase in density after restoration, can be directly estimated. Although BACI and Bayesian methods are used widely for assessing natural and human-induced impacts for field experiments, the application of hierarchal Bayesian modeling with MCMC sampling to BACI designs is less common. Here, we combine these approaches and extend the typical presentation of results with an easy to interpret ratio, which provides an answer to the main study question-"How much impact did a management action or natural perturbation have?" As an example of this approach, we evaluate the impact of a restoration project, which implemented beaver dam analogs, on survival and density of juvenile steelhead. Results indicated the probabilities of a ≥30 % increase were high for survival and density after the dams were installed, 0.88 and 0.99, respectively, while probabilities for a higher increase of ≥50 % were variable, 0.17 and 0.82, respectively. This approach demonstrates a useful extension of Bayesian methods that can easily be generalized to other study designs from simple (e.g., single factor ANOVA, paired t test) to more complicated block designs (e.g., crossover, split-plot). This approach is valuable for estimating the probabilities of restoration impacts or other management actions.

8. Engineering Drawing of Panama Gun Mount by U.S. Engineering ...

Library of Congress Historic Buildings Survey, Historic Engineering Record, Historic Landscapes Survey

8. Engineering Drawing of Panama Gun Mount by U.S. Engineering Office, San Francisco, California - Fort Funston, Panama Mounts for 155mm Guns, Skyline Boulevard & Great Highway, San Francisco, San Francisco County, CA

Metapopulations in temporary streams - the role of drought-flood cycles in promoting high genetic diversity in a critically endangered freshwater fish and its consequences for the future.

PubMed

Sousa-Santos, Carla; Robalo, Joana I; Francisco, Sara M; Carrapato, Carlos; Cardoso, Ana Cristina; Doadrio, Ignacio

2014-11-01

Genetic factors have direct and indirect impacts in the viability of endangered species. Assessing their genetic diversity levels and population structure is thus fundamental for conservation and management. In this paper we use mitochondrial and nuclear markers to address phylogeographic and demographic data on the critically endangered Anaecypris hispanica, using a broad sampling set which covered its known distribution area in the Iberian Peninsula. Our results showed that the populations of A. hispanica are strongly differentiated (high and significant ФST and FST values, corroborated by the results from AMOVA and SAMOVA) and genetically diversified. We suggest that the restricted gene flow between populations may have been potentiated by ecological, hydrological and anthropogenic causes. Bayesian skyline plots revealed a signal for expansion for all populations (tMRCA between 68kya and 1.33Mya) and a genetic diversity latitudinal gradient was detected between the populations from the Upper (more diversified) and the Lower (less diversified) Guadiana river basin. We postulate a Pleistocenic westwards colonization route for A. hispanica in the Guadiana river basin, which is in agreement with the tempo and mode of paleoevolution of this drainage. The colonization of River Guadalquivir around 60kya with migrants from the Upper Guadiana, most likely by stream capture, is also suggested. This study highlights the view that critically endangered species facing range retreats (about 47% of its known populations have disappeared in the last 15years) are not necessarily small and genetically depleted. However, the extinction risk is not negligible since A. hispanica faces the combined effect of several deterministic and stochastic negative factors and, moreover, recolonization events after localized extinctions are very unlikely to occur due to the strong isolation of populations and to the patchily ecologically-conditioned distribution of fish. The inferred species distribution models highlight the significant contribution of temperature seasonality and isothermality to A. hispanica occurrence in Guadiana environments and emphasize the importance of stable climatic conditions for the preservation of this species. Given the strong population structure, high percentage of private haplotypes and virtual absence of inter-basin gene flow we suggest that each A. hispanica population should be considered as an independent Operational Conservation Unit and that ex-situ and in-situ actions should be conducted in parallel to allow for the long-term survival of the species and the preservation of the genetic integrity of its populations. Copyright © 2014 Elsevier Inc. All rights reserved.

Efficiently Selecting the Best Web Services

NASA Astrophysics Data System (ADS)

Goncalves, Marlene; Vidal, Maria-Esther; Regalado, Alfredo; Yacoubi Ayadi, Nadia

Emerging technologies and linking data initiatives have motivated the publication of a large number of datasets, and provide the basis for publishing Web services and tools to manage the available data. This wealth of resources opens a world of possibilities to satisfy user requests. However, Web services may have similar functionality and assess different performance; therefore, it is required to identify among the Web services that satisfy a user request, the ones with the best quality. In this paper we propose a hybrid approach that combines reasoning tasks with ranking techniques to aim at the selection of the Web services that best implement a user request. Web service functionalities are described in terms of input and output attributes annotated with existing ontologies, non-functionality is represented as Quality of Services (QoS) parameters, and user requests correspond to conjunctive queries whose sub-goals impose restrictions on the functionality and quality of the services to be selected. The ontology annotations are used in different reasoning tasks to infer service implicit properties and to augment the size of the service search space. Furthermore, QoS parameters are considered by a ranking metric to classify the services according to how well they meet a user non-functional condition. We assume that all the QoS parameters of the non-functional condition are equally important, and apply the Top-k Skyline approach to select the k services that best meet this condition. Our proposal relies on a two-fold solution which fires a deductive-based engine that performs different reasoning tasks to discover the services that satisfy the requested functionality, and an efficient implementation of the Top-k Skyline approach to compute the top-k services that meet the majority of the QoS constraints. Our Top-k Skyline solution exploits the properties of the Skyline Frequency metric and identifies the top-k services by just analyzing a subset of the services that meet the non-functional condition. We report on the effects of the proposed reasoning tasks, the quality of the top-k services selected by the ranking metric, and the performance of the proposed ranking techniques. Our results suggest that the number of services can be augmented by up two orders of magnitude. In addition, our ranking techniques are able to identify services that have the best values in at least half of the QoS parameters, while the performance is improved.

Glacial refugia and recolonization pathways in the brown seaweed Fucus serratus.

PubMed

Hoarau, G; Coyer, J A; Veldsink, J H; Stam, W T; Olsen, J L

2007-09-01

The last glacial maximum (20,000-18,000 years ago) dramatically affected extant distributions of virtually all northern European biota. Locations of refugia and postglacial recolonization pathways were examined in Fucus serratus (Heterokontophyta; Fucaceae) using a highly variable intergenic spacer developed from the complete mitochondrial genome of Fucus vesiculosus. Over 1,500 samples from the entire range of F. serratus were analysed using fluorescent single strand conformation polymorphism. A total of 28 mtDNA haplotypes was identified and sequenced. Three refugia were recognized based on high haplotype diversities and the presence of endemic haplotypes: southwest Ireland, the northern Brittany-Hurd Deep area of the English Channel, and the northwest Iberian Peninsula. The Irish refugium was the source for a recolonization sweep involving a single haplotype via northern Scotland and throughout Scandinavia, whereas recolonization from the Brittany-Hurd Deep refugium was more limited, probably because of unsuitable soft-bottom habitat in the Bay of Biscay and along the Belgian and Dutch coasts. The Iberian populations reflect a remnant refugium at the present-day southern boundary of the species range. A generalized skyline plot suggested exponential population expansion beginning in the mid-Pleistocene with maximal growth during the Eems interglacial 128,000-67,000 years ago, implying that the last glacial maximum mainly shaped population distributions rather than demography.

Reliability modelling and analysis of a multi-state element based on a dynamic Bayesian network

NASA Astrophysics Data System (ADS)

Li, Zhiqiang; Xu, Tingxue; Gu, Junyuan; Dong, Qi; Fu, Linyu

2018-04-01

This paper presents a quantitative reliability modelling and analysis method for multi-state elements based on a combination of the Markov process and a dynamic Bayesian network (DBN), taking perfect repair, imperfect repair and condition-based maintenance (CBM) into consideration. The Markov models of elements without repair and under CBM are established, and an absorbing set is introduced to determine the reliability of the repairable element. According to the state-transition relations between the states determined by the Markov process, a DBN model is built. In addition, its parameters for series and parallel systems, namely, conditional probability tables, can be calculated by referring to the conditional degradation probabilities. Finally, the power of a control unit in a failure model is used as an example. A dynamic fault tree (DFT) is translated into a Bayesian network model, and subsequently extended to a DBN. The results show the state probabilities of an element and the system without repair, with perfect and imperfect repair, and under CBM, with an absorbing set plotted by differential equations and verified. Through referring forward, the reliability value of the control unit is determined in different kinds of modes. Finally, weak nodes are noted in the control unit.

Sylvatic plague vaccine partially protects prairie dogs (Cynomys spp.) in field trials

USGS Publications Warehouse

Rocke, Tonie E.; Tripp, Daniel W.; Russell, Robin E.; Abbott, Rachel C.; Richgels, Katherine; Matchett, Marc R.; Biggins, Dean E.; Griebel, Randall; Schroeder, Greg; Grassel, Shaun M.; Pipkin, David R.; Cordova, Jennifer; Kavalunas, Adam; Maxfield, Brian; Boulerice, Jesse; Miller, Michael W.

2017-01-01

Sylvatic plague, caused by Yersinia pestis, frequently afflicts prairie dogs (Cynomys spp.), causing population declines and local extirpations. We tested the effectiveness of bait-delivered sylvatic plague vaccine (SPV) in prairie dog colonies on 29 paired placebo and treatment plots (1–59 ha in size; average 16.9 ha) in 7 western states from 2013 to 2015. We compared relative abundance (using catch per unit effort (CPUE) as an index) and apparent survival of prairie dogs on 26 of the 29 paired plots, 12 with confirmed or suspected plague (Y. pestis positive carcasses or fleas). Even though plague mortality occurred in prairie dogs on vaccine plots, SPV treatment had an overall positive effect on CPUE in all three years, regardless of plague status. Odds of capturing a unique animal were 1.10 (95% confidence interval [C.I.] 1.02–1.19) times higher per trap day on vaccine-treated plots than placebo plots in 2013, 1.47 (95% C.I. 1.41–1.52) times higher in 2014 and 1.19 (95% C.I. 1.13–1.25) times higher in 2015. On pairs where plague occurred, odds of apparent survival were 1.76 (95% Bayesian credible interval [B.C.I.] 1.28–2.43) times higher on vaccine plots than placebo plots for adults and 2.41 (95% B.C.I. 1.72–3.38) times higher for juveniles. Our results provide evidence that consumption of vaccine-laden baits can protect prairie dogs against plague; however, further evaluation and refinement are needed to optimize SPV use as a management tool.

76 FR 49753 - Privacy Act of 1974; System of Records

Federal Register 2010, 2011, 2012, 2013, 2014

2011-08-11

... Defense. DHA 14 System name: Computer/Electronics Accommodations Program for People with Disabilities... with ``Computer/Electronic Accommodations Program.'' System location: Delete entry and replace with ``Computer/Electronic Accommodations Program, Skyline 5, Suite 302, 5111 Leesburg Pike, Falls Church, VA...

ORD BROWNFIELDS RESEARCH

EPA Science Inventory

The exhibit is a 10'x10' skyline truss which will be used to highlight the activities of the U.S.-German Bilateral Working Group in the area of brownfields revitalization. The U.S. product, Sustainable Management Approaches and Revitalization Tools - electronic (SMARTe) will be d...

Implementation of precast concrete deck system NUDECK (2nd generation).

DOT National Transportation Integrated Search

2013-12-01

The first generation of precast concrete deck system, NUDECK, developed by the University of NebraskaLincoln (UNL) for Nebraska Department of Roads (NDOR), was implemented on the Skyline Bridge, : Omaha, NE in 2004. The project was highly successful ...

STS-119 Launch Skyline

NASA Image and Video Library

2009-03-15

STS119-S-025 (15 March 2009) --- The setting sun paints the clouds over NASA's Kennedy Space Center in Florida before the launch of Space Shuttle Discovery on the STS-119 mission. Liftoff is scheduled for 7:43 p.m. (EDT) on March 15, 2009.

4. A river level view of the Broad Street bridge ...

Library of Congress Historic Buildings Survey, Historic Engineering Record, Historic Landscapes Survey

4. A river level view of the Broad Street bridge and Columbus skyline from the railroad truss north of the bridge. - Broad Street Bridge, Spanning Scioto River at U.S. Route 40 (Broad Street), Columbus, Franklin County, OH

Deadly Everest Avalanche Site Spotted by NASA Spacecraft

NASA Image and Video Library

2014-04-28

On Friday, April 26, 2014, an avalanche on Mount Everest killed at least 13 Sherpa guides. NASA Terra spacecraft looked toward the northeast, with Mount Everest center, and Lhotse, the fourth-highest mountain on Earth, on the skyline to right center.

101. Catalog HHistory 1, C.C.C., 34 Landscaping, Negative No. 1340 ...

Library of Congress Historic Buildings Survey, Historic Engineering Record, Historic Landscapes Survey

101. Catalog H-History 1, C.C.C., 34 Landscaping, Negative No. 1340 (Photographer and date unknown) BANK BLENDING WORK BY CCC. - Skyline Drive, From Front Royal, VA to Rockfish Gap, VA , Luray, Page County, VA

98. Catalog HHistory 1, C.C.C., 19 Tree Planting, Negative No. ...

Library of Congress Historic Buildings Survey, Historic Engineering Record, Historic Landscapes Survey

98. Catalog H-History 1, C.C.C., 19 Tree Planting, Negative No. P 474c (Photographer and date unknown) TRANSPLANTING TREE. - Skyline Drive, From Front Royal, VA to Rockfish Gap, VA , Luray, Page County, VA

Automatic classification of spectra from the Infrared Astronomical Satellite (IRAS)

NASA Technical Reports Server (NTRS)

Cheeseman, Peter; Stutz, John; Self, Matthew; Taylor, William; Goebel, John; Volk, Kevin; Walker, Helen

1989-01-01

A new classification of Infrared spectra collected by the Infrared Astronomical Satellite (IRAS) is presented. The spectral classes were discovered automatically by a program called Auto Class 2. This program is a method for discovering (inducing) classes from a data base, utilizing a Bayesian probability approach. These classes can be used to give insight into the patterns that occur in the particular domain, in this case, infrared astronomical spectroscopy. The classified spectra are the entire Low Resolution Spectra (LRS) Atlas of 5,425 sources. There are seventy-seven classes in this classification and these in turn were meta-classified to produce nine meta-classes. The classification is presented as spectral plots, IRAS color-color plots, galactic distribution plots and class commentaries. Cross-reference tables, listing the sources by IRAS name and by Auto Class class, are also given. These classes show some of the well known classes, such as the black-body class, and silicate emission classes, but many other classes were unsuspected, while others show important subtle differences within the well known classes.

A Bayesian Approach for Summarizing and Modeling Time-Series Exposure Data with Left Censoring.

PubMed

Houseman, E Andres; Virji, M Abbas

2017-08-01

Direct reading instruments are valuable tools for measuring exposure as they provide real-time measurements for rapid decision making. However, their use is limited to general survey applications in part due to issues related to their performance. Moreover, statistical analysis of real-time data is complicated by autocorrelation among successive measurements, non-stationary time series, and the presence of left-censoring due to limit-of-detection (LOD). A Bayesian framework is proposed that accounts for non-stationary autocorrelation and LOD issues in exposure time-series data in order to model workplace factors that affect exposure and estimate summary statistics for tasks or other covariates of interest. A spline-based approach is used to model non-stationary autocorrelation with relatively few assumptions about autocorrelation structure. Left-censoring is addressed by integrating over the left tail of the distribution. The model is fit using Markov-Chain Monte Carlo within a Bayesian paradigm. The method can flexibly account for hierarchical relationships, random effects and fixed effects of covariates. The method is implemented using the rjags package in R, and is illustrated by applying it to real-time exposure data. Estimates for task means and covariates from the Bayesian model are compared to those from conventional frequentist models including linear regression, mixed-effects, and time-series models with different autocorrelation structures. Simulations studies are also conducted to evaluate method performance. Simulation studies with percent of measurements below the LOD ranging from 0 to 50% showed lowest root mean squared errors for task means and the least biased standard deviations from the Bayesian model compared to the frequentist models across all levels of LOD. In the application, task means from the Bayesian model were similar to means from the frequentist models, while the standard deviations were different. Parameter estimates for covariates were significant in some frequentist models, but in the Bayesian model their credible intervals contained zero; such discrepancies were observed in multiple datasets. Variance components from the Bayesian model reflected substantial autocorrelation, consistent with the frequentist models, except for the auto-regressive moving average model. Plots of means from the Bayesian model showed good fit to the observed data. The proposed Bayesian model provides an approach for modeling non-stationary autocorrelation in a hierarchical modeling framework to estimate task means, standard deviations, quantiles, and parameter estimates for covariates that are less biased and have better performance characteristics than some of the contemporary methods. Published by Oxford University Press on behalf of the British Occupational Hygiene Society 2017.

Evaluating the constructability of NUDECK precast concrete deck panels for Kearney Bypass Project.

DOT National Transportation Integrated Search

2015-02-01

The first generation of precast concrete deck system, NUDECK, was implemented on the Skyline Bridge, : Omaha, NE in 2004. The second generation of NUDECK system was developed to further simplify the : system and improve its constructability and durab...

66. BIG MEADOWS. VIEW OF PARKING AREA AT THE GATED ...

Library of Congress Historic Buildings Survey, Historic Engineering Record, Historic Landscapes Survey

66. BIG MEADOWS. VIEW OF PARKING AREA AT THE GATED ENTRANCE TO RAPIDAN FIRE ROAD, THE ACCESS ROAD TO CAMP HOOVER. LOOKING SOUTH, MILE 51.3. - Skyline Drive, From Front Royal, VA to Rockfish Gap, VA , Luray, Page County, VA

2. VIEW OF PARK SIGNAGE AT FRONT ROYAL. SIGN SAYS: ...

Library of Congress Historic Buildings Survey, Historic Engineering Record, Historic Landscapes Survey

2. VIEW OF PARK SIGNAGE AT FRONT ROYAL. SIGN SAYS: "NORTH ENTRANCE SHENANDOAH NATIONAL PARK." LOCATED ON EXIT SIDE OF ROAD. LOOKING SOUTHWEST, MILE 0.0. - Skyline Drive, From Front Royal, VA to Rockfish Gap, VA , Luray, Page County, VA

100. Catalog HHistory 1, C.C.C., 34 Landscaping, Negative No. P ...

Library of Congress Historic Buildings Survey, Historic Engineering Record, Historic Landscapes Survey

100. Catalog H-History 1, C.C.C., 34 Landscaping, Negative No. P 733c (Photographer and date unknown) SLOPE MAINTENANCE WORK BY CCC. - Skyline Drive, From Front Royal, VA to Rockfish Gap, VA , Luray, Page County, VA

99. Catalog HHistory 1, C.C.C., 23 Guard Rail Construction, Negative ...

Library of Congress Historic Buildings Survey, Historic Engineering Record, Historic Landscapes Survey

99. Catalog H-History 1, C.C.C., 23 Guard Rail Construction, Negative No. P455e (Photographer and date unknown) GUARD RAIL INSTALLATION. - Skyline Drive, From Front Royal, VA to Rockfish Gap, VA , Luray, Page County, VA

A Microsoft-Excel-based tool for running and critically appraising network meta-analyses--an overview and application of NetMetaXL.

PubMed

Brown, Stephen; Hutton, Brian; Clifford, Tammy; Coyle, Doug; Grima, Daniel; Wells, George; Cameron, Chris

2014-09-29

The use of network meta-analysis has increased dramatically in recent years. WinBUGS, a freely available Bayesian software package, has been the most widely used software package to conduct network meta-analyses. However, the learning curve for WinBUGS can be daunting, especially for new users. Furthermore, critical appraisal of network meta-analyses conducted in WinBUGS can be challenging given its limited data manipulation capabilities and the fact that generation of graphical output from network meta-analyses often relies on different software packages than the analyses themselves. We developed a freely available Microsoft-Excel-based tool called NetMetaXL, programmed in Visual Basic for Applications, which provides an interface for conducting a Bayesian network meta-analysis using WinBUGS from within Microsoft Excel. . This tool allows the user to easily prepare and enter data, set model assumptions, and run the network meta-analysis, with results being automatically displayed in an Excel spreadsheet. It also contains macros that use NetMetaXL's interface to generate evidence network diagrams, forest plots, league tables of pairwise comparisons, probability plots (rankograms), and inconsistency plots within Microsoft Excel. All figures generated are publication quality, thereby increasing the efficiency of knowledge transfer and manuscript preparation. We demonstrate the application of NetMetaXL using data from a network meta-analysis published previously which compares combined resynchronization and implantable defibrillator therapy in left ventricular dysfunction. We replicate results from the previous publication while demonstrating result summaries generated by the software. Use of the freely available NetMetaXL successfully demonstrated its ability to make running network meta-analyses more accessible to novice WinBUGS users by allowing analyses to be conducted entirely within Microsoft Excel. NetMetaXL also allows for more efficient and transparent critical appraisal of network meta-analyses, enhanced standardization of reporting, and integration with health economic evaluations which are frequently Excel-based.

A Microsoft-Excel-based tool for running and critically appraising network meta-analyses—an overview and application of NetMetaXL

PubMed Central

2014-01-01

Background The use of network meta-analysis has increased dramatically in recent years. WinBUGS, a freely available Bayesian software package, has been the most widely used software package to conduct network meta-analyses. However, the learning curve for WinBUGS can be daunting, especially for new users. Furthermore, critical appraisal of network meta-analyses conducted in WinBUGS can be challenging given its limited data manipulation capabilities and the fact that generation of graphical output from network meta-analyses often relies on different software packages than the analyses themselves. Methods We developed a freely available Microsoft-Excel-based tool called NetMetaXL, programmed in Visual Basic for Applications, which provides an interface for conducting a Bayesian network meta-analysis using WinBUGS from within Microsoft Excel. . This tool allows the user to easily prepare and enter data, set model assumptions, and run the network meta-analysis, with results being automatically displayed in an Excel spreadsheet. It also contains macros that use NetMetaXL’s interface to generate evidence network diagrams, forest plots, league tables of pairwise comparisons, probability plots (rankograms), and inconsistency plots within Microsoft Excel. All figures generated are publication quality, thereby increasing the efficiency of knowledge transfer and manuscript preparation. Results We demonstrate the application of NetMetaXL using data from a network meta-analysis published previously which compares combined resynchronization and implantable defibrillator therapy in left ventricular dysfunction. We replicate results from the previous publication while demonstrating result summaries generated by the software. Conclusions Use of the freely available NetMetaXL successfully demonstrated its ability to make running network meta-analyses more accessible to novice WinBUGS users by allowing analyses to be conducted entirely within Microsoft Excel. NetMetaXL also allows for more efficient and transparent critical appraisal of network meta-analyses, enhanced standardization of reporting, and integration with health economic evaluations which are frequently Excel-based. PMID:25267416

10. Detail of map showing Battery Davis and Panama Gun ...

Library of Congress Historic Buildings Survey, Historic Engineering Record, Historic Landscapes Survey

10. Detail of map showing Battery Davis and Panama Gun Mounts at right, by U.S. Engineering Office, San Francisco, California, August 5, 1934. - Fort Funston, Panama Mounts for 155mm Guns, Skyline Boulevard & Great Highway, San Francisco, San Francisco County, CA

5. VIEW LOOKING NORTHEAST INTO CENTRAL COURTYARD OF TECHWOOD DORMITORY, ...

Library of Congress Historic Buildings Survey, Historic Engineering Record, Historic Landscapes Survey

5. VIEW LOOKING NORTHEAST INTO CENTRAL COURTYARD OF TECHWOOD DORMITORY, SHOWING WEST FRONT OF CENTER WING AND PART OF SOUTH SIDE OF NORTH WING. MIDTOWN SKYLINE VISIBLE IN BACKGROUND. - Techwood Homes, McDaniel Dormitory, 581-587 Techwood Drive, Atlanta, Fulton County, GA

Skyline logging productivity under alternative harvesting prescriptions and levels of utilization in larch-fir stands

Treesearch

Rulon B. Gardner

1980-01-01

Larch-fir stands in northwest Montana were experimentally logged to determine the influence of increasingly intensive levels of utilization upon rates of yarding production, under three different silvicultural prescriptions. Variables influencing rate of production were also identified.

Reliability modelling and analysis of a multi-state element based on a dynamic Bayesian network

PubMed Central

Xu, Tingxue; Gu, Junyuan; Dong, Qi; Fu, Linyu

2018-01-01

This paper presents a quantitative reliability modelling and analysis method for multi-state elements based on a combination of the Markov process and a dynamic Bayesian network (DBN), taking perfect repair, imperfect repair and condition-based maintenance (CBM) into consideration. The Markov models of elements without repair and under CBM are established, and an absorbing set is introduced to determine the reliability of the repairable element. According to the state-transition relations between the states determined by the Markov process, a DBN model is built. In addition, its parameters for series and parallel systems, namely, conditional probability tables, can be calculated by referring to the conditional degradation probabilities. Finally, the power of a control unit in a failure model is used as an example. A dynamic fault tree (DFT) is translated into a Bayesian network model, and subsequently extended to a DBN. The results show the state probabilities of an element and the system without repair, with perfect and imperfect repair, and under CBM, with an absorbing set plotted by differential equations and verified. Through referring forward, the reliability value of the control unit is determined in different kinds of modes. Finally, weak nodes are noted in the control unit. PMID:29765629

Iterative Assessment of Statistically-Oriented and Standard Algorithms for Determining Muscle Onset with Intramuscular Electromyography.

PubMed

Tenan, Matthew S; Tweedell, Andrew J; Haynes, Courtney A

2017-12-01

The onset of muscle activity, as measured by electromyography (EMG), is a commonly applied metric in biomechanics. Intramuscular EMG is often used to examine deep musculature and there are currently no studies examining the effectiveness of algorithms for intramuscular EMG onset. The present study examines standard surface EMG onset algorithms (linear envelope, Teager-Kaiser Energy Operator, and sample entropy) and novel algorithms (time series mean-variance analysis, sequential/batch processing with parametric and nonparametric methods, and Bayesian changepoint analysis). Thirteen male and 5 female subjects had intramuscular EMG collected during isolated biceps brachii and vastus lateralis contractions, resulting in 103 trials. EMG onset was visually determined twice by 3 blinded reviewers. Since the reliability of visual onset was high (ICC (1,1) : 0.92), the mean of the 6 visual assessments was contrasted with the algorithmic approaches. Poorly performing algorithms were stepwise eliminated via (1) root mean square error analysis, (2) algorithm failure to identify onset/premature onset, (3) linear regression analysis, and (4) Bland-Altman plots. The top performing algorithms were all based on Bayesian changepoint analysis of rectified EMG and were statistically indistinguishable from visual analysis. Bayesian changepoint analysis has the potential to produce more reliable, accurate, and objective intramuscular EMG onset results than standard methodologies.

75 FR 5289 - Defense Health Board (DHB) Meeting

Federal Register 2010, 2011, 2012, 2013, 2014

2010-02-02

... DEPARTMENT OF DEFENSE Office of the Secretary Defense Health Board (DHB) Meeting AGENCY... announces that the Defense Health Board (DHB or Board) will meet on March 1-2, 2010, to address and.... Feeks, Executive Secretary, Defense Health Board, Five Skyline Place, 5111 Leesburg Pike, Suite 810...

3 CFR 8410 - Proclamation 8410 of September 3, 2009. National Days of Prayer and Remembrance, 2009

Code of Federal Regulations, 2010 CFR

2010-01-01

... struck the skyline of New York City, the structure of the Pentagon, and the grass of Pennsylvania. In the... world. They have left the safety of home so that our Nation might be more secure. They have endured...

75 FR 25198 - Intermountain Region, Boise National Forest, Emmett Ranger District; Idaho Scriver Creek...

Federal Register 2010, 2011, 2012, 2013, 2014

2010-05-07

... commercial and noncommercial vegetation management and road system modifications and maintenance. DATES... stands and old forest habitat; (2) improve watershed conditions and reduce road- related impacts to... commercial timber harvest on about 3,265 acres utilizing tractor/off-road jammer (1,124 acres), skyline (926...

Economics of hardwood silviculture using skyline and conventional logging

Treesearch

John E. Baumgras; Gary W. Miller; Chris B. LeDoux

1995-01-01

Managing Appalachian hardwood forests to satisfy the growing and diverse demands on this resource will require alternatives to traditional silvicultural methods and harvesting systems. Determining the relative economic efficiency of these alternative methods and systems with respect to harvest cash flows is essential. The effects of silvicultural methods and roundwood...

Block 3. Central view of Block 3 observed from the ...

Library of Congress Historic Buildings Survey, Historic Engineering Record, Historic Landscapes Survey

Block 3. Central view of Block 3 observed from the west to the east. This photograph reveals the alignment of trees within the central path of the park. In addition, this photograph exposes broken bricks aligning tree beds - Skyline Park, 1500-1800 Arapaho Street, Denver, Denver County, CO

SIMYAR: a cable-yarding simulation model.

Treesearch

R.J. McGaughey; R.H. Twito

1987-01-01

A skyline-logging simulation model designed to help planners evaluate potential yarding options and alternative harvest plans is presented. The model, called SIMYAR, uses information about the timber stand, yarding equipment, and unit geometry to estimate yarding co stand productivity for a particular operation. The costs of felling, bucking, loading, and hauling are...

Balloon logging with the inverted skyline

NASA Technical Reports Server (NTRS)

Mosher, C. F.

1975-01-01

There is a gap in aerial logging techniques that has to be filled. The need for a simple, safe, sizeable system has to be developed before aerial logging will become effective and accepted in the logging industry. This paper presents such a system designed on simple principles with realistic cost and ecological benefits.

97. Catalog B, Higher Plants, 200 2 American Chestnut Tree, ...

Library of Congress Historic Buildings Survey, Historic Engineering Record, Historic Landscapes Survey

97. Catalog B, Higher Plants, 200 2 American Chestnut Tree, Negative No. 6032 (Photographer and date unknown) THIS GHOST FOREST OF BLIGHTED CHESTNUTS ONCE STOOD APPROXIMATELY AT THE LOCATION OF THE BYRD VISITOR CENTER. - Skyline Drive, From Front Royal, VA to Rockfish Gap, VA , Luray, Page County, VA

A Spoonful of Sugar

ERIC Educational Resources Information Center

Fedore, Heidi

2005-01-01

In 2002, with pressure on students and educators mounting regarding performance on standardized tests, the author, who is an assistant principal at Skyline High School in Issaquah, Washington, and some staff members decided to have a little fun in the midst of the preparation for the state's high-stakes test, the Washington Assessment of Student…

PHOTOGRAPH NUMBERS 40, 39, 38 FORM A 189 DEGREE PANORAMA ...

Library of Congress Historic Buildings Survey, Historic Engineering Record, Historic Landscapes Survey

PHOTOGRAPH NUMBERS 40, 39, 38 FORM A 189 DEGREE PANORAMA FROM LEFT TO RIGHT. PHOTOGRAPH NUMBER 38 LOOKING NORTHEAST TO SKYLINE FROM ROOF OF POLSON BUILDING; PHOTOGRAPH NUMBER 39 VIEW NORTH; PHOTOGRAPH NUMBER 40 VIEW NORTHWEST. - Alaskan Way Viaduct and Battery Street Tunnel, Seattle, King County, WA

77 FR 9624 - Narrow Woven Ribbons With Woven Selvedge From Taiwan: Rescission, in Part, of Antidumping Duty...

Federal Register 2010, 2011, 2012, 2013, 2014

2012-02-17

...) Multicolor Inc.; (7) Novelty Handicrafts Co., Ltd.; (8) Pacific Imports; (9) Papillon Ribbon & Bow (Canada... Lion Ribbon Company, Inc., for the following companies: (1) Apex Ribbon; (2) Apex Trimmings; (3) FinerRibbon.com ; (4) Hsien Chan Enterprise Co., Ltd.; (5) Hubschercorp; (6) Intercontinental Skyline; (7...

Nutrient losses from timber harvesting in a larch/ Douglas-fir forest

Treesearch

Nellie M. Stark

1979-01-01

Nutrient levels as a result of experimental clearcutting, shelterwood cutting, and group selection cutting - each with three levels of harvesting intensity - were studied in a larchfir forest in northwest Montana, experimentally logged with a skyline system. None of the treatments altered nutrient levels in an intermittent stream, nor were excessive amounts of...

Trends in streamflow and suspended sediment after logging, North Fork Caspar Creek

Treesearch

Jack Lewis; Elizabeth T. Keppeler

2007-01-01

Streamflow and suspended sediment were intensively monitored at fourteen gaging stations before and after logging a second-growth redwood (Sequoia sempervirens) forest. About 50 percent of the watershed was harvested, primarily by clear-cutting with skyline-cable systems. New road construction and tractor skidding were restricted to gently-sloping...

102. Catalog HHistory 1, C.C.C., 34 Landscaping, Negative No. 6040a ...

Library of Congress Historic Buildings Survey, Historic Engineering Record, Historic Landscapes Survey

102. Catalog H-History 1, C.C.C., 34 Landscaping, Negative No. 6040a (Photographer and date unknown) BEAUTIFICATION PROGRAM STARTED AS SOON AS GRADING ALONG THE DRIVE WAS COMPLETED. CCC CAMP 3 SHOWN PLANTING LAUREL. - Skyline Drive, From Front Royal, VA to Rockfish Gap, VA , Luray, Page County, VA

Smith Assists in Superstorm Sandy Relief Efforts | Poster

Cancer.gov

By Cathy McClintock, Guest Writer It should have been routine by now for a 30-year volunteer firefighter/ emergency medical technician from Thurmont, Md., but it wasn’t. That first night, as Ross Smith, IT security, looked across the Hudson River from Jersey City, N.J., he saw an unusually dark New York skyline.

The Automatic Recognition of the Abnormal Sky-subtraction Spectra Based on Hadoop

NASA Astrophysics Data System (ADS)

An, An; Pan, Jingchang

2017-10-01

The skylines, superimposing on the target spectrum as a main noise, If the spectrum still contains a large number of high strength skylight residuals after sky-subtraction processing, it will not be conducive to the follow-up analysis of the target spectrum. At the same time, the LAMOST can observe a quantity of spectroscopic data in every night. We need an efficient platform to proceed the recognition of the larger numbers of abnormal sky-subtraction spectra quickly. Hadoop, as a distributed parallel data computing platform, can deal with large amounts of data effectively. In this paper, we conduct the continuum normalization firstly and then a simple and effective method will be presented to automatic recognize the abnormal sky-subtraction spectra based on Hadoop platform. Obtain through the experiment, the Hadoop platform can implement the recognition with more speed and efficiency, and the simple method can recognize the abnormal sky-subtraction spectra and find the abnormal skyline positions of different residual strength effectively, can be applied to the automatic detection of abnormal sky-subtraction of large number of spectra.

Estimating the Effective Sample Size of Tree Topologies from Bayesian Phylogenetic Analyses

PubMed Central

Lanfear, Robert; Hua, Xia; Warren, Dan L.

2016-01-01

Bayesian phylogenetic analyses estimate posterior distributions of phylogenetic tree topologies and other parameters using Markov chain Monte Carlo (MCMC) methods. Before making inferences from these distributions, it is important to assess their adequacy. To this end, the effective sample size (ESS) estimates how many truly independent samples of a given parameter the output of the MCMC represents. The ESS of a parameter is frequently much lower than the number of samples taken from the MCMC because sequential samples from the chain can be non-independent due to autocorrelation. Typically, phylogeneticists use a rule of thumb that the ESS of all parameters should be greater than 200. However, we have no method to calculate an ESS of tree topology samples, despite the fact that the tree topology is often the parameter of primary interest and is almost always central to the estimation of other parameters. That is, we lack a method to determine whether we have adequately sampled one of the most important parameters in our analyses. In this study, we address this problem by developing methods to estimate the ESS for tree topologies. We combine these methods with two new diagnostic plots for assessing posterior samples of tree topologies, and compare their performance on simulated and empirical data sets. Combined, the methods we present provide new ways to assess the mixing and convergence of phylogenetic tree topologies in Bayesian MCMC analyses. PMID:27435794

Bayesian Nonparametric Ordination for the Analysis of Microbial Communities.

PubMed

Ren, Boyu; Bacallado, Sergio; Favaro, Stefano; Holmes, Susan; Trippa, Lorenzo

2017-01-01

Human microbiome studies use sequencing technologies to measure the abundance of bacterial species or Operational Taxonomic Units (OTUs) in samples of biological material. Typically the data are organized in contingency tables with OTU counts across heterogeneous biological samples. In the microbial ecology community, ordination methods are frequently used to investigate latent factors or clusters that capture and describe variations of OTU counts across biological samples. It remains important to evaluate how uncertainty in estimates of each biological sample's microbial distribution propagates to ordination analyses, including visualization of clusters and projections of biological samples on low dimensional spaces. We propose a Bayesian analysis for dependent distributions to endow frequently used ordinations with estimates of uncertainty. A Bayesian nonparametric prior for dependent normalized random measures is constructed, which is marginally equivalent to the normalized generalized Gamma process, a well-known prior for nonparametric analyses. In our prior, the dependence and similarity between microbial distributions is represented by latent factors that concentrate in a low dimensional space. We use a shrinkage prior to tune the dimensionality of the latent factors. The resulting posterior samples of model parameters can be used to evaluate uncertainty in analyses routinely applied in microbiome studies. Specifically, by combining them with multivariate data analysis techniques we can visualize credible regions in ecological ordination plots. The characteristics of the proposed model are illustrated through a simulation study and applications in two microbiome datasets.

Characterizing Giant Exoplanets through Multiwavelength Transit Observations: KELT-9b

NASA Astrophysics Data System (ADS)

Gardner, Cristilyn N.; Cole, Jackson L.; Garver, Bethany R.; Jarka, Kyla L.; Kar, Aman; McGough, Aylin M.; PeQueen, David J.; Rivera, Daniel I.; Kasper, David; Jang-Condell, Hannah; Kobulnicky, Henry A.; Dale, Daniel A.

2018-01-01

Multiwavelength observations of host stellar light scattered through an exoplanet's atmosphere during a transit characterizes exoplanetary parameters. Using the Wyoming Infrared Observatory 2.3-meter telescope, we observed primary transits of KELT-9b in the ugriz Sloan filters. We present an analysis of the phase-folded transit observations of KELT-9b using a Bayesian statistical approach. By plotting the transit depth as a function of wavelength, our preliminary results are indicative of scattering in the atmosphere surrounding KELT-9b. This work is supported by the National Science Foundation under REU grant AST 1560461 and PAARE grant AST 1559559.

A Computational Observer For Performing Contrast-Detail Analysis Of Ultrasound Images

NASA Astrophysics Data System (ADS)

Lopez, H.; Loew, M. H.

1988-06-01

Contrast-Detail (C/D) analysis allows the quantitative determination of an imaging system's ability to display a range of varying-size targets as a function of contrast. Using this technique, a contrast-detail plot is obtained which can, in theory, be used to compare image quality from one imaging system to another. The C/D plot, however, is usually obtained by using data from human observer readings. We have shown earlier(7) that the performance of human observers in the task of threshold detection of simulated lesions embedded in random ultrasound noise is highly inaccurate and non-reproducible for untrained observers. We present an objective, computational method for the determination of the C/D curve for ultrasound images. This method utilizes digital images of the C/D phantom developed at CDRH, and lesion-detection algorithms that simulate the Bayesian approach using the likelihood function for an ideal observer. We present the results of this method, and discuss the relationship to the human observer and to the comparability of image quality between systems.

Linear models for airborne-laser-scanning-based operational forest inventory with small field sample size and highly correlated LiDAR data

USGS Publications Warehouse

Junttila, Virpi; Kauranne, Tuomo; Finley, Andrew O.; Bradford, John B.

2015-01-01

Modern operational forest inventory often uses remotely sensed data that cover the whole inventory area to produce spatially explicit estimates of forest properties through statistical models. The data obtained by airborne light detection and ranging (LiDAR) correlate well with many forest inventory variables, such as the tree height, the timber volume, and the biomass. To construct an accurate model over thousands of hectares, LiDAR data must be supplemented with several hundred field sample measurements of forest inventory variables. This can be costly and time consuming. Different LiDAR-data-based and spatial-data-based sampling designs can reduce the number of field sample plots needed. However, problems arising from the features of the LiDAR data, such as a large number of predictors compared with the sample size (overfitting) or a strong correlation among predictors (multicollinearity), may decrease the accuracy and precision of the estimates and predictions. To overcome these problems, a Bayesian linear model with the singular value decomposition of predictors, combined with regularization, is proposed. The model performance in predicting different forest inventory variables is verified in ten inventory areas from two continents, where the number of field sample plots is reduced using different sampling designs. The results show that, with an appropriate field plot selection strategy and the proposed linear model, the total relative error of the predicted forest inventory variables is only 5%–15% larger using 50 field sample plots than the error of a linear model estimated with several hundred field sample plots when we sum up the error due to both the model noise variance and the model’s lack of fit.

Model for Evaluating the Cost Consequences of Deferring New System Acquisition Through Upgrades

DTIC Science & Technology

1999-07-01

Analysis & Evaluation The Pentagon Washington, DC 20301 Attn: Mr. Eric Coulter, Director Projection Forces Division, Room 2E314 Lt Col Kathleen Conley...1034 Office of the Air National Guard ANG/AQM 5109 Leesburg Pike Skyline VI, Suite 302A Falls Church, VA 22041-3201 Attn: Col Brent Marler 1 Lt Col

Installation and use of epoxy-grouted rock anchors for skyline logging in southeast Alaska.

Treesearch

W.L. Schroeder; D.N. Swanston

1992-01-01

Field tests of the load-carrying capacity of epoxy-grouted rock anchors in poor quality bedrock on Wrangel Island in southeast Alaska demonstrated the effectiveness of rock anchors as substitutes for stump anchors for logging system guylines. Ultimate capacity depends mainly on rock hardness or strength and length of the imbedded anchor.

An earth anchor system: installation and design guide.

Treesearch

R.L. Copstead; D.D. Studier

1990-01-01

A system for anchoring the guylines and skylines of cable yarding equipment is presented. A description of three types of tipping plate anchors is given. Descriptions of the installation equipment and methods specific to each type are given. Procedures for determining the correct number of anchors to install are included, as are guidelines for installing the anchors so...

Production and cost of a live skyline cable yarder tested in Appalachia

Treesearch

Edward L. Fisher; Harry G. Gibson; Cleveland J. Biller

1980-01-01

Logging systems that are profitable and environmentally acceptable are needed in Appalachian hardwood forests. Small, mobile cable yarders show promise in meeting both economic and environmental objectives. One such yarder, the Ecologger, was tested on the Jefferson National Forest near Marion, Virginia. Production rates and costs are presented for the system along...

103. Catalog HHistory 1, C.C.C., 58 Landscaping, Negative No. 870 ...

Library of Congress Historic Buildings Survey, Historic Engineering Record, Historic Landscapes Survey

103. Catalog H-History 1, C.C.C., 58 Landscaping, Negative No. 870 10 ca. 1936 PROPAGATION AND PLANTING. ROOTED PLANTS TRANSPLANTED FROM HOT BEDS TO CANS TO SHADED BEDS IN PREPARATION FOR PLANTING ON ROAD SLOPES. NURSERY AT NORTH ENTRANCE. - Skyline Drive, From Front Royal, VA to Rockfish Gap, VA , Luray, Page County, VA

Influence of geology and human activity on the genetic structure and demography of the Oriental fire-bellied toad (Bombina orientalis).

PubMed

Fong, Jonathan J; Li, Pi-Peng; Yang, Bao-Tian; Zhou, Zheng-Yan; Leaché, Adam D; Min, Mi-Sook; Waldman, Bruce

2016-04-01

The Oriental fire-bellied toad (Bombina orientalis) is a commonly used study organism, but knowledge of its evolutionary history is incomplete. We analyze sequence data from four genetic markers (mtDNA genes encoding cytochrome c oxidase subunit I, cytochrome b, and 12S-16S rRNA; nuDNA gene encoding recombination activating gene 2) from 188 individuals across its range in Northeast Asia to elucidate phylogeographic patterns and to identify the historic events that shaped its evolutionary history. Although morphologically similar across its range, B. orientalis exhibits phylogeographic structure, which we infer was shaped by geologic, climatic, and anthropogenic events. Phylogenetic and divergence-dating analyses recover four genetically distinct groups of B. orientalis: Lineage 1-Shandong Province and Beijing (China); Lineage 2-Bukhan Mountain (Korea); Lineage 3-Russia, Northeast China, and northern South Korea; and Lineage 4-South Korea. Lineage 2 was previously unknown. Additionally, we discover an area of secondary contact on the Korean Peninsula, and infer a single dispersal event as the origin of the insular Jeju population. Skyline plots estimate different population histories for the four lineages: Lineages 1 and 2 experienced population decreases, Lineage 3 remained stable, while Lineage 4 experienced a sharp increase during the Holocene. The timing of the population expansion of Lineage 4 coincides with the advent of rice cultivation, which may have facilitated the increase in population size by providing additional breeding habitat. Copyright © 2016 Elsevier Inc. All rights reserved.

Cost and production analysis of the Bitterroot Miniyarder on an Appalachian hardwood site

Treesearch

John E. Baumgras; Penn A. Peters; Penn A. Peters

1985-01-01

An 18-horsepower skyline yarder was studied on a steep slope clearcut, yarding small hardwood trees uphill for fuelwood. Yarding cycle characteristics sampled include: total cycle time including delays, 5.20 minutes; yarding distance, 208 feet (350 feet maximum); turn volume, 11.6 cubic feet (24 cubic feet maximum); pieces per turn, 2.3. Cost analysis shows yarding...

Predicting the payload capability of cable logging systems including the effect of partial suspension

Treesearch

Gary D. Falk

1981-01-01

A systematic procedure for predicting the payload capability of running, live, and standing skylines is presented. Three hand-held calculator programs are used to predict payload capability that includes the effect of partial suspension. The programs allow for predictions for downhill yarding and for yarding away from the yarder. The equations and basic principles...

A second look at cable logging in the Appalachians

Treesearch

Harry G. Gibson; Cleveland J. Biller

1975-01-01

Cable logging, once used extensively in the Appalachians, is being re-examined to see if smaller, more mobile systems can help solve some of the timber-managment problems on steep slopes. A small Austrian skyline was tested in West Virginia to determine its feasibility for harvesting enstern hardwoods. The short-term test included both selection and clearcut harvesting...

Gods of the City? Reflecting on City Building Games as an Early Introduction to Urban Systems

ERIC Educational Resources Information Center

Bereitschaft, Bradley

2016-01-01

For millions of gamers and students alike, city building games (CBGs) like SimCity and the more recent Cities: Skylines present a compelling initial introduction to the world of urban planning and development. As such, these games have great potential to shape players' understanding and expectations of real urban patterns and processes. In this…

DNA breaks and end resection measured genome-wide by end sequencing | Center for Cancer Research

Cancer.gov

About the Cover The cover depicts a ribbon of DNA portrayed as a city skyline. The central gap in the landscape localizes to the precise site of the DNA break. The features surrounding the break denote the processing of DNA-end structures (end-resection) emanating from the break location. Cover artwork by Ethan Tyler, NIH. Abstract

The California Community College Baccalaureate Degree Pilot Program: A Case Study of Baccalaureate Degree Implementation

ERIC Educational Resources Information Center

Yeager, Susan Cadavid

2017-01-01

This case study examined the implementation of a baccalaureate degree at Skyline Community College--one of the 15 California community colleges authorized to offer baccalaureate degrees established as part of a pilot program enacted by the California Legislature via Senate Bill 850 (2014). The study explored the policies and procedures in place at…

High gain solar photovoltaics

NASA Astrophysics Data System (ADS)

MacDonald, B.; Finot, M.; Heiken, B.; Trowbridge, T.; Ackler, H.; Leonard, L.; Johnson, E.; Chang, B.; Keating, T.

2009-08-01

Skyline Solar Inc. has developed a novel silicon-based PV system to simultaneously reduce energy cost and improve scalability of solar energy. The system achieves high gain through a combination of high capacity factor and optical concentration. The design approach drives innovation not only into the details of the system hardware, but also into manufacturing and deployment-related costs and bottlenecks. The result of this philosophy is a modular PV system whose manufacturing strategy relies only on currently existing silicon solar cell, module, reflector and aluminum parts supply chains, as well as turnkey PV module production lines and metal fabrication industries that already exist at enormous scale. Furthermore, with a high gain system design, the generating capacity of all components is multiplied, leading to a rapidly scalable system. The product design and commercialization strategy cooperate synergistically to promise dramatically lower LCOE with substantially lower risk relative to materials-intensive innovations. In this paper, we will present the key design aspects of Skyline's system, including aspects of the optical, mechanical and thermal components, revealing the ease of scalability, low cost and high performance. Additionally, we will present performance and reliability results on modules and the system, using ASTM and UL/IEC methodologies.

Adaptive sequential Bayesian classification using Page's test

NASA Astrophysics Data System (ADS)

Lynch, Robert S., Jr.; Willett, Peter K.

2002-03-01

In this paper, the previously introduced Mean-Field Bayesian Data Reduction Algorithm is extended for adaptive sequential hypothesis testing utilizing Page's test. In general, Page's test is well understood as a method of detecting a permanent change in distribution associated with a sequence of observations. However, the relationship between detecting a change in distribution utilizing Page's test with that of classification and feature fusion is not well understood. Thus, the contribution of this work is based on developing a method of classifying an unlabeled vector of fused features (i.e., detect a change to an active statistical state) as quickly as possible given an acceptable mean time between false alerts. In this case, the developed classification test can be thought of as equivalent to performing a sequential probability ratio test repeatedly until a class is decided, with the lower log-threshold of each test being set to zero and the upper log-threshold being determined by the expected distance between false alerts. It is of interest to estimate the delay (or, related stopping time) to a classification decision (the number of time samples it takes to classify the target), and the mean time between false alerts, as a function of feature selection and fusion by the Mean-Field Bayesian Data Reduction Algorithm. Results are demonstrated by plotting the delay to declaring the target class versus the mean time between false alerts, and are shown using both different numbers of simulated training data and different numbers of relevant features for each class.

Cyber-T web server: differential analysis of high-throughput data.

PubMed

Kayala, Matthew A; Baldi, Pierre

2012-07-01

The Bayesian regularization method for high-throughput differential analysis, described in Baldi and Long (A Bayesian framework for the analysis of microarray expression data: regularized t-test and statistical inferences of gene changes. Bioinformatics 2001: 17: 509-519) and implemented in the Cyber-T web server, is one of the most widely validated. Cyber-T implements a t-test using a Bayesian framework to compute a regularized variance of the measurements associated with each probe under each condition. This regularized estimate is derived by flexibly combining the empirical measurements with a prior, or background, derived from pooling measurements associated with probes in the same neighborhood. This approach flexibly addresses problems associated with low replication levels and technology biases, not only for DNA microarrays, but also for other technologies, such as protein arrays, quantitative mass spectrometry and next-generation sequencing (RNA-seq). Here we present an update to the Cyber-T web server, incorporating several useful new additions and improvements. Several preprocessing data normalization options including logarithmic and (Variance Stabilizing Normalization) VSN transforms are included. To augment two-sample t-tests, a one-way analysis of variance is implemented. Several methods for multiple tests correction, including standard frequentist methods and a probabilistic mixture model treatment, are available. Diagnostic plots allow visual assessment of the results. The web server provides comprehensive documentation and example data sets. The Cyber-T web server, with R source code and data sets, is publicly available at http://cybert.ics.uci.edu/.

Upscaling of greenhouse gas emissions in upland forestry following clearfell

NASA Astrophysics Data System (ADS)

Toet, Sylvia; Keane, Ben; Yamulki, Sirwan; Blei, Emanuel; Gibson-Poole, Simon; Xenakis, Georgios; Perks, Mike; Morison, James; Ineson, Phil

2016-04-01

Data on greenhouse gas (GHG) emissions caused by forest management activities are limited. Management such as clearfelling may, however, have major impacts on the GHG balance of forests through effects of soil disturbance, increased water table, and brash and root inputs. Besides carbon dioxide (CO2), the biogenic GHGs nitrous oxide (N2O) and methane (CH4) may also contribute to GHG emissions from managed forests. Accurate flux estimates of all three GHGs are therefore necessary, but, since GHG emissions usually show large spatial and temporal variability, in particular CH4 and N2O fluxes, high-frequency GHG flux measurements and better understanding of their controls are central to improve process-based flux models and GHG budgets at multiple scales. In this study, we determined CO2, CH4 and N2O emissions following felling in a mature Sitka spruce (Picea sitchensis) stand in an upland forest in northern England. High-frequency measurements were made along a transect using a novel, automated GHG chamber flux system ('SkyLine') developed at the University of York. The replicated, linear experiment aimed (1) to quantify GHG emissions from three main topographical features at the clearfell site, i.e. the ridges on which trees had been planted, the hollows in between and the drainage ditches, and (2) to determine the effects of the green-needle component of the discarded brash. We also measured abiotic soil and climatic factors alongside the 'SkyLine' GHG flux measurements to identify drivers of the observed GHG emissions. All three topographic features were overall sources of GHG emissions (in CO2 equivalents), and, although drainage ditches are often not included in studies, GHG emissions per unit area were highest from ditches, followed by ridges and lowest in hollows. The CO2 emissions were most important in the GHG balance of ridges and hollows, but CH4 emissions were very high from the drainage ditches, contributing to over 50% of their overall net GHG emissions. Ridges usually emitted N2O, whilst N2O emissions from hollows and ditches were very low. As much as 25% of the total GHG flux resulted from large intermittent emissions from the ditches following rainfall. Addition of green needles from the brash immediately increased soil respiration and reduced CH4 emission in comparison to controls. To upscale our high-frequency 'SkyLine' GHG flux measurements at the different topographic features to the field scale, we collected high resolution imagery from unmanned aerial vehicle (UAV) flights. We will compare results using this upscaling technique to GHG emissions simultaneously measured by eddy covariance with the 'SkyLine' system in the predominant footprint. This detailed knowledge of the spatial and temporal distribution of GHG emissions in an upland forest after felling and their drivers, and development of robust upscaling techniques can provide important tools to improve GHG flux models and to design appropriate management practices in upland forestry to mitigate GHG emissions following clearfell.

Evaluation of a new inference method for estimating ammonia volatilisation from multiple agronomic plots

NASA Astrophysics Data System (ADS)

Loubet, Benjamin; Carozzi, Marco; Voylokov, Polina; Cohan, Jean-Pierre; Trochard, Robert; Génermont, Sophie

2018-06-01

Tropospheric ammonia (NH3) is a threat to the environment and human health and is mainly emitted by agriculture. Ammonia volatilisation following application of nitrogen in the field accounts for more than 40 % of the total NH3 emissions in France. This represents a major loss of nitrogen use efficiency which needs to be reduced by appropriate agricultural practices. In this study we evaluate a novel method to infer NH3 volatilisation from small agronomic plots consisting of multiple treatments with repetition. The method is based on the combination of a set of NH3 diffusion sensors exposed for durations of 3 h to 1 week and a short-range atmospheric dispersion model, used to retrieve the emissions from each plot. The method is evaluated by mimicking NH3 emissions from an ensemble of nine plots with a resistance analogue-compensation point-surface exchange scheme over a yearly meteorological database separated into 28-day periods. A multifactorial simulation scheme is used to test the effects of sensor numbers and heights, plot dimensions, source strengths, and background concentrations on the quality of the inference method. We further demonstrate by theoretical considerations in the case of an isolated plot that inferring emissions with diffusion sensors integrating over daily periods will always lead to underestimations due to correlations between emissions and atmospheric transfer. We evaluated these underestimations as -8 % ± 6 % of the emissions for a typical western European climate. For multiple plots, we find that this method would lead to median underestimations of -16 % with an interquartile [-8-22 %] for two treatments differing by a factor of up to 20 and a control treatment with no emissions. We further evaluate the methodology for varying background concentrations and NH3 emissions patterns and demonstrate the low sensitivity of the method to these factors. The method was also tested in a real case and proved to provide sound evaluations of NH3 losses from surface applied and incorporated slurry. We hence showed that this novel method should be robust and suitable for estimating NH3 emissions from agronomic plots. We believe that the method could be further improved by using Bayesian inference and inferring surface concentrations rather than surface fluxes. Validating against controlled source is also a remaining challenge.

Population Genetics of Overwintering Monarch Butterflies, Danaus plexippus (Linnaeus), from Central Mexico Inferred from Mitochondrial DNA and Microsatellite Markers

PubMed Central

Pfeiler, Edward; Nazario-Yepiz, Nestor O.; Pérez-Gálvez, Fernan; Chávez-Mora, Cristina Alejandra; Laclette, Mariana Ramírez Loustalot; Rendón-Salinas, Eduardo

2017-01-01

Abstract Population genetic variation and demographic history in Danaus plexippus (L.), from Mexico were assessed based on analyses of mitochondrial cytochrome c oxidase subunit I (COI; 658 bp) and subunit II (COII; 503 bp) gene segments and 7 microsatellite loci. The sample of 133 individuals included both migratory monarchs, mainly from 4 overwintering sites within the Monarch Butterfly Biosphere Reserve (MBBR) in central Mexico (states of Michoacán and México), and a nonmigratory population from Irapuato, Guanajuato. Haplotype (h) and nucleotide (π) diversities were relatively low, averaging 0.466 and 0.00073, respectively, for COI, and 0.629 and 0.00245 for COII. Analysis of molecular variance of the COI data set, which included additional GenBank sequences from a nonmigratory Costa Rican population, showed significant population structure between Mexican migratory monarchs and nonmigratory monarchs from both Mexico and Costa Rica, suggesting limited gene flow between the 2 behaviorally distinct groups. Interestingly, while the COI haplotype frequencies of the nonmigratory populations differed from the migratory, they were similar to each other, despite the great physical distance between them. Microsatellite analyses, however, suggested a lack of structure between the 2 groups, possibly owing to the number of significant deviations from Hardy–Weinberg equilibrium resulting from heterzoygote deficiencies found for most of the loci. Estimates of demographic history of the combined migratory MBBR monarch population, based on the mismatch distribution and Bayesian skyline analyses of the concatenated COI and COII data set (n = 89) suggested a population expansion dating to the late Pleistocene (~35000–40000 years before present) followed by a stable effective female population size (Nef) of about 6 million over the last 10000 years. PMID:28003372

Population Genetics of Overwintering Monarch Butterflies, Danaus plexippus (Linnaeus), from Central Mexico Inferred from Mitochondrial DNA and Microsatellite Markers.

PubMed

Pfeiler, Edward; Nazario-Yepiz, Nestor O; Pérez-Gálvez, Fernan; Chávez-Mora, Cristina Alejandra; Laclette, Mariana Ramírez Loustalot; Rendón-Salinas, Eduardo; Markow, Therese Ann

2017-03-01

Population genetic variation and demographic history in Danaus plexippus (L.), from Mexico were assessed based on analyses of mitochondrial cytochrome c oxidase subunit I (COI; 658 bp) and subunit II (COII; 503 bp) gene segments and 7 microsatellite loci. The sample of 133 individuals included both migratory monarchs, mainly from 4 overwintering sites within the Monarch Butterfly Biosphere Reserve (MBBR) in central Mexico (states of Michoacán and México), and a nonmigratory population from Irapuato, Guanajuato. Haplotype (h) and nucleotide (π) diversities were relatively low, averaging 0.466 and 0.00073, respectively, for COI, and 0.629 and 0.00245 for COII. Analysis of molecular variance of the COI data set, which included additional GenBank sequences from a nonmigratory Costa Rican population, showed significant population structure between Mexican migratory monarchs and nonmigratory monarchs from both Mexico and Costa Rica, suggesting limited gene flow between the 2 behaviorally distinct groups. Interestingly, while the COI haplotype frequencies of the nonmigratory populations differed from the migratory, they were similar to each other, despite the great physical distance between them. Microsatellite analyses, however, suggested a lack of structure between the 2 groups, possibly owing to the number of significant deviations from Hardy-Weinberg equilibrium resulting from heterzoygote deficiencies found for most of the loci. Estimates of demographic history of the combined migratory MBBR monarch population, based on the mismatch distribution and Bayesian skyline analyses of the concatenated COI and COII data set (n = 89) suggested a population expansion dating to the late Pleistocene (~35000-40000 years before present) followed by a stable effective female population size (Nef) of about 6 million over the last 10000 years. © The American Genetic Association 2016.

Predicting bunching costs for the Radio Horse 9 winch

Treesearch

Chris B. LeDoux; Bruce W. Kling; Patrice A. Harou; Patrice A. Harou

1987-01-01

Data from field studies and a prebunching cost simulator have been assembled and converted into a general equation that can be used to estimate the prebunching cost of the Radio Horse 9 winch. The methods can be used to estimate prebunching cost for bunching under the skyline corridor for swinging with cable systems, for bunching to skid trail edge to be picked up by a...

76 FR 76684 - Idaho: Tentative Approval of State Underground Storage Tank Program

Federal Register 2010, 2011, 2012, 2013, 2014

2011-12-08

.... Skyline, Suite B, Idaho Falls, ID 83402 from 10 a.m. to 12 p.m. and 1 p.m. to 4 p.m.; and 6. IDEQ Lewiston... ENVIRONMENTAL PROTECTION AGENCY 40 CFR Part 281 [EPA-R10-UST-2011-0896; FRL-9502-6] Idaho...). ACTION: Proposed rule. SUMMARY: The State of Idaho has applied for final approval of its Underground...

104. Catalog HHistory 1, C.C.C., 73 Picnic Furniture Construction, Negative ...

Library of Congress Historic Buildings Survey, Historic Engineering Record, Historic Landscapes Survey

104. Catalog H-History 1, C.C.C., 73 Picnic Furniture Construction, Negative No. 8821 ca. 1936 WOOD UTILIZATION. COMPLETED RUSTIC BENCH MADE BY CCC ENROLLEES AT CAMP NP-3 FOR USE AT PARKING OVERLOOKS AND PICNIC GROUNDS. NOTE SAW IN BACKGROUND USED FOR HALVING CHESTNUT. - Skyline Drive, From Front Royal, VA to Rockfish Gap, VA , Luray, Page County, VA

Stochastic modelling of the monthly average maximum and minimum temperature patterns in India 1981-2015

NASA Astrophysics Data System (ADS)

Narasimha Murthy, K. V.; Saravana, R.; Vijaya Kumar, K.

2018-04-01

The paper investigates the stochastic modelling and forecasting of monthly average maximum and minimum temperature patterns through suitable seasonal auto regressive integrated moving average (SARIMA) model for the period 1981-2015 in India. The variations and distributions of monthly maximum and minimum temperatures are analyzed through Box plots and cumulative distribution functions. The time series plot indicates that the maximum temperature series contain sharp peaks in almost all the years, while it is not true for the minimum temperature series, so both the series are modelled separately. The possible SARIMA model has been chosen based on observing autocorrelation function (ACF), partial autocorrelation function (PACF), and inverse autocorrelation function (IACF) of the logarithmic transformed temperature series. The SARIMA (1, 0, 0) × (0, 1, 1)12 model is selected for monthly average maximum and minimum temperature series based on minimum Bayesian information criteria. The model parameters are obtained using maximum-likelihood method with the help of standard error of residuals. The adequacy of the selected model is determined using correlation diagnostic checking through ACF, PACF, IACF, and p values of Ljung-Box test statistic of residuals and using normal diagnostic checking through the kernel and normal density curves of histogram and Q-Q plot. Finally, the forecasting of monthly maximum and minimum temperature patterns of India for the next 3 years has been noticed with the help of selected model.

A probabilistic model framework for evaluating year-to-year variation in crop productivity

NASA Astrophysics Data System (ADS)

Yokozawa, M.; Iizumi, T.; Tao, F.

2008-12-01

Most models describing the relation between crop productivity and weather condition have so far been focused on mean changes of crop yield. For keeping stable food supply against abnormal weather as well as climate change, evaluating the year-to-year variations in crop productivity rather than the mean changes is more essential. We here propose a new framework of probabilistic model based on Bayesian inference and Monte Carlo simulation. As an example, we firstly introduce a model on paddy rice production in Japan. It is called PRYSBI (Process- based Regional rice Yield Simulator with Bayesian Inference; Iizumi et al., 2008). The model structure is the same as that of SIMRIW, which was developed and used widely in Japan. The model includes three sub- models describing phenological development, biomass accumulation and maturing of rice crop. These processes are formulated to include response nature of rice plant to weather condition. This model inherently was developed to predict rice growth and yield at plot paddy scale. We applied it to evaluate the large scale rice production with keeping the same model structure. Alternatively, we assumed the parameters as stochastic variables. In order to let the model catch up actual yield at larger scale, model parameters were determined based on agricultural statistical data of each prefecture of Japan together with weather data averaged over the region. The posterior probability distribution functions (PDFs) of parameters included in the model were obtained using Bayesian inference. The MCMC (Markov Chain Monte Carlo) algorithm was conducted to numerically solve the Bayesian theorem. For evaluating the year-to-year changes in rice growth/yield under this framework, we firstly iterate simulations with set of parameter values sampled from the estimated posterior PDF of each parameter and then take the ensemble mean weighted with the posterior PDFs. We will also present another example for maize productivity in China. The framework proposed here provides us information on uncertainties, possibilities and limitations on future improvements in crop model as well.

Linking big models to big data: efficient ecosystem model calibration through Bayesian model emulation

NASA Astrophysics Data System (ADS)

Fer, I.; Kelly, R.; Andrews, T.; Dietze, M.; Richardson, A. D.

2016-12-01

Our ability to forecast ecosystems is limited by how well we parameterize ecosystem models. Direct measurements for all model parameters are not always possible and inverse estimation of these parameters through Bayesian methods is computationally costly. A solution to computational challenges of Bayesian calibration is to approximate the posterior probability surface using a Gaussian Process that emulates the complex process-based model. Here we report the integration of this method within an ecoinformatics toolbox, Predictive Ecosystem Analyzer (PEcAn), and its application with two ecosystem models: SIPNET and ED2.1. SIPNET is a simple model, allowing application of MCMC methods both to the model itself and to its emulator. We used both approaches to assimilate flux (CO2 and latent heat), soil respiration, and soil carbon data from Bartlett Experimental Forest. This comparison showed that emulator is reliable in terms of convergence to the posterior distribution. A 10000-iteration MCMC analysis with SIPNET itself required more than two orders of magnitude greater computation time than an MCMC run of same length with its emulator. This difference would be greater for a more computationally demanding model. Validation of the emulator-calibrated SIPNET against both the assimilated data and out-of-sample data showed improved fit and reduced uncertainty around model predictions. We next applied the validated emulator method to the ED2, whose complexity precludes standard Bayesian data assimilation. We used the ED2 emulator to assimilate demographic data from a network of inventory plots. For validation of the calibrated ED2, we compared the model to results from Empirical Succession Mapping (ESM), a novel synthesis of successional patterns in Forest Inventory and Analysis data. Our results revealed that while the pre-assimilation ED2 formulation cannot capture the emergent demographic patterns from ESM analysis, constrained model parameters controlling demographic processes increased their agreement considerably.

Bayesian population receptive field modelling.

PubMed

Zeidman, Peter; Silson, Edward Harry; Schwarzkopf, Dietrich Samuel; Baker, Chris Ian; Penny, Will

2017-09-08

We introduce a probabilistic (Bayesian) framework and associated software toolbox for mapping population receptive fields (pRFs) based on fMRI data. This generic approach is intended to work with stimuli of any dimension and is demonstrated and validated in the context of 2D retinotopic mapping. The framework enables the experimenter to specify generative (encoding) models of fMRI timeseries, in which experimental stimuli enter a pRF model of neural activity, which in turns drives a nonlinear model of neurovascular coupling and Blood Oxygenation Level Dependent (BOLD) response. The neuronal and haemodynamic parameters are estimated together on a voxel-by-voxel or region-of-interest basis using a Bayesian estimation algorithm (variational Laplace). This offers several novel contributions to receptive field modelling. The variance/covariance of parameters are estimated, enabling receptive fields to be plotted while properly representing uncertainty about pRF size and location. Variability in the haemodynamic response across the brain is accounted for. Furthermore, the framework introduces formal hypothesis testing to pRF analysis, enabling competing models to be evaluated based on their log model evidence (approximated by the variational free energy), which represents the optimal tradeoff between accuracy and complexity. Using simulations and empirical data, we found that parameters typically used to represent pRF size and neuronal scaling are strongly correlated, which is taken into account by the Bayesian methods we describe when making inferences. We used the framework to compare the evidence for six variants of pRF model using 7 T functional MRI data and we found a circular Difference of Gaussians (DoG) model to be the best explanation for our data overall. We hope this framework will prove useful for mapping stimulus spaces with any number of dimensions onto the anatomy of the brain. Copyright © 2017 The Authors. Published by Elsevier Inc. All rights reserved.

On compensation of mismatched recording conditions in the Bayesian approach for forensic automatic speaker recognition.

PubMed

Botti, F; Alexander, A; Drygajlo, A

2004-12-02

This paper deals with a procedure to compensate for mismatched recording conditions in forensic speaker recognition, using a statistical score normalization. Bayesian interpretation of the evidence in forensic automatic speaker recognition depends on three sets of recordings in order to perform forensic casework: reference (R) and control (C) recordings of the suspect, and a potential population database (P), as well as a questioned recording (QR) . The requirement of similar recording conditions between suspect control database (C) and the questioned recording (QR) is often not satisfied in real forensic cases. The aim of this paper is to investigate a procedure of normalization of scores, which is based on an adaptation of the Test-normalization (T-norm) [2] technique used in the speaker verification domain, to compensate for the mismatch. Polyphone IPSC-02 database and ASPIC (an automatic speaker recognition system developed by EPFL and IPS-UNIL in Lausanne, Switzerland) were used in order to test the normalization procedure. Experimental results for three different recording condition scenarios are presented using Tippett plots and the effect of the compensation on the evaluation of the strength of the evidence is discussed.

Cycle-time equation for the Koller K300 cable yarder operating on steep slopes in the Northeast

Treesearch

Neil K. Huyler; Chris B. LeDoux

1997-01-01

Describes a delay-free-cycle time equation for the Koller K300 skyline yarder operating on steep slopes in the Northeast. Using the equation, the average delay-free-cycle time was 5.72 minutes. This means that about 420 cubic feet of material per hour can be produced. The important variables used in the equation were slope yarding distance, lateral yarding distance,...

Reliable Execution Based on CPN and Skyline Optimization for Web Service Composition

PubMed Central

Ha, Weitao; Zhang, Guojun

2013-01-01

With development of SOA, the complex problem can be solved by combining available individual services and ordering them to best suit user's requirements. Web services composition is widely used in business environment. With the features of inherent autonomy and heterogeneity for component web services, it is difficult to predict the behavior of the overall composite service. Therefore, transactional properties and nonfunctional quality of service (QoS) properties are crucial for selecting the web services to take part in the composition. Transactional properties ensure reliability of composite Web service, and QoS properties can identify the best candidate web services from a set of functionally equivalent services. In this paper we define a Colored Petri Net (CPN) model which involves transactional properties of web services in the composition process. To ensure reliable and correct execution, unfolding processes of the CPN are followed. The execution of transactional composition Web service (TCWS) is formalized by CPN properties. To identify the best services of QoS properties from candidate service sets formed in the TCSW-CPN, we use skyline computation to retrieve dominant Web service. It can overcome that the reduction of individual scores to an overall similarity leads to significant information loss. We evaluate our approach experimentally using both real and synthetically generated datasets. PMID:23935431

Effect of collision energy optimization on the measurement of peptides by selected reaction monitoring (SRM) mass spectrometry.

PubMed

Maclean, Brendan; Tomazela, Daniela M; Abbatiello, Susan E; Zhang, Shucha; Whiteaker, Jeffrey R; Paulovich, Amanda G; Carr, Steven A; Maccoss, Michael J

2010-12-15

Proteomics experiments based on Selected Reaction Monitoring (SRM, also referred to as Multiple Reaction Monitoring or MRM) are being used to target large numbers of protein candidates in complex mixtures. At present, instrument parameters are often optimized for each peptide, a time and resource intensive process. Large SRM experiments are greatly facilitated by having the ability to predict MS instrument parameters that work well with the broad diversity of peptides they target. For this reason, we investigated the impact of using simple linear equations to predict the collision energy (CE) on peptide signal intensity and compared it with the empirical optimization of the CE for each peptide and transition individually. Using optimized linear equations, the difference between predicted and empirically derived CE values was found to be an average gain of only 7.8% of total peak area. We also found that existing commonly used linear equations fall short of their potential, and should be recalculated for each charge state and when introducing new instrument platforms. We provide a fully automated pipeline for calculating these equations and individually optimizing CE of each transition on SRM instruments from Agilent, Applied Biosystems, Thermo-Scientific and Waters in the open source Skyline software tool ( http://proteome.gs.washington.edu/software/skyline ).

Implementation of statistical process control for proteomic experiments via LC MS/MS.

PubMed

Bereman, Michael S; Johnson, Richard; Bollinger, James; Boss, Yuval; Shulman, Nick; MacLean, Brendan; Hoofnagle, Andrew N; MacCoss, Michael J

2014-04-01

Statistical process control (SPC) is a robust set of tools that aids in the visualization, detection, and identification of assignable causes of variation in any process that creates products, services, or information. A tool has been developed termed Statistical Process Control in Proteomics (SProCoP) which implements aspects of SPC (e.g., control charts and Pareto analysis) into the Skyline proteomics software. It monitors five quality control metrics in a shotgun or targeted proteomic workflow. None of these metrics require peptide identification. The source code, written in the R statistical language, runs directly from the Skyline interface, which supports the use of raw data files from several of the mass spectrometry vendors. It provides real time evaluation of the chromatographic performance (e.g., retention time reproducibility, peak asymmetry, and resolution), and mass spectrometric performance (targeted peptide ion intensity and mass measurement accuracy for high resolving power instruments) via control charts. Thresholds are experiment- and instrument-specific and are determined empirically from user-defined quality control standards that enable the separation of random noise and systematic error. Finally, Pareto analysis provides a summary of performance metrics and guides the user to metrics with high variance. The utility of these charts to evaluate proteomic experiments is illustrated in two case studies.

Reliable execution based on CPN and skyline optimization for Web service composition.

PubMed

Chen, Liping; Ha, Weitao; Zhang, Guojun

2013-01-01

With development of SOA, the complex problem can be solved by combining available individual services and ordering them to best suit user's requirements. Web services composition is widely used in business environment. With the features of inherent autonomy and heterogeneity for component web services, it is difficult to predict the behavior of the overall composite service. Therefore, transactional properties and nonfunctional quality of service (QoS) properties are crucial for selecting the web services to take part in the composition. Transactional properties ensure reliability of composite Web service, and QoS properties can identify the best candidate web services from a set of functionally equivalent services. In this paper we define a Colored Petri Net (CPN) model which involves transactional properties of web services in the composition process. To ensure reliable and correct execution, unfolding processes of the CPN are followed. The execution of transactional composition Web service (TCWS) is formalized by CPN properties. To identify the best services of QoS properties from candidate service sets formed in the TCSW-CPN, we use skyline computation to retrieve dominant Web service. It can overcome that the reduction of individual scores to an overall similarity leads to significant information loss. We evaluate our approach experimentally using both real and synthetically generated datasets.

Inferring epidemiological dynamics of infectious diseases using Tajima's D statistic on nucleotide sequences of pathogens.

PubMed

Kim, Kiyeon; Omori, Ryosuke; Ito, Kimihito

2017-12-01

The estimation of the basic reproduction number is essential to understand epidemic dynamics, and time series data of infected individuals are usually used for the estimation. However, such data are not always available. Methods to estimate the basic reproduction number using genealogy constructed from nucleotide sequences of pathogens have been proposed so far. Here, we propose a new method to estimate epidemiological parameters of outbreaks using the time series change of Tajima's D statistic on the nucleotide sequences of pathogens. To relate the time evolution of Tajima's D to the number of infected individuals, we constructed a parsimonious mathematical model describing both the transmission process of pathogens among hosts and the evolutionary process of the pathogens. As a case study we applied this method to the field data of nucleotide sequences of pandemic influenza A (H1N1) 2009 viruses collected in Argentina. The Tajima's D-based method estimated basic reproduction number to be 1.55 with 95% highest posterior density (HPD) between 1.31 and 2.05, and the date of epidemic peak to be 10th July with 95% HPD between 22nd June and 9th August. The estimated basic reproduction number was consistent with estimation by birth-death skyline plot and estimation using the time series of the number of infected individuals. These results suggested that Tajima's D statistic on nucleotide sequences of pathogens could be useful to estimate epidemiological parameters of outbreaks. Copyright © 2017 The Authors. Published by Elsevier B.V. All rights reserved.

Phylodynamic Analysis Revealed That Epidemic of CRF07_BC Strain in Men Who Have Sex with Men Drove Its Second Spreading Wave in China.

PubMed

Zhang, Min; Jia, Dijing; Li, Hanping; Gui, Tao; Jia, Lei; Wang, Xiaolin; Li, Tianyi; Liu, Yongjian; Bao, Zuoyi; Liu, Siyang; Zhuang, Daomin; Li, Jingyun; Li, Lin

2017-10-01

CRF07_BC was originally formed in Yunnan province of China in 1980s and spread quickly in injecting drug users (IDUs). In recent years, it has been introduced into men who have sex with men (MSM) and become the most dominant strain in China. In this study, we performed a comprehensively phylodynamic analysis of CRF07_BC sequences from China. All CRF07_BC sequences identified in China were retrieved from database. More sequences obtained in our laboratory were added to make the dataset more representative. A maximum-likelihood (ML) tree was constructed with PhyML3.0. Maximum clade credibility (MCC) tree and effective population size were predicted by using Markov Chains Monte Carlo sampling method with Beast software. A total of 610 CRF07_BC sequences coving 1,473 bp of the gag gene (from 817 to 2,289 according to HXB2 calculator) were included into the dataset. Three epidemic clusters were identified; two clusters comprised sequences from IDUs, while one cluster mainly contained sequences from MSMs. The time of the most recent common ancestor of clusters that composed of sequences from MSMs was estimated to be in 2000. Two rapid spreading waves of effective population size of CRF07_BC infections were identified in the skyline plot. The second wave coincided with the expanding of MSM cluster. The results indicated that the control of CRF07_BC infections in MSMs would help to decrease its epidemic in China.

Isotope partitioning of soil respiration: A Bayesian solution to accommodate multiple sources of variability

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

Ogle, Kiona; Pendall, Elise

Isotopic methods offer great potential for partitioning trace gas fluxes such as soil respiration into their different source contributions. Traditional partitioning methods face challenges due to variability introduced by different measurement methods, fractionation effects, and end-member uncertainty. To address these challenges, we describe in this paper a hierarchical Bayesian (HB) approach for isotopic partitioning of soil respiration that directly accommodates such variability. We apply our HB method to data from an experiment conducted in a shortgrass steppe ecosystem, where decomposition was previously shown to be stimulated by elevated CO 2. Our approach simultaneously fits Keeling plot (KP) models to observationsmore » of soil or soil-respired δ 13C and [CO 2] obtained via chambers and gas wells, corrects the KP intercepts for apparent fractionation (Δ) due to isotope-specific diffusion rates and/or method artifacts, estimates method- and treatment-specific values for Δ, propagates end-member uncertainty, and calculates proportional contributions from two distinct respiration sources (“old” and “new” carbon). The chamber KP intercepts were estimated with greater confidence than the well intercepts and compared to the theoretical value of 4.4‰, our results suggest that Δ varies between 2 and 5.2‰ depending on method (chambers versus wells) and CO 2 treatment. Because elevated CO 2 plots were fumigated with 13C-depleted CO 2, the source contributions were tightly constrained, and new C accounted for 64% (range = 55–73%) of soil respiration. The contributions were less constrained for the ambient CO 2 treatments, but new C accounted for significantly less (47%, range = 15–82%) of soil respiration. Finally, our new HB partitioning approach contrasts our original analysis (higher contribution of old C under elevated CO 2) because it uses additional data sources, accounts for end-member bias, and estimates apparent fractionation effects.« less

Costs of harvesting forest biomass on steep slopes with a small cable yarder: results from field trials and simulations

Treesearch

John E. Baumgras; Chris B. LeDoux

1986-01-01

Cable yarding can reduce the environmental impact of timber harvesting on steep slopes by increasing road spacing and reducing soil disturbance. To determine the cost of harvesting forest biomass with a small cable yarder, a 13.4 kW (18 hp) skyline yarder was tested on two southern Appalachian sites. At both sites, fuelwood was harvested from the boles of hardwood...

2. A panoramic view of the historical district as seen ...

Library of Congress Historic Buildings Survey, Historic Engineering Record, Historic Landscapes Survey

2. A panoramic view of the historical district as seen from the top of the Waterford Towers. This picture shows the Town Street bridge in the foreground, the Broad Street bridge in the background, Central High School on the left and the Columbus skyline on the right (facing north), and Bicentennial Park just below. - Broad Street Bridge, Spanning Scioto River at U.S. Route 40 (Broad Street), Columbus, Franklin County, OH

Manatee grazing impacts on a mixed species seagrass bed

USGS Publications Warehouse

Lefebvre, Lynn W.; Provancha, Jane A.; Slone, Daniel H.; Kenworthy, W. Judson

2017-01-01

The endangered manatee Trichechus manatus is one of few large grazers in seagrass systems. To assess the long-term impacts of repeated grazing on seagrasses, we selected a study site within Kennedy Space Center in the northern Banana River, Brevard County, Florida, that was typically grazed by large numbers of manatees in spring. Two 13x13 m manatee exclosures and 2 paired open plots of equal size were established at the study site in October 1990. Shoot counts, biomass, and species composition of the co-dominant seagrass species, Syringodium filiforme and Halodule wrightii, were sampled 3 times per year in all 4 plots between October 1990 and October 1994. We used a Bayesian modelling approach, accounting for the influence of depth, to detect treatment (exclosed vs. open) effects. S. filiforme shoot counts, total biomass, and frequency of occurrence significantly increased in the exclosures. By July 1993, mean biomass values in the exclosures (167 g dry wt m-2) greatly exceeded those in the open plots (28 g dry wt m-2). H. wrightii decreased in the exclosures by 1994. Initially, both S. filiforme and H. wrightii responded positively to release from manatee grazing pressure. As S. filiforme continued to become denser in the exclosures, it gradually replaced H. wrightii. Our findings may be helpful to biologists and managers interested in predicting seagrass recovery and manatee carrying capacity of repeatedly grazed seagrass beds in areas of special significance to manatees and seagrass conservation.

Linear mixed-effects models to describe individual tree crown width for China-fir in Fujian Province, southeast China.

PubMed

Hao, Xu; Yujun, Sun; Xinjie, Wang; Jin, Wang; Yao, Fu

2015-01-01

A multiple linear model was developed for individual tree crown width of Cunninghamia lanceolata (Lamb.) Hook in Fujian province, southeast China. Data were obtained from 55 sample plots of pure China-fir plantation stands. An Ordinary Linear Least Squares (OLS) regression was used to establish the crown width model. To adjust for correlations between observations from the same sample plots, we developed one level linear mixed-effects (LME) models based on the multiple linear model, which take into account the random effects of plots. The best random effects combinations for the LME models were determined by the Akaike's information criterion, the Bayesian information criterion and the -2logarithm likelihood. Heteroscedasticity was reduced by three residual variance functions: the power function, the exponential function and the constant plus power function. The spatial correlation was modeled by three correlation structures: the first-order autoregressive structure [AR(1)], a combination of first-order autoregressive and moving average structures [ARMA(1,1)], and the compound symmetry structure (CS). Then, the LME model was compared to the multiple linear model using the absolute mean residual (AMR), the root mean square error (RMSE), and the adjusted coefficient of determination (adj-R2). For individual tree crown width models, the one level LME model showed the best performance. An independent dataset was used to test the performance of the models and to demonstrate the advantage of calibrating LME models.

Defining the Estimated Core Genome of Bacterial Populations Using a Bayesian Decision Model

PubMed Central

van Tonder, Andries J.; Mistry, Shilan; Bray, James E.; Hill, Dorothea M. C.; Cody, Alison J.; Farmer, Chris L.; Klugman, Keith P.; von Gottberg, Anne; Bentley, Stephen D.; Parkhill, Julian; Jolley, Keith A.; Maiden, Martin C. J.; Brueggemann, Angela B.

2014-01-01

The bacterial core genome is of intense interest and the volume of whole genome sequence data in the public domain available to investigate it has increased dramatically. The aim of our study was to develop a model to estimate the bacterial core genome from next-generation whole genome sequencing data and use this model to identify novel genes associated with important biological functions. Five bacterial datasets were analysed, comprising 2096 genomes in total. We developed a Bayesian decision model to estimate the number of core genes, calculated pairwise evolutionary distances (p-distances) based on nucleotide sequence diversity, and plotted the median p-distance for each core gene relative to its genome location. We designed visually-informative genome diagrams to depict areas of interest in genomes. Case studies demonstrated how the model could identify areas for further study, e.g. 25% of the core genes with higher sequence diversity in the Campylobacter jejuni and Neisseria meningitidis genomes encoded hypothetical proteins. The core gene with the highest p-distance value in C. jejuni was annotated in the reference genome as a putative hydrolase, but further work revealed that it shared sequence homology with beta-lactamase/metallo-beta-lactamases (enzymes that provide resistance to a range of broad-spectrum antibiotics) and thioredoxin reductase genes (which reduce oxidative stress and are essential for DNA replication) in other C. jejuni genomes. Our Bayesian model of estimating the core genome is principled, easy to use and can be applied to large genome datasets. This study also highlighted the lack of knowledge currently available for many core genes in bacterial genomes of significant global public health importance. PMID:25144616

Bayesian quantitative precipitation forecasts in terms of quantiles

NASA Astrophysics Data System (ADS)

Bentzien, Sabrina; Friederichs, Petra

2014-05-01

Ensemble prediction systems (EPS) for numerical weather predictions on the mesoscale are particularly developed to obtain probabilistic guidance for high impact weather. An EPS not only issues a deterministic future state of the atmosphere but a sample of possible future states. Ensemble postprocessing then translates such a sample of forecasts into probabilistic measures. This study focus on probabilistic quantitative precipitation forecasts in terms of quantiles. Quantiles are particular suitable to describe precipitation at various locations, since no assumption is required on the distribution of precipitation. The focus is on the prediction during high-impact events and related to the Volkswagen Stiftung funded project WEX-MOP (Mesoscale Weather Extremes - Theory, Spatial Modeling and Prediction). Quantile forecasts are derived from the raw ensemble and via quantile regression. Neighborhood method and time-lagging are effective tools to inexpensively increase the ensemble spread, which results in more reliable forecasts especially for extreme precipitation events. Since an EPS provides a large amount of potentially informative predictors, a variable selection is required in order to obtain a stable statistical model. A Bayesian formulation of quantile regression allows for inference about the selection of predictive covariates by the use of appropriate prior distributions. Moreover, the implementation of an additional process layer for the regression parameters accounts for spatial variations of the parameters. Bayesian quantile regression and its spatially adaptive extension is illustrated for the German-focused mesoscale weather prediction ensemble COSMO-DE-EPS, which runs (pre)operationally since December 2010 at the German Meteorological Service (DWD). Objective out-of-sample verification uses the quantile score (QS), a weighted absolute error between quantile forecasts and observations. The QS is a proper scoring function and can be decomposed into reliability, resolutions and uncertainty parts. A quantile reliability plot gives detailed insights in the predictive performance of the quantile forecasts.

User-Driven Geolocation of Untagged Desert Imagery Using Digital Elevation Models (Open Access)

DTIC Science & Technology

2013-09-12

IEEE International Conference on, pages 3677–3680. IEEE, 2011. [13] W. Zhang and J. Kosecka. Image based localization in urban environments. In 3D ...non- urban environments such as deserts. Our system generates synthetic skyline views from a DEM and extracts stable concavity-based features from these...fine as 100m2. 1. Introduction Automatic geolocation of imagery has many exciting use cases. For example, such a tool could semantically orga- nize

User-Driven Geolocation of Untagged Desert Imagery Using Digital Elevation Models

DTIC Science & Technology

2013-01-01

Conference on, pages 3677–3680. IEEE, 2011. [13] W. Zhang and J. Kosecka. Image based localization in urban environments. In 3D Data Processing...non- urban environments such as deserts. Our system generates synthetic skyline views from a DEM and extracts stable concavity-based features from these...fine as 100m2. 1. Introduction Automatic geolocation of imagery has many exciting use cases. For example, such a tool could semantically orga- nize

Ariadne's Thread: A Robust Software Solution Leading to Automated Absolute and Relative Quantification of SRM Data.

PubMed

Nasso, Sara; Goetze, Sandra; Martens, Lennart

2015-09-04

Selected reaction monitoring (SRM) MS is a highly selective and sensitive technique to quantify protein abundances in complex biological samples. To enhance the pace of SRM large studies, a validated, robust method to fully automate absolute quantification and to substitute for interactive evaluation would be valuable. To address this demand, we present Ariadne, a Matlab software. To quantify monitored targets, Ariadne exploits metadata imported from the transition lists, and targets can be filtered according to mProphet output. Signal processing and statistical learning approaches are combined to compute peptide quantifications. To robustly estimate absolute abundances, the external calibration curve method is applied, ensuring linearity over the measured dynamic range. Ariadne was benchmarked against mProphet and Skyline by comparing its quantification performance on three different dilution series, featuring either noisy/smooth traces without background or smooth traces with complex background. Results, evaluated as efficiency, linearity, accuracy, and precision of quantification, showed that Ariadne's performance is independent of data smoothness and complex background presence and that Ariadne outperforms mProphet on the noisier data set and improved 2-fold Skyline's accuracy and precision for the lowest abundant dilution with complex background. Remarkably, Ariadne could statistically distinguish from each other all different abundances, discriminating dilutions as low as 0.1 and 0.2 fmol. These results suggest that Ariadne offers reliable and automated analysis of large-scale SRM differential expression studies.

Biodiversity effects on the water balance of an experimental grassland

NASA Astrophysics Data System (ADS)

Leimer, Sophia; Kreutziger, Yvonne; Rosenkranz, Stephan; Beßler, Holger; Engels, Christof; Oelmann, Yvonne; Weisser, Wolfgang W.; Wirth, Christian; Wilcke, Wolfgang

2013-04-01

Plant species richness increases aboveground biomass production in biodiversity experiments. Biomass production depends on and feeds back to the water balance, but it remains unclear how plant species richness influences soil water contents and water fluxes (actual evapotranspiration (ETa), downward flux (DF), and upward flux (UF)). Our objective was to determine the effects of plant species and functional richness and functional identity on soil water contents and water fluxes for two soil depths (0-0.3 and 0.3.-0.7 m). To achieve this, we used a water balance model in connection with Bayesian hierarchical modeling. We monitored soil water contents on 86 plots of a grassland plant diversity experiment in Jena, Germany between July 2002 and January 2006. In the field experiment, plant species richness (0, 1, 2, 4, 8, 16, 60) and functional group composition (0-4 functional groups: legumes, grasses, non-leguminous tall herbs, non-leguminous small herbs) were manipulated in a factorial design. Climate data (air temperature, precipitation, wind velocity, relative humidity, global radiation, soil moisture) was measured at a central climate station between July 2002 and December 2007. Root biomass data from July 2006 was available per plot. Missing water contents per plot and depth were estimated in weekly resolution for the years 2003-2007 with a Bayesian hierarchical model using measured water contents per plot and centrally measured soil moisture. To obtain ETa, DF, and UF of the two different soil depths, we modified a soil water balance model which had been developed for our study site. The model is based on changes in soil water content between subsequent observation dates and modeled potential evapotranspiration which was partitioned between soil layers according to percentage of root biomass. The presence of specific functional groups significantly changed water contents and fluxes with partly opposing effects in the two soil depths. Presence of grasses decreased water contents in both depths, DF in topsoil, and ETa in subsoil, but increased ETa in topsoil. As grasses produce less shade than other plant functional groups because of their leaf morphology, higher ETa in topsoil could be explained by higher soil evaporation. Moreover, grasses have an extensive, shallow rooting system which facilitates exhaustive water use from the upper soil layer and therefore probably decreases water contents and DF. Species richness did not significantly affect water contents and fluxes in both soil layers except that the relation between species richness and water contents in subsoil changed over time. This can be explained by two equivalent but opposite effects. Transpiration increases with biomass which is positively correlated with species richness. By contrast, soil evaporation decreases with species richness because the greater vegetation cover in species-rich communities produces more shade. We conclude that the contrasting effects of plant species richness on transpiration and evaporation counterbalance each other and that functional traits of specific plant functional groups mediate the biologically-induced changes in the water balance.

Evaluation of out-of-core computer programs for the solution of symmetric banded linear equations. [simultaneous equations

NASA Technical Reports Server (NTRS)

Dunham, R. S.

1976-01-01

FORTRAN coded out-of-core equation solvers that solve using direct methods symmetric banded systems of simultaneous algebraic equations. Banded, frontal and column (skyline) solvers were studied as well as solvers that can partition the working area and thus could fit into any available core. Comparison timings are presented for several typical two dimensional and three dimensional continuum type grids of elements with and without midside nodes. Extensive conclusions are also given.

Parallel-Vector Algorithm For Rapid Structural Anlysis

NASA Technical Reports Server (NTRS)

Agarwal, Tarun R.; Nguyen, Duc T.; Storaasli, Olaf O.

1993-01-01

New algorithm developed to overcome deficiency of skyline storage scheme by use of variable-band storage scheme. Exploits both parallel and vector capabilities of modern high-performance computers. Gives engineers and designers opportunity to include more design variables and constraints during optimization of structures. Enables use of more refined finite-element meshes to obtain improved understanding of complex behaviors of aerospace structures leading to better, safer designs. Not only attractive for current supercomputers but also for next generation of shared-memory supercomputers.

Lustration: Transitional Justice in Poland and Its Continuous Struggle to Make Means With the Past

DTIC Science & Technology

2008-06-01

Warsaw, just as the secret police did over its citizens. The skyline of Warsaw, dominated by this building, offers a daily reminder of life under the...the communist regime (especially acts of collaboration with the secret police) and in turn disqualifying members of these groups from holding high...Ministry of Interior for their name to be vetted through the Secret Police files of the former regime.3 A similar approach was adopted in Poland, but due

Ancient Chinese Astronomy - An Overview

NASA Astrophysics Data System (ADS)

Shi, Yunli

Documentary and archaeological evidence testifies the early origin and continuous development of ancient Chinese astronomy to meet both the ideological and practical needs of a society largely based on agriculture. There was a long period when the beginning of the year, month, and season was determined by direct observation of celestial phenomena, including their alignments with respect to the local skyline. As the need for more exact study arose, new instruments for more exact observation were invented and the system of calendrical astronomy became entirely mathematized.

Multilocus Phylogeography of the Treefrog Scinax eurydice (Anura, Hylidae) Reveals a Plio-Pleistocene Diversification in the Atlantic Forest.

PubMed

Menezes, Lucas; Canedo, Clarissa; Batalha-Filho, Henrique; Garda, Adrian Antonio; Gehara, Marcelo; Napoli, Marcelo Felgueiras

2016-01-01

We aim to evaluate the genetic structure of an Atlantic Forest amphibian species, Scinax eurydice, testing the congruence among patterns identified and proposed by the literature for Pleistocene refugia, microrefugia, and geographic barriers to gene flow such as major rivers. Furthermore, we aim to evaluate predictions of such barriers and refugia on the genetic structure of the species, such as presence/absence of dispersal, timing since separation, and population expansions/contractions. We sequenced mitochondrial and nuclear genetic markers on 94 tissue samples from 41 localities. We inferred a gene tree and estimated genetic distances using mtDNA sequences. We then ran population clustering and assignment methods, AMOVA, and estimated migration rates among populations identified through mtDNA and nDNA analyses. We used a dated species tree, skyline plots, and summary statistics to evaluate concordance between population's distributions and geographic barriers and Pleistocene refugia. Scinax eurydice showed high mtDNA divergences and four clearly distinct mtDNA lineages. Species tree and population assignment tests supported the existence of two major clades corresponding to northeastern and southeastern Atlantic Forest in Brazil, each one composed of two other clades. Lineage splitting events occurred from late Pliocene to Pleistocene. We identified demographic expansions in two clades, and inexistent to low levels of migrations among different populations. Genetic patterns and demographic data support the existence of two northern Refuge and corroborate microrefugia south of the Doce/Jequitinhonha Rivers biogeographic divide. The results agree with a scenario of recent demographic expansion of lowland taxa. Scinax eurydice comprises a species complex, harboring undescribed taxa consistent with Pleistocene refugia. Two rivers lie at the boundaries among populations and endorse their role as secondary barriers to gene flow.

Multilocus Phylogeography of the Treefrog Scinax eurydice (Anura, Hylidae) Reveals a Plio-Pleistocene Diversification in the Atlantic Forest

PubMed Central

Menezes, Lucas; Canedo, Clarissa; Batalha-Filho, Henrique; Garda, Adrian Antonio; Gehara, Marcelo; Napoli, Marcelo Felgueiras

2016-01-01

We aim to evaluate the genetic structure of an Atlantic Forest amphibian species, Scinax eurydice, testing the congruence among patterns identified and proposed by the literature for Pleistocene refugia, microrefugia, and geographic barriers to gene flow such as major rivers. Furthermore, we aim to evaluate predictions of such barriers and refugia on the genetic structure of the species, such as presence/absence of dispersal, timing since separation, and population expansions/contractions. We sequenced mitochondrial and nuclear genetic markers on 94 tissue samples from 41 localities. We inferred a gene tree and estimated genetic distances using mtDNA sequences. We then ran population clustering and assignment methods, AMOVA, and estimated migration rates among populations identified through mtDNA and nDNA analyses. We used a dated species tree, skyline plots, and summary statistics to evaluate concordance between population’s distributions and geographic barriers and Pleistocene refugia. Scinax eurydice showed high mtDNA divergences and four clearly distinct mtDNA lineages. Species tree and population assignment tests supported the existence of two major clades corresponding to northeastern and southeastern Atlantic Forest in Brazil, each one composed of two other clades. Lineage splitting events occurred from late Pliocene to Pleistocene. We identified demographic expansions in two clades, and inexistent to low levels of migrations among different populations. Genetic patterns and demographic data support the existence of two northern Refuge and corroborate microrefugia south of the Doce/Jequitinhonha Rivers biogeographic divide. The results agree with a scenario of recent demographic expansion of lowland taxa. Scinax eurydice comprises a species complex, harboring undescribed taxa consistent with Pleistocene refugia. Two rivers lie at the boundaries among populations and endorse their role as secondary barriers to gene flow. PMID:27248688

Functional traits help predict post-disturbance demography of tropical trees.

PubMed

Flores, Olivier; Hérault, Bruno; Delcamp, Matthieu; Garnier, Éric; Gourlet-Fleury, Sylvie

2014-01-01

How tropical tree species respond to disturbance is a central issue of forest ecology, conservation and resource management. We define a hierarchical model to investigate how functional traits measured in control plots relate to the population change rate and to demographic rates for recruitment and mortality after disturbance by logging operations. Population change and demographic rates were quantified on a 12-year period after disturbance and related to seven functional traits measured in control plots. The model was calibrated using a Bayesian Network approach on 53 species surveyed in permanent forest plots (37.5 ha) at Paracou in French Guiana. The network analysis allowed us to highlight both direct and indirect relationships among predictive variables. Overall, 89% of interspecific variability in the population change rate after disturbance were explained by the two demographic rates, the recruitment rate being the most explicative variable. Three direct drivers explained 45% of the variability in recruitment rates, including leaf phosphorus concentration, with a positive effect, and seed size and wood density with negative effects. Mortality rates were explained by interspecific variability in maximum diameter only (25%). Wood density, leaf nitrogen concentration, maximum diameter and seed size were not explained by variables in the analysis and thus appear as independent drivers of post-disturbance demography. Relationships between functional traits and demographic parameters were consistent with results found in undisturbed forests. Functional traits measured in control conditions can thus help predict the fate of tropical tree species after disturbance. Indirect relationships also suggest how different processes interact to mediate species demographic response.

A comparison of effectiveness among frequent treatments of recurrent spontaneous abortion: A Bayesian network meta-analysis.

PubMed

Lv, Sha; Yu, Jing; Xu, Xiaoxiao

2018-04-30

A comprehensive network meta-analysis was designed to clarify contradictions and offer valuable clinical guidance in the treatment of recurrent spontaneous abortion (RSA). The included clinical trials were selected from the relevant medical journal databases and screened. Treatments were ranked by the surface under the cumulative ranking curve. Heat plots were constructed to analyze the inconsistency between direct data and network results, and adjusted funnel plots were constructed to assess publication bias. Forty-nine randomized controlled trials involving a total of 8496 RSA patients were selected. With placebo as control, corticosteroid plus low dose aspirin (LDA) plus unfractionated heparin (UFH), granulocyte colony-stimulating factor (G-CSF) alone, and LDA plus low molecular weight heparin (LMWH) all demonstrated effectiveness in increasing successful live birth rates and reducing the incidences of miscarriage. However, no treatment was demonstrably superior to placebo in terms of pregnancy success. For all 3 endpoints (live birth, abortion and success pregnancy), the adjusted funnel plots were symmetric to zero and indicated no publication bias. In terms of live birth and abortion rates, no treatment outperformed placebo in patients with antiphospholipid syndrome. In consideration of live birth and abortion rates, corticosteroid plus LDA plus UFH appeared to be the optimum treatment strategy; G-CSF was second, followed by LDA with LMWH, LDA plus LMWH plus intravenous immunoglobulin, corticosteroid with LDA and others. Subgroup analysis demonstrated no benefit of antithrombotic therapy in patients with antiphospholipid syndrome. © 2018 John Wiley & Sons A/S. Published by John Wiley & Sons Ltd.

Landsat Time-series for the Masses: Predicting Wood Biomass Growth from Tree-rings Using Departures from Mean Phenology in Google Earth Engine

NASA Astrophysics Data System (ADS)

Foster, J. R.; D'Amato, A. W.; Itter, M.; Reinikainen, M.; Curzon, M.

2017-12-01

The terrestrial carbon cycle is perturbed when disturbances remove leaf biomass from the forest canopy during the growing season. Changes in foliar biomass arise from defoliation caused by insects, disease, drought, frost or human management. As ephemeral disturbances, these often go undetected and their significance to models that predict forest growth from climatic drivers remains unknown. Here, we seek to distinguish the roles of weather vs. canopy disturbance on forest growth by using dense Landsat time-series to quantify departures in mean phenology that in turn predict changes in leaf biomass. We estimated a foliar biomass index (FBMI) from 1984-2016, and predict plot-level wood growth over 28 years on 156 tree-ring monitoring plots in Minnesota, USA. We accessed the entire Landsat archive (sensors 4, 5 & 7) to compute FBMI using Google Earth Engine's cloud computing platform (GEE). GEE allows this pixel-level approach to be applied at any location; a feature we demonstrate with published wood-growth data from flux tower sites. Our Bayesian models predicted biomass changes from tree-ring plots as a function of Landsat FBMI and annual climate data. We expected model parameters to vary by tree functional groups defined by differences in xylem anatomy and leaf longevity, two traits with linkages to phenology, as reported in a recent review. We found that Landsat FBMI was a surprisingly strong predictor of aggregate wood-growth, explaining up to 80% of annual growth variation for some deciduous plots. Growth responses to canopy disturbance varied among tree functional groups, and the importance of some seasonal climate metrics diminished or changed sign when FBMI was included (e.g. fall and spring climatic water deficit), while others remained unchanged (current and lagged summer deficit). Insights emerging from these models can clear up sources of persistent uncertainty and open a new frontier for models of forest productivity.

RadVel: The Radial Velocity Modeling Toolkit

NASA Astrophysics Data System (ADS)

Fulton, Benjamin J.; Petigura, Erik A.; Blunt, Sarah; Sinukoff, Evan

2018-04-01

RadVel is an open-source Python package for modeling Keplerian orbits in radial velocity (RV) timeseries. RadVel provides a convenient framework to fit RVs using maximum a posteriori optimization and to compute robust confidence intervals by sampling the posterior probability density via Markov Chain Monte Carlo (MCMC). RadVel allows users to float or fix parameters, impose priors, and perform Bayesian model comparison. We have implemented real-time MCMC convergence tests to ensure adequate sampling of the posterior. RadVel can output a number of publication-quality plots and tables. Users may interface with RadVel through a convenient command-line interface or directly from Python. The code is object-oriented and thus naturally extensible. We encourage contributions from the community. Documentation is available at http://radvel.readthedocs.io.

Mitochondrial Analysis of the Most Basal Canid Reveals Deep Divergence between Eastern and Western North American Gray Foxes (Urocyon spp.) and Ancient Roots in Pleistocene California.

PubMed

Goddard, Natalie S; Statham, Mark J; Sacks, Benjamin N

2015-01-01

Pleistocene aridification in central North America caused many temperate forest-associated vertebrates to split into eastern and western lineages. Such divisions can be cryptic when Holocene expansions have closed the gaps between once-disjunct ranges or when local morphological variation obscures deeper regional divergences. We investigated such cryptic divergence in the gray fox (Urocyon cinereoargenteus), the most basal extant canid in the world. We also investigated the phylogeography of this species and its diminutive relative, the island fox (U. littoralis), in California. The California Floristic Province was a significant source of Pleistocene diversification for a wide range of taxa and, we hypothesized, for the gray fox as well. Alternatively, gray foxes in California potentially reflected a recent Holocene expansion from further south. We sequenced mitochondrial DNA from 169 gray foxes from the southeastern and southwestern United States and 11 island foxes from three of the Channel Islands. We estimated a 1.3% sequence divergence in the cytochrome b gene between eastern and western foxes and used coalescent simulations to date the divergence to approximately 500,000 years before present (YBP), which is comparable to that between recognized sister species within the Canidae. Gray fox samples collected from throughout California exhibited high haplotype diversity, phylogeographic structure, and genetic signatures of a late-Holocene population decline. Bayesian skyline analysis also indicated an earlier population increase dating to the early Wisconsin glaciation (~70,000 YBP) and a root height extending back to the previous interglacial (~100,000 YBP). Together these findings support California's role as a long-term Pleistocene refugium for western Urocyon. Lastly, based both on our results and re-interpretation of those of another study, we conclude that island foxes of the Channel Islands trace their origins to at least 3 distinct female founders from the mainland rather than to a single matriline, as previously suggested.

Mitochondrial Analysis of the Most Basal Canid Reveals Deep Divergence between Eastern and Western North American Gray Foxes (Urocyon spp.) and Ancient Roots in Pleistocene California

PubMed Central

Goddard, Natalie S.; Statham, Mark J.; Sacks, Benjamin N.

2015-01-01

Pleistocene aridification in central North America caused many temperate forest-associated vertebrates to split into eastern and western lineages. Such divisions can be cryptic when Holocene expansions have closed the gaps between once-disjunct ranges or when local morphological variation obscures deeper regional divergences. We investigated such cryptic divergence in the gray fox (Urocyon cinereoargenteus), the most basal extant canid in the world. We also investigated the phylogeography of this species and its diminutive relative, the island fox (U. littoralis), in California. The California Floristic Province was a significant source of Pleistocene diversification for a wide range of taxa and, we hypothesized, for the gray fox as well. Alternatively, gray foxes in California potentially reflected a recent Holocene expansion from further south. We sequenced mitochondrial DNA from 169 gray foxes from the southeastern and southwestern United States and 11 island foxes from three of the Channel Islands. We estimated a 1.3% sequence divergence in the cytochrome b gene between eastern and western foxes and used coalescent simulations to date the divergence to approximately 500,000 years before present (YBP), which is comparable to that between recognized sister species within the Canidae. Gray fox samples collected from throughout California exhibited high haplotype diversity, phylogeographic structure, and genetic signatures of a late-Holocene population decline. Bayesian skyline analysis also indicated an earlier population increase dating to the early Wisconsin glaciation (~70,000 YBP) and a root height extending back to the previous interglacial (~100,000 YBP). Together these findings support California’s role as a long-term Pleistocene refugium for western Urocyon. Lastly, based both on our results and re-interpretation of those of another study, we conclude that island foxes of the Channel Islands trace their origins to at least 3 distinct female founders from the mainland rather than to a single matriline, as previously suggested. PMID:26288066

The connection between landscapes and the solar ephemeris in honeybees.

PubMed

Towne, William F; Moscrip, Heather

2008-12-01

Honeybees connect the sun's daily pattern of azimuthal movement to some aspect of the landscape around their nests. In the present study, we ask what aspect of the landscape is used in this context--the entire landscape panorama or only sectors seen along familiar flight routes. Previous studies of the solar ephemeris memory in bees have generally used bees that had experience flying a specific route, usually along a treeline, to a feeder. When such bees were moved to a differently oriented treeline on overcast days, the bees oriented their communicative dances as if they were still at the first treeline, based on a memory of the sun's course in relation to some aspect of the site, possibly the familiar route along the treeline or possibly the entire landscape or skyline panorama. Our results show that bees lacking specific flight-route training can nonetheless recall the sun's compass bearing relative to novel flight routes in their natal landscape. Specifically, we moved a hive from one landscape to a differently oriented twin landscape, and only after transplantation under overcast skies did we move a feeder away from the hive. These bees nonetheless danced accurately by memory of the sun's course in relation to their natal landscape. The bees' knowledge of the relationship between the sun and landscape, therefore, is not limited to familiar flight routes and so may encompass, at least functionally, the entire panorama. Further evidence suggests that the skyline in particular may be the bees' preferred reference in this context.

Discrimination of Isomers of Released N- and O-Glycans Using Diagnostic Product Ions in Negative Ion PGC-LC-ESI-MS/MS

NASA Astrophysics Data System (ADS)

Ashwood, Christopher; Lin, Chi-Hung; Thaysen-Andersen, Morten; Packer, Nicolle H.

2018-03-01

Profiling cellular protein glycosylation is challenging due to the presence of highly similar glycan structures that play diverse roles in cellular physiology. As the anomericity and the exact linkage type of a single glycosidic bond can influence glycan function, there is a demand for improved and automated methods to confirm detailed structural features and to discriminate between structurally similar isomers, overcoming a significant bottleneck in the analysis of data generated by glycomics experiments. We used porous graphitized carbon-LC-ESI-MS/MS to separate and detect released N- and O-glycan isomers from mammalian model glycoproteins using negative mode resonance activation CID-MS/MS. By interrogating similar fragment spectra from closely related glycan isomers that differ only in arm position and sialyl linkage, product fragment ions for discrimination between these features were discovered. Using the Skyline software, at least two diagnostic fragment ions of high specificity were validated for automated discrimination of sialylation and arm position in N-glycan structures, and sialylation in O-glycan structures, complementing existing structural diagnostic ions. These diagnostic ions were shown to be useful for isomer discrimination using both linear and 3D ion trap mass spectrometers when analyzing complex glycan mixtures from cell lysates. Skyline was found to serve as a useful tool for automated assessment of glycan isomer discrimination. This platform-independent workflow can potentially be extended to automate the characterization and quantitation of other challenging glycan isomers. [Figure not available: see fulltext.

Examining spectral properties of Landsat 8 OLI for predicting above-ground carbon of Labanan Forest, Berau

NASA Astrophysics Data System (ADS)

Suhardiman, A.; Tampubolon, B. A.; Sumaryono, M.

2018-04-01

Many studies revealed significant correlation between satellite image properties and forest data attributes such as stand volume, biomass or carbon stock. However, further study is still relevant due to advancement of remote sensing technology as well as improvement on methods of data analysis. In this study, the properties of three vegetation indices derived from Landsat 8 OLI were tested upon above-ground carbon stock data from 50 circular sample plots (30-meter radius) from ground survey in PT. Inhutani I forest concession in Labanan, Berau, East Kalimantan. Correlation analysis using Pearson method exhibited a promising results when the coefficient of correlation (r-value) was higher than 0.5. Further regression analysis was carried out to develop mathematical model describing the correlation between sample plots data and vegetation index image using various mathematical models.Power and exponential model were demonstrated a good result for all vegetation indices. In order to choose the most adequate mathematical model for predicting Above-ground Carbon (AGC), the Bayesian Information Criterion (BIC) was applied. The lowest BIC value (i.e. -376.41) shown by Transformed Vegetation Index (TVI) indicates this formula, AGC = 9.608*TVI21.54, is the best predictor of AGC of study area.

Individual and population pharmacokinetic compartment analysis: a graphic procedure for quantification of predictive performance.

PubMed

Eksborg, Staffan

2013-01-01

Pharmacokinetic studies are important for optimizing of drug dosing, but requires proper validation of the used pharmacokinetic procedures. However, simple and reliable statistical methods suitable for evaluation of the predictive performance of pharmacokinetic analysis are essentially lacking. The aim of the present study was to construct and evaluate a graphic procedure for quantification of predictive performance of individual and population pharmacokinetic compartment analysis. Original data from previously published pharmacokinetic compartment analyses after intravenous, oral, and epidural administration, and digitized data, obtained from published scatter plots of observed vs predicted drug concentrations from population pharmacokinetic studies using the NPEM algorithm and NONMEM computer program and Bayesian forecasting procedures, were used for estimating the predictive performance according to the proposed graphical method and by the method of Sheiner and Beal. The graphical plot proposed in the present paper proved to be a useful tool for evaluation of predictive performance of both individual and population compartment pharmacokinetic analysis. The proposed method is simple to use and gives valuable information concerning time- and concentration-dependent inaccuracies that might occur in individual and population pharmacokinetic compartment analysis. Predictive performance can be quantified by the fraction of concentration ratios within arbitrarily specified ranges, e.g. within the range 0.8-1.2.

Open Source Software Tool Skyline Reaches Key Agreement with Mass Spectrometer Vendors | Office of Cancer Clinical Proteomics Research

Cancer.gov

The full proteomics analysis of a small tumor sample (similar in mass to a few grains of rice) produces well over 500 megabytes of unprocessed "raw" data when analyzed on a mass spectrometer (MS). Thus, for every proteomics experiment there is a vast amount of raw data that must be analyzed and interrogated in order to extract biological information. Moreover, the raw data output from different MS vendors are generally in different formats inhibiting the ability of labs to productively work together.

Space Shuttle Discovery DC Fly-Over

NASA Image and Video Library

2012-04-17

Space shuttle Discovery, mounted atop a NASA 747 Shuttle Carrier Aircraft (SCA), flies over the Washington skyline as seen from a NASA T-38 aircraft, Tuesday, April 17, 2012. Discovery, the first orbiter retired from NASA’s shuttle fleet, completed 39 missions, spent 365 days in space, orbited the Earth 5,830 times, and traveled 148,221,675 miles. NASA will transfer Discovery to the National Air and Space Museum to begin its new mission to commemorate past achievements in space and to educate and inspire future generations of explorers. Photo Credit: (NASA/Robert Markowitz)

Model selection as a science driver for dark energy surveys

NASA Astrophysics Data System (ADS)

Mukherjee, Pia; Parkinson, David; Corasaniti, Pier Stefano; Liddle, Andrew R.; Kunz, Martin

2006-07-01

A key science goal of upcoming dark energy surveys is to seek time-evolution of the dark energy. This problem is one of model selection, where the aim is to differentiate between cosmological models with different numbers of parameters. However, the power of these surveys is traditionally assessed by estimating their ability to constrain parameters, which is a different statistical problem. In this paper, we use Bayesian model selection techniques, specifically forecasting of the Bayes factors, to compare the abilities of different proposed surveys in discovering dark energy evolution. We consider six experiments - supernova luminosity measurements by the Supernova Legacy Survey, SNAP, JEDI and ALPACA, and baryon acoustic oscillation measurements by WFMOS and JEDI - and use Bayes factor plots to compare their statistical constraining power. The concept of Bayes factor forecasting has much broader applicability than dark energy surveys.

Does plant diversity affect the water balance of established grassland systems?

NASA Astrophysics Data System (ADS)

Leimer, Sophia; Bischoff, Sebastian; Blaser, Stefan; Boch, Steffen; Busch, Verena; Escher, Peter; Fischer, Markus; Kaupenjohann, Martin; Kerber, Katja; Klaus, Valentin; Michalzik, Beate; Prati, Daniel; Schäfer, Deborah; Schmitt, Barbara; Schöning, Ingo; Schwarz, Martin T.; Siemens, Jan; Thieme, Lisa; Wilcke, Wolfgang

2017-04-01

The water cycle drives nutrient cycles and plant productivity. The impact of land use on the water cycle has been extensively studied and there is experimental evidence that biodiversity modifies the water cycle in grasslands. However, the combined influences of land-use and associated biodiversity on the water cycle in established land-use systems are unclear. Therefore, we investigated how evapotranspiration (ETa), downward water flux (DF), and capillary rise (CR) in topsoil and subsoil are related to land-use and plant diversity in established, commercially managed grassland and compared these results to findings from experiments where plant diversity was manipulated. In three Central European regions ("Biodiversity Exploratories"), we studied 29 grassland plots (50 m x 50 m; 9-11 plots per region) from 2010 to 2015. The land-use types cover pasture, mown pasture, and meadow in at least triplicate per region. On each plot, we measured soil water contents, meteorological data (hourly resolution), cumulative precipitation (biweekly), plant species richness, the number of plants in the functional groups of grasses, herbs, and legumes (annually), and root biomass (once). Potential evapotranspiration (ETp) was calculated from meteorological data per plot. Missing data points of ETp and soil water contents were estimated with Bayesian hierarchical models. ETa, DF, and CR were calculated for two soil layers with a soil water balance model. The model is based on changes in soil water storage between subsequent observation dates and ETp, which was partitioned between soil layers according to root distribution. Water fluxes in annual resolution were statistically analyzed for land-use and biodiversity effects using repeated-measures analysis of variance (ANOVA). Land-use type did not affect water fluxes. Species richness did not influence DF and CR. DF from topsoil was higher on plots with more grass species, which is opposite to the results from a manipulative biodiversity experiment. The number of grasses and herbs influenced CR into topsoil. ETa from topsoil decreased with increasing species richness while ETa from subsoil increased. Opposing effects on ETa in the two soil layers were also observed for the numbers of herb and legume species. In manipulative biodiversity experiments, opposing effects on ETa from different soil layers are explained by higher plant cover and biomass in species-rich mixtures, reducing evaporation by shading of the topsoil, and deeper roots in species-rich mixtures, facilitating water use and increasing transpiration from subsoil. In our study, biomass decreased with increasing species richness because fertilizer application increased biomass production and decreased species richness. Plots with more grasses showed lower ETa from topsoil than plots with less grasses. However, the within-subject effects indicated higher ETa from topsoil in years with more grasses on individual plots than in years with less grasses. The latter finding complies with the results from a manipulative biodiversity experiment, which has homogeneous soil properties and management. The opposite between-subject effect is probably caused by variations in environmental conditions between plots. This indicates that processes controlling the biodiversity-water cycle relationship vary in real-world systems with environmental conditions, which are largely controlled for in manipulative biodiversity experiments.

Hydrology-oriented forest management trade-offs. A modeling framework coupling field data, simulation results and Bayesian Networks.

PubMed

Garcia-Prats, Alberto; González-Sanchis, María; Del Campo, Antonio D; Lull, Cristina

2018-10-15

Hydrology-oriented forest management sets water as key factor of the forest management for adaptation due to water is the most limiting factor in the Mediterranean forest ecosystems. The aim of this study was to apply Bayesian Network modeling to assess potential indirect effects and trade-offs when hydrology-oriented forest management is applied to a real Mediterranean forest ecosystem. Water, carbon and nitrogen cycles, and forest fire risk were included in the modeling framework. Field data from experimental plots were employed to calibrate and validate the mechanistic Biome-BGCMuSo model that simulates the storage and flux of water, carbon, and nitrogen between the ecosystem and the atmosphere. Many other 50-year long scenarios with different conditions to the ones measured in the field experiment were simulated and the outcomes employed to build the Bayesian Network in a linked chain of models. Hydrology-oriented forest management was very positive insofar as more water was made available to the stand because of an interception reduction. This resource was made available to the stand, which increased the evapotranspiration and its components, the soil water content and a slightly increase of deep percolation. Conversely, Stemflow was drastically reduced. No effect was observed on Runof due to the thinning treatment. The soil organic carbon content was also increased which in turn caused a greater respiration. The long-term effect of the thinning treatment on the LAI was very positive. This was undoubtedly due to the increased vigor generated by the greater availability of water and nutrients for the stand and the reduction of competence between trees. This greater activity resulted in an increase in GPP and vegetation carbon, and therefore, we would expect a higher carbon sequestration. It is worth emphasizing that this extra amount of water and nutrients was taken up by the stand and did not entail any loss of nutrients. Copyright © 2018 Elsevier B.V. All rights reserved.

Unique patellofemoral alignment in a patient with a symptomatic bipartite patella.

PubMed

Ishikawa, Masakazu; Adachi, Nobuo; Deie, Masataka; Nakamae, Atsuo; Nakasa, Tomoyuki; Kamei, Goki; Takazawa, Kobun; Ochi, Mitsuo

2016-01-01

A symptomatic bipartite patella is rarely seen in athletic adolescents or young adults in daily clinical practice. To date, only a limited number of studies have focused on patellofemoral alignment. The current study revealed a unique patellofemoral alignment in a patient with a symptomatic bipartite patella. Twelve patients with 12 symptomatic bipartite patellae who underwent arthroscopic vastus lateralis release (VLR) were investigated (10 males and two females, age: 15.7±4.4years). The radiographic data of contralateral intact and affected knees were reviewed retrospectively. From the lateral- and skyline-view imaging, the following parameters were measured: the congruence angle (CA), the lateral patellofemoral angle (LPA), and the Caton-Deschamps index (CDI). As an additional parameter, the bipartite fragment angle (BFA) was evaluated against the main part of the patella in the skyline view. Compared with the contralateral side, the affected patellae were significantly medialized and laterally tilted (CA: P=0.019; LPA: P=0.016), although there was no significant difference in CDI (P=0.877). This patellar malalignment was found to significantly change after VLR (CA: P=0.001; LPA: P=0.003) and the patellar height was significantly lower than in the preoperative condition (P=0.016). In addition, the BFA significantly shifted to a higher degree after operation (P=0.001). Patients with symptomatic bipartite patellae presented significantly medialized and laterally tilted patellae compared with the contralateral intact side. This malalignment was corrected by VLR, and the alignment of the bipartite fragment was also significantly changed. Level IV, case series. Copyright © 2015 Elsevier B.V. All rights reserved.

Viking Lander imaging investigation: Picture catalog of primary mission experiment data record

NASA Technical Reports Server (NTRS)

Tucker, R. B.

1978-01-01

All the images returned by the two Viking Landers during the primary phase of the Viking Mission are presented. Listings of supplemental information which described the conditions under which the images were acquired are included together with skyline drawings which show where the images are positioned in the field of view of the cameras. Subsets of the images are listed in a variety of sequences to aid in locating images of interest. The format and organization of the digital magnetic tape storage of the images are described. The mission and the camera system are briefly described.

Shuttle Enterprise Flight to New York

NASA Image and Video Library

2012-04-27

Space shuttle Enterprise, mounted atop a NASA 747 Shuttle Carrier Aircraft (SCA), is seen as it flies over the Manhattan Skyline with Freedom Tower in the background, Friday, April 27, 2012, in New York. Enterprise was the first shuttle orbiter built for NASA performing test flights in the atmosphere and was incapable of spaceflight. Originally housed at the Smithsonian's Steven F. Udvar-Hazy Center, Enterprise will be demated from the SCA and placed on a barge that will eventually be moved by tugboat up the Hudson River to the Intrepid Sea, Air & Space Museum in June. Photo Credit: (NASA/Robert Markowitz)

Shuttle Enterprise Flight to New York

NASA Image and Video Library

2012-04-27

Space shuttle Enterprise, mounted atop a NASA 747 Shuttle Carrier Aircraft (SCA), is seen as it flies near the Statue of Liberty and the Manhattan skyline, Friday, April 27, 2012, in New York. Enterprise was the first shuttle orbiter built for NASA performing test flights in the atmosphere and was incapable of spaceflight. Originally housed at the Smithsonian's Steven F. Udvar-Hazy Center, Enterprise will be demated from the SCA and placed on a barge that will eventually be moved by tugboat up the Hudson River to the Intrepid Sea, Air & Space Museum in June. Photo Credit: (NASA/Robert Markowitz)

LiDAR based prediction of forest biomass using hierarchical models with spatially varying coefficients

USGS Publications Warehouse

Babcock, Chad; Finley, Andrew O.; Bradford, John B.; Kolka, Randall K.; Birdsey, Richard A.; Ryan, Michael G.

2015-01-01

Many studies and production inventory systems have shown the utility of coupling covariates derived from Light Detection and Ranging (LiDAR) data with forest variables measured on georeferenced inventory plots through regression models. The objective of this study was to propose and assess the use of a Bayesian hierarchical modeling framework that accommodates both residual spatial dependence and non-stationarity of model covariates through the introduction of spatial random effects. We explored this objective using four forest inventory datasets that are part of the North American Carbon Program, each comprising point-referenced measures of above-ground forest biomass and discrete LiDAR. For each dataset, we considered at least five regression model specifications of varying complexity. Models were assessed based on goodness of fit criteria and predictive performance using a 10-fold cross-validation procedure. Results showed that the addition of spatial random effects to the regression model intercept improved fit and predictive performance in the presence of substantial residual spatial dependence. Additionally, in some cases, allowing either some or all regression slope parameters to vary spatially, via the addition of spatial random effects, further improved model fit and predictive performance. In other instances, models showed improved fit but decreased predictive performance—indicating over-fitting and underscoring the need for cross-validation to assess predictive ability. The proposed Bayesian modeling framework provided access to pixel-level posterior predictive distributions that were useful for uncertainty mapping, diagnosing spatial extrapolation issues, revealing missing model covariates, and discovering locally significant parameters.

bayesPop: Probabilistic Population Projections

PubMed Central

Ševčíková, Hana; Raftery, Adrian E.

2016-01-01

We describe bayesPop, an R package for producing probabilistic population projections for all countries. This uses probabilistic projections of total fertility and life expectancy generated by Bayesian hierarchical models. It produces a sample from the joint posterior predictive distribution of future age- and sex-specific population counts, fertility rates and mortality rates, as well as future numbers of births and deaths. It provides graphical ways of summarizing this information, including trajectory plots and various kinds of probabilistic population pyramids. An expression language is introduced which allows the user to produce the predictive distribution of a wide variety of derived population quantities, such as the median age or the old age dependency ratio. The package produces aggregated projections for sets of countries, such as UN regions or trading blocs. The methodology has been used by the United Nations to produce their most recent official population projections for all countries, published in the World Population Prospects. PMID:28077933

High-resolution gravity model of Venus

NASA Technical Reports Server (NTRS)

Reasenberg, R. D.; Goldberg, Z. M.

1992-01-01

The anomalous gravity field of Venus shows high correlation with surface features revealed by radar. We extract gravity models from the Doppler tracking data from the Pioneer Venus Orbiter by means of a two-step process. In the first step, we solve the nonlinear spacecraft state estimation problem using a Kalman filter-smoother. The Kalman filter has been evaluated through simulations. This evaluation and some unusual features of the filter are discussed. In the second step, we perform a geophysical inversion using a linear Bayesian estimator. To allow an unbiased comparison between gravity and topography, we use a simulation technique to smooth and distort the radar topographic data so as to yield maps having the same characteristics as our gravity maps. The maps presented cover 2/3 of the surface of Venus and display the strong topography-gravity correlation previously reported. The topography-gravity scatter plots show two distinct trends.

An integrated strategy for the quantitative analysis of endogenous proteins: A case of gender-dependent expression of P450 enzymes in rat liver microsome.

PubMed

Shao, Yuhao; Yin, Xiaoxi; Kang, Dian; Shen, Boyu; Zhu, Zhangpei; Li, Xinuo; Li, Haofeng; Xie, Lin; Wang, Guangji; Liang, Yan

2017-08-01

Liquid chromatography mass spectrometry based methods provide powerful tools for protein analysis. Cytochromes P450 (CYPs), the most important drug metabolic enzymes, always exhibit sex-dependent expression patterns and metabolic activities. To date, analysis of CYPs based on mass spectrometry is still facing critical technical challenges due to the complexity and diversity of CYP isoforms besides lack of corresponding standards. The aim of present work consisted in developing a label-free qualitative and quantitative strategy for endogenous proteins, and then applying to the gender-difference study for CYPs in rat liver microsomes (RLMs). Initially, trypsin digested RLM specimens were analyzed by the nanoLC-LTQ-Orbitrap MS/MS. Skyline, an open source and freely available software for targeted proteomics research, was then used to screen the main CYP isoforms in RLMs under a series of criteria automatically, and a total of 40 and 39 CYP isoforms were identified in male and female RLMs, respectively. More importantly, a robust quantitative method in a tandem mass spectrometry-multiple reaction mode (MS/MS-MRM) was built and optimized under the help of Skyline, and successfully applied into the CYP gender difference study in RLMs. In this process, a simple and accurate approach named 'Standard Curve Slope" (SCS) was established based on the difference of standard curve slopes of CYPs between female and male RLMs in order to assess the gender difference of CYPs in RLMs. This presently developed methodology and approach could be widely used in the protein regulation study during drug pharmacological mechanism research. Copyright © 2017 Elsevier B.V. All rights reserved.

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.

Logistic random effects regression models: a comparison of statistical packages for binary and ordinal outcomes.

PubMed

Li, Baoyue; Lingsma, Hester F; Steyerberg, Ewout W; Lesaffre, Emmanuel

2011-05-23

Logistic random effects models are a popular tool to analyze multilevel also called hierarchical data with a binary or ordinal outcome. Here, we aim to compare different statistical software implementations of these models. We used individual patient data from 8509 patients in 231 centers with moderate and severe Traumatic Brain Injury (TBI) enrolled in eight Randomized Controlled Trials (RCTs) and three observational studies. We fitted logistic random effects regression models with the 5-point Glasgow Outcome Scale (GOS) as outcome, both dichotomized as well as ordinal, with center and/or trial as random effects, and as covariates age, motor score, pupil reactivity or trial. We then compared the implementations of frequentist and Bayesian methods to estimate the fixed and random effects. Frequentist approaches included R (lme4), Stata (GLLAMM), SAS (GLIMMIX and NLMIXED), MLwiN ([R]IGLS) and MIXOR, Bayesian approaches included WinBUGS, MLwiN (MCMC), R package MCMCglmm and SAS experimental procedure MCMC.Three data sets (the full data set and two sub-datasets) were analysed using basically two logistic random effects models with either one random effect for the center or two random effects for center and trial. For the ordinal outcome in the full data set also a proportional odds model with a random center effect was fitted. The packages gave similar parameter estimates for both the fixed and random effects and for the binary (and ordinal) models for the main study and when based on a relatively large number of level-1 (patient level) data compared to the number of level-2 (hospital level) data. However, when based on relatively sparse data set, i.e. when the numbers of level-1 and level-2 data units were about the same, the frequentist and Bayesian approaches showed somewhat different results. The software implementations differ considerably in flexibility, computation time, and usability. There are also differences in the availability of additional tools for model evaluation, such as diagnostic plots. The experimental SAS (version 9.2) procedure MCMC appeared to be inefficient. On relatively large data sets, the different software implementations of logistic random effects regression models produced similar results. Thus, for a large data set there seems to be no explicit preference (of course if there is no preference from a philosophical point of view) for either a frequentist or Bayesian approach (if based on vague priors). The choice for a particular implementation may largely depend on the desired flexibility, and the usability of the package. For small data sets the random effects variances are difficult to estimate. In the frequentist approaches the MLE of this variance was often estimated zero with a standard error that is either zero or could not be determined, while for Bayesian methods the estimates could depend on the chosen "non-informative" prior of the variance parameter. The starting value for the variance parameter may be also critical for the convergence of the Markov chain.

Beyond context to the skyline: thinking in 3D.

PubMed

Hoagwood, Kimberly; Olin, Serene; Cleek, Andrew

2013-01-01

Sweeping and profound structural, regulatory, and fiscal changes are rapidly reshaping the contours of health and mental health practice. The community-based practice contexts described in the excellent review by Garland and colleagues are being fundamentally altered with different business models, regional networks, accountability standards, and incentive structures. If community-based mental health services are to remain viable, the two-dimensional and flat research and practice paradigm has to be replaced with three-dimensional thinking. Failure to take seriously the changes that are happening to the larger healthcare context and respond actively through significant system redesign will lead to the demise of specialty mental health services.

Viking lander imaging investigation during extended and continuation automatic missions. Volume 2: Lander 2 picture catalog of experiment data record

NASA Technical Reports Server (NTRS)

Jones, K. L.; Henshaw, M.; Mcmenomy, C.; Robles, A.; Scribner, P. C.; Wall, S. D.; Wilson, J. W.

1981-01-01

Images returned by the two Viking landers during the extended and continuation automatic phases of the Viking Mission are presented. Information describing the conditions under which the images were acquired is included with skyline drawings showing the images positioned in the field of view of the cameras. Subsets of the images are listed in a variety of sequences to aid in locating images of interest. The format and organization of the digital magnetic tape storage of the images are described. A brief description of the mission and the camera system is also included.

Viking lander imaging investigation during extended and continuation automatic missions. Volume 1: Lander 1 picture catalog of experiment data record

NASA Technical Reports Server (NTRS)

Jones, K. L.; Henshaw, M.; Mcmenomy, C.; Robles, A.; Scribner, P. C.; Wall, S. D.; Wilson, J. W.

1981-01-01

All images returned by Viking Lander 1 during the extended and continuation automatic phases of the Viking Mission are presented. Listings of supplemental information which describe the conditions under which the images were acquired are included together with skyline drawings which show where the images are positioned in the field of view of the cameras. Subsets of the images are listed in a variety of sequences to aid in locating images of interest. The format and organization of the digital magnetic tape storage of the images are described as well as the mission and the camera system.

Response of Demographic Rates of Tropical Trees to Light Availability: Can Position-Based Competition Indices Replace Information from Canopy Census Data?

PubMed Central

Grote, Steffi; Condit, Richard; Hubbell, Stephen; Wirth, Christian; Rüger, Nadja

2013-01-01

For trees in tropical forests, competition for light is thought to be a central process that offers opportunities for niche differentiation through light gradient partitioning. In previous studies, a canopy index based on three-dimensional canopy census data has been shown to be a good predictor of species-specific demographic rates across the entire tree community on Barro Colorado Island, Panama, and has allowed quantifying between-species variation in light response. However, almost all other forest census plots lack data on the canopy structure. Hence, this study aims at assessing whether position-based neighborhood competition indices can replace information from canopy census data and produce similar estimates of the interspecific variation of light responses. We used inventory data from the census plot at Barro Colorado Island and calculated neighborhood competition indices with varying relative effects of the size and distance of neighboring trees. Among these indices, we selected the one that was most strongly correlated with the canopy index. We then compared outcomes of hierarchical Bayesian models for species-specific recruitment and growth rates including either the canopy index or the selected neighborhood competition index as predictor. Mean posterior estimates of light response parameters were highly correlated between models (r>0.85) and indicated that most species regenerate and grow better in higher light. Both light estimation approaches consistently found that the interspecific variation of light response was larger for recruitment than for growth rates. However, the classification of species into different groups of light response, e.g. weaker than linear (decelerating) vs. stronger than linear (accelerating) differed between approaches. These results imply that while the classification into light response groups might be biased when using neighborhood competition indices, they may be useful for determining species rankings and between-species variation of light response and therefore enable large comparative studies between different forest census plots. PMID:24324723

Characterizing Oscillatory Bursts in Single-Trial EEG Data

NASA Technical Reports Server (NTRS)

Knuth, K. H.; Shah, A. S.; Lakatos, P.; Schroeder, C. E.

2004-01-01

Oscillatory bursts in numerous bands ranging from low (theta) to high frequencies (e.g., gamma) undoubtedly play an important role in cortical dynamics. Largely because of the inadequacy of existing analytic techniques. however, oscillatory bursts and their role in cortical processing remains poorly understood. To study oscillatory bursts effectively one must be able to isolate them and characterize them in the single trial. We describe a series of straightforward analysis techniques that produce useful indices of burst characteristics. First, stimulus-evoked responses are estimated using Differentially Variable Component Analysis (dVCA), and are subtracted from the single-trial. The single-trial characteristics of the evoked responses are stored to identify possible correlations with burst activity. Time-frequency (T-F), or wavelet, analyses are then applied to the single trial residuals. While T-F plots have been used in recent studies to identify and isolate bursts, we go further by fitting each burst in the T-F plot with a two-dimensional Gaussian. This provides a set of burst characteristics, such as, center time. burst duration, center frequency. frequency dispersion. and amplitude, all of which contribute to the accurate characterization of the individual burst. The burst phase can also be estimated. Burst characteristics can be quantified with several standard techniques (e.g.. histogramming and clustering), as well as Bayesian techniques (e.g., blocking) to allow a more parametric description analysis of the characteristics of oscillatory bursts, and the relationships of specific parameters to cortical excitability and stimulus integration.

Bayesian ISOLA: new tool for automated centroid moment tensor inversion

NASA Astrophysics Data System (ADS)

Vackář, Jiří; Burjánek, Jan; Gallovič, František; Zahradník, Jiří; Clinton, John

2017-04-01

Focal mechanisms are important for understanding seismotectonics of a region, and they serve as a basic input for seismic hazard assessment. Usually, the point source approximation and the moment tensor (MT) are used. We have developed a new, fully automated tool for the centroid moment tensor (CMT) inversion in a Bayesian framework. It includes automated data retrieval, data selection where station components with various instrumental disturbances and high signal-to-noise are rejected, and full-waveform inversion in a space-time grid around a provided hypocenter. The method is innovative in the following aspects: (i) The CMT inversion is fully automated, no user interaction is required, although the details of the process can be visually inspected latter on many figures which are automatically plotted.(ii) The automated process includes detection of disturbances based on MouseTrap code, so disturbed recordings do not affect inversion.(iii) A data covariance matrix calculated from pre-event noise yields an automated weighting of the station recordings according to their noise levels and also serves as an automated frequency filter suppressing noisy frequencies.(iv) Bayesian approach is used, so not only the best solution is obtained, but also the posterior probability density function.(v) A space-time grid search effectively combined with the least-squares inversion of moment tensor components speeds up the inversion and allows to obtain more accurate results compared to stochastic methods. The method has been tested on synthetic and observed data. It has been tested by comparison with manually processed moment tensors of all events greater than M≥3 in the Swiss catalogue over 16 years using data available at the Swiss data center (http://arclink.ethz.ch). The quality of the results of the presented automated process is comparable with careful manual processing of data. The software package programmed in Python has been designed to be as versatile as possible in order to be applicable in various networks ranging from local to regional. The method can be applied either to the everyday network data flow, or to process large previously existing earthquake catalogues and data sets.

A flexible Bayesian hierarchical model of preterm birth risk among US Hispanic subgroups in relation to maternal nativity and education

PubMed Central

2011-01-01

Background Previous research has documented heterogeneity in the effects of maternal education on adverse birth outcomes by nativity and Hispanic subgroup in the United States. In this article, we considered the risk of preterm birth (PTB) using 9 years of vital statistics birth data from New York City. We employed finer categorizations of exposure than used previously and estimated the risk dose-response across the range of education by nativity and ethnicity. Methods Using Bayesian random effects logistic regression models with restricted quadratic spline terms for years of completed maternal education, we calculated and plotted the estimated posterior probabilities of PTB (gestational age < 37 weeks) for each year of education by ethnic and nativity subgroups adjusted for only maternal age, as well as with more extensive covariate adjustments. We then estimated the posterior risk difference between native and foreign born mothers by ethnicity over the continuous range of education exposures. Results The risk of PTB varied substantially by education, nativity and ethnicity. Native born groups showed higher absolute risk of PTB and declining risk associated with higher levels of education beyond about 10 years, as did foreign-born Puerto Ricans. For most other foreign born groups, however, risk of PTB was flatter across the education range. For Mexicans, Central Americans, Dominicans, South Americans and "Others", the protective effect of foreign birth diminished progressively across the educational range. Only for Puerto Ricans was there no nativity advantage for the foreign born, although small numbers of foreign born Cubans limited precision of estimates for that group. Conclusions Using flexible Bayesian regression models with random effects allowed us to estimate absolute risks without strong modeling assumptions. Risk comparisons for any sub-groups at any exposure level were simple to calculate. Shrinkage of posterior estimates through the use of random effects allowed for finer categorization of exposures without restricting joint effects to follow a fixed parametric scale. Although foreign born Hispanic women with the least education appeared to generally have low risk, this seems likely to be a marker for unmeasured environmental and behavioral factors, rather than a causally protective effect of low education itself. PMID:21504612

A flexible Bayesian hierarchical model of preterm birth risk among US Hispanic subgroups in relation to maternal nativity and education.

PubMed

Kaufman, Jay S; MacLehose, Richard F; Torrone, Elizabeth A; Savitz, David A

2011-04-19

Previous research has documented heterogeneity in the effects of maternal education on adverse birth outcomes by nativity and Hispanic subgroup in the United States. In this article, we considered the risk of preterm birth (PTB) using 9 years of vital statistics birth data from New York City. We employed finer categorizations of exposure than used previously and estimated the risk dose-response across the range of education by nativity and ethnicity. Using Bayesian random effects logistic regression models with restricted quadratic spline terms for years of completed maternal education, we calculated and plotted the estimated posterior probabilities of PTB (gestational age < 37 weeks) for each year of education by ethnic and nativity subgroups adjusted for only maternal age, as well as with more extensive covariate adjustments. We then estimated the posterior risk difference between native and foreign born mothers by ethnicity over the continuous range of education exposures. The risk of PTB varied substantially by education, nativity and ethnicity. Native born groups showed higher absolute risk of PTB and declining risk associated with higher levels of education beyond about 10 years, as did foreign-born Puerto Ricans. For most other foreign born groups, however, risk of PTB was flatter across the education range. For Mexicans, Central Americans, Dominicans, South Americans and "Others", the protective effect of foreign birth diminished progressively across the educational range. Only for Puerto Ricans was there no nativity advantage for the foreign born, although small numbers of foreign born Cubans limited precision of estimates for that group. Using flexible Bayesian regression models with random effects allowed us to estimate absolute risks without strong modeling assumptions. Risk comparisons for any sub-groups at any exposure level were simple to calculate. Shrinkage of posterior estimates through the use of random effects allowed for finer categorization of exposures without restricting joint effects to follow a fixed parametric scale. Although foreign born Hispanic women with the least education appeared to generally have low risk, this seems likely to be a marker for unmeasured environmental and behavioral factors, rather than a causally protective effect of low education itself.

The Development of Bayesian Theory and Its Applications in Business and Bioinformatics

NASA Astrophysics Data System (ADS)

Zhang, Yifei

2018-03-01

Bayesian Theory originated from an Essay of a British mathematician named Thomas Bayes in 1763, and after its development in 20th century, Bayesian Statistics has been taking a significant part in statistical study of all fields. Due to the recent breakthrough of high-dimensional integral, Bayesian Statistics has been improved and perfected, and now it can be used to solve problems that Classical Statistics failed to solve. This paper summarizes Bayesian Statistics’ history, concepts and applications, which are illustrated in five parts: the history of Bayesian Statistics, the weakness of Classical Statistics, Bayesian Theory and its development and applications. The first two parts make a comparison between Bayesian Statistics and Classical Statistics in a macroscopic aspect. And the last three parts focus on Bayesian Theory in specific -- from introducing some particular Bayesian Statistics’ concepts to listing their development and finally their applications.

Bayesian demography 250 years after Bayes

PubMed Central

Bijak, Jakub; Bryant, John

2016-01-01

Bayesian statistics offers an alternative to classical (frequentist) statistics. It is distinguished by its use of probability distributions to describe uncertain quantities, which leads to elegant solutions to many difficult statistical problems. Although Bayesian demography, like Bayesian statistics more generally, is around 250 years old, only recently has it begun to flourish. The aim of this paper is to review the achievements of Bayesian demography, address some misconceptions, and make the case for wider use of Bayesian methods in population studies. We focus on three applications: demographic forecasts, limited data, and highly structured or complex models. The key advantages of Bayesian methods are the ability to integrate information from multiple sources and to describe uncertainty coherently. Bayesian methods also allow for including additional (prior) information next to the data sample. As such, Bayesian approaches are complementary to many traditional methods, which can be productively re-expressed in Bayesian terms. PMID:26902889

Statistical design and analysis for plant cover studies with multiple sources of observation errors

USGS Publications Warehouse

Wright, Wilson; Irvine, Kathryn M.; Warren, Jeffrey M .; Barnett, Jenny K.

2017-01-01

Effective wildlife habitat management and conservation requires understanding the factors influencing distribution and abundance of plant species. Field studies, however, have documented observation errors in visually estimated plant cover including measurements which differ from the true value (measurement error) and not observing a species that is present within a plot (detection error). Unlike the rapid expansion of occupancy and N-mixture models for analysing wildlife surveys, development of statistical models accounting for observation error in plants has not progressed quickly. Our work informs development of a monitoring protocol for managed wetlands within the National Wildlife Refuge System.Zero-augmented beta (ZAB) regression is the most suitable method for analysing areal plant cover recorded as a continuous proportion but assumes no observation errors. We present a model extension that explicitly includes the observation process thereby accounting for both measurement and detection errors. Using simulations, we compare our approach to a ZAB regression that ignores observation errors (naïve model) and an “ad hoc” approach using a composite of multiple observations per plot within the naïve model. We explore how sample size and within-season revisit design affect the ability to detect a change in mean plant cover between 2 years using our model.Explicitly modelling the observation process within our framework produced unbiased estimates and nominal coverage of model parameters. The naïve and “ad hoc” approaches resulted in underestimation of occurrence and overestimation of mean cover. The degree of bias was primarily driven by imperfect detection and its relationship with cover within a plot. Conversely, measurement error had minimal impacts on inferences. We found >30 plots with at least three within-season revisits achieved reasonable posterior probabilities for assessing change in mean plant cover.For rapid adoption and application, code for Bayesian estimation of our single-species ZAB with errors model is included. Practitioners utilizing our R-based simulation code can explore trade-offs among different survey efforts and parameter values, as we did, but tuned to their own investigation. Less abundant plant species of high ecological interest may warrant the additional cost of gathering multiple independent observations in order to guard against erroneous conclusions.

Model Diagnostics for Bayesian Networks

ERIC Educational Resources Information Center

Sinharay, Sandip

2006-01-01

Bayesian networks are frequently used in educational assessments primarily for learning about students' knowledge and skills. There is a lack of works on assessing fit of Bayesian networks. This article employs the posterior predictive model checking method, a popular Bayesian model checking tool, to assess fit of simple Bayesian networks. A…

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

The neglected tool in the Bayesian ecologist's shed: a case study testing informative priors' effect on model accuracy

PubMed Central

Morris, William K; Vesk, Peter A; McCarthy, Michael A; Bunyavejchewin, Sarayudh; Baker, Patrick J

2015-01-01

Despite benefits for precision, ecologists rarely use informative priors. One reason that ecologists may prefer vague priors is the perception that informative priors reduce accuracy. To date, no ecological study has empirically evaluated data-derived informative priors' effects on precision and accuracy. To determine the impacts of priors, we evaluated mortality models for tree species using data from a forest dynamics plot in Thailand. Half the models used vague priors, and the remaining half had informative priors. We found precision was greater when using informative priors, but effects on accuracy were more variable. In some cases, prior information improved accuracy, while in others, it was reduced. On average, models with informative priors were no more or less accurate than models without. Our analyses provide a detailed case study on the simultaneous effect of prior information on precision and accuracy and demonstrate that when priors are specified appropriately, they lead to greater precision without systematically reducing model accuracy. PMID:25628867

The neglected tool in the Bayesian ecologist's shed: a case study testing informative priors' effect on model accuracy.

PubMed

Morris, William K; Vesk, Peter A; McCarthy, Michael A; Bunyavejchewin, Sarayudh; Baker, Patrick J

2015-01-01

Despite benefits for precision, ecologists rarely use informative priors. One reason that ecologists may prefer vague priors is the perception that informative priors reduce accuracy. To date, no ecological study has empirically evaluated data-derived informative priors' effects on precision and accuracy. To determine the impacts of priors, we evaluated mortality models for tree species using data from a forest dynamics plot in Thailand. Half the models used vague priors, and the remaining half had informative priors. We found precision was greater when using informative priors, but effects on accuracy were more variable. In some cases, prior information improved accuracy, while in others, it was reduced. On average, models with informative priors were no more or less accurate than models without. Our analyses provide a detailed case study on the simultaneous effect of prior information on precision and accuracy and demonstrate that when priors are specified appropriately, they lead to greater precision without systematically reducing model accuracy.

Calculating system reliability with SRFYDO

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

Morzinski, Jerome; Anderson - Cook, Christine M; Klamann, Richard M

2010-01-01

SRFYDO is a process for estimating reliability of complex systems. Using information from all applicable sources, including full-system (flight) data, component test data, and expert (engineering) judgment, SRFYDO produces reliability estimates and predictions. It is appropriate for series systems with possibly several versions of the system which share some common components. It models reliability as a function of age and up to 2 other lifecycle (usage) covariates. Initial output from its Exploratory Data Analysis mode consists of plots and numerical summaries so that the user can check data entry and model assumptions, and help determine a final form for themore » system model. The System Reliability mode runs a complete reliability calculation using Bayesian methodology. This mode produces results that estimate reliability at the component, sub-system, and system level. The results include estimates of uncertainty, and can predict reliability at some not-too-distant time in the future. This paper presents an overview of the underlying statistical model for the analysis, discusses model assumptions, and demonstrates usage of SRFYDO.« less

Genetic diversity and structure of Capparis spinosa L. in Iran as revealed by ISSR markers.

PubMed

Ahmadi, Maryam; Saeidi, Hojjatollah

2018-05-01

Capparis spinosa L. (caper bush) is an economically and ecologically important perennial shrub that grows across different regions of Iran. In this study, the genetic diversity and population structure of Iranian genepool of C. spinosa is evaluated using Inter Simple Sequence Repeat (ISSR) markers. Using 10 ISSR primers, 387 DNA fragments (bands) were amplified from the genomic DNA of 92 individuals belonging to twenty-one populations of C . spinosa , of which 378 (97.7%) were polymorphic. High level of genetic diversity (percentage of polymorphic loci = 98.2%, h = 0.1382, I = 0.243), high genetic differentiation (G st  = 0.5234) and low gene flow (Nm = 0.4553) among populations were observed. Caper bush populations were divided into 4 groups in the dendrogram, PCoA plot and Bayesian clustering results, mostly corresponded to their geographic regions. The results showed that there are value in sampling Iranian caper bush populations to look for valuable alleles for use in plant breeding programs.

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…

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.

The current state of Bayesian methods in medical product development: survey results and recommendations from the DIA Bayesian Scientific Working Group.

PubMed

Natanegara, Fanni; Neuenschwander, Beat; Seaman, John W; Kinnersley, Nelson; Heilmann, Cory R; Ohlssen, David; Rochester, George

2014-01-01

Bayesian applications in medical product development have recently gained popularity. Despite many advances in Bayesian methodology and computations, increase in application across the various areas of medical product development has been modest. The DIA Bayesian Scientific Working Group (BSWG), which includes representatives from industry, regulatory agencies, and academia, has adopted the vision to ensure Bayesian methods are well understood, accepted more broadly, and appropriately utilized to improve decision making and enhance patient outcomes. As Bayesian applications in medical product development are wide ranging, several sub-teams were formed to focus on various topics such as patient safety, non-inferiority, prior specification, comparative effectiveness, joint modeling, program-wide decision making, analytical tools, and education. The focus of this paper is on the recent effort of the BSWG Education sub-team to administer a Bayesian survey to statisticians across 17 organizations involved in medical product development. We summarize results of this survey, from which we provide recommendations on how to accelerate progress in Bayesian applications throughout medical product development. The survey results support findings from the literature and provide additional insight on regulatory acceptance of Bayesian methods and information on the need for a Bayesian infrastructure within an organization. The survey findings support the claim that only modest progress in areas of education and implementation has been made recently, despite substantial progress in Bayesian statistical research and software availability. Copyright © 2013 John Wiley & Sons, Ltd.

Logistic random effects regression models: a comparison of statistical packages for binary and ordinal outcomes

PubMed Central

2011-01-01

Background Logistic random effects models are a popular tool to analyze multilevel also called hierarchical data with a binary or ordinal outcome. Here, we aim to compare different statistical software implementations of these models. Methods We used individual patient data from 8509 patients in 231 centers with moderate and severe Traumatic Brain Injury (TBI) enrolled in eight Randomized Controlled Trials (RCTs) and three observational studies. We fitted logistic random effects regression models with the 5-point Glasgow Outcome Scale (GOS) as outcome, both dichotomized as well as ordinal, with center and/or trial as random effects, and as covariates age, motor score, pupil reactivity or trial. We then compared the implementations of frequentist and Bayesian methods to estimate the fixed and random effects. Frequentist approaches included R (lme4), Stata (GLLAMM), SAS (GLIMMIX and NLMIXED), MLwiN ([R]IGLS) and MIXOR, Bayesian approaches included WinBUGS, MLwiN (MCMC), R package MCMCglmm and SAS experimental procedure MCMC. Three data sets (the full data set and two sub-datasets) were analysed using basically two logistic random effects models with either one random effect for the center or two random effects for center and trial. For the ordinal outcome in the full data set also a proportional odds model with a random center effect was fitted. Results The packages gave similar parameter estimates for both the fixed and random effects and for the binary (and ordinal) models for the main study and when based on a relatively large number of level-1 (patient level) data compared to the number of level-2 (hospital level) data. However, when based on relatively sparse data set, i.e. when the numbers of level-1 and level-2 data units were about the same, the frequentist and Bayesian approaches showed somewhat different results. The software implementations differ considerably in flexibility, computation time, and usability. There are also differences in the availability of additional tools for model evaluation, such as diagnostic plots. The experimental SAS (version 9.2) procedure MCMC appeared to be inefficient. Conclusions On relatively large data sets, the different software implementations of logistic random effects regression models produced similar results. Thus, for a large data set there seems to be no explicit preference (of course if there is no preference from a philosophical point of view) for either a frequentist or Bayesian approach (if based on vague priors). The choice for a particular implementation may largely depend on the desired flexibility, and the usability of the package. For small data sets the random effects variances are difficult to estimate. In the frequentist approaches the MLE of this variance was often estimated zero with a standard error that is either zero or could not be determined, while for Bayesian methods the estimates could depend on the chosen "non-informative" prior of the variance parameter. The starting value for the variance parameter may be also critical for the convergence of the Markov chain. PMID:21605357

Constraint of soil moisture on CO2 efflux from tundra lichen, moss, and tussock in Council, Alaska using a hierarchical Bayesian model

NASA Astrophysics Data System (ADS)

Kim, Y.; Nishina, K.; Chae, N.; Park, S.; Yoon, Y.; Lee, B.

2014-04-01

The tundra ecosystem is quite vulnerable to drastic climate change in the Arctic, and the quantification of carbon dynamics is of significant importance in response to thawing permafrost, changes in the snow-covered period and snow and shrub community extent, and the decline of sea ice in the Arctic. Here, CO2 efflux measurements using a manual chamber system within a 40 m × 40 m (5 m interval; 81 total points) plot were conducted in dominant tundra vegetation on the Seward Peninsula of Alaska, during the growing seasons of 2011 and 2012, for the assessment of the driving parameters of CO2 efflux. We applied a hierarchical Bayesian (HB) model - which is a function of soil temperature, soil moisture, vegetation type and thaw depth - to quantify the effect of environmental parameters on CO2 efflux, and to estimate growing season CO2 emission. Our results showed that average CO2 efflux in 2011 is 1.4-fold higher than in 2012, resulting from the distinct difference in soil moisture between the two years. Tussock-dominated CO2 efflux is 1.4 to 2.3 times higher than those measured in lichen and moss communities, reflecting tussock as a significant CO2 source in the Arctic, with wide area distribution on a circumpolar scale. CO2 efflux followed soil temperature nearly exponentially from both the observed data and the posterior medians of the HB model. This reveals soil temperature as the most important parameter in regulating CO2 efflux, rather than soil moisture and thaw depth. Obvious changes in soil moisture during the growing seasons of 2011 and 2012 resulted in an explicit difference in CO2 efflux - 742 and 539 g CO2 m-2 period-1 in 2011 and 2012, respectively, suggesting that the 2012 CO2 emission rate was constrained by 27% (95% credible interval: 17-36%) compared to 2011, due to higher soil moisture from severe rain. Estimated growing season CO2 emission rate ranged from 0.86 Mg CO2 period-1 in 2012 to 1.2 Mg CO2 period-1 in 2011 within a 40 m × 40 m plot, corresponding to 86% and 80% of the annual CO2 emission rates within the Alaska western tundra ecosystem. Therefore, the HB model can be readily applied to observed CO2 efflux, as it demands only four environmental parameters and can also be effective for quantitatively assessing the driving parameters of CO2 efflux.

On the Adequacy of Bayesian Evaluations of Categorization Models: Reply to Vanpaemel and Lee (2012)

ERIC Educational Resources Information Center

Wills, Andy J.; Pothos, Emmanuel M.

2012-01-01

Vanpaemel and Lee (2012) argued, and we agree, that the comparison of formal models can be facilitated by Bayesian methods. However, Bayesian methods neither precede nor supplant our proposals (Wills & Pothos, 2012), as Bayesian methods can be applied both to our proposals and to their polar opposites. Furthermore, the use of Bayesian methods to…

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.

Post-Fire Spatial Patterns of Soil Nitrogen Mineralization and Microbial Abundance

PubMed Central

Smithwick, Erica A. H.; Naithani, Kusum J.; Balser, Teri C.; Romme, William H.; Turner, Monica G.

2012-01-01

Stand-replacing fires influence soil nitrogen availability and microbial community composition, which may in turn mediate post-fire successional dynamics and nutrient cycling. However, fires create patchiness at both local and landscape scales and do not result in consistent patterns of ecological dynamics. The objectives of this study were to (1) quantify the spatial structure of microbial communities in forest stands recently affected by stand-replacing fire and (2) determine whether microbial variables aid predictions of in situ net nitrogen mineralization rates in recently burned stands. The study was conducted in lodgepole pine (Pinus contorta var. latifolia) and Engelmann spruce/subalpine fir (Picea engelmannii/Abies lasiocarpa) forest stands that burned during summer 2000 in Greater Yellowstone (Wyoming, USA). Using a fully probabilistic spatial process model and Bayesian kriging, the spatial structure of microbial lipid abundance and fungi-to-bacteria ratios were found to be spatially structured within plots two years following fire (for most plots, autocorrelation range varied from 1.5 to 10.5 m). Congruence of spatial patterns among microbial variables, in situ net N mineralization, and cover variables was evident. Stepwise regression resulted in significant models of in situ net N mineralization and included variables describing fungal and bacterial abundance, although explained variance was low (R2<0.29). Unraveling complex spatial patterns of nutrient cycling and the biotic factors that regulate it remains challenging but is critical for explaining post-fire ecosystem function, especially in Greater Yellowstone, which is projected to experience increased fire frequencies by mid 21st Century. PMID:23226324

Genet-specific DNA methylation probabilities detected in a spatial epigenetic analysis of a clonal plant population.

PubMed

Araki, Kiwako S; Kubo, Takuya; Kudoh, Hiroshi

2017-01-01

In sessile organisms such as plants, spatial genetic structures of populations show long-lasting patterns. These structures have been analyzed across diverse taxa to understand the processes that determine the genetic makeup of organismal populations. For many sessile organisms that mainly propagate via clonal spread, epigenetic status can vary between clonal individuals in the absence of genetic changes. However, fewer previous studies have explored the epigenetic properties in comparison to the genetic properties of natural plant populations. Here, we report the simultaneous evaluation of the spatial structure of genetic and epigenetic variation in a natural population of the clonal plant Cardamine leucantha. We applied a hierarchical Bayesian model to evaluate the effects of membership of a genet (a group of individuals clonally derived from a single seed) and vegetation cover on the epigenetic variation between ramets (clonal plants that are physiologically independent individuals). We sampled 332 ramets in a 20 m × 20 m study plot that contained 137 genets (identified using eight SSR markers). We detected epigenetic variation in DNA methylation at 24 methylation-sensitive amplified fragment length polymorphism (MS-AFLP) loci. There were significant genet effects at all 24 MS-AFLP loci in the distribution of subepiloci. Vegetation cover had no statistically significant effect on variation in the majority of MS-AFLP loci. The spatial aggregation of epigenetic variation is therefore largely explained by the aggregation of ramets that belong to the same genets. By applying hierarchical Bayesian analyses, we successfully identified a number of genet-specific changes in epigenetic status within a natural plant population in a complex context, where genotypes and environmental factors are unevenly distributed. This finding suggests that it requires further studies on the spatial epigenetic structure of natural populations of diverse organisms, particularly for sessile clonal species.

HELP: XID+, the probabilistic de-blender for Herschel SPIRE maps

NASA Astrophysics Data System (ADS)

Hurley, P. D.; Oliver, S.; Betancourt, M.; Clarke, C.; Cowley, W. I.; Duivenvoorden, S.; Farrah, D.; Griffin, M.; Lacey, C.; Le Floc'h, E.; Papadopoulos, A.; Sargent, M.; Scudder, J. M.; Vaccari, M.; Valtchanov, I.; Wang, L.

2017-01-01

We have developed a new prior-based source extraction tool, XID+, to carry out photometry in the Herschel SPIRE (Spectral and Photometric Imaging Receiver) maps at the positions of known sources. XID+ is developed using a probabilistic Bayesian framework that provides a natural framework in which to include prior information, and uses the Bayesian inference tool Stan to obtain the full posterior probability distribution on flux estimates. In this paper, we discuss the details of XID+ and demonstrate the basic capabilities and performance by running it on simulated SPIRE maps resembling the COSMOS field, and comparing to the current prior-based source extraction tool DESPHOT. Not only we show that XID+ performs better on metrics such as flux accuracy and flux uncertainty accuracy, but we also illustrate how obtaining the posterior probability distribution can help overcome some of the issues inherent with maximum-likelihood-based source extraction routines. We run XID+ on the COSMOS SPIRE maps from Herschel Multi-Tiered Extragalactic Survey using a 24-μm catalogue as a positional prior, and a uniform flux prior ranging from 0.01 to 1000 mJy. We show the marginalized SPIRE colour-colour plot and marginalized contribution to the cosmic infrared background at the SPIRE wavelengths. XID+ is a core tool arising from the Herschel Extragalactic Legacy Project (HELP) and we discuss how additional work within HELP providing prior information on fluxes can and will be utilized. The software is available at https://github.com/H-E-L-P/XID_plus. We also provide the data product for COSMOS. We believe this is the first time that the full posterior probability of galaxy photometry has been provided as a data product.

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 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.

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

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.

A Bayesian-frequentist two-stage single-arm phase II clinical trial design.

PubMed

Dong, Gaohong; Shih, Weichung Joe; Moore, Dirk; Quan, Hui; Marcella, Stephen

2012-08-30

It is well-known that both frequentist and Bayesian clinical trial designs have their own advantages and disadvantages. To have better properties inherited from these two types of designs, we developed a Bayesian-frequentist two-stage single-arm phase II clinical trial design. This design allows both early acceptance and rejection of the null hypothesis ( H(0) ). The measures (for example probability of trial early termination, expected sample size, etc.) of the design properties under both frequentist and Bayesian settings are derived. Moreover, under the Bayesian setting, the upper and lower boundaries are determined with predictive probability of trial success outcome. Given a beta prior and a sample size for stage I, based on the marginal distribution of the responses at stage I, we derived Bayesian Type I and Type II error rates. By controlling both frequentist and Bayesian error rates, the Bayesian-frequentist two-stage design has special features compared with other two-stage designs. Copyright © 2012 John Wiley & Sons, Ltd.

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.

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.

A local approach for focussed Bayesian fusion

NASA Astrophysics Data System (ADS)

Sander, Jennifer; Heizmann, Michael; Goussev, Igor; Beyerer, Jürgen

2009-04-01

Local Bayesian fusion approaches aim to reduce high storage and computational costs of Bayesian fusion which is separated from fixed modeling assumptions. Using the small world formalism, we argue why this proceeding is conform with Bayesian theory. Then, we concentrate on the realization of local Bayesian fusion by focussing the fusion process solely on local regions that are task relevant with a high probability. The resulting local models correspond then to restricted versions of the original one. In a previous publication, we used bounds for the probability of misleading evidence to show the validity of the pre-evaluation of task specific knowledge and prior information which we perform to build local models. In this paper, we prove the validity of this proceeding using information theoretic arguments. For additional efficiency, local Bayesian fusion can be realized in a distributed manner. Here, several local Bayesian fusion tasks are evaluated and unified after the actual fusion process. For the practical realization of distributed local Bayesian fusion, software agents are predestinated. There is a natural analogy between the resulting agent based architecture and criminal investigations in real life. We show how this analogy can be used to improve the efficiency of distributed local Bayesian fusion additionally. Using a landscape model, we present an experimental study of distributed local Bayesian fusion in the field of reconnaissance, which highlights its high potential.

A Hierarchical Analysis of Tree Growth and Environmental Drivers Across Eastern US Temperate Forests

NASA Astrophysics Data System (ADS)

Mantooth, J.; Dietze, M.

2014-12-01

Improving predictions of how forests in the eastern United States will respond to future global change requires a better understanding of the drivers of variability in tree growth rates. Current inventory data lack the temporal resolution to characterize interannual variability, while existing growth records lack the extent required to assess spatial scales of variability. Therefore, we established a network of forest inventory plots across ten sites across the eastern US, and measured growth in adult trees using increment cores. Sites were chosen to maximize climate space explored, while within sites, plots were spread across primary environmental gradients to explore landscape-level variability in growth. Using the annual growth record available from tree cores, we explored the responses of trees to multiple environmental covariates over multiple spatial and temporal scales. We hypothesized that within and across sites growth rates vary among species, and that intraspecific growth rates increase with temperature along a species' range. We also hypothesized that trees show synchrony in growth responses to landscape-scale climatic changes. Initial analyses of growth increments indicate that across sites, trees with intermediate shade tolerance, e.g. Red Oak (Quercus rubra), tend to have the highest growth rates. At the site level, there is evidence for synchrony in response to large-scale climatic events (e.g. prolonged drought and above average temperatures). However, growth responses to climate at the landscape scale have yet to be detected. Our current analysis utilizes hierarchical Bayesian state-space modeling to focus on growth responses of adult trees to environmental covariates at multiple spatial and temporal scales. This predictive model of tree growth currently incorporates observed effects at the individual, plot, site, and landscape scale. Current analysis using this model shows a potential slowing of growth in the past decade for two sites in the northeastern US (Harvard Forest and Bartlett Experimental Forest), however more work is required to determine the robustness of this trend. Finally, these observations are being incorporated into ecosystem models using the Brown Dog informatics tools and the Predictive Ecosystem Analyzer (PEcAn) data assimilation workflow.

Comparison of two matrix data structures for advanced CSM testbed applications

NASA Technical Reports Server (NTRS)

Regelbrugge, M. E.; Brogan, F. A.; Nour-Omid, B.; Rankin, C. C.; Wright, M. A.

1989-01-01

The first section describes data storage schemes presently used by the Computational Structural Mechanics (CSM) testbed sparse matrix facilities and similar skyline (profile) matrix facilities. The second section contains a discussion of certain features required for the implementation of particular advanced CSM algorithms, and how these features might be incorporated into the data storage schemes described previously. The third section presents recommendations, based on the discussions of the prior sections, for directing future CSM testbed development to provide necessary matrix facilities for advanced algorithm implementation and use. The objective is to lend insight into the matrix structures discussed and to help explain the process of evaluating alternative matrix data structures and utilities for subsequent use in the CSM testbed.

A second level of the Saint Petersburg skyline

NASA Astrophysics Data System (ADS)

Krasnopolsky, Andrey; Bolotin, Sergey

2018-03-01

The article considers the history of the residential development in Saint Petersburg and states corresponding landmark dates. In recent years, changes in the altitude range of the residential development are noted, the influence of this factor on the formation of the city's silhouette is assessed. Reasons for such changes are identified. Attractiveness of high-rise residential complexes for living is assessed. Conclusions are made of tendencies in further housing construction development in terms of its altitude range. It is noted that it is possible to locate multi-storied buildings in the periphery of the city, taking into account specific visual characteristics of the construction site and silhouette of erected buildings; as for central districts, strict regulations regarding the altitude range are needed.

Interpreting megalithic tomb orientation and siting within broader cultural contexts

NASA Astrophysics Data System (ADS)

Prendergast, Frank

2016-02-01

This paper assesses the measured axial orientations and siting of Irish passage tombs. The distribution of monuments with passages/entrances directed at related tombs/cairns is shown. Where this phenomenon occurs, the targeted structure is invariably located at a higher elevation on the skyline and this could suggest a symbolic and hierarchical relationship in their relative siting in the landscape. Additional analysis of astronomical declinations at a national scale has identified tombs with an axial alignment towards the rising and setting positions of the Sun at the winter and summer solstices. A criteria-based framework is developed which potentially allows for these types of data to be more meaningfully considered and culturally interpreted within broader archaeological and social anthropological contexts.

A Bayesian Nonparametric Approach to Test Equating

ERIC Educational Resources Information Center

Karabatsos, George; Walker, Stephen G.

2009-01-01

A Bayesian nonparametric model is introduced for score equating. It is applicable to all major equating designs, and has advantages over previous equating models. Unlike the previous models, the Bayesian model accounts for positive dependence between distributions of scores from two tests. The Bayesian model and the previous equating models are…

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…

Semisupervised learning using Bayesian interpretation: application to LS-SVM.

PubMed

Adankon, Mathias M; Cheriet, Mohamed; Biem, Alain

2011-04-01

Bayesian reasoning provides an ideal basis for representing and manipulating uncertain knowledge, with the result that many interesting algorithms in machine learning are based on Bayesian inference. In this paper, we use the Bayesian approach with one and two levels of inference to model the semisupervised learning problem and give its application to the successful kernel classifier support vector machine (SVM) and its variant least-squares SVM (LS-SVM). Taking advantage of Bayesian interpretation of LS-SVM, we develop a semisupervised learning algorithm for Bayesian LS-SVM using our approach based on two levels of inference. Experimental results on both artificial and real pattern recognition problems show the utility of our method.

Bayesian Regression with Network Prior: Optimal Bayesian Filtering Perspective

PubMed Central

Qian, Xiaoning; Dougherty, Edward R.

2017-01-01

The recently introduced intrinsically Bayesian robust filter (IBRF) provides fully optimal filtering relative to a prior distribution over an uncertainty class ofjoint random process models, whereas formerly the theory was limited to model-constrained Bayesian robust filters, for which optimization was limited to the filters that are optimal for models in the uncertainty class. This paper extends the IBRF theory to the situation where there are both a prior on the uncertainty class and sample data. The result is optimal Bayesian filtering (OBF), where optimality is relative to the posterior distribution derived from the prior and the data. The IBRF theories for effective characteristics and canonical expansions extend to the OBF setting. A salient focus of the present work is to demonstrate the advantages of Bayesian regression within the OBF setting over the classical Bayesian approach in the context otlinear Gaussian models. PMID:28824268

An introduction to using Bayesian linear regression with clinical data.

PubMed

Baldwin, Scott A; Larson, Michael J

2017-11-01

Statistical training psychology focuses on frequentist methods. Bayesian methods are an alternative to standard frequentist methods. This article provides researchers with an introduction to fundamental ideas in Bayesian modeling. We use data from an electroencephalogram (EEG) and anxiety study to illustrate Bayesian models. Specifically, the models examine the relationship between error-related negativity (ERN), a particular event-related potential, and trait anxiety. Methodological topics covered include: how to set up a regression model in a Bayesian framework, specifying priors, examining convergence of the model, visualizing and interpreting posterior distributions, interval estimates, expected and predicted values, and model comparison tools. We also discuss situations where Bayesian methods can outperform frequentist methods as well has how to specify more complicated regression models. Finally, we conclude with recommendations about reporting guidelines for those using Bayesian methods in their own research. We provide data and R code for replicating our analyses. Copyright © 2017 Elsevier Ltd. All rights reserved.

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…

BMDS: A Collection of R Functions for Bayesian Multidimensional Scaling

ERIC Educational Resources Information Center

Okada, Kensuke; Shigemasu, Kazuo

2009-01-01

Bayesian multidimensional scaling (MDS) has attracted a great deal of attention because: (1) it provides a better fit than do classical MDS and ALSCAL; (2) it provides estimation errors of the distances; and (3) the Bayesian dimension selection criterion, MDSIC, provides a direct indication of optimal dimensionality. However, Bayesian MDS is not…

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…

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 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.

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.

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.

The Psychology of Bayesian Reasoning

DTIC Science & Technology

2014-10-21

The psychology of Bayesian reasoning David R. Mandel* Socio-Cognitive Systems Section, Defence Research and Development Canada and Department...belief revision, subjective probability, human judgment, psychological methods. Most psychological research on Bayesian reasoning since the 1970s has...attention to some important problems with the conventional approach to studying Bayesian reasoning in psychology that has been dominant since the

Bayesian Just-So Stories in Psychology and Neuroscience

ERIC Educational Resources Information Center

Bowers, Jeffrey S.; Davis, Colin J.

2012-01-01

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.…

Teaching Bayesian Statistics in a Health Research Methodology Program

ERIC Educational Resources Information Center

Pullenayegum, Eleanor M.; Thabane, Lehana

2009-01-01

Despite the appeal of Bayesian methods in health research, they are not widely used. This is partly due to a lack of courses in Bayesian methods at an appropriate level for non-statisticians in health research. Teaching such a course can be challenging because most statisticians have been taught Bayesian methods using a mathematical approach, and…

Bayesian inference based on dual generalized order statistics from the exponentiated Weibull model

NASA Astrophysics Data System (ADS)

Al Sobhi, Mashail M.

2015-02-01

Bayesian estimation for the two parameters and the reliability function of the exponentiated Weibull model are obtained based on dual generalized order statistics (DGOS). Also, Bayesian prediction bounds for future DGOS from exponentiated Weibull model are obtained. The symmetric and asymmetric loss functions are considered for Bayesian computations. The Markov chain Monte Carlo (MCMC) methods are used for computing the Bayes estimates and prediction bounds. The results have been specialized to the lower record values. Comparisons are made between Bayesian and maximum likelihood estimators via Monte Carlo simulation.

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.

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

Assessment of Cropping System Diversity in the Fergana Valley Through Image Fusion of Landsat 8 and SENTINEL-1

NASA Astrophysics Data System (ADS)

Dimov, D.; Kuhn, J.; Conrad, C.

2016-06-01

In the transitioning agricultural societies of the world, food security is an essential element of livelihood and economic development with the agricultural sector very often being the major employment factor and income source. Rapid population growth, urbanization, pollution, desertification, soil degradation and climate change pose a variety of threats to a sustainable agricultural development and can be expressed as agricultural vulnerability components. Diverse cropping patterns may help to adapt the agricultural systems to those hazards in terms of increasing the potential yield and resilience to water scarcity. Thus, the quantification of crop diversity using indices like the Simpson Index of Diversity (SID) e.g. through freely available remote sensing data becomes a very important issue. This however requires accurate land use classifications. In this study, the focus is set on the cropping system diversity of garden plots, summer crop fields and orchard plots which are the prevalent agricultural systems in the test area of the Fergana Valley in Uzbekistan. In order to improve the accuracy of land use classification algorithms with low or medium resolution data, a novel processing chain through the hitherto unique fusion of optical and SAR data from the Landsat 8 and Sentinel-1 platforms is proposed. The combination of both sensors is intended to enhance the object's textural and spectral signature rather than just to enhance the spatial context through pansharpening. It could be concluded that the Ehlers fusion algorithm gave the most suitable results. Based on the derived image fusion different object-based image classification algorithms such as SVM, Naïve Bayesian and Random Forest were evaluated whereby the latter one achieved the highest classification accuracy. Subsequently, the SID was applied to measure the diversification of the three main cropping systems.

An image-guided radiotherapy decision support framework incorporating a Bayesian network and visualization tool.

PubMed

Hargrave, Catriona; Deegan, Timothy; Bednarz, Tomasz; Poulsen, Michael; Harden, Fiona; Mengersen, Kerrie

2018-05-17

To describe a Bayesian network (BN) and complementary visualization tool that aim to support decision-making during online cone-beam computed tomography (CBCT)-based image-guided radiotherapy (IGRT) for prostate cancer patients. The BN was created to represent relationships between observed prostate, proximal seminal vesicle (PSV), bladder and rectum volume variations, an image feature alignment score (FAS TV _ OAR ), delivered dose, and treatment plan compliance (TPC). Variables influencing tumor volume (TV) targeting accuracy such as intrafraction motion, and contouring and couch shift errors were also represented. A score of overall TPC (FAS global ) and factors such as image quality were used to inform the BN output node providing advice about proceeding with treatment. The BN was quantified using conditional probabilities generated from published studies, FAS TV _ OAR /global modeling, and a survey of IGRT decision-making practices. A new IGRT visualization tool (IGRT REV ), in the form of Mollweide projection plots, was developed to provide a global summary of residual errors after online CBCT-planning CT registration. Sensitivity and scenario analyses were undertaken to evaluate the performance of the BN and the relative influence of the network variables on TPC and the decision to proceed with treatment. The IGRT REV plots were evaluated in conjunction with the BN scenario testing, using additional test data generated from retrospective CBCT-planning CT soft-tissue registrations for 13/36 patients whose data were used in the FAS TV _ OAR /global modeling. Modeling of the TV targeting errors resulted in a very low probability of corrected distances between the CBCT and planning CT prostate or PSV volumes being within their thresholds. Strength of influence evaluation with and without the BN TV targeting error nodes indicated that rectum- and bladder-related network variables had the highest relative importance. When the TV targeting error nodes were excluded from the BN, TPC was sensitive to observed PSV and rectum variations while the decision to treat was sensitive to observed prostate and PSV variations. When root nodes were set so the PSV and rectum variations exceeded thresholds, the probability of low TPC increased to 40%. Prostate and PSV variations exceeding thresholds increased the likelihood of repositioning or repeating patient preparation to 43%. Scenario testing using the test data from 13 patients, demonstrated two cases where the BN provided increased high TPC probabilities, despite some of the prostate and PSV volume variation metrics not being within tolerance. The IGRT REV tool was effective in highlighting and quantifying where TV and OAR variations occurred, supporting the BN recommendation to reposition the patient or repeat their bladder and bowel preparation. In another case, the IGRT REV tool was also effective in highlighting where PSV volume variation significantly exceeded tolerance when the BN had indicated to proceed with treatment. This study has demonstrated that both the BN and IGRT REV plots are effective tools for inclusion in a decision support system for online CBCT-based IGRT for prostate cancer patients. Alternate approaches to modeling TV targeting errors need to be explored as well as extension of the BN to support offline IGRT decisions related to adaptive radiotherapy. © 2018 American Association of Physicists in Medicine.

Some practical aspects of prestack waveform inversion using a genetic algorithm: An example from the east Texas Woodbine gas sand

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

Mallick, S.

1999-03-01

In this paper, a prestack inversion method using a genetic algorithm (GA) is presented, and issues relating to the implementation of prestack GA inversion in practice are discussed. GA is a Monte-Carlo type inversion, using a natural analogy to the biological evolution process. When GA is cast into a Bayesian framework, a priori information of the model parameters and the physics of the forward problem are used to compute synthetic data. These synthetic data can then be matched with observations to obtain approximate estimates of the marginal a posteriori probability density (PPD) functions in the model space. Plots of thesemore » PPD functions allow an interpreter to choose models which best describe the specific geologic setting and lead to an accurate prediction of seismic lithology. Poststack inversion and prestack GA inversion were applied to a Woodbine gas sand data set from East Texas. A comparison of prestack inversion with poststack inversion demonstrates that prestack inversion shows detailed stratigraphic features of the subsurface which are not visible on the poststack inversion.« less

Municipal mortality due to thyroid cancer in Spain

PubMed Central

Lope, Virginia; Pollán, Marina; Pérez-Gómez, Beatriz; Aragonés, Nuria; Ramis, Rebeca; Gómez-Barroso, Diana; López-Abente, Gonzalo

2006-01-01

Background Thyroid cancer is a tumor with a low but growing incidence in Spain. This study sought to depict its spatial municipal mortality pattern, using the classic model proposed by Besag, York and Mollié. Methods It was possible to compile and ascertain the posterior distribution of relative risk on the basis of a single Bayesian spatial model covering all of Spain's 8077 municipal areas. Maps were plotted depicting standardized mortality ratios, smoothed relative risk (RR) estimates, and the posterior probability that RR > 1. Results From 1989 to 1998 a total of 2,538 thyroid cancer deaths were registered in 1,041 municipalities. The highest relative risks were mostly situated in the Canary Islands, the province of Lugo, the east of La Coruña (Corunna) and western areas of Asturias and Orense. Conclusion The observed mortality pattern coincides with areas in Spain where goiter has been declared endemic. The higher frequency in these same areas of undifferentiated, more aggressive carcinomas could be reflected in the mortality figures. Other unknown genetic or environmental factors could also play a role in the etiology of this tumor. PMID:17173668

Coral reefs as drivers of cladogenesis: expanding coral reefs, cryptic extinction events, and the development of biodiversity hotspots.

PubMed

Cowman, P F; Bellwood, D R

2011-12-01

Diversification rates within four conspicuous coral reef fish families (Labridae, Chaetodontidae, Pomacentridae and Apogonidae) were estimated using Bayesian inference. Lineage through time plots revealed a possible late Eocene/early Oligocene cryptic extinction event coinciding with the collapse of the ancestral Tethyan/Arabian hotspot. Rates of diversification analysis revealed elevated cladogenesis in all families in the Oligocene/Miocene. Throughout the Miocene, lineages with a high percentage of coral reef-associated taxa display significantly higher net diversification rates than expected. The development of a complex mosaic of reef habitats in the Indo-Australian Archipelago (IAA) during the Oligocene/Miocene appears to have been a significant driver of cladogenesis. Patterns of diversification suggest that coral reefs acted as a refuge from high extinction, as reef taxa are able to sustain diversification at high extinction rates. The IAA appears to support both cladogenesis and survival in associated lineages, laying the foundation for the recent IAA marine biodiversity hotspot. © 2011 The Authors. Journal of Evolutionary Biology © 2011 European Society For Evolutionary Biology.

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.

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

How the Bayesians Got Their Beliefs (and What Those Beliefs Actually Are): Comment on Bowers and Davis (2012)

ERIC Educational Resources Information Center

Griffiths, Thomas L.; Chater, Nick; Norris, Dennis; Pouget, Alexandre

2012-01-01

Bowers and Davis (2012) criticize Bayesian modelers for telling "just so" stories about cognition and neuroscience. Their criticisms are weakened by not giving an accurate characterization of the motivation behind Bayesian modeling or the ways in which Bayesian models are used and by not evaluating this theoretical framework against specific…

Construction of monitoring model and algorithm design on passenger security during shipping based on improved Bayesian network.

PubMed

Wang, Jiali; Zhang, Qingnian; Ji, Wenfeng

2014-01-01

A large number of data is needed by the computation of the objective Bayesian network, but the data is hard to get in actual computation. The calculation method of Bayesian network was improved in this paper, and the fuzzy-precise Bayesian network was obtained. Then, the fuzzy-precise Bayesian network was used to reason Bayesian network model when the data is limited. The security of passengers during shipping is affected by various factors, and it is hard to predict and control. The index system that has the impact on the passenger safety during shipping was established on basis of the multifield coupling theory in this paper. Meanwhile, the fuzzy-precise Bayesian network was applied to monitor the security of passengers in the shipping process. The model was applied to monitor the passenger safety during shipping of a shipping company in Hainan, and the effectiveness of this model was examined. This research work provides guidance for guaranteeing security of passengers during shipping.

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

A study of finite mixture model: Bayesian approach on financial time series data

NASA Astrophysics Data System (ADS)

Phoong, Seuk-Yen; Ismail, Mohd Tahir

2014-07-01

Recently, statistician have emphasized on the fitting finite mixture model by using Bayesian method. Finite mixture model is a mixture of distributions in modeling a statistical distribution meanwhile Bayesian method is a statistical method that use to fit the mixture model. Bayesian method is being used widely because it has asymptotic properties which provide remarkable result. In addition, Bayesian method also shows consistency characteristic which means the parameter estimates are close to the predictive distributions. In the present paper, the number of components for mixture model is studied by using Bayesian Information Criterion. Identify the number of component is important because it may lead to an invalid result. Later, the Bayesian method is utilized to fit the k-component mixture model in order to explore the relationship between rubber price and stock market price for Malaysia, Thailand, Philippines and Indonesia. Lastly, the results showed that there is a negative effect among rubber price and stock market price for all selected countries.

Construction of Monitoring Model and Algorithm Design on Passenger Security during Shipping Based on Improved Bayesian Network

PubMed Central

Wang, Jiali; Zhang, Qingnian; Ji, Wenfeng

2014-01-01

A large number of data is needed by the computation of the objective Bayesian network, but the data is hard to get in actual computation. The calculation method of Bayesian network was improved in this paper, and the fuzzy-precise Bayesian network was obtained. Then, the fuzzy-precise Bayesian network was used to reason Bayesian network model when the data is limited. The security of passengers during shipping is affected by various factors, and it is hard to predict and control. The index system that has the impact on the passenger safety during shipping was established on basis of the multifield coupling theory in this paper. Meanwhile, the fuzzy-precise Bayesian network was applied to monitor the security of passengers in the shipping process. The model was applied to monitor the passenger safety during shipping of a shipping company in Hainan, and the effectiveness of this model was examined. This research work provides guidance for guaranteeing security of passengers during shipping. PMID:25254227

Philosophy and the practice of Bayesian statistics

PubMed Central

Gelman, Andrew; Shalizi, Cosma Rohilla

2015-01-01

A substantial school in the philosophy of science identifies Bayesian inference with inductive inference and even rationality as such, and seems to be strengthened by the rise and practical success of Bayesian statistics. We argue that the most successful forms of Bayesian statistics do not actually support that particular philosophy but rather accord much better with sophisticated forms of hypothetico-deductivism. We examine the actual role played by prior distributions in Bayesian models, and the crucial aspects of model checking and model revision, which fall outside the scope of Bayesian confirmation theory. We draw on the literature on the consistency of Bayesian updating and also on our experience of applied work in social science. Clarity about these matters should benefit not just philosophy of science, but also statistical practice. At best, the inductivist view has encouraged researchers to fit and compare models without checking them; at worst, theorists have actively discouraged practitioners from performing model checking because it does not fit into their framework. PMID:22364575

Philosophy and the practice of Bayesian statistics.

PubMed

Gelman, Andrew; Shalizi, Cosma Rohilla

2013-02-01

A substantial school in the philosophy of science identifies Bayesian inference with inductive inference and even rationality as such, and seems to be strengthened by the rise and practical success of Bayesian statistics. We argue that the most successful forms of Bayesian statistics do not actually support that particular philosophy but rather accord much better with sophisticated forms of hypothetico-deductivism. We examine the actual role played by prior distributions in Bayesian models, and the crucial aspects of model checking and model revision, which fall outside the scope of Bayesian confirmation theory. We draw on the literature on the consistency of Bayesian updating and also on our experience of applied work in social science. Clarity about these matters should benefit not just philosophy of science, but also statistical practice. At best, the inductivist view has encouraged researchers to fit and compare models without checking them; at worst, theorists have actively discouraged practitioners from performing model checking because it does not fit into their framework. © 2012 The British Psychological Society.

Bayesian statistics in medicine: a 25 year review.

PubMed

Ashby, Deborah

2006-11-15

This review examines the state of Bayesian thinking as Statistics in Medicine was launched in 1982, reflecting particularly on its applicability and uses in medical research. It then looks at each subsequent five-year epoch, with a focus on papers appearing in Statistics in Medicine, putting these in the context of major developments in Bayesian thinking and computation with reference to important books, landmark meetings and seminal papers. It charts the growth of Bayesian statistics as it is applied to medicine and makes predictions for the future. From sparse beginnings, where Bayesian statistics was barely mentioned, Bayesian statistics has now permeated all the major areas of medical statistics, including clinical trials, epidemiology, meta-analyses and evidence synthesis, spatial modelling, longitudinal modelling, survival modelling, molecular genetics and decision-making in respect of new technologies.

With or without you: predictive coding and Bayesian inference in the brain

PubMed Central

Aitchison, Laurence; Lengyel, Máté

2018-01-01

Two theoretical ideas have emerged recently with the ambition to provide a unifying functional explanation of neural population coding and dynamics: predictive coding and Bayesian inference. Here, we describe the two theories and their combination into a single framework: Bayesian predictive coding. We clarify how the two theories can be distinguished, despite sharing core computational concepts and addressing an overlapping set of empirical phenomena. We argue that predictive coding is an algorithmic / representational motif that can serve several different computational goals of which Bayesian inference is but one. Conversely, while Bayesian inference can utilize predictive coding, it can also be realized by a variety of other representations. We critically evaluate the experimental evidence supporting Bayesian predictive coding and discuss how to test it more directly. PMID:28942084

Hepatitis disease detection using Bayesian theory

NASA Astrophysics Data System (ADS)

Maseleno, Andino; Hidayati, Rohmah Zahroh

2017-02-01

This paper presents hepatitis disease diagnosis using a Bayesian theory for better understanding of the theory. In this research, we used a Bayesian theory for detecting hepatitis disease and displaying the result of diagnosis process. Bayesian algorithm theory is rediscovered and perfected by Laplace, the basic idea is using of the known prior probability and conditional probability density parameter, based on Bayes theorem to calculate the corresponding posterior probability, and then obtained the posterior probability to infer and make decisions. Bayesian methods combine existing knowledge, prior probabilities, with additional knowledge derived from new data, the likelihood function. The initial symptoms of hepatitis which include malaise, fever and headache. The probability of hepatitis given the presence of malaise, fever, and headache. The result revealed that a Bayesian theory has successfully identified the existence of hepatitis disease.

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.

Efficient fuzzy Bayesian inference algorithms for incorporating expert knowledge in parameter estimation

NASA Astrophysics Data System (ADS)

Rajabi, Mohammad Mahdi; Ataie-Ashtiani, Behzad

2016-05-01

Bayesian inference has traditionally been conceived as the proper framework for the formal incorporation of expert knowledge in parameter estimation of groundwater models. However, conventional Bayesian inference is incapable of taking into account the imprecision essentially embedded in expert provided information. In order to solve this problem, a number of extensions to conventional Bayesian inference have been introduced in recent years. One of these extensions is 'fuzzy Bayesian inference' which is the result of integrating fuzzy techniques into Bayesian statistics. Fuzzy Bayesian inference has a number of desirable features which makes it an attractive approach for incorporating expert knowledge in the parameter estimation process of groundwater models: (1) it is well adapted to the nature of expert provided information, (2) it allows to distinguishably model both uncertainty and imprecision, and (3) it presents a framework for fusing expert provided information regarding the various inputs of the Bayesian inference algorithm. However an important obstacle in employing fuzzy Bayesian inference in groundwater numerical modeling applications is the computational burden, as the required number of numerical model simulations often becomes extremely exhaustive and often computationally infeasible. In this paper, a novel approach of accelerating the fuzzy Bayesian inference algorithm is proposed which is based on using approximate posterior distributions derived from surrogate modeling, as a screening tool in the computations. The proposed approach is first applied to a synthetic test case of seawater intrusion (SWI) in a coastal aquifer. It is shown that for this synthetic test case, the proposed approach decreases the number of required numerical simulations by an order of magnitude. Then the proposed approach is applied to a real-world test case involving three-dimensional numerical modeling of SWI in Kish Island, located in the Persian Gulf. An expert elicitation methodology is developed and applied to the real-world test case in order to provide a road map for the use of fuzzy Bayesian inference in groundwater modeling 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.

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

Bayesian Fundamentalism or Enlightenment? On the explanatory status and theoretical contributions of Bayesian models of cognition.

PubMed

Jones, Matt; Love, Bradley C

2011-08-01

The prominence of Bayesian modeling of cognition has increased recently largely because of mathematical advances in specifying and deriving predictions from complex probabilistic models. Much of this research aims to demonstrate that cognitive behavior can be explained from rational principles alone, without recourse to psychological or neurological processes and representations. We note commonalities between this rational approach and other movements in psychology - namely, Behaviorism and evolutionary psychology - that set aside mechanistic explanations or make use of optimality assumptions. Through these comparisons, we identify a number of challenges that limit the rational program's potential contribution to psychological theory. Specifically, rational Bayesian models are significantly unconstrained, both because they are uninformed by a wide range of process-level data and because their assumptions about the environment are generally not grounded in empirical measurement. The psychological implications of most Bayesian models are also unclear. Bayesian inference itself is conceptually trivial, but strong assumptions are often embedded in the hypothesis sets and the approximation algorithms used to derive model predictions, without a clear delineation between psychological commitments and implementational details. Comparing multiple Bayesian models of the same task is rare, as is the realization that many Bayesian models recapitulate existing (mechanistic level) theories. Despite the expressive power of current Bayesian models, we argue they must be developed in conjunction with mechanistic considerations to offer substantive explanations of cognition. We lay out several means for such an integration, which take into account the representations on which Bayesian inference operates, as well as the algorithms and heuristics that carry it out. We argue this unification will better facilitate lasting contributions to psychological theory, avoiding the pitfalls that have plagued previous theoretical movements.

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.

Prediction of Individual Serum Infliximab Concentrations in Inflammatory Bowel Disease by a Bayesian Dashboard System.

PubMed

Eser, Alexander; Primas, Christian; Reinisch, Sieglinde; Vogelsang, Harald; Novacek, Gottfried; Mould, Diane R; Reinisch, Walter

2018-01-30

Despite a robust exposure-response relationship of infliximab in inflammatory bowel disease (IBD), attempts to adjust dosing to individually predicted serum concentrations of infliximab (SICs) are lacking. Compared with labor-intensive conventional software for pharmacokinetic (PK) modeling (eg, NONMEM) dashboards are easy-to-use programs incorporating complex Bayesian statistics to determine individual pharmacokinetics. We evaluated various infliximab detection assays and the number of samples needed to precisely forecast individual SICs using a Bayesian dashboard. We assessed long-term infliximab retention in patients being dosed concordantly versus discordantly with Bayesian dashboard recommendations. Three hundred eighty-two serum samples from 117 adult IBD patients on infliximab maintenance therapy were analyzed by 3 commercially available assays. Data from each assay was modeled using NONMEM and a Bayesian dashboard. PK parameter precision and residual variability were assessed. Forecast concentrations from both systems were compared with observed concentrations. Infliximab retention was assessed by prediction for dose intensification via Bayesian dashboard versus real-life practice. Forecast precision of SICs varied between detection assays. At least 3 SICs from a reliable assay are needed for an accurate forecast. The Bayesian dashboard performed similarly to NONMEM to predict SICs. Patients dosed concordantly with Bayesian dashboard recommendations had a significantly longer median drug survival than those dosed discordantly (51.5 versus 4.6 months, P < .0001). The Bayesian dashboard helps to assess the diagnostic performance of infliximab detection assays. Three, not single, SICs provide sufficient information for individualized dose adjustment when incorporated into the Bayesian dashboard. Treatment adjusted to forecasted SICs is associated with longer drug retention of infliximab. © 2018, The American College of Clinical Pharmacology.

Experimental evaluation of certification trails using abstract data type validation

NASA Technical Reports Server (NTRS)

Wilson, Dwight S.; Sullivan, Gregory F.; Masson, Gerald M.

1993-01-01

Certification trails are a recently introduced and promising approach to fault-detection and fault-tolerance. Recent experimental work reveals many cases in which a certification-trail approach allows for significantly faster program execution time than a basic time-redundancy approach. Algorithms for answer-validation of abstract data types allow a certification trail approach to be used for a wide variety of problems. An attempt to assess the performance of algorithms utilizing certification trails on abstract data types is reported. Specifically, this method was applied to the following problems: heapsort, Hullman tree, shortest path, and skyline. Previous results used certification trails specific to a particular problem and implementation. The approach allows certification trails to be localized to 'data structure modules,' making the use of this technique transparent to the user of such modules.

VizieR Online Data Catalog: Investigating Tully-Fisher relation with KMOS3D (Ubler+,

NASA Astrophysics Data System (ADS)

Ubler, H.; Forster Schreiber, N. M.; Genzel, R.; Wisnioski, E.; Wuyts, S.; Lang, P.; Naab, T.; Burkert, A.; van Dokkum, P. G.; Tacconi, L. J.; Wilman, D. J.; Fossati, M.; Mendel, J. T.; Beifiori, A.; Belli, S.; Bender, R.; Brammer, G. B.; Chan, J.; Davies, R.; Fabricius, M.; Galametz, A.; Lutz, D.; Momcheva, I. G.; Nelson, E. J.; Saglia, R. P.; Seitz, S.; Tadaki, K.

2018-02-01

This work is based on the first 3yr of observations of KMOS3D multiyear near-infrared (near-IR) IFS survey of more than 600 mass-selected star-forming galaxies (SFGs) at 0.6<~z<~2.6 with the K-band Multi Object Spectrograph (KMOS; Sharples+ 2013Msngr.151...21S) on the Very Large Telescope. The KMOS3D survey and data reduction are described in detail by Wisnioski et al. 2015ApJ...799..209W The results presented in this paper build on the KMOS3D sample as of 2016 January, with 536 observed galaxies. Of these, 316 are detected in, and have spatially resolved, Hα emission free from skyline contamination from which two-dimensional velocity and dispersion maps are produced. (1 data file).

Closer Look: Majestic Mountains and Frozen Plains

NASA Image and Video Library

2015-09-17

Just 15 minutes after its closest approach to Pluto on July 14, 2015, NASA's New Horizons spacecraft looked back toward the sun and captured a near-sunset view of the rugged, icy mountains and flat ice plains extending to Pluto's horizon. The smooth expanse of the informally named Sputnik Planum (right) is flanked to the west (left) by rugged mountains up to 11,000 feet (3,500 meters) high, including the informally named Norgay Montes in the foreground and Hillary Montes on the skyline. The backlighting highlights more than a dozen layers of haze in Pluto's tenuous but distended atmosphere. The image was taken from a distance of 11,000 miles (18,000 kilometers) to Pluto; the scene is 230 miles (380 kilometers) across. http://photojournal.jpl.nasa.gov/catalog/PIA19947

Preparing to Test for Deep Space

NASA Image and Video Library

2015-07-15

A structural steel section is lifted into place atop the B-2 Test Stand at NASA’s Stennis Space Center as part of modification work to prepare for testing the core stage of NASA’s new Space Launch System. The section is part of the Main Propulsion Test Article (MPTA) framework, which will support the SLS core stage for testing. The existing framework was installed on the stand in the late 1970s to test the shuttle MPTA. However, that framework had to be repositioned and modified to accommodate the larger SLS stage. About 1 million pounds of structural steel has been added, extending the framework about 100 feet higher and providing a new look to the Stennis skyline. Stennis will test the actual flight core stage for the first uncrewed SLS mission, Exploration Mission-1.

Bayesian Probability Theory

NASA Astrophysics Data System (ADS)

von der Linden, Wolfgang; Dose, Volker; von Toussaint, Udo

2014-06-01

Preface; Part I. Introduction: 1. The meaning of probability; 2. Basic definitions; 3. Bayesian inference; 4. Combinatrics; 5. Random walks; 6. Limit theorems; 7. Continuous distributions; 8. The central limit theorem; 9. Poisson processes and waiting times; Part II. Assigning Probabilities: 10. Transformation invariance; 11. Maximum entropy; 12. Qualified maximum entropy; 13. Global smoothness; Part III. Parameter Estimation: 14. Bayesian parameter estimation; 15. Frequentist parameter estimation; 16. The Cramer-Rao inequality; Part IV. Testing Hypotheses: 17. The Bayesian way; 18. The frequentist way; 19. Sampling distributions; 20. Bayesian vs frequentist hypothesis tests; Part V. Real World Applications: 21. Regression; 22. Inconsistent data; 23. Unrecognized signal contributions; 24. Change point problems; 25. Function estimation; 26. Integral equations; 27. Model selection; 28. Bayesian experimental design; Part VI. Probabilistic Numerical Techniques: 29. Numerical integration; 30. Monte Carlo methods; 31. Nested sampling; Appendixes; References; Index.

Universal Darwinism As a Process of Bayesian Inference.

PubMed

Campbell, John O

2016-01-01

Many of the mathematical frameworks describing natural selection are equivalent to Bayes' Theorem, also known as Bayesian updating. By definition, a process of Bayesian Inference is one which involves a Bayesian update, so we may conclude that these frameworks describe natural selection as a process of Bayesian inference. Thus, natural selection serves as a counter example to a widely-held interpretation that restricts Bayesian Inference to human mental processes (including the endeavors of statisticians). As Bayesian inference can always be cast in terms of (variational) free energy minimization, natural selection can be viewed as comprising two components: a generative model of an "experiment" in the external world environment, and the results of that "experiment" or the "surprise" entailed by predicted and actual outcomes of the "experiment." Minimization of free energy implies that the implicit measure of "surprise" experienced serves to update the generative model in a Bayesian manner. This description closely accords with the mechanisms of generalized Darwinian process proposed both by Dawkins, in terms of replicators and vehicles, and Campbell, in terms of inferential systems. Bayesian inference is an algorithm for the accumulation of evidence-based knowledge. This algorithm is now seen to operate over a wide range of evolutionary processes, including natural selection, the evolution of mental models and cultural evolutionary processes, notably including science itself. The variational principle of free energy minimization may thus serve as a unifying mathematical framework for universal Darwinism, the study of evolutionary processes operating throughout nature.

Universal Darwinism As a Process of Bayesian Inference

PubMed Central

Campbell, John O.

2016-01-01

Many of the mathematical frameworks describing natural selection are equivalent to Bayes' Theorem, also known as Bayesian updating. By definition, a process of Bayesian Inference is one which involves a Bayesian update, so we may conclude that these frameworks describe natural selection as a process of Bayesian inference. Thus, natural selection serves as a counter example to a widely-held interpretation that restricts Bayesian Inference to human mental processes (including the endeavors of statisticians). As Bayesian inference can always be cast in terms of (variational) free energy minimization, natural selection can be viewed as comprising two components: a generative model of an “experiment” in the external world environment, and the results of that “experiment” or the “surprise” entailed by predicted and actual outcomes of the “experiment.” Minimization of free energy implies that the implicit measure of “surprise” experienced serves to update the generative model in a Bayesian manner. This description closely accords with the mechanisms of generalized Darwinian process proposed both by Dawkins, in terms of replicators and vehicles, and Campbell, in terms of inferential systems. Bayesian inference is an algorithm for the accumulation of evidence-based knowledge. This algorithm is now seen to operate over a wide range of evolutionary processes, including natural selection, the evolution of mental models and cultural evolutionary processes, notably including science itself. The variational principle of free energy minimization may thus serve as a unifying mathematical framework for universal Darwinism, the study of evolutionary processes operating throughout nature. PMID:27375438

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.

Constraint of soil moisture on CO2 efflux from tundra lichen, moss, and tussock in Council, Alaska, using a hierarchical Bayesian model

NASA Astrophysics Data System (ADS)

Kim, Y.; Nishina, K.; Chae, N.; Park, S. J.; Yoon, Y. J.; Lee, B. Y.

2014-10-01

The tundra ecosystem is quite vulnerable to drastic climate change in the Arctic, and the quantification of carbon dynamics is of significant importance regarding thawing permafrost, changes to the snow-covered period and snow and shrub community extent, and the decline of sea ice in the Arctic. Here, CO2 efflux measurements using a manual chamber system within a 40 m × 40 m (5 m interval; 81 total points) plot were conducted within dominant tundra vegetation on the Seward Peninsula of Alaska, during the growing seasons of 2011 and 2012, for the assessment of driving parameters of CO2 efflux. We applied a hierarchical Bayesian (HB) model - a function of soil temperature, soil moisture, vegetation type, and thaw depth - to quantify the effects of environmental factors on CO2 efflux and to estimate growing season CO2 emissions. Our results showed that average CO2 efflux in 2011 was 1.4 times higher than in 2012, resulting from the distinct difference in soil moisture between the 2 years. Tussock-dominated CO2 efflux is 1.4 to 2.3 times higher than those measured in lichen and moss communities, revealing tussock as a significant CO2 source in the Arctic, with a wide area distribution on the circumpolar scale. CO2 efflux followed soil temperature nearly exponentially from both the observed data and the posterior medians of the HB model. This reveals that soil temperature regulates the seasonal variation of CO2 efflux and that soil moisture contributes to the interannual variation of CO2 efflux for the two growing seasons in question. Obvious changes in soil moisture during the growing seasons of 2011 and 2012 resulted in an explicit difference between CO2 effluxes - 742 and 539 g CO2 m-2 period-1 for 2011 and 2012, respectively, suggesting the 2012 CO2 emission rate was reduced to 27% (95% credible interval: 17-36%) of the 2011 emission, due to higher soil moisture from severe rain. The estimated growing season CO2 emission rate ranged from 0.86 Mg CO2 in 2012 to 1.20 Mg CO2 in 2011 within a 40 m × 40 m plot, corresponding to 86 and 80% of annual CO2 emission rates within the western Alaska tundra ecosystem, estimated from the temperature dependence of CO2 efflux. Therefore, this HB model can be readily applied to observed CO2 efflux, as it demands only four environmental factors and can also be effective for quantitatively assessing the driving parameters of CO2 efflux.

Enhancements to the Bayesian Infrasound Source Location Method

DTIC Science & Technology

2012-09-01

ENHANCEMENTS TO THE BAYESIAN INFRASOUND SOURCE LOCATION METHOD Omar E. Marcillo, Stephen J. Arrowsmith, Rod W. Whitaker, and Dale N. Anderson Los...ABSTRACT We report on R&D that is enabling enhancements to the Bayesian Infrasound Source Location (BISL) method for infrasound event location...the Bayesian Infrasound Source Location Method 5a. CONTRACT NUMBER 5b. GRANT NUMBER 5c. PROGRAM ELEMENT NUMBER 6. AUTHOR(S) 5d. PROJECT NUMBER

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.

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.

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.

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.

Estimating virus occurrence using Bayesian modeling in multiple drinking water systems of the United States

USGS Publications Warehouse

Varughese, Eunice A.; Brinkman, Nichole E; Anneken, Emily M; Cashdollar, Jennifer S; Fout, G. Shay; Furlong, Edward T.; Kolpin, Dana W.; Glassmeyer, Susan T.; Keely, Scott P

2017-01-01

incorporated into a Bayesian model to more accurately determine viral load in both source and treated water. Results of the Bayesian model indicated that viruses are present in source water and treated water. By using a Bayesian framework that incorporates inhibition, as well as many other parameters that affect viral detection, this study offers an approach for more accurately estimating the occurrence of viral pathogens in environmental waters.

The Bayesian reader: explaining word recognition as an optimal Bayesian decision process.

PubMed

Norris, Dennis

2006-04-01

This article presents a theory of visual word recognition that assumes that, in the tasks of word identification, lexical decision, and semantic categorization, human readers behave as optimal Bayesian decision makers. This leads to the development of a computational model of word recognition, the Bayesian reader. The Bayesian reader successfully simulates some of the most significant data on human reading. The model accounts for the nature of the function relating word frequency to reaction time and identification threshold, the effects of neighborhood density and its interaction with frequency, and the variation in the pattern of neighborhood density effects seen in different experimental tasks. Both the general behavior of the model and the way the model predicts different patterns of results in different tasks follow entirely from the assumption that human readers approximate optimal Bayesian decision makers. ((c) 2006 APA, all rights reserved).

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.

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

Spatio-temporal interpolation of precipitation during monsoon periods in Pakistan

NASA Astrophysics Data System (ADS)

Hussain, Ijaz; Spöck, Gunter; Pilz, Jürgen; Yu, Hwa-Lung

2010-08-01

Spatio-temporal estimation of precipitation over a region is essential to the modeling of hydrologic processes for water resources management. The changes of magnitude and space-time heterogeneity of rainfall observations make space-time estimation of precipitation a challenging task. In this paper we propose a Box-Cox transformed hierarchical Bayesian multivariate spatio-temporal interpolation method for the skewed response variable. The proposed method is applied to estimate space-time monthly precipitation in the monsoon periods during 1974-2000, and 27-year monthly average precipitation data are obtained from 51 stations in Pakistan. The results of transformed hierarchical Bayesian multivariate spatio-temporal interpolation are compared to those of non-transformed hierarchical Bayesian interpolation by using cross-validation. The software developed by [11] is used for Bayesian non-stationary multivariate space-time interpolation. It is observed that the transformed hierarchical Bayesian method provides more accuracy than the non-transformed hierarchical Bayesian method.

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).

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

Fundamentals and Recent Developments in Approximate Bayesian Computation

PubMed Central

Lintusaari, Jarno; Gutmann, Michael U.; Dutta, Ritabrata; Kaski, Samuel; Corander, Jukka

2017-01-01

Abstract Bayesian inference plays an important role in phylogenetics, evolutionary biology, and in many other branches of science. It provides a principled framework for dealing with uncertainty and quantifying how it changes in the light of new evidence. For many complex models and inference problems, however, only approximate quantitative answers are obtainable. Approximate Bayesian computation (ABC) refers to a family of algorithms for approximate inference that makes a minimal set of assumptions by only requiring that sampling from a model is possible. We explain here the fundamentals of ABC, review the classical algorithms, and highlight recent developments. [ABC; approximate Bayesian computation; Bayesian inference; likelihood-free inference; phylogenetics; simulator-based models; stochastic simulation models; tree-based models.] PMID:28175922

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.

Curiosity Self-Portrait at Murray Buttes.

NASA Image and Video Library

2016-10-03

This self-portrait of NASA's Curiosity Mars rover shows the vehicle at the "Quela" drilling location in the "Murray Buttes" area on lower Mount Sharp. Key features on the skyline of this panorama are the dark mesa called "M12" to the left of the rover's mast and pale, upper Mount Sharp to the right of the mast. The top of M12 stands about 23 feet (7 meters) above the base of the sloping piles of rocks just behind Curiosity. The scene combines approximately 60 images taken by the Mars Hand Lens Imager (MAHLI) camera at the end of the rover's robotic arm. Most of the component images were taken on Sept. 17, 2016, during the 1,463rd Martian day, or sol, of Curiosity's work on Mars. Two component images of the drill-hole area in front of the rover were taken on Sol 1466 (Sept. 20) to show the hole created by collecting a drilled sample at Quela on Sol 1464 (Sept. 18). The skyline sweeps from west on the left to south-southwest on the right, with the rover's mast at northeast. The rover's location when it recorded this scene was where it ended a drive on Sol 1455, mapped at http://mars.nasa.gov/msl/multimedia/images/?ImageID=8029. The view does not include the rover's arm nor the MAHLI camera itself, except in the miniature scene reflected upside down in the parabolic mirror at the top of the mast. That mirror is part of Curiosity's Chemistry and Camera (ChemCam) instrument. MAHLI appears in the center of the mirror. Wrist motions and turret rotations on the arm allowed MAHLI to acquire the mosaic's component images. The arm was positioned out of the shot in the images, or portions of images, that were used in this mosaic. This process was used previously in acquiring and assembling Curiosity self-portraits taken at other sample-collection sites, including "Rocknest" (PIA16468), "Windjana" (PIA18390"), "Buckskin" (PIA19808) and "Gobabeb" (PIA20316). For scale, the rover's wheels are 20 inches (50 centimeters) in diameter and about 16 inches (40 centimeters) wide. http://photojournal.jpl.nasa.gov/catalog/PIA20844

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.

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.

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…

Bayesian networks for maritime traffic accident prevention: benefits and challenges.

PubMed

Hänninen, Maria

2014-12-01

Bayesian networks are quantitative modeling tools whose applications to the maritime traffic safety context are becoming more popular. This paper discusses the utilization of Bayesian networks in maritime safety modeling. Based on literature and the author's own experiences, the paper studies what Bayesian networks can offer to maritime accident prevention and safety modeling and discusses a few challenges in their application to this context. It is argued that the capability of representing rather complex, not necessarily causal but uncertain relationships makes Bayesian networks an attractive modeling tool for the maritime safety and accidents. Furthermore, as the maritime accident and safety data is still rather scarce and has some quality problems, the possibility to combine data with expert knowledge and the easy way of updating the model after acquiring more evidence further enhance their feasibility. However, eliciting the probabilities from the maritime experts might be challenging and the model validation can be tricky. It is concluded that with the utilization of several data sources, Bayesian updating, dynamic modeling, and hidden nodes for latent variables, Bayesian networks are rather well-suited tools for the maritime safety management and decision-making. Copyright © 2014 Elsevier Ltd. All rights reserved.

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.

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.

The image recognition based on neural network and Bayesian decision

NASA Astrophysics Data System (ADS)

Wang, Chugege

2018-04-01

The artificial neural network began in 1940, which is an important part of artificial intelligence. At present, it has become a hot topic in the fields of neuroscience, computer science, brain science, mathematics, and psychology. Thomas Bayes firstly reported the Bayesian theory in 1763. After the development in the twentieth century, it has been widespread in all areas of statistics. In recent years, due to the solution of the problem of high-dimensional integral calculation, Bayesian Statistics has been improved theoretically, which solved many problems that cannot be solved by classical statistics and is also applied to the interdisciplinary fields. In this paper, the related concepts and principles of the artificial neural network are introduced. It also summarizes the basic content and principle of Bayesian Statistics, and combines the artificial neural network technology and Bayesian decision theory and implement them in all aspects of image recognition, such as enhanced face detection method based on neural network and Bayesian decision, as well as the image classification based on the Bayesian decision. It can be seen that the combination of artificial intelligence and statistical algorithms has always been the hot research topic.

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.

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.

Bayesian Framework for Water Quality Model Uncertainty Estimation and Risk Management

EPA Science Inventory

A formal Bayesian methodology is presented for integrated model calibration and risk-based water quality management using Bayesian Monte Carlo simulation and maximum likelihood estimation (BMCML). The primary focus is on lucid integration of model calibration with risk-based wat...

Advances in Bayesian Modeling in Educational Research

ERIC Educational Resources Information Center

Levy, Roy

2016-01-01

In this article, I provide a conceptually oriented overview of Bayesian approaches to statistical inference and contrast them with frequentist approaches that currently dominate conventional practice in educational research. The features and advantages of Bayesian approaches are illustrated with examples spanning several statistical modeling…

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 ...

A SEMIPARAMETRIC BAYESIAN MODEL FOR CIRCULAR-LINEAR REGRESSION

EPA Science Inventory

We present a Bayesian approach to regress a circular variable on a linear predictor. The regression coefficients are assumed to have a nonparametric distribution with a Dirichlet process prior. The semiparametric Bayesian approach gives added flexibility to the model and is usefu...

Bayesian truthing as experimental verification of C4ISR sensors

NASA Astrophysics Data System (ADS)

Jannson, Tomasz; Forrester, Thomas; Romanov, Volodymyr; Wang, Wenjian; Nielsen, Thomas; Kostrzewski, Andrew

2015-05-01

In this paper, the general methodology for experimental verification/validation of C4ISR and other sensors' performance, is presented, based on Bayesian inference, in general, and binary sensors, in particular. This methodology, called Bayesian Truthing, defines Performance Metrics for binary sensors in: physics, optics, electronics, medicine, law enforcement, C3ISR, QC, ATR (Automatic Target Recognition), terrorism related events, and many others. For Bayesian Truthing, the sensing medium itself is not what is truly important; it is how the decision process is affected.

National-scale aboveground biomass geostatistical mapping with FIA inventory and GLAS data: Preparation for sparsely sampled lidar assisted forest inventory

NASA Astrophysics Data System (ADS)

Babcock, C. R.; Finley, A. O.; Andersen, H. E.; Moskal, L. M.; Morton, D. C.; Cook, B.; Nelson, R.

2017-12-01

Upcoming satellite lidar missions, such as GEDI and IceSat-2, are designed to collect laser altimetry data from space for narrow bands along orbital tracts. As a result lidar metric sets derived from these sources will not be of complete spatial coverage. This lack of complete coverage, or sparsity, means traditional regression approaches that consider lidar metrics as explanatory variables (without error) cannot be used to generate wall-to-wall maps of forest inventory variables. We implement a coregionalization framework to jointly model sparsely sampled lidar information and point-referenced forest variable measurements to create wall-to-wall maps with full probabilistic uncertainty quantification of all inputs. We inform the model with USFS Forest Inventory and Analysis (FIA) in-situ forest measurements and GLAS lidar data to spatially predict aboveground forest biomass (AGB) across the contiguous US. We cast our model within a Bayesian hierarchical framework to better model complex space-varying correlation structures among the lidar metrics and FIA data, which yields improved prediction and uncertainty assessment. To circumvent computational difficulties that arise when fitting complex geostatistical models to massive datasets, we use a Nearest Neighbor Gaussian process (NNGP) prior. Results indicate that a coregionalization modeling approach to leveraging sampled lidar data to improve AGB estimation is effective. Further, fitting the coregionalization model within a Bayesian mode of inference allows for AGB quantification across scales ranging from individual pixel estimates of AGB density to total AGB for the continental US with uncertainty. The coregionalization framework examined here is directly applicable to future spaceborne lidar acquisitions from GEDI and IceSat-2. Pairing these lidar sources with the extensive FIA forest monitoring plot network using a joint prediction framework, such as the coregionalization model explored here, offers the potential to improve forest AGB accounting certainty and provide maps for post-model fitting analysis of the spatial distribution of AGB.

Bayesian Parameter Inference and Model Selection by Population Annealing in Systems Biology

PubMed Central

Murakami, Yohei

2014-01-01

Parameter inference and model selection are very important for mathematical modeling in systems biology. Bayesian statistics can be used to conduct both parameter inference and model selection. Especially, the framework named approximate Bayesian computation is often used for parameter inference and model selection in systems biology. However, Monte Carlo methods needs to be used to compute Bayesian posterior distributions. In addition, the posterior distributions of parameters are sometimes almost uniform or very similar to their prior distributions. In such cases, it is difficult to choose one specific value of parameter with high credibility as the representative value of the distribution. To overcome the problems, we introduced one of the population Monte Carlo algorithms, population annealing. Although population annealing is usually used in statistical mechanics, we showed that population annealing can be used to compute Bayesian posterior distributions in the approximate Bayesian computation framework. To deal with un-identifiability of the representative values of parameters, we proposed to run the simulations with the parameter ensemble sampled from the posterior distribution, named “posterior parameter ensemble”. We showed that population annealing is an efficient and convenient algorithm to generate posterior parameter ensemble. We also showed that the simulations with the posterior parameter ensemble can, not only reproduce the data used for parameter inference, but also capture and predict the data which was not used for parameter inference. Lastly, we introduced the marginal likelihood in the approximate Bayesian computation framework for Bayesian model selection. We showed that population annealing enables us to compute the marginal likelihood in the approximate Bayesian computation framework and conduct model selection depending on the Bayes factor. PMID:25089832

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.

Quantum mechanics: The Bayesian theory generalized to the space of Hermitian matrices

NASA Astrophysics Data System (ADS)

Benavoli, Alessio; Facchini, Alessandro; Zaffalon, Marco

2016-10-01

We consider the problem of gambling on a quantum experiment and enforce rational behavior by a few rules. These rules yield, in the classical case, the Bayesian theory of probability via duality theorems. In our quantum setting, they yield the Bayesian theory generalized to the space of Hermitian matrices. This very theory is quantum mechanics: in fact, we derive all its four postulates from the generalized Bayesian theory. This implies that quantum mechanics is self-consistent. It also leads us to reinterpret the main operations in quantum mechanics as probability rules: Bayes' rule (measurement), marginalization (partial tracing), independence (tensor product). To say it with a slogan, we obtain that quantum mechanics is the Bayesian theory in the complex numbers.

Defining Probability in Sex Offender Risk Assessment.

PubMed

Elwood, Richard W

2016-12-01

There is ongoing debate and confusion over using actuarial scales to predict individuals' risk of sexual recidivism. Much of the debate comes from not distinguishing Frequentist from Bayesian definitions of probability. Much of the confusion comes from applying Frequentist probability to individuals' risk. By definition, only Bayesian probability can be applied to the single case. The Bayesian concept of probability resolves most of the confusion and much of the debate in sex offender risk assessment. Although Bayesian probability is well accepted in risk assessment generally, it has not been widely used to assess the risk of sex offenders. I review the two concepts of probability and show how the Bayesian view alone provides a coherent scheme to conceptualize individuals' risk of sexual recidivism.

Accurate Biomass Estimation via Bayesian Adaptive Sampling

NASA Technical Reports Server (NTRS)

Wheeler, Kevin R.; Knuth, Kevin H.; Castle, Joseph P.; Lvov, Nikolay

2005-01-01

The following concepts were introduced: a) Bayesian adaptive sampling for solving biomass estimation; b) Characterization of MISR Rahman model parameters conditioned upon MODIS landcover. c) Rigorous non-parametric Bayesian approach to analytic mixture model determination. d) Unique U.S. asset for science product validation and verification.

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.

Bayesian cloud detection for MERIS, AATSR, and their combination

NASA Astrophysics Data System (ADS)

Hollstein, A.; Fischer, J.; Carbajal Henken, C.; Preusker, R.

2014-11-01

A broad range of different of Bayesian cloud detection schemes is applied to measurements from the Medium Resolution Imaging Spectrometer (MERIS), the Advanced Along-Track Scanning Radiometer (AATSR), and their combination. The cloud masks were designed to be numerically efficient and suited for the processing of large amounts of data. Results from the classical and naive approach to Bayesian cloud masking are discussed for MERIS and AATSR as well as for their combination. A sensitivity study on the resolution of multidimensional histograms, which were post-processed by Gaussian smoothing, shows how theoretically insufficient amounts of truth data can be used to set up accurate classical Bayesian cloud masks. Sets of exploited features from single and derived channels are numerically optimized and results for naive and classical Bayesian cloud masks are presented. The application of the Bayesian approach is discussed in terms of reproducing existing algorithms, enhancing existing algorithms, increasing the robustness of existing algorithms, and on setting up new classification schemes based on manually classified scenes.

Bayesian cloud detection for MERIS, AATSR, and their combination

NASA Astrophysics Data System (ADS)

Hollstein, A.; Fischer, J.; Carbajal Henken, C.; Preusker, R.

2015-04-01

A broad range of different of Bayesian cloud detection schemes is applied to measurements from the Medium Resolution Imaging Spectrometer (MERIS), the Advanced Along-Track Scanning Radiometer (AATSR), and their combination. The cloud detection schemes were designed to be numerically efficient and suited for the processing of large numbers of data. Results from the classical and naive approach to Bayesian cloud masking are discussed for MERIS and AATSR as well as for their combination. A sensitivity study on the resolution of multidimensional histograms, which were post-processed by Gaussian smoothing, shows how theoretically insufficient numbers of truth data can be used to set up accurate classical Bayesian cloud masks. Sets of exploited features from single and derived channels are numerically optimized and results for naive and classical Bayesian cloud masks are presented. The application of the Bayesian approach is discussed in terms of reproducing existing algorithms, enhancing existing algorithms, increasing the robustness of existing algorithms, and on setting up new classification schemes based on manually classified scenes.

Bayesian modeling of flexible cognitive control

PubMed Central

Jiang, Jiefeng; Heller, Katherine; Egner, Tobias

2014-01-01

“Cognitive control” describes endogenous guidance of behavior in situations where routine stimulus-response associations are suboptimal for achieving a desired goal. The computational and neural mechanisms underlying this capacity remain poorly understood. We examine recent advances stemming from the application of a Bayesian learner perspective that provides optimal prediction for control processes. In reviewing the application of Bayesian models to cognitive control, we note that an important limitation in current models is a lack of a plausible mechanism for the flexible adjustment of control over conflict levels changing at varying temporal scales. We then show that flexible cognitive control can be achieved by a Bayesian model with a volatility-driven learning mechanism that modulates dynamically the relative dependence on recent and remote experiences in its prediction of future control demand. We conclude that the emergent Bayesian perspective on computational mechanisms of cognitive control holds considerable promise, especially if future studies can identify neural substrates of the variables encoded by these models, and determine the nature (Bayesian or otherwise) of their neural implementation. PMID:24929218

Bayesian generalized linear mixed modeling of Tuberculosis using informative priors.

PubMed

Ojo, Oluwatobi Blessing; Lougue, Siaka; Woldegerima, Woldegebriel Assefa

2017-01-01

TB is rated as one of the world's deadliest diseases and South Africa ranks 9th out of the 22 countries with hardest hit of TB. Although many pieces of research have been carried out on this subject, this paper steps further by inculcating past knowledge into the model, using Bayesian approach with informative prior. Bayesian statistics approach is getting popular in data analyses. But, most applications of Bayesian inference technique are limited to situations of non-informative prior, where there is no solid external information about the distribution of the parameter of interest. The main aim of this study is to profile people living with TB in South Africa. In this paper, identical regression models are fitted for classical and Bayesian approach both with non-informative and informative prior, using South Africa General Household Survey (GHS) data for the year 2014. For the Bayesian model with informative prior, South Africa General Household Survey dataset for the year 2011 to 2013 are used to set up priors for the model 2014.

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

Bayesian estimation inherent in a Mexican-hat-type neural network

NASA Astrophysics Data System (ADS)

Takiyama, Ken

2016-05-01

Brain functions, such as perception, motor control and learning, and decision making, have been explained based on a Bayesian framework, i.e., to decrease the effects of noise inherent in the human nervous system or external environment, our brain integrates sensory and a priori information in a Bayesian optimal manner. However, it remains unclear how Bayesian computations are implemented in the brain. Herein, I address this issue by analyzing a Mexican-hat-type neural network, which was used as a model of the visual cortex, motor cortex, and prefrontal cortex. I analytically demonstrate that the dynamics of an order parameter in the model corresponds exactly to a variational inference of a linear Gaussian state-space model, a Bayesian estimation, when the strength of recurrent synaptic connectivity is appropriately stronger than that of an external stimulus, a plausible condition in the brain. This exact correspondence can reveal the relationship between the parameters in the Bayesian estimation and those in the neural network, providing insight for understanding brain functions.

Uses and misuses of Bayes' rule and Bayesian classifiers in cybersecurity

NASA Astrophysics Data System (ADS)

Bard, Gregory V.

2017-12-01

This paper will discuss the applications of Bayes' Rule and Bayesian Classifiers in Cybersecurity. While the most elementary form of Bayes' rule occurs in undergraduate coursework, there are more complicated forms as well. As an extended example, Bayesian spam filtering is explored, and is in many ways the most triumphant accomplishment of Bayesian reasoning in computer science, as nearly everyone with an email address has a spam folder. Bayesian Classifiers have also been responsible significant cybersecurity research results; yet, because they are not part of the standard curriculum, few in the mathematics or information-technology communities have seen the exact definitions, requirements, and proofs that comprise the subject. Moreover, numerous errors have been made by researchers (described in this paper), due to some mathematical misunderstandings dealing with conditional independence, or other badly chosen assumptions. Finally, to provide instructors and researchers with real-world examples, 25 published cybersecurity papers that use Bayesian reasoning are given, with 2-4 sentence summaries of the focus and contributions of each paper.

Win-Stay, Lose-Sample: a simple sequential algorithm for approximating Bayesian inference.

PubMed

Bonawitz, Elizabeth; Denison, Stephanie; Gopnik, Alison; Griffiths, Thomas L

2014-11-01

People can behave in a way that is consistent with Bayesian models of cognition, despite the fact that performing exact Bayesian inference is computationally challenging. What algorithms could people be using to make this possible? We show that a simple sequential algorithm "Win-Stay, Lose-Sample", inspired by the Win-Stay, Lose-Shift (WSLS) principle, can be used to approximate Bayesian inference. We investigate the behavior of adults and preschoolers on two causal learning tasks to test whether people might use a similar algorithm. These studies use a "mini-microgenetic method", investigating how people sequentially update their beliefs as they encounter new evidence. Experiment 1 investigates a deterministic causal learning scenario and Experiments 2 and 3 examine how people make inferences in a stochastic scenario. The behavior of adults and preschoolers in these experiments is consistent with our Bayesian version of the WSLS principle. This algorithm provides both a practical method for performing Bayesian inference and a new way to understand people's judgments. Copyright © 2014 Elsevier Inc. All rights reserved.

Leveraging 35 years of Pinus taeda research in the southeastern US to constrain forest carbon cycle predictions: regional data assimilation using ecosystem experiments

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

Thomas, R. Quinn; Brooks, Evan B.; Jersild, Annika L.

Predicting how forest carbon cycling will change in response to climate change and management depends on the collective knowledge from measurements across environmental gradients, ecosystem manipulations of global change factors, and mathematical models. Formally integrating these sources of knowledge through data assimilation, or model–data fusion, allows the use of past observations to constrain model parameters and estimate prediction uncertainty. Data assimilation (DA) focused on the regional scale has the opportunity to integrate data from both environmental gradients and experimental studies to constrain model parameters. Here, we introduce a hierarchical Bayesian DA approach (Data Assimilation to Predict Productivity for Ecosystems and Regions,more » DAPPER) that uses observations of carbon stocks, carbon fluxes, water fluxes, and vegetation dynamics from loblolly pine plantation ecosystems across the southeastern US to constrain parameters in a modified version of the Physiological Principles Predicting Growth (3-PG) forest growth model. The observations included major experiments that manipulated atmospheric carbon dioxide (CO 2) concentration, water, and nutrients, along with nonexperimental surveys that spanned environmental gradients across an 8.6 × 10 5 km 2 region. We optimized regionally representative posterior distributions for model parameters, which dependably predicted data from plots withheld from the data assimilation. While the mean bias in predictions of nutrient fertilization experiments, irrigation experiments, and CO 2 enrichment experiments was low, future work needs to focus modifications to model structures that decrease the bias in predictions of drought experiments. Predictions of how growth responded to elevated CO 2 strongly depended on whether ecosystem experiments were assimilated and whether the assimilated field plots in the CO 2 study were allowed to have different mortality parameters than the other field plots in the region. We present predictions of stem biomass productivity under elevated CO 2, decreased precipitation, and increased nutrient availability that include estimates of uncertainty for the southeastern US. Overall, we (1) demonstrated how three decades of research in southeastern US planted pine forests can be used to develop DA techniques that use multiple locations, multiple data streams, and multiple ecosystem experiment types to optimize parameters and (2) developed a tool for the development of future predictions of forest productivity for natural resource managers that leverage a rich dataset of integrated ecosystem observations across a region.« less

Leveraging 35 years of Pinus taeda research in the southeastern US to constrain forest carbon cycle predictions: regional data assimilation using ecosystem experiments

DOE PAGES

Thomas, R. Quinn; Brooks, Evan B.; Jersild, Annika L.; ...

2017-07-26

Predicting how forest carbon cycling will change in response to climate change and management depends on the collective knowledge from measurements across environmental gradients, ecosystem manipulations of global change factors, and mathematical models. Formally integrating these sources of knowledge through data assimilation, or model–data fusion, allows the use of past observations to constrain model parameters and estimate prediction uncertainty. Data assimilation (DA) focused on the regional scale has the opportunity to integrate data from both environmental gradients and experimental studies to constrain model parameters. Here, we introduce a hierarchical Bayesian DA approach (Data Assimilation to Predict Productivity for Ecosystems and Regions,more » DAPPER) that uses observations of carbon stocks, carbon fluxes, water fluxes, and vegetation dynamics from loblolly pine plantation ecosystems across the southeastern US to constrain parameters in a modified version of the Physiological Principles Predicting Growth (3-PG) forest growth model. The observations included major experiments that manipulated atmospheric carbon dioxide (CO 2) concentration, water, and nutrients, along with nonexperimental surveys that spanned environmental gradients across an 8.6 × 10 5 km 2 region. We optimized regionally representative posterior distributions for model parameters, which dependably predicted data from plots withheld from the data assimilation. While the mean bias in predictions of nutrient fertilization experiments, irrigation experiments, and CO 2 enrichment experiments was low, future work needs to focus modifications to model structures that decrease the bias in predictions of drought experiments. Predictions of how growth responded to elevated CO 2 strongly depended on whether ecosystem experiments were assimilated and whether the assimilated field plots in the CO 2 study were allowed to have different mortality parameters than the other field plots in the region. We present predictions of stem biomass productivity under elevated CO 2, decreased precipitation, and increased nutrient availability that include estimates of uncertainty for the southeastern US. Overall, we (1) demonstrated how three decades of research in southeastern US planted pine forests can be used to develop DA techniques that use multiple locations, multiple data streams, and multiple ecosystem experiment types to optimize parameters and (2) developed a tool for the development of future predictions of forest productivity for natural resource managers that leverage a rich dataset of integrated ecosystem observations across a region.« less

Leveraging 35 years of Pinus taeda research in the southeastern US to constrain forest carbon cycle predictions: regional data assimilation using ecosystem experiments

NASA Astrophysics Data System (ADS)

Quinn Thomas, R.; Brooks, Evan B.; Jersild, Annika L.; Ward, Eric J.; Wynne, Randolph H.; Albaugh, Timothy J.; Dinon-Aldridge, Heather; Burkhart, Harold E.; Domec, Jean-Christophe; Fox, Thomas R.; Gonzalez-Benecke, Carlos A.; Martin, Timothy A.; Noormets, Asko; Sampson, David A.; Teskey, Robert O.

2017-07-01

Predicting how forest carbon cycling will change in response to climate change and management depends on the collective knowledge from measurements across environmental gradients, ecosystem manipulations of global change factors, and mathematical models. Formally integrating these sources of knowledge through data assimilation, or model-data fusion, allows the use of past observations to constrain model parameters and estimate prediction uncertainty. Data assimilation (DA) focused on the regional scale has the opportunity to integrate data from both environmental gradients and experimental studies to constrain model parameters. Here, we introduce a hierarchical Bayesian DA approach (Data Assimilation to Predict Productivity for Ecosystems and Regions, DAPPER) that uses observations of carbon stocks, carbon fluxes, water fluxes, and vegetation dynamics from loblolly pine plantation ecosystems across the southeastern US to constrain parameters in a modified version of the Physiological Principles Predicting Growth (3-PG) forest growth model. The observations included major experiments that manipulated atmospheric carbon dioxide (CO2) concentration, water, and nutrients, along with nonexperimental surveys that spanned environmental gradients across an 8.6 × 105 km2 region. We optimized regionally representative posterior distributions for model parameters, which dependably predicted data from plots withheld from the data assimilation. While the mean bias in predictions of nutrient fertilization experiments, irrigation experiments, and CO2 enrichment experiments was low, future work needs to focus modifications to model structures that decrease the bias in predictions of drought experiments. Predictions of how growth responded to elevated CO2 strongly depended on whether ecosystem experiments were assimilated and whether the assimilated field plots in the CO2 study were allowed to have different mortality parameters than the other field plots in the region. We present predictions of stem biomass productivity under elevated CO2, decreased precipitation, and increased nutrient availability that include estimates of uncertainty for the southeastern US. Overall, we (1) demonstrated how three decades of research in southeastern US planted pine forests can be used to develop DA techniques that use multiple locations, multiple data streams, and multiple ecosystem experiment types to optimize parameters and (2) developed a tool for the development of future predictions of forest productivity for natural resource managers that leverage a rich dataset of integrated ecosystem observations across a region.

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.

A systematic review of Bayesian articles in psychology: The last 25 years.

PubMed

van de Schoot, Rens; Winter, Sonja D; Ryan, Oisín; Zondervan-Zwijnenburg, Mariëlle; Depaoli, Sarah

2017-06-01

Although the statistical tools most often used by researchers in the field of psychology over the last 25 years are based on frequentist statistics, it is often claimed that the alternative Bayesian approach to statistics is gaining in popularity. In the current article, we investigated this claim by performing the very first systematic review of Bayesian psychological articles published between 1990 and 2015 (n = 1,579). We aim to provide a thorough presentation of the role Bayesian statistics plays in psychology. This historical assessment allows us to identify trends and see how Bayesian methods have been integrated into psychological research in the context of different statistical frameworks (e.g., hypothesis testing, cognitive models, IRT, SEM, etc.). We also describe take-home messages and provide "big-picture" recommendations to the field as Bayesian statistics becomes more popular. Our review indicated that Bayesian statistics is used in a variety of contexts across subfields of psychology and related disciplines. There are many different reasons why one might choose to use Bayes (e.g., the use of priors, estimating otherwise intractable models, modeling uncertainty, etc.). We found in this review that the use of Bayes has increased and broadened in the sense that this methodology can be used in a flexible manner to tackle many different forms of questions. We hope this presentation opens the door for a larger discussion regarding the current state of Bayesian statistics, as well as future trends. (PsycINFO Database Record (c) 2017 APA, all rights reserved).

Modelling UV irradiances on arbitrarily oriented surfaces: effects of sky obstructions

NASA Astrophysics Data System (ADS)

Hess, M.; Koepke, P.

2008-02-01

A method is presented to calculate UV irradiances on inclined surfaces that additionally takes into account the influence of sky obstructions caused by obstacles such as mountains, houses, trees, or umbrellas. Thus the method allows calculating the impact of UV radiation on biological systems, such as for instance the human skin or eye, in any natural or artificial environment. The method, a combination of radiation models, is explained and the correctness of its results is demonstrated. The effect of a natural skyline is shown for an Alpine ski area, where the UV irradiance even on a horizontal surface may increase due to reflection at snow by more than 10%. In contrast in a street canyon the irradiance on a horizontal surface is reduced down to 30% in shadow and to about 75% for a position in the sun.

Progress made in understanding Mount Rainier's hazards

USGS Publications Warehouse

Sisson, T.W.; Vallance, J.W.; Pringle, P.T.

2001-01-01

At 4392 m high, glacier-clad Mount Rainier dominates the skyline of the southern Puget Sound region and is the centerpiece of Mount Rainier National Park. About 2.5 million people of the greater Seattle-Tacoma metropolitan area can see Mount Rainier on clear days, and 150,000 live in areas swept by lahars and floods that emanated from the volcano during the last 6,000 years (Figure 1). These lahars include the voluminous Osceola Mudflow that floors the lowlands south of Seattle and east of Tacoma, and which was generated by massive volcano flank-collapse. Mount Rainier's last eruption was a light dusting of ash in 1894; minor pumice last erupted between 1820 and 1854; and the most recent large eruptions we know of were about 1100 and 2300 years ago, according to reports from the U.S. Geological Survey.

Photogrammetric mobile satellite service prediction

NASA Technical Reports Server (NTRS)

Akturan, Riza; Vogel, Wolfhard J.

1994-01-01

Photographic images of the sky were taken with a camera through a fisheye lens with a 180 deg field-of-view. The images of rural, suburban, and urban scenes were analyzed on a computer to derive quantitative information about the elevation angles at which the sky becomes visible. Such knowledge is needed by designers of mobile and personal satellite communications systems and is desired by customers of these systems. The 90th percentile elevation angle of the skyline was found to be 10 deg, 17 deg, and 51 deg in the three environments. At 8 deg, 75 percent, 75 percent, and 35 percent of the sky was visible, respectively. The elevation autocorrelation fell to zero with a 72 deg lag in the rural and urban environment and a 40 deg lag in the suburb. Mean estimation errors are below 4 deg.

Using a multifrontal sparse solver in a high performance, finite element code

NASA Technical Reports Server (NTRS)

King, Scott D.; Lucas, Robert; Raefsky, Arthur

1990-01-01

We consider the performance of the finite element method on a vector supercomputer. The computationally intensive parts of the finite element method are typically the individual element forms and the solution of the global stiffness matrix both of which are vectorized in high performance codes. To further increase throughput, new algorithms are needed. We compare a multifrontal sparse solver to a traditional skyline solver in a finite element code on a vector supercomputer. The multifrontal solver uses the Multiple-Minimum Degree reordering heuristic to reduce the number of operations required to factor a sparse matrix and full matrix computational kernels (e.g., BLAS3) to enhance vector performance. The net result in an order-of-magnitude reduction in run time for a finite element application on one processor of a Cray X-MP.

The Bayesian Revolution Approaches Psychological Development

ERIC Educational Resources Information Center

Shultz, Thomas R.

2007-01-01

This commentary reviews five articles that apply Bayesian ideas to psychological development, some with psychology experiments, some with computational modeling, and some with both experiments and modeling. The reviewed work extends the current Bayesian revolution into tasks often studied in children, such as causal learning and word learning, and…

Covariate Balance in Bayesian Propensity Score Approaches for Observational Studies

ERIC Educational Resources Information Center

Chen, Jianshen; Kaplan, David

2015-01-01

Bayesian alternatives to frequentist propensity score approaches have recently been proposed. However, few studies have investigated their covariate balancing properties. This article compares a recently developed two-step Bayesian propensity score approach to the frequentist approach with respect to covariate balance. The effects of different…

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…

What Is the Probability You Are a Bayesian?

ERIC Educational Resources Information Center

Wulff, Shaun S.; Robinson, Timothy J.

2014-01-01

Bayesian methodology continues to be widely used in statistical applications. As a result, it is increasingly important to introduce students to Bayesian thinking at early stages in their mathematics and statistics education. While many students in upper level probability courses can recite the differences in the Frequentist and Bayesian…

Using Bayesian Networks to Improve Knowledge Assessment

ERIC Educational Resources Information Center

Millan, Eva; Descalco, Luis; Castillo, Gladys; Oliveira, Paula; Diogo, Sandra

2013-01-01

In this paper, we describe the integration and evaluation of an existing generic Bayesian student model (GBSM) into an existing computerized testing system within the Mathematics Education Project (PmatE--Projecto Matematica Ensino) of the University of Aveiro. This generic Bayesian student model had been previously evaluated with simulated…

Bayesian Decision Theoretical Framework for Clustering

ERIC Educational Resources Information Center

Chen, Mo

2011-01-01

In this thesis, we establish a novel probabilistic framework for the data clustering problem from the perspective of Bayesian decision theory. The Bayesian decision theory view justifies the important questions: what is a cluster and what a clustering algorithm should optimize. We prove that the spectral clustering (to be specific, the…

Using Bayesian belief networks in adaptive management.

Treesearch

J.B. Nyberg; B.G. Marcot; R. Sulyma

2006-01-01

Bayesian belief and decision networks are relatively new modeling methods that are especially well suited to adaptive-management applications, but they appear not to have been widely used in adaptive management to date. Bayesian belief networks (BBNs) can serve many purposes for practioners of adaptive management, from illustrating system relations conceptually to...

Using Alien Coins to Test Whether Simple Inference Is Bayesian

ERIC Educational Resources Information Center

Cassey, Peter; Hawkins, Guy E.; Donkin, Chris; Brown, Scott D.

2016-01-01

Reasoning and inference are well-studied aspects of basic cognition that have been explained as statistically optimal Bayesian inference. Using a simplified experimental design, we conducted quantitative comparisons between Bayesian inference and human inference at the level of individuals. In 3 experiments, with more than 13,000 participants, we…

On Bayesian Testing of Additive Conjoint Measurement Axioms Using Synthetic Likelihood

ERIC Educational Resources Information Center

Karabatsos, George

2017-01-01

This article introduces a Bayesian method for testing the axioms of additive conjoint measurement. The method is based on an importance sampling algorithm that performs likelihood-free, approximate Bayesian inference using a synthetic likelihood to overcome the analytical intractability of this testing problem. This new method improves upon…

Searching Algorithm Using Bayesian Updates

ERIC Educational Resources Information Center

Caudle, Kyle

2010-01-01

In late October 1967, the USS Scorpion was lost at sea, somewhere between the Azores and Norfolk Virginia. Dr. Craven of the U.S. Navy's Special Projects Division is credited with using Bayesian Search Theory to locate the submarine. Bayesian Search Theory is a straightforward and interesting application of Bayes' theorem which involves searching…

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…

Dynamic Bayesian Network Modeling of Game Based Diagnostic Assessments. CRESST Report 837

ERIC Educational Resources Information Center

Levy, Roy

2014-01-01

Digital games offer an appealing environment for assessing student proficiencies, including skills and misconceptions in a diagnostic setting. This paper proposes a dynamic Bayesian network modeling approach for observations of student performance from an educational video game. A Bayesian approach to model construction, calibration, and use in…

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…

Modeling Diagnostic Assessments with Bayesian Networks

ERIC Educational Resources Information Center

Almond, Russell G.; DiBello, Louis V.; Moulder, Brad; Zapata-Rivera, Juan-Diego

2007-01-01

This paper defines Bayesian network models and examines their applications to IRT-based cognitive diagnostic modeling. These models are especially suited to building inference engines designed to be synchronous with the finer grained student models that arise in skills diagnostic assessment. Aspects of the theory and use of Bayesian network models…

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.

Technical Topic 3.2.2.d Bayesian and Non-Parametric Statistics: Integration of Neural Networks with Bayesian Networks for Data Fusion and Predictive Modeling

DTIC Science & Technology

2016-05-31

and included explosives such as TATP, HMTD, RDX, RDX, ammonium nitrate , potassium perchlorate, potassium nitrate , sugar, and TNT. The approach...Distribution Unlimited UU UU UU UU 31-05-2016 15-Apr-2014 14-Jan-2015 Final Report: Technical Topic 3.2.2. d Bayesian and Non- parametric Statistics...of Papers published in non peer-reviewed journals: Final Report: Technical Topic 3.2.2. d Bayesian and Non-parametric Statistics: Integration of Neural

Editorial: Bayesian benefits for child psychology and psychiatry researchers.

PubMed

Oldehinkel, Albertine J

2016-09-01

For many scientists, performing statistical tests has become an almost automated routine. However, p-values are frequently used and interpreted incorrectly; and even when used appropriately, p-values tend to provide answers that do not match researchers' questions and hypotheses well. Bayesian statistics present an elegant and often more suitable alternative. The Bayesian approach has rarely been applied in child psychology and psychiatry research so far, but the development of user-friendly software packages and tutorials has placed it well within reach now. Because Bayesian analyses require a more refined definition of hypothesized probabilities of possible outcomes than the classical approach, going Bayesian may offer the additional benefit of sparkling the development and refinement of theoretical models in our field. © 2016 Association for Child and Adolescent Mental Health.

Quantum-Like Representation of Non-Bayesian Inference

NASA Astrophysics Data System (ADS)

Asano, M.; Basieva, I.; Khrennikov, A.; Ohya, M.; Tanaka, Y.

2013-01-01

This research is related to the problem of "irrational decision making or inference" that have been discussed in cognitive psychology. There are some experimental studies, and these statistical data cannot be described by classical probability theory. The process of decision making generating these data cannot be reduced to the classical Bayesian inference. For this problem, a number of quantum-like coginitive models of decision making was proposed. Our previous work represented in a natural way the classical Bayesian inference in the frame work of quantum mechanics. By using this representation, in this paper, we try to discuss the non-Bayesian (irrational) inference that is biased by effects like the quantum interference. Further, we describe "psychological factor" disturbing "rationality" as an "environment" correlating with the "main system" of usual Bayesian inference.

Evidence reasoning method for constructing conditional probability tables in a Bayesian network of multimorbidity.

PubMed

Du, Yuanwei; Guo, Yubin

2015-01-01

The intrinsic mechanism of multimorbidity is difficult to recognize and prediction and diagnosis are difficult to carry out accordingly. Bayesian networks can help to diagnose multimorbidity in health care, but it is difficult to obtain the conditional probability table (CPT) because of the lack of clinically statistical data. Today, expert knowledge and experience are increasingly used in training Bayesian networks in order to help predict or diagnose diseases, but the CPT in Bayesian networks is usually irrational or ineffective for ignoring realistic constraints especially in multimorbidity. In order to solve these problems, an evidence reasoning (ER) approach is employed to extract and fuse inference data from experts using a belief distribution and recursive ER algorithm, based on which evidence reasoning method for constructing conditional probability tables in Bayesian network of multimorbidity is presented step by step. A multimorbidity numerical example is used to demonstrate the method and prove its feasibility and application. Bayesian network can be determined as long as the inference assessment is inferred by each expert according to his/her knowledge or experience. Our method is more effective than existing methods for extracting expert inference data accurately and is fused effectively for constructing CPTs in a Bayesian network of multimorbidity.

Bayesian techniques for analyzing group differences in the Iowa Gambling Task: A case study of intuitive and deliberate decision-makers.

PubMed

Steingroever, Helen; Pachur, Thorsten; Šmíra, Martin; Lee, Michael D

2018-06-01

The Iowa Gambling Task (IGT) is one of the most popular experimental paradigms for comparing complex decision-making across groups. Most commonly, IGT behavior is analyzed using frequentist tests to compare performance across groups, and to compare inferred parameters of cognitive models developed for the IGT. Here, we present a Bayesian alternative based on Bayesian repeated-measures ANOVA for comparing performance, and a suite of three complementary model-based methods for assessing the cognitive processes underlying IGT performance. The three model-based methods involve Bayesian hierarchical parameter estimation, Bayes factor model comparison, and Bayesian latent-mixture modeling. We illustrate these Bayesian methods by applying them to test the extent to which differences in intuitive versus deliberate decision style are associated with differences in IGT performance. The results show that intuitive and deliberate decision-makers behave similarly on the IGT, and the modeling analyses consistently suggest that both groups of decision-makers rely on similar cognitive processes. Our results challenge the notion that individual differences in intuitive and deliberate decision styles have a broad impact on decision-making. They also highlight the advantages of Bayesian methods, especially their ability to quantify evidence in favor of the null hypothesis, and that they allow model-based analyses to incorporate hierarchical and latent-mixture structures.

Invited commentary: Lost in estimation--searching for alternatives to markov chains to fit complex Bayesian models.

PubMed

Molitor, John

2012-03-01

Bayesian methods have seen an increase in popularity in a wide variety of scientific fields, including epidemiology. One of the main reasons for their widespread application is the power of the Markov chain Monte Carlo (MCMC) techniques generally used to fit these models. As a result, researchers often implicitly associate Bayesian models with MCMC estimation procedures. However, Bayesian models do not always require Markov-chain-based methods for parameter estimation. This is important, as MCMC estimation methods, while generally quite powerful, are complex and computationally expensive and suffer from convergence problems related to the manner in which they generate correlated samples used to estimate probability distributions for parameters of interest. In this issue of the Journal, Cole et al. (Am J Epidemiol. 2012;175(5):368-375) present an interesting paper that discusses non-Markov-chain-based approaches to fitting Bayesian models. These methods, though limited, can overcome some of the problems associated with MCMC techniques and promise to provide simpler approaches to fitting Bayesian models. Applied researchers will find these estimation approaches intuitively appealing and will gain a deeper understanding of Bayesian models through their use. However, readers should be aware that other non-Markov-chain-based methods are currently in active development and have been widely published in other fields.

Using Bayesian Adaptive Trial Designs for Comparative Effectiveness Research: A Virtual Trial Execution.

PubMed

Luce, Bryan R; Connor, Jason T; Broglio, Kristine R; Mullins, C Daniel; Ishak, K Jack; Saunders, Elijah; Davis, Barry R

2016-09-20

Bayesian and adaptive clinical trial designs offer the potential for more efficient processes that result in lower sample sizes and shorter trial durations than traditional designs. To explore the use and potential benefits of Bayesian adaptive clinical trial designs in comparative effectiveness research. Virtual execution of ALLHAT (Antihypertensive and Lipid-Lowering Treatment to Prevent Heart Attack Trial) as if it had been done according to a Bayesian adaptive trial design. Comparative effectiveness trial of antihypertensive medications. Patient data sampled from the more than 42 000 patients enrolled in ALLHAT with publicly available data. Number of patients randomly assigned between groups, trial duration, observed numbers of events, and overall trial results and conclusions. The Bayesian adaptive approach and original design yielded similar overall trial conclusions. The Bayesian adaptive trial randomly assigned more patients to the better-performing group and would probably have ended slightly earlier. This virtual trial execution required limited resampling of ALLHAT patients for inclusion in RE-ADAPT (REsearch in ADAptive methods for Pragmatic Trials). Involvement of a data monitoring committee and other trial logistics were not considered. In a comparative effectiveness research trial, Bayesian adaptive trial designs are a feasible approach and potentially generate earlier results and allocate more patients to better-performing groups. National Heart, Lung, and Blood Institute.

Good fences make for good neighbors but bad science: a review of what improves Bayesian reasoning and why

PubMed Central

Brase, Gary L.; Hill, W. Trey

2015-01-01

Bayesian reasoning, defined here as the updating of a posterior probability following new information, has historically been problematic for humans. Classic psychology experiments have tested human Bayesian reasoning through the use of word problems and have evaluated each participant’s performance against the normatively correct answer provided by Bayes’ theorem. The standard finding is of generally poor performance. Over the past two decades, though, progress has been made on how to improve Bayesian reasoning. Most notably, research has demonstrated that the use of frequencies in a natural sampling framework—as opposed to single-event probabilities—can improve participants’ Bayesian estimates. Furthermore, pictorial aids and certain individual difference factors also can play significant roles in Bayesian reasoning success. The mechanics of how to build tasks which show these improvements is not under much debate. The explanations for why naturally sampled frequencies and pictures help Bayesian reasoning remain hotly contested, however, with many researchers falling into ingrained “camps” organized around two dominant theoretical perspectives. The present paper evaluates the merits of these theoretical perspectives, including the weight of empirical evidence, theoretical coherence, and predictive power. By these criteria, the ecological rationality approach is clearly better than the heuristics and biases view. Progress in the study of Bayesian reasoning will depend on continued research that honestly, vigorously, and consistently engages across these different theoretical accounts rather than staying “siloed” within one particular perspective. The process of science requires an understanding of competing points of view, with the ultimate goal being integration. PMID:25873904

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.

Good fences make for good neighbors but bad science: a review of what improves Bayesian reasoning and why.

PubMed

Brase, Gary L; Hill, W Trey

2015-01-01

Bayesian reasoning, defined here as the updating of a posterior probability following new information, has historically been problematic for humans. Classic psychology experiments have tested human Bayesian reasoning through the use of word problems and have evaluated each participant's performance against the normatively correct answer provided by Bayes' theorem. The standard finding is of generally poor performance. Over the past two decades, though, progress has been made on how to improve Bayesian reasoning. Most notably, research has demonstrated that the use of frequencies in a natural sampling framework-as opposed to single-event probabilities-can improve participants' Bayesian estimates. Furthermore, pictorial aids and certain individual difference factors also can play significant roles in Bayesian reasoning success. The mechanics of how to build tasks which show these improvements is not under much debate. The explanations for why naturally sampled frequencies and pictures help Bayesian reasoning remain hotly contested, however, with many researchers falling into ingrained "camps" organized around two dominant theoretical perspectives. The present paper evaluates the merits of these theoretical perspectives, including the weight of empirical evidence, theoretical coherence, and predictive power. By these criteria, the ecological rationality approach is clearly better than the heuristics and biases view. Progress in the study of Bayesian reasoning will depend on continued research that honestly, vigorously, and consistently engages across these different theoretical accounts rather than staying "siloed" within one particular perspective. The process of science requires an understanding of competing points of view, with the ultimate goal being integration.

A Bayesian pick-the-winner design in a randomized phase II clinical trial.

PubMed

Chen, Dung-Tsa; Huang, Po-Yu; Lin, Hui-Yi; Chiappori, Alberto A; Gabrilovich, Dmitry I; Haura, Eric B; Antonia, Scott J; Gray, Jhanelle E

2017-10-24

Many phase II clinical trials evaluate unique experimental drugs/combinations through multi-arm design to expedite the screening process (early termination of ineffective drugs) and to identify the most effective drug (pick the winner) to warrant a phase III trial. Various statistical approaches have been developed for the pick-the-winner design but have been criticized for lack of objective comparison among the drug agents. We developed a Bayesian pick-the-winner design by integrating a Bayesian posterior probability with Simon two-stage design in a randomized two-arm clinical trial. The Bayesian posterior probability, as the rule to pick the winner, is defined as probability of the response rate in one arm higher than in the other arm. The posterior probability aims to determine the winner when both arms pass the second stage of the Simon two-stage design. When both arms are competitive (i.e., both passing the second stage), the Bayesian posterior probability performs better to correctly identify the winner compared with the Fisher exact test in the simulation study. In comparison to a standard two-arm randomized design, the Bayesian pick-the-winner design has a higher power to determine a clear winner. In application to two studies, the approach is able to perform statistical comparison of two treatment arms and provides a winner probability (Bayesian posterior probability) to statistically justify the winning arm. We developed an integrated design that utilizes Bayesian posterior probability, Simon two-stage design, and randomization into a unique setting. It gives objective comparisons between the arms to determine the winner.

A Variational Bayes Genomic-Enabled Prediction Model with Genotype × Environment Interaction

PubMed Central

Montesinos-López, Osval A.; Montesinos-López, Abelardo; Crossa, José; Montesinos-López, José Cricelio; Luna-Vázquez, Francisco Javier; Salinas-Ruiz, Josafhat; Herrera-Morales, José R.; Buenrostro-Mariscal, Raymundo

2017-01-01

There are Bayesian and non-Bayesian genomic models that take into account G×E interactions. However, the computational cost of implementing Bayesian models is high, and becomes almost impossible when the number of genotypes, environments, and traits is very large, while, in non-Bayesian models, there are often important and unsolved convergence problems. The variational Bayes method is popular in machine learning, and, by approximating the probability distributions through optimization, it tends to be faster than Markov Chain Monte Carlo methods. For this reason, in this paper, we propose a new genomic variational Bayes version of the Bayesian genomic model with G×E using half-t priors on each standard deviation (SD) term to guarantee highly noninformative and posterior inferences that are not sensitive to the choice of hyper-parameters. We show the complete theoretical derivation of the full conditional and the variational posterior distributions, and their implementations. We used eight experimental genomic maize and wheat data sets to illustrate the new proposed variational Bayes approximation, and compared its predictions and implementation time with a standard Bayesian genomic model with G×E. Results indicated that prediction accuracies are slightly higher in the standard Bayesian model with G×E than in its variational counterpart, but, in terms of computation time, the variational Bayes genomic model with G×E is, in general, 10 times faster than the conventional Bayesian genomic model with G×E. For this reason, the proposed model may be a useful tool for researchers who need to predict and select genotypes in several environments. PMID:28391241

Bayesian estimates of the incidence of rare cancers in Europe.

PubMed

Botta, Laura; Capocaccia, Riccardo; Trama, Annalisa; Herrmann, Christian; Salmerón, Diego; De Angelis, Roberta; Mallone, Sandra; Bidoli, Ettore; Marcos-Gragera, Rafael; Dudek-Godeau, Dorota; Gatta, Gemma; Cleries, Ramon

2018-04-21

The RARECAREnet project has updated the estimates of the burden of the 198 rare cancers in each European country. Suspecting that scant data could affect the reliability of statistical analysis, we employed a Bayesian approach to estimate the incidence of these cancers. We analyzed about 2,000,000 rare cancers diagnosed in 2000-2007 provided by 83 population-based cancer registries from 27 European countries. We considered European incidence rates (IRs), calculated over all the data available in RARECAREnet, as a valid a priori to merge with country-specific observed data. Therefore we provided (1) Bayesian estimates of IRs and the yearly numbers of cases of rare cancers in each country; (2) the expected time (T) in years needed to observe one new case; and (3) practical criteria to decide when to use the Bayesian approach. Bayesian and classical estimates did not differ much; substantial differences (>10%) ranged from 77 rare cancers in Iceland to 14 in England. The smaller the population the larger the number of rare cancers needing a Bayesian approach. Bayesian estimates were useful for cancers with fewer than 150 observed cases in a country during the study period; this occurred mostly when the population of the country is small. For the first time the Bayesian estimates of IRs and the yearly expected numbers of cases for each rare cancer in each individual European country were calculated. Moreover, the indicator T is useful to convey incidence estimates for exceptionally rare cancers and in small countries; it far exceeds the professional lifespan of a medical doctor. Copyright © 2018 Elsevier Ltd. All rights reserved.

A Variational Bayes Genomic-Enabled Prediction Model with Genotype × Environment Interaction.

PubMed

Montesinos-López, Osval A; Montesinos-López, Abelardo; Crossa, José; Montesinos-López, José Cricelio; Luna-Vázquez, Francisco Javier; Salinas-Ruiz, Josafhat; Herrera-Morales, José R; Buenrostro-Mariscal, Raymundo

2017-06-07

There are Bayesian and non-Bayesian genomic models that take into account G×E interactions. However, the computational cost of implementing Bayesian models is high, and becomes almost impossible when the number of genotypes, environments, and traits is very large, while, in non-Bayesian models, there are often important and unsolved convergence problems. The variational Bayes method is popular in machine learning, and, by approximating the probability distributions through optimization, it tends to be faster than Markov Chain Monte Carlo methods. For this reason, in this paper, we propose a new genomic variational Bayes version of the Bayesian genomic model with G×E using half-t priors on each standard deviation (SD) term to guarantee highly noninformative and posterior inferences that are not sensitive to the choice of hyper-parameters. We show the complete theoretical derivation of the full conditional and the variational posterior distributions, and their implementations. We used eight experimental genomic maize and wheat data sets to illustrate the new proposed variational Bayes approximation, and compared its predictions and implementation time with a standard Bayesian genomic model with G×E. Results indicated that prediction accuracies are slightly higher in the standard Bayesian model with G×E than in its variational counterpart, but, in terms of computation time, the variational Bayes genomic model with G×E is, in general, 10 times faster than the conventional Bayesian genomic model with G×E. For this reason, the proposed model may be a useful tool for researchers who need to predict and select genotypes in several environments. Copyright © 2017 Montesinos-López et al.

Stan : A Probabilistic Programming Language

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

Carpenter, Bob; Gelman, Andrew; Hoffman, Matthew D.

Stan is a probabilistic programming language for specifying statistical models. A Stan program imperatively defines a log probability function over parameters conditioned on specified data and constants. As of version 2.14.0, Stan provides full Bayesian inference for continuous-variable models through Markov chain Monte Carlo methods such as the No-U-Turn sampler, an adaptive form of Hamiltonian Monte Carlo sampling. Penalized maximum likelihood estimates are calculated using optimization methods such as the limited memory Broyden-Fletcher-Goldfarb-Shanno algorithm. Stan is also a platform for computing log densities and their gradients and Hessians, which can be used in alternative algorithms such as variational Bayes, expectationmore » propagation, and marginal inference using approximate integration. To this end, Stan is set up so that the densities, gradients, and Hessians, along with intermediate quantities of the algorithm such as acceptance probabilities, are easily accessible. Stan can also be called from the command line using the cmdstan package, through R using the rstan package, and through Python using the pystan package. All three interfaces support sampling and optimization-based inference with diagnostics and posterior analysis. rstan and pystan also provide access to log probabilities, gradients, Hessians, parameter transforms, and specialized plotting.« less

Tree Species Traits but Not Diversity Mitigate Stem Breakage in a Subtropical Forest following a Rare and Extreme Ice Storm

PubMed Central

Nadrowski, Karin; Pietsch, Katherina; Baruffol, Martin; Both, Sabine; Gutknecht, Jessica; Bruelheide, Helge; Heklau, Heike; Kahl, Anja; Kahl, Tiemo; Niklaus, Pascal; Kröber, Wenzel; Liu, Xiaojuan; Mi, Xiangcheng; Michalski, Stefan; von Oheimb, Goddert; Purschke, Oliver; Schmid, Bernhard; Fang, Teng; Welk, Erik; Wirth, Christian

2014-01-01

Future climates are likely to include extreme events, which in turn have great impacts on ecological systems. In this study, we investigated possible effects that could mitigate stem breakage caused by a rare and extreme ice storm in a Chinese subtropical forest across a gradient of forest diversity. We used Bayesian modeling to correct stem breakage for tree size and variance components analysis to quantify the influence of taxon, leaf and wood functional traits, and stand level properties on the probability of stem breakage. We show that the taxon explained four times more variance in individual stem breakage than did stand level properties; trees with higher specific leaf area (SLA) were less susceptible to breakage. However, a large part of the variation at the taxon scale remained unexplained, implying that unmeasured or undefined traits could be used to predict damage caused by ice storms. When aggregated at the plot level, functional diversity and wood density increased after the ice storm. We suggest that for the adaption of forest management to climate change, much can still be learned from looking at functional traits at the taxon level. PMID:24879434

Detection and Distribution of Natural Gaps in Tropical Rainforest

NASA Astrophysics Data System (ADS)

Goulamoussène, Y.; Linguet, L.; Hérault, B.

2014-12-01

Forest management is important to assess biodiversity and ecological processes. Requirements for disturbance information have also been motivated by the scientific community. Therefore, understanding and monitoring the distribution frequencies of treefall gaps is relevant to better understanding and predicting the carbon budget in response to global change and land use change. In this work we characterize and quantify the frequency distribution of natural canopy gaps. We observe then interaction between environment variables and gap formation across tropical rainforest of the French Guiana region by using high resolution airborne Light Detection and Ranging (LiDAR). We mapped gaps with canopy model distribution on 40000 ha of forest. We used a Bayesian modelling framework to estimate and select useful covariate model parameters. Topographic variables are included in a model to predict gap size distribution. We discuss results from the interaction between environment and gap size distribution, mainly topographic indexes. The use of both airborne and space-based techniques has improved our ability to supply needed disturbance information. This work is an approach at plot scale. The use of satellite data will allow us to work at forest scale. The inclusion of climate variables in our model will let us assess the impact of global change on tropical rainforest.

The color of sea level: Importance of spatial variations in spectral shape for assessing the significance of trends

NASA Astrophysics Data System (ADS)

Hughes, Chris W.; Williams, Simon D. P.

2010-10-01

We investigate spatial variations in the shape of the spectrum of sea level variability based on a homogeneously sampled 12 year gridded altimeter data set. We present a method of plotting spectral information as color, focusing on periods between 2 and 24 weeks, which shows that significant spatial variations in the spectral shape exist and contain useful dynamical information. Using the Bayesian Information Criterion, we determine that, typically, a fifth-order autoregressive model is needed to capture the structure in the spectrum. Using this model, we show that statistical errors in fitted local trends range between less than 1 and more than 5 times of what would be calculated assuming "white" noise and that the time needed to detect a 1 mm/yr trend ranges between about 5 years and many decades. For global mean sea level, the statistical error reduces to 0.1 mm/yr over 12 years, with only 2 years needed to detect a 1 mm/yr trend. We find significant regional differences in trend from the global mean. The patterns of these regional differences are indicative of a sea level trend dominated by dynamical ocean processes over this period.

Stan : A Probabilistic Programming Language

DOE PAGES

Carpenter, Bob; Gelman, Andrew; Hoffman, Matthew D.; ...

2017-01-01

Stan is a probabilistic programming language for specifying statistical models. A Stan program imperatively defines a log probability function over parameters conditioned on specified data and constants. As of version 2.14.0, Stan provides full Bayesian inference for continuous-variable models through Markov chain Monte Carlo methods such as the No-U-Turn sampler, an adaptive form of Hamiltonian Monte Carlo sampling. Penalized maximum likelihood estimates are calculated using optimization methods such as the limited memory Broyden-Fletcher-Goldfarb-Shanno algorithm. Stan is also a platform for computing log densities and their gradients and Hessians, which can be used in alternative algorithms such as variational Bayes, expectationmore » propagation, and marginal inference using approximate integration. To this end, Stan is set up so that the densities, gradients, and Hessians, along with intermediate quantities of the algorithm such as acceptance probabilities, are easily accessible. Stan can also be called from the command line using the cmdstan package, through R using the rstan package, and through Python using the pystan package. All three interfaces support sampling and optimization-based inference with diagnostics and posterior analysis. rstan and pystan also provide access to log probabilities, gradients, Hessians, parameter transforms, and specialized plotting.« less

Parametric Analysis of a Hover Test Vehicle using Advanced Test Generation and Data Analysis

NASA Technical Reports Server (NTRS)

Gundy-Burlet, Karen; Schumann, Johann; Menzies, Tim; Barrett, Tony

2009-01-01

Large complex aerospace systems are generally validated in regions local to anticipated operating points rather than through characterization of the entire feasible operational envelope of the system. This is due to the large parameter space, and complex, highly coupled nonlinear nature of the different systems that contribute to the performance of the aerospace system. We have addressed the factors deterring such an analysis by applying a combination of technologies to the area of flight envelop assessment. We utilize n-factor (2,3) combinatorial parameter variations to limit the number of cases, but still explore important interactions in the parameter space in a systematic fashion. The data generated is automatically analyzed through a combination of unsupervised learning using a Bayesian multivariate clustering technique (AutoBayes) and supervised learning of critical parameter ranges using the machine-learning tool TAR3, a treatment learner. Covariance analysis with scatter plots and likelihood contours are used to visualize correlations between simulation parameters and simulation results, a task that requires tool support, especially for large and complex models. We present results of simulation experiments for a cold-gas-powered hover test vehicle.

Bayesian Learning and the Psychology of Rule Induction

ERIC Educational Resources Information Center

Endress, Ansgar D.

2013-01-01

In recent years, Bayesian learning models have been applied to an increasing variety of domains. While such models have been criticized on theoretical grounds, the underlying assumptions and predictions are rarely made concrete and tested experimentally. Here, I use Frank and Tenenbaum's (2011) Bayesian model of rule-learning as a case study to…

Properties of the Bayesian Knowledge Tracing Model

ERIC Educational Resources Information Center

van de Sande, Brett

2013-01-01

Bayesian Knowledge Tracing is used very widely to model student learning. It comes in two different forms: The first form is the Bayesian Knowledge Tracing "hidden Markov model" which predicts the probability of correct application of a skill as a function of the number of previous opportunities to apply that skill and the model…

Bayesian Item Selection in Constrained Adaptive Testing Using Shadow Tests

ERIC Educational Resources Information Center

Veldkamp, Bernard P.

2010-01-01

Application of Bayesian item selection criteria in computerized adaptive testing might result in improvement of bias and MSE of the ability estimates. The question remains how to apply Bayesian item selection criteria in the context of constrained adaptive testing, where large numbers of specifications have to be taken into account in the item…

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…

Bayesian Asymmetric Regression as a Means to Estimate and Evaluate Oral Reading Fluency Slopes

ERIC Educational Resources Information Center

Solomon, Benjamin G.; Forsberg, Ole J.

2017-01-01

Bayesian techniques have become increasingly present in the social sciences, fueled by advances in computer speed and the development of user-friendly software. In this paper, we forward the use of Bayesian Asymmetric Regression (BAR) to monitor intervention responsiveness when using Curriculum-Based Measurement (CBM) to assess oral reading…

A Comparison of a Bayesian and a Maximum Likelihood Tailored Testing Procedure.

ERIC Educational Resources Information Center

McKinley, Robert L.; Reckase, Mark D.

A study was conducted to compare tailored testing procedures based on a Bayesian ability estimation technique and on a maximum likelihood ability estimation technique. The Bayesian tailored testing procedure selected items so as to minimize the posterior variance of the ability estimate distribution, while the maximum likelihood tailored testing…

Bayesian Approaches to Imputation, Hypothesis Testing, and Parameter Estimation

ERIC Educational Resources Information Center

Ross, Steven J.; Mackey, Beth

2015-01-01

This chapter introduces three applications of Bayesian inference to common and novel issues in second language research. After a review of the critiques of conventional hypothesis testing, our focus centers on ways Bayesian inference can be used for dealing with missing data, for testing theory-driven substantive hypotheses without a default null…

Teaching Bayesian Statistics to Undergraduate Students through Debates

ERIC Educational Resources Information Center

Stewart, Sepideh; Stewart, Wayne

2014-01-01

This paper describes a lecturer's approach to teaching Bayesian statistics to students who were only exposed to the classical paradigm. The study shows how the lecturer extended himself by making use of ventriloquist dolls to grab hold of students' attention and embed important ideas in revealing the differences between the Bayesian and classical…

Bayesian generalized linear mixed modeling of Tuberculosis using informative priors

PubMed Central

Woldegerima, Woldegebriel Assefa

2017-01-01

TB is rated as one of the world’s deadliest diseases and South Africa ranks 9th out of the 22 countries with hardest hit of TB. Although many pieces of research have been carried out on this subject, this paper steps further by inculcating past knowledge into the model, using Bayesian approach with informative prior. Bayesian statistics approach is getting popular in data analyses. But, most applications of Bayesian inference technique are limited to situations of non-informative prior, where there is no solid external information about the distribution of the parameter of interest. The main aim of this study is to profile people living with TB in South Africa. In this paper, identical regression models are fitted for classical and Bayesian approach both with non-informative and informative prior, using South Africa General Household Survey (GHS) data for the year 2014. For the Bayesian model with informative prior, South Africa General Household Survey dataset for the year 2011 to 2013 are used to set up priors for the model 2014. PMID:28257437

Multilevel modeling of single-case data: A comparison of maximum likelihood and Bayesian estimation.

PubMed

Moeyaert, Mariola; Rindskopf, David; Onghena, Patrick; Van den Noortgate, Wim

2017-12-01

The focus of this article is to describe Bayesian estimation, including construction of prior distributions, and to compare parameter recovery under the Bayesian framework (using weakly informative priors) and the maximum likelihood (ML) framework in the context of multilevel modeling of single-case experimental data. Bayesian estimation results were found similar to ML estimation results in terms of the treatment effect estimates, regardless of the functional form and degree of information included in the prior specification in the Bayesian framework. In terms of the variance component estimates, both the ML and Bayesian estimation procedures result in biased and less precise variance estimates when the number of participants is small (i.e., 3). By increasing the number of participants to 5 or 7, the relative bias is close to 5% and more precise estimates are obtained for all approaches, except for the inverse-Wishart prior using the identity matrix. When a more informative prior was added, more precise estimates for the fixed effects and random effects were obtained, even when only 3 participants were included. (PsycINFO Database Record (c) 2017 APA, all rights reserved).

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.

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.

Comparing spatially varying coefficient models: a case study examining violent crime rates and their relationships to alcohol outlets and illegal drug arrests

NASA Astrophysics Data System (ADS)

Wheeler, David C.; Waller, Lance A.

2009-03-01

In this paper, we compare and contrast a Bayesian spatially varying coefficient process (SVCP) model with a geographically weighted regression (GWR) model for the estimation of the potentially spatially varying regression effects of alcohol outlets and illegal drug activity on violent crime in Houston, Texas. In addition, we focus on the inherent coefficient shrinkage properties of the Bayesian SVCP model as a way to address increased coefficient variance that follows from collinearity in GWR models. We outline the advantages of the Bayesian model in terms of reducing inflated coefficient variance, enhanced model flexibility, and more formal measuring of model uncertainty for prediction. We find spatially varying effects for alcohol outlets and drug violations, but the amount of variation depends on the type of model used. For the Bayesian model, this variation is controllable through the amount of prior influence placed on the variance of the coefficients. For example, the spatial pattern of coefficients is similar for the GWR and Bayesian models when a relatively large prior variance is used in the Bayesian model.

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

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

Hierarchical Bayesian Modeling of Fluid-Induced Seismicity

NASA Astrophysics Data System (ADS)

Broccardo, M.; Mignan, A.; Wiemer, S.; Stojadinovic, B.; Giardini, D.

2017-11-01

In this study, we present a Bayesian hierarchical framework to model fluid-induced seismicity. The framework is based on a nonhomogeneous Poisson process with a fluid-induced seismicity rate proportional to the rate of injected fluid. The fluid-induced seismicity rate model depends upon a set of physically meaningful parameters and has been validated for six fluid-induced case studies. In line with the vision of hierarchical Bayesian modeling, the rate parameters are considered as random variables. We develop both the Bayesian inference and updating rules, which are used to develop a probabilistic forecasting model. We tested the Basel 2006 fluid-induced seismic case study to prove that the hierarchical Bayesian model offers a suitable framework to coherently encode both epistemic uncertainty and aleatory variability. Moreover, it provides a robust and consistent short-term seismic forecasting model suitable for online risk quantification and mitigation.

UNIFORMLY MOST POWERFUL BAYESIAN TESTS

PubMed Central

Johnson, Valen E.

2014-01-01

Uniformly most powerful tests are statistical hypothesis tests that provide the greatest power against a fixed null hypothesis among all tests of a given size. In this article, the notion of uniformly most powerful tests is extended to the Bayesian setting by defining uniformly most powerful Bayesian tests to be tests that maximize the probability that the Bayes factor, in favor of the alternative hypothesis, exceeds a specified threshold. Like their classical counterpart, uniformly most powerful Bayesian tests are most easily defined in one-parameter exponential family models, although extensions outside of this class are possible. The connection between uniformly most powerful tests and uniformly most powerful Bayesian tests can be used to provide an approximate calibration between p-values and Bayes factors. Finally, issues regarding the strong dependence of resulting Bayes factors and p-values on sample size are discussed. PMID:24659829

Bayesian network modeling applied to coastal geomorphology: lessons learned from a decade of experimentation and application

NASA Astrophysics Data System (ADS)

Plant, N. G.; Thieler, E. R.; Gutierrez, B.; Lentz, E. E.; Zeigler, S. L.; Van Dongeren, A.; Fienen, M. N.

2016-12-01

We evaluate the strengths and weaknesses of Bayesian networks that have been used to address scientific and decision-support questions related to coastal geomorphology. We will provide an overview of coastal geomorphology research that has used Bayesian networks and describe what this approach can do and when it works (or fails to work). Over the past decade, Bayesian networks have been formulated to analyze the multi-variate structure and evolution of coastal morphology and associated human and ecological impacts. The approach relates observable system variables to each other by estimating discrete correlations. The resulting Bayesian-networks make predictions that propagate errors, conduct inference via Bayes rule, or both. In scientific applications, the model results are useful for hypothesis testing, using confidence estimates to gage the strength of tests while applications to coastal resource management are aimed at decision-support, where the probabilities of desired ecosystems outcomes are evaluated. The range of Bayesian-network applications to coastal morphology includes emulation of high-resolution wave transformation models to make oceanographic predictions, morphologic response to storms and/or sea-level rise, groundwater response to sea-level rise and morphologic variability, habitat suitability for endangered species, and assessment of monetary or human-life risk associated with storms. All of these examples are based on vast observational data sets, numerical model output, or both. We will discuss the progression of our experiments, which has included testing whether the Bayesian-network approach can be implemented and is appropriate for addressing basic and applied scientific problems and evaluating the hindcast and forecast skill of these implementations. We will present and discuss calibration/validation tests that are used to assess the robustness of Bayesian-network models and we will compare these results to tests of other models. This will demonstrate how Bayesian networks are used to extract new insights about coastal morphologic behavior, assess impacts to societal and ecological systems, and communicate probabilistic predictions to decision makers.

[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.

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.

Order priors for Bayesian network discovery with an application to malware phylogeny

DOE PAGES

Oyen, Diane; Anderson, Blake; Sentz, Kari; ...

2017-09-15

Here, Bayesian networks have been used extensively to model and discover dependency relationships among sets of random variables. We learn Bayesian network structure with a combination of human knowledge about the partial ordering of variables and statistical inference of conditional dependencies from observed data. Our approach leverages complementary information from human knowledge and inference from observed data to produce networks that reflect human beliefs about the system as well as to fit the observed data. Applying prior beliefs about partial orderings of variables is an approach distinctly different from existing methods that incorporate prior beliefs about direct dependencies (or edges)more » in a Bayesian network. We provide an efficient implementation of the partial-order prior in a Bayesian structure discovery learning algorithm, as well as an edge prior, showing that both priors meet the local modularity requirement necessary for an efficient Bayesian discovery algorithm. In benchmark studies, the partial-order prior improves the accuracy of Bayesian network structure learning as well as the edge prior, even though order priors are more general. Our primary motivation is in characterizing the evolution of families of malware to aid cyber security analysts. For the problem of malware phylogeny discovery, we find that our algorithm, compared to existing malware phylogeny algorithms, more accurately discovers true dependencies that are missed by other algorithms.« less

Order priors for Bayesian network discovery with an application to malware phylogeny

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

Oyen, Diane; Anderson, Blake; Sentz, Kari

Here, Bayesian networks have been used extensively to model and discover dependency relationships among sets of random variables. We learn Bayesian network structure with a combination of human knowledge about the partial ordering of variables and statistical inference of conditional dependencies from observed data. Our approach leverages complementary information from human knowledge and inference from observed data to produce networks that reflect human beliefs about the system as well as to fit the observed data. Applying prior beliefs about partial orderings of variables is an approach distinctly different from existing methods that incorporate prior beliefs about direct dependencies (or edges)more » in a Bayesian network. We provide an efficient implementation of the partial-order prior in a Bayesian structure discovery learning algorithm, as well as an edge prior, showing that both priors meet the local modularity requirement necessary for an efficient Bayesian discovery algorithm. In benchmark studies, the partial-order prior improves the accuracy of Bayesian network structure learning as well as the edge prior, even though order priors are more general. Our primary motivation is in characterizing the evolution of families of malware to aid cyber security analysts. For the problem of malware phylogeny discovery, we find that our algorithm, compared to existing malware phylogeny algorithms, more accurately discovers true dependencies that are missed by other algorithms.« less

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.

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.

Basics of Bayesian methods.

PubMed

Ghosh, Sujit K

2010-01-01

Bayesian methods are rapidly becoming popular tools for making statistical inference in various fields of science including biology, engineering, finance, and genetics. One of the key aspects of Bayesian inferential method is its logical foundation that provides a coherent framework to utilize not only empirical but also scientific information available to a researcher. Prior knowledge arising from scientific background, expert judgment, or previously collected data is used to build a prior distribution which is then combined with current data via the likelihood function to characterize the current state of knowledge using the so-called posterior distribution. Bayesian methods allow the use of models of complex physical phenomena that were previously too difficult to estimate (e.g., using asymptotic approximations). Bayesian methods offer a means of more fully understanding issues that are central to many practical problems by allowing researchers to build integrated models based on hierarchical conditional distributions that can be estimated even with limited amounts of data. Furthermore, advances in numerical integration methods, particularly those based on Monte Carlo methods, have made it possible to compute the optimal Bayes estimators. However, there is a reasonably wide gap between the background of the empirically trained scientists and the full weight of Bayesian statistical inference. Hence, one of the goals of this chapter is to bridge the gap by offering elementary to advanced concepts that emphasize linkages between standard approaches and full probability modeling via Bayesian methods.

Bayesian Networks Improve Causal Environmental Assessments for Evidence-Based Policy.

PubMed

Carriger, John F; Barron, Mace G; Newman, Michael C

2016-12-20

Rule-based weight of evidence approaches to ecological risk assessment may not account for uncertainties and generally lack probabilistic integration of lines of evidence. Bayesian networks allow causal inferences to be made from evidence by including causal knowledge about the problem, using this knowledge with probabilistic calculus to combine multiple lines of evidence, and minimizing biases in predicting or diagnosing causal relationships. Too often, sources of uncertainty in conventional weight of evidence approaches are ignored that can be accounted for with Bayesian networks. Specifying and propagating uncertainties improve the ability of models to incorporate strength of the evidence in the risk management phase of an assessment. Probabilistic inference from a Bayesian network allows evaluation of changes in uncertainty for variables from the evidence. The network structure and probabilistic framework of a Bayesian approach provide advantages over qualitative approaches in weight of evidence for capturing the impacts of multiple sources of quantifiable uncertainty on predictions of ecological risk. Bayesian networks can facilitate the development of evidence-based policy under conditions of uncertainty by incorporating analytical inaccuracies or the implications of imperfect information, structuring and communicating causal issues through qualitative directed graph formulations, and quantitatively comparing the causal power of multiple stressors on valued ecological resources. These aspects are demonstrated through hypothetical problem scenarios that explore some major benefits of using Bayesian networks for reasoning and making inferences in evidence-based policy.

Estimation of Post-Test Probabilities by Residents: Bayesian Reasoning versus Heuristics?

ERIC Educational Resources Information Center

Hall, Stacey; Phang, Sen Han; Schaefer, Jeffrey P.; Ghali, William; Wright, Bruce; McLaughlin, Kevin

2014-01-01

Although the process of diagnosing invariably begins with a heuristic, we encourage our learners to support their diagnoses by analytical cognitive processes, such as Bayesian reasoning, in an attempt to mitigate the effects of heuristics on diagnosing. There are, however, limited data on the use ± impact of Bayesian reasoning on the accuracy of…

Development of an Integrated Team Training Design and Assessment Architecture to Support Adaptability in Healthcare Teams

DTIC Science & Technology

2016-10-01

and implementation of embedded, adaptive feedback and performance assessment. The investigators also initiated work designing a Bayesian Belief ...training; Teamwork; Adaptive performance; Leadership; Simulation; Modeling; Bayesian belief networks (BBN) 16. SECURITY CLASSIFICATION OF: 17. LIMITATION...Trauma teams Team training Teamwork Adaptability Adaptive performance Leadership Simulation Modeling Bayesian belief networks (BBN) 6

A Bayesian Network Approach to Modeling Learning Progressions and Task Performance. CRESST Report 776

ERIC Educational Resources Information Center

West, Patti; Rutstein, Daisy Wise; Mislevy, Robert J.; Liu, Junhui; Choi, Younyoung; Levy, Roy; Crawford, Aaron; DiCerbo, Kristen E.; Chappel, Kristina; Behrens, John T.

2010-01-01

A major issue in the study of learning progressions (LPs) is linking student performance on assessment tasks to the progressions. This report describes the challenges faced in making this linkage using Bayesian networks to model LPs in the field of computer networking. The ideas are illustrated with exemplar Bayesian networks built on Cisco…

Python Environment for Bayesian Learning: Inferring the Structure of Bayesian Networks from Knowledge and Data

PubMed Central

Shah, Abhik; Woolf, Peter

2009-01-01

Summary In this paper, we introduce pebl, a Python library and application for learning Bayesian network structure from data and prior knowledge that provides features unmatched by alternative software packages: the ability to use interventional data, flexible specification of structural priors, modeling with hidden variables and exploitation of parallel processing. PMID:20161541

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…

Is Bayesian Estimation Proper for Estimating the Individual's Ability? Research Report 80-3.

ERIC Educational Resources Information Center

Samejima, Fumiko

The effect of prior information in Bayesian estimation is considered, mainly from the standpoint of objective testing. In the estimation of a parameter belonging to an individual, the prior information is, in most cases, the density function of the population to which the individual belongs. Bayesian estimation was compared with maximum likelihood…

A Comparison of General Diagnostic Models (GDM) and Bayesian Networks Using a Middle School Mathematics Test

ERIC Educational Resources Information Center

Wu, Haiyan

2013-01-01

General diagnostic models (GDMs) and Bayesian networks are mathematical frameworks that cover a wide variety of psychometric models. Both extend latent class models, and while GDMs also extend item response theory (IRT) models, Bayesian networks can be parameterized using discretized IRT. The purpose of this study is to examine similarities and…