Energy Technology Data Exchange (ETDEWEB)
Stahle, David (Tree-Ring Laboratory, University of Arkansas)
2003-02-12
The original presettlement forests of North America have been dramatically altered, but thousands of unmolested ancient forests survive on remote or noncommercial terrain, including dry-site eastern hardwoods such as chestnut oak and post oak, the pinyon-juniper woodlands of the semiarid West, oak woodlands of California and in northeast Mexico, and the boreal forests of Canada and Alaska. Long tree-ring chronologies derived from these ancient forest remnants provide irreplaceable archives of environmental variability which are crucial for evaluating present and future change. Temperature sensitive tree -ring chronologies from cold treeline environments place 20th century warming into long historical perspective, and moisture sensitive tree-ring chronologies provide analogs to the decadal moisture regimes of the 20th century. These tree-ring data suggests that the 16th century megadrought was the most severe-sustained drought to impact North America in 1500 years, and had huge environmental and social impacts at the dawn of European settlement.
Diversity of Ancient Woody Species in Urban Forests
Directory of Open Access Journals (Sweden)
Fornal-Pieniak Beata
2014-06-01
Full Text Available Mostly parks and forest are the most important ‘green islands’ in urban ecological network. Urban forests are belong to green areas and collected many plant species. The main aim of the article was characteristic of ancient plant species in urban forests in Tarnów. The field studies were carried out in years 2011-2012. It covered 80 phytosociological records on the area 500 m2 in herb layer of urban forests and in forest nature on oak-hornbeam. The results showed that many ancient plant species were growing in urban forest but less than in nature reserves
A Very Simple Safe-Bayesian Random Forest.
Quadrianto, Novi; Ghahramani, Zoubin
2015-06-01
Random forests works by averaging several predictions of de-correlated trees. We show a conceptually radical approach to generate a random forest: random sampling of many trees from a prior distribution, and subsequently performing a weighted ensemble of predictive probabilities. Our approach uses priors that allow sampling of decision trees even before looking at the data, and a power likelihood that explores the space spanned by combination of decision trees. While each tree performs Bayesian inference to compute its predictions, our aggregation procedure uses the power likelihood rather than the likelihood and is therefore strictly speaking not Bayesian. Nonetheless, we refer to it as a Bayesian random forest but with a built-in safety. The safeness comes as it has good predictive performance even if the underlying probabilistic model is wrong. We demonstrate empirically that our Safe-Bayesian random forest outperforms MCMC or SMC based Bayesian decision trees in term of speed and accuracy, and achieves competitive performance to entropy or Gini optimised random forest, yet is very simple to construct.
Using Bayesian neural networks to classify forest scenes
Vehtari, Aki; Heikkonen, Jukka; Lampinen, Jouko; Juujarvi, Jouni
1998-10-01
We present results that compare the performance of Bayesian learning methods for neural networks on the task of classifying forest scenes into trees and background. Classification task is demanding due to the texture richness of the trees, occlusions of the forest scene objects and diverse lighting conditions under operation. This makes it difficult to determine which are optimal image features for the classification. A natural way to proceed is to extract many different types of potentially suitable features, and to evaluate their usefulness in later processing stages. One approach to cope with large number of features is to use Bayesian methods to control the model complexity. Bayesian learning uses a prior on model parameters, combines this with evidence from a training data, and the integrates over the resulting posterior to make predictions. With this method, we can use large networks and many features without fear of overfitting. For this classification task we compare two Bayesian learning methods for multi-layer perceptron (MLP) neural networks: (1) The evidence framework of MacKay uses a Gaussian approximation to the posterior weight distribution and maximizes with respect to hyperparameters. (2) In a Markov Chain Monte Carlo (MCMC) method due to Neal, the posterior distribution of the network parameters is numerically integrated using the MCMC method. As baseline classifiers for comparison we use (3) MLP early stop committee, (4) K-nearest-neighbor and (5) Classification And Regression Tree.
Modern tree species composition reflects ancient Maya "forest gardens" in northwest Belize.
Ross, Nanci J
2011-01-01
Ecology and ethnobotany were integrated to assess the impact of ancient Maya tree-dominated home gardens (i.e., "forest gardens"), which contained a diversity of tree species used for daily household needs, on the modern tree species composition of a Mesoamerican forest. Researchers have argued that the ubiquity of these ancient gardens throughout Mesoamerica led to the dominance of species useful to Maya in the contemporary forest, but this pattern may be localized depending on ancient land use. The tested hypothesis was that species composition would be significantly different between areas of dense ancient residential structures (high density) and areas of little or no ancient settlement (low density). Sixty-three 400-m2 plots (31 high density and 32 low density) were censused around the El Pilar Archaeological Reserve in northwestern Belize. Species composition was significantly different, with higher abundances of commonly utilized "forest garden" species still persisting in high-density forest areas despite centuries of abandonment. Subsequent edaphic analyses only explained 5% of the species composition differences. This research provides data on the long-term impacts of Maya forests gardens for use in development of future conservation models. For Mesoamerican conservation programs to work, we must understand the complex ecological and social interactions within an ecosystem that developed in intimate association with humans.
Vacik, Harald; Huber, Patrick; Hujala, Teppo; Kurtilla, Mikko; Wolfslehner, Bernhard
2015-04-01
It is an integral element of the European understanding of sustainable forest management to foster the design and marketing of forest products, non-wood forest products (NWFPs) and services that go beyond the production of timber. Despite the relevance of NWFPs in Europe, forest management and planning methods have been traditionally tailored towards wood and wood products, because most forest management models and silviculture techniques were developed to ensure a sustained production of timber. Although several approaches exist which explicitly consider NWFPs as management objectives in forest planning, specific models are needed for the assessment of their production potential in different environmental contexts and for different management regimes. Empirical data supporting a comprehensive assessment of the potential of NWFPs are rare, thus making development of statistical models particularly problematic. However, the complex causal relationships between the sustained production of NWFPs, the available ecological resources, as well as the organizational and the market potential of forest management regimes are well suited for knowledge-based expert models. Bayesian belief networks (BBNs) are a kind of probabilistic graphical model that have become very popular to practitioners and scientists mainly due to the powerful probability theory involved, which makes BBNs suitable to deal with a wide range of environmental problems. In this contribution we present the development of a Bayesian belief network to assess the potential of NWFPs for small scale forest owners. A three stage iterative process with stakeholder and expert participation was used to develop the Bayesian Network within the frame of the StarTree Project. The group of participants varied in the stages of the modelling process. A core team, consisting of one technical expert and two domain experts was responsible for the entire modelling process as well as for the first prototype of the network
Directory of Open Access Journals (Sweden)
M. Bagnara
2014-10-01
Full Text Available Forest models are being increasingly used to study ecosystem functioning, through the reproduction of carbon fluxes and productivity in very different forests all over the world. Over the last two decades, the need for simple and "easy to use" models for practical applications, characterized by few parameters and equations, has become clear, and some have been developed for this purpose. These models aim to represent the main drivers underlying forest ecosystem processes while being applicable to the widest possible range of forest ecosystems. Recently, it has also become clear that model performance should not be assessed only in terms of accuracy of estimations and predictions, but also in terms of estimates of model uncertainties. Therefore, the Bayesian approach has increasingly been applied to calibrate forest models, with the aim of estimating the uncertainty of their results, and of comparing their performances. Some forest models, considered to be user-friendly, rely on a multiplicative or quasi-multiplicative mathematical structure, which is known to cause problems during the calibration process, mainly due to high correlations between parameters. In a Bayesian framework using a Markov Chain Monte Carlo sampling this is likely to impair the reaching of a proper convergence of the chains and the sampling from the correct posterior distribution. Here we show two methods to reach proper convergence when using a forest model with a multiplicative structure, applying different algorithms with different number of iterations during the Markov Chain Monte Carlo or a two-steps calibration. The results showed that recently proposed algorithms for adaptive calibration do not confer a clear advantage over the Metropolis–Hastings Random Walk algorithm for the forest model used here. Moreover, the calibration remains time consuming and mathematically difficult, so advantages of using a fast and user-friendly model can be lost due to the calibration
Spake, Rebecca; van der Linde, Sietse; Newton, Adrian C.; Suz, Laura M.; Bidartondo, Martin I.; Doncaster, C. Patrick
2016-01-01
Setting aside overmature planted forests is currently seen as an option for preserving species associated with old-growth forests, such as those with dispersal limitation. Few data exist, however, on the utility of set-aside plantations for this purpose, or the value of this habitat type for biodiversity relative to old-growth semi-natural ecosystems. Here, we evaluate the contribution of forest type relative to habitat characteristics in determining species richness and composition in seven forest blocks, each containing an ancient old-growth stand (> 1000 yrs) paired with a set-aside even-aged planted stand (ca. 180 yrs). We investigated the functionally important yet relatively neglected ectomycorrhizal fungi (EMF), a group for which the importance of forest age has not been assessed in broadleaved forests. We found that forest type was not an important determinant of EMF species richness or composition, demonstrating that set-aside can be an effective option for conserving ancient EMF communities. Species richness of above-ground EMF fruiting bodies was principally related to the basal area of the stand (a correlate of canopy cover) and tree species diversity, whilst richness of below-ground ectomycorrhizae was driven only by tree diversity. Our results suggest that overmature planted forest stands, particularly those that are mixed-woods with high basal area, are an effective means to connect and expand ecological networks of ancient old-growth forests in historically deforested and fragmented landscapes for ectomycorrhizal fungi. PMID:26917858
Dawson, Andria; Paciorek, Christopher J.; McLachlan, Jason S.; Goring, Simon; Williams, John W.; Jackson, Stephen T.
2016-04-01
Mitigation of climate change and adaptation to its effects relies partly on how effectively land-atmosphere interactions can be quantified. Quantifying composition of past forest ecosystems can help understand processes governing forest dynamics in a changing world. Fossil pollen data provide information about past forest composition, but rigorous interpretation requires development of pollen-vegetation models (PVMs) that account for interspecific differences in pollen production and dispersal. Widespread and intensified land-use over the 19th and 20th centuries may have altered pollen-vegetation relationships. Here we use STEPPS, a Bayesian hierarchical spatial PVM, to estimate key process parameters and associated uncertainties in the pollen-vegetation relationship. We apply alternate dispersal kernels, and calibrate STEPPS using a newly developed Euro-American settlement-era calibration data set constructed from Public Land Survey data and fossil pollen samples matched to the settlement-era using expert elicitation. Models based on the inverse power-law dispersal kernel outperformed those based on the Gaussian dispersal kernel, indicating that pollen dispersal kernels are fat tailed. Pine and birch have the highest pollen productivities. Pollen productivity and dispersal estimates are generally consistent with previous understanding from modern data sets, although source area estimates are larger. Tests of model predictions demonstrate the ability of STEPPS to predict regional compositional patterns.
Bayesian inference reveals ancient origin of simian foamy virus in orangutans.
Reid, Michael J C; Switzer, William M; Schillaci, Michael A; Klegarth, Amy R; Campbell, Ellsworth; Ragonnet, Manon; Joanisse, Isabelle; Caminiti, Kyna; Lowenberger, Carl A; Galdikas, Birute Mary F; Hollocher, Hope; Sandstrom, Paul A; Brooks, James I
2017-03-05
Simian foamy viruses (SFVs) infect most nonhuman primate species and appears to co-evolve with its hosts. This co-evolutionary signal is particularly strong among great apes, including orangutans (genus Pongo). Previous studies have identified three distinct orangutan SFV clades. The first of these three clades is composed of SFV from P. abelii from Sumatra, the second consists of SFV from P. pygmaeus from Borneo, while the third clade is mixed, comprising an SFV strain found in both species of orangutan. The existence of the mixed clade has been attributed to an expansion of P. pygmaeus into Sumatra following the Mount Toba super-volcanic eruption about 73,000years ago. Divergence dating, however, has yet to be performed to establish a temporal association with the Toba eruption. Here, we use a Bayesian framework and a relaxed molecular clock model with fossil calibrations to test the Toba hypothesis and to gain a more complete understanding of the evolutionary history of orangutan SFV. As with previous studies, our results show a similar three-clade orangutan SFV phylogeny, along with strong statistical support for SFV-host co-evolution in orangutans. Using Bayesian inference, we date the origin of orangutan SFV to >4.7 million years ago (mya), while the mixed species clade dates to approximately 1.7mya, >1.6 million years older than the Toba super-eruption. These results, combined with fossil and paleogeographic evidence, suggest that the origin of SFV in Sumatran and Bornean orangutans, including the mixed species clade, likely occurred on the mainland of Indo-China during the Late Pliocene and Calabrian stage of the Pleistocene, respectively.
Bayesian classifier applications of airborne hyperspectral imagery processing for forested areas
Kozoderov, Vladimir; Kondranin, Timofei; Dmitriev, Egor; Kamentsev, Vladimir
2015-06-01
Pattern recognition problem is outlined in the context of textural and spectral analysis of remote sensing imagery processing. Main attention is paid to Bayesian classifier that can be used to realize the processing procedures based on parallel machine-learning algorithms and high-productive computers. We consider the maximum of the posterior probability principle and the formalism of Markov random fields for the neighborhood description of the pixels for the related classes of objects with the emphasis on forests of different species and ages. The energy category of the selected classes serves to account for the likelihood measure between the registered radiances and the theoretical distribution functions approximating remotely sensed data. Optimization procedures are undertaken to solve the pattern recognition problem of the texture description for the forest classes together with finding thin nuances of their spectral distribution in the feature space. As a result, possible redundancy of the channels for imaging spectrometer due to their correlations is removed. Difficulties are revealed due to different sampling data while separating pixels, which characterize the sunlit tops, shaded space and intermediate cases of the Sun illumination conditions on the hyperspectral images. Such separation of pixels for the forest classes is maintained to enhance the recognition accuracy, but learning ensembles of data need to be agreed for these categories of pixels. We present some results of the Bayesian classifier applicability for recognizing airborne hyperspectral images using the relevant improvements in separating such pixels for the forest classes on a test area of the 4 × 10 km size encompassed by 13 airborne tracks, each forming the images by 500 pixels across the track and from 10,000 to 14,000 pixels along the track. The spatial resolution of each image is near to 1 m from the altitude near to 2 km above the ground level. The results of the hyperspectral imagery
Technical Note: Approximate Bayesian parameterization of a complex tropical forest model
Directory of Open Access Journals (Sweden)
F. Hartig
2013-08-01
Full Text Available Inverse parameter estimation of process-based models is a long-standing problem in ecology and evolution. A key problem of inverse parameter estimation is to define a metric that quantifies how well model predictions fit to the data. Such a metric can be expressed by general cost or objective functions, but statistical inversion approaches are based on a particular metric, the probability of observing the data given the model, known as the likelihood. Deriving likelihoods for dynamic models requires making assumptions about the probability for observations to deviate from mean model predictions. For technical reasons, these assumptions are usually derived without explicit consideration of the processes in the simulation. Only in recent years have new methods become available that allow generating likelihoods directly from stochastic simulations. Previous applications of these approximate Bayesian methods have concentrated on relatively simple models. Here, we report on the application of a simulation-based likelihood approximation for FORMIND, a parameter-rich individual-based model of tropical forest dynamics. We show that approximate Bayesian inference, based on a parametric likelihood approximation placed in a conventional MCMC, performs well in retrieving known parameter values from virtual field data generated by the forest model. We analyze the results of the parameter estimation, examine the sensitivity towards the choice and aggregation of model outputs and observed data (summary statistics, and show results from using this method to fit the FORMIND model to field data from an Ecuadorian tropical forest. Finally, we discuss differences of this approach to Approximate Bayesian Computing (ABC, another commonly used method to generate simulation-based likelihood approximations. Our results demonstrate that simulation-based inference, which offers considerable conceptual advantages over more traditional methods for inverse parameter
Institute of Scientific and Technical Information of China (English)
DING Ping; SHEN ChengDe; WANG Ning; YI WeiXi; LIU KeXin; DING XingFang; FU DongPo
2009-01-01
We present the carbon isotopic composition of the total organic carbon (TOC) and fine roots in the sedimentary profile from the underground ancient forest in Sihui to study the climatic and environ-mental changes from 4.5 ka BP to 0.6 ka BP. Results show that C3 plant was the main vegetation from 4.5 ka BP to 0.6 ka BP in this region. The ancient forest began to develop in the wetland st around 4 ks BP and disappeared together with the wetland at about 3.0 ka BP, implying that the climate had changed greatly at around 3.0 ka BP. As indicated by the simulation results, the content of atmospheric CO2 increased slightly during 3.5 ka BP and 3.0 ka BP, implying climate warming during that period. The interval of radiocarbon age between 3.0 ka BP and 1.2 ka BP was possibly caused by the strong erosion when the block was lifted in the neotectonic movement. From 1.2 ks BP to 0.6 ka BP, the region re-mained in terrestrial sedimentary environment, and the surface plant biomass declined gradually. Drought caused by the climate change was the likely cause for the disappearance of the ancient forest. South transition of Intertropical Convergence Zone (ITCZ) was probably the main mechanism for the climate change.
Institute of Scientific and Technical Information of China (English)
无
2009-01-01
We present the carbon isotopic composition of the total organic carbon(TOC) and fine roots in the sedimentary profile from the underground ancient forest in Sihui to study the climatic and environmental changes from 4.5 ka BP to 0.6 ka BP.Results show that C3 plant was the main vegetation from 4.5 ka BP to 0.6 ka BP in this region.The ancient forest began to develop in the wetland at around 4 ka BP and disappeared together with the wetland at about 3.0 ka BP,implying that the climate had changed greatly at around 3.0 ka BP.As indicated by the simulation results,the content of atmospheric CO2 increased slightly during 3.5 ka BP and 3.0 ka BP,implying climate warming during that period.The interval of radiocarbon age between 3.0 ka BP and 1.2 ka BP was possibly caused by the strong erosion when the block was lifted in the neotectonic movement.From 1.2 ka BP to 0.6 ka BP,the region remained in terrestrial sedimentary environment,and the surface plant biomass declined gradually.Drought caused by the climate change was the likely cause for the disappearance of the ancient forest.South transition of Intertropical Convergence Zone(ITCZ) was probably the main mechanism for the climate change.
Pollination biology of the urban populations of an ancient forest, spring ephemeral plant
Directory of Open Access Journals (Sweden)
Maciej A. Ziemiański
2016-04-01
Full Text Available Habitat fragmentation, caused by, among all, agriculture and urbanization, is one of the most important drivers of plant biodiversity decline worldwide. One of the signs of deteriorating zoogamous plant reproduction is pollen limitation, often associated with a decline in pollinator diversity and abundance. Various authors predict that the most vulnerable taxa are outbreeding plant species characterized by specialist pollination systems. We have, therefore, focused on self-incompatible Corydalis solida, an ancient forest, spring ephemeral plant, growing in three remnant urban populations in the city of Warsaw (Poland. Over two years, we checked for pollen limitation and recorded insect diversity and abundance for C. solida flowers. Our study populations composed of self-incompatible individuals were mainly visited by generalist pollinators, and produced more seeds when supplementally pollinated. Pollen limitation, however, was greater during 1 year with an early spring onset, when we observed a decline in floral visitors diversity and activity. This was probably an effect of phenological mismatch between plants and their pollinators, in this case, mostly social bees, i.e., over-wintered bumblebee queens and Apis mellifera. We conclude that for outbreeding zoogamous spring ephemerals, such as C. solida serviced by generalist pollinators, changing climatic conditions may override the effects of habitat fragmentation and influence their reproductive success.
Forests, fields, and the edge of sustainability at the ancient Maya city of Tikal.
Lentz, David L; Dunning, Nicholas P; Scarborough, Vernon L; Magee, Kevin S; Thompson, Kim M; Weaver, Eric; Carr, Christopher; Terry, Richard E; Islebe, Gerald; Tankersley, Kenneth B; Grazioso Sierra, Liwy; Jones, John G; Buttles, Palma; Valdez, Fred; Ramos Hernandez, Carmen E
2014-12-30
Tikal has long been viewed as one of the leading polities of the ancient Maya realm, yet how the city was able to maintain its substantial population in the midst of a tropical forest environment has been a topic of unresolved debate among researchers for decades. We present ecological, paleoethnobotanical, hydraulic, remote sensing, edaphic, and isotopic evidence that reveals how the Late Classic Maya at Tikal practiced intensive forms of agriculture (including irrigation, terrace construction, arboriculture, household gardens, and short fallow swidden) coupled with carefully controlled agroforestry and a complex system of water retention and redistribution. Empirical evidence is presented to demonstrate that this assiduously managed anthropogenic ecosystem of the Classic period Maya was a landscape optimized in a way that provided sustenance to a relatively large population in a preindustrial, low-density urban community. This landscape productivity optimization, however, came with a heavy cost of reduced environmental resiliency and a complete reliance on consistent annual rainfall. Recent speleothem data collected from regional caves showed that persistent episodes of unusually low rainfall were prevalent in the mid-9th century A.D., a time period that coincides strikingly with the abandonment of Tikal and the erection of its last dated monument in A.D. 869. The intensified resource management strategy used at Tikal-already operating at the landscape's carrying capacity-ceased to provide adequate food, fuel, and drinking water for the Late Classic populace in the face of extended periods of drought. As a result, social disorder and abandonment ensued.
Impact of ancient charcoal kilns on chemical properties of several forest soils after 2 centuries
Dufey, Joseph; Hardy, Brieuc; Cornelis, Jean-Thomas
2014-05-01
Pyrogenic carbon plays a major role in soil biogeochemical processes and carbon budgets. Until the early 19th century, charcoal was the unique combustible used for iron metallurgy in Wallonia (Belgium). Traditional charcoal kilns were built directly in the forest: wood logs were piled into a mound and isolated from air oxygen with a covering of vegetation residues and soil before setting fire, inducing wood pyrolysis. Nowadays, ancient wood-charring platforms are still easy to identify on the forest floor as heightened domes of 10 meters in diameter characterized by a very dark topsoil horizon containing charcoal dust and fragments. Our goal is to assess the effects of wood charring at mound kiln sites on the properties of various forest soil types in Wallonia (Belgium), after two centuries. We sampled soil by horizon in 18 ancient kiln sites to 1.20 meter depth. The adjacent charcoal-unaffected soils were sampled the same way. We also collected recent charcoal fragments and topsoil samples from a still active charcoal kiln located close to Dole (France) to apprehend the evolution of soil properties over time. The pH, total carbon (C) and nitrogen (N) content, available phosphorus (Pav), cation exchange capacity at pH 7 (CEC), exchangeable cations (Ca++, Mg++, K+, Na+) and loss on ignition at 550°C (LI550) were measured on each soil sample. We separated the soil profiles in 5 groups based on the nature of soil substrate and pedogenesis for interpretation of the results. We show that the total carbon stock is significantly increased at kiln sites due to higher C concentrations and greater depth of the organo-mineral horizon. The C/N ratio in charcoal-enriched soil horizons is significantly higher than in the neighboring reference soils but clearly attenuated compared to pure wood-charcoal fragments. The CEC is higher in the charcoal-enriched soil horizons, not only due to higher C concentrations but also to increased CEC by carbon unit at kiln sites. The high
Berglund, Håkan; O'Hara, Robert B; Jonsson, Bengt Gunnar
2009-10-01
Quantitative conservation objectives require detailed consideration of the habitat requirements of target species. Tree-living bryophytes, lichens, and fungi are a critical and declining biodiversity component of boreal forests. To understand their requirements, Bayesian methods were used to analyze the relationships between the occurrence of individual species and habitat factors at the tree and the stand scale in a naturally fragmented boreal forest landscape. The importance of unexplained between-stand variation in occurrence of species was estimated, and the ability of derived models to predict species' occurrence was tested. The occurrence of species was affected by quality of individual trees. Furthermore, the relationships between occurrence of species at the tree level and size and shape of stands indicated edge effects, implying that some species were restricted to interior habitats of large, regular stands. Yet for the habitat factors studied, requirements of many species appeared similar. Species occurrence also varied between stands; most of the seemingly suitable trees in some stands were unoccupied. The models captured most variation in species occurrence at tree level. They also successfully accounted for between-stand variation in species occurrence, thus providing realistic simulations of stand-level occupancy of species. Important unexplained between-stand variation in species occurrence warns against a simplified view that only local habitat factors influence species' occurrence. Apparently, similar stands will host populations of different sizes due to historical, spatial, and stochastic factors. Thus, habitat suitability cannot be assessed simply by population sizes, and stands lacking a species may still provide suitable habitat and merit protection.
Gonzalez-Redin, Julen; Luque, Sandra; Poggio, Laura; Smith, Ron; Gimona, Alessandro
2016-01-01
An integrated methodology, based on linking Bayesian belief networks (BBN) with GIS, is proposed for combining available evidence to help forest managers evaluate implications and trade-offs between forest production and conservation measures to preserve biodiversity in forested habitats. A Bayesian belief network is a probabilistic graphical model that represents variables and their dependencies through specifying probabilistic relationships. In spatially explicit decision problems where it is difficult to choose appropriate combinations of interventions, the proposed integration of a BBN with GIS helped to facilitate shared understanding of the human-landscape relationships, while fostering collective management that can be incorporated into landscape planning processes. Trades-offs become more and more relevant in these landscape contexts where the participation of many and varied stakeholder groups is indispensable. With these challenges in mind, our integrated approach incorporates GIS-based data with expert knowledge to consider two different land use interests - biodiversity value for conservation and timber production potential - with the focus on a complex mountain landscape in the French Alps. The spatial models produced provided different alternatives of suitable sites that can be used by policy makers in order to support conservation priorities while addressing management options. The approach provided provide a common reasoning language among different experts from different backgrounds while helped to identify spatially explicit conflictive areas.
Directory of Open Access Journals (Sweden)
Dirk W. te Velde
2006-12-01
Full Text Available Commercialization of non-timber forest products (NTFPs has been widely promoted as a means of sustainably developing tropical forest resources, in a way that promotes forest conservation while supporting rural livelihoods. However, in practice, NTFP commercialization has often failed to deliver the expected benefits. Progress in analyzing the causes of such failure has been hindered by the lack of a suitable framework for the analysis of NTFP case studies, and by the lack of predictive theory. We address these needs by developing a probabilistic model based on a livelihood framework, enabling the impact of NTFP commercialization on livelihoods to be predicted. The framework considers five types of capital asset needed to support livelihoods: natural, human, social, physical, and financial. Commercialization of NTFPs is represented in the model as the conversion of one form of capital asset into another, which is influenced by a variety of socio-economic, environmental, and political factors. Impacts on livelihoods are determined by the availability of the five types of assets following commercialization. The model, implemented as a Bayesian Belief Network, was tested using data from participatory research into 19 NTFP case studies undertaken in Mexico and Bolivia. The model provides a novel tool for diagnosing the causes of success and failure in NTFP commercialization, and can be used to explore the potential impacts of policy options and other interventions on livelihoods. The potential value of this approach for the development of NTFP theory is discussed.
Directory of Open Access Journals (Sweden)
AF. Colombo
Full Text Available After 500 years of exploitation and destruction, the Brazilian Atlantic Forest has been reduced to less the 8% of its original cover, and climate change may pose a new threat to the remnants of this biodiversity hotspot. In this study we used modelling techniques to determine present and future geographical distribution of 38 species of trees that are typical of the Brazilian Atlantic Forest (Mata Atlântica, considering two global warming scenarios. The optimistic scenario, based in a 0.5% increase in the concentration of CO2 in the atmosphere, predicts an increase of up to 2 °C in the Earth's average temperature; in the pessimistic scenario, based on a 1% increase in the concentration of CO2 in the atmosphere, temperature increase may reach 4 °C. Using these parameters, the occurrence points of the studied species registered in literature, the Genetic Algorithm for Rule-set Predictions/GARP and Maximum entropy modeling of species geographic distributions/MaxEnt we developed models of present and future possible occurrence of each species, considering Earth's mean temperature by 2050 with the optimistic and the pessimistic scenarios of CO2 emission. The results obtained show an alarming reduction in the area of possible occurrence of the species studied, as well as a shift towards southern areas of Brazil. Using GARP, on average, in the optimistic scenario this reduction is of 25% while in the pessimistic scenario it reaches 50%, and the species that will suffer the worst reduction in their possible area of occurrence are: Euterpe edulis, Mollinedia schottiana, Virola bicuhyba, Inga sessilis and Vochysia magnifica. Using MaxEnt, on average, in the optimistic scenario the reduction will be of 20% while in the pessimistic scenario it reaches 30%, and the species that will suffer the worst reduction are: Hyeronima alchorneoides, Schefflera angustissima, Andira fraxinifolia and the species of Myrtaceae studied.
Ancient associations of aquatic beetles and tank bromeliads in the Neotropical forest canopy.
Balke, Michael; Gómez-Zurita, Jesús; Ribera, Ignacio; Viloria, Angel; Zillikens, Anne; Steiner, Josephina; García, Mauricio; Hendrich, Lars; Vogler, Alfried P
2008-04-29
Water reservoirs formed by the leaf axils of bromeliads are a highly derived system for nutrient and water capture that also house a diverse fauna of invertebrate specialists. Here we investigate the origin and specificity of bromeliad-associated insects using Copelatinae diving beetles (Dytiscidae). This group is widely distributed in small water bodies throughout tropical forests, but a subset of species encountered in bromeliad tanks is strictly specialized to this habitat. An extensive molecular phylogenetic analysis of Neotropical Copelatinae places these bromeliadicolous species in at least three clades nested within other Copelatus. One lineage is morphologically distinct, and its origin was estimated to reach back to 12-23 million years ago, comparable to the age of the tank habitat itself. Species of this clade in the Atlantic rainforest of southern Brazil and mountain ranges of northern Venezuela and Trinidad show marked phylogeographical structure with up to 8% mtDNA divergence, possibly indicating allopatric speciation. The other two invasions of bromeliad water tanks are more recent, and haplotype distributions within species are best explained by recent expansion into newly formed habitat. Hence, bromeliad tanks create a second stratum of aquatic freshwater habitat independent of that on the ground but affected by parallel processes of species and population diversification at various temporal scales, possibly reflecting the paleoclimatic history of neotropical forests.
Ancient biomolecules from deep ice cores reveal a forested southern Greenland.
Willerslev, Eske; Cappellini, Enrico; Boomsma, Wouter; Nielsen, Rasmus; Hebsgaard, Martin B; Brand, Tina B; Hofreiter, Michael; Bunce, Michael; Poinar, Hendrik N; Dahl-Jensen, Dorthe; Johnsen, Sigfus; Steffensen, Jørgen Peder; Bennike, Ole; Schwenninger, Jean-Luc; Nathan, Roger; Armitage, Simon; de Hoog, Cees-Jan; Alfimov, Vasily; Christl, Marcus; Beer, Juerg; Muscheler, Raimund; Barker, Joel; Sharp, Martin; Penkman, Kirsty E H; Haile, James; Taberlet, Pierre; Gilbert, M Thomas P; Casoli, Antonella; Campani, Elisa; Collins, Matthew J
2007-07-06
It is difficult to obtain fossil data from the 10% of Earth's terrestrial surface that is covered by thick glaciers and ice sheets, and hence, knowledge of the paleoenvironments of these regions has remained limited. We show that DNA and amino acids from buried organisms can be recovered from the basal sections of deep ice cores, enabling reconstructions of past flora and fauna. We show that high-altitude southern Greenland, currently lying below more than 2 kilometers of ice, was inhabited by a diverse array of conifer trees and insects within the past million years. The results provide direct evidence in support of a forested southern Greenland and suggest that many deep ice cores may contain genetic records of paleoenvironments in their basal sections.
Insect leaf-chewing damage tracks herbivore richness in modern and ancient forests.
Directory of Open Access Journals (Sweden)
Mónica R Carvalho
Full Text Available The fossil record demonstrates that past climate changes and extinctions significantly affected the diversity of insect leaf-feeding damage, implying that the richness of damage types reflects that of the unsampled damage makers, and that the two are correlated through time. However, this relationship has not been quantified for living leaf-chewing insects, whose richness and mouthpart convergence have obscured their value for understanding past and present herbivore diversity. We hypothesized that the correlation of leaf-chewing damage types (DTs and damage maker richness is directly observable in living forests. Using canopy access cranes at two lowland tropical rainforest sites in Panamá to survey 24 host-plant species, we found significant correlations between the numbers of leaf chewing insect species collected and the numbers of DTs observed to be made by the same species in feeding experiments, strongly supporting our hypothesis. Damage type richness was largely driven by insect species that make multiple DTs. Also, the rank-order abundances of DTs recorded at the Panamá sites and across a set of latest Cretaceous to middle Eocene fossil floras were highly correlated, indicating remarkable consistency of feeding-mode distributions through time. Most fossil and modern host-plant pairs displayed high similarity indices for their leaf-chewing DTs, but informative differences and trends in fossil damage composition became apparent when endophytic damage was included. Our results greatly expand the potential of insect-mediated leaf damage for interpreting insect herbivore richness and compositional heterogeneity from fossil floras and, equally promisingly, in living forests.
Bidartondo, M.I.; Baar, J.; Bruns, T.D.
2001-01-01
Intersite variation in ectomycorrhizal (ECM) inoculum potential in soils from 16 sites located in arid subalpine areas of the White Mountains of California was quantified. The study sites included valleys dominated by big sagebrush (Artemisia tridentata Nutt.) and mountainsides dominated by ancient
Finley, Andrew O.; Banerjee, Sudipto; Cook, Bruce D.; Bradford, John B.
2013-01-01
In this paper we detail a multivariate spatial regression model that couples LiDAR, hyperspectral and forest inventory data to predict forest outcome variables at a high spatial resolution. The proposed model is used to analyze forest inventory data collected on the US Forest Service Penobscot Experimental Forest (PEF), ME, USA. In addition to helping meet the regression model's assumptions, results from the PEF analysis suggest that the addition of multivariate spatial random effects improves model fit and predictive ability, compared with two commonly applied modeling approaches. This improvement results from explicitly modeling the covariation among forest outcome variables and spatial dependence among observations through the random effects. Direct application of such multivariate models to even moderately large datasets is often computationally infeasible because of cubic order matrix algorithms involved in estimation. We apply a spatial dimension reduction technique to help overcome this computational hurdle without sacrificing richness in modeling.
DEFF Research Database (Denmark)
Willerslev, Eske; Cooper, Alan
2004-01-01
ancient DNA, palaeontology, palaeoecology, archaeology, population genetics, DNA damage and repair......ancient DNA, palaeontology, palaeoecology, archaeology, population genetics, DNA damage and repair...
Directory of Open Access Journals (Sweden)
Mark H. Huff
2006-12-01
Full Text Available We developed a set of decision-aiding models as Bayesian belief networks (BBNs that represented a complex set of evaluation guidelines used to determine the appropriate conservation of hundreds of potentially rare species on federally-administered lands in the Pacific Northwest United States. The models were used in a structured assessment and paneling procedure as part of an adaptive management process that evaluated new scientific information under the Northwest Forest Plan. The models were not prescriptive but helped resource managers and specialists to evaluate complicated and at times conflicting conservation guidelines and to reduce bias and uncertainty in evaluating the scientific data. We concluded that applying the BBN modeling framework to complex and equivocal evaluation guidelines provided a set of clear, intuitive decision-aiding tools that greatly aided the species evaluation and conservation process.
Ancient deforestation revisited.
Hughes, J Donald
2011-01-01
The image of the classical Mediterranean environment of the Greeks and Romans had a formative influence on the art, literature, and historical perception of modern Europe and America. How closely does is this image congruent with the ancient environment as it in reality existed? In particular, how forested was the ancient Mediterranean world, was there deforestation, and if so, what were its effects? The consensus of historians, geographers, and other scholars from the mid-nineteenth century through the first three quarters of the twentieth century was that human activities had depleted the forests to a major extent and caused severe erosion. My research confirmed this general picture. Since then, revisionist historians have questioned these conclusions, maintaining instead that little environmental damage was done to forests and soils in ancient Greco-Roman times. In a reconsideration of the question, this paper looks at recent scientific work providing proxy evidence for the condition of forests at various times in ancient history. I look at three scientific methodologies, namely anthracology, palynology, and computer modeling. Each of these avenues of research offers support for the concept of forest change, both in abundance and species composition, and episodes of deforestation and erosion, and confirms my earlier work.
Institute of Scientific and Technical Information of China (English)
陈耀华; 张欧
2015-01-01
As the development of conservation work of Ancient Tea Forests of Jingmai Mountain in Pu’er, defining its outstanding universal value in the context of World Heritage is of much importance. Based on social and natural investigation, this article mainly introduces the typical cultural landscape of the Ancient Tea Forests of Jingmai Mountain in Pu’er. It is considered that the ancient tea forests have not only the significance in interaction between man and nature, but also have a unique value and cultural significance in the cultural landscape heritages in physical geography and cultural geography perspective. The article expounds the development history, the key cultivation technology and the whole landscape of the forests and their important influence on man-land relationship and cultural inheritance. In the paper, the present situation and protection status of the ancient forests under the protection of the World Heritage Convention are also discussed, and a comparison with similar world famous agricultural landscape or famous tea garden is made. The preliminary results suggest that the landscape of the forests includes a high degree of integration of man and nature and has precious outstanding universal value. Generally speaking, the value of the Ancient Tea Forests of Jingmai Mountain in Pu’er is unique, as compared with other world heritage. The authenticity, integrality of the landscape may fit the world heritage criteria iii and v, thus the research and the understanding of the value of the ancient tea forests seem to be especially important for us, and they should be further investigated.%文章基于地理学视角，从普洱景迈山古茶林的自然科学价值和历史文化价值2个层次出发，研究并阐述了古茶林的“突出普遍价值”，探讨该景观在发展历史、关键技术、整体景观、人地关系及文化传承等方面产生的重要影响。在进一步分析和阐述古茶林现阶段保护情况的基础上
Evers, Virginia
This four-week fourth grade social studies unit dealing with religious dimensions in ancient Egyptian culture was developed by the Public Education Religion Studies Center at Wright State University. It seeks to help students understand ancient Egypt by looking at the people, the culture, and the people's world view. The unit begins with outlines…
Ancient and modern environmental DNA
DEFF Research Database (Denmark)
Pedersen, Mikkel Winther; Overballe-Petersen, Søren; Ermini, Luca
2015-01-01
DNA obtained from environmental samples such as sediments, ice or water (environmental DNA, eDNA), represents an important source of information on past and present biodiversity. It has revealed an ancient forest in Greenland, extended by several thousand years the survival dates for mainland woo...
Lesaffre, Emmanuel
2012-01-01
The growth of biostatistics has been phenomenal in recent years and has been marked by considerable technical innovation in both methodology and computational practicality. One area that has experienced significant growth is Bayesian methods. The growing use of Bayesian methodology has taken place partly due to an increasing number of practitioners valuing the Bayesian paradigm as matching that of scientific discovery. In addition, computational advances have allowed for more complex models to be fitted routinely to realistic data sets. Through examples, exercises and a combination of introd
新家, 健精
2013-01-01
© 2012 Springer Science+Business Media, LLC. All rights reserved. Article Outline: Glossary Definition of the Subject and Introduction The Bayesian Statistical Paradigm Three Examples Comparison with the Frequentist Statistical Paradigm Future Directions Bibliography
DEFF Research Database (Denmark)
Der Sarkissian, Clio; Allentoft, Morten Erik; Avila Arcos, Maria del Carmen
2015-01-01
by increasing the number of sequence reads to billions effectively means that contamination issues that have haunted aDNA research for decades, particularly in human studies, can now be efficiently and confidently quantified. At present, whole genomes have been sequenced from ancient anatomically modern humans......, archaic hominins, ancient pathogens and megafaunal species. Those have revealed important functional and phenotypic information, as well as unexpected adaptation, migration and admixture patterns. As such, the field of aDNA has entered the new era of genomics and has provided valuable information when...
DEFF Research Database (Denmark)
Der Sarkissian, Clio; Allentoft, Morten Erik; Avila Arcos, Maria del Carmen;
2015-01-01
, archaic hominins, ancient pathogens and megafaunal species. Those have revealed important functional and phenotypic information, as well as unexpected adaptation, migration and admixture patterns. As such, the field of aDNA has entered the new era of genomics and has provided valuable information when...
Bernardo, Jose M
2000-01-01
This highly acclaimed text, now available in paperback, provides a thorough account of key concepts and theoretical results, with particular emphasis on viewing statistical inference as a special case of decision theory. Information-theoretic concepts play a central role in the development of the theory, which provides, in particular, a detailed discussion of the problem of specification of so-called prior ignorance . The work is written from the authors s committed Bayesian perspective, but an overview of non-Bayesian theories is also provided, and each chapter contains a wide-ranging critica
Villalba, Jesús
2015-01-01
In this document we are going to derive the equations needed to implement a Variational Bayes estimation of the parameters of the simplified probabilistic linear discriminant analysis (SPLDA) model. This can be used to adapt SPLDA from one database to another with few development data or to implement the fully Bayesian recipe. Our approach is similar to Bishop's VB PPCA.
Hedlund, Jonas
2014-01-01
This paper introduces private sender information into a sender-receiver game of Bayesian persuasion with monotonic sender preferences. I derive properties of increasing differences related to the precision of signals and use these to fully characterize the set of equilibria robust to the intuitive criterion. In particular, all such equilibria are either separating, i.e., the sender's choice of signal reveals his private information to the receiver, or fully disclosing, i.e., the outcome of th...
Kirstein, Roland
2005-01-01
This paper presents a modification of the inspection game: The ?Bayesian Monitoring? model rests on the assumption that judges are interested in enforcing compliant behavior and making correct decisions. They may base their judgements on an informative but imperfect signal which can be generated costlessly. In the original inspection game, monitoring is costly and generates a perfectly informative signal. While the inspection game has only one mixed strategy equilibrium, three Perfect Bayesia...
Swamy, Ashwin Balegar
This thesis involves development of an interactive GIS (Geographic Information System) based application, which gives information about the ancient history of Egypt. The astonishing architecture, the strange burial rituals and their civilization were some of the intriguing questions that motivated me towards developing this application. The application is a historical timeline starting from 3100 BC, leading up to 664 BC, focusing on the evolution of the Egyptian dynasties. The tool holds information regarding some of the famous monuments which were constructed during that era and also about the civilizations that co-existed. It also provides details about the religions followed by their kings. It also includes the languages spoken during those periods. The tool is developed using JAVA, a programing language and MOJO (Map Objects Java Objects) a product of ESRI (Environmental Science Research Institute) to create map objects, to provide geographic information. JAVA Swing is used for designing the user interface. HTML (Hyper Text Markup Language) pages are created to provide the user with more information related to the historic period. CSS (Cascade Style Sheets) and JAVA Scripts are used with HTML5 to achieve creative display of content. The tool is kept simple and easy for the user to interact with. The tool also includes pictures and videos for the user to get a feel of the historic period. The application is built to motivate people to know more about one of the prominent and ancient civilization of the Mediterranean world.
Bessiere, Pierre; Ahuactzin, Juan Manuel; Mekhnacha, Kamel
2013-01-01
Probability as an Alternative to Boolean LogicWhile logic is the mathematical foundation of rational reasoning and the fundamental principle of computing, it is restricted to problems where information is both complete and certain. However, many real-world problems, from financial investments to email filtering, are incomplete or uncertain in nature. Probability theory and Bayesian computing together provide an alternative framework to deal with incomplete and uncertain data. Decision-Making Tools and Methods for Incomplete and Uncertain DataEmphasizing probability as an alternative to Boolean
Face detection by aggregated Bayesian network classifiers
Pham, T.V.; Worring, M.; Smeulders, A.W.M.
2002-01-01
A face detection system is presented. A new classification method using forest-structured Bayesian networks is used. The method is used in an aggregated classifier to discriminate face from non-face patterns. The process of generating non-face patterns is integrated with the construction of the aggr
Institute of Scientific and Technical Information of China (English)
丁平; 沈承德; 王宁; 易惟熙; 丁杏芳; 付东坡; 刘克新
2012-01-01
珠江三角洲四会市和高要市两地埋藏古森林在发育历史时期形成了一层或多层腐殖质层.其中,四会埋藏古森林腐殖质层发育起止年代大致为4218±91cal.aB.P.～3291±24cal.aB.P.;高要埋藏古森林腐殖质层发育有3期,它们的年代大致为4910±64～ 1966±42cal.aB.P.,但在4347±63～4017±35cal.aB.P.和3658±45～ 3539±19cal.aB.P.之间发育中断,形成两层灰白色粘土层,3期腐殖质层(从上至下)发育持续的时间分别为1500a,400a和500a,约1000±500a.在四会埋藏古森林腐殖质层中,有机碳含量在26.2％～48.9％之间变化,δ13C值波动介于-29.8‰～ -25.6‰之间,其中,粘土层与腐殖质层边界点的有机碳含量为26.2％,δ13C值为-25.6‰,对应的年代为3291±24cal.aB.P.;在高要埋藏古森林腐殖质层中,有机碳含量在20.3％ ～ 64.0％之间变化,δ13C值波动介于-30.9‰ ～ -29.0‰之间,而在腐殖质层之间的粘土层的中心位置,有机碳含量从上至下分别为1.0％和8.8％,对应的δ13C值分别为-28.2‰和-27.8‰,较相邻腐殖质层平均δ13C值偏正约2.0‰至2.5‰.腐殖质层有机碳含量与δ13C值显示,埋藏古森林腐殖质层形成于湿地环境,而粘土层中有机碳含量和δ13C值与腐殖质层中的显著差异及粘土层的沉积特征则说明粘土层很可能形成旱地环境.沉积环境干湿变化的周期与腐殖质层持续的时间一致,大致为1000±500a,这种变化可能与中全新世以来气候在千百年尺度上的波动相关,而四会和高要两地古森林湿地发育的起止时间不一致则主要与两地的地理位置及地形不同相关.%Sihui and Gaoyao are both located in the Pearl River Delta. The buried ancient forests with an area about 0. 02km2 in Sihui is situated at Longfu(23°22'359"N,112°42'497"E) ,the center of Sihui. The buried ancient forest profile in Sihui is 4. 8m high,consisting of four layers; the yellow brown coarse aleuritic clay layer
Introduction to Bayesian statistics
Bolstad, William M
2017-01-01
There is a strong upsurge in the use of Bayesian methods in applied statistical analysis, yet most introductory statistics texts only present frequentist methods. Bayesian statistics has many important advantages that students should learn about if they are going into fields where statistics will be used. In this Third Edition, four newly-added chapters address topics that reflect the rapid advances in the field of Bayesian staistics. The author continues to provide a Bayesian treatment of introductory statistical topics, such as scientific data gathering, discrete random variables, robust Bayesian methods, and Bayesian approaches to inferenfe cfor discrete random variables, bionomial proprotion, Poisson, normal mean, and simple linear regression. In addition, newly-developing topics in the field are presented in four new chapters: Bayesian inference with unknown mean and variance; Bayesian inference for Multivariate Normal mean vector; Bayesian inference for Multiple Linear RegressionModel; and Computati...
Bayesian artificial intelligence
Korb, Kevin B
2003-01-01
As the power of Bayesian techniques has become more fully realized, the field of artificial intelligence has embraced Bayesian methodology and integrated it to the point where an introduction to Bayesian techniques is now a core course in many computer science programs. Unlike other books on the subject, Bayesian Artificial Intelligence keeps mathematical detail to a minimum and covers a broad range of topics. The authors integrate all of Bayesian net technology and learning Bayesian net technology and apply them both to knowledge engineering. They emphasize understanding and intuition but also provide the algorithms and technical background needed for applications. Software, exercises, and solutions are available on the authors' website.
Bayesian artificial intelligence
Korb, Kevin B
2010-01-01
Updated and expanded, Bayesian Artificial Intelligence, Second Edition provides a practical and accessible introduction to the main concepts, foundation, and applications of Bayesian networks. It focuses on both the causal discovery of networks and Bayesian inference procedures. Adopting a causal interpretation of Bayesian networks, the authors discuss the use of Bayesian networks for causal modeling. They also draw on their own applied research to illustrate various applications of the technology.New to the Second EditionNew chapter on Bayesian network classifiersNew section on object-oriente
Applied Bayesian Hierarchical Methods
Congdon, Peter D
2010-01-01
Bayesian methods facilitate the analysis of complex models and data structures. Emphasizing data applications, alternative modeling specifications, and computer implementation, this book provides a practical overview of methods for Bayesian analysis of hierarchical models.
Gelman, Andrew; Stern, Hal S; Dunson, David B; Vehtari, Aki; Rubin, Donald B
2013-01-01
FUNDAMENTALS OF BAYESIAN INFERENCEProbability and InferenceSingle-Parameter Models Introduction to Multiparameter Models Asymptotics and Connections to Non-Bayesian ApproachesHierarchical ModelsFUNDAMENTALS OF BAYESIAN DATA ANALYSISModel Checking Evaluating, Comparing, and Expanding ModelsModeling Accounting for Data Collection Decision AnalysisADVANCED COMPUTATION Introduction to Bayesian Computation Basics of Markov Chain Simulation Computationally Efficient Markov Chain Simulation Modal and Distributional ApproximationsREGRESSION MODELS Introduction to Regression Models Hierarchical Linear
Discovering the Ancient Maya from Space
Sever, T. L.
2008-01-01
The Pet6n region of northern Guatemala contains some of the most significant Mayan archeological sites in Latin America. It was in this region that the Maya civilization began, flourished, and abruptly disappeared. Remote sensing technology is helping to locate and map ancient Maya sites that are threatened today by accelerating deforestation and looting. Thematic Mapper, IKONOS, and QuickBird satellite, and airborne STAR-3i and AIRSAR radar data, combined with Global Positioning System (GPS) technology, are successfully detecting ancient Maya features such as sites, roadways, canals, and water reservoirs. Satellite imagery is also being used to map the bajos, which are seasonally flooded swamps that cover over 40% of the land surface. Through the use of various airborne and satellite sensor systems we have been able to detect and map ancient causeways, temples, reservoirs, and land forms, and locate these features on the ground through GPS technology. Recently, we have discovered that there is a strong relationship between a tropical forest vegetation signature in satellite imagery and the location of archeological sites. We believe that the use of limestone and lime plasters in ancient Maya construction affects the moisture, nutrition, and plant species of the surface vegetation. We have mapped these vegetation signatures in the imagery and verified through field survey that they are indicative of archeological sites. Through the use of remote sensing and GIS technology it is possible to identify unrecorded archeological features in a dense tropical forest environment and monitor these cultural features for their protection.
Forest crimes as a threat to sustainable forest management
2016-01-01
From ancient times to the present day, forest public relations has been an issue on the agenda. This relationship’s purpose was initially needed for shelter and nutrition; however today this process has changed with urbanization, overpopulation and understanding the new functions of forests. When land ownership became a tool of production, offenses occurred in order to convert forestlands to agricultural lands. So the vast majority of the world’s forests have been lost for this reason. Today,...
Bayesian Games with Intentions
Directory of Open Access Journals (Sweden)
Adam Bjorndahl
2016-06-01
Full Text Available We show that standard Bayesian games cannot represent the full spectrum of belief-dependent preferences. However, by introducing a fundamental distinction between intended and actual strategies, we remove this limitation. We define Bayesian games with intentions, generalizing both Bayesian games and psychological games, and prove that Nash equilibria in psychological games correspond to a special class of equilibria as defined in our setting.
Bayesian statistics an introduction
Lee, Peter M
2012-01-01
Bayesian Statistics is the school of thought that combines prior beliefs with the likelihood of a hypothesis to arrive at posterior beliefs. The first edition of Peter Lee’s book appeared in 1989, but the subject has moved ever onwards, with increasing emphasis on Monte Carlo based techniques. This new fourth edition looks at recent techniques such as variational methods, Bayesian importance sampling, approximate Bayesian computation and Reversible Jump Markov Chain Monte Carlo (RJMCMC), providing a concise account of the way in which the Bayesian approach to statistics develops as wel
Understanding Computational Bayesian Statistics
Bolstad, William M
2011-01-01
A hands-on introduction to computational statistics from a Bayesian point of view Providing a solid grounding in statistics while uniquely covering the topics from a Bayesian perspective, Understanding Computational Bayesian Statistics successfully guides readers through this new, cutting-edge approach. With its hands-on treatment of the topic, the book shows how samples can be drawn from the posterior distribution when the formula giving its shape is all that is known, and how Bayesian inferences can be based on these samples from the posterior. These ideas are illustrated on common statistic
Parsamian, Elma S.
2007-08-01
The most important discovery, which enriched our knowledge of ancient astronomy in Armenia, was the complex of platforms for astronomical observations on the Small Hill of Metzamor, which may be called an ancient “observatory”. Investigations on that Hill show that the ancient inhabitants of the Armenian Highlands have left us not only pictures of celestial bodies, but a very ancient complex of platforms for observing the sky. Among the ancient monuments in Armenia there is a megalithic monument, probably, being connected with astronomy. 250km South-East of Yerevan there is a structure Zorats Kar (Karahunge) dating back to II millennium B.C. Vertical megaliths many of which are more than two meters high form stone rings resembling ancient stone monuments - henges in Great Britain and Brittany. Medieval observations of comets and novas by data in ancient Armenian manuscripts are found. In the collection of ancient Armenian manuscripts (Matenadaran) in Yerevan there are many manuscripts with information about observations of astronomical events as: solar and lunar eclipses, comets and novas, bolides and meteorites etc. in medieval Armenia.
Endalamaw, T.B.; Wiersum, K.F.
2009-01-01
Forest beekeeping is an ancient form of forest exploitation in south west Ethiopia. The practice has continued to the present with a gradual evolution in beekeeping technology and resource access and management arrangements. The aim of the present study is to study traditional forest management syst
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…
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.
Konstruksi Bayesian Network Dengan Algoritma Bayesian Association Rule Mining Network
Octavian
2015-01-01
Beberapa tahun terakhir, Bayesian Network telah menjadi konsep yang populer digunakan dalam berbagai bidang kehidupan seperti dalam pengambilan sebuah keputusan dan menentukan peluang suatu kejadian dapat terjadi. Sayangnya, pengkonstruksian struktur dari Bayesian Network itu sendiri bukanlah hal yang sederhana. Oleh sebab itu, penelitian ini mencoba memperkenalkan algoritma Bayesian Association Rule Mining Network untuk memudahkan kita dalam mengkonstruksi Bayesian Network berdasarkan data ...
Institute of Scientific and Technical Information of China (English)
1997-01-01
Clearly defined rites governing speech and actions dominated both the social and domestic activities of ancient Chinese people. Rites not only dominated the lives of men, but were also prominent in the lives of women.
Institute of Scientific and Technical Information of China (English)
1993-01-01
CHINESE people have accu-mulated a great deal ofexperience in architecture,constantly improving building ma-terials and thus creating uniquebuilding styles.The history of ancient Chinesearchitechtural development can be
Model Diagnostics for Bayesian Networks
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…
Bayesian Lensing Shear Measurement
Bernstein, Gary M
2013-01-01
We derive an estimator of weak gravitational lensing shear from background galaxy images that avoids noise-induced biases through a rigorous Bayesian treatment of the measurement. The Bayesian formalism requires a prior describing the (noiseless) distribution of the target galaxy population over some parameter space; this prior can be constructed from low-noise images of a subsample of the target population, attainable from long integrations of a fraction of the survey field. We find two ways to combine this exact treatment of noise with rigorous treatment of the effects of the instrumental point-spread function and sampling. The Bayesian model fitting (BMF) method assigns a likelihood of the pixel data to galaxy models (e.g. Sersic ellipses), and requires the unlensed distribution of galaxies over the model parameters as a prior. The Bayesian Fourier domain (BFD) method compresses galaxies to a small set of weighted moments calculated after PSF correction in Fourier space. It requires the unlensed distributi...
Fox, G.J.A.; Berg, van den S.M.; Veldkamp, B.P.; Irwing, P.; Booth, T.; Hughes, D.
2015-01-01
In educational and psychological studies, psychometric methods are involved in the measurement of constructs, and in constructing and validating measurement instruments. Assessment results are typically used to measure student proficiency levels and test characteristics. Recently, Bayesian item resp
Noncausal Bayesian Vector Autoregression
DEFF Research Database (Denmark)
Lanne, Markku; Luoto, Jani
We propose a Bayesian inferential procedure for the noncausal vector autoregressive (VAR) model that is capable of capturing nonlinearities and incorporating effects of missing variables. In particular, we devise a fast and reliable posterior simulator that yields the predictive distribution...
Granade, Christopher; Cory, D G
2015-01-01
In recent years, Bayesian methods have been proposed as a solution to a wide range of issues in quantum state and process tomography. State-of- the-art Bayesian tomography solutions suffer from three problems: numerical intractability, a lack of informative prior distributions, and an inability to track time-dependent processes. Here, we solve all three problems. First, we use modern statistical methods, as pioneered by Husz\\'ar and Houlsby and by Ferrie, to make Bayesian tomography numerically tractable. Our approach allows for practical computation of Bayesian point and region estimators for quantum states and channels. Second, we propose the first informative priors on quantum states and channels. Finally, we develop a method that allows online tracking of time-dependent states and estimates the drift and diffusion processes affecting a state. We provide source code and animated visual examples for our methods.
Directory of Open Access Journals (Sweden)
Quentin Rougemont
2016-04-01
Full Text Available Inferring the history of isolation and gene flow during species divergence is a central question in evolutionary biology. The European river lamprey (Lampetra fluviatilis and brook lamprey (L. planeri show a low reproductive isolation but have highly distinct life histories, the former being parasitic-anadromous and the latter non-parasitic and freshwater resident. Here we used microsatellite data from six replicated population pairs to reconstruct their history of divergence using an approximate Bayesian computation framework combined with a random forest model. In most population pairs, scenarios of divergence with recent isolation were outcompeted by scenarios proposing ongoing gene flow, namely the Secondary Contact (SC and Isolation with Migration (IM models. The estimation of demographic parameters under the SC model indicated a time of secondary contact close to the time of speciation, explaining why SC and IM models could not be discriminated. In case of an ancient secondary contact, the historical signal of divergence is lost and neutral markers converge to the same equilibrium as under the less parameterized model allowing ongoing gene flow. Our results imply that models of secondary contacts should be systematically compared to models of divergence with gene flow; given the difficulty to discriminate among these models, we suggest that genome-wide data are needed to adequately reconstruct divergence history.
Dentistry in ancient mesopotamia.
Neiburger, E J
2000-01-01
Sumer, an empire in ancient Mesopotamia (southern Iraq), is well known as the cradle of our modern civilization and the home of biblical Abraham. An analysis of skeletal remains from cemeteries at the ancient cities of Ur and Kish (circa 2000 B.C.), show a genetically homogeneous, diseased, and short-lived population. These ancient Mesopotamians suffered severe dental attrition (95 percent), periodontal disease (42 percent), and caries (2 percent). Many oral congenital and neoplastic lesions were noted. During this period, the "local dentists" knew only a few modern dental techniques. Skeletal (dental) evidence indicates that the population suffered from chronic malnutrition. Malnutrition was probably caused by famine, which is substantiated in historic cuneiform and biblical writings, geologic strata samples, and analysis of skeletal and forensic dental pathology. These people had modern dentition but relatively poor dental health. The population's lack of malocclusions, caries, and TMJ problems appear to be due to flat plane occlusion.
Kozma, Chahira
2006-02-15
Ancient Egypt was one of the most advanced and productive civilizations in antiquity, spanning 3000 years before the "Christian" era. Ancient Egyptians built colossal temples and magnificent tombs to honor their gods and religious leaders. Their hieroglyphic language, system of organization, and recording of events give contemporary researchers insights into their daily activities. Based on the record left by their art, the ancient Egyptians documented the presence of dwarfs in almost every facet of life. Due to the hot dry climate and natural and artificial mummification, Egypt is a major source of information on achondroplasia in the old world. The remains of dwarfs are abundant and include complete and partial skeletons. Dwarfs were employed as personal attendants, animal tenders, jewelers, and entertainers. Several high-ranking dwarfs especially from the Old Kingdom (2700-2190 BCE) achieved important status and had lavish burial places close to the pyramids. Their costly tombs in the royal cemeteries and the inscriptions on their statutes indicate their high-ranking position in Egyptian society and their close relation to the king. Some of them were Seneb, Pereniankh, Khnumhotpe, and Djeder. There were at least two dwarf gods, Ptah and Bes. The god Ptah was associated with regeneration and rejuvenation. The god Bes was a protector of sexuality, childbirth, women, and children. He was a favored deity particularly during the Greco-Roman period. His temple was recently excavated in the Baharia oasis in the middle of Egypt. The burial sites and artistic sources provide glimpses of the positions of dwarfs in daily life in ancient Egypt. Dwarfs were accepted in ancient Egypt; their recorded daily activities suggest assimilation into daily life, and their disorder was not shown as a physical handicap. Wisdom writings and moral teachings in ancient Egypt commanded respect for dwarfs and other individuals with disabilities.
Bayesian Face Sketch Synthesis.
Wang, Nannan; Gao, Xinbo; Sun, Leiyu; Li, Jie
2017-03-01
Exemplar-based face sketch synthesis has been widely applied to both digital entertainment and law enforcement. In this paper, we propose a Bayesian framework for face sketch synthesis, which provides a systematic interpretation for understanding the common properties and intrinsic difference in different methods from the perspective of probabilistic graphical models. The proposed Bayesian framework consists of two parts: the neighbor selection model and the weight computation model. Within the proposed framework, we further propose a Bayesian face sketch synthesis method. The essential rationale behind the proposed Bayesian method is that we take the spatial neighboring constraint between adjacent image patches into consideration for both aforementioned models, while the state-of-the-art methods neglect the constraint either in the neighbor selection model or in the weight computation model. Extensive experiments on the Chinese University of Hong Kong face sketch database demonstrate that the proposed Bayesian method could achieve superior performance compared with the state-of-the-art methods in terms of both subjective perceptions and objective evaluations.
Creative Ventures: Ancient Civilizations.
Stark, Rebecca
The open-ended activities in this book are designed to extend the imagination and creativity of students and encourage students to examine their feelings and values about historic eras. Civilizations addressed include ancient Egypt, Greece, Rome, Mayan, Stonehenge, and Mesopotamia. The activities focus upon the cognitive and affective pupil…
Ancient Egypt: Personal Perspectives.
Wolinski, Arelene
This teacher resource book provides information on ancient Egypt via short essays, photographs, maps, charts, and drawings. Egyptian social and religious life, including writing, art, architecture, and even the practice of mummification, is conveniently summarized for the teacher or other practitioner in a series of one to three page articles with…
Institute of Scientific and Technical Information of China (English)
2009-01-01
west of Tiananmen Square in Beijing, in Zhongshan Park, there stand several ancient cypress trees, each more than 1,000 years old. Their leafy crowns are all more than 20 meters high, while four have trunks that are 6 meters in circumference. The most unique of these
Digital Repository Service at National Institute of Oceanography (India)
Tripati, S.
The ancient Kingdom of Kalinga mentioned in the Hathigumpha inscription of Kharavela (1st century B.C.) extended from the mouths of the Ganges to the estuary of Godavari river on the East Coast. Ptolemy (100 A.D.) mentions that Paluru (District...
Printing Ancient Terracotta Warriors
Gadecki, Victoria L.
2010-01-01
Standing in awe in Xian, China, at the Terra Cotta warrior archaeological site, the author thought of sharing this experience and excitement with her sixth-grade students. She decided to let her students carve patterns of the ancient soldiers to understand their place in Chinese history. They would make block prints and print multiple soldiers on…
Bayesian least squares deconvolution
Asensio Ramos, A.; Petit, P.
2015-11-01
Aims: We develop a fully Bayesian least squares deconvolution (LSD) that can be applied to the reliable detection of magnetic signals in noise-limited stellar spectropolarimetric observations using multiline techniques. Methods: We consider LSD under the Bayesian framework and we introduce a flexible Gaussian process (GP) prior for the LSD profile. This prior allows the result to automatically adapt to the presence of signal. We exploit several linear algebra identities to accelerate the calculations. The final algorithm can deal with thousands of spectral lines in a few seconds. Results: We demonstrate the reliability of the method with synthetic experiments and we apply it to real spectropolarimetric observations of magnetic stars. We are able to recover the magnetic signals using a small number of spectral lines, together with the uncertainty at each velocity bin. This allows the user to consider if the detected signal is reliable. The code to compute the Bayesian LSD profile is freely available.
Hybrid Batch Bayesian Optimization
Azimi, Javad; Fern, Xiaoli
2012-01-01
Bayesian Optimization aims at optimizing an unknown non-convex/concave function that is costly to evaluate. We are interested in application scenarios where concurrent function evaluations are possible. Under such a setting, BO could choose to either sequentially evaluate the function, one input at a time and wait for the output of the function before making the next selection, or evaluate the function at a batch of multiple inputs at once. These two different settings are commonly referred to as the sequential and batch settings of Bayesian Optimization. In general, the sequential setting leads to better optimization performance as each function evaluation is selected with more information, whereas the batch setting has an advantage in terms of the total experimental time (the number of iterations). In this work, our goal is to combine the strength of both settings. Specifically, we systematically analyze Bayesian optimization using Gaussian process as the posterior estimator and provide a hybrid algorithm t...
Bayesian least squares deconvolution
Ramos, A Asensio
2015-01-01
Aims. To develop a fully Bayesian least squares deconvolution (LSD) that can be applied to the reliable detection of magnetic signals in noise-limited stellar spectropolarimetric observations using multiline techniques. Methods. We consider LSD under the Bayesian framework and we introduce a flexible Gaussian Process (GP) prior for the LSD profile. This prior allows the result to automatically adapt to the presence of signal. We exploit several linear algebra identities to accelerate the calculations. The final algorithm can deal with thousands of spectral lines in a few seconds. Results. We demonstrate the reliability of the method with synthetic experiments and we apply it to real spectropolarimetric observations of magnetic stars. We are able to recover the magnetic signals using a small number of spectral lines, together with the uncertainty at each velocity bin. This allows the user to consider if the detected signal is reliable. The code to compute the Bayesian LSD profile is freely available.
Bayesian Exploratory Factor Analysis
DEFF Research Database (Denmark)
Conti, Gabriella; Frühwirth-Schnatter, Sylvia; Heckman, James J.;
2014-01-01
This paper develops and applies a Bayesian approach to Exploratory Factor Analysis that improves on ad hoc classical approaches. Our framework relies on dedicated factor models and simultaneously determines the number of factors, the allocation of each measurement to a unique factor, and the corr......This paper develops and applies a Bayesian approach to Exploratory Factor Analysis that improves on ad hoc classical approaches. Our framework relies on dedicated factor models and simultaneously determines the number of factors, the allocation of each measurement to a unique factor......, and the corresponding factor loadings. Classical identification criteria are applied and integrated into our Bayesian procedure to generate models that are stable and clearly interpretable. A Monte Carlo study confirms the validity of the approach. The method is used to produce interpretable low dimensional aggregates...
Center, Julian L.; Knuth, Kevin H.
2011-03-01
Visual odometry refers to tracking the motion of a body using an onboard vision system. Practical visual odometry systems combine the complementary accuracy characteristics of vision and inertial measurement units. The Mars Exploration Rovers, Spirit and Opportunity, used this type of visual odometry. The visual odometry algorithms in Spirit and Opportunity were based on Bayesian methods, but a number of simplifying approximations were needed to deal with onboard computer limitations. Furthermore, the allowable motion of the rover had to be severely limited so that computations could keep up. Recent advances in computer technology make it feasible to implement a fully Bayesian approach to visual odometry. This approach combines dense stereo vision, dense optical flow, and inertial measurements. As with all true Bayesian methods, it also determines error bars for all estimates. This approach also offers the possibility of using Micro-Electro Mechanical Systems (MEMS) inertial components, which are more economical, weigh less, and consume less power than conventional inertial components.
Probabilistic Inferences in Bayesian Networks
Ding, Jianguo
2010-01-01
This chapter summarizes the popular inferences methods in Bayesian networks. The results demonstrates that the evidence can propagated across the Bayesian networks by any links, whatever it is forward or backward or intercausal style. The belief updating of Bayesian networks can be obtained by various available inference techniques. Theoretically, exact inferences in Bayesian networks is feasible and manageable. However, the computing and inference is NP-hard. That means, in applications, in ...
Bayesian multiple target tracking
Streit, Roy L
2013-01-01
This second edition has undergone substantial revision from the 1999 first edition, recognizing that a lot has changed in the multiple target tracking field. One of the most dramatic changes is in the widespread use of particle filters to implement nonlinear, non-Gaussian Bayesian trackers. This book views multiple target tracking as a Bayesian inference problem. Within this framework it develops the theory of single target tracking, multiple target tracking, and likelihood ratio detection and tracking. In addition to providing a detailed description of a basic particle filter that implements
Bayesian methods for hackers probabilistic programming and Bayesian inference
Davidson-Pilon, Cameron
2016-01-01
Bayesian methods of inference are deeply natural and extremely powerful. However, most discussions of Bayesian inference rely on intensely complex mathematical analyses and artificial examples, making it inaccessible to anyone without a strong mathematical background. Now, though, Cameron Davidson-Pilon introduces Bayesian inference from a computational perspective, bridging theory to practice–freeing you to get results using computing power. Bayesian Methods for Hackers illuminates Bayesian inference through probabilistic programming with the powerful PyMC language and the closely related Python tools NumPy, SciPy, and Matplotlib. Using this approach, you can reach effective solutions in small increments, without extensive mathematical intervention. Davidson-Pilon begins by introducing the concepts underlying Bayesian inference, comparing it with other techniques and guiding you through building and training your first Bayesian model. Next, he introduces PyMC through a series of detailed examples a...
DEFF Research Database (Denmark)
Jensen, Finn Verner; Nielsen, Thomas Dyhre
2016-01-01
and edges. The nodes represent variables, which may be either discrete or continuous. An edge between two nodes A and B indicates a direct influence between the state of A and the state of B, which in some domains can also be interpreted as a causal relation. The wide-spread use of Bayesian networks...
DEFF Research Database (Denmark)
Antoniou, Constantinos; Harrison, Glenn W.; Lau, Morten I.;
2015-01-01
A large literature suggests that many individuals do not apply Bayes’ Rule when making decisions that depend on them correctly pooling prior information and sample data. We replicate and extend a classic experimental study of Bayesian updating from psychology, employing the methods of experimental...
Across and within-forest effects on breeding success in Mediterranean Great Tits Parus major
Atienzar, Francisco; Visser, Marcel E.; Greno, Jose L.; Holleman, Leonard J. M.; Belda, Eduardo J.; Barba, Emilio
2010-01-01
Forest type and habitat structure can have profound effects on different aspects of avian life histories. These effects may, however, strongly differ across and within forests that vary in vegetation composition and structure, especially when an ancient forest has been replaced by a new forest. To t
Warinner, Christina; Speller, Camilla; Collins, Matthew J; Lewis, Cecil M
2015-02-01
Very recently, we discovered a vast new microbial self: the human microbiome. Our native microbiota interface with our biology and culture to influence our health, behavior, and quality of life, and yet we know very little about their origin, evolution, or ecology. With the advent of industrialization, globalization, and modern sanitation, it is intuitive that we have changed our relationship with microbes, but we have little information about the ancestral state of our microbiome, and we therefore lack a foundation for characterizing this change. High-throughput sequencing has opened up new opportunities in the field of paleomicrobiology, allowing us to investigate the evolution of the complex microbial ecologies that inhabit our bodies. By focusing on recent coprolite and dental calculus research, we explore how emerging research on ancient human microbiomes is changing the way we think about ancient disease and how archaeological studies can contribute to a medical understanding of health and nutrition today.
Gupta, Patrick Das
2014-01-01
The Indo-aryans of ancient India observed stars and constellations for ascertaining auspicious times for sacrificial rites ordained by vedas. It is but natural that they would have recounted in the vedic texts about comets. In Rigveda ($\\sim $ 1700 - 1500 BC) and Atharvaveda ($\\sim $ 1150 BC), there are references to dhumaketus and ketus, which stand for comets in Sanskrit. Varahamihira in 550 AD and Ballala Sena ($\\sim $ 1100 - 1200 AD) have described a large number of comets recorded by ancient seers such as Parashara, Vriddha Garga, Narada, Garga, etc. In this article, I conjecture that an episode narrated in Mahabharata of a radiant king, Nahusha, ruling the heavens, and later turning into a serpent after he had kicked the seer Agastya (also the star Canopus), is a mythological retelling of a cometary event.
Institute of Scientific and Technical Information of China (English)
HUOJIANYING
2004-01-01
IN 196 B.C. a Chinese philosopher observedto his ruler: "A lord's to ppriority is the welfare of his subjects; to the peopie, eating is foremost." Chinese ancients perceived clearly the essentiality of grain cultivation to the survival of the population and country as a whole. This is apparent in the premillennial term for "country" -sheji literally translated as god of land and grain.
Budde, K B; González-Martínez, S C; Hardy, O J; Heuertz, M
2013-07-01
Understanding the history of forests and their species' demographic responses to past disturbances is important for predicting impacts of future environmental changes. Tropical rainforests of the Guineo-Congolian region in Central Africa are believed to have survived the Pleistocene glacial periods in a few major refugia, essentially centred on mountainous regions close to the Atlantic Ocean. We tested this hypothesis by investigating the phylogeographic structure of a widespread, ancient rainforest tree species, Symphonia globulifera L. f. (Clusiaceae), using plastid DNA sequences (chloroplast DNA [cpDNA], psbA-trnH intergenic spacer) and nuclear microsatellites (simple sequence repeats, SSRs). SSRs identified four gene pools located in Benin, West Cameroon, South Cameroon and Gabon, and São Tomé. This structure was also apparent at cpDNA. Approximate Bayesian Computation detected recent bottlenecks approximately dated to the last glacial maximum in Benin, West Cameroon and São Tomé, and an older bottleneck in South Cameroon and Gabon, suggesting a genetic effect of Pleistocene cycles of forest contraction. CpDNA haplotype distribution indicated wide-ranging long-term persistence of S. globulifera both inside and outside of postulated forest refugia. Pollen flow was four times greater than that of seed in South Cameroon and Gabon, which probably enabled rapid population recovery after bottlenecks. Furthermore, our study suggested ecotypic differentiation-coastal or swamp vs terra firme-in S. globulifera. Comparison with other tree phylogeographic studies in Central Africa highlighted the relevance of species-specific responses to environmental change in forest trees.
Institute of Scientific and Technical Information of China (English)
2012-01-01
The typical style and features of mountains and waters in Caoshi Ancient Town,have hitherto been well preserved. Caoshi Ancient Town boasts superior base of the natural eco-environment and deep-rooted background of regional culture,where mountains,waters,shoals,towns and other landscape elements are merged harmoniously,the transportation and geographical conditions have been fundamentally changed. Ancient towns,old temples,ancient forests,ancient wells and ancient piers are unique in different ways,with characteristics of tourism resources such as long history and ancient folklore. It should seize the historical opportunity of China vigorously developing rural tourism based on the construction of the new socialist countryside,to make characteristic agricultural economy gain ground; assume the leading role to drive the development of tourism economy in surrounding areas; correctly handle the relationship between development and protection to walk the path of sustainable development of tourism.
Laios, K; Tsoukalas, G; Kontaxaki, M-I; Karamanou, M; Androutsos, G
2014-01-01
The theme of suicide appears several times in ancient Greek literature. However, each such reference acquires special significance depending on the field from which it originates. Most of the information found in mythology, but the suicide in a mythological tale, although in terms of motivation and mental situation of heroes may be in imitation of similar incidents of real life, in fact is linked with the principles of the ancient Greek religion. In ancient drama and mainly in tragedies suicide conduces to the tragic hypostasis of the heroes and to the evolution of the plot and also is a tool in order to be presented the ideas of poets for the relations of the gods, the relation among gods and men and the relation among the men. In ancient Greek philosophy there were the deniers of suicide, who were more concerned about the impact of suicide on society and also these who accepted it, recognizing the right of the individual to put an end to his life, in order to avoid personal misfortunes. Real suicides will be found mostly from historical sources, but most of them concern leading figures of the ancient world. Closer to the problem of suicide in the everyday life of antiquity are ancient Greek medicines, who studied the phenomenon more general without references to specific incidents. Doctors did not approve in principal the suicide and dealt with it as insane behavior in the development of the mental diseases, of melancholia and mania. They considered that the discrepancy of humors in the organ of logic in the human body will cause malfunction, which will lead to the absurdity and consequently to suicide, either due to excessive concentration of black bile in melancholia or due to yellow bile in mania. They believed that greater risk to commit suicide had women, young people and the elderly. As therapy they used the drugs of their time with the intention to induce calm and repression in the ill person, therefore they mainly used mandragora. In general, we would say
Dance in Ancient Greek Culture
Spalva, Rita
2015-01-01
The greatness and harmony of ancient Greece has had an impact upon the development of the Western European culture to this day. The ancient Greek culture has influenced contemporary literature genres and systems of philosophy, principles of architecture, sculpture and drama and has formed basis for such sciences as astronomy and mathematics. The art of ancient Greece with its penchant for beauty and clarity has been the example of the humanity’s search for an aesthetic ideal. Despite only bei...
Probability and Bayesian statistics
1987-01-01
This book contains selected and refereed contributions to the "Inter national Symposium on Probability and Bayesian Statistics" which was orga nized to celebrate the 80th birthday of Professor Bruno de Finetti at his birthplace Innsbruck in Austria. Since Professor de Finetti died in 1985 the symposium was dedicated to the memory of Bruno de Finetti and took place at Igls near Innsbruck from 23 to 26 September 1986. Some of the pa pers are published especially by the relationship to Bruno de Finetti's scientific work. The evolution of stochastics shows growing importance of probability as coherent assessment of numerical values as degrees of believe in certain events. This is the basis for Bayesian inference in the sense of modern statistics. The contributions in this volume cover a broad spectrum ranging from foundations of probability across psychological aspects of formulating sub jective probability statements, abstract measure theoretical considerations, contributions to theoretical statistics an...
DEFF Research Database (Denmark)
Mørup, Morten; Schmidt, Mikkel N
2012-01-01
Many networks of scientific interest naturally decompose into clusters or communities with comparatively fewer external than internal links; however, current Bayesian models of network communities do not exert this intuitive notion of communities. We formulate a nonparametric Bayesian model...... consistent with ground truth, and on real networks, it outperforms existing approaches in predicting missing links. This suggests that community structure is an important structural property of networks that should be explicitly modeled....... for community detection consistent with an intuitive definition of communities and present a Markov chain Monte Carlo procedure for inferring the community structure. A Matlab toolbox with the proposed inference procedure is available for download. On synthetic and real networks, our model detects communities...
Bayesian Independent Component Analysis
DEFF Research Database (Denmark)
Winther, Ole; Petersen, Kaare Brandt
2007-01-01
In this paper we present an empirical Bayesian framework for independent component analysis. The framework provides estimates of the sources, the mixing matrix and the noise parameters, and is flexible with respect to choice of source prior and the number of sources and sensors. Inside the engine...... in a Matlab toolbox, is demonstrated for non-negative decompositions and compared with non-negative matrix factorization....
Dantzig, Tobias
2006-01-01
More than a history of mathematics, this lively book traces mathematical ideas and processes to their sources, stressing the methods used by the masters of the ancient world. Author Tobias Dantzig portrays the human story behind mathematics, showing how flashes of insight in the minds of certain gifted individuals helped mathematics take enormous forward strides. Dantzig demonstrates how the Greeks organized their precursors' melange of geometric maxims into an elegantly abstract deductive system. He also explains the ways in which some of the famous mathematical brainteasers of antiquity led
Sparavigna, Amelia Carolina
2011-01-01
It is commonly believed that the ancient Romans were the first to create and use concrete. This is not true, as we can easily learn from the Latin literature itself. For sure, Romans were able to prepare high-quality hydraulic cements, comparable with the modern Portland cements. In this paper, we will see that the use of concrete is quite older, ranging back to the Homeric times. For instance, it was used for the floors of some courts and galleries of the Mycenaean palace at Tiryns
DEFF Research Database (Denmark)
Climate, and human responses to it, have a strongly interconnected relationship. This when climate change occurs, the result of either natural or human causes, societies should react and adapt to these. But do they? If so, what is the nature of that change, and are the responses positive...... or negative for the long-term survival of social groups? In this volume, scholars from diverse disciplines including archaeology, geology and climate sciences explore scientific and material evidence for climate changes in the past, their causes, their effects on ancient societies and how those societies...
Bayesian theory and applications
Dellaportas, Petros; Polson, Nicholas G; Stephens, David A
2013-01-01
The development of hierarchical models and Markov chain Monte Carlo (MCMC) techniques forms one of the most profound advances in Bayesian analysis since the 1970s and provides the basis for advances in virtually all areas of applied and theoretical Bayesian statistics. This volume guides the reader along a statistical journey that begins with the basic structure of Bayesian theory, and then provides details on most of the past and present advances in this field. The book has a unique format. There is an explanatory chapter devoted to each conceptual advance followed by journal-style chapters that provide applications or further advances on the concept. Thus, the volume is both a textbook and a compendium of papers covering a vast range of topics. It is appropriate for a well-informed novice interested in understanding the basic approach, methods and recent applications. Because of its advanced chapters and recent work, it is also appropriate for a more mature reader interested in recent applications and devel...
Exploring Ancient Skies A Survey of Ancient and Cultural Astronomy
Kelley, David H
2011-01-01
Exploring Ancient Skies brings together the methods of archaeology and the insights of modern astronomy to explore the science of astronomy as it was practiced in various cultures prior to the invention of the telescope. The book reviews an enormous and growing body of literature on the cultures of the ancient Mediterranean, the Far East, and the New World (particularly Mesoamerica), putting the ancient astronomical materials into their archaeological and cultural contexts. The authors begin with an overview of the field and proceed to essential aspects of naked-eye astronomy, followed by an examination of specific cultures. The book concludes by taking into account the purposes of ancient astronomy: astrology, navigation, calendar regulation, and (not least) the understanding of our place and role in the universe. Skies are recreated to display critical events as they would have appeared to ancient observers—events such as the supernova of 1054 A.D., the "lion horoscope," and the Star of Bethlehem. Explori...
Authenticity in ancient DNA studies
DEFF Research Database (Denmark)
Gilbert, M Thomas P; Willerslev, Eske
2006-01-01
Ancient DNA studies represent a powerful tool that can be used to obtain genetic insights into the past. However, despite the publication of large numbers of apparently successful ancient DNA studies, a number of problems exist with the field that are often ignored. Therefore, questions exist as ...
Tamil merchant in ancient Mesopotamia.
Directory of Open Access Journals (Sweden)
Malliya Gounder Palanichamy
Full Text Available Recent analyses of ancient Mesopotamian mitochondrial genomes have suggested a genetic link between the Indian subcontinent and Mesopotamian civilization. There is no consensus on the origin of the ancient Mesopotamians. They may be descendants of migrants, who founded regional Mesopotamian groups like that of Terqa or they may be merchants who were involved in trans Mesopotamia trade. To identify the Indian source population showing linkage to the ancient Mesopotamians, we screened a total of 15,751 mitochondrial DNAs (11,432 from the literature and 4,319 from this study representing all major populations of India. Our results although suggest that south India (Tamil Nadu and northeast India served as the source of the ancient Mesopotamian mtDNA gene pool, mtDNA of these ancient Mesopotamians probably contributed by Tamil merchants who were involved in the Indo-Roman trade.
Tamil merchant in ancient Mesopotamia.
Palanichamy, Malliya Gounder; Mitra, Bikash; Debnath, Monojit; Agrawal, Suraksha; Chaudhuri, Tapas Kumar; Zhang, Ya-Ping
2014-01-01
Recent analyses of ancient Mesopotamian mitochondrial genomes have suggested a genetic link between the Indian subcontinent and Mesopotamian civilization. There is no consensus on the origin of the ancient Mesopotamians. They may be descendants of migrants, who founded regional Mesopotamian groups like that of Terqa or they may be merchants who were involved in trans Mesopotamia trade. To identify the Indian source population showing linkage to the ancient Mesopotamians, we screened a total of 15,751 mitochondrial DNAs (11,432 from the literature and 4,319 from this study) representing all major populations of India. Our results although suggest that south India (Tamil Nadu) and northeast India served as the source of the ancient Mesopotamian mtDNA gene pool, mtDNA of these ancient Mesopotamians probably contributed by Tamil merchants who were involved in the Indo-Roman trade.
Mapping the Ancient Maya Landscape from Space
Sever, Tom
2003-01-01
This project uses new satellite and airborne imagery in combination with remote sensing, GIS, and GPS technology to understand the dynamics of how the Maya successfully interacted with their karst topographic landscape for several centuries in the northern Peten region of Guatemala. The ancient Maya attained one of the greatest population densities in human history in the tropical forest of the Peten, Guatemala, and it was in this region that the Maya civilization began, flourished, and abruptly disappeared for unknown reasons around AD 800. How the Maya were able to successfully manage water and feed this dense population is not known at this time. However, a recent NASA-funded project was the first to investigate large seasonal swamps (bajos) that make up 40 percent of the landscape. Through the use of remote sensing, ancient Maya features such as cities, roadways, canals and water reservoirs have been detected and verified through ground reconnaissance. The results of this research cast new light on the adaptation of the ancient Maya to their environment. Micro-environmental variation within the wetlands was elucidated and the different vegetational associations identified in the satellite imagery. More than 70 new archeological sites within and at the edges of the bajo were mapped and tested. Modification of the landscape by the Maya in the form of dams and reservoirs in the Holmul River and its tributaries and possible drainage canals in bajos was demonstrated. The recent acquisition of one-meter IKONOS imagery and high resolution STAR-3i radar imagery (2.5m backscatter/ 10m DEM), opens new possibilities for understanding how a civilization was able to survive for centuries upon a karst topographic landscape and their human-induced effects upon the local climate. This understanding is critical for the current population that is presently experiencing rapid population growth and destroying the landscape through non-traditional farming and grazing techniques
Characterization of Ancient Tripitaka
Gong, Y. X.; Geng, L.; Gong, D. C.
2015-08-01
Tripitaka is the world's most comprehensive version of Buddhist sutra. There are limited numbers of Tripitaka currently preserved, most of them present various patterns of degradation. As little is known about the materials and crafts used in Tripitaka, it appeared necessary to identify them, and to further define adapted conservation treatment. In this work, a study concerning the paper source and dyestuff of the Tripitaka from approximate 16th century was carried out using fiber analysis and thin-layer chromatography (TLC). The results proved that the papers were mainly made from hemp or bark of mulberry tree, and indigo was used for colorizing the paper. At the end, we provide with suggestions for protecting and restoring the ancient Tripitaka.
DEFF Research Database (Denmark)
Hartelius, Karsten; Carstensen, Jens Michael
2003-01-01
A method for locating distorted grid structures in images is presented. The method is based on the theories of template matching and Bayesian image restoration. The grid is modeled as a deformable template. Prior knowledge of the grid is described through a Markov random field (MRF) model which...... nodes and the arc prior models variations in row and column spacing across the grid. Grid matching is done by placing an initial rough grid over the image and applying an ensemble annealing scheme to maximize the posterior distribution of the grid. The method can be applied to noisy images with missing...
Congdon, Peter
2014-01-01
This book provides an accessible approach to Bayesian computing and data analysis, with an emphasis on the interpretation of real data sets. Following in the tradition of the successful first edition, this book aims to make a wide range of statistical modeling applications accessible using tested code that can be readily adapted to the reader's own applications. The second edition has been thoroughly reworked and updated to take account of advances in the field. A new set of worked examples is included. The novel aspect of the first edition was the coverage of statistical modeling using WinBU
Bayesian nonparametric data analysis
Müller, Peter; Jara, Alejandro; Hanson, Tim
2015-01-01
This book reviews nonparametric Bayesian methods and models that have proven useful in the context of data analysis. Rather than providing an encyclopedic review of probability models, the book’s structure follows a data analysis perspective. As such, the chapters are organized by traditional data analysis problems. In selecting specific nonparametric models, simpler and more traditional models are favored over specialized ones. The discussed methods are illustrated with a wealth of examples, including applications ranging from stylized examples to case studies from recent literature. The book also includes an extensive discussion of computational methods and details on their implementation. R code for many examples is included in on-line software pages.
Classification using Bayesian neural nets
J.C. Bioch (Cor); O. van der Meer; R. Potharst (Rob)
1995-01-01
textabstractRecently, Bayesian methods have been proposed for neural networks to solve regression and classification problems. These methods claim to overcome some difficulties encountered in the standard approach such as overfitting. However, an implementation of the full Bayesian approach to neura
Bayesian Intersubjectivity and Quantum Theory
Pérez-Suárez, Marcos; Santos, David J.
2005-02-01
Two of the major approaches to probability, namely, frequentism and (subjectivistic) Bayesian theory, are discussed, together with the replacement of frequentist objectivity for Bayesian intersubjectivity. This discussion is then expanded to Quantum Theory, as quantum states and operations can be seen as structural elements of a subjective nature.
Bayesian Approach for Inconsistent Information.
Stein, M; Beer, M; Kreinovich, V
2013-10-01
In engineering situations, we usually have a large amount of prior knowledge that needs to be taken into account when processing data. Traditionally, the Bayesian approach is used to process data in the presence of prior knowledge. Sometimes, when we apply the traditional Bayesian techniques to engineering data, we get inconsistencies between the data and prior knowledge. These inconsistencies are usually caused by the fact that in the traditional approach, we assume that we know the exact sample values, that the prior distribution is exactly known, etc. In reality, the data is imprecise due to measurement errors, the prior knowledge is only approximately known, etc. So, a natural way to deal with the seemingly inconsistent information is to take this imprecision into account in the Bayesian approach - e.g., by using fuzzy techniques. In this paper, we describe several possible scenarios for fuzzifying the Bayesian approach. Particular attention is paid to the interaction between the estimated imprecise parameters. In this paper, to implement the corresponding fuzzy versions of the Bayesian formulas, we use straightforward computations of the related expression - which makes our computations reasonably time-consuming. Computations in the traditional (non-fuzzy) Bayesian approach are much faster - because they use algorithmically efficient reformulations of the Bayesian formulas. We expect that similar reformulations of the fuzzy Bayesian formulas will also drastically decrease the computation time and thus, enhance the practical use of the proposed methods.
Inference in hybrid Bayesian networks
DEFF Research Database (Denmark)
Lanseth, Helge; Nielsen, Thomas Dyhre; Rumí, Rafael
2009-01-01
Since the 1980s, Bayesian Networks (BNs) have become increasingly popular for building statistical models of complex systems. This is particularly true for boolean systems, where BNs often prove to be a more efficient modelling framework than traditional reliability-techniques (like fault trees...... decade's research on inference in hybrid Bayesian networks. The discussions are linked to an example model for estimating human reliability....
Bayesian Inference on Gravitational Waves
Directory of Open Access Journals (Sweden)
Asad Ali
2015-12-01
Full Text Available The Bayesian approach is increasingly becoming popular among the astrophysics data analysis communities. However, the Pakistan statistics communities are unaware of this fertile interaction between the two disciplines. Bayesian methods have been in use to address astronomical problems since the very birth of the Bayes probability in eighteenth century. Today the Bayesian methods for the detection and parameter estimation of gravitational waves have solid theoretical grounds with a strong promise for the realistic applications. This article aims to introduce the Pakistan statistics communities to the applications of Bayesian Monte Carlo methods in the analysis of gravitational wave data with an overview of the Bayesian signal detection and estimation methods and demonstration by a couple of simplified examples.
Approximate Bayesian computation.
Directory of Open Access Journals (Sweden)
Mikael Sunnåker
Full Text Available Approximate Bayesian computation (ABC constitutes a class of computational methods rooted in Bayesian statistics. In all model-based statistical inference, the likelihood function is of central importance, since it expresses the probability of the observed data under a particular statistical model, and thus quantifies the support data lend to particular values of parameters and to choices among different models. For simple models, an analytical formula for the likelihood function can typically be derived. However, for more complex models, an analytical formula might be elusive or the likelihood function might be computationally very costly to evaluate. ABC methods bypass the evaluation of the likelihood function. In this way, ABC methods widen the realm of models for which statistical inference can be considered. ABC methods are mathematically well-founded, but they inevitably make assumptions and approximations whose impact needs to be carefully assessed. Furthermore, the wider application domain of ABC exacerbates the challenges of parameter estimation and model selection. ABC has rapidly gained popularity over the last years and in particular for the analysis of complex problems arising in biological sciences (e.g., in population genetics, ecology, epidemiology, and systems biology.
Borsboom, D.; Haig, B.D.
2013-01-01
Unlike most other statistical frameworks, Bayesian statistical inference is wedded to a particular approach in the philosophy of science (see Howson & Urbach, 2006); this approach is called Bayesianism. Rather than being concerned with model fitting, this position in the philosophy of science primar
Implementing Bayesian Vector Autoregressions Implementing Bayesian Vector Autoregressions
Directory of Open Access Journals (Sweden)
Richard M. Todd
1988-03-01
Full Text Available Implementing Bayesian Vector Autoregressions This paper discusses how the Bayesian approach can be used to construct a type of multivariate forecasting model known as a Bayesian vector autoregression (BVAR. In doing so, we mainly explain Doan, Littermann, and Sims (1984 propositions on how to estimate a BVAR based on a certain family of prior probability distributions. indexed by a fairly small set of hyperparameters. There is also a discussion on how to specify a BVAR and set up a BVAR database. A 4-variable model is used to iliustrate the BVAR approach.
Effects of tree species composition on within-forest distribution of understorey species
Oijen, van D.; Feijen, M.; Hommel, P.W.F.M.; Ouden, den J.; Waal, de R.W.
2005-01-01
Question: Do tree species, with different litter qualities, affect the within-forest distribution of forest understorey species on intermediate to base-rich soils? Since habitat loss and fragmentation have caused ancient forest species to decline, those species are the main focus of this study. Loca
Aylesworth, Grant R.
Although there is little doubt that the ancient Maya of Mesoamerica laid their cities out based, in part, on astronomical considerations, the proliferation of "cosmograms" in contemporary scholarly discourse has complicated matters for the acceptance of rigorous archaeoastronomical research.
Astronomical Significance of Ancient Monuments
Simonia, I.
2011-06-01
Astronomical significance of Gokhnari megalithic monument (eastern Georgia) is considered. Possible connection of Amirani ancient legend with Gokhnari monument is discussed. Concepts of starry practicality and solar stations are proposed.
Hunting for Ancient Rocky Shores.
Johnson, Markes E.
1988-01-01
Promotes the study of ancient rocky shores by showing how they can be recognized and what directions future research may follow. A bibliography of previous research articles, arranged by geologic period, is provided in the appendix to this paper. (CW)
Book review: Bayesian analysis for population ecology
Link, William A.
2011-01-01
Brian Dennis described the field of ecology as “fertile, uncolonized ground for Bayesian ideas.” He continued: “The Bayesian propagule has arrived at the shore. Ecologists need to think long and hard about the consequences of a Bayesian ecology. The Bayesian outlook is a successful competitor, but is it a weed? I think so.” (Dennis 2004)
Ortega, Pedro A
2011-01-01
Discovering causal relationships is a hard task, often hindered by the need for intervention, and often requiring large amounts of data to resolve statistical uncertainty. However, humans quickly arrive at useful causal relationships. One possible reason is that humans use strong prior knowledge; and rather than encoding hard causal relationships, they encode beliefs over causal structures, allowing for sound generalization from the observations they obtain from directly acting in the world. In this work we propose a Bayesian approach to causal induction which allows modeling beliefs over multiple causal hypotheses and predicting the behavior of the world under causal interventions. We then illustrate how this method extracts causal information from data containing interventions and observations.
Blundell, Charles; Heller, Katherine A
2012-01-01
Hierarchical structure is ubiquitous in data across many domains. There are many hier- archical clustering methods, frequently used by domain experts, which strive to discover this structure. However, most of these meth- ods limit discoverable hierarchies to those with binary branching structure. This lim- itation, while computationally convenient, is often undesirable. In this paper we ex- plore a Bayesian hierarchical clustering algo- rithm that can produce trees with arbitrary branching structure at each node, known as rose trees. We interpret these trees as mixtures over partitions of a data set, and use a computationally efficient, greedy ag- glomerative algorithm to find the rose trees which have high marginal likelihood given the data. Lastly, we perform experiments which demonstrate that rose trees are better models of data than the typical binary trees returned by other hierarchical clustering algorithms.
Bayesian inference in geomagnetism
Backus, George E.
1988-01-01
The inverse problem in empirical geomagnetic modeling is investigated, with critical examination of recently published studies. Particular attention is given to the use of Bayesian inference (BI) to select the damping parameter lambda in the uniqueness portion of the inverse problem. The mathematical bases of BI and stochastic inversion are explored, with consideration of bound-softening problems and resolution in linear Gaussian BI. The problem of estimating the radial magnetic field B(r) at the earth core-mantle boundary from surface and satellite measurements is then analyzed in detail, with specific attention to the selection of lambda in the studies of Gubbins (1983) and Gubbins and Bloxham (1985). It is argued that the selection method is inappropriate and leads to lambda values much larger than those that would result if a reasonable bound on the heat flow at the CMB were assumed.
Forest crimes as a threat to sustainable forest management
Directory of Open Access Journals (Sweden)
S. Özden
2016-08-01
Full Text Available From ancient times to the present day, forest public relations has been an issue on the agenda. This relationship’s purpose was initially needed for shelter and nutrition; however today this process has changed with urbanization, overpopulation and understanding the new functions of forests. When land ownership became a tool of production, offenses occurred in order to convert forestlands to agricultural lands. So the vast majority of the world’s forests have been lost for this reason. Today, deforestation is occurring in tropical countries that are expecting to gain agricultural area. The purpose of this study is to investigate the relationship between urbanization and the qualitative and quantitative characteristics of forest crimes, which are a major obstacle for sustainable forestry. Although forests cover about 27 % of Turkey’s territory, the forests are losing viability; the status of wood raw material per unit area and the total area of the country in the ratio of productive forests are becoming critical in Turkey. Turkey’s rugged terrain and factors such as human interventions, fires, deforestation for agriculture, illegal cuttings, or improper grazing reduce existing forests or cause deterioration of their structure. In the past, deforestation, as a result of human interventions in Turkey, was done by forest villagers who live in rural areas. The forest crimes depend on various socio-economic reasons and have many adverse effects on the sustainability of forest and forest existence. In developed countries, illegal interventions such as opening, grazing, cutting, occupation, use, settlement, or hunting crimes have been largely eliminated because of the absence of cadastral problems, the existence of more responsive people to protect the environment and forests and a rural population, which has a higher standard of living. In the last 20 years, there has been both a dramatic decrease in the population living in rural areas and a
Current trends in Bayesian methodology with applications
Upadhyay, Satyanshu K; Dey, Dipak K; Loganathan, Appaia
2015-01-01
Collecting Bayesian material scattered throughout the literature, Current Trends in Bayesian Methodology with Applications examines the latest methodological and applied aspects of Bayesian statistics. The book covers biostatistics, econometrics, reliability and risk analysis, spatial statistics, image analysis, shape analysis, Bayesian computation, clustering, uncertainty assessment, high-energy astrophysics, neural networking, fuzzy information, objective Bayesian methodologies, empirical Bayes methods, small area estimation, and many more topics.Each chapter is self-contained and focuses on
DEFF Research Database (Denmark)
Balooni, Kulbhushan; Lund, Jens Friis
2014-01-01
One of the proposed strategies for implementation of reducing emissions from deforestation and forest degradation plus (REDD+) is to incentivize conservation of forests managed by communities under decentralized forest management. Yet, we argue that this is a challenging road to REDD+ because......+ transactions costs. Third, beyond the “conservation islands” represented by forests under decentralized management, processes of deforestation and forest degradation continue. Given these challenges, we argue that REDD+ efforts through decentralized forestry should be redirected from incentivizing further...
Irregular-Time Bayesian Networks
Ramati, Michael
2012-01-01
In many fields observations are performed irregularly along time, due to either measurement limitations or lack of a constant immanent rate. While discrete-time Markov models (as Dynamic Bayesian Networks) introduce either inefficient computation or an information loss to reasoning about such processes, continuous-time Markov models assume either a discrete state space (as Continuous-Time Bayesian Networks), or a flat continuous state space (as stochastic dif- ferential equations). To address these problems, we present a new modeling class called Irregular-Time Bayesian Networks (ITBNs), generalizing Dynamic Bayesian Networks, allowing substantially more compact representations, and increasing the expressivity of the temporal dynamics. In addition, a globally optimal solution is guaranteed when learning temporal systems, provided that they are fully observed at the same irregularly spaced time-points, and a semiparametric subclass of ITBNs is introduced to allow further adaptation to the irregular nature of t...
Did the ancient Egyptians migrate to ancient Nigeria?
Directory of Open Access Journals (Sweden)
Jock M. Agai
2014-01-01
Full Text Available Literatures concerning the history of West African peoples published from 1900 to 1970 debate�the possible migrations of the Egyptians into West Africa. Writers like Samuel Johnson and�Lucas Olumide believe that the ancient Egyptians penetrated through ancient Nigeria but Leo�Frobenius and Geoffrey Parrinder frowned at this opinion. Using the works of these early�20th century writers of West African history together with a Yoruba legend which teaches�about the origin of their earliest ancestor(s, this researcher investigates the theories that the�ancient Egyptians had contact with the ancient Nigerians and particularly with the Yorubas.Intradisciplinary and/or interdisciplinary implications: There is an existing ideology�amongst the Yorubas and other writers of Yoruba history that the original ancestors of�the Yorubas originated in ancient Egypt hence there was migration between Egypt and�Yorubaland. This researcher contends that even if there was migration between Egypt and�Nigeria, such migration did not take place during the predynastic and dynastic period as�speculated by some scholars. The subject is open for further research.
Carbon Budget of Russian Forests
Directory of Open Access Journals (Sweden)
A. Z. Shvidenko
2014-02-01
Full Text Available Net Ecosystem Carbon Balance (NECB of Russian forests for 2007–2009 is presented based on consistent application of applied systems analysis and modern information technologies. Use of landscape-ecosystem approach resulted in the NECB at 546±120 Tg C year–1, or 66±15 g C m–2 year–1. There is a substantial difference between the NECB of European and Asian parts, as well as the clear zonal gradients within these geographical regions. While the total carbon sink is high, large forest areas, particularly on permafrost, serve as a carbon source. The ratio between net primary production and soil heterotrophic respiration, together with natural and human-induced disturbances are major drivers of the magnitude and spatial distribution of the NECB of forest ecosystems. Using the Bayesian approach, mutual constraints of results that are obtained by independent methods enable to decrease uncertainties of the final result.
Bayesian Inference: with ecological applications
Link, William A.; Barker, Richard J.
2010-01-01
This text provides a mathematically rigorous yet accessible and engaging introduction to Bayesian inference with relevant examples that will be of interest to biologists working in the fields of ecology, wildlife management and environmental studies as well as students in advanced undergraduate statistics.. This text opens the door to Bayesian inference, taking advantage of modern computational efficiencies and easily accessible software to evaluate complex hierarchical models.
Bayesian Methods for Statistical Analysis
Puza, Borek
2015-01-01
Bayesian methods for statistical analysis is a book on statistical methods for analysing a wide variety of data. The book consists of 12 chapters, starting with basic concepts and covering numerous topics, including Bayesian estimation, decision theory, prediction, hypothesis testing, hierarchical models, Markov chain Monte Carlo methods, finite population inference, biased sampling and nonignorable nonresponse. The book contains many exercises, all with worked solutions, including complete c...
Bayesian Networks and Influence Diagrams
DEFF Research Database (Denmark)
Kjærulff, Uffe Bro; Madsen, Anders Læsø
Probabilistic networks, also known as Bayesian networks and influence diagrams, have become one of the most promising technologies in the area of applied artificial intelligence, offering intuitive, efficient, and reliable methods for diagnosis, prediction, decision making, classification......, troubleshooting, and data mining under uncertainty. Bayesian Networks and Influence Diagrams: A Guide to Construction and Analysis provides a comprehensive guide for practitioners who wish to understand, construct, and analyze intelligent systems for decision support based on probabilistic networks. Intended...
Dynamic Batch Bayesian Optimization
Azimi, Javad; Fern, Xiaoli
2011-01-01
Bayesian optimization (BO) algorithms try to optimize an unknown function that is expensive to evaluate using minimum number of evaluations/experiments. Most of the proposed algorithms in BO are sequential, where only one experiment is selected at each iteration. This method can be time inefficient when each experiment takes a long time and more than one experiment can be ran concurrently. On the other hand, requesting a fix-sized batch of experiments at each iteration causes performance inefficiency in BO compared to the sequential policies. In this paper, we present an algorithm that asks a batch of experiments at each time step t where the batch size p_t is dynamically determined in each step. Our algorithm is based on the observation that the sequence of experiments selected by the sequential policy can sometimes be almost independent from each other. Our algorithm identifies such scenarios and request those experiments at the same time without degrading the performance. We evaluate our proposed method us...
Forest Histories & Forest Futures
Whitlock, Cathy
2009-01-01
The climate changes projected for the future will have significant consequences for forest ecosystems and our ability to manage them. It is reasonable to ask: Are there historical precedents that help us understand what might happen in the future or are historical perspectives becoming irrelevant? What synergisms and feedbacks might be expected between rapidly changing climate and land–use in different settings, especially at the wildland–urban interface? What lessons from the past might help...
Mapping The Ancient Maya Landscape From Space
Sever, Tom; Arnold, James E. (Technical Monitor)
2002-01-01
The Peten region of northern Guatemala is one of the last places on earth where major archeological sites remain to be discovered. It was in this region that the Maya civilization began, flourished, and abruptly disappeared. Remote sensing technology is helping to locate and map ancient Maya sites that are threatened today by accelerating deforestation and looting. Thematic Mapper and IKONOS satellite and airborne Star3-I radar data, combined with Global Positioning System (GPS) technology, are successfully detecting ancient Maya features such as cities, roadways, canals, and water reservoirs. Satellite imagery is also being used to map the bajos, which are seasonally flooded swamps that cover over 40% of the land surface. The use of bajos for farming has been a source of debate within the professional community for many years. But the recent detection and verification of cultural features within the bajo system by our research team are providing conclusive evidence that the ancient Maya had adapted well to wetland environments from the earliest times and utilized them until the time of the Maya collapse. The use of the bajos for farming is also an important resource for the future of the current inhabitants who are experiencing rapid population growth. Remote sensing imagery is also demonstrating that in the Preclassic period (600 BC- AD 250), the Maya had already achieved a high organizational level as evidenced by the construction of massive temples and an elaborate inter-connecting roadway system. Although they experienced several setbacks such as droughts and hurricanes, the Maya nevertheless managed the delicate forest ecosystem successfully for several centuries. However, around AD 800, something happened to the Maya to cause their rapid decline and eventual disappearance from the region. The evidence indicates that at this time there was increased climatic dryness, extensive deforestation, overpopulation, and widespread warfare. This raises a question that
Neonatal medicine in ancient art.
Yurdakök, Murat
2010-01-01
There are a limited number of artistic objects from ancient times with particular importance in neonatal medicine. The best examples are figurines from ancient Egypt of Isis nursing Horus, showing the importance of breastfeeding. The earliest images of the human fetus were made by the Olmecs in Mexico around 1200- 400 BCE. One of the earliest representations of congenital anomalies is a figurine of diencephalic twins thought to be the goddess of Anatolia, dated to around 6500 BCE. In addition to these figurines, three sets of twins in the ancient world have medical importance, and Renaissance artists often used them as a subject for their paintings: "direct suckling animals" (Romulus and Remus), "heteropaternal superfecundation" (mother: Leda, fathers: Zeus, the king of the Olympian gods, and Leda's husband, Tyndareus), and "twin-to-twin transfusion" in monozygotic twins (Jacob and Esau).
Ancient "Observatories" - A Relevant Concept?
Belmonte, Juan Antonio
It is quite common, when reading popular books on astronomy, to see a place referred to as "the oldest observatory in the world". In addition, numerous books on archaeoastronomy, of various levels of quality, frequently refer to the existence of "prehistoric" or "ancient" observatories when describing or citing monuments that were certainly not built with the primary purpose of observing the skies. Internet sources are also guilty of this practice. In this chapter, the different meanings of the word observatory will be analyzed, looking at how their significances can be easily confused or even interchanged. The proclaimed "ancient observatories" are a typical result of this situation. Finally, the relevance of the concept of the ancient observatory will be evaluated.
Skeletal dysplasia in ancient Egypt.
Kozma, Chahira
2008-12-01
The ancient Egyptian civilization lasted for over 3000 years and ended in 30 BCE. Many aspects of ancient Egyptian culture, including the existence of skeletal dysplasias, and in particular achondroplasia, are well known through the monuments and records that survived until modern times. The hot and dry climate in Egypt allowed for the preservation of bodies and skeletal anomalies. The oldest dwarf skeleton, the Badarian skeleton (4500 BCE), possibly represents an epiphyseal disorder. Among the remains of dwarfs with achondroplasia from ancient Egypt (2686-2190 BCE), exists a skeleton of a pregnant female, believed to have died during delivery with a baby's remains in situ. British museums have partial skeletons of dwarfs with achondroplasia, humeri probably affected with mucopolysaccharidoses, and a skeleton of a child with osteogenesis imperfecta. Skeletal dysplasia is also found among royal remains. The mummy of the pharaoh Siptah (1342-1197 BCE) shows a deformity of the left leg and foot. A mummified fetus, believed to be the daughter of king Tutankhamun, has scoliosis, spina bifida, and Sprengel deformity. In 2006 I reviewed the previously existing knowledge of dwarfism in ancient Egypt. The purpose of this second historical review is to add to that knowledge with an expanded contribution. The artistic documentation of people with skeletal dysplasia from ancient Egypt is plentiful including hundreds of amulets, statues, and drawing on tomb and temple walls. Examination of artistic reliefs provides a glance of the role of people with skeletal dysplasia and the societal attitudes toward them. Both artistic evidence and moral teachings in ancient Egypt reveal wide integration of individuals with disabilities into the society.
Night blindness and ancient remedy
Directory of Open Access Journals (Sweden)
H.A. Hajar Al Binali
2014-01-01
Full Text Available The aim of this article is to briefly review the history of night blindness and its treatment from ancient times until the present. The old Egyptians, the Babylonians, the Greeks and the Arabs used animal liver for treatment and successfully cured the disease. The author had the opportunity to observe the application of the old remedy to a patient. Now we know what the ancients did not know, that night blindness is caused by Vitamin A deficiency and the animal liver is the store house for Vitamin A.
Directory of Open Access Journals (Sweden)
Louise Cilliers
2008-09-01
Full Text Available In spite of an array of effective antibiotics, tuberculosis is still very common in developing countries where overcrowding, malnutrition and poor hygienic conditions prevail. Over the past 30 years associated HIV infection has worsened the situation by increasing the infection rate and mortality of tuberculosis. Of those diseases caused by a single organism only HIV causes more deaths internationally than tuberculosis. The tubercle bacillus probably first infected man in Neolithic times, and then via infected cattle, but the causative Mycobacteriacea have been in existence for 300 million years. Droplet infection is the most common way of acquiring tuberculosis, although ingestion (e.g. of infected cows’ milk may occur. Tuberculosis probably originated in Africa. The earliest path gnomonic evidence of human tuberculosis in man was found in osteo-archaeological findings of bone tuberculosis (Pott’s disease of the spine in the skeleton of anEgyptian priest from the 21st Dynasty (approximately 1 000 BC. Suggestive but not conclusiveevidence of tuberculotic lesions had been found in even earlier skeletons from Egypt and Europe. Medical hieroglyphics from ancient Egypt are silent on the disease, which could be tuberculosis,as do early Indian and Chinese writings. The Old Testament refers to the disease schachapeth, translated as phthisis in the Greek Septuagint. Although the Bible is not specific about this condition, tuberculosis is still called schachapeth in modern Hebrew. In pre-Hippocratic Greece Homer did not mention phthisis, a word meaning non-specific wasting of the body. However. Alexander of Tralles (6th century BC seemed to narrow the concept down to a specific disease, and in the Hippocratic Corpus (5th-4th centuries BC phthisis can be recognised as tuberculosis. It was predominantly a respiratory disease commonly seen and considered to be caused by an imbalance of bodily humours. It was commonest in autumn, winter and spring
Energy Technology Data Exchange (ETDEWEB)
None
2016-06-01
Forest biomass is an abundant biomass feedstock that complements the conventional forest use of wood for paper and wood materials. It may be utilized for bioenergy production, such as heat and electricity, as well as for biofuels and a variety of bioproducts, such as industrial chemicals, textiles, and other renewable materials. The resources within the 2016 Billion-Ton Report include primary forest resources, which are taken directly from timberland-only forests, removed from the land, and taken to the roadside.
Bayesian seismic AVO inversion
Energy Technology Data Exchange (ETDEWEB)
Buland, Arild
2002-07-01
A new linearized AVO inversion technique is developed in a Bayesian framework. The objective is to obtain posterior distributions for P-wave velocity, S-wave velocity and density. Distributions for other elastic parameters can also be assessed, for example acoustic impedance, shear impedance and P-wave to S-wave velocity ratio. The inversion algorithm is based on the convolutional model and a linearized weak contrast approximation of the Zoeppritz equation. The solution is represented by a Gaussian posterior distribution with explicit expressions for the posterior expectation and covariance, hence exact prediction intervals for the inverted parameters can be computed under the specified model. The explicit analytical form of the posterior distribution provides a computationally fast inversion method. Tests on synthetic data show that all inverted parameters were almost perfectly retrieved when the noise approached zero. With realistic noise levels, acoustic impedance was the best determined parameter, while the inversion provided practically no information about the density. The inversion algorithm has also been tested on a real 3-D dataset from the Sleipner Field. The results show good agreement with well logs but the uncertainty is high. The stochastic model includes uncertainties of both the elastic parameters, the wavelet and the seismic and well log data. The posterior distribution is explored by Markov chain Monte Carlo simulation using the Gibbs sampler algorithm. The inversion algorithm has been tested on a seismic line from the Heidrun Field with two wells located on the line. The uncertainty of the estimated wavelet is low. In the Heidrun examples the effect of including uncertainty of the wavelet and the noise level was marginal with respect to the AVO inversion results. We have developed a 3-D linearized AVO inversion method with spatially coupled model parameters where the objective is to obtain posterior distributions for P-wave velocity, S
Bayesian microsaccade detection
Mihali, Andra; van Opheusden, Bas; Ma, Wei Ji
2017-01-01
Microsaccades are high-velocity fixational eye movements, with special roles in perception and cognition. The default microsaccade detection method is to determine when the smoothed eye velocity exceeds a threshold. We have developed a new method, Bayesian microsaccade detection (BMD), which performs inference based on a simple statistical model of eye positions. In this model, a hidden state variable changes between drift and microsaccade states at random times. The eye position is a biased random walk with different velocity distributions for each state. BMD generates samples from the posterior probability distribution over the eye state time series given the eye position time series. Applied to simulated data, BMD recovers the “true” microsaccades with fewer errors than alternative algorithms, especially at high noise. Applied to EyeLink eye tracker data, BMD detects almost all the microsaccades detected by the default method, but also apparent microsaccades embedded in high noise—although these can also be interpreted as false positives. Next we apply the algorithms to data collected with a Dual Purkinje Image eye tracker, whose higher precision justifies defining the inferred microsaccades as ground truth. When we add artificial measurement noise, the inferences of all algorithms degrade; however, at noise levels comparable to EyeLink data, BMD recovers the “true” microsaccades with 54% fewer errors than the default algorithm. Though unsuitable for online detection, BMD has other advantages: It returns probabilities rather than binary judgments, and it can be straightforwardly adapted as the generative model is refined. We make our algorithm available as a software package. PMID:28114483
Maximum margin Bayesian network classifiers.
Pernkopf, Franz; Wohlmayr, Michael; Tschiatschek, Sebastian
2012-03-01
We present a maximum margin parameter learning algorithm for Bayesian network classifiers using a conjugate gradient (CG) method for optimization. In contrast to previous approaches, we maintain the normalization constraints on the parameters of the Bayesian network during optimization, i.e., the probabilistic interpretation of the model is not lost. This enables us to handle missing features in discriminatively optimized Bayesian networks. In experiments, we compare the classification performance of maximum margin parameter learning to conditional likelihood and maximum likelihood learning approaches. Discriminative parameter learning significantly outperforms generative maximum likelihood estimation for naive Bayes and tree augmented naive Bayes structures on all considered data sets. Furthermore, maximizing the margin dominates the conditional likelihood approach in terms of classification performance in most cases. We provide results for a recently proposed maximum margin optimization approach based on convex relaxation. While the classification results are highly similar, our CG-based optimization is computationally up to orders of magnitude faster. Margin-optimized Bayesian network classifiers achieve classification performance comparable to support vector machines (SVMs) using fewer parameters. Moreover, we show that unanticipated missing feature values during classification can be easily processed by discriminatively optimized Bayesian network classifiers, a case where discriminative classifiers usually require mechanisms to complete unknown feature values in the data first.
Phylogenetic estimation of timescales using ancient DNA
DEFF Research Database (Denmark)
Molak, Martyna; Lorenzen, Eline; Shapiro, Beth;
2013-01-01
In recent years, ancient DNA has increasingly been used for estimating molecular timescales, particularly in studies of substitution rates and demographic histories. Molecular clocks can be calibrated using temporal information from ancient DNA sequences. This information comes from the ages...
Chen, Han Y H; Luo, Yong
2015-10-01
Biomass change of the world's forests is critical to the global carbon cycle. Despite storing nearly half of global forest carbon, the boreal biome of diverse forest types and ages is a poorly understood component of the carbon cycle. Using data from 871 permanent plots in the western boreal forest of Canada, we examined net annual aboveground biomass change (ΔAGB) of four major forest types between 1958 and 2011. We found that ΔAGB was higher for deciduous broadleaf (DEC) (1.44 Mg ha(-1) year(-1) , 95% Bayesian confidence interval (CI), 1.22-1.68) and early-successional coniferous forests (ESC) (1.42, CI, 1.30-1.56) than mixed forests (MIX) (0.80, CI, 0.50-1.11) and late-successional coniferous (LSC) forests (0.62, CI, 0.39-0.88). ΔAGB declined with forest age as well as calendar year. After accounting for the effects of forest age, ΔAGB declined by 0.035, 0.021, 0.032 and 0.069 Mg ha(-1) year(-1) per calendar year in DEC, ESC, MIX and LSC forests, respectively. The ΔAGB declines resulted from increased tree mortality and reduced growth in all forest types except DEC, in which a large biomass loss from mortality was accompanied with a small increase in growth. With every degree of annual temperature increase, ΔAGB decreased by 1.00, 0.20, 0.55 and 1.07 Mg ha(-1) year(-1) in DEC, ESC, MIX and LSC forests, respectively. With every cm decrease of annual climatic moisture availability, ΔAGB decreased 0.030, 0.045 and 0.17 Mg ha(-1) year(-1) in ESC, MIX and LSC forests, but changed little in DEC forests. Our results suggest that persistent warming and decreasing water availability have profound negative effects on forest biomass in the boreal forests of western Canada. Furthermore, our results indicate that forest responses to climate change are strongly dependent on forest composition with late-successional coniferous forests being most vulnerable to climate changes in terms of aboveground biomass.
The eye and its diseases in Ancient Egypt
DEFF Research Database (Denmark)
Andersen, S. Ry
1997-01-01
Ophthalmology, History of ophthalmology, eyes in the Ancient Egypt, eye disease in Ancient Egypt, porotic hyperostosis, mummification......Ophthalmology, History of ophthalmology, eyes in the Ancient Egypt, eye disease in Ancient Egypt, porotic hyperostosis, mummification...
Bayesian modeling using WinBUGS
Ntzoufras, Ioannis
2009-01-01
A hands-on introduction to the principles of Bayesian modeling using WinBUGS Bayesian Modeling Using WinBUGS provides an easily accessible introduction to the use of WinBUGS programming techniques in a variety of Bayesian modeling settings. The author provides an accessible treatment of the topic, offering readers a smooth introduction to the principles of Bayesian modeling with detailed guidance on the practical implementation of key principles. The book begins with a basic introduction to Bayesian inference and the WinBUGS software and goes on to cover key topics, including: Markov Chain Monte Carlo algorithms in Bayesian inference Generalized linear models Bayesian hierarchical models Predictive distribution and model checking Bayesian model and variable evaluation Computational notes and screen captures illustrate the use of both WinBUGS as well as R software to apply the discussed techniques. Exercises at the end of each chapter allow readers to test their understanding of the presented concepts and all ...
Hobson, Allan
2013-12-01
Revision of Freud's theory requires a new way of seeking dream meaning. With the idea of elaborative encoding, Sue Llewellyn has provided a method of dream interpretation that takes into account both modern sleep science and the ancient art of memory. Her synthesis is elegant and compelling. But is her hypothesis testable?
Zuskin, Eugenija; Lipozencić, Jasna; Pucarin-Cvetković, Jasna; Mustajbegović, Jadranka; Schachter, Neil; Mucić-Pucić, Branka; Neralić-Meniga, Inja
2008-01-01
Different aspects of medicine and/or healing in several societies are presented. In the ancient times as well as today medicine has been closely related to magic, science and religion. Various ancient societies and cultures had developed different views of medicine. It was believed that a human being has two bodies: a visible body that belongs to the earth and an invisible body of heaven. In the earliest prehistoric days, a different kind of medicine was practiced in countries such as Egypt, Greece, Rome, Mesopotamia, India, Tibet, China, and others. In those countries, "medicine people" practiced medicine from the magic to modern physical practices. Medicine was magical and mythological, and diseases were attributed mostly to the supernatural forces. The foundation of modern medicine can be traced back to ancient Greeks. Tibetan culture, for instance, even today, combines spiritual and practical medicine. Chinese medicine developed as a concept of yin and yang, acupuncture and acupressure, and it has even been used in the modern medicine. During medieval Europe, major universities and medical schools were established. In the ancient time, before hospitals had developed, patients were treated mostly in temples.
Bayesian Methods and Universal Darwinism
Campbell, John
2010-01-01
Bayesian methods since the time of Laplace have been understood by their practitioners as closely aligned to the scientific method. Indeed a recent champion of Bayesian methods, E. T. Jaynes, titled his textbook on the subject Probability Theory: the Logic of Science. Many philosophers of science including Karl Popper and Donald Campbell have interpreted the evolution of Science as a Darwinian process consisting of a 'copy with selective retention' algorithm abstracted from Darwin's theory of Natural Selection. Arguments are presented for an isomorphism between Bayesian Methods and Darwinian processes. Universal Darwinism, as the term has been developed by Richard Dawkins, Daniel Dennett and Susan Blackmore, is the collection of scientific theories which explain the creation and evolution of their subject matter as due to the operation of Darwinian processes. These subject matters span the fields of atomic physics, chemistry, biology and the social sciences. The principle of Maximum Entropy states that system...
Attention in a bayesian framework
DEFF Research Database (Denmark)
Whiteley, Louise Emma; Sahani, Maneesh
2012-01-01
The behavioral phenomena of sensory attention are thought to reflect the allocation of a limited processing resource, but there is little consensus on the nature of the resource or why it should be limited. Here we argue that a fundamental bottleneck emerges naturally within Bayesian models...... of perception, and use this observation to frame a new computational account of the need for, and action of, attention - unifying diverse attentional phenomena in a way that goes beyond previous inferential, probabilistic and Bayesian models. Attentional effects are most evident in cluttered environments......, and include both selective phenomena, where attention is invoked by cues that point to particular stimuli, and integrative phenomena, where attention is invoked dynamically by endogenous processing. However, most previous Bayesian accounts of attention have focused on describing relatively simple experimental...
Probability biases as Bayesian inference
Directory of Open Access Journals (Sweden)
Andre; C. R. Martins
2006-11-01
Full Text Available In this article, I will show how several observed biases in human probabilistic reasoning can be partially explained as good heuristics for making inferences in an environment where probabilities have uncertainties associated to them. Previous results show that the weight functions and the observed violations of coalescing and stochastic dominance can be understood from a Bayesian point of view. We will review those results and see that Bayesian methods should also be used as part of the explanation behind other known biases. That means that, although the observed errors are still errors under the be understood as adaptations to the solution of real life problems. Heuristics that allow fast evaluations and mimic a Bayesian inference would be an evolutionary advantage, since they would give us an efficient way of making decisions. %XX In that sense, it should be no surprise that humans reason with % probability as it has been observed.
A Huge Ancient Schwannoma of the Epiglottis.
Lee, Dong Hoon; Kim, Jo Heon; Yoon, Tae Mi; Lee, Joon Kyoo; Lim, Sang Chul
2016-03-01
Ancient schwannoma of the epiglottis is extremely rare. The authors report the first case of a patient with a huge ancient schwannoma of the epiglottis. Clinicians should consider the possibility that ancient schwannoma may originate in the epiglottis mimicking the other more frequently observed lesions.
Livistona palms in Australia: ancient relics or opportunistic immigrants?
Crisp, Michael D; Isagi, Yuji; Kato, Yohei; Cook, Lyn G; Bowman, David M J S
2010-02-01
Eighteen of the 34 species of the fan palm genus Livistona (Arecaceae) are restricted to Australia and southern New Guinea, east of Wallace's Line, an ancient biogeographic boundary between the former supercontinents Laurasia and Gondwana. The remaining species extend from SE Asia to Africa, west of Wallace's Line. Competing hypotheses contend that Livistona is (a) ancient, its current distribution a relict of the supercontinents, or (b) a Miocene immigrant from the north into Australia as it drifted towards Asia. We have tested these hypotheses using Bayesian and penalized likelihood molecular dating based on 4Kb of nuclear and chloroplast DNA sequences with multiple fossil calibration points. Ancestral areas and biomes were reconstructed using parsimony and maximum likelihood. We found strong support for the second hypothesis, that a single Livistona ancestor colonized Australia from the north about 10-17Ma. Spread and diversification of the genus within Australia was likely favoured by a transition from the aseasonal wet to monsoonal biome, to which it could have been preadapted by fire-tolerance.
Bayesian Missile System Reliability from Point Estimates
2014-10-28
OCT 2014 2. REPORT TYPE N/A 3. DATES COVERED - 4. TITLE AND SUBTITLE Bayesian Missile System Reliability from Point Estimates 5a. CONTRACT...Principle (MEP) to convert point estimates to probability distributions to be used as priors for Bayesian reliability analysis of missile data, and...illustrate this approach by applying the priors to a Bayesian reliability model of a missile system. 15. SUBJECT TERMS priors, Bayesian , missile
Perception, illusions and Bayesian inference.
Nour, Matthew M; Nour, Joseph M
2015-01-01
Descriptive psychopathology makes a distinction between veridical perception and illusory perception. In both cases a perception is tied to a sensory stimulus, but in illusions the perception is of a false object. This article re-examines this distinction in light of new work in theoretical and computational neurobiology, which views all perception as a form of Bayesian statistical inference that combines sensory signals with prior expectations. Bayesian perceptual inference can solve the 'inverse optics' problem of veridical perception and provides a biologically plausible account of a number of illusory phenomena, suggesting that veridical and illusory perceptions are generated by precisely the same inferential mechanisms.
Bayesian test and Kuhn's paradigm
Institute of Scientific and Technical Information of China (English)
Chen Xiaoping
2006-01-01
Kuhn's theory of paradigm reveals a pattern of scientific progress,in which normal science alternates with scientific revolution.But Kuhn underrated too much the function of scientific test in his pattern,because he focuses all his attention on the hypothetico-deductive schema instead of Bayesian schema.This paper employs Bayesian schema to re-examine Kuhn's theory of paradigm,to uncover its logical and rational components,and to illustrate the tensional structure of logic and belief,rationality and irrationality,in the process of scientific revolution.
3D Bayesian contextual classifiers
DEFF Research Database (Denmark)
Larsen, Rasmus
2000-01-01
We extend a series of multivariate Bayesian 2-D contextual classifiers to 3-D by specifying a simultaneous Gaussian distribution for the feature vectors as well as a prior distribution of the class variables of a pixel and its 6 nearest 3-D neighbours.......We extend a series of multivariate Bayesian 2-D contextual classifiers to 3-D by specifying a simultaneous Gaussian distribution for the feature vectors as well as a prior distribution of the class variables of a pixel and its 6 nearest 3-D neighbours....
A Bayesian Nonparametric Approach to Test Equating
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
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…
Bayesian networks and food security - An introduction
Stein, A.
2004-01-01
This paper gives an introduction to Bayesian networks. Networks are defined and put into a Bayesian context. Directed acyclical graphs play a crucial role here. Two simple examples from food security are addressed. Possible uses of Bayesian networks for implementation and further use in decision sup
Plug & Play object oriented Bayesian networks
DEFF Research Database (Denmark)
Bangsø, Olav; Flores, J.; Jensen, Finn Verner
2003-01-01
Object oriented Bayesian networks have proven themselves useful in recent years. The idea of applying an object oriented approach to Bayesian networks has extended their scope to larger domains that can be divided into autonomous but interrelated entities. Object oriented Bayesian networks have b...
Bayesian stable isotope mixing models
In this paper we review recent advances in Stable Isotope Mixing Models (SIMMs) and place them into an over-arching Bayesian statistical framework which allows for several useful extensions. SIMMs are used to quantify the proportional contributions of various sources to a mixtur...
Naive Bayesian for Email Filtering
Institute of Scientific and Technical Information of China (English)
无
2002-01-01
The paper presents a method of email filter based on Naive Bayesian theory that can effectively filter junk mail and illegal mail. Furthermore, the keys of implementation are discussed in detail. The filtering model is obtained from training set of email. The filtering can be done without the users specification of filtering rules.
Bayesian analysis of binary sequences
Torney, David C.
2005-03-01
This manuscript details Bayesian methodology for "learning by example", with binary n-sequences encoding the objects under consideration. Priors prove influential; conformable priors are described. Laplace approximation of Bayes integrals yields posterior likelihoods for all n-sequences. This involves the optimization of a definite function over a convex domain--efficiently effectuated by the sequential application of the quadratic program.
Bayesian NL interpretation and learning
Zeevat, H.
2011-01-01
Everyday natural language communication is normally successful, even though contemporary computational linguistics has shown that NL is characterised by very high degree of ambiguity and the results of stochastic methods are not good enough to explain the high success rate. Bayesian natural language
ANALYSIS OF BAYESIAN CLASSIFIER ACCURACY
Directory of Open Access Journals (Sweden)
Felipe Schneider Costa
2013-01-01
Full Text Available The naÃ¯ve Bayes classifier is considered one of the most effective classification algorithms today, competing with more modern and sophisticated classifiers. Despite being based on unrealistic (naÃ¯ve assumption that all variables are independent, given the output class, the classifier provides proper results. However, depending on the scenario utilized (network structure, number of samples or training cases, number of variables, the network may not provide appropriate results. This study uses a process variable selection, using the chi-squared test to verify the existence of dependence between variables in the data model in order to identify the reasons which prevent a Bayesian network to provide good performance. A detailed analysis of the data is also proposed, unlike other existing work, as well as adjustments in case of limit values between two adjacent classes. Furthermore, variable weights are used in the calculation of a posteriori probabilities, calculated with mutual information function. Tests were applied in both a naÃ¯ve Bayesian network and a hierarchical Bayesian network. After testing, a significant reduction in error rate has been observed. The naÃ¯ve Bayesian network presented a drop in error rates from twenty five percent to five percent, considering the initial results of the classification process. In the hierarchical network, there was not only a drop in fifteen percent error rate, but also the final result came to zero.
Bayesian inference for Hawkes processes
DEFF Research Database (Denmark)
Rasmussen, Jakob Gulddahl
The Hawkes process is a practically and theoretically important class of point processes, but parameter-estimation for such a process can pose various problems. In this paper we explore and compare two approaches to Bayesian inference. The first approach is based on the so-called conditional...
Bayesian Classification of Image Structures
DEFF Research Database (Denmark)
Goswami, Dibyendu; Kalkan, Sinan; Krüger, Norbert
2009-01-01
In this paper, we describe work on Bayesian classi ers for distinguishing between homogeneous structures, textures, edges and junctions. We build semi-local classiers from hand-labeled images to distinguish between these four different kinds of structures based on the concept of intrinsic dimensi...
3-D contextual Bayesian classifiers
DEFF Research Database (Denmark)
Larsen, Rasmus
In this paper we will consider extensions of a series of Bayesian 2-D contextual classification pocedures proposed by Owen (1984) Hjort & Mohn (1984) and Welch & Salter (1971) and Haslett (1985) to 3 spatial dimensions. It is evident that compared to classical pixelwise classification further...
Bayesian Networks and Influence Diagrams
DEFF Research Database (Denmark)
Kjærulff, Uffe Bro; Madsen, Anders Læsø
Bayesian Networks and Influence Diagrams: A Guide to Construction and Analysis, Second Edition, provides a comprehensive guide for practitioners who wish to understand, construct, and analyze intelligent systems for decision support based on probabilistic networks. This new edition contains six new...
Bayesian image restoration, using configurations
DEFF Research Database (Denmark)
Thorarinsdottir, Thordis
configurations are expressed in terms of the mean normal measure of the random set. These probabilities are used as prior probabilities in a Bayesian image restoration approach. Estimation of the remaining parameters in the model is outlined for salt and pepper noise. The inference in the model is discussed...
Bayesian image restoration, using configurations
DEFF Research Database (Denmark)
Thorarinsdottir, Thordis Linda
2006-01-01
configurations are expressed in terms of the mean normal measure of the random set. These probabilities are used as prior probabilities in a Bayesian image restoration approach. Estimation of the remaining parameters in the model is outlined for the salt and pepper noise. The inference in the model is discussed...
Bayesian Evidence and Model Selection
Knuth, Kevin H; Malakar, Nabin K; Mubeen, Asim M; Placek, Ben
2014-01-01
In this paper we review the concept of the Bayesian evidence and its application to model selection. The theory is presented along with a discussion of analytic, approximate and numerical techniques. Application to several practical examples within the context of signal processing are discussed.
Differentiated Bayesian Conjoint Choice Designs
Z. Sándor (Zsolt); M. Wedel (Michel)
2003-01-01
textabstractPrevious conjoint choice design construction procedures have produced a single design that is administered to all subjects. This paper proposes to construct a limited set of different designs. The designs are constructed in a Bayesian fashion, taking into account prior uncertainty about
Bayesian Alternation During Tactile Augmentation
Directory of Open Access Journals (Sweden)
Caspar Mathias Goeke
2016-10-01
Full Text Available A large number of studies suggest that the integration of multisensory signals by humans is well described by Bayesian principles. However, there are very few reports about cue combination between a native and an augmented sense. In particular, we asked the question whether adult participants are able to integrate an augmented sensory cue with existing native sensory information. Hence for the purpose of this study we build a tactile augmentation device. Consequently, we compared different hypotheses of how untrained adult participants combine information from a native and an augmented sense. In a two-interval forced choice (2 IFC task, while subjects were blindfolded and seated on a rotating platform, our sensory augmentation device translated information on whole body yaw rotation to tactile stimulation. Three conditions were realized: tactile stimulation only (augmented condition, rotation only (native condition, and both augmented and native information (bimodal condition. Participants had to choose one out of two consecutive rotations with higher angular rotation. For the analysis, we fitted the participants’ responses with a probit model and calculated the just notable difference (JND. Then we compared several models for predicting bimodal from unimodal responses. An objective Bayesian alternation model yielded a better prediction (χred2 = 1.67 than the Bayesian integration model (χred2= 4.34. Slightly higher accuracy showed a non-Bayesian winner takes all model (χred2= 1.64, which either used only native or only augmented values per subject for prediction. However the performance of the Bayesian alternation model could be substantially improved (χred2= 1.09 utilizing subjective weights obtained by a questionnaire. As a result, the subjective Bayesian alternation model predicted bimodal performance most accurately among all tested models. These results suggest that information from augmented and existing sensory modalities in
Bayesian analysis of rare events
Energy Technology Data Exchange (ETDEWEB)
Straub, Daniel, E-mail: straub@tum.de; Papaioannou, Iason; Betz, Wolfgang
2016-06-01
In many areas of engineering and science there is an interest in predicting the probability of rare events, in particular in applications related to safety and security. Increasingly, such predictions are made through computer models of physical systems in an uncertainty quantification framework. Additionally, with advances in IT, monitoring and sensor technology, an increasing amount of data on the performance of the systems is collected. This data can be used to reduce uncertainty, improve the probability estimates and consequently enhance the management of rare events and associated risks. Bayesian analysis is the ideal method to include the data into the probabilistic model. It ensures a consistent probabilistic treatment of uncertainty, which is central in the prediction of rare events, where extrapolation from the domain of observation is common. We present a framework for performing Bayesian updating of rare event probabilities, termed BUS. It is based on a reinterpretation of the classical rejection-sampling approach to Bayesian analysis, which enables the use of established methods for estimating probabilities of rare events. By drawing upon these methods, the framework makes use of their computational efficiency. These methods include the First-Order Reliability Method (FORM), tailored importance sampling (IS) methods and Subset Simulation (SuS). In this contribution, we briefly review these methods in the context of the BUS framework and investigate their applicability to Bayesian analysis of rare events in different settings. We find that, for some applications, FORM can be highly efficient and is surprisingly accurate, enabling Bayesian analysis of rare events with just a few model evaluations. In a general setting, BUS implemented through IS and SuS is more robust and flexible.
Ancient DNA from marine mammals
DEFF Research Database (Denmark)
Foote, Andrew David; Hofreiter, Michael; Morin, Philip A
2012-01-01
such as bone, tooth, baleen, skin, fur, whiskers and scrimshaw using ancient DNA (aDNA) approaches provide an oppor- tunity for investigating such changes over evolutionary and ecological timescales. Here, we review the application of aDNA techniques to the study of marine mammals. Most of the studies have...... focused on detecting changes in genetic diversity following periods of exploitation and environmental change. To date, these studies have shown that even small sample sizes can provide useful information on historical genetic diversity. Ancient DNA has also been used in investigations of changes...... in distribution and range of marine mammal species; we review these studies and discuss the limitations of such ‘presence only’ studies. Combining aDNA data with stable isotopes can provide further insights into changes in ecology and we review past studies and suggest future potential applications. We also...
Mitogenomic analyses from ancient DNA
DEFF Research Database (Denmark)
Paijmans, Johanna L.A.; Gilbert, M Thomas P; Hofreiter, Michael
2013-01-01
analyses (whether using modern or ancient DNA) were largely restricted to the analysis of short fragments of the mitochondrial genome. However, due to many technological advances during the past decade, a growing number of studies have explored the power of complete mitochondrial genome sequences...... (mitogenomes). Such studies were initially limited to analyses of extant organisms, but developments in both DNA sequencing technologies and general methodological aspects related to working with degraded DNA have resulted in complete mitogenomes becoming increasingly popular for ancient DNA studies as well....... To date, at least 124 partially or fully assembled mitogenomes from more than 20 species have been obtained, and, given the rapid progress in sequencing technology, this number is likely to dramatically increase in the future. The increased information content offered by analysing full mitogenomes has...
Molecular analysis of ancient caries.
Simón, Marc; Montiel, Rafael; Smerling, Andrea; Solórzano, Eduvigis; Díaz, Nancy; Álvarez-Sandoval, Brenda A; Jiménez-Marín, Andrea R; Malgosa, Assumpció
2014-09-01
An 84 base pair sequence of the Streptococcus mutans virulence factor, known as dextranase, has been obtained from 10 individuals from the Bronze Age to the Modern Era in Europe and from before and after the colonization in America. Modern samples show four polymorphic sites that have not been found in the ancient samples studied so far. The nucleotide and haplotype diversity of this region have increased over time, which could be reflecting the footprint of a population expansion. While this segment has apparently evolved according to neutral evolution, we have been able to detect one site that is under positive selection pressure both in present and past populations. This study is a first step to study the evolution of this microorganism, analysed using direct evidence obtained from ancient remains.
Bruel, Per V.
2002-11-01
Models were made of vases described by Vitruvius in Rome in about the year 70 A.D. and of sound vases (lydpotter) placed in Danish churches from 1100-1300 A.D. Measurements of vase's resonant frequencies and damping (reradiation) verified that the model vases obeyed expected physical rules. It was concluded that the excellent acoustical quality of many ancient Greek and Roman theaters cannot be ascribed to the vases placed under their seats. This study also found that sound vases placed in Nordic churches could not have shortened the reverberation time because there are far too few of them. Moreover, they could not have covered a broad frequency range. It remains a mystery why vases were installed under the seats of ancient Greek theaters and why, 1000 years later, Danes placed vases in their churches.
STATISTICAL BAYESIAN ANALYSIS OF EXPERIMENTAL DATA.
Directory of Open Access Journals (Sweden)
AHLAM LABDAOUI
2012-12-01
Full Text Available The Bayesian researcher should know the basic ideas underlying Bayesian methodology and the computational tools used in modern Bayesian econometrics. Some of the most important methods of posterior simulation are Monte Carlo integration, importance sampling, Gibbs sampling and the Metropolis- Hastings algorithm. The Bayesian should also be able to put the theory and computational tools together in the context of substantive empirical problems. We focus primarily on recent developments in Bayesian computation. Then we focus on particular models. Inevitably, we combine theory and computation in the context of particular models. Although we have tried to be reasonably complete in terms of covering the basic ideas of Bayesian theory and the computational tools most commonly used by the Bayesian, there is no way we can cover all the classes of models used in econometrics. We propose to the user of analysis of variance and linear regression model.
Bayesian methods for measures of agreement
Broemeling, Lyle D
2009-01-01
Using WinBUGS to implement Bayesian inferences of estimation and testing hypotheses, Bayesian Methods for Measures of Agreement presents useful methods for the design and analysis of agreement studies. It focuses on agreement among the various players in the diagnostic process.The author employs a Bayesian approach to provide statistical inferences based on various models of intra- and interrater agreement. He presents many examples that illustrate the Bayesian mode of reasoning and explains elements of a Bayesian application, including prior information, experimental information, the likelihood function, posterior distribution, and predictive distribution. The appendices provide the necessary theoretical foundation to understand Bayesian methods as well as introduce the fundamentals of programming and executing the WinBUGS software.Taking a Bayesian approach to inference, this hands-on book explores numerous measures of agreement, including the Kappa coefficient, the G coefficient, and intraclass correlation...
Hierarchical Bayesian spatial models for multispecies conservation planning and monitoring.
Carroll, Carlos; Johnson, Devin S; Dunk, Jeffrey R; Zielinski, William J
2010-12-01
Biologists who develop and apply habitat models are often familiar with the statistical challenges posed by their data's spatial structure but are unsure of whether the use of complex spatial models will increase the utility of model results in planning. We compared the relative performance of nonspatial and hierarchical Bayesian spatial models for three vertebrate and invertebrate taxa of conservation concern (Church's sideband snails [Monadenia churchi], red tree voles [Arborimus longicaudus], and Pacific fishers [Martes pennanti pacifica]) that provide examples of a range of distributional extents and dispersal abilities. We used presence-absence data derived from regional monitoring programs to develop models with both landscape and site-level environmental covariates. We used Markov chain Monte Carlo algorithms and a conditional autoregressive or intrinsic conditional autoregressive model framework to fit spatial models. The fit of Bayesian spatial models was between 35 and 55% better than the fit of nonspatial analogue models. Bayesian spatial models outperformed analogous models developed with maximum entropy (Maxent) methods. Although the best spatial and nonspatial models included similar environmental variables, spatial models provided estimates of residual spatial effects that suggested how ecological processes might structure distribution patterns. Spatial models built from presence-absence data improved fit most for localized endemic species with ranges constrained by poorly known biogeographic factors and for widely distributed species suspected to be strongly affected by unmeasured environmental variables or population processes. By treating spatial effects as a variable of interest rather than a nuisance, hierarchical Bayesian spatial models, especially when they are based on a common broad-scale spatial lattice (here the national Forest Inventory and Analysis grid of 24 km(2) hexagons), can increase the relevance of habitat models to multispecies
Splendid Arts Fram Ancient Capitals
Institute of Scientific and Technical Information of China (English)
1998-01-01
IT was in the golden autumn in Beijing, when the sky was high and the air clear, that I hurried to Zhongshan Park to witness the display of the songs and dances of the seven Chinese ancient capitals. The flower beds arranged for the celebration of National Day were still there and the colorful blooms looked especially bright in the sunshine. The seven cities which have served as capitals in Chinese history are Beijing,
Psychiatric Thoughts in Ancient India
Directory of Open Access Journals (Sweden)
Ravi Abhyankar
2015-01-01
Full Text Available A review of the literature regarding psychiatric thoughts in ancient India is attempted. Besides interesting reading, many of the concepts are still relevant and can be used in day-to-day practice especially towards healthy and happy living. Certain concepts are surprisingly contemporary and valid today. They can be used in psychotherapy and counselling and for promoting mental health. However, the description and classification of mental illness is not in tune with modern psychiatry.
Nanoscience of an ancient pigment.
Johnson-McDaniel, Darrah; Barrett, Christopher A; Sharafi, Asma; Salguero, Tina T
2013-02-06
We describe monolayer nanosheets of calcium copper tetrasilicate, CaCuSi(4)O(10), which have strong near-IR luminescence and are amenable to solution processing methods. The facile exfoliation of bulk CaCuSi(4)O(10) into nanosheets is especially surprising in view of the long history of this material as the colored component of Egyptian blue, a well-known pigment from ancient times.
Directory of Open Access Journals (Sweden)
Dongsheng Chen
2016-01-01
Full Text Available Accurate biomass estimations are important for assessing and monitoring forest carbon storage. Bayesian theory has been widely applied to tree biomass models. Recently, a hierarchical Bayesian approach has received increasing attention for improving biomass models. In this study, tree biomass data were obtained by sampling 310 trees from 209 permanent sample plots from larch plantations in six regions across China. Non-hierarchical and hierarchical Bayesian approaches were used to model allometric biomass equations. We found that the total, root, stem wood, stem bark, branch and foliage biomass model relationships were statistically significant (p-values < 0.001 for both the non-hierarchical and hierarchical Bayesian approaches, but the hierarchical Bayesian approach increased the goodness-of-fit statistics over the non-hierarchical Bayesian approach. The R2 values of the hierarchical approach were higher than those of the non-hierarchical approach by 0.008, 0.018, 0.020, 0.003, 0.088 and 0.116 for the total tree, root, stem wood, stem bark, branch and foliage models, respectively. The hierarchical Bayesian approach significantly improved the accuracy of the biomass model (except for the stem bark and can reflect regional differences by using random parameters to improve the regional scale model accuracy.
Bayesian versus 'plain-vanilla Bayesian' multitarget statistics
Mahler, Ronald P. S.
2004-08-01
Finite-set statistics (FISST) is a direct generalization of single-sensor, single-target Bayes statistics to the multisensor-multitarget realm, based on random set theory. Various aspects of FISST are being investigated by several research teams around the world. In recent years, however, a few partisans have claimed that a "plain-vanilla Bayesian approach" suffices as down-to-earth, "straightforward," and general "first principles" for multitarget problems. Therefore, FISST is mere mathematical "obfuscation." In this and a companion paper I demonstrate the speciousness of these claims. In this paper I summarize general Bayes statistics, what is required to use it in multisensor-multitarget problems, and why FISST is necessary to make it practical. Then I demonstrate that the "plain-vanilla Bayesian approach" is so heedlessly formulated that it is erroneous, not even Bayesian denigrates FISST concepts while unwittingly assuming them, and has resulted in a succession of algorithms afflicted by inherent -- but less than candidly acknowledged -- computational "logjams."
DEFF Research Database (Denmark)
Jacobs, Douglass F.; Oliet, Juan A.; Aronson, James;
2015-01-01
Forest loss and degradation is occurring at high rates but humankind is experiencing historical momentum that favors forest restoration. Approaches to restoration may follow various paradigms depending on stakeholder objectives, regional climate, or the degree of site degradation. The vast amount...
Improving Bayesian population dynamics inference: a coalescent-based model for multiple loci.
Gill, Mandev S; Lemey, Philippe; Faria, Nuno R; Rambaut, Andrew; Shapiro, Beth; Suchard, Marc A
2013-03-01
Effective population size is fundamental in population genetics and characterizes genetic diversity. To infer past population dynamics from molecular sequence data, coalescent-based models have been developed for Bayesian nonparametric estimation of effective population size over time. Among the most successful is a Gaussian Markov random field (GMRF) model for a single gene locus. Here, we present a generalization of the GMRF model that allows for the analysis of multilocus sequence data. Using simulated data, we demonstrate the improved performance of our method to recover true population trajectories and the time to the most recent common ancestor (TMRCA). We analyze a multilocus alignment of HIV-1 CRF02_AG gene sequences sampled from Cameroon. Our results are consistent with HIV prevalence data and uncover some aspects of the population history that go undetected in Bayesian parametric estimation. Finally, we recover an older and more reconcilable TMRCA for a classic ancient DNA data set.
Bayesian priors for transiting planets
Kipping, David M
2016-01-01
As astronomers push towards discovering ever-smaller transiting planets, it is increasingly common to deal with low signal-to-noise ratio (SNR) events, where the choice of priors plays an influential role in Bayesian inference. In the analysis of exoplanet data, the selection of priors is often treated as a nuisance, with observers typically defaulting to uninformative distributions. Such treatments miss a key strength of the Bayesian framework, especially in the low SNR regime, where even weak a priori information is valuable. When estimating the parameters of a low-SNR transit, two key pieces of information are known: (i) the planet has the correct geometric alignment to transit and (ii) the transit event exhibits sufficient signal-to-noise to have been detected. These represent two forms of observational bias. Accordingly, when fitting transits, the model parameter priors should not follow the intrinsic distributions of said terms, but rather those of both the intrinsic distributions and the observational ...
Bayesian approach to rough set
Marwala, Tshilidzi
2007-01-01
This paper proposes an approach to training rough set models using Bayesian framework trained using Markov Chain Monte Carlo (MCMC) method. The prior probabilities are constructed from the prior knowledge that good rough set models have fewer rules. Markov Chain Monte Carlo sampling is conducted through sampling in the rough set granule space and Metropolis algorithm is used as an acceptance criteria. The proposed method is tested to estimate the risk of HIV given demographic data. The results obtained shows that the proposed approach is able to achieve an average accuracy of 58% with the accuracy varying up to 66%. In addition the Bayesian rough set give the probabilities of the estimated HIV status as well as the linguistic rules describing how the demographic parameters drive the risk of HIV.
Deep Learning and Bayesian Methods
Directory of Open Access Journals (Sweden)
Prosper Harrison B.
2017-01-01
Full Text Available A revolution is underway in which deep neural networks are routinely used to solve diffcult problems such as face recognition and natural language understanding. Particle physicists have taken notice and have started to deploy these methods, achieving results that suggest a potentially significant shift in how data might be analyzed in the not too distant future. We discuss a few recent developments in the application of deep neural networks and then indulge in speculation about how such methods might be used to automate certain aspects of data analysis in particle physics. Next, the connection to Bayesian methods is discussed and the paper ends with thoughts on a significant practical issue, namely, how, from a Bayesian perspective, one might optimize the construction of deep neural networks.
Deep Learning and Bayesian Methods
Prosper, Harrison B.
2017-03-01
A revolution is underway in which deep neural networks are routinely used to solve diffcult problems such as face recognition and natural language understanding. Particle physicists have taken notice and have started to deploy these methods, achieving results that suggest a potentially significant shift in how data might be analyzed in the not too distant future. We discuss a few recent developments in the application of deep neural networks and then indulge in speculation about how such methods might be used to automate certain aspects of data analysis in particle physics. Next, the connection to Bayesian methods is discussed and the paper ends with thoughts on a significant practical issue, namely, how, from a Bayesian perspective, one might optimize the construction of deep neural networks.
Bayesian Source Separation and Localization
Knuth, K H
1998-01-01
The problem of mixed signals occurs in many different contexts; one of the most familiar being acoustics. The forward problem in acoustics consists of finding the sound pressure levels at various detectors resulting from sound signals emanating from the active acoustic sources. The inverse problem consists of using the sound recorded by the detectors to separate the signals and recover the original source waveforms. In general, the inverse problem is unsolvable without additional information. This general problem is called source separation, and several techniques have been developed that utilize maximum entropy, minimum mutual information, and maximum likelihood. In previous work, it has been demonstrated that these techniques can be recast in a Bayesian framework. This paper demonstrates the power of the Bayesian approach, which provides a natural means for incorporating prior information into a source model. An algorithm is developed that utilizes information regarding both the statistics of the amplitudes...
Bayesian Inference for Radio Observations
Lochner, Michelle; Zwart, Jonathan T L; Smirnov, Oleg; Bassett, Bruce A; Oozeer, Nadeem; Kunz, Martin
2015-01-01
(Abridged) New telescopes like the Square Kilometre Array (SKA) will push into a new sensitivity regime and expose systematics, such as direction-dependent effects, that could previously be ignored. Current methods for handling such systematics rely on alternating best estimates of instrumental calibration and models of the underlying sky, which can lead to inaccurate uncertainty estimates and biased results because such methods ignore any correlations between parameters. These deconvolution algorithms produce a single image that is assumed to be a true representation of the sky, when in fact it is just one realisation of an infinite ensemble of images compatible with the noise in the data. In contrast, here we report a Bayesian formalism that simultaneously infers both systematics and science. Our technique, Bayesian Inference for Radio Observations (BIRO), determines all parameters directly from the raw data, bypassing image-making entirely, by sampling from the joint posterior probability distribution. Thi...
Bayesian inference on proportional elections.
Directory of Open Access Journals (Sweden)
Gabriel Hideki Vatanabe Brunello
Full Text Available Polls for majoritarian voting systems usually show estimates of the percentage of votes for each candidate. However, proportional vote systems do not necessarily guarantee the candidate with the most percentage of votes will be elected. Thus, traditional methods used in majoritarian elections cannot be applied on proportional elections. In this context, the purpose of this paper was to perform a Bayesian inference on proportional elections considering the Brazilian system of seats distribution. More specifically, a methodology to answer the probability that a given party will have representation on the chamber of deputies was developed. Inferences were made on a Bayesian scenario using the Monte Carlo simulation technique, and the developed methodology was applied on data from the Brazilian elections for Members of the Legislative Assembly and Federal Chamber of Deputies in 2010. A performance rate was also presented to evaluate the efficiency of the methodology. Calculations and simulations were carried out using the free R statistical software.
Bayesian analysis for kaon photoproduction
Energy Technology Data Exchange (ETDEWEB)
Marsainy, T., E-mail: tmart@fisika.ui.ac.id; Mart, T., E-mail: tmart@fisika.ui.ac.id [Department Fisika, FMIPA, Universitas Indonesia, Depok 16424 (Indonesia)
2014-09-25
We have investigated contribution of the nucleon resonances in the kaon photoproduction process by using an established statistical decision making method, i.e. the Bayesian method. This method does not only evaluate the model over its entire parameter space, but also takes the prior information and experimental data into account. The result indicates that certain resonances have larger probabilities to contribute to the process.
Bayesian priors and nuisance parameters
Gupta, Sourendu
2016-01-01
Bayesian techniques are widely used to obtain spectral functions from correlators. We suggest a technique to rid the results of nuisance parameters, ie, parameters which are needed for the regularization but cannot be determined from data. We give examples where the method works, including a pion mass extraction with two flavours of staggered quarks at a lattice spacing of about 0.07 fm. We also give an example where the method does not work.
Space Shuttle RTOS Bayesian Network
Morris, A. Terry; Beling, Peter A.
2001-01-01
With shrinking budgets and the requirements to increase reliability and operational life of the existing orbiter fleet, NASA has proposed various upgrades for the Space Shuttle that are consistent with national space policy. The cockpit avionics upgrade (CAU), a high priority item, has been selected as the next major upgrade. The primary functions of cockpit avionics include flight control, guidance and navigation, communication, and orbiter landing support. Secondary functions include the provision of operational services for non-avionics systems such as data handling for the payloads and caution and warning alerts to the crew. Recently, a process to selection the optimal commercial-off-the-shelf (COTS) real-time operating system (RTOS) for the CAU was conducted by United Space Alliance (USA) Corporation, which is a joint venture between Boeing and Lockheed Martin, the prime contractor for space shuttle operations. In order to independently assess the RTOS selection, NASA has used the Bayesian network-based scoring methodology described in this paper. Our two-stage methodology addresses the issue of RTOS acceptability by incorporating functional, performance and non-functional software measures related to reliability, interoperability, certifiability, efficiency, correctness, business, legal, product history, cost and life cycle. The first stage of the methodology involves obtaining scores for the various measures using a Bayesian network. The Bayesian network incorporates the causal relationships between the various and often competing measures of interest while also assisting the inherently complex decision analysis process with its ability to reason under uncertainty. The structure and selection of prior probabilities for the network is extracted from experts in the field of real-time operating systems. Scores for the various measures are computed using Bayesian probability. In the second stage, multi-criteria trade-off analyses are performed between the scores
Elements of Bayesian experimental design
Energy Technology Data Exchange (ETDEWEB)
Sivia, D.S. [Rutherford Appleton Lab., Oxon (United Kingdom)
1997-09-01
We consider some elements of the Bayesian approach that are important for optimal experimental design. While the underlying principles used are very general, and are explained in detail in a recent tutorial text, they are applied here to the specific case of characterising the inferential value of different resolution peakshapes. This particular issue was considered earlier by Silver, Sivia and Pynn (1989, 1990a, 1990b), and the following presentation confirms and extends the conclusions of their analysis.
Bayesian Sampling using Condition Indicators
DEFF Research Database (Denmark)
Faber, Michael H.; Sørensen, John Dalsgaard
2002-01-01
. This allows for a Bayesian formulation of the indicators whereby the experience and expertise of the inspection personnel may be fully utilized and consistently updated as frequentistic information is collected. The approach is illustrated on an example considering a concrete structure subject to corrosion....... It is shown how half-cell potential measurements may be utilized to update the probability of excessive repair after 50 years....
Institute of Scientific and Technical Information of China (English)
SHEN Xian-sheng; LI Shu-mei; YANG Jie-pin; SUN Hao
2004-01-01
A large number of plant remains were discovered in the ancient-woods layer of Zhujiajian Island, Zhejiang Province.There were some thick trunks, complete laminas, fruit, seeds and so on. According to radiocarbon tests conducted for plant remains, the ancient-woods layer has been dated back to about 8750 - 6200 years, and the vegetation was a subtropical evergreen and deciduous broad-leaved mixed forests on the island in the past. In the middle of the ancient-woods layer, two grains of wild rice were explored accidentally, which are Oryza rufipogon, along with the fruit and seeds of some water plants, such as Ceratophyllum demersum, C. oryzetorum, Euryale ferox, Trapa incisa var. quadricaudata , Scirpus yagara and so on. There might be marshy soil and a pond in ancient forest vegetation from where the grains of wild rice and hydrophytic fruit were found. It is of tremendous importance to study the origin of wild rice in China.
Institute of Scientific and Technical Information of China (English)
SHENXian-sheng; LIShu-mei; YANGJie-pin; SUNHao
2004-01-01
A large number of plant remains were discovered in the ancient-woods layer of Zhujiajian Island, Zhejiang Province.There were some thick trunks, complete laminas, fruit, seeds and so on. According to radiocarbon tests conducted for plant remains, the ancient-woods layer has been dated back to about 8750 - 6200 years, and the vegetation was a subtropical evergreen and deciduous broad-leaved mixed forests on the island in the past. In the middle of the ancient-woods layer, two grains of wild rice were explored accidentally, which are Oryza rufipogon, along with the fruit and seeds of some water plants, such as Ceratophyllum dcmcrsum, C.oryzetoum, Euryale fetox, Trapa incisa var. quadricaudata , Scirpus yagara and so on. There might be marshy soil and a pond in ancient forest vegetation from where the grains of wild rice and hydrophytic fruit were found. It is of tremendous importance to study the origin of wild rice in China.
From Here I Walked into Ancient China
Institute of Scientific and Technical Information of China (English)
Yan Manman
2011-01-01
@@ When I was a little girl, I had heard about the eighth world wonder - terra cotta warriors in Qin Emperor Mausoleum.I have been wishing to visit there to see those magnificent scene which were created thousands of years ago.While with my age added, I gradually learned the terra cotta warriors were lust only one of many ancient marks of Xi'an, which once was capital of 13 dynasties in ancient China.Xi'an actually is a carrier of ancient China culture, where I walked from the modern world to the ancient China.
Ancient Indian Leaps into Mathematics
Yadav, B S
2011-01-01
This book presents contributions of mathematicians covering topics from ancient India, placing them in the broader context of the history of mathematics. Although the translations of some Sanskrit mathematical texts are available in the literature, Indian contributions are rarely presented in major Western historical works. Yet some of the well-known and universally-accepted discoveries from India, including the concept of zero and the decimal representation of numbers, have made lasting contributions to the foundation of modern mathematics. Through a systematic approach, this book examines th
Chinese Ancient Football with Romanticism
Institute of Scientific and Technical Information of China (English)
江凌; 李晓勤
2004-01-01
Like other traditional Chinese sports, the ancient Chinese football, which used to be called “cuju”, has some differences from several sports in western countries concerning cultural and hamanist purport as well as metal aspiration, although it was similar with modern football to some extent, such as a leather-made ball with a bladder, rectangle sports ground, referee, goal and certain competitiveness. The author tries to talk about such difference in cultural and humanist purport as well as mental aspiration by making a comparison between “cuju” and modern football.
12th Brazilian Meeting on Bayesian Statistics
Louzada, Francisco; Rifo, Laura; Stern, Julio; Lauretto, Marcelo
2015-01-01
Through refereed papers, this volume focuses on the foundations of the Bayesian paradigm; their comparison to objectivistic or frequentist Statistics counterparts; and the appropriate application of Bayesian foundations. This research in Bayesian Statistics is applicable to data analysis in biostatistics, clinical trials, law, engineering, and the social sciences. EBEB, the Brazilian Meeting on Bayesian Statistics, is held every two years by the ISBrA, the International Society for Bayesian Analysis, one of the most active chapters of the ISBA. The 12th meeting took place March 10-14, 2014 in Atibaia. Interest in foundations of inductive Statistics has grown recently in accordance with the increasing availability of Bayesian methodological alternatives. Scientists need to deal with the ever more difficult choice of the optimal method to apply to their problem. This volume shows how Bayes can be the answer. The examination and discussion on the foundations work towards the goal of proper application of Bayesia...
Varvia, Petri; Rautiainen, Miina; Seppänen, Aku
2017-04-01
Hyperspectral remote sensing data carry information on the leaf area index (LAI) of forests, and thus in principle, LAI can be estimated based on the data by inverting a forest reflectance model. However, LAI is usually not the only unknown in a reflectance model; especially, the leaf spectral albedo and understory reflectance are also not known. If the uncertainties of these parameters are not accounted for, the inversion of a forest reflectance model can lead to biased estimates for LAI. In this paper, we study the effects of reflectance model uncertainties on LAI estimates, and further, investigate whether the LAI estimates could recover from these uncertainties with the aid of Bayesian inference. In the proposed approach, the unknown leaf albedo and understory reflectance are estimated simultaneously with LAI from hyperspectral remote sensing data. The feasibility of the approach is tested with numerical simulation studies. The results show that in the presence of unknown parameters, the Bayesian LAI estimates which account for the model uncertainties outperform the conventional estimates that are based on biased model parameters. Moreover, the results demonstrate that the Bayesian inference can also provide feasible measures for the uncertainty of the estimated LAI.
Bayesian Inversion of Seabed Scattering Data
2014-09-30
Bayesian Inversion of Seabed Scattering Data (Special Research Award in Ocean Acoustics) Gavin A.M.W. Steininger School of Earth & Ocean...project are to carry out joint Bayesian inversion of scattering and reflection data to estimate the in-situ seabed scattering and geoacoustic parameters...valid OMB control number. 1. REPORT DATE 30 SEP 2014 2. REPORT TYPE 3. DATES COVERED 00-00-2014 to 00-00-2014 4. TITLE AND SUBTITLE Bayesian
Anomaly Detection and Attribution Using Bayesian Networks
2014-06-01
UNCLASSIFIED Anomaly Detection and Attribution Using Bayesian Networks Andrew Kirk, Jonathan Legg and Edwin El-Mahassni National Security and...detection in Bayesian networks , en- abling both the detection and explanation of anomalous cases in a dataset. By exploiting the structure of a... Bayesian network , our algorithm is able to efficiently search for local maxima of data conflict between closely related vari- ables. Benchmark tests using
Compiling Relational Bayesian Networks for Exact Inference
DEFF Research Database (Denmark)
Jaeger, Manfred; Chavira, Mark; Darwiche, Adnan
2004-01-01
We describe a system for exact inference with relational Bayesian networks as defined in the publicly available \\primula\\ tool. The system is based on compiling propositional instances of relational Bayesian networks into arithmetic circuits and then performing online inference by evaluating...... and differentiating these circuits in time linear in their size. We report on experimental results showing the successful compilation, and efficient inference, on relational Bayesian networks whose {\\primula}--generated propositional instances have thousands of variables, and whose jointrees have clusters...
SYNTHESIZED EXPECTED BAYESIAN METHOD OF PARAMETRIC ESTIMATE
Institute of Scientific and Technical Information of China (English)
Ming HAN; Yuanyao DING
2004-01-01
This paper develops a new method of parametric estimate, which is named as "synthesized expected Bayesian method". When samples of products are tested and no failure events occur, thedefinition of expected Bayesian estimate is introduced and the estimates of failure probability and failure rate are provided. After some failure information is introduced by making an extra-test, a synthesized expected Bayesian method is defined and used to estimate failure probability, failure rateand some other parameters in exponential distribution and Weibull distribution of populations. Finally,calculations are performed according to practical problems, which show that the synthesized expected Bayesian method is feasible and easy to operate.
Learning dynamic Bayesian networks with mixed variables
DEFF Research Database (Denmark)
Bøttcher, Susanne Gammelgaard
This paper considers dynamic Bayesian networks for discrete and continuous variables. We only treat the case, where the distribution of the variables is conditional Gaussian. We show how to learn the parameters and structure of a dynamic Bayesian network and also how the Markov order can be learned....... An automated procedure for specifying prior distributions for the parameters in a dynamic Bayesian network is presented. It is a simple extension of the procedure for the ordinary Bayesian networks. Finally the W¨olfer?s sunspot numbers are analyzed....
Variational bayesian method of estimating variance components.
Arakawa, Aisaku; Taniguchi, Masaaki; Hayashi, Takeshi; Mikawa, Satoshi
2016-07-01
We developed a Bayesian analysis approach by using a variational inference method, a so-called variational Bayesian method, to determine the posterior distributions of variance components. This variational Bayesian method and an alternative Bayesian method using Gibbs sampling were compared in estimating genetic and residual variance components from both simulated data and publically available real pig data. In the simulated data set, we observed strong bias toward overestimation of genetic variance for the variational Bayesian method in the case of low heritability and low population size, and less bias was detected with larger population sizes in both methods examined. The differences in the estimates of variance components between the variational Bayesian and the Gibbs sampling were not found in the real pig data. However, the posterior distributions of the variance components obtained with the variational Bayesian method had shorter tails than those obtained with the Gibbs sampling. Consequently, the posterior standard deviations of the genetic and residual variances of the variational Bayesian method were lower than those of the method using Gibbs sampling. The computing time required was much shorter with the variational Bayesian method than with the method using Gibbs sampling.
Foreign Guests in Ancient Greece
Directory of Open Access Journals (Sweden)
Zora Žbontar
2013-12-01
Full Text Available Xenía was a special relationship between a foreign guest and his host in Ancient Greece. The ritual of hosting a foreigner included an exchange of objects, feasting, and the establishment of friendship between people from different social backgrounds. This relationship implied trust, loyalty, friendship, and mutual aid between the people involved. Goods and services were also exchanged without any form of payment. There were no formal laws governing xenía – it was based entirely on a moral appeal. Mutual appreciation between the host and the guest was established during the ritual, but the host did retain a certain level of superiority over the guest. Xenía was one of the most important institutions in Ancient Greece. It had a lot of features and obligations similar to kinship and marriage. In literary sources the word xénos varies in meaning from “enemy stranger”, “friendly stranger”, “foreigner”, “guest”, “host” to “ritual friend”, and it is often hard to tell which usage is appropriate in a given passage. The paper describes the emphasis on hospitality towards foreigners. It presents an example of a depiction indicating xenía is presented, as well as several objects which were traded during the ritual. The paper also addresses the importance of hospitality in Greek drama in general, especially with examples of violations of the hospitality code.
[Ancient history of Indian pharmacy].
Okuda, Jun; Natsume, Yohko
2010-01-01
The study of the ancient history of Indian medicine has recently been revived due to the publication of polyglot translations. However, little is known of ancient Indian pharmacy. Archaeological evidence suggests the Indus people lived a settled life approximately in 2500 B.C. Their cities were enjoying the cleanest and most hygienic daily life with elaborate civic sanitation systems. The whole conception shows a remarkable concern for health. Then, the early Aryans invaded India about 1500 B.C. and the Vedic age started. The Rgveda texts contain the hymns for Soma and those for herbs. The term Ayurveda (i.e., science of life) is found in some old versions of both Ramāyana and Mahābhārata and in the Atharvaveda. Suśruta had the credit of making a breakthrough in the field of surgery. The Ayurveda, a work on internal medicine, gives the following transmission of sages: Brahmā-->Daksa-->Prajāpati-->Aśivinau-->Indra-->Caraka. On the other hand, the Suśruta-samhitā, which deals mainly with surgical medicine, explains it as follows; Indra-->Dhanvantari-->Suśruta Both Caraka and Suśruta were medical doctors as well as pharmacists, so they studied more than 1000 herbs thoroughly. The Ayurveda had been used by his devotees for medical purposes. It eventually spread over Asia with the advanced evolution of Buddhism.
FS National Forest Dataset (US Forest Service Proclaimed Forests)
US Forest Service, Department of Agriculture — A map service on the www depicting the boundaries encompassing the National Forest System (NFS) lands within the original proclaimed National Forests, along with...
Attitudes Toward Deviant Sex in Ancient Mesopotamia
Bullough, Vern L.
1971-01-01
The article concludes that the whole question of sexual life in ancient Mesopotamia is difficult to reconstruct and fraught with many uncertainties. Nevertheless, it seems certain that the ancient Mesopotamians had fewer prohibitions against sex than our own civilization, and regarded as acceptable many practices which later societies condemned.…
Women--Sex Objects in Ancient Egypt.
Mutimer, Brian T. P.
Although it has been said that the women in Ancient Egypt enjoyed a reasonable state of social and professional equality with men, this paper presents an alternate theory--that women were second-class citizens whose physical prowess was secondary to their role as sex objects. It appears that men and women in Ancient Egypt often participated in the…
The Idea of Ancient Greek Philosophy
Institute of Scientific and Technical Information of China (English)
苏雪
2016-01-01
As the source of western philosophy, ancient Greek philosophy had a profound influence on western philosophy. Ancient philosophers were hard to reach a consensus on the existence of all the things in the world. They tried to grasp the profound understanding of the world, which is the clue of the history of philosophy.
Directory of Open Access Journals (Sweden)
V V Robin
Full Text Available BACKGROUND: Sky islands, formed by the highest reaches of mountain tracts physically isolated from one another, represent one of the biodiversity-rich regions of the world. Comparative studies of geographically isolated populations on such islands can provide valuable insights into the biogeography and evolution of species on these islands. The Western Ghats mountains of southern India form a sky island system, where the relationship between the island structure and the evolution of its species remains virtually unknown despite a few population genetic studies. METHODS AND PRINCIPAL FINDINGS: We investigated how ancient geographic gaps and glacial cycles have partitioned genetic variation in modern populations of a threatened endemic bird, the White-bellied Shortwing Brachypteryx major, across the montane Shola forests on these islands and also inferred its evolutionary history. We used bayesian and maximum likelihood-based phylogenetic and population-genetic analyses on data from three mitochondrial markers and one nuclear marker (totally 2594 bp obtained from 33 White-bellied Shortwing individuals across five islands. Genetic differentiation between populations of the species correlated with the locations of deep valleys in the Western Ghats but not with geographical distance between these populations. All populations revealed demographic histories consistent with population founding and expansion during the Last Glacial Maximum. Given the level of genetic differentiation north and south of the Palghat Gap, we suggest that these populations be considered two different taxonomic species. CONCLUSIONS AND SIGNIFICANCE: Our results show that the physiography and paleo-climate of this region historically resulted in multiple glacial refugia that may have subsequently driven the evolutionary history and current population structure of this bird. The first avian genetic study from this biodiversity hotspot, our results provide insights into processes
Bayesian Methods and Universal Darwinism
Campbell, John
2009-12-01
Bayesian methods since the time of Laplace have been understood by their practitioners as closely aligned to the scientific method. Indeed a recent Champion of Bayesian methods, E. T. Jaynes, titled his textbook on the subject Probability Theory: the Logic of Science. Many philosophers of science including Karl Popper and Donald Campbell have interpreted the evolution of Science as a Darwinian process consisting of a `copy with selective retention' algorithm abstracted from Darwin's theory of Natural Selection. Arguments are presented for an isomorphism between Bayesian Methods and Darwinian processes. Universal Darwinism, as the term has been developed by Richard Dawkins, Daniel Dennett and Susan Blackmore, is the collection of scientific theories which explain the creation and evolution of their subject matter as due to the Operation of Darwinian processes. These subject matters span the fields of atomic physics, chemistry, biology and the social sciences. The principle of Maximum Entropy states that Systems will evolve to states of highest entropy subject to the constraints of scientific law. This principle may be inverted to provide illumination as to the nature of scientific law. Our best cosmological theories suggest the universe contained much less complexity during the period shortly after the Big Bang than it does at present. The scientific subject matter of atomic physics, chemistry, biology and the social sciences has been created since that time. An explanation is proposed for the existence of this subject matter as due to the evolution of constraints in the form of adaptations imposed on Maximum Entropy. It is argued these adaptations were discovered and instantiated through the Operations of a succession of Darwinian processes.
Bayesian phylogeography finds its roots.
Directory of Open Access Journals (Sweden)
Philippe Lemey
2009-09-01
Full Text Available As a key factor in endemic and epidemic dynamics, the geographical distribution of viruses has been frequently interpreted in the light of their genetic histories. Unfortunately, inference of historical dispersal or migration patterns of viruses has mainly been restricted to model-free heuristic approaches that provide little insight into the temporal setting of the spatial dynamics. The introduction of probabilistic models of evolution, however, offers unique opportunities to engage in this statistical endeavor. Here we introduce a Bayesian framework for inference, visualization and hypothesis testing of phylogeographic history. By implementing character mapping in a Bayesian software that samples time-scaled phylogenies, we enable the reconstruction of timed viral dispersal patterns while accommodating phylogenetic uncertainty. Standard Markov model inference is extended with a stochastic search variable selection procedure that identifies the parsimonious descriptions of the diffusion process. In addition, we propose priors that can incorporate geographical sampling distributions or characterize alternative hypotheses about the spatial dynamics. To visualize the spatial and temporal information, we summarize inferences using virtual globe software. We describe how Bayesian phylogeography compares with previous parsimony analysis in the investigation of the influenza A H5N1 origin and H5N1 epidemiological linkage among sampling localities. Analysis of rabies in West African dog populations reveals how virus diffusion may enable endemic maintenance through continuous epidemic cycles. From these analyses, we conclude that our phylogeographic framework will make an important asset in molecular epidemiology that can be easily generalized to infer biogeogeography from genetic data for many organisms.
Mechanisms in ancient Chinese books with illustrations
Hsiao, Kuo-Hung
2014-01-01
This book presents a unique approach for studying mechanisms and machines with drawings that were depicted unclearly in ancient Chinese books. The historical, cultural and technical backgrounds of the mechanisms are explained, and various mechanisms described and illustrated in ancient books are introduced. By utilizing the idea for the conceptual design of modern mechanisms, all feasible designs of ancient mechanisms with uncertain members and joints that meet the technical standards of the subjects’ time periods are synthesized systematically. Ancient Chinese crossbows (the original crossbow and repeating crossbows), textile mechanisms (silk-reeling mechanism, spinning mechanisms, and looms), and many other artisan's tool mechanisms are used as illustrated examples. Such an approach provides a logical method for the reconstruction designs of ancient mechanisms with uncertain structures. It also provides an innovative direction for researchers to further identify the original structures of mechanisms...
Structural recognition of ancient Chinese ideographic characters
Institute of Scientific and Technical Information of China (English)
Li Ning; Chen Dan
2014-01-01
Ancient Chinese characters, typically the ideographic characters on bones and bronze before Shang Dynasty (16th—11th century B.C.), are valuable culture legacy of history. However the recognition of Ancient Chinese characters has been the task of paleography experts for long. With the help of modern computer technique, everyone can expect to be able to recognize the characters and understand the ancient inscriptions. This research is aimed to help people recognize and understand those ancient Chinese characters by combining Chinese paleography theory and computer information processing technology. Based on the analysis of ancient character features, a method for structural character recognition is proposed. The important characteristics of strokes and basic components or radicals used in recognition are introduced in detail. A system was implemented based on above method to show the effectiveness of the method.
Bayesian Query-Focused Summarization
Daumé, Hal
2009-01-01
We present BayeSum (for ``Bayesian summarization''), a model for sentence extraction in query-focused summarization. BayeSum leverages the common case in which multiple documents are relevant to a single query. Using these documents as reinforcement for query terms, BayeSum is not afflicted by the paucity of information in short queries. We show that approximate inference in BayeSum is possible on large data sets and results in a state-of-the-art summarization system. Furthermore, we show how BayeSum can be understood as a justified query expansion technique in the language modeling for IR framework.
Numeracy, frequency, and Bayesian reasoning
Directory of Open Access Journals (Sweden)
Gretchen B. Chapman
2009-02-01
Full Text Available Previous research has demonstrated that Bayesian reasoning performance is improved if uncertainty information is presented as natural frequencies rather than single-event probabilities. A questionnaire study of 342 college students replicated this effect but also found that the performance-boosting benefits of the natural frequency presentation occurred primarily for participants who scored high in numeracy. This finding suggests that even comprehension and manipulation of natural frequencies requires a certain threshold of numeracy abilities, and that the beneficial effects of natural frequency presentation may not be as general as previously believed.
Bayesian inference for Hawkes processes
DEFF Research Database (Denmark)
Rasmussen, Jakob Gulddahl
2013-01-01
The Hawkes process is a practically and theoretically important class of point processes, but parameter-estimation for such a process can pose various problems. In this paper we explore and compare two approaches to Bayesian inference. The first approach is based on the so-called conditional...... intensity function, while the second approach is based on an underlying clustering and branching structure in the Hawkes process. For practical use, MCMC (Markov chain Monte Carlo) methods are employed. The two approaches are compared numerically using three examples of the Hawkes process....
Bayesian inference for Hawkes processes
DEFF Research Database (Denmark)
Rasmussen, Jakob Gulddahl
The Hawkes process is a practically and theoretically important class of point processes, but parameter-estimation for such a process can pose various problems. In this paper we explore and compare two approaches to Bayesian inference. The first approach is based on the so-called conditional...... intensity function, while the second approach is based on an underlying clustering and branching structure in the Hawkes process. For practical use, MCMC (Markov chain Monte Carlo) methods are employed. The two approaches are compared numerically using three examples of the Hawkes process....
Bayesian homeopathy: talking normal again.
Rutten, A L B
2007-04-01
Homeopathy has a communication problem: important homeopathic concepts are not understood by conventional colleagues. Homeopathic terminology seems to be comprehensible only after practical experience of homeopathy. The main problem lies in different handling of diagnosis. In conventional medicine diagnosis is the starting point for randomised controlled trials to determine the effect of treatment. In homeopathy diagnosis is combined with other symptoms and personal traits of the patient to guide treatment and predict response. Broadening our scope to include diagnostic as well as treatment research opens the possibility of multi factorial reasoning. Adopting Bayesian methodology opens the possibility of investigating homeopathy in everyday practice and of describing some aspects of homeopathy in conventional terms.
Low tortoise abundances in pine forest plantations in forest-shrubland transition areas
Rodríguez-Caro, Roberto C.; Oedekoven, Cornelia S.; Graciá, Eva; Anadón, José D.; Buckland, Stephen T.; Esteve-Selma, Miguel A.; Martinez, Julia; Giménez, Andrés
2017-01-01
In the transition between Mediterranean forest and the arid subtropical shrublands of the southeastern Iberian Peninsula, humans have transformed habitat since ancient times. Understanding the role of the original mosaic landscapes in wildlife species and the effects of the current changes as pine forest plantations, performed even outside the forest ecological boundaries, are important conservation issues. We studied variation in the density of the endangered spur-thighed tortoise (Testudo graeca) in three areas that include the four most common land types within the species’ range (pine forests, natural shrubs, dryland crop fields, and abandoned crop fields). Tortoise densities were estimated using a two-stage modeling approach with line transect distance sampling. Densities in dryland crop fields, abandoned crop fields and natural shrubs were higher (>6 individuals/ha) than in pine forests (1.25 individuals/ha). We also found large variation in density in the pine forests. Recent pine plantations showed higher densities than mature pine forests where shrub and herbaceous cover was taller and thicker. We hypothesize that mature pine forest might constrain tortoise activity by acting as partial barriers to movements. This issue is relevant for management purposes given that large areas in the tortoise’s range have recently been converted to pine plantations. PMID:28273135
Updating beliefs and combining evidence in adaptive forest management under climate change
DEFF Research Database (Denmark)
Yousefpour, Rasoul; Temperli, Christian; Bugmann, Harald;
2013-01-01
We study climate uncertainty and how managers' beliefs about climate change develop and influence their decisions. We develop an approach for updating knowledge and beliefs based on the observation of forest and climate variables and illustrate its application for the adaptive management of an even......-aged Norway spruce (Picea abies L. Karst) forest in the Black Forest, Germany. We simulated forest development under a range of climate change scenarios and forest management alternatives. Our analysis used Bayesian updating and Dempster's rule of combination to simulate how observations of climate and forest...... variables may influence a decision maker's beliefs about climate development and thereby management decisions. While forest managers may be inclined to rely on observed forest variables to infer climate change and impacts, we found that observation of climate state, e.g. temperature or precipitation...
Bayesian credible interval construction for Poisson statistics
Institute of Scientific and Technical Information of China (English)
ZHU Yong-Sheng
2008-01-01
The construction of the Bayesian credible (confidence) interval for a Poisson observable including both the signal and background with and without systematic uncertainties is presented.Introducing the conditional probability satisfying the requirement of the background not larger than the observed events to construct the Bayesian credible interval is also discussed.A Fortran routine,BPOCI,has been developed to implement the calculation.
Advances in Bayesian Modeling in Educational Research
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…
Nonparametric Bayesian Modeling of Complex Networks
DEFF Research Database (Denmark)
Schmidt, Mikkel Nørgaard; Mørup, Morten
2013-01-01
Modeling structure in complex networks using Bayesian nonparametrics makes it possible to specify flexible model structures and infer the adequate model complexity from the observed data. This article provides a gentle introduction to nonparametric Bayesian modeling of complex networks: Using...... for complex networks can be derived and point out relevant literature....
Modeling Diagnostic Assessments with Bayesian Networks
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…
Using Bayesian Networks to Improve Knowledge Assessment
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…
The Bayesian Revolution Approaches Psychological Development
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…
Bayesian analysis of exoplanet and binary orbits
Schulze-Hartung, Tim; Launhardt, Ralf; Henning, Thomas
2012-01-01
We introduce BASE (Bayesian astrometric and spectroscopic exoplanet detection and characterisation tool), a novel program for the combined or separate Bayesian analysis of astrometric and radial-velocity measurements of potential exoplanet hosts and binary stars. The capabilities of BASE are demonstrated using all publicly available data of the binary Mizar A.
Bayesian Network for multiple hypthesis tracking
W.P. Zajdel; B.J.A. Kröse
2002-01-01
For a flexible camera-to-camera tracking of multiple objects we model the objects behavior with a Bayesian network and combine it with the multiple hypohesis framework that associates observations with objects. Bayesian networks offer a possibility to factor complex, joint distributions into a produ
[Anomalous pregnancies in ancient medicine].
Gazzaniga, Valentina
2010-01-01
In ancient Greek medicine female physiology is determined by a particular state of non-steady equilibrium, largely based on pregnancy and lactation, presented as the only balanced and healthy periods in women's life. Nonetheless, pregnancy can be also a pathological moment, in particular referring to specific alterations of its 'normal time' ('seven-months', 'eight-months' and 'ten-months' children). The article analyzes the well-known case of myle, an abnormal pregnancy developing in three and sometimes four years, non resolving in a normal delivery, but often in a dramatic haemorrhagic flux. The author compares Hippocratic and Aristotelic testimonies about myle and abnormal pregnancies with the evidence fournished by the historical-religious recent studies about Hera and her parthenogenetic, monstrous children.
Detecting hybridization using ancient DNA.
Schaefer, Nathan K; Shapiro, Beth; Green, Richard E
2016-06-01
It is well established that related species hybridize and that this can have varied but significant effects on speciation and environmental adaptation. It should therefore come as no surprise that hybridization is not limited to species that are alive today. In the last several decades, advances in technologies for recovering and sequencing DNA from fossil remains have enabled the assembly of high-coverage genome sequences for a growing diversity of organisms, including many that are extinct. Thanks to the development of new statistical approaches for detecting and quantifying admixture from genomic data, genomes from extinct populations have proven useful both in revealing previously unknown hybridization events and informing the study of hybridization between living organisms. Here, we review some of the key recent statistical innovations for detecting ancient hybridization using genomewide sequence data and discuss how these innovations have revised our understanding of human evolutionary history.
[Being old in ancient Hellas].
van Hooff, A J
1983-08-01
There is room for a more balanced view of old age among the ancient Greeks than is furnished by De Beauvoir's la Vieillesse and other more or less one-sided publications. The old body was despised by the Greeks of classical times; especially walking with three legs (tripous) was stressed as a mark of old age. The Hippocratic writings show some interest in the infirmities of elderly people. Specific psychic and intellectual qualities were not attributed to senescence: old age brought out good and bad qualities of a person more sharply than before. The share of old people in the population cannot be established with any certainty, but there was always a group of men in their sixties who had specific tasks in society. Old age was not an autonomous theme in art, it was solely accidental. The position of the elderly was challenged occasionally in democratic Athens, but it was never undermined. Old people were never marginated in classical Greece.
Ancient Acupuncture Literature on Apoplexy
Institute of Scientific and Technical Information of China (English)
XU Yi-zeng; BI Zhen; Xiao Yuan-chun
2003-01-01
This paper reviews twenty-eight Chinese medicine books with complete prescriptions prior to the Qing Dynasty, and analyzes the characteristics of acupoint selection and needling manipulations from the perspective of apoplectic symptoms. It is concluded that,in ancient times, apoplexy is often treated on the basis of its symptoms and a great number of acupoints are employed; hemiplegia is mainly treated by the acupoints of the Large Intestine Meridian and Gallbladder Meridian,with two key acupoints; coma is mainly treated by first-aid acupoints and qi-supplementing acupoints, with seven key acupoints; wry mouth and convulsion are mainly treated by the local acupoints; as for needling manipulations, moxibustion with moxa cones is principally used, while needling is less used.
Hepatitis disease detection using Bayesian theory
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.
2nd Bayesian Young Statisticians Meeting
Bitto, Angela; Kastner, Gregor; Posekany, Alexandra
2015-01-01
The Second Bayesian Young Statisticians Meeting (BAYSM 2014) and the research presented here facilitate connections among researchers using Bayesian Statistics by providing a forum for the development and exchange of ideas. WU Vienna University of Business and Economics hosted BAYSM 2014 from September 18th to 19th. The guidance of renowned plenary lecturers and senior discussants is a critical part of the meeting and this volume, which follows publication of contributions from BAYSM 2013. The meeting's scientific program reflected the variety of fields in which Bayesian methods are currently employed or could be introduced in the future. Three brilliant keynote lectures by Chris Holmes (University of Oxford), Christian Robert (Université Paris-Dauphine), and Mike West (Duke University), were complemented by 24 plenary talks covering the major topics Dynamic Models, Applications, Bayesian Nonparametrics, Biostatistics, Bayesian Methods in Economics, and Models and Methods, as well as a lively poster session ...
Use of pollen and ancient DNA as conservation baselines for offshore islands in New Zealand.
Wilmshurst, Janet M; Moar, Neville T; Wood, Jamie R; Bellingham, Peter J; Findlater, Amy M; Robinson, James J; Stone, Clive
2014-02-01
Islands play a key role globally in the conservation of endemic species. Many island reserves have been highly modified since human colonization, and their restoration and management usually occur without knowledge of their prehuman state. However, conservation paleoecology is increasingly being recognized as a tool that can help to inform both restoration and conservation of island reserves by providing prehuman vegetation baselines. Many of New Zealand's mammal-free offshore islands are foci for biological diversity conservation and, like many islands in the Polynesian region, were deforested following initial human settlement. Therefore, their current restoration, replanting, and management are guided either by historic vegetation descriptions or the occurrence of species on forested islands. We analyzed pollen and ancient DNA in soil cores from an offshore island in northern New Zealand. The result was a 2000-year record of vegetation change that began >1200 years before human settlement and spanned 550 years of human occupation and 180 years of forest succession since human occupation ceased. Between prehuman and contemporary forests there was nearly a complete species turnover including the extirpation of a dominant conifer and a palm tree. The podocarp-dominated forests were replaced by a native but novel angiosperm-dominated forest. There is no modern analog of the prehuman forests on any northern New Zealand island, and those islands that are forested are dominated by angiosperms which are assumed to be climax forests. The pollen and DNA evidence for conifer- and palm-rich forests in the prehuman era challenge this climax forest assumption. Prehuman vegetation records can thus help to inform future restoration of degraded offshore islands by informing the likely rate and direction of successional change; helping to determine whether natural rates of succession are preferable to more costly replanting programs; and providing past species lists if
BAYESIAN BICLUSTERING FOR PATIENT STRATIFICATION.
Khakabimamaghani, Sahand; Ester, Martin
2016-01-01
The move from Empirical Medicine towards Personalized Medicine has attracted attention to Stratified Medicine (SM). Some methods are provided in the literature for patient stratification, which is the central task of SM, however, there are still significant open issues. First, it is still unclear if integrating different datatypes will help in detecting disease subtypes more accurately, and, if not, which datatype(s) are most useful for this task. Second, it is not clear how we can compare different methods of patient stratification. Third, as most of the proposed stratification methods are deterministic, there is a need for investigating the potential benefits of applying probabilistic methods. To address these issues, we introduce a novel integrative Bayesian biclustering method, called B2PS, for patient stratification and propose methods for evaluating the results. Our experimental results demonstrate the superiority of B2PS over a popular state-of-the-art method and the benefits of Bayesian approaches. Our results agree with the intuition that transcriptomic data forms a better basis for patient stratification than genomic data.
Putting Us on the Map: Remote Sensing Investigation of the Ancient Maya Landscape
Sever, Thomas L.; Saturno, William
2004-01-01
A common problem for archaeologists studying ancient settlement in the Maya Lowlands is overcoming the dense vegetation in order to obtain an accurate regional perspective of the presence of archaeological sites, their exact locations and their overall extents. Most often this is done by extensive ground surveys in which many individuals chop parallel paths through the vegetation in search of sites. Once a site is found an effort is made to mark its location on a regional map and to explore its perimeter. Obtaining locational information has been made dramatically easier in recent years with the advent of improved Global Positioning Systems (GPS), however the process of initial identification of sites and the determination of their borders is exceedingly labor intensive and has remained relatively unchanged since the beginning of settlement surveys in the region in the 1950 s. Currently, we are revolutionizing settlement survey in the Maya Lowlands by using remotely sensed data from IKONOS, Quickbird, and Eo 1, satellites as well as airborne AIRSAR radar data. The Ancient Maya built their cities, towns and even their smallest hamlets using excavated limestone and lime plasters. We propose that the decay of these structures provides a unique microenvironment for the growth of vegetation as the levels of moisture and nutrition within the ruins vary substantially from those in the surrounding forest. These microenvironmental differences on the ground are likewise represented by compositional differences in the forest canopy both in the species present and in leaf color (representing moisture/nutritional stress) visible through the analysis of high-resolution satellite data. In this way the detailed analysis of forest composition can reveal a detailed picture of the ancient settlements that lie beneath it. Preliminary examinations using this technique have been very successful and we are refining these techniques in order to efficiently comprehend the details of
US Forest Service National Forest System Roads
US Forest Service, Department of Agriculture — A map service on the www depicting existing National Forest System Roads (NFSR) that are under the jurisdiction of the U.S. Forest Service. Each feature represents a...
Salmona, Jordi; Salamolard, Marc; Fouillot, Damien; Ghestemme, Thomas; Larose, Jerry; Centon, Jean-François; Sousa, Vitor; Dawson, Deborah A.; Thebaud, Christophe; Chikhi, Lounès
2012-01-01
The exceptional biodiversity of Reunion Island is threatened by anthropogenic landscape changes that took place during the 350 years of human colonization. During this period the human population size increased dramatically from 250 to 800,000. The arrival of humans together with the development of agriculture, invasive species such as rats and cats, and deforestation has lead to the extinction of more than half of the original vertebrate species of the island. For the remaining species, significant work is being carried out to identify threats and conservation status, but little genetic work has been carried on some of the most endangered species. In the last decade theoretical studies have shown the ability of neutral genetic markers to infer the demographic history of endangered species and identify and date past population size changes (expansions or bottlenecks). In this study we provide the first genetic data on the critically endangered species the Reunion cuckoo-shrike Coracina newtoni. The Reunion cuckoo-shrike is a rare endemic forest bird surviving in a restricted 12-km2 area of forested uplands and mountains. The total known population consists of less than one hundred individuals out of which 45 were genotyped using seventeen polymorphic microsatellite loci. We found a limited level of genetic variability and weak population structure, probably due to the limited geographic distribution. Using Bayesian methods, we identified a strong decline in population size during the Holocene, most likely caused by an ancient climatic or volcanic event around 5000 years ago. This result was surprising as it appeared in apparent contradiction with the accepted theory of recent population collapse due to deforestation and predator introduction. These results suggest that new methods allowing for more complex demographic models are necessary to reconstruct the demographic history of populations. PMID:22916272
Almathen, Faisal; Charruau, Pauline; Mohandesan, Elmira; Mwacharo, Joram M; Orozco-terWengel, Pablo; Pitt, Daniel; Abdussamad, Abdussamad M; Uerpmann, Margarethe; Uerpmann, Hans-Peter; De Cupere, Bea; Magee, Peter; Alnaqeeb, Majed A; Salim, Bashir; Raziq, Abdul; Dessie, Tadelle; Abdelhadi, Omer M; Banabazi, Mohammad H; Al-Eknah, Marzook; Walzer, Chris; Faye, Bernard; Hofreiter, Michael; Peters, Joris; Hanotte, Olivier; Burger, Pamela A
2016-06-14
Dromedaries have been fundamental to the development of human societies in arid landscapes and for long-distance trade across hostile hot terrains for 3,000 y. Today they continue to be an important livestock resource in marginal agro-ecological zones. However, the history of dromedary domestication and the influence of ancient trading networks on their genetic structure have remained elusive. We combined ancient DNA sequences of wild and early-domesticated dromedary samples from arid regions with nuclear microsatellite and mitochondrial genotype information from 1,083 extant animals collected across the species' range. We observe little phylogeographic signal in the modern population, indicative of extensive gene flow and virtually affecting all regions except East Africa, where dromedary populations have remained relatively isolated. In agreement with archaeological findings, we identify wild dromedaries from the southeast Arabian Peninsula among the founders of the domestic dromedary gene pool. Approximate Bayesian computations further support the "restocking from the wild" hypothesis, with an initial domestication followed by introgression from individuals from wild, now-extinct populations. Compared with other livestock, which show a long history of gene flow with their wild ancestors, we find a high initial diversity relative to the native distribution of the wild ancestor on the Arabian Peninsula and to the brief coexistence of early-domesticated and wild individuals. This study also demonstrates the potential to retrieve ancient DNA sequences from osseous remains excavated in hot and dry desert environments.
Thomson, Vicki A; Lebrasseur, Ophélie; Austin, Jeremy J; Hunt, Terry L; Burney, David A; Denham, Tim; Rawlence, Nicolas J; Wood, Jamie R; Gongora, Jaime; Girdland Flink, Linus; Linderholm, Anna; Dobney, Keith; Larson, Greger; Cooper, Alan
2014-04-01
The human colonization of Remote Oceania remains one of the great feats of exploration in history, proceeding east from Asia across the vast expanse of the Pacific Ocean. Human commensal and domesticated species were widely transported as part of this diaspora, possibly as far as South America. We sequenced mitochondrial control region DNA from 122 modern and 22 ancient chicken specimens from Polynesia and Island Southeast Asia and used these together with Bayesian modeling methods to examine the human dispersal of chickens across this area. We show that specific techniques are essential to remove contaminating modern DNA from experiments, which appear to have impacted previous studies of Pacific chickens. In contrast to previous reports, we find that all ancient specimens and a high proportion of the modern chickens possess a group of unique, closely related haplotypes found only in the Pacific. This group of haplotypes appears to represent the authentic founding mitochondrial DNA chicken lineages transported across the Pacific, and allows the early dispersal of chickens across Micronesia and Polynesia to be modeled. Importantly, chickens carrying this genetic signature persist on several Pacific islands at high frequencies, suggesting that the original Polynesian chicken lineages may still survive. No early South American chicken samples have been detected with the diagnostic Polynesian mtDNA haplotypes, arguing against reports that chickens provide evidence of Polynesian contact with pre-European South America. Two modern specimens from the Philippines carry haplotypes similar to the ancient Pacific samples, providing clues about a potential homeland for the Polynesian chicken.
gargammel: a sequence simulator for ancient DNA.
Renaud, Gabriel; Hanghøj, Kristian; Willerslev, Eske; Orlando, Ludovic
2016-10-29
Ancient DNA has emerged as a remarkable tool to infer the history of extinct species and past populations. However, many of its characteristics, such as extensive fragmentation, damage and contamination, can influence downstream analyses. To help investigators measure how these could impact their analyses in silico, we have developed gargammel, a package that simulates ancient DNA fragments given a set of known reference genomes. Our package simulates the entire molecular process from post-mortem DNA fragmentation and DNA damage to experimental sequencing errors, and reproduces most common bias observed in ancient DNA datasets.
Endels, Patrick; Adriaens, Dries; Bekker, Renee M.; Knevel, Irma C.; Decocq, Guillaume; Hermy, Martin
2007-01-01
Questions: 1. Do relationships among forest plant traits correspond to dispersability-persistence trade-offs or other intertrait correlations found in the literature? 2. Do species groups delineated by trait similarity, differ in occurrence in ancient vs. new forests or isolated vs more continuous f
1992-01-01
NASA's Technology Applications Center, with other government and academic agencies, provided technology for improved resources management to the Cibola National Forest. Landsat satellite images enabled vegetation over a large area to be classified for purposes of timber analysis, wildlife habitat, range measurement and development of general vegetation maps.
Quantum Bayesianism at the Perimeter
Fuchs, Christopher A
2010-01-01
The author summarizes the Quantum Bayesian viewpoint of quantum mechanics, developed originally by C. M. Caves, R. Schack, and himself. It is a view crucially dependent upon the tools of quantum information theory. Work at the Perimeter Institute for Theoretical Physics continues the development and is focused on the hard technical problem of a finding a good representation of quantum mechanics purely in terms of probabilities, without amplitudes or Hilbert-space operators. The best candidate representation involves a mysterious entity called a symmetric informationally complete quantum measurement. Contemplation of it gives a way of thinking of the Born Rule as an addition to the rules of probability theory, applicable when one gambles on the consequences of interactions with physical systems. The article ends by outlining some directions for future work.
On Bayesian System Reliability Analysis
Energy Technology Data Exchange (ETDEWEB)
Soerensen Ringi, M.
1995-05-01
The view taken in this thesis is that reliability, the probability that a system will perform a required function for a stated period of time, depends on a person`s state of knowledge. Reliability changes as this state of knowledge changes, i.e. when new relevant information becomes available. Most existing models for system reliability prediction are developed in a classical framework of probability theory and they overlook some information that is always present. Probability is just an analytical tool to handle uncertainty, based on judgement and subjective opinions. It is argued that the Bayesian approach gives a much more comprehensive understanding of the foundations of probability than the so called frequentistic school. A new model for system reliability prediction is given in two papers. The model encloses the fact that component failures are dependent because of a shared operational environment. The suggested model also naturally permits learning from failure data of similar components in non identical environments. 85 refs.
Hedging Strategies for Bayesian Optimization
Brochu, Eric; de Freitas, Nando
2010-01-01
Bayesian optimization with Gaussian processes has become an increasingly popular tool in the machine learning community. It is efficient and can be used when very little is known about the objective function, making it popular in expensive black-box optimization scenarios. It is able to do this by sampling the objective using an acquisition function which incorporates the model's estimate of the objective and the uncertainty at any given point. However, there are several different parameterized acquisition functions in the literature, and it is often unclear which one to use. Instead of using a single acquisition function, we adopt a portfolio of acquisition functions governed by an online multi-armed bandit strategy. We describe the method, which we call GP-Hedge, and show that this method almost always outperforms the best individual acquisition function.
Nonparametric Bayesian inference in biostatistics
Müller, Peter
2015-01-01
As chapters in this book demonstrate, BNP has important uses in clinical sciences and inference for issues like unknown partitions in genomics. Nonparametric Bayesian approaches (BNP) play an ever expanding role in biostatistical inference from use in proteomics to clinical trials. Many research problems involve an abundance of data and require flexible and complex probability models beyond the traditional parametric approaches. As this book's expert contributors show, BNP approaches can be the answer. Survival Analysis, in particular survival regression, has traditionally used BNP, but BNP's potential is now very broad. This applies to important tasks like arrangement of patients into clinically meaningful subpopulations and segmenting the genome into functionally distinct regions. This book is designed to both review and introduce application areas for BNP. While existing books provide theoretical foundations, this book connects theory to practice through engaging examples and research questions. Chapters c...
Bayesian Inference with Optimal Maps
Moselhy, Tarek A El
2011-01-01
We present a new approach to Bayesian inference that entirely avoids Markov chain simulation, by constructing a map that pushes forward the prior measure to the posterior measure. Existence and uniqueness of a suitable measure-preserving map is established by formulating the problem in the context of optimal transport theory. We discuss various means of explicitly parameterizing the map and computing it efficiently through solution of an optimization problem, exploiting gradient information from the forward model when possible. The resulting algorithm overcomes many of the computational bottlenecks associated with Markov chain Monte Carlo. Advantages of a map-based representation of the posterior include analytical expressions for posterior moments and the ability to generate arbitrary numbers of independent posterior samples without additional likelihood evaluations or forward solves. The optimization approach also provides clear convergence criteria for posterior approximation and facilitates model selectio...
Multiview Bayesian Correlated Component Analysis
DEFF Research Database (Denmark)
Kamronn, Simon Due; Poulsen, Andreas Trier; Hansen, Lars Kai
2015-01-01
Correlated component analysis as proposed by Dmochowski, Sajda, Dias, and Parra (2012) is a tool for investigating brain process similarity in the responses to multiple views of a given stimulus. Correlated components are identified under the assumption that the involved spatial networks are iden......Correlated component analysis as proposed by Dmochowski, Sajda, Dias, and Parra (2012) is a tool for investigating brain process similarity in the responses to multiple views of a given stimulus. Correlated components are identified under the assumption that the involved spatial networks...... we denote Bayesian correlated component analysis, evaluates favorably against three relevant algorithms in simulated data. A well-established benchmark EEG data set is used to further validate the new model and infer the variability of spatial representations across multiple subjects....
Bayesian networks in educational assessment
Almond, Russell G; Steinberg, Linda S; Yan, Duanli; Williamson, David M
2015-01-01
Bayesian inference networks, a synthesis of statistics and expert systems, have advanced reasoning under uncertainty in medicine, business, and social sciences. This innovative volume is the first comprehensive treatment exploring how they can be applied to design and analyze innovative educational assessments. Part I develops Bayes nets’ foundations in assessment, statistics, and graph theory, and works through the real-time updating algorithm. Part II addresses parametric forms for use with assessment, model-checking techniques, and estimation with the EM algorithm and Markov chain Monte Carlo (MCMC). A unique feature is the volume’s grounding in Evidence-Centered Design (ECD) framework for assessment design. This “design forward” approach enables designers to take full advantage of Bayes nets’ modularity and ability to model complex evidentiary relationships that arise from performance in interactive, technology-rich assessments such as simulations. Part III describes ECD, situates Bayes nets as ...
Elvira, Clément; Dobigeon, Nicolas
2015-01-01
Sparse representations have proven their efficiency in solving a wide class of inverse problems encountered in signal and image processing. Conversely, enforcing the information to be spread uniformly over representation coefficients exhibits relevant properties in various applications such as digital communications. Anti-sparse regularization can be naturally expressed through an $\\ell_{\\infty}$-norm penalty. This paper derives a probabilistic formulation of such representations. A new probability distribution, referred to as the democratic prior, is first introduced. Its main properties as well as three random variate generators for this distribution are derived. Then this probability distribution is used as a prior to promote anti-sparsity in a Gaussian linear inverse problem, yielding a fully Bayesian formulation of anti-sparse coding. Two Markov chain Monte Carlo (MCMC) algorithms are proposed to generate samples according to the posterior distribution. The first one is a standard Gibbs sampler. The seco...
Bayesian Inference in Queueing Networks
Sutton, Charles
2010-01-01
Modern Web services, such as those at Google, Yahoo!, and Amazon, handle billions of requests per day on clusters of thousands of computers. Because these services operate under strict performance requirements, a statistical understanding of their performance is of great practical interest. Such services are modeled by networks of queues, where one queue models each of the individual computers in the system. A key challenge is that the data is incomplete, because recording detailed information about every request to a heavily used system can require unacceptable overhead. In this paper we develop a Bayesian perspective on queueing models in which the arrival and departure times that are not observed are treated as latent variables. Underlying this viewpoint is the observation that a queueing model defines a deterministic transformation between the data and a set of independent variables called the service times. With this viewpoint in hand, we sample from the posterior distribution over missing data and model...
A Bayesian Reflection on Surfaces
Directory of Open Access Journals (Sweden)
David R. Wolf
1999-10-01
Full Text Available Abstract: The topic of this paper is a novel Bayesian continuous-basis field representation and inference framework. Within this paper several problems are solved: The maximally informative inference of continuous-basis fields, that is where the basis for the field is itself a continuous object and not representable in a finite manner; the tradeoff between accuracy of representation in terms of information learned, and memory or storage capacity in bits; the approximation of probability distributions so that a maximal amount of information about the object being inferred is preserved; an information theoretic justification for multigrid methodology. The maximally informative field inference framework is described in full generality and denoted the Generalized Kalman Filter. The Generalized Kalman Filter allows the update of field knowledge from previous knowledge at any scale, and new data, to new knowledge at any other scale. An application example instance, the inference of continuous surfaces from measurements (for example, camera image data, is presented.
A Hierarchical Bayesian Model to Predict Self-Thinning Line for Chinese Fir in Southern China.
Directory of Open Access Journals (Sweden)
Xiongqing Zhang
Full Text Available Self-thinning is a dynamic equilibrium between forest growth and mortality at full site occupancy. Parameters of the self-thinning lines are often confounded by differences across various stand and site conditions. For overcoming the problem of hierarchical and repeated measures, we used hierarchical Bayesian method to estimate the self-thinning line. The results showed that the self-thinning line for Chinese fir (Cunninghamia lanceolata (Lamb.Hook. plantations was not sensitive to the initial planting density. The uncertainty of model predictions was mostly due to within-subject variability. The simulation precision of hierarchical Bayesian method was better than that of stochastic frontier function (SFF. Hierarchical Bayesian method provided a reasonable explanation of the impact of other variables (site quality, soil type, aspect, etc. on self-thinning line, which gave us the posterior distribution of parameters of self-thinning line. The research of self-thinning relationship could be benefit from the use of hierarchical Bayesian method.
Aiding the Interpretation of Ancient Documents
DEFF Research Database (Denmark)
Roued-Cunliffe, Henriette
How can Decision Support System (DSS) software aid the interpretation process involved in the reading of ancient documents? This paper discusses the development of a DSS prototype for the reading of ancient texts. In this context the term ‘ancient documents’ is used to describe mainly Greek...... and Latin texts and the term ‘scholars’ is used to describe readers of these documents (e.g. papyrologists, epigraphers, palaeographers). However, the results from this research can be applicable to many other texts ranging from Nordic runes to 18th Century love letters. In order to develop an appropriate...... tool it is important first to comprehend the interpretation process involved in reading ancient documents. This is not a linear process but rather a recursive process where the scholar moves between different levels of reading, such as ‘understanding the meaning of a character’ or ‘understanding...
AN INTERESTING CASE OF ANCIENT SCHWANNOMA
Directory of Open Access Journals (Sweden)
Binu
2015-01-01
Full Text Available INTRODUCTION : Schwannoma is a common benign tumour of nerve sheath. Degenerating type of schwannoma is called ancient schwannoma. Ancient schwannomas of scalp are rare and are often misdiagnosed as sebaceous cyst or dermoid cyst. CASE REPORT : We present a thirty two year old male presented with scalp swel ling of eight years duration. X - ray showed no intracranial extension. He underwent excision of the tumour and histopathology was reported as ancient schwannoma. DISCUSSION : Histopathologically , ancient schwannomas charecterised by cellular Antoni type A ar eas and less cellular Antoni type - B areas. 9 th , 7 th , 11 th , 5 th and 4 th cranial nerves are often affected and may be associated with multiple neuro fibramatosis (Von - Recklinghausen’s disease. Impact : Case is presented for its rarity and possible pre - operative misdiagnosis
Ancient Magnetic Reversals: Clues to the Geodynamo.
Hoffman, Kenneth A.
1988-01-01
Discusses the question posed by some that the earth's magnetic field may reverse. States that rocks magnetized by ancient fields may offer clues to the underlying reversal mechanism in the earth's core. (TW)
Bayesian models a statistical primer for ecologists
Hobbs, N Thompson
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 probabili
Compiling Relational Bayesian Networks for Exact Inference
DEFF Research Database (Denmark)
Jaeger, Manfred; Darwiche, Adnan; Chavira, Mark
2006-01-01
We describe in this paper a system for exact inference with relational Bayesian networks as defined in the publicly available PRIMULA tool. The system is based on compiling propositional instances of relational Bayesian networks into arithmetic circuits and then performing online inference...... by evaluating and differentiating these circuits in time linear in their size. We report on experimental results showing successful compilation and efficient inference on relational Bayesian networks, whose PRIMULA--generated propositional instances have thousands of variables, and whose jointrees have clusters...
Surgical history of ancient China: Part 2.
Fu, Louis
2010-03-01
In this second part of ancient Chinese surgical history, the practice of bone setting in China began around 3000 years ago. Throughout this period, significant progress was made, some highlights of which are cited. These methods, comparable with Western orthopaedic technique, are still being practised today. In conclusion, the possible reasons for the lack of advancement in operative surgery are discussed, within context of the cultural, social and religious background of ancient China.
Radiocarbon dating of ancient Japanese documents
Energy Technology Data Exchange (ETDEWEB)
Oda, H. [Nagoya Univ., Center for Chronological Research, Nagoya, Aichi (Japan)
2001-06-01
History is a reconstruction of past human activity, evidence of which is remained in the form of documents or relics. For the reconstruction of historic period, the radiocarbon dating of ancient documents provides important information. Although radiocarbon age is converted into calendar age with the calibration curve, the calibrated radiocarbon age is still different from the historical age when the document was written. The difference is known as 'old wood effect' for wooden cultural property. The discrepancy becomes more serious problem for recent sample which requires more accurate age determination. Using Tandetron accelerator mass spectrometer at Nagoya University, we have measured radiocarbon ages of Japanese ancient documents, sutras and printed books written dates of which are clarified from the paleographic standpoint. The purpose is to clarify the relation between calibrated radiocarbon age and historical age of ancient Japanese document by AMS radiocarbon dating. This paper reports 23 radiocarbon ages of ancient Japanese documents, sutras and printed books. The calibrated radiocarbon ages are in good agreement with the corresponding historical ages. It was shown by radiocarbon dating of the ancient documents that Japanese paper has little gap by 'old wood effect'; accordingly, ancient Japanese paper is a suitable sample for radiocarbon dating of recent historic period. (author)
The Diagnosis of Reciprocating Machinery by Bayesian Networks
Institute of Scientific and Technical Information of China (English)
无
2003-01-01
A Bayesian Network is a reasoning tool based on probability theory and has many advantages that other reasoning tools do not have. This paper discusses the basic theory of Bayesian networks and studies the problems in constructing Bayesian networks. The paper also constructs a Bayesian diagnosis network of a reciprocating compressor. The example helps us to draw a conclusion that Bayesian diagnosis networks can diagnose reciprocating machinery effectively.
Ancient Maya impacts on the Earth's surface: An Early Anthropocene analog?
Beach, Tim; Luzzadder-Beach, Sheryl; Cook, Duncan; Dunning, Nicholas; Kennett, Douglas J.; Krause, Samantha; Terry, Richard; Trein, Debora; Valdez, Fred
2015-09-01
The measure of the "Mayacene," a microcosm of the Early Anthropocene that occurred from c. 3000 to 1000 BP, comes from multiple Late Quaternary paleoenvironmental records. We synthesized the evidence for Maya impacts on climate, vegetation, hydrology and the lithosphere, from studies of soils, lakes, floodplains, wetlands and other ecosystems. Maya civilization had likely altered local to regional ecosystems and hydrology by the Preclassic Period (3000-1700 BP), but these impacts waned by 1000 BP. They altered ecosystems with vast urban and rural infrastructure that included thousands of reservoirs, wetland fields and canals, terraces, field ridges, and temples. Although there is abundant evidence that indicates the Maya altered their forests, even at the large urban complex of Tikal as much as 40% of the forest remained intact through the Classic period. Existing forests are still influenced by ancient Maya forest gardening, particularly by the large expanses of ancient stone structures, terraces, and wetland fields that form their substrates. A few studies suggest deforestation and other land uses probably also warmed and dried regional climate by the Classic Period (1700-1100 BP). A much larger body of research documents the Maya impacts on hydrology, in the form of dams, reservoirs, canals, eroded soils and urban design for runoff. Another metric of the "Mayacene" are paleosols, which contain chemical evidence for human occupation, revealed by high phosphorus concentrations and carbon isotope ratios of C4 species like maize in the C3-dominated tropical forest ecosystem. Paleosol sequences exhibit "Maya Clays," a facies that reflects a glut of rapidly eroded sediments that overlie pre-Maya paleosols. This stratigraphy is conspicuous in many dated soil profiles and marks the large-scale Maya transformation of the landscape in the Preclassic and Classic periods. Some of these also have increased phosphorous and carbon isotope evidence of C4 species. We synthesize
GPstuff: Bayesian Modeling with Gaussian Processes
Vanhatalo, J.; Riihimaki, J.; Hartikainen, J.; Jylänki, P.P.; Tolvanen, V.; Vehtari, A.
2013-01-01
The GPstuff toolbox is a versatile collection of Gaussian process models and computational tools required for Bayesian inference. The tools include, among others, various inference methods, sparse approximations and model assessment methods.
Bayesian Uncertainty Analyses Via Deterministic Model
Krzysztofowicz, R.
2001-05-01
Rational decision-making requires that the total uncertainty about a variate of interest (a predictand) be quantified in terms of a probability distribution, conditional on all available information and knowledge. Suppose the state-of-knowledge is embodied in a deterministic model, which is imperfect and outputs only an estimate of the predictand. Fundamentals are presented of three Bayesian approaches to producing a probability distribution of the predictand via any deterministic model. The Bayesian Processor of Output (BPO) quantifies the total uncertainty in terms of a posterior distribution, conditional on model output. The Bayesian Processor of Ensemble (BPE) quantifies the total uncertainty in terms of a posterior distribution, conditional on an ensemble of model output. The Bayesian Forecasting System (BFS) decomposes the total uncertainty into input uncertainty and model uncertainty, which are characterized independently and then integrated into a predictive distribution.
Picturing classical and quantum Bayesian inference
Coecke, Bob
2011-01-01
We introduce a graphical framework for Bayesian inference that is sufficiently general to accommodate not just the standard case but also recent proposals for a theory of quantum Bayesian inference wherein one considers density operators rather than probability distributions as representative of degrees of belief. The diagrammatic framework is stated in the graphical language of symmetric monoidal categories and of compact structures and Frobenius structures therein, in which Bayesian inversion boils down to transposition with respect to an appropriate compact structure. We characterize classical Bayesian inference in terms of a graphical property and demonstrate that our approach eliminates some purely conventional elements that appear in common representations thereof, such as whether degrees of belief are represented by probabilities or entropic quantities. We also introduce a quantum-like calculus wherein the Frobenius structure is noncommutative and show that it can accommodate Leifer's calculus of `cond...
Learning Bayesian networks for discrete data
Liang, Faming
2009-02-01
Bayesian networks have received much attention in the recent literature. In this article, we propose an approach to learn Bayesian networks using the stochastic approximation Monte Carlo (SAMC) algorithm. Our approach has two nice features. Firstly, it possesses the self-adjusting mechanism and thus avoids essentially the local-trap problem suffered by conventional MCMC simulation-based approaches in learning Bayesian networks. Secondly, it falls into the class of dynamic importance sampling algorithms; the network features can be inferred by dynamically weighted averaging the samples generated in the learning process, and the resulting estimates can have much lower variation than the single model-based estimates. The numerical results indicate that our approach can mix much faster over the space of Bayesian networks than the conventional MCMC simulation-based approaches. © 2008 Elsevier B.V. All rights reserved.
An Intuitive Dashboard for Bayesian Network Inference
Reddy, Vikas; Charisse Farr, Anna; Wu, Paul; Mengersen, Kerrie; Yarlagadda, Prasad K. D. V.
2014-03-01
Current Bayesian network software packages provide good graphical interface for users who design and develop Bayesian networks for various applications. However, the intended end-users of these networks may not necessarily find such an interface appealing and at times it could be overwhelming, particularly when the number of nodes in the network is large. To circumvent this problem, this paper presents an intuitive dashboard, which provides an additional layer of abstraction, enabling the end-users to easily perform inferences over the Bayesian networks. Unlike most software packages, which display the nodes and arcs of the network, the developed tool organises the nodes based on the cause-and-effect relationship, making the user-interaction more intuitive and friendly. In addition to performing various types of inferences, the users can conveniently use the tool to verify the behaviour of the developed Bayesian network. The tool has been developed using QT and SMILE libraries in C++.
ProFit: Bayesian galaxy fitting tool
Robotham, A. S. G.; Taranu, D.; Tobar, R.
2016-12-01
ProFit is a Bayesian galaxy fitting tool that uses the fast C++ image generation library libprofit (ascl:1612.003) and a flexible R interface to a large number of likelihood samplers. It offers a fully featured Bayesian interface to galaxy model fitting (also called profiling), using mostly the same standard inputs as other popular codes (e.g. GALFIT ascl:1104.010), but it is also able to use complex priors and a number of likelihoods.
Bayesian target tracking based on particle filter
Institute of Scientific and Technical Information of China (English)
无
2005-01-01
For being able to deal with the nonlinear or non-Gaussian problems, particle filters have been studied by many researchers. Based on particle filter, the extended Kalman filter (EKF) proposal function is applied to Bayesian target tracking. Markov chain Monte Carlo (MCMC) method, the resampling step, etc novel techniques are also introduced into Bayesian target tracking. And the simulation results confirm the improved particle filter with these techniques outperforms the basic one.
Variational Bayesian Approximation methods for inverse problems
Mohammad-Djafari, Ali
2012-09-01
Variational Bayesian Approximation (VBA) methods are recent tools for effective Bayesian computations. In this paper, these tools are used for inverse problems where the prior models include hidden variables and where where the estimation of the hyper parameters has also to be addressed. In particular two specific prior models (Student-t and mixture of Gaussian models) are considered and details of the algorithms are given.
Bayesian Modeling of a Human MMORPG Player
Synnaeve, Gabriel
2010-01-01
This paper describes an application of Bayesian programming to the control of an autonomous avatar in a multiplayer role-playing game (the example is based on World of Warcraft). We model a particular task, which consists of choosing what to do and to select which target in a situation where allies and foes are present. We explain the model in Bayesian programming and show how we could learn the conditional probabilities from data gathered during human-played sessions.
Bayesian Modeling of a Human MMORPG Player
Synnaeve, Gabriel; Bessière, Pierre
2011-03-01
This paper describes an application of Bayesian programming to the control of an autonomous avatar in a multiplayer role-playing game (the example is based on World of Warcraft). We model a particular task, which consists of choosing what to do and to select which target in a situation where allies and foes are present. We explain the model in Bayesian programming and show how we could learn the conditional probabilities from data gathered during human-played sessions.
Fuzzy Functional Dependencies and Bayesian Networks
Institute of Scientific and Technical Information of China (English)
LIU WeiYi(刘惟一); SONG Ning(宋宁)
2003-01-01
Bayesian networks have become a popular technique for representing and reasoning with probabilistic information. The fuzzy functional dependency is an important kind of data dependencies in relational databases with fuzzy values. The purpose of this paper is to set up a connection between these data dependencies and Bayesian networks. The connection is done through a set of methods that enable people to obtain the most information of independent conditions from fuzzy functional dependencies.
Yan, Donghui; Jordan, Michael I
2011-01-01
Inspired by Random Forests (RF) in the context of classification, we propose a new clustering ensemble method---Cluster Forests (CF). Geometrically, CF randomly probes a high-dimensional data cloud to obtain "good local clusterings" and then aggregates via spectral clustering to obtain cluster assignments for the whole dataset. The search for good local clusterings is guided by a cluster quality measure $\\kappa$. CF progressively improves each local clustering in a fashion that resembles the tree growth in RF. Empirical studies on several real-world datasets under two different performance metrics show that CF compares favorably to its competitors. Theoretical analysis shows that the $\\kappa$ criterion is shown to grow each local clustering in a desirable way---it is "noise-resistant." A closed-form expression is obtained for the mis-clustering rate of spectral clustering under a perturbation model, which yields new insights into some aspects of spectral clustering.
Philosophy and the practice of Bayesian statistics.
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.
Joint hierarchical models for sparsely sampled high-dimensional LiDAR and forest variables
Finley, Andrew O.; Banerjee, Sudipto; Zhou, Yuzhen; Cook, Bruce D; Babcock, Chad
2016-01-01
Recent advancements in remote sensing technology, specifically Light Detection and Ranging (LiDAR) sensors, provide the data needed to quantify forest characteristics at a fine spatial resolution over large geographic domains. From an inferential standpoint, there is interest in prediction and interpolation of the often sparsely sampled and spatially misaligned LiDAR signals and forest variables. We propose a fully process-based Bayesian hierarchical model for above ground biomass (AGB) and L...
DEFF Research Database (Denmark)
Jagger, Pamela; Luckert, Martin K.; Duchelle, Amy E.
2014-01-01
We explore the relationship between tenure and forest income in 271 villages throughout the tropics. We find that state-owned forests generate more forest income than private and community-owned forests both per household and per hectare. We explore whether forest income varies according to the e...
Forests and Forest Cover - Ozark National Forest Service Compartments (polygon)
NSGIC GIS Inventory (aka Ramona) — Ozark - St. Francis National Forests stand inventory data for vegetation, maintained in polygon format. Compartment is defined as a division of forest for purposes...
Forests and Forest Cover - MDC_NaturalForestCommunity
NSGIC GIS Inventory (aka Ramona) — A point feature class of NFCs - Natural Forest Communities. Natural Forest Community shall mean all stands of trees (including their associated understory) which...
Bayesian demography 250 years after Bayes.
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.
Bayesian inference for OPC modeling
Burbine, Andrew; Sturtevant, John; Fryer, David; Smith, Bruce W.
2016-03-01
The use of optical proximity correction (OPC) demands increasingly accurate models of the photolithographic process. Model building and inference techniques in the data science community have seen great strides in the past two decades which make better use of available information. This paper aims to demonstrate the predictive power of Bayesian inference as a method for parameter selection in lithographic models by quantifying the uncertainty associated with model inputs and wafer data. Specifically, the method combines the model builder's prior information about each modelling assumption with the maximization of each observation's likelihood as a Student's t-distributed random variable. Through the use of a Markov chain Monte Carlo (MCMC) algorithm, a model's parameter space is explored to find the most credible parameter values. During parameter exploration, the parameters' posterior distributions are generated by applying Bayes' rule, using a likelihood function and the a priori knowledge supplied. The MCMC algorithm used, an affine invariant ensemble sampler (AIES), is implemented by initializing many walkers which semiindependently explore the space. The convergence of these walkers to global maxima of the likelihood volume determine the parameter values' highest density intervals (HDI) to reveal champion models. We show that this method of parameter selection provides insights into the data that traditional methods do not and outline continued experiments to vet the method.
Bayesian analysis of cosmic structures
Kitaura, Francisco-Shu
2011-01-01
We revise the Bayesian inference steps required to analyse the cosmological large-scale structure. Here we make special emphasis in the complications which arise due to the non-Gaussian character of the galaxy and matter distribution. In particular we investigate the advantages and limitations of the Poisson-lognormal model and discuss how to extend this work. With the lognormal prior using the Hamiltonian sampling technique and on scales of about 4 h^{-1} Mpc we find that the over-dense regions are excellent reconstructed, however, under-dense regions (void statistics) are quantitatively poorly recovered. Contrary to the maximum a posteriori (MAP) solution which was shown to over-estimate the density in the under-dense regions we obtain lower densities than in N-body simulations. This is due to the fact that the MAP solution is conservative whereas the full posterior yields samples which are consistent with the prior statistics. The lognormal prior is not able to capture the full non-linear regime at scales ...
Variation in rainfall interception along a forest succession gradient
Zimmermann, Beate; Zimmermann, Alexander; van Breugel, Michiel
2013-04-01
Rainfall interception by forest canopies reduces the water influx to the forest floor. When forests are replaced by pasture, the process of canopy interception temporarily stops until a new forest develops on abandoned pasture land. Modern land-cover change typically involves regrowing forests but the relation between forest succession and canopy interception is hardly understood. This lack of knowledge is unfortunate because rainfall interception plays an important role in regional water cycles and needs to be quantified for modeling purposes. To help close the knowledge gap, we designed a chronosequence study of throughfall along a secondary succession gradient in a tropical forest region of Panama. The investigated gradient comprises 20 natural forest patches regrowing for 1 up to about 130 years. We sampled each patch with a minimum of 20 funnel-type throughfall collectors over a continuous two-month period that had nearly 900 mm of rain. At the same time and locations, we acquired forest structure data based on DBH measurements of all trees > 1 cm DBH, identified all tree species, and took hemispherical photographs to calculate canopy openness. We used Bayesian Model Averaging (BMA) to identify those vegetation parameters that have the strongest influence on interception variation. Interception loss increased with forest age from 0 to nearly 200 mm of the total rainfall input (0 - 20 %), with the steepest rise occurring within the first decade of forest succession. Parsimonious models which contain canopy openness and basal area or stem density of stems smaller than 5 cm DBH are favored about more complex models. Leave-one-out cross validation revealed that our BMA approach can be used to predict interception with an RMSE of 5 %. Based on our results we argue that hydrological modeling exercises should account for variation in interception due to succession stage, which is possible e.g. by using a statistical approach to relate interception estimates to forest
Evidence for Ancient Mesoamerican Earthquakes
Kovach, R. L.; Garcia, B.
2001-12-01
Evidence for past earthquake damage at Mesoamerican ruins is often overlooked because of the invasive effects of tropical vegetation and is usually not considered as a casual factor when restoration and reconstruction of many archaeological sites are undertaken. Yet the proximity of many ruins to zones of seismic activity would argue otherwise. Clues as to the types of damage which should be soughtwere offered in September 1999 when the M = 7.5 Oaxaca earthquake struck the ruins of Monte Alban, Mexico, where archaeological renovations were underway. More than 20 structures were damaged, 5 of them seriously. Damage features noted were walls out of plumb, fractures in walls, floors, basal platforms and tableros, toppling of columns, and deformation, settling and tumbling of walls. A Modified Mercalli Intensity of VII (ground accelerations 18-34 %b) occurred at the site. Within the diffuse landward extension of the Caribbean plate boundary zone M = 7+ earthquakes occur with repeat times of hundreds of years arguing that many Maya sites were subjected to earthquakes. Damage to re-erected and reinforced stelae, walls, and buildings were witnessed at Quirigua, Guatemala, during an expedition underway when then 1976 M = 7.5 Guatemala earthquake on the Motagua fault struck. Excavations also revealed evidence (domestic pttery vessels and skeleton of a child crushed under fallen walls) of an ancient earthquake occurring about the teim of the demise and abandonment of Quirigua in the late 9th century. Striking evidence for sudden earthquake building collapse at the end of the Mayan Classic Period ~A.D. 889 was found at Benque Viejo (Xunantunich), Belize, located 210 north of Quirigua. It is argued that a M = 7.5 to 7.9 earthquake at the end of the Maya Classic period centered in the vicinity of the Chixoy-Polochic and Motagua fault zones cound have produced the contemporaneous earthquake damage to the above sites. As a consequences this earthquake may have accelerated the
Genetic diversity among ancient Nordic populations.
Melchior, Linea; Lynnerup, Niels; Siegismund, Hans R; Kivisild, Toomas; Dissing, Jørgen
2010-01-01
Using established criteria for work with fossil DNA we have analysed mitochondrial DNA from 92 individuals from 18 locations in Denmark ranging in time from the Mesolithic to the Medieval Age. Unequivocal assignment of mtDNA haplotypes was possible for 56 of the ancient individuals; however, the success rate varied substantially between sites; the highest rates were obtained with untouched, freshly excavated material, whereas heavy handling, archeological preservation and storage for many years influenced the ability to obtain authentic endogenic DNA. While the nucleotide diversity at two locations was similar to that among extant Danes, the diversity at four sites was considerably higher. This supports previous observations for ancient Britons. The overall occurrence of haplogroups did not deviate from extant Scandinavians, however, haplogroup I was significantly more frequent among the ancient Danes (average 13%) than among extant Danes and Scandinavians (approximately 2.5%) as well as among other ancient population samples reported. Haplogroup I could therefore have been an ancient Southern Scandinavian type "diluted" by later immigration events. Interestingly, the two Neolithic samples (4,200 YBP, Bell Beaker culture) that were typed were haplogroup U4 and U5a, respectively, and the single Bronze Age sample (3,300-3,500 YBP) was haplogroup U4. These two haplogroups have been associated with the Mesolithic populations of Central and Northern Europe. Therefore, at least for Southern Scandinavia, our findings do not support a possible replacement of a haplogroup U dominated hunter-gatherer population by a more haplogroup diverse Neolithic Culture.
Schneider, Claudio Albert
This research is aimed at the solution of two common but still largely unsolved problems in the classification of remotely sensed data: (1) Classification accuracy of remotely sensed data decreases significantly in mountainous terrain, where topography strongly influences the spectral response of the features on the ground; and (2) when attempting to obtain more detailed classifications, e.g. forest cover types or species, rather than just broad categories of forest such as coniferous or deciduous, the accuracy of the classification generally decreases significantly. The main objective of the study was to develop a widely applicable and efficient classification procedure for mapping forest and other cover types in mountainous terrain, using an integrated GIS/neural network/Bayesian classification approach. The performance of this new technique was compared to a standard supervised Maximum Likelihood classification technique, a "conventional" Bayesian/Maximum Likelihood classification, and to a "conventional" neural network classifier. Results indicate a considerable improvement of the new technique over the standard Maximum Likelihood classification technique, as well as a better accuracy than the "conventional" Bayesian/Maximum Likelihood classifier (13.08 percent improvement in overall accuracy), but the "conventional" neural network classifiers outperformed all the techniques compared in this study, with an overall accuracy improvement of 15.94 percent as compared to the standard Maximum Likelihood classifier (from 46.77 percent to 62.71 percent). However, the overall accuracies of all the classification techniques compared in this study were relative low. It is believed that this was caused by problems related to the inadequacy of the reference data. On the other hand, the results also indicate the need to develop a different sampling design to more effectively cover the variability across all the parameters needed by the neural network classification technique
Will Passive Protection Save Congo Forests?
Directory of Open Access Journals (Sweden)
Gillian L Galford
Full Text Available Central Africa's tropical forests are among the world's largest carbon reserves. Historically, they have experienced low rates of deforestation. Pressures to clear land are increasing due to development of infrastructure and livelihoods, foreign investment in agriculture, and shifting land use management, particularly in the Democratic Republic of Congo (DRC. The DRC contains the greatest area of intact African forests. These store approximately 22 billion tons of carbon in aboveground live biomass, yet only 10% are protected. Can the status quo of passive protection - forest management that is low or nonexistent - ensure the preservation of this forest and its carbon? We have developed the SimCongo model to simulate changes in land cover and land use based on theorized policy scenarios from 2010 to 2050. Three scenarios were examined: the first (Historical Trends assumes passive forest protection; the next (Conservation posits active protection of forests and activation of the national REDD+ action plan, and the last (Agricultural Development assumes increased agricultural activities in forested land with concomitant increased deforestation. SimCongo is a cellular automata model based on Bayesian statistical methods tailored for the DRC, built with the Dinamica-EGO platform. The model is parameterized and validated with deforestation observations from the past and runs the scenarios from 2010 through 2050 with a yearly time step. We estimate the Historical Trends trajectory will result in average emissions of 139 million t CO2 year-1 by the 2040s, a 15% increase over current emissions. The Conservation scenario would result in 58% less clearing than Historical Trends and would conserve carbon-dense forest and woodland savanna areas. The Agricultural Development scenario leads to emissions of 212 million t CO2 year-1 by the 2040s. These scenarios are heuristic examples of policy's influence on forest conservation and carbon storage. Our results
Will Passive Protection Save Congo Forests?
Galford, Gillian L; Soares-Filho, Britaldo S; Sonter, Laura J; Laporte, Nadine
2015-01-01
Central Africa's tropical forests are among the world's largest carbon reserves. Historically, they have experienced low rates of deforestation. Pressures to clear land are increasing due to development of infrastructure and livelihoods, foreign investment in agriculture, and shifting land use management, particularly in the Democratic Republic of Congo (DRC). The DRC contains the greatest area of intact African forests. These store approximately 22 billion tons of carbon in aboveground live biomass, yet only 10% are protected. Can the status quo of passive protection - forest management that is low or nonexistent - ensure the preservation of this forest and its carbon? We have developed the SimCongo model to simulate changes in land cover and land use based on theorized policy scenarios from 2010 to 2050. Three scenarios were examined: the first (Historical Trends) assumes passive forest protection; the next (Conservation) posits active protection of forests and activation of the national REDD+ action plan, and the last (Agricultural Development) assumes increased agricultural activities in forested land with concomitant increased deforestation. SimCongo is a cellular automata model based on Bayesian statistical methods tailored for the DRC, built with the Dinamica-EGO platform. The model is parameterized and validated with deforestation observations from the past and runs the scenarios from 2010 through 2050 with a yearly time step. We estimate the Historical Trends trajectory will result in average emissions of 139 million t CO2 year-1 by the 2040s, a 15% increase over current emissions. The Conservation scenario would result in 58% less clearing than Historical Trends and would conserve carbon-dense forest and woodland savanna areas. The Agricultural Development scenario leads to emissions of 212 million t CO2 year-1 by the 2040s. These scenarios are heuristic examples of policy's influence on forest conservation and carbon storage. Our results suggest that 1
An introduction to Gaussian Bayesian networks.
Grzegorczyk, Marco
2010-01-01
The extraction of regulatory networks and pathways from postgenomic data is important for drug -discovery and development, as the extracted pathways reveal how genes or proteins regulate each other. Following up on the seminal paper of Friedman et al. (J Comput Biol 7:601-620, 2000), Bayesian networks have been widely applied as a popular tool to this end in systems biology research. Their popularity stems from the tractability of the marginal likelihood of the network structure, which is a consistent scoring scheme in the Bayesian context. This score is based on an integration over the entire parameter space, for which highly expensive computational procedures have to be applied when using more complex -models based on differential equations; for example, see (Bioinformatics 24:833-839, 2008). This chapter gives an introduction to reverse engineering regulatory networks and pathways with Gaussian Bayesian networks, that is Bayesian networks with the probabilistic BGe scoring metric [see (Geiger and Heckerman 235-243, 1995)]. In the BGe model, the data are assumed to stem from a Gaussian distribution and a normal-Wishart prior is assigned to the unknown parameters. Gaussian Bayesian network methodology for analysing static observational, static interventional as well as dynamic (observational) time series data will be described in detail in this chapter. Finally, we apply these Bayesian network inference methods (1) to observational and interventional flow cytometry (protein) data from the well-known RAF pathway to evaluate the global network reconstruction accuracy of Bayesian network inference and (2) to dynamic gene expression time series data of nine circadian genes in Arabidopsis thaliana to reverse engineer the unknown regulatory network topology for this domain.
Twins in Ancient Greece: a synopsis.
Malamitsi-Puchner, Ariadne
2016-01-01
This brief outline associates twins with several aspects of life in Ancient Greece. In Greek mythology twins caused ambivalent reactions and were believed to have ambivalent feelings for each other. Very often, they were viewed as the representatives of the dualistic nature of the universe. Heteropaternal superfecundation, which dominates in ancient myths, explains on one hand, the god-like qualities and, on the other hand, the mortal nature of many twins. An assumption is presented that legends referring to twins might reflect the territorial expansions of Ancient Greeks in Northern Mediterranean, around the Black Sea, in Asia Minor, as well as North East Africa. In conclusion, in Greek antiquity, twins have been used as transitional figures between myth and reality.
Genetic diversity among ancient Nordic populations
DEFF Research Database (Denmark)
Melchior, Linea Cecilie; Lynnerup, Niels; Siegismund, Hans Redlef
2010-01-01
the ancient Danes (average 13%) than among extant Danes and Scandinavians ( approximately 2.5%) as well as among other ancient population samples reported. Haplogroup I could therefore have been an ancient Southern Scandinavian type "diluted" by later immigration events. Interestingly, the two Neolithic...... samples (4,200 YBP, Bell Beaker culture) that were typed were haplogroup U4 and U5a, respectively, and the single Bronze Age sample (3,300-3,500 YBP) was haplogroup U4. These two haplogroups have been associated with the Mesolithic populations of Central and Northern Europe. Therefore, at least...... for Southern Scandinavia, our findings do not support a possible replacement of a haplogroup U dominated hunter-gatherer population by a more haplogroup diverse Neolithic Culture....
The Vindolanda Tablets and the Ancient Economy
DEFF Research Database (Denmark)
Evers, Kasper Grønlund
, a model is outlined which takes into account the different economic behaviours revealed by the tablets and attempts to fit them together into one coherent, economic system, whilst also relating the activities to questions of scale in the ancient economy; moreover, the conclusions drawn in the study......, the aim is to investigate how best to comprehend the economic system attested at Vindolanda and to consider the wider implications for studies of the ancient economy in general. This is accomplished by a three-step approach: first, the nature of the Vindolandan evidence is assessed, and the state...... of research on both studies of the ancient economy and the economy of early Roman Britain is accounted for, so as to highlight the value of the Vindolanda Tablets and lay the ground for the interpretations which follow. Secondly, the economic activities attested by the tablets are analysed in terms of market...
Palaeoparasitology - Human Parasites in Ancient Material.
Araújo, Adauto; Reinhard, Karl; Ferreira, Luiz Fernando
2015-01-01
Parasite finds in ancient material launched a new field of science: palaeoparasitology. Ever since the pioneering studies, parasites were identified in archaeological and palaeontological remains, some preserved for millions of years by fossilization. However, the palaeoparasitological record consists mainly of parasites found specifically in human archaeological material, preserved in ancient occupation sites, from prehistory until closer to 2015. The results include some helminth intestinal parasites still commonly found in 2015, such as Ascaris lumbricoides, Trichuris trichiura and hookworms, besides others such as Amoebidae and Giardia intestinalis, as well as viruses, bacteria, fungi and arthropods. These parasites as a whole provide important data on health, diet, climate and living conditions among ancient populations. This chapter describes the principal findings and their importance for knowledge on the origin and dispersal of infectious diseases.
The biochemistry of ancient DNA in bone.
Tuross, N
1994-06-15
The amount of DNA in ancient bone was determined by ethidium bromide staining after the removal of the potent Taq inhibitor, fulvic acid. A complete decalcification and a perfusion protocol were used to recover DNA from bone. A variety of purification techniques including molecular sieve, hydroxyapatite binding and 'Magic' preparations yielded DNA that spanned from 3.4 micrograms/g of bone to below detectable limits. Fulvic acid was shown to interfere with the quantification of DNA derived from ancient human skeletal material one hundred to over seven thousand years old. Scanning UV in the 300 to 230 nm range is a simple and sensitive technique for documenting fulvic acid contamination in ancient bone extracts.
Bayesian inference for multivariate point processes observed at sparsely distributed times
DEFF Research Database (Denmark)
Rasmussen, Jakob Gulddahl; Møller, Jesper; Aukema, B.H.;
normalizing constants. We discuss the advantages and disadvantages of using continuous time processes compared to discrete time processes in the setting of the present paper as well as other spatial-temporal situations. Keywords: Bark beetle, conditional intensity, forest entomology, Markov chain Monte Carlo......We consider statistical and computational aspects of simulation-based Bayesian inference for a multivariate point process which is only observed at sparsely distributed times. For specicity we consider a particular data set which has earlier been analyzed by a discrete time model involving unknown...
Pectus excavatum in mummies from ancient Egypt.
Kwiecinski, Jakub
2016-12-01
Pectus excavatum is one of the common congenital anomalies, yet there seems to be a suspicious absence of any cases or descriptions of this deformity from antiquity. This could represent a real change in disease prevalence but is more likely just due to an inadequate reporting in medico-historical literature. The current study reviews reports of computed tomography (CT) scans of 217 ancient Egyptian mummies, revealing 3 presumed cases of this deformity. Therefore, pectus excavatum was in fact present already in ancient times, with prevalence roughly similar to the modern one.
Symmetries in Images on Ancient Seals
Sparavigna, Amelia
2008-01-01
In this paper, we discuss the presence of symmetries in images engraved on ancient seals, in particular on stamp seals. Mainly used to secure the containers from tampering and for owner's identification, these objects appeared during the 5th millennium BC in Mesopotamia. Usually the seals were engraved with simple images, suitable to communicate an immediate information. Rotational symmetries are already displayed by the most ancient stamp seals, whose images reach a quasi-perfect symmetry in their small circular or ovoid spaces. Bilateral symmetries are quite common in Egyptian scarab seals.
Automatic indexing and reformulation of ancient dictionaries
Belaïd, Abdel; Turcan, Isabelle; Pierrel, Jean-Marie; Belaïd, Yolande; Rangoni, Yves; Hadjamar, Hassen
2004-01-01
International audience; This paper is related to automatic indexing and reformu-lation of ancient dictionaries. The objective is to make easy the access to ancient printed documents from XVI to XIX century for a diversified public (historians, scien-tists, librarians, etc.). Since the facsimile mode is insuffi-cient, the aim is to look further for the use of the index-ing based on the formal structure representative of some contents in order to optimize their exploration. Starting from a firs...
Mythological Emblem Glyphs of Ancient Maya Kings
DEFF Research Database (Denmark)
Helmke, Christophe
2012-01-01
Heinrich Berlin’s identification of Emblem Glyphs in 1958 has rightly been hailed as one of the major breakthroughs in the decipherment of ancient Maya writing. Although their exact function and meaning was unclear at the time, these are now recognized to serve as exalted regal titles that incorp......Heinrich Berlin’s identification of Emblem Glyphs in 1958 has rightly been hailed as one of the major breakthroughs in the decipherment of ancient Maya writing. Although their exact function and meaning was unclear at the time, these are now recognized to serve as exalted regal titles...
A Modern Take on an Ancient Master
Institute of Scientific and Technical Information of China (English)
无
2011-01-01
A new English translation of The Analects gives a fresh perspective on Confucius and his philosophy by Zan Jifang Confucius(551-491 B.C.) is generally viewed as ancient China’s foremost thinker.His philosophy is probably best catalogued in The Analects,a record of the sage’s wisdom compiled after his death.This Confucian classic provides a shortcut to understanding Chinese culture. A new English edition of the ancient classic(published by the Foreign Languages Press)
Evolution of medical education in ancient Greece
Institute of Scientific and Technical Information of China (English)
Emmanouil Pikoulis; Pavlos Msaouel; Efthimios D Avgerinos; Sofia Anagnostopoulou; Christos Tsigris
2008-01-01
@@ The study of ancient Greece is essential for the proper understanding of the evolution of modem Western medicine.An important innovation of classical Greek medicine was the development of a body of medical theory associated with natural philosophy,i.e.a strong secular tradition of free enquiry,or what would now be called "science" (Επιστημη).Medical education rests upon the ancient Greek foundations and its history remains a fascinating topic for modem physicians and medical teachers.
Bayesian Calibration of Microsimulation Models.
Rutter, Carolyn M; Miglioretti, Diana L; Savarino, James E
2009-12-01
Microsimulation models that describe disease processes synthesize information from multiple sources and can be used to estimate the effects of screening and treatment on cancer incidence and mortality at a population level. These models are characterized by simulation of individual event histories for an idealized population of interest. Microsimulation models are complex and invariably include parameters that are not well informed by existing data. Therefore, a key component of model development is the choice of parameter values. Microsimulation model parameter values are selected to reproduce expected or known results though the process of model calibration. Calibration may be done by perturbing model parameters one at a time or by using a search algorithm. As an alternative, we propose a Bayesian method to calibrate microsimulation models that uses Markov chain Monte Carlo. We show that this approach converges to the target distribution and use a simulation study to demonstrate its finite-sample performance. Although computationally intensive, this approach has several advantages over previously proposed methods, including the use of statistical criteria to select parameter values, simultaneous calibration of multiple parameters to multiple data sources, incorporation of information via prior distributions, description of parameter identifiability, and the ability to obtain interval estimates of model parameters. We develop a microsimulation model for colorectal cancer and use our proposed method to calibrate model parameters. The microsimulation model provides a good fit to the calibration data. We find evidence that some parameters are identified primarily through prior distributions. Our results underscore the need to incorporate multiple sources of variability (i.e., due to calibration data, unknown parameters, and estimated parameters and predicted values) when calibrating and applying microsimulation models.
Dimensionality reduction in Bayesian estimation algorithms
Directory of Open Access Journals (Sweden)
G. W. Petty
2013-03-01
Full Text Available An idealized synthetic database loosely resembling 3-channel passive microwave observations of precipitation against a variable background is employed to examine the performance of a conventional Bayesian retrieval algorithm. For this dataset, algorithm performance is found to be poor owing to an irreconcilable conflict between the need to find matches in the dependent database versus the need to exclude inappropriate matches. It is argued that the likelihood of such conflicts increases sharply with the dimensionality of the observation space of real satellite sensors, which may utilize 9 to 13 channels to retrieve precipitation, for example. An objective method is described for distilling the relevant information content from N real channels into a much smaller number (M of pseudochannels while also regularizing the background (geophysical plus instrument noise component. The pseudochannels are linear combinations of the original N channels obtained via a two-stage principal component analysis of the dependent dataset. Bayesian retrievals based on a single pseudochannel applied to the independent dataset yield striking improvements in overall performance. The differences between the conventional Bayesian retrieval and reduced-dimensional Bayesian retrieval suggest that a major potential problem with conventional multichannel retrievals – whether Bayesian or not – lies in the common but often inappropriate assumption of diagonal error covariance. The dimensional reduction technique described herein avoids this problem by, in effect, recasting the retrieval problem in a coordinate system in which the desired covariance is lower-dimensional, diagonal, and unit magnitude.
Bayesian modeling of flexible cognitive control.
Jiang, Jiefeng; Heller, Katherine; Egner, Tobias
2014-10-01
"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.
Multi-Fraction Bayesian Sediment Transport Model
Directory of Open Access Journals (Sweden)
Mark L. Schmelter
2015-09-01
Full Text Available A Bayesian approach to sediment transport modeling can provide a strong basis for evaluating and propagating model uncertainty, which can be useful in transport applications. Previous work in developing and applying Bayesian sediment transport models used a single grain size fraction or characterized the transport of mixed-size sediment with a single characteristic grain size. Although this approach is common in sediment transport modeling, it precludes the possibility of capturing processes that cause mixed-size sediments to sort and, thereby, alter the grain size available for transport and the transport rates themselves. This paper extends development of a Bayesian transport model from one to k fractional dimensions. The model uses an existing transport function as its deterministic core and is applied to the dataset used to originally develop the function. The Bayesian multi-fraction model is able to infer the posterior distributions for essential model parameters and replicates predictive distributions of both bulk and fractional transport. Further, the inferred posterior distributions are used to evaluate parametric and other sources of variability in relations representing mixed-size interactions in the original model. Successful OPEN ACCESS J. Mar. Sci. Eng. 2015, 3 1067 development of the model demonstrates that Bayesian methods can be used to provide a robust and rigorous basis for quantifying uncertainty in mixed-size sediment transport. Such a method has heretofore been unavailable and allows for the propagation of uncertainty in sediment transport applications.
Tactile length contraction as Bayesian inference.
Tong, Jonathan; Ngo, Vy; Goldreich, Daniel
2016-08-01
To perceive, the brain must interpret stimulus-evoked neural activity. This is challenging: The stochastic nature of the neural response renders its interpretation inherently uncertain. Perception would be optimized if the brain used Bayesian inference to interpret inputs in light of expectations derived from experience. Bayesian inference would improve perception on average but cause illusions when stimuli violate expectation. Intriguingly, tactile, auditory, and visual perception are all prone to length contraction illusions, characterized by the dramatic underestimation of the distance between punctate stimuli delivered in rapid succession; the origin of these illusions has been mysterious. We previously proposed that length contraction illusions occur because the brain interprets punctate stimulus sequences using Bayesian inference with a low-velocity expectation. A novel prediction of our Bayesian observer model is that length contraction should intensify if stimuli are made more difficult to localize. Here we report a tactile psychophysical study that tested this prediction. Twenty humans compared two distances on the forearm: a fixed reference distance defined by two taps with 1-s temporal separation and an adjustable comparison distance defined by two taps with temporal separation t ≤ 1 s. We observed significant length contraction: As t was decreased, participants perceived the two distances as equal only when the comparison distance was made progressively greater than the reference distance. Furthermore, the use of weaker taps significantly enhanced participants' length contraction. These findings confirm the model's predictions, supporting the view that the spatiotemporal percept is a best estimate resulting from a Bayesian inference process.
Bayesian modeling of flexible cognitive control
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
Computationally efficient Bayesian inference for inverse problems.
Energy Technology Data Exchange (ETDEWEB)
Marzouk, Youssef M.; Najm, Habib N.; Rahn, Larry A.
2007-10-01
Bayesian statistics provides a foundation for inference from noisy and incomplete data, a natural mechanism for regularization in the form of prior information, and a quantitative assessment of uncertainty in the inferred results. Inverse problems - representing indirect estimation of model parameters, inputs, or structural components - can be fruitfully cast in this framework. Complex and computationally intensive forward models arising in physical applications, however, can render a Bayesian approach prohibitive. This difficulty is compounded by high-dimensional model spaces, as when the unknown is a spatiotemporal field. We present new algorithmic developments for Bayesian inference in this context, showing strong connections with the forward propagation of uncertainty. In particular, we introduce a stochastic spectral formulation that dramatically accelerates the Bayesian solution of inverse problems via rapid evaluation of a surrogate posterior. We also explore dimensionality reduction for the inference of spatiotemporal fields, using truncated spectral representations of Gaussian process priors. These new approaches are demonstrated on scalar transport problems arising in contaminant source inversion and in the inference of inhomogeneous material or transport properties. We also present a Bayesian framework for parameter estimation in stochastic models, where intrinsic stochasticity may be intermingled with observational noise. Evaluation of a likelihood function may not be analytically tractable in these cases, and thus several alternative Markov chain Monte Carlo (MCMC) schemes, operating on the product space of the observations and the parameters, are introduced.
U.S. Environmental Protection Agency — Forests provide economic and ecological value. High percentages of forest cover (FORPCTFuture) generally indicate healthier ecosystems and cleaner surface water....
U.S. Environmental Protection Agency — Forests provide economic and ecological value. High percentages of forest cover (FORPCT) generally indicate healthier ecosystems and cleaner surface water. More...
US Forest Service Administrative Forest Boundaries
US Forest Service, Department of Agriculture — A map service on the www depicting all the National Forest System lands administered by an unit. These areas encompasse private lands, other governmental agency...
US Forest Service Healthy Forest Restoration Act
US Forest Service, Department of Agriculture — A map service on the www depicting areas designated within National Forest System Lands, in 37 States, that are eligible for insect and disease treatments under...
US Forest Service National Forest System Trails
US Forest Service, Department of Agriculture — A map service on the world wide web that depicts National Forest Service trails that have been approved for publication. This service is used internally and...
Directory of Open Access Journals (Sweden)
S Elizabeth Alter
Full Text Available 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.
Bayesian Inference in Polling Technique: 1992 Presidential Polls.
Satake, Eiki
1994-01-01
Explores the potential utility of Bayesian statistical methods in determining the predictability of multiple polls. Compares Bayesian techniques to the classical statistical method employed by pollsters. Considers these questions in the context of the 1992 presidential elections. (HB)
DEFF Research Database (Denmark)
Bravo-Oviedo, Andres; Pretzsch, Hans; Ammer, Christian;
2014-01-01
Aim of study: We aim at (i) developing a reference definition of mixed forests in order to harmonize comparative research in mixed forests and (ii) review the research perspectives in mixed forests. Area of study: The definition is developed in Europe but can be tested worldwide. Material...... and Methods: Review of existent definitions of mixed forests based and literature review encompassing dynamics, management and economic valuation of mixed forests. Main results: A mixed forest is defined as a forest unit, excluding linear formations, where at least two tree species coexist at any...... density in mixed forests, (iii) conversion of monocultures to mixed-species forest and (iv) economic valuation of ecosystem services provided by mixed forests. Research highlights: The definition is considered a high-level one which encompasses previous attempts to define mixed forests. Current fields...
DEFF Research Database (Denmark)
Bravo-Oviedo, Andres; Pretzsch, Hans; Ammer, Christian
2014-01-01
density in mixed forests, (iii) conversion of monocultures to mixed-species forest and (iv) economic valuation of ecosystem services provided by mixed forests. Research highlights: The definition is considered a high-level one which encompasses previous attempts to define mixed forests. Current fields......Aim of study: We aim at (i) developing a reference definition of mixed forests in order to harmonize comparative research in mixed forests and (ii) review the research perspectives in mixed forests. Area of study: The definition is developed in Europe but can be tested worldwide. Material...... and Methods: Review of existent definitions of mixed forests based and literature review encompassing dynamics, management and economic valuation of mixed forests. Main results: A mixed forest is defined as a forest unit, excluding linear formations, where at least two tree species coexist at any...
Records of solar eclipse observations in ancient China
Institute of Scientific and Technical Information of China (English)
无
2009-01-01
Like ancient people at other places of the world, the ancient Chinese lived in awe of the Sun. As they felt solar eclipses extremely significant events, they closely observed the occurrence of solar eclipse. Ancient astronomers further realized very early that solar eclipses were one of the important astronomical phenomena to revise and improve the ancient calendar. Interestingly, ancient emperors regarded solar eclipses as warnings from heaven that might affect the stability of their throne. Consequently, observing and recording solar eclipses became official, which dated far back to ancient China when numerous relevant descriptions were recorded in historical books. These records contribute substantially to China as an ancient civilization, as well as to the research of the long-term variation of the rotation rate of the Earth during >2000 years before the 17th century. This paper briefly reviews the perception, observations and recording of solar eclipses by ancient Chinese astronomers.
Records of solar eclipse observations in ancient China
Institute of Scientific and Technical Information of China (English)
HAN YanBen; QIAO OiYuan
2009-01-01
Like ancient people at other places of the world, the ancient Chinese lived in awe of the Sun. As they felt solar eclipses extremely significant events, they closely observed the occurrence of solar eclipse. Ancient astronomers further realized very early that solar eclipses were one of the important astro-nomical phenomena to revise and improve the ancient calendar. Interestingly, ancient emperors re-garded solar eclipses as warnings from heaven that might affect the stability of their throne. Conse-quently, observing and recording solar eclipses became official, which dated far back to ancient China when numerous relevant descriptions were recorded in historical books. These records contribute substantially to China as an ancient civilization, as well as to the research of the long-term variation of the rotation rate of the Earth during >2000 years before the 17th century. This paper briefly reviews the perception, observations and recording of solar eclipses by ancient Chinese astronomers.
Bayesian modeling of unknown diseases for biosurveillance.
Shen, Yanna; Cooper, Gregory F
2009-11-14
This paper investigates Bayesian modeling of unknown causes of events in the context of disease-outbreak detection. We introduce a Bayesian approach that models and detects both (1) known diseases (e.g., influenza and anthrax) by using informative prior probabilities and (2) unknown diseases (e.g., a new, highly contagious respiratory virus that has never been seen before) by using relatively non-informative prior probabilities. We report the results of simulation experiments which support that this modeling method can improve the detection of new disease outbreaks in a population. A key contribution of this paper is that it introduces a Bayesian approach for jointly modeling both known and unknown causes of events. Such modeling has broad applicability in medical informatics, where the space of known causes of outcomes of interest is seldom complete.
Learning Bayesian Networks from Correlated Data
Bae, Harold; Monti, Stefano; Montano, Monty; Steinberg, Martin H.; Perls, Thomas T.; Sebastiani, Paola
2016-05-01
Bayesian networks are probabilistic models that represent complex distributions in a modular way and have become very popular in many fields. There are many methods to build Bayesian networks from a random sample of independent and identically distributed observations. However, many observational studies are designed using some form of clustered sampling that introduces correlations between observations within the same cluster and ignoring this correlation typically inflates the rate of false positive associations. We describe a novel parameterization of Bayesian networks that uses random effects to model the correlation within sample units and can be used for structure and parameter learning from correlated data without inflating the Type I error rate. We compare different learning metrics using simulations and illustrate the method in two real examples: an analysis of genetic and non-genetic factors associated with human longevity from a family-based study, and an example of risk factors for complications of sickle cell anemia from a longitudinal study with repeated measures.
Bayesian Methods for Radiation Detection and Dosimetry
Groer, Peter G
2002-01-01
We performed work in three areas: radiation detection, external and internal radiation dosimetry. In radiation detection we developed Bayesian techniques to estimate the net activity of high and low activity radioactive samples. These techniques have the advantage that the remaining uncertainty about the net activity is described by probability densities. Graphs of the densities show the uncertainty in pictorial form. Figure 1 below demonstrates this point. We applied stochastic processes for a method to obtain Bayesian estimates of 222Rn-daughter products from observed counting rates. In external radiation dosimetry we studied and developed Bayesian methods to estimate radiation doses to an individual with radiation induced chromosome aberrations. We analyzed chromosome aberrations after exposure to gammas and neutrons and developed a method for dose-estimation after criticality accidents. The research in internal radiation dosimetry focused on parameter estimation for compartmental models from observed comp...
Event generator tuning using Bayesian optimization
Ilten, Philip; Yang, Yunjie
2016-01-01
Monte Carlo event generators contain a large number of parameters that must be determined by comparing the output of the generator with experimental data. Generating enough events with a fixed set of parameter values to enable making such a comparison is extremely CPU intensive, which prohibits performing a simple brute-force grid-based tuning of the parameters. Bayesian optimization is a powerful method designed for such black-box tuning applications. In this article, we show that Monte Carlo event generator parameters can be accurately obtained using Bayesian optimization and minimal expert-level physics knowledge. A tune of the PYTHIA 8 event generator using $e^+e^-$ events, where 20 parameters are optimized, can be run on a modern laptop in just two days. Combining the Bayesian optimization approach with expert knowledge should enable producing better tunes in the future, by making it faster and easier to study discrepancies between Monte Carlo and experimental data.
Learning Bayesian Networks from Correlated Data.
Bae, Harold; Monti, Stefano; Montano, Monty; Steinberg, Martin H; Perls, Thomas T; Sebastiani, Paola
2016-05-05
Bayesian networks are probabilistic models that represent complex distributions in a modular way and have become very popular in many fields. There are many methods to build Bayesian networks from a random sample of independent and identically distributed observations. However, many observational studies are designed using some form of clustered sampling that introduces correlations between observations within the same cluster and ignoring this correlation typically inflates the rate of false positive associations. We describe a novel parameterization of Bayesian networks that uses random effects to model the correlation within sample units and can be used for structure and parameter learning from correlated data without inflating the Type I error rate. We compare different learning metrics using simulations and illustrate the method in two real examples: an analysis of genetic and non-genetic factors associated with human longevity from a family-based study, and an example of risk factors for complications of sickle cell anemia from a longitudinal study with repeated measures.
Bayesian Inference Methods for Sparse Channel Estimation
DEFF Research Database (Denmark)
Pedersen, Niels Lovmand
2013-01-01
This thesis deals with sparse Bayesian learning (SBL) with application to radio channel estimation. As opposed to the classical approach for sparse signal representation, we focus on the problem of inferring complex signals. Our investigations within SBL constitute the basis for the development...... of Bayesian inference algorithms for sparse channel estimation. Sparse inference methods aim at finding the sparse representation of a signal given in some overcomplete dictionary of basis vectors. Within this context, one of our main contributions to the field of SBL is a hierarchical representation...... analysis of the complex prior representation, where we show that the ability to induce sparse estimates of a given prior heavily depends on the inference method used and, interestingly, whether real or complex variables are inferred. We also show that the Bayesian estimators derived from the proposed...
Bayesian Fusion of Multi-Band Images
Wei, Qi; Tourneret, Jean-Yves
2013-01-01
In this paper, a Bayesian fusion technique for remotely sensed multi-band images is presented. The observed images are related to the high spectral and high spatial resolution image to be recovered through physical degradations, e.g., spatial and spectral blurring and/or subsampling defined by the sensor characteristics. The fusion problem is formulated within a Bayesian estimation framework. An appropriate prior distribution exploiting geometrical consideration is introduced. To compute the Bayesian estimator of the scene of interest from its posterior distribution, a Markov chain Monte Carlo algorithm is designed to generate samples asymptotically distributed according to the target distribution. To efficiently sample from this high-dimension distribution, a Hamiltonian Monte Carlo step is introduced in the Gibbs sampling strategy. The efficiency of the proposed fusion method is evaluated with respect to several state-of-the-art fusion techniques. In particular, low spatial resolution hyperspectral and mult...
Distributed Bayesian Networks for User Modeling
DEFF Research Database (Denmark)
Tedesco, Roberto; Dolog, Peter; Nejdl, Wolfgang
2006-01-01
by such adaptive applications are often partial fragments of an overall user model. The fragments have then to be collected and merged into a global user profile. In this paper we investigate and present algorithms able to cope with distributed, fragmented user models – based on Bayesian Networks – in the context...... of Web-based eLearning platforms. The scenario we are tackling assumes learners who use several systems over time, which are able to create partial Bayesian Networks for user models based on the local system context. In particular, we focus on how to merge these partial user models. Our merge mechanism...... efficiently combines distributed learner models without the need to exchange internal structure of local Bayesian networks, nor local evidence between the involved platforms....
Bayesian Image Reconstruction Based on Voronoi Diagrams
Cabrera, G F; Hitschfeld, N
2007-01-01
We present a Bayesian Voronoi image reconstruction technique (VIR) for interferometric data. Bayesian analysis applied to the inverse problem allows us to derive the a-posteriori probability of a novel parameterization of interferometric images. We use a variable Voronoi diagram as our model in place of the usual fixed pixel grid. A quantization of the intensity field allows us to calculate the likelihood function and a-priori probabilities. The Voronoi image is optimized including the number of polygons as free parameters. We apply our algorithm to deconvolve simulated interferometric data. Residuals, restored images and chi^2 values are used to compare our reconstructions with fixed grid models. VIR has the advantage of modeling the image with few parameters, obtaining a better image from a Bayesian point of view.
Variational Bayesian Inference of Line Spectra
DEFF Research Database (Denmark)
Badiu, Mihai Alin; Hansen, Thomas Lundgaard; Fleury, Bernard Henri
2016-01-01
In this paper, we address the fundamental problem of line spectral estimation in a Bayesian framework. We target model order and parameter estimation via variational inference in a probabilistic model in which the frequencies are continuous-valued, i.e., not restricted to a grid; and the coeffici......In this paper, we address the fundamental problem of line spectral estimation in a Bayesian framework. We target model order and parameter estimation via variational inference in a probabilistic model in which the frequencies are continuous-valued, i.e., not restricted to a grid......; and the coefficients are governed by a Bernoulli-Gaussian prior model turning model order selection into binary sequence detection. Unlike earlier works which retain only point estimates of the frequencies, we undertake a more complete Bayesian treatment by estimating the posterior probability density functions (pdfs...
Hessian PDF reweighting meets the Bayesian methods
Paukkunen, Hannu
2014-01-01
We discuss the Hessian PDF reweighting - a technique intended to estimate the effects that new measurements have on a set of PDFs. The method stems straightforwardly from considering new data in a usual $\\chi^2$-fit and it naturally incorporates also non-zero values for the tolerance, $\\Delta\\chi^2>1$. In comparison to the contemporary Bayesian reweighting techniques, there is no need to generate large ensembles of PDF Monte-Carlo replicas, and the observables need to be evaluated only with the central and the error sets of the original PDFs. In spite of the apparently rather different methodologies, we find that the Hessian and the Bayesian techniques are actually equivalent if the $\\Delta\\chi^2$ criterion is properly included to the Bayesian likelihood function that is a simple exponential.
Bayesian analysis of MEG visual evoked responses
Energy Technology Data Exchange (ETDEWEB)
Schmidt, D.M.; George, J.S.; Wood, C.C.
1999-04-01
The authors developed a method for analyzing neural electromagnetic data that allows probabilistic inferences to be drawn about regions of activation. The method involves the generation of a large number of possible solutions which both fir the data and prior expectations about the nature of probable solutions made explicit by a Bayesian formalism. In addition, they have introduced a model for the current distributions that produce MEG and (EEG) data that allows extended regions of activity, and can easily incorporate prior information such as anatomical constraints from MRI. To evaluate the feasibility and utility of the Bayesian approach with actual data, they analyzed MEG data from a visual evoked response experiment. They compared Bayesian analyses of MEG responses to visual stimuli in the left and right visual fields, in order to examine the sensitivity of the method to detect known features of human visual cortex organization. They also examined the changing pattern of cortical activation as a function of time.
Bayesian Analysis of Perceived Eye Level
Orendorff, Elaine E.; Kalesinskas, Laurynas; Palumbo, Robert T.; Albert, Mark V.
2016-01-01
To accurately perceive the world, people must efficiently combine internal beliefs and external sensory cues. We introduce a Bayesian framework that explains the role of internal balance cues and visual stimuli on perceived eye level (PEL)—a self-reported measure of elevation angle. This framework provides a single, coherent model explaining a set of experimentally observed PEL over a range of experimental conditions. Further, it provides a parsimonious explanation for the additive effect of low fidelity cues as well as the averaging effect of high fidelity cues, as also found in other Bayesian cue combination psychophysical studies. Our model accurately estimates the PEL and explains the form of previous equations used in describing PEL behavior. Most importantly, the proposed Bayesian framework for PEL is more powerful than previous behavioral modeling; it permits behavioral estimation in a wider range of cue combination and perceptual studies than models previously reported. PMID:28018204
Dynamic Bayesian Combination of Multiple Imperfect Classifiers
Simpson, Edwin; Psorakis, Ioannis; Smith, Arfon
2012-01-01
Classifier combination methods need to make best use of the outputs of multiple, imperfect classifiers to enable higher accuracy classifications. In many situations, such as when human decisions need to be combined, the base decisions can vary enormously in reliability. A Bayesian approach to such uncertain combination allows us to infer the differences in performance between individuals and to incorporate any available prior knowledge about their abilities when training data is sparse. In this paper we explore Bayesian classifier combination, using the computationally efficient framework of variational Bayesian inference. We apply the approach to real data from a large citizen science project, Galaxy Zoo Supernovae, and show that our method far outperforms other established approaches to imperfect decision combination. We go on to analyse the putative community structure of the decision makers, based on their inferred decision making strategies, and show that natural groupings are formed. Finally we present ...
Structure learning for Bayesian networks as models of biological networks.
Larjo, Antti; Shmulevich, Ilya; Lähdesmäki, Harri
2013-01-01
Bayesian networks are probabilistic graphical models suitable for modeling several kinds of biological systems. In many cases, the structure of a Bayesian network represents causal molecular mechanisms or statistical associations of the underlying system. Bayesian networks have been applied, for example, for inferring the structure of many biological networks from experimental data. We present some recent progress in learning the structure of static and dynamic Bayesian networks from data.
Dialogue Genre Texts in Ancient Greek Prose: Linguostylistic Aspect
Gita Bērziņa
2011-01-01
Dialogue Genre Texts in Ancient Greek Prose: Linguostylistic Aspect Doctoral thesis deals with the study of essential linguistic features of the Ancient Greek dialogue as an important ancient prose genre. The goal of the thesis is to disclose the specific linguistic characteristics of the genre of Ancient Greek dialogue on the basis of comparative analysis of the linguistic structure (on all levels as well as in style) of the texts of three most prominent authors (Plato, Xenoph...
Fire usage and ancient hominin detoxification genes
Aarts, Jac M.M.J.G.; Alink, Gerrit M.; Scherjon, Fulco; MacDonald, Katharine; Smith, Alison C.; Nijveen, Harm; Roebroeks, Wil
2016-01-01
Studies of the defence capacity of ancient hominins against toxic substances may contribute importantly to the reconstruction of their niche, including their diets and use of fire. Fire usage implies frequent exposure to hazardous compounds from smoke and heated food, known to affect general heal
Ancient Human Parasites in Ethnic Chinese Populations
Yeh, Hui-Yuan; Mitchell, Piers D.
2016-01-01
Whilst archaeological evidence for many aspects of life in ancient China is well studied, there has been much less interest in ancient infectious diseases, such as intestinal parasites in past Chinese populations. Here, we bring together evidence from mummies, ancient latrines, and pelvic soil from burials, dating from the Neolithic Period to the Qing Dynasty, in order to better understand the health of the past inhabitants of China and the diseases endemic in the region. Seven species of intestinal parasite have been identified, namely roundworm, whipworm, Chinese liver fluke, oriental schistosome, pinworm, Taenia sp. tapeworm, and the intestinal fluke Fasciolopsis buski. It was found that in the past, roundworm, whipworm, and Chinese liver fluke appear to have been much more common than the other species. While roundworm and whipworm remained common into the late 20th century, Chinese liver fluke seems to have undergone a marked decline in its prevalence over time. The iconic transport route known as the Silk Road has been shown to have acted as a vector for the transmission of ancient diseases, highlighted by the discovery of Chinese liver fluke in a 2,000 year-old relay station in northwest China, 1,500 km outside its endemic range. PMID:27853113
Ancient bronze disks, decorations and calendars
Sparavigna, Amelia Carolina
2012-01-01
Recently, it was published that some ancient bronze disks could had been calendars, that is, that their decorations had this function. Here I am discussing an example, the disk of the Trundholm Sun Chariot, proposing a new interpretation of it, giving a calendar of 360 days. Some geometric diagrams concerning the decoration layout are also proposed.
Ancient DNA analysis of dental calculus.
Weyrich, Laura S; Dobney, Keith; Cooper, Alan
2015-02-01
Dental calculus (calcified tartar or plaque) is today widespread on modern human teeth around the world. A combination of soft starchy foods, changing acidity of the oral environment, genetic pre-disposition, and the absence of dental hygiene all lead to the build-up of microorganisms and food debris on the tooth crown, which eventually calcifies through a complex process of mineralisation. Millions of oral microbes are trapped and preserved within this mineralised matrix, including pathogens associated with the oral cavity and airways, masticated food debris, and other types of extraneous particles that enter the mouth. As a result, archaeologists and anthropologists are increasingly using ancient human dental calculus to explore broad aspects of past human diet and health. Most recently, high-throughput DNA sequencing of ancient dental calculus has provided valuable insights into the evolution of the oral microbiome and shed new light on the impacts of some of the major biocultural transitions on human health throughout history and prehistory. Here, we provide a brief historical overview of archaeological dental calculus research, and discuss the current approaches to ancient DNA sampling and sequencing. Novel applications of ancient DNA from dental calculus are discussed, highlighting the considerable scope of this new research field for evolutionary biology and modern medicine.
Tapping Ancient Roots: Plaited Paper Baskets
Patrick, Jane
2011-01-01
With ancient roots, basket making has been practiced since the earliest civilizations, and according to textile experts, probably pre-dates pottery. This is partly conjecture since few baskets remain. It is through evidence found in clay impressions that the earliest baskets reveal themselves. Basically, basketry construction is like flat weaving.…
Ancient Pyramids Help Students Learn Math Concepts
Smith, Courtney D.; Stump, Amanda M.; Lazaros, Edward J.
2010-01-01
This article presents an activity that allows students to use mathematics and critical-thinking skills to emulate processes used by the ancient Egyptians to prepare the site for the Pyramids of Giza. To accomplish this, they use three different methods. First, they create a square using only simple technological tools that were available to the…
Defining Astrology in Ancient and Classical History
Campion, Nicholas
2015-05-01
Astrology in the ancient and classical worlds can be partly defined by its role, and partly by the way in which scholars spoke about it. The problem is complicated by the fact that the word is Greek - it has no Babylonian or Egyptian cognates - and even in Greece it was interchangeable with its cousin, 'astronomy'. Yet if we are to understand the role of the sky, stars and planets in culture, debates about the nature of ancient astrology, by both classical and modern scholars, must be taken into account. This talk will consider modern scholars' typologies of ancient astrology, together with ancient debates from Cicero in the 1st century BC, to Plotinus (204/5-270 AD) and Isidore of Seville (c. 560 - 4 April 636). It will consider the implications for our understanding of astronomy's role in culture, and conclude that in the classical period astrology may be best understood through its diversity and allegiance to competing philosophies, and that its functions were therefore similarly varied.
Ancient whole grain gluten-free flatbreads
The USDA food guide recommends that at least ½ of all the grains eaten should be whole grains. The FDA allows food Health Claim labels for food containing 51% whole gains and 11 g of dietary fiber. This is the only report demonstrating innovative ancient whole grain gluten-free (no yeast or chemical...
An ancient musical instrument returns home
Institute of Scientific and Technical Information of China (English)
1997-01-01
After 300 years abroad, an ancient Chinese musical instrument returned home with its face lifted and a Japanese name. Originally a one-stringed plucker, the Daisho Modo now features a whole family of electric high-, medium-pitched and bass instruments. With crisp tone and wide range, the Daisho Modo is
Fossil avian eggshell preserves ancient DNA
DEFF Research Database (Denmark)
Oskam, Charlotte L; Haile, James Seymour; McLay, Emma
2010-01-01
Owing to exceptional biomolecule preservation, fossil avian eggshell has been used extensively in geochronology and palaeodietary studies. Here, we show, to our knowledge, for the first time that fossil eggshell is a previously unrecognized source of ancient DNA (aDNA). We describe the successful...
The Study of Women in Ancient Society.
Moscovich, M. James
1982-01-01
Presents ideas for teaching about the roles of women in ancient Greek and Roman societies for undergraduate history and sociology classes. The discussion covers the roots of misogyny in Western culture, parallels between mythologies and sociocultural patterns, and the legal status of women in antiquity. (AM)
[Ancient tattooing from today's point of view].
Zimmermann, R; Zimmermann, K
1981-06-01
Both literary and arachaeological evidence indicates that, up to now, ancient tattoos can be traced with certainty in painting only among Thracians. A comparison with modern tattoos reveals differences of motivation and motifs, whereas localization, technique, and removal show similarities. The illustrations demonstrate some tattoos typical for Thracians on Greek vases.
Case report 872. "Ancient" schwannoma (degenerated neurilemoma).
Schultz, E; Sapan, M R; McHeffey-Atkinson, B; Naidich, J B; Arlen, M
1994-10-01
A case of an ancient schwannoma was presented. The rare occurrence of this tumor has resulted in only a few reported cases with descriptions of its features on imaging. Our patient's tumor, like one previously reported case, demonstrated calcification on the plain film - a finding not associated with other histologic types of schwannomas. Angiography revealed the tumor to be hypervascular. Evaluation by MRI demonstrated a lobulated, encapsulated soft tissue mass containing several cystic areas that corresponded histologically to areas of necrosis. Hypertrophied blood vessels were seen in the periphery of the tumoral mass. Too few ancient schwannomas have been reported to conclude whether or not radiographic evidence of soft tissue calcification is characteristic of this histologically distinctive subtype of schwannoma. However, since calcification is seen histologically as part of the degenerating process, its presence on plain films could be a feature of this tumor. Furthermore, the presence of cystic areas on MRI is not surprising given the pathological changes that occur in this tumor. We suggest that a diagnosis of ancient schwannoma be considered when a patient presents with a hypervascular soft tissue mass containing amorphous calcification on plain films and cystic areas on MRI. Despite the nonspecificity of these imaging findings, this point is relevant because each of these features suggests the presence of a malignant mass. Awareness of the possibility of a benign ancient schwannoma could obviate unnecessary radical surgery.
Communication Arts in the Ancient World.
Havelock, Eric A., Ed.; Hershbell, Jackson P., Ed.
Intended for both classicists and nonclassicists, this volume explores the beginnings of literacy in ancient Greece and Rome and examines the effects of written communication on these cultures. The nine articles, written by classical scholars and educators in the field of communication, discuss the following: the superiority of the alphabet over…
Paragons of Education in Ancient Times
Institute of Scientific and Technical Information of China (English)
1997-01-01
MOTHERS contributed greatly to children’s education in ancient China long before schools took shape. Behind many prominent figures lay greatmothers whose personal example and verbal instruction benefited their children throughout life. There is an old sayingabout the "stern father and compassionate mother."However, you will always
The Roots of Science in Ancient China.
Fisher, Arthur
1982-01-01
A 45-year-old research project (culminating in the multivolume "Science and Civilization in China") is examining major scientific innovations in ancient China and attempting to explain why, although the Chinese gained a technological edge in the past, they did not make the forward leap into modern science. (JN)
The Challenges of Qualitatively Coding Ancient Texts
Slingerland, Edward; Chudek, Maciej
2012-01-01
We respond to several important and valid concerns about our study ("The Prevalence of Folk Dualism in Early China," "Cognitive Science" 35: 997-1007) by Klein and Klein, defending our interpretation of our data. We also argue that, despite the undeniable challenges involved in qualitatively coding texts from ancient cultures, the standard tools…
Mitochondrial phylogenomics of modern and ancient equids
DEFF Research Database (Denmark)
Vilstrup, Julia T; Seguin-Orlando, Andaine; Stiller, Mathias;
2013-01-01
to calibrate reliable molecular clocks. Additional mitochondrial genome sequence data, including radiocarbon dated ancient equids, will be required before revisiting the exact timing of the lineage radiation leading up to modern equids, which for now were found to have possibly shared a common ancestor as far...
Genomic correlates of atherosclerosis in ancient humans.
Zink, Albert; Wann, L Samuel; Thompson, Randall C; Keller, Andreas; Maixner, Frank; Allam, Adel H; Finch, Caleb E; Frohlich, Bruno; Kaplan, Hillard; Lombardi, Guido P; Sutherland, M Linda; Sutherland, James D; Watson, Lucia; Cox, Samantha L; Miyamoto, Michael I; Narula, Jagat; Stewart, Alexandre F R; Thomas, Gregory S; Krause, Johannes
2014-06-01
Paleogenetics offers a unique opportunity to study human evolution, population dynamics, and disease evolution in situ. Although histologic and computed x-ray tomographic investigations of ancient mummies have clearly shown that atherosclerosis has been present in humans for more than 5,000 years, limited data are available on the presence of genetic predisposition for cardiovascular disease in ancient human populations. In a previous whole-genome study of the Tyrolean Iceman, a 5,300-year-old glacier mummy from the Alps, an increased risk for coronary heart disease was detected. The Iceman's genome revealed several single nucleotide polymorphisms that are linked with cardiovascular disease in genome-wide association studies. Future genetic studies of ancient humans from various geographic origins and time periods have the potential to provide more insights into the presence and possible changes of genetic risk factors in our ancestors. The study of ancient humans and a better understanding of the interaction between environmental and genetic influences on the development of heart diseases may lead to a more effective prevention and treatment of the most common cause of death in the modern world.
The Ancient stellar population of Leo A.
Saha, Abhijit; Fiorentino, Giuliana; Tolstoy, Eline; Cole, Andrew
2010-01-01
The primary goal of our proposal is the characterisation of the oldest stellar populations in Leo A using the properties of ancient RR Lyrae variable stars as tracers. Well known and long established correlations exist between the periods and luminosities of RR Lyrae variable stars and their ages an
A Bayesian Analysis of Spectral ARMA Model
Directory of Open Access Journals (Sweden)
Manoel I. Silvestre Bezerra
2012-01-01
Full Text Available Bezerra et al. (2008 proposed a new method, based on Yule-Walker equations, to estimate the ARMA spectral model. In this paper, a Bayesian approach is developed for this model by using the noninformative prior proposed by Jeffreys (1967. The Bayesian computations, simulation via Markov Monte Carlo (MCMC is carried out and characteristics of marginal posterior distributions such as Bayes estimator and confidence interval for the parameters of the ARMA model are derived. Both methods are also compared with the traditional least squares and maximum likelihood approaches and a numerical illustration with two examples of the ARMA model is presented to evaluate the performance of the procedures.
Length Scales in Bayesian Automatic Adaptive Quadrature
Directory of Open Access Journals (Sweden)
Adam Gh.
2016-01-01
Full Text Available Two conceptual developments in the Bayesian automatic adaptive quadrature approach to the numerical solution of one-dimensional Riemann integrals [Gh. Adam, S. Adam, Springer LNCS 7125, 1–16 (2012] are reported. First, it is shown that the numerical quadrature which avoids the overcomputing and minimizes the hidden floating point loss of precision asks for the consideration of three classes of integration domain lengths endowed with specific quadrature sums: microscopic (trapezoidal rule, mesoscopic (Simpson rule, and macroscopic (quadrature sums of high algebraic degrees of precision. Second, sensitive diagnostic tools for the Bayesian inference on macroscopic ranges, coming from the use of Clenshaw-Curtis quadrature, are derived.
Bayesian estimation and tracking a practical guide
Haug, Anton J
2012-01-01
A practical approach to estimating and tracking dynamic systems in real-worl applications Much of the literature on performing estimation for non-Gaussian systems is short on practical methodology, while Gaussian methods often lack a cohesive derivation. Bayesian Estimation and Tracking addresses the gap in the field on both accounts, providing readers with a comprehensive overview of methods for estimating both linear and nonlinear dynamic systems driven by Gaussian and non-Gaussian noices. Featuring a unified approach to Bayesian estimation and tracking, the book emphasizes the derivation
Bayesian long branch attraction bias and corrections.
Susko, Edward
2015-03-01
Previous work on the star-tree paradox has shown that Bayesian methods suffer from a long branch attraction bias. That work is extended to settings involving more taxa and partially resolved trees. The long branch attraction bias is confirmed to arise more broadly and an additional source of bias is found. A by-product of the analysis is methods that correct for biases toward particular topologies. The corrections can be easily calculated using existing Bayesian software. Posterior support for a set of two or more trees can thus be supplemented with corrected versions to cross-check or replace results. Simulations show the corrections to be highly effective.
From retrodiction to Bayesian quantum imaging
Speirits, Fiona C.; Sonnleitner, Matthias; Barnett, Stephen M.
2017-04-01
We employ quantum retrodiction to develop a robust Bayesian algorithm for reconstructing the intensity values of an image from sparse photocount data, while also accounting for detector noise in the form of dark counts. This method yields not only a reconstructed image but also provides the full probability distribution function for the intensity at each pixel. We use simulated as well as real data to illustrate both the applications of the algorithm and the analysis options that are only available when the full probability distribution functions are known. These include calculating Bayesian credible regions for each pixel intensity, allowing an objective assessment of the reliability of the reconstructed image intensity values.
A Bayesian Concept Learning Approach to Crowdsourcing
DEFF Research Database (Denmark)
Viappiani, Paolo Renato; Zilles, Sandra; Hamilton, Howard J.;
2011-01-01
techniques, inference methods, and query selection strategies to assist a user charged with choosing a configuration that satisfies some (partially known) concept. Our model is able to simultaneously learn the concept definition and the types of the experts. We evaluate our model with simulations, showing......We develop a Bayesian approach to concept learning for crowdsourcing applications. A probabilistic belief over possible concept definitions is maintained and updated according to (noisy) observations from experts, whose behaviors are modeled using discrete types. We propose recommendation...... that our Bayesian strategies are effective even in large concept spaces with many uninformative experts....
Bayesian Optimisation Algorithm for Nurse Scheduling
Li, Jingpeng
2008-01-01
Our research has shown that schedules can be built mimicking a human scheduler by using a set of rules that involve domain knowledge. This chapter presents a Bayesian Optimization Algorithm (BOA) for the nurse scheduling problem that chooses such suitable scheduling rules from a set for each nurses assignment. Based on the idea of using probabilistic models, the BOA builds a Bayesian network for the set of promising solutions and samples these networks to generate new candidate solutions. Computational results from 52 real data instances demonstrate the success of this approach. It is also suggested that the learning mechanism in the proposed algorithm may be suitable for other scheduling problems.
Ancient Egyptian Medicine: A Systematic Review
Directory of Open Access Journals (Sweden)
Samuel Adu-Gyamfi
2015-12-01
Full Text Available Our present day knowledge in the area of medicine in Ancient Egypt has been severally sourced from medical papyri several of which have been deduced and analyzed by different scholars. For educational purposes it is always imperative to consult different literature or sources in the teaching of ancient Egypt and medicine in particular. To avoid subjectivity the author has found the need to re-engage the efforts made by several scholars in adducing evidences from medical papyri. In the quest to re-engage the efforts of earlier writers and commentaries on the medical papyri, we are afforded the opportunity to be informed about the need to ask further questions to enable us to construct or reconstruct both past and modern views on ancient Egyptian medical knowledge. It is this vocation the author sought to pursue in the interim, through a preliminary review, to highlight, comment and reinvigorate in the reader or researcher the need for a continuous engagement of some pertinent documentary sources on Ancient Egyptian medical knowledge for educational and research purposes. The study is based on qualitative review of published literature. The selection of those articles as sources was based on the focus of the review, in order to purposively select and comment on articles that were published based either on information from a medical papyrus or focused on medical specialization among the ancient Egyptians as well as ancient Egyptian knowledge on diseases and medicine. It was found that the Egyptians developed relatively sophisticated medical practices covering significant medical fields such as herbal medicine, gynecology and obstetrics, anatomy and physiology, mummification and even the preliminary form of surgery. These practices, perhaps, were developed as remedies for the prevailing diseases and the accidents that might have occurred during the construction of their giant pyramids. It must be stated that they were not without flaws. Also, the
Bayesian Just-So Stories in Psychology and Neuroscience
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.…
A Fast Iterative Bayesian Inference Algorithm for Sparse Channel Estimation
DEFF Research Database (Denmark)
Pedersen, Niels Lovmand; Manchón, Carles Navarro; Fleury, Bernard Henri
2013-01-01
representation of the Bessel K probability density function; a highly efficient, fast iterative Bayesian inference method is then applied to the proposed model. The resulting estimator outperforms other state-of-the-art Bayesian and non-Bayesian estimators, either by yielding lower mean squared estimation error...
Prior approval: the growth of Bayesian methods in psychology.
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 default Bayesian hypothesis test for ANOVA designs
Wetzels, R.; Grasman, R.P.P.P.; Wagenmakers, E.J.
2012-01-01
This article presents a Bayesian hypothesis test for analysis of variance (ANOVA) designs. The test is an application of standard Bayesian methods for variable selection in regression models. We illustrate the effect of various g-priors on the ANOVA hypothesis test. The Bayesian test for ANOVA desig
From arguments to constraints on a Bayesian network
Bex, F.J.; Renooij, S.
2016-01-01
In this paper, we propose a way to derive constraints for a Bayesian Network from structured arguments. Argumentation and Bayesian networks can both be considered decision support techniques, but are typically used by experts with different backgrounds. Bayesian network experts have the mathematical
A Gentle Introduction to Bayesian Analysis : Applications to Developmental Research
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, t
A SAS Interface for Bayesian Analysis with WinBUGS
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…
The Ancient Kemetic Roots of Library and Information Science.
Zulu, Itibari M.
This paper argues that the ancient people of Kemet (Egypt), "the black land," built and operated the first major libraries and institutions of higher education in the world. Topics of discussion include the Ancient Egyptians as an African people; a chronology of Ancient Kemet; literature in Kemet; a history of Egyptian Librarianship; the…
Deep sequencing of RNA from ancient maize kernels
DEFF Research Database (Denmark)
Fordyce, Sarah Louise; Avila Arcos, Maria del Carmen; Rasmussen, Morten;
2013-01-01
The characterization of biomolecules from ancient samples can shed otherwise unobtainable insights into the past. Despite the fundamental role of transcriptomal change in evolution, the potential of ancient RNA remains unexploited - perhaps due to dogma associated with the fragility of RNA. We...... maize kernels. The results suggest that ancient seed transcriptomics may offer a powerful new tool with which to study plant domestication....
Ancient DNA assessment of tiger salamander population in Yellowstone National Park.
McMenamin, Sarah K; Hadly, Elizabeth A
2012-01-01
Recent data indicates that blotched tiger salamanders (Ambystoma tigrinum melanostictum) in northern regions of Yellowstone National Park are declining due to climate-related habitat changes. In this study, we used ancient and modern mitochondrial haplotype diversity to model the effective size of this amphibian population through recent geological time and to assess past responses to climatic changes in the region. Using subfossils collected from a cave in northern Yellowstone, we analyzed >700 base pairs of mitochondrial sequence from 16 samples ranging in age from 100 to 3300 years old and found that all shared an identical haplotype. Although mitochondrial diversity was extremely low within the living population, we still were able to detect geographic subdivision within the local area. Using serial coalescent modelling with Bayesian priors from both modern and ancient genetic data we simulated a range of probable population sizes and mutation rates through time. Our simulations suggest that regional mitochondrial diversity has remained relatively constant even through climatic fluctuations of recent millennia.
Ancient DNA assessment of tiger salamander population in Yellowstone National Park.
Directory of Open Access Journals (Sweden)
Sarah K McMenamin
Full Text Available Recent data indicates that blotched tiger salamanders (Ambystoma tigrinum melanostictum in northern regions of Yellowstone National Park are declining due to climate-related habitat changes. In this study, we used ancient and modern mitochondrial haplotype diversity to model the effective size of this amphibian population through recent geological time and to assess past responses to climatic changes in the region. Using subfossils collected from a cave in northern Yellowstone, we analyzed >700 base pairs of mitochondrial sequence from 16 samples ranging in age from 100 to 3300 years old and found that all shared an identical haplotype. Although mitochondrial diversity was extremely low within the living population, we still were able to detect geographic subdivision within the local area. Using serial coalescent modelling with Bayesian priors from both modern and ancient genetic data we simulated a range of probable population sizes and mutation rates through time. Our simulations suggest that regional mitochondrial diversity has remained relatively constant even through climatic fluctuations of recent millennia.
Genetic diversity among ancient Nordic populations.
Directory of Open Access Journals (Sweden)
Linea Melchior
Full Text Available Using established criteria for work with fossil DNA we have analysed mitochondrial DNA from 92 individuals from 18 locations in Denmark ranging in time from the Mesolithic to the Medieval Age. Unequivocal assignment of mtDNA haplotypes was possible for 56 of the ancient individuals; however, the success rate varied substantially between sites; the highest rates were obtained with untouched, freshly excavated material, whereas heavy handling, archeological preservation and storage for many years influenced the ability to obtain authentic endogenic DNA. While the nucleotide diversity at two locations was similar to that among extant Danes, the diversity at four sites was considerably higher. This supports previous observations for ancient Britons. The overall occurrence of haplogroups did not deviate from extant Scandinavians, however, haplogroup I was significantly more frequent among the ancient Danes (average 13% than among extant Danes and Scandinavians (approximately 2.5% as well as among other ancient population samples reported. Haplogroup I could therefore have been an ancient Southern Scandinavian type "diluted" by later immigration events. Interestingly, the two Neolithic samples (4,200 YBP, Bell Beaker culture that were typed were haplogroup U4 and U5a, respectively, and the single Bronze Age sample (3,300-3,500 YBP was haplogroup U4. These two haplogroups have been associated with the Mesolithic populations of Central and Northern Europe. Therefore, at least for Southern Scandinavia, our findings do not support a possible replacement of a haplogroup U dominated hunter-gatherer population by a more haplogroup diverse Neolithic Culture.
Ancient Egypt in our Cultural Heritage?
Directory of Open Access Journals (Sweden)
Vera Vasiljević
2016-02-01
Full Text Available Inspiration derived from ancient Egypt is usually expressed through the Egyptian motifs in arts and popular culture of the 19th and 20th centuries, as well as through the non-scientific interpretations of the culture, very much based upon the Renaissance ones. The number and variety of material and non-material traces of this fascination are most expressed in the countries where, along with the early support for the institutional development of Egyptology, there existed economically potent educated middle classes (Western and Central Europe, USA, but may also be traced elsewhere. The public fascination by ancient Egypt has not ceased by the times of foundation of Egyptology, marked by the decipherment of the hieroglyphic script in 1822. Until the end of the 20th century Egyptologists have rarely dealt with the prelude to their discipline, limiting their interest to the critical approach to ancient sources and to noting the attempts to interpret the hieroglyphic script and the function of pyramids. However, the rising importance of the reception studies in other disciplines raised the interest of Egyptologists for the "fascination of Egypt", thus changing the status of various modes of expressing "Egyptomania" – they have thus become a part of the cultural heritage, registered, documented, preserved and studied. The research of this kind is only beginning in Serbia. The line of inquiry enhances the knowledge of the scope, manifestations and roles of the interest in Egypt, not limited by the national or political borders. On the other hand, the existence of the cultural heritage similar to the wider European view of ancient Egypt – short remarks by Jerotej Račanin, Kandor by Atanasije Stojković, the usage of architectural motifs derived from Egypt, the emergence of small private collections, to mention several early examples – all show that the research into the reception of ancient Egypt may contribute to the knowledge about the history
Ancient and Medieval Cosmology in Armenian Highland
Farmanyan, Sona V.; Mickaelian, Areg M.
2016-12-01
Humankind has always sought to recognize the nature of various sky related phenomena and tried to give them explanations. It is especially vivid in ancient cultures, many of which are related to the Middle East. The purpose of this study is to identify ancient Armenian's pantheistic and cosmological perceptions, world view, notions and beliefs. By this study we answer the question "How did the Universe work in Ancient Armenian Highland?" The paper focuses on the structure of the Universe and many phenomena of nature that have always had major influence on ancient Armenians thinking. Here we weave together astronomy, anthropology and mythology of Armenia, and scientific thinking revealed in local astronomy traditions. The initial review of the study covers Moses of Khoren, Yeznik of Koghb, Anania Shirakatsi and other 5th-7th centuries historians' and scientists' records about the Universe related superstitious beliefs and cosmological understanding. By discussing and comparing Universe structure in various regional traditions, myths, folk songs and phraseological units we very often came across "seven worlds", "seven earths" and "seven layers" concepts. We draw parallels between scientific and mythological Earth and Heaven and thus find similar number of layers on both of the ancient and modern thinking. In the article we also give some details about the tripartite structure of the Universe and how these parts are connected with axis. This axis is either a column or a Cosmic Tree (Kenatz Tsar). In Armenian culture the preliminary meanings of the Kenatz Tsar are more vivid in folk songs (Jan gyulums), plays, epic, and so on, which was subsequently mixed with religious and spiritual views. We conclude that the perception of the Universe structure and celestial objects had a significant impact on culture and worldview of the people of the Armenian Highland; particularly it was one of the bases of the regional cultural diversity.
Bal, Tara L.
2014-01-01
"Forest health" is an important concept often not covered in tree, forest, insect, or fungal ecology and biology. With minimal, inexpensive equipment, students can investigate and conduct their own forest health survey to assess the percentage of trees with natural or artificial wounds or stress. Insects and diseases in the forest are…
Evidence and Implications of Frequent Fires in Ancient Shrub Tundra
Energy Technology Data Exchange (ETDEWEB)
Higuera, P E; Brubaker, L B; Anderson, P M; Brown, T A; Kennedy, A T; Hu, F S
2008-03-06
Understanding feedbacks between terrestrial and atmospheric systems is vital for predicting the consequences of global change, particularly in the rapidly changing Arctic. Fire is a key process in this context, but the consequences of altered fire regimes in tundra ecosystems are rarely considered, largely because tundra fires occur infrequently on the modern landscape. We present paleoecological data that indicate frequent tundra fires in northcentral Alaska between 14,000 and 10,000 years ago. Charcoal and pollen from lake sediments reveal that ancient birchdominated shrub tundra burned as often as modern boreal forests in the region, every 144 years on average (+/- 90 s.d.; n = 44). Although paleoclimate interpretations and data from modern tundra fires suggest that increased burning was aided by low effective moisture, vegetation cover clearly played a critical role in facilitating the paleo-fires by creating an abundance of fine fuels. These records suggest that greater fire activity will likely accompany temperature-related increases in shrub-dominated tundra predicted for the 21st century and beyond. Increased tundra burning will have broad impacts on physical and biological systems as well as land-atmosphere interactions in the Arctic, including the potential to release stored organic carbon to the atmosphere.
Der Sarkissian, Clio; Balanovsky, Oleg; Brandt, Guido; Khartanovich, Valery; Buzhilova, Alexandra; Koshel, Sergey; Zaporozhchenko, Valery; Gronenborn, Detlef; Moiseyev, Vyacheslav; Kolpakov, Eugen; Shumkin, Vladimir; Alt, Kurt W; Balanovska, Elena; Cooper, Alan; Haak, Wolfgang
2013-01-01
North East Europe harbors a high diversity of cultures and languages, suggesting a complex genetic history. Archaeological, anthropological, and genetic research has revealed a series of influences from Western and Eastern Eurasia in the past. While genetic data from modern-day populations is commonly used to make inferences about their origins and past migrations, ancient DNA provides a powerful test of such hypotheses by giving a snapshot of the past genetic diversity. In order to better understand the dynamics that have shaped the gene pool of North East Europeans, we generated and analyzed 34 mitochondrial genotypes from the skeletal remains of three archaeological sites in northwest Russia. These sites were dated to the Mesolithic and the Early Metal Age (7,500 and 3,500 uncalibrated years Before Present). We applied a suite of population genetic analyses (principal component analysis, genetic distance mapping, haplotype sharing analyses) and compared past demographic models through coalescent simulations using Bayesian Serial SimCoal and Approximate Bayesian Computation. Comparisons of genetic data from ancient and modern-day populations revealed significant changes in the mitochondrial makeup of North East Europeans through time. Mesolithic foragers showed high frequencies and diversity of haplogroups U (U2e, U4, U5a), a pattern observed previously in European hunter-gatherers from Iberia to Scandinavia. In contrast, the presence of mitochondrial DNA haplogroups C, D, and Z in Early Metal Age individuals suggested discontinuity with Mesolithic hunter-gatherers and genetic influx from central/eastern Siberia. We identified remarkable genetic dissimilarities between prehistoric and modern-day North East Europeans/Saami, which suggests an important role of post-Mesolithic migrations from Western Europe and subsequent population replacement/extinctions. This work demonstrates how ancient DNA can improve our understanding of human population movements across
Directory of Open Access Journals (Sweden)
Clio Der Sarkissian
Full Text Available North East Europe harbors a high diversity of cultures and languages, suggesting a complex genetic history. Archaeological, anthropological, and genetic research has revealed a series of influences from Western and Eastern Eurasia in the past. While genetic data from modern-day populations is commonly used to make inferences about their origins and past migrations, ancient DNA provides a powerful test of such hypotheses by giving a snapshot of the past genetic diversity. In order to better understand the dynamics that have shaped the gene pool of North East Europeans, we generated and analyzed 34 mitochondrial genotypes from the skeletal remains of three archaeological sites in northwest Russia. These sites were dated to the Mesolithic and the Early Metal Age (7,500 and 3,500 uncalibrated years Before Present. We applied a suite of population genetic analyses (principal component analysis, genetic distance mapping, haplotype sharing analyses and compared past demographic models through coalescent simulations using Bayesian Serial SimCoal and Approximate Bayesian Computation. Comparisons of genetic data from ancient and modern-day populations revealed significant changes in the mitochondrial makeup of North East Europeans through time. Mesolithic foragers showed high frequencies and diversity of haplogroups U (U2e, U4, U5a, a pattern observed previously in European hunter-gatherers from Iberia to Scandinavia. In contrast, the presence of mitochondrial DNA haplogroups C, D, and Z in Early Metal Age individuals suggested discontinuity with Mesolithic hunter-gatherers and genetic influx from central/eastern Siberia. We identified remarkable genetic dissimilarities between prehistoric and modern-day North East Europeans/Saami, which suggests an important role of post-Mesolithic migrations from Western Europe and subsequent population replacement/extinctions. This work demonstrates how ancient DNA can improve our understanding of human population
What do we know about our graduates? Graduate analysis for forest sciences and related curricula
Schmidt, P.; Lewark, S.; Strange, N.
2010-01-01
Forestry as such is an old trade; already the ancient Romans did it. Its education is less old, about two centuries. Apparently, as Lewark remarked in his introduction, in general foresters educated at universities matched the need of the forestry sector.. Only about 40 years ago, the need to know m
Babcock, C. R.; Andersen, H. E.; Finley, A. O.; Cook, B.; Morton, D. C.
2015-12-01
Models using repeat LiDAR and field campaigns may be one mechanism to monitor carbon storage and flux in forested regions. Considering the ability of multi-temporal LiDAR to estimate growth, it is not surprising that there is great interest in developing forest carbon monitoring strategies that rely on repeated LiDAR acquisitions. Allowing for sparser field campaigns, LiDAR stands to make monitoring forest carbon cheaper and more efficient than field-only sampling procedures. Here, we look to the spatio-temporally data-rich Kenai Peninsula in Alaska to examine the potential for Bayesian spatio-temporal mapping of forest carbon storage and uncertainty. The framework explored here can predict forest carbon through space and time, while formally propagating uncertainty through to prediction. Bayesian spatio-temporal models are flexible frameworks allowing for forest growth processes to be formally integrated into the model. By incorporating a mechanism for growth---using temporally repeated field and LiDAR data---we can more fully exploit the information-rich inventory network to improve prediction accuracy. LiDAR data for the Kenai Peninsula has been collected on four different occasions---spatially coincident LiDAR strip samples in 2004, 09 and 14, along with a wall-to-wall collection in 2008. There were 436 plots measured twice between 2002 and 2014. LiDAR was acquired at least once over most inventory plots with many having LiDAR collected during 2, 3 or 4 different campaigns. Results from this research will impact how forests are inventoried. It is too expensive to monitor terrestrial carbon using field-only sampling strategies and currently proposed LiDAR model-based techniques lack the ability to properly utilize temporally repeated and misaligned data. Bayesian hierarchical spatio-temporal models offer a solution to these shortcomings and allow for formal predictive error assessment, which is useful for policy development and decision making.
Institute of Scientific and Technical Information of China (English)
张松懋
1994-01-01
Forest grammar,a new type of high-dimensional grammar,is proposed in this paper,of which both the left and the right parts of every production are concatenations of tree structures.A classification of forest grammar is studied,especially,a subclass of the forest grammar,i.e.the context-sensitive forest grammar,and one of its subclasses is defined,called the weak precedence forest grammar.
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
Bayesian Vector Autoregressions with Stochastic Volatility
Uhlig, H.F.H.V.S.
1996-01-01
This paper proposes a Bayesian approach to a vector autoregression with stochastic volatility, where the multiplicative evolution of the precision matrix is driven by a multivariate beta variate.Exact updating formulas are given to the nonlinear filtering of the precision matrix.Estimation of the au
Bayesian Estimation Supersedes the "t" Test
Kruschke, John K.
2013-01-01
Bayesian estimation for 2 groups provides complete distributions of credible values for the effect size, group means and their difference, standard deviations and their difference, and the normality of the data. The method handles outliers. The decision rule can accept the null value (unlike traditional "t" tests) when certainty in the estimate is…
Bayesian Meta-Analysis of Coefficient Alpha
Brannick, Michael T.; Zhang, Nanhua
2013-01-01
The current paper describes and illustrates a Bayesian approach to the meta-analysis of coefficient alpha. Alpha is the most commonly used estimate of the reliability or consistency (freedom from measurement error) for educational and psychological measures. The conventional approach to meta-analysis uses inverse variance weights to combine…
Comprehension and computation in Bayesian problem solving
Directory of Open Access Journals (Sweden)
Eric D. Johnson
2015-07-01
Full Text Available Humans have long been characterized as poor probabilistic reasoners when presented with explicit numerical information. Bayesian word problems provide a well-known example of this, where even highly educated and cognitively skilled individuals fail to adhere to mathematical norms. It is widely agreed that natural frequencies can facilitate Bayesian reasoning relative to normalized formats (e.g. probabilities, percentages, both by clarifying logical set-subset relations and by simplifying numerical calculations. Nevertheless, between-study performance on transparent Bayesian problems varies widely, and generally remains rather unimpressive. We suggest there has been an over-focus on this representational facilitator (i.e. transparent problem structures at the expense of the specific logical and numerical processing requirements and the corresponding individual abilities and skills necessary for providing Bayesian-like output given specific verbal and numerical input. We further suggest that understanding this task-individual pair could benefit from considerations from the literature on mathematical cognition, which emphasizes text comprehension and problem solving, along with contributions of online executive working memory, metacognitive regulation, and relevant stored knowledge and skills. We conclude by offering avenues for future research aimed at identifying the stages in problem solving at which correct versus incorrect reasoners depart, and how individual difference might influence this time point.
Bayesian Networks: Aspects of Approximate Inference
Bolt, J.H.
2008-01-01
A Bayesian network can be used to model consisely the probabilistic knowledge with respect to a given problem domain. Such a network consists of an acyclic directed graph in which the nodes represent stochastic variables, supplemented with probabilities indicating the strength of the influences betw
Bayesian Benefits for the Pragmatic Researcher
Wagenmakers, E.-J.; Morey, R.D.; Lee, M.D.
2016-01-01
The practical advantages of Bayesian inference are demonstrated here through two concrete examples. In the first example, we wish to learn about a criminal’s IQ: a problem of parameter estimation. In the second example, we wish to quantify and track support in favor of the null hypothesis that Adam
Communication cost in Distributed Bayesian Belief Networks
Gosliga, S.P. van; Maris, M.G.
2005-01-01
In this paper, two different methods for information fusionare compared with respect to communication cost. These are the lambda-pi and the junction tree approach as the probability computing methods in Bayesian networks. The analysis is done within the scope of large distributed networks of computi
Decision generation tools and Bayesian inference
Jannson, Tomasz; Wang, Wenjian; Forrester, Thomas; Kostrzewski, Andrew; Veeris, Christian; Nielsen, Thomas
2014-05-01
Digital Decision Generation (DDG) tools are important software sub-systems of Command and Control (C2) systems and technologies. In this paper, we present a special type of DDGs based on Bayesian Inference, related to adverse (hostile) networks, including such important applications as terrorism-related networks and organized crime ones.
Bayesian semiparametric dynamic Nelson-Siegel model
C. Cakmakli
2011-01-01
This paper proposes the Bayesian semiparametric dynamic Nelson-Siegel model where the density of the yield curve factors and thereby the density of the yields are estimated along with other model parameters. This is accomplished by modeling the error distributions of the factors according to a Diric
Multisnapshot Sparse Bayesian Learning for DOA
DEFF Research Database (Denmark)
Gerstoft, Peter; Mecklenbrauker, Christoph F.; Xenaki, Angeliki
2016-01-01
The directions of arrival (DOA) of plane waves are estimated from multisnapshot sensor array data using sparse Bayesian learning (SBL). The prior for the source amplitudes is assumed independent zero-mean complex Gaussian distributed with hyperparameters, the unknown variances (i.e., the source p...
Von Neumann Was Not a Quantum Bayesian
Stacey, Blake C
2014-01-01
Wikipedia has claimed for over two years now that John von Neumann was the "first quantum Bayesian." In context, this reads as stating that von Neumann inaugurated QBism, the approach to quantum theory promoted by Fuchs, Mermin and Schack. This essay explores how such a claim is, historically speaking, unsupported.
Bayesian networks in neuroscience: a survey.
Bielza, Concha; Larrañaga, Pedro
2014-01-01
Bayesian networks are a type of probabilistic graphical models lie at the intersection between statistics and machine learning. They have been shown to be powerful tools to encode dependence relationships among the variables of a domain under uncertainty. Thanks to their generality, Bayesian networks can accommodate continuous and discrete variables, as well as temporal processes. In this paper we review Bayesian networks and how they can be learned automatically from data by means of structure learning algorithms. Also, we examine how a user can take advantage of these networks for reasoning by exact or approximate inference algorithms that propagate the given evidence through the graphical structure. Despite their applicability in many fields, they have been little used in neuroscience, where they have focused on specific problems, like functional connectivity analysis from neuroimaging data. Here we survey key research in neuroscience where Bayesian networks have been used with different aims: discover associations between variables, perform probabilistic reasoning over the model, and classify new observations with and without supervision. The networks are learned from data of any kind-morphological, electrophysiological, -omics and neuroimaging-, thereby broadening the scope-molecular, cellular, structural, functional, cognitive and medical- of the brain aspects to be studied.
Bayesian Estimation of Thermonuclear Reaction Rates
Iliadis, Christian; Coc, Alain; Timmes, Frank; Starrfield, Sumner
2016-01-01
The problem of estimating non-resonant astrophysical S-factors and thermonuclear reaction rates, based on measured nuclear cross sections, is of major interest for nuclear energy generation, neutrino physics, and element synthesis. Many different methods have been applied in the past to this problem, all of them based on traditional statistics. Bayesian methods, on the other hand, are now in widespread use in the physical sciences. In astronomy, for example, Bayesian statistics is applied to the observation of extra-solar planets, gravitational waves, and type Ia supernovae. However, nuclear physics, in particular, has been slow to adopt Bayesian methods. We present the first astrophysical S-factors and reaction rates based on Bayesian statistics. We develop a framework that incorporates robust parameter estimation, systematic effects, and non-Gaussian uncertainties in a consistent manner. The method is applied to the d(p,$\\gamma$)$^3$He, $^3$He($^3$He,2p)$^4$He, and $^3$He($\\alpha$,$\\gamma$)$^7$Be reactions,...
Bayesian Estimation of Thermonuclear Reaction Rates
Iliadis, C.; Anderson, K. S.; Coc, A.; Timmes, F. X.; Starrfield, S.
2016-11-01
The problem of estimating non-resonant astrophysical S-factors and thermonuclear reaction rates, based on measured nuclear cross sections, is of major interest for nuclear energy generation, neutrino physics, and element synthesis. Many different methods have been applied to this problem in the past, almost all of them based on traditional statistics. Bayesian methods, on the other hand, are now in widespread use in the physical sciences. In astronomy, for example, Bayesian statistics is applied to the observation of extrasolar planets, gravitational waves, and Type Ia supernovae. However, nuclear physics, in particular, has been slow to adopt Bayesian methods. We present astrophysical S-factors and reaction rates based on Bayesian statistics. We develop a framework that incorporates robust parameter estimation, systematic effects, and non-Gaussian uncertainties in a consistent manner. The method is applied to the reactions d(p,γ)3He, 3He(3He,2p)4He, and 3He(α,γ)7Be, important for deuterium burning, solar neutrinos, and Big Bang nucleosynthesis.
Bayesian regularization of diffusion tensor images
DEFF Research Database (Denmark)
Frandsen, Jesper; Hobolth, Asger; Østergaard, Leif;
2007-01-01
several directions. The measured diffusion coefficients and thereby the diffusion tensors are subject to noise, leading to possibly flawed representations of the three dimensional fibre bundles. In this paper we develop a Bayesian procedure for regularizing the diffusion tensor field, fully utilizing...
Inverse Problems in a Bayesian Setting
Matthies, Hermann G.
2016-02-13
In a Bayesian setting, inverse problems and uncertainty quantification (UQ)—the propagation of uncertainty through a computational (forward) model—are strongly connected. In the form of conditional expectation the Bayesian update becomes computationally attractive. We give a detailed account of this approach via conditional approximation, various approximations, and the construction of filters. Together with a functional or spectral approach for the forward UQ there is no need for time-consuming and slowly convergent Monte Carlo sampling. The developed sampling-free non-linear Bayesian update in form of a filter is derived from the variational problem associated with conditional expectation. This formulation in general calls for further discretisation to make the computation possible, and we choose a polynomial approximation. After giving details on the actual computation in the framework of functional or spectral approximations, we demonstrate the workings of the algorithm on a number of examples of increasing complexity. At last, we compare the linear and nonlinear Bayesian update in form of a filter on some examples.
Neural network classification - A Bayesian interpretation
Wan, Eric A.
1990-01-01
The relationship between minimizing a mean squared error and finding the optimal Bayesian classifier is reviewed. This provides a theoretical interpretation for the process by which neural networks are used in classification. A number of confidence measures are proposed to evaluate the performance of the neural network classifier within a statistical framework.
On local optima in learning bayesian networks
DEFF Research Database (Denmark)
Dalgaard, Jens; Kocka, Tomas; Pena, Jose
2003-01-01
This paper proposes and evaluates the k-greedy equivalence search algorithm (KES) for learning Bayesian networks (BNs) from complete data. The main characteristic of KES is that it allows a trade-off between greediness and randomness, thus exploring different good local optima. When greediness...
Automatic Thesaurus Construction Using Bayesian Networks.
Park, Young C.; Choi, Key-Sun
1996-01-01
Discusses automatic thesaurus construction and characterizes the statistical behavior of terms by using an inference network. Highlights include low-frequency terms and data sparseness, Bayesian networks, collocation maps and term similarity, constructing a thesaurus from a collocation map, and experiments with test collections. (Author/LRW)
Posterior Predictive Model Checking in Bayesian Networks
Crawford, Aaron
2014-01-01
This simulation study compared the utility of various discrepancy measures within a posterior predictive model checking (PPMC) framework for detecting different types of data-model misfit in multidimensional Bayesian network (BN) models. The investigated conditions were motivated by an applied research program utilizing an operational complex…
Diagnosis of Subtraction Bugs Using Bayesian Networks
Lee, Jihyun; Corter, James E.
2011-01-01
Diagnosis of misconceptions or "bugs" in procedural skills is difficult because of their unstable nature. This study addresses this problem by proposing and evaluating a probability-based approach to the diagnosis of bugs in children's multicolumn subtraction performance using Bayesian networks. This approach assumes a causal network relating…
Basics of Bayesian Learning - Basically Bayes
DEFF Research Database (Denmark)
Larsen, Jan
Tutorial presented at the IEEE Machine Learning for Signal Processing Workshop 2006, Maynooth, Ireland, September 8, 2006. The tutorial focuses on the basic elements of Bayesian learning and its relation to classical learning paradigms. This includes a critical discussion of the pros and cons...
Bayesian analysis of Markov point processes
DEFF Research Database (Denmark)
Berthelsen, Kasper Klitgaard; Møller, Jesper
2006-01-01
Recently Møller, Pettitt, Berthelsen and Reeves introduced a new MCMC methodology for drawing samples from a posterior distribution when the likelihood function is only specified up to a normalising constant. We illustrate the method in the setting of Bayesian inference for Markov point processes...
Bayesian Averaging is Well-Temperated
DEFF Research Database (Denmark)
Hansen, Lars Kai
2000-01-01
Bayesian predictions are stochastic just like predictions of any other inference scheme that generalize from a finite sample. While a simple variational argument shows that Bayes averaging is generalization optimal given that the prior matches the teacher parameter distribution the situation...
Bayesian calibration of car-following models
Van Hinsbergen, C.P.IJ.; Van Lint, H.W.C.; Hoogendoorn, S.P.; Van Zuylen, H.J.
2010-01-01
Recent research has revealed that there exist large inter-driver differences in car-following behavior such that different car-following models may apply to different drivers. This study applies Bayesian techniques to the calibration of car-following models, where prior distributions on each model p
Bayesian Analyses of Nonhomogeneous Autoregressive Processes
1986-09-01
random coefficient autoregressive processes have a wide applicability in the analysis of economic, sociological, biological and industrial data...1980). Approximate Bayesian Methods. Trabajos Estadistica , Vol. 32, pp. 223-237. LIU, L. M. and G. C. TIAO (1980). Random Coefficient First
Error probabilities in default Bayesian hypothesis testing
Gu, Xin; Hoijtink, Herbert; Mulder, J,
2016-01-01
This paper investigates the classical type I and type II error probabilities of default Bayes factors for a Bayesian t test. Default Bayes factors quantify the relative evidence between the null hypothesis and the unrestricted alternative hypothesis without needing to specify prior distributions for
Most frugal explanations in Bayesian networks
Kwisthout, J.H.P.
2015-01-01
Inferring the most probable explanation to a set of variables, given a partial observation of the remaining variables, is one of the canonical computational problems in Bayesian networks, with widespread applications in AI and beyond. This problem, known as MAP, is computationally intractable (NP-ha
Modelling crime linkage with Bayesian networks
J. de Zoete; M. Sjerps; D. Lagnado; N. Fenton
2015-01-01
When two or more crimes show specific similarities, such as a very distinct modus operandi, the probability that they were committed by the same offender becomes of interest. This probability depends on the degree of similarity and distinctiveness. We show how Bayesian networks can be used to model
Frelich, Lee
2016-01-01
Forest dynamics encompass changes in stand structure, species composition, and species interactions with disturbance and environment over a range of spatial and temporal scales. For convenience, spatial scale is defined as individual tree, neighborhood, stand, and landscape. Whether a given canopy-leveling disturbance will initiate a sequence of development in structure with little change in composition or initiate an episode of succession depends on a match or mismatch, respectively, with traits of the dominant tree species that allow the species to survive disturbance. When these match, certain species-disturbance type combinations lock in a pattern of stand and landscape dynamics that can persist for several generations of trees; thus, dominant tree species regulate, as well as respond to, disturbance. A complex interaction among tree species, neighborhood effects, disturbance type and severity, landform, and soils determines how stands of differing composition form and the mosaic of stands that compose the landscape. Neighborhood effects (e.g., serotinous seed rain, sprouting, shading, leaf-litter chemistry, and leaf-litter physical properties) operate at small spatial extents of the individual tree and its neighbors but play a central role in forest dynamics by contributing to patch formation at stand scales and dynamics of the entire landscape. Dominance by tree species with neutral to negative neighborhood effects leads to unstable landscape dynamics in disturbance-prone regions, wherein most stands are undergoing succession; stability can only occur under very low-severity disturbance regimes. Dominance by species with positive effects leads to stable landscape dynamics wherein only a small proportion of stands undergo succession at any one time. Positive neighborhood effects are common in temperate and boreal zones, whereas negative effects are more common in tropical climates. Landscapes with positive dynamics have alternate categories of dynamics
Improving standard practices for prediction in ungauged basins: Bayesian approach
Prieto, Cristina; Le-Vine, Nataliya; García, Eduardo; Medina, Raúl
2015-04-01
In hydrological modelling, the prediction of flows in ungauged basins is still a defiance. Among the different alternatives to quantify and reduce the uncertainty in the predictions, a Bayesian framework has proven to be advantageous. This framework allows flow prediction in ungauged basins based on regionalised hydrological indices. Being grounded on probability theory, the procedure requires a number of assumptions and decisions to be made. Among the most important ones are 1) selection of representative hydrological signatures, 2) selection of regionalization model functional form, and 3) a 'perfect' model/ input assumption. The contribution of this research is to address these three assumptions. First, to reduce an extensive set of available hydrological signatures we select a compact orthogonal set of information pieces using Principal Component Analysis. This advances the standard practice of semi-empirical selection of individual hydrological signatures. Second, we use functional-form-assumption-free Random Forests to regionalize the selected information. This allows the traditional assumption of linear regression between catchment properties and characteristics of hydrological response to be relaxes. And third, we propose utilizing non-traditional metrics to flag-up possible model/ input errors: Bayes' Factor and a newly-proposed 'Suitability' test. This addresses the typical non-realistic assumption that model is 'perfect' and the input is noise-free. The proposed methodological developments are illustrated for the empirical challenge of flow prediction in rivers in Northern Spain.
Exhausting the Information: Novel Bayesian Combination of Photometric Redshift PDFs
Kind, M Carrasco
2014-01-01
The estimation and utilization of photometric redshift (photo-z) PDFs has become increasingly important over the last few years. Primarily this is because of the prominent role photo-z PDFs play in enabling photometric survey data to be used to make cosmological constraints, especially when compared to single estimates. Currently there exist a wide variety of algorithms to compute photo-z's, each with their own strengths and weaknesses. In this paper, we present a novel and efficient Bayesian framework that combines the results from different photo-z techniques into a more powerful and robust estimate by maximizing the information from the photometric data. To demonstrate this we use a supervised machine learning technique based on prediction trees and a random forest, an unsupervised method based on self organizing maps and a random atlas, and a standard template fitting method but can be easily extend to other existing techniques. We use data from the DEEP2 survey and more than $10^6$ galaxies from the SDSS...
A tutorial on Bayesian Normal linear regression
Klauenberg, Katy; Wübbeler, Gerd; Mickan, Bodo; Harris, Peter; Elster, Clemens
2015-12-01
Regression is a common task in metrology and often applied to calibrate instruments, evaluate inter-laboratory comparisons or determine fundamental constants, for example. Yet, a regression model cannot be uniquely formulated as a measurement function, and consequently the Guide to the Expression of Uncertainty in Measurement (GUM) and its supplements are not applicable directly. Bayesian inference, however, is well suited to regression tasks, and has the advantage of accounting for additional a priori information, which typically robustifies analyses. Furthermore, it is anticipated that future revisions of the GUM shall also embrace the Bayesian view. Guidance on Bayesian inference for regression tasks is largely lacking in metrology. For linear regression models with Gaussian measurement errors this tutorial gives explicit guidance. Divided into three steps, the tutorial first illustrates how a priori knowledge, which is available from previous experiments, can be translated into prior distributions from a specific class. These prior distributions have the advantage of yielding analytical, closed form results, thus avoiding the need to apply numerical methods such as Markov Chain Monte Carlo. Secondly, formulas for the posterior results are given, explained and illustrated, and software implementations are provided. In the third step, Bayesian tools are used to assess the assumptions behind the suggested approach. These three steps (prior elicitation, posterior calculation, and robustness to prior uncertainty and model adequacy) are critical to Bayesian inference. The general guidance given here for Normal linear regression tasks is accompanied by a simple, but real-world, metrological example. The calibration of a flow device serves as a running example and illustrates the three steps. It is shown that prior knowledge from previous calibrations of the same sonic nozzle enables robust predictions even for extrapolations.
Précis of bayesian rationality: The probabilistic approach to human reasoning.
Oaksford, Mike; Chater, Nick
2009-02-01
According to Aristotle, humans are the rational animal. The borderline between rationality and irrationality is fundamental to many aspects of human life including the law, mental health, and language interpretation. But what is it to be rational? One answer, deeply embedded in the Western intellectual tradition since ancient Greece, is that rationality concerns reasoning according to the rules of logic--the formal theory that specifies the inferential connections that hold with certainty between propositions. Piaget viewed logical reasoning as defining the end-point of cognitive development; and contemporary psychology of reasoning has focussed on comparing human reasoning against logical standards. Bayesian Rationality argues that rationality is defined instead by the ability to reason about uncertainty. Although people are typically poor at numerical reasoning about probability, human thought is sensitive to subtle patterns of qualitative Bayesian, probabilistic reasoning. In Chapters 1-4 of Bayesian Rationality (Oaksford & Chater 2007), the case is made that cognition in general, and human everyday reasoning in particular, is best viewed as solving probabilistic, rather than logical, inference problems. In Chapters 5-7 the psychology of "deductive" reasoning is tackled head-on: It is argued that purportedly "logical" reasoning problems, revealing apparently irrational behaviour, are better understood from a probabilistic point of view. Data from conditional reasoning, Wason's selection task, and syllogistic inference are captured by recasting these problems probabilistically. The probabilistic approach makes a variety of novel predictions which have been experimentally confirmed. The book considers the implications of this work, and the wider "probabilistic turn" in cognitive science and artificial intelligence, for understanding human rationality.
Bayesian structural equation modeling in sport and exercise psychology.
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.
Universal Darwinism as a process of Bayesian inference
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 clo...
AMS radiocarbon dating of ancient Japanese sutras
Oda, H; Nakamura, T; Fujita, K
2000-01-01
Radiocarbon ages of ancient Japanese sutras whose historical ages were known paleographically were measured by means of accelerator mass spectrometry (AMS). Calibrated radiocarbon ages of five samples were consistent with the corresponding historical ages; the 'old wood effect' is negligible for ancient Japanese sutras. Japanese paper has been made from fresh branches grown within a few years and the interval from trimming off the branches to writing sutra on the paper is within one year. The good agreement between the calibrated radiocarbon ages and the historical ages is supported by such characteristics of Japanese paper. It is indicated in this study that Japanese sutra is a suitable sample for radiocarbon dating in the historic period because of little gap by 'old wood effect'.
Paleo-Environmental Reconstruction Using Ancient DNA
DEFF Research Database (Denmark)
Pedersen, Mikkel Winther
The aim of this thesis has been to investigate and expand the methodology and applicability for using ancient DNA deposited in lake sediments to detect and determine its genetic sources for paleo-environmental reconstruction. The aim was furthermore to put this tool into an applicable context...... solving other scientifically interesting questions. Still in its childhood, ancient environmental DNA research has a large potential for still developing, improving and discovering its possibilities and limitations in different environments and for identifying various organisms, both in terms...... of the sampling methods and strategies (taphonomic processes), the more fundamental molecular methodologies (e.g. extraction and sequencing) and eventually the bioinformatic processing. In the enclosed studies we have tried to take some principal steps towards improving this, firstly by reviewing previous...
Human evolution: a tale from ancient genomes.
Llamas, Bastien; Willerslev, Eske; Orlando, Ludovic
2017-02-05
The field of human ancient DNA (aDNA) has moved from mitochondrial sequencing that suffered from contamination and provided limited biological insights, to become a fully genomic discipline that is changing our conception of human history. Recent successes include the sequencing of extinct hominins, and true population genomic studies of Bronze Age populations. Among the emerging areas of aDNA research, the analysis of past epigenomes is set to provide more new insights into human adaptation and disease susceptibility through time. Starting as a mere curiosity, ancient human genetics has become a major player in the understanding of our evolutionary history.This article is part of the themed issue 'Evo-devo in the genomics era, and the origins of morphological diversity'.
Lipids of aquatic sediments, recent and ancient
Eglinton, G.; Hajibrahim, S. K.; Maxwell, J. R.; Quirke, J. M. E.; Shaw, G. J.; Volkman, J. K.; Wardroper, A. M. K.
1979-01-01
Computerized gas chromatography-mass spectrometry (GC-MS) is now an essential tool in the analysis of the complex mixtures of lipids (geolipids) encountered in aquatic sediments, both 'recent' (less than 1 million years old) and ancient. The application of MS, and particularly GC-MS, has been instrumental in the rapid development of organic geochemistry and environmental organic chemistry in recent years. The techniques used have resulted in the identification of numerous compounds of a variety of types in sediments. Most attention has been concentrated on molecules of limited size, mainly below 500 molecular mass, and of limited functionality, for examples, hydrocarbons, fatty acids and alcohols. Examples from recent studies (at Bristol) of contemporary, 'recent' and ancient sediments are presented and discussed.
Putative ancient microorganisms from amber nuggets.
Veiga-Crespo, Patricia; Blasco, Lucía; Poza, Margarita; Villa, Tomás G
2007-06-01
Evolutionary microbiology studies based on the isolation of ancient DNA and/or microbial samples are scarce due to the difficulty of finding well preserved biological specimens. However, amber is a fossil resin with natural preserving properties for microbial cells and DNA. The visualization by transmission electron microscopy of different microorganism-like specimens found in amber nuggets from both the Miocene and the Cretaceous periods was accompanied by studies of ancient DNA obtained from the nuggets. After the design of specific primers based on the present sequences of both genes in Saccharomyces cerevisiae, the ancestral AGP2 sequence from the Miocene, as well as the 18S rRNA from the Cretaceous, were amplified.
Rangifer and man: An ancient relationship
Directory of Open Access Journals (Sweden)
Bryan Gordon
2003-04-01
Full Text Available A long-term relationship between Rangifer and humans is documented in three case studies: the Canadian Barrenlands (8000 years ago to Historic period, Ice-Age France (11 000-19 000 years ago and Mesolithic Russia (7000¬10 000 years ago. Ancient human and herd migration occurred in all areas, based upon Rangifer remains and seasonal variations in tools along reconstructed migration routes, with few if any hunting camps outside the routes. An April peak of ancient human births is inferred from the historic record where we see births occurring nine months after peak nutritional states in herds and people. The origin of reindeer domestication and breeding in Eurasia is discussed.
Segmentation of Ancient Telugu Text Documents
Directory of Open Access Journals (Sweden)
Srinivasa Rao A.V
2012-07-01
Full Text Available OCR of ancient document images remains a challenging task till date. Scanning process itself introduces deformation of document images. Cleaning process of these document images will result in information loss. Segmentation contributes an invariance process in OCR. Complex scripts, like derivatives of Brahmi, encounter many problems in the segmentation process. Segmentation of meaningful units, (instead of isolated patterns, revealed interesting trends. A segmentation technique for the ancient Telugu document image into meaningful units is proposed. The topological features of the meaningful units within the script line are adopted as a basis, while segmenting the text line. Horizontal profile pattern is convolved with Gaussian kernel. The statistical properties of meaningful units are explored by extensively analyzing the geometrical patterns of the meaningful unit. The efficiency of the proposed algorithm involving segmentation process is found to be 73.5% for the case of uncleaned document images.
The ancient Greeks present: Rational Trigonometry
Wildberger, N J
2008-01-01
Pythagoras' theorem, the area of a triangle as one half the base times the height, and Heron's formula are amongst the most important and useful results of ancient Greek geometry. Here we look at all three in a new and improved light, using quadrance not distance. This leads to a simpler and more elegant trigonometry, in which angle is replaced by spread, and which extends to arbitrary fields and more general quadratic forms.
Computed tomography of ancient Egyptian mummies.
Harwood-Nash, D C
1979-12-01
This first report of the application of computed tomography (CT) to the study of ancient mummies, the desiccated brain of a boy and the body of a young woman within her cartonnage, shows that CT is uniquely suitable for the study of such antiquities, a study that does not necessitate destruction of the mummy or its cartonnage. Exquisite images result that are of great paleoanatomical, paleopathological, and archeological significance.
Volatile and Isotopic Imprints of Ancient Mars
Mahaffy, Paul R.; Conrad, Pamela G.
2015-01-01
The science investigations enabled by Curiosity rover's instruments focus on identifying and exploring the habitability of the Martian environment. Measurements of noble gases, organic and inorganic compounds, and the isotopes of light elements permit the study of the physical and chemical processes that have transformed Mars throughout its history. Samples of the atmosphere, volatiles released from soils, and rocks from the floor of Gale Crater have provided a wealth of new data and a window into conditions on ancient Mars.
Chemistry Progress and Civilization in Ancient China
Institute of Scientific and Technical Information of China (English)
JIANG Yu-Qian; RUAN Shu-Xiang; TANG Shan; SHUAI Zhi-Gang
2011-01-01
@@ During the 6,000 years of Chinese civilization, chemistry has played an essential role.The bronzed chime bells of the Warring States Period (475-221 BC) unearthed in Hubei Province shows not only the excellence in musical instruments in ancient China, but also the technological advances in metallurgy.Chinese alchemy was not originated from the quest to turn common metals to gold, instead, it was for searching medicines for longevity of human beings, mostly practised by Taoists.
Ancient News: HMGBs are Universal Sentinels
Institute of Scientific and Technical Information of China (English)
Marco E. Bianchi; Barbara Celona
2010-01-01
@@ Yanai et al. (2009, Nature 462, 99-103) have shown that high mobility group boxs (HMGBs) are universal sensors of viral nucleic acids, and thus of cell infection. This appears to be an evolutionary ancient mechanism of virus detection, and possibly might be a facet of a more general propensity of HMGBs to act as integrators of signals that pertain to peace and stress, life and death.
US Forest Service Forest Health Protection Insect and Disease Survey
US Forest Service, Department of Agriculture — This data is a compilation of forest insect, disease and abiotic damage mapped by aerial detection surveys on forested areas in the United States. US Forest Service,...
Yousefpour, Rasoul; Temperli, Christian; Bugmann, Harald; Elkin, Che; Hanewinkel, Marc; Meilby, Henrik; Jacobsen, Jette Bredahl; Thorsen, Bo Jellesmark
2013-06-15
We study climate uncertainty and how managers' beliefs about climate change develop and influence their decisions. We develop an approach for updating knowledge and beliefs based on the observation of forest and climate variables and illustrate its application for the adaptive management of an even-aged Norway spruce (Picea abies L. Karst) forest in the Black Forest, Germany. We simulated forest development under a range of climate change scenarios and forest management alternatives. Our analysis used Bayesian updating and Dempster's rule of combination to simulate how observations of climate and forest variables may influence a decision maker's beliefs about climate development and thereby management decisions. While forest managers may be inclined to rely on observed forest variables to infer climate change and impacts, we found that observation of climate state, e.g. temperature or precipitation is superior for updating beliefs and supporting decision-making. However, with little conflict among information sources, the strongest evidence would be offered by a combination of at least two informative variables, e.g., temperature and precipitation. The success of adaptive forest management depends on when managers switch to forward-looking management schemes. Thus, robust climate adaptation policies may depend crucially on a better understanding of what factors influence managers' belief in climate change.
Bayesian network learning for natural hazard assessments
Vogel, Kristin
2016-04-01
Even though quite different in occurrence and consequences, from a modelling perspective many natural hazards share similar properties and challenges. Their complex nature as well as lacking knowledge about their driving forces and potential effects make their analysis demanding. On top of the uncertainty about the modelling framework, inaccurate or incomplete event observations and the intrinsic randomness of the natural phenomenon add up to different interacting layers of uncertainty, which require a careful handling. Thus, for reliable natural hazard assessments it is crucial not only to capture and quantify involved uncertainties, but also to express and communicate uncertainties in an intuitive way. Decision-makers, who often find it difficult to deal with uncertainties, might otherwise return to familiar (mostly deterministic) proceedings. In the scope of the DFG research training group „NatRiskChange" we apply the probabilistic framework of Bayesian networks for diverse natural hazard and vulnerability studies. The great potential of Bayesian networks was already shown in previous natural hazard assessments. Treating each model component as random variable, Bayesian networks aim at capturing the joint distribution of all considered variables. Hence, each conditional distribution of interest (e.g. the effect of precautionary measures on damage reduction) can be inferred. The (in-)dependencies between the considered variables can be learned purely data driven or be given by experts. Even a combination of both is possible. By translating the (in-)dependences into a graph structure, Bayesian networks provide direct insights into the workings of the system and allow to learn about the underlying processes. Besides numerous studies on the topic, learning Bayesian networks from real-world data remains challenging. In previous studies, e.g. on earthquake induced ground motion and flood damage assessments, we tackled the problems arising with continuous variables
2000 Year-old ancient equids: an ancient-DNA lesson from pompeii remains.
Di Bernardo, Giovanni; Del Gaudio, Stefania; Galderisi, Umberto; Cipollaro, Marilena
2004-11-15
Ancient DNA extracted from 2000 year-old equine bones was examined in order to amplify mitochondrial and nuclear DNA fragments. A specific equine satellite-type sequence representing 3.7%-11% of the entire equine genome, proved to be a suitable target to address the question of the presence of aDNA in ancient bones. The PCR strategy designed to investigate this specific target also allowed us to calculate the molecular weight of amplifiable DNA fragments. Sequencing of a 370 bp DNA fragment of mitochondrial control region allowed the comparison of ancient DNA sequences with those of modern horses to assess their genetic relationship. The 16S rRNA mitochondrial gene was also examined to unravel the post-mortem base modification feature and to test the status of Pompeian equids taxon on the basis of a Mae III restriction site polymorphism.
Directory of Open Access Journals (Sweden)
Stella Xu
2012-05-01
Full Text Available The ancient history of Korea has been one of the most controversial and difficult phases to incorporate into an East Asian history survey class, not only because there are indeed quite a number of contested issues, but also because very few updated materials are available in English. This essay aims to provide a comprehensive and critical overview of research on the topic of Korean ancient history in the past six decades (mainly in South Korea, so that the ancient history of Korea can be understood first within the broader frame of East Asian history, and then in relation to the intellectual and ideological evolution which has significantly impacted historical interpretations in South Korea.
Bayesian system reliability assessment under fuzzy environments
Energy Technology Data Exchange (ETDEWEB)
Wu, H.-C
2004-03-01
The Bayesian system reliability assessment under fuzzy environments is proposed in this paper. In order to apply the Bayesian approach, the fuzzy parameters are assumed as fuzzy random variables with fuzzy prior distributions. The (conventional) Bayes estimation method will be used to create the fuzzy Bayes point estimator of system reliability by invoking the well-known theorem called 'Resolution Identity' in fuzzy sets theory. On the other hand, we also provide the computational procedures to evaluate the membership degree of any given Bayes point estimate of system reliability. In order to achieve this purpose, we transform the original problem into a nonlinear programming problem. This nonlinear programming problem is then divided into four subproblems for the purpose of simplifying computation. Finally, the subproblems can be solved by using any commercial optimizers, e.g. GAMS or LINGO.
Bayesian information fusion networks for biosurveillance applications.
Mnatsakanyan, Zaruhi R; Burkom, Howard S; Coberly, Jacqueline S; Lombardo, Joseph S
2009-01-01
This study introduces new information fusion algorithms to enhance disease surveillance systems with Bayesian decision support capabilities. A detection system was built and tested using chief complaints from emergency department visits, International Classification of Diseases Revision 9 (ICD-9) codes from records of outpatient visits to civilian and military facilities, and influenza surveillance data from health departments in the National Capital Region (NCR). Data anomalies were identified and distribution of time offsets between events in the multiple data streams were established. The Bayesian Network was built to fuse data from multiple sources and identify influenza-like epidemiologically relevant events. Results showed increased specificity compared with the alerts generated by temporal anomaly detection algorithms currently deployed by NCR health departments. Further research should be done to investigate correlations between data sources for efficient fusion of the collected data.
Bayesian Population Projections for the United Nations.
Raftery, Adrian E; Alkema, Leontine; Gerland, Patrick
2014-02-01
The United Nations regularly publishes projections of the populations of all the world's countries broken down by age and sex. These projections are the de facto standard and are widely used by international organizations, governments and researchers. Like almost all other population projections, they are produced using the standard deterministic cohort-component projection method and do not yield statements of uncertainty. We describe a Bayesian method for producing probabilistic population projections for most countries that the United Nations could use. It has at its core Bayesian hierarchical models for the total fertility rate and life expectancy at birth. We illustrate the method and show how it can be extended to address concerns about the UN's current assumptions about the long-term distribution of fertility. The method is implemented in the R packages bayesTFR, bayesLife, bayesPop and bayesDem.
Bayesian peak picking for NMR spectra.
Cheng, Yichen; Gao, Xin; Liang, Faming
2014-02-01
Protein structure determination is a very important topic in structural genomics, which helps people to understand varieties of biological functions such as protein-protein interactions, protein-DNA interactions and so on. Nowadays, nuclear magnetic resonance (NMR) has often been used to determine the three-dimensional structures of protein in vivo. This study aims to automate the peak picking step, the most important and tricky step in NMR structure determination. We propose to model the NMR spectrum by a mixture of bivariate Gaussian densities and use the stochastic approximation Monte Carlo algorithm as the computational tool to solve the problem. Under the Bayesian framework, the peak picking problem is casted as a variable selection problem. The proposed method can automatically distinguish true peaks from false ones without preprocessing the data. To the best of our knowledge, this is the first effort in the literature that tackles the peak picking problem for NMR spectrum data using Bayesian method.
Neuroadaptive Bayesian Optimization and Hypothesis Testing.
Lorenz, Romy; Hampshire, Adam; Leech, Robert
2017-03-01
Cognitive neuroscientists are often interested in broad research questions, yet use overly narrow experimental designs by considering only a small subset of possible experimental conditions. This limits the generalizability and reproducibility of many research findings. Here, we propose an alternative approach that resolves these problems by taking advantage of recent developments in real-time data analysis and machine learning. Neuroadaptive Bayesian optimization is a powerful strategy to efficiently explore more experimental conditions than is currently possible with standard methodology. We argue that such an approach could broaden the hypotheses considered in cognitive science, improving the generalizability of findings. In addition, Bayesian optimization can be combined with preregistration to cover exploration, mitigating researcher bias more broadly and improving reproducibility.
QBism, the Perimeter of Quantum Bayesianism
Fuchs, Christopher A
2010-01-01
This article summarizes the Quantum Bayesian point of view of quantum mechanics, with special emphasis on the view's outer edges---dubbed QBism. QBism has its roots in personalist Bayesian probability theory, is crucially dependent upon the tools of quantum information theory, and most recently, has set out to investigate whether the physical world might be of a type sketched by some false-started philosophies of 100 years ago (pragmatism, pluralism, nonreductionism, and meliorism). Beyond conceptual issues, work at Perimeter Institute is focused on the hard technical problem of finding a good representation of quantum mechanics purely in terms of probabilities, without amplitudes or Hilbert-space operators. The best candidate representation involves a mysterious entity called a symmetric informationally complete quantum measurement. Contemplation of it gives a way of thinking of the Born Rule as an addition to the rules of probability theory, applicable when an agent considers gambling on the consequences of...
Bayesian network modelling of upper gastrointestinal bleeding
Aisha, Nazziwa; Shohaimi, Shamarina; Adam, Mohd Bakri
2013-09-01
Bayesian networks are graphical probabilistic models that represent causal and other relationships between domain variables. In the context of medical decision making, these models have been explored to help in medical diagnosis and prognosis. In this paper, we discuss the Bayesian network formalism in building medical support systems and we learn a tree augmented naive Bayes Network (TAN) from gastrointestinal bleeding data. The accuracy of the TAN in classifying the source of gastrointestinal bleeding into upper or lower source is obtained. The TAN achieves a high classification accuracy of 86% and an area under curve of 92%. A sensitivity analysis of the model shows relatively high levels of entropy reduction for color of the stool, history of gastrointestinal bleeding, consistency and the ratio of blood urea nitrogen to creatinine. The TAN facilitates the identification of the source of GIB and requires further validation.
Bayesian parameter estimation for effective field theories
Wesolowski, S.; Klco, N.; Furnstahl, R. J.; Phillips, D. R.; Thapaliya, A.
2016-07-01
We present procedures based on Bayesian statistics for estimating, from data, the parameters of effective field theories (EFTs). The extraction of low-energy constants (LECs) is guided by theoretical expectations in a quantifiable way through the specification of Bayesian priors. A prior for natural-sized LECs reduces the possibility of overfitting, and leads to a consistent accounting of different sources of uncertainty. A set of diagnostic tools is developed that analyzes the fit and ensures that the priors do not bias the EFT parameter estimation. The procedures are illustrated using representative model problems, including the extraction of LECs for the nucleon-mass expansion in SU(2) chiral perturbation theory from synthetic lattice data.
BONNSAI: correlated stellar observables in Bayesian methods
Schneider, F R N; Fossati, L; Langer, N; de Koter, A
2016-01-01
In an era of large spectroscopic surveys of stars and big data, sophisticated statistical methods become more and more important in order to infer fundamental stellar parameters such as mass and age. Bayesian techniques are powerful methods because they can match all available observables simultaneously to stellar models while taking prior knowledge properly into account. However, in most cases it is assumed that observables are uncorrelated which is generally not the case. Here, we include correlations in the Bayesian code BONNSAI by incorporating the covariance matrix in the likelihood function. We derive a parametrisation of the covariance matrix that, in addition to classical uncertainties, only requires the specification of a correlation parameter that describes how observables co-vary. Our correlation parameter depends purely on the method with which observables have been determined and can be analytically derived in some cases. This approach therefore has the advantage that correlations can be accounte...
Subgroup finding via Bayesian additive regression trees.
Sivaganesan, Siva; Müller, Peter; Huang, Bin
2017-03-09
We provide a Bayesian decision theoretic approach to finding subgroups that have elevated treatment effects. Our approach separates the modeling of the response variable from the task of subgroup finding and allows a flexible modeling of the response variable irrespective of potential subgroups of interest. We use Bayesian additive regression trees to model the response variable and use a utility function defined in terms of a candidate subgroup and the predicted response for that subgroup. Subgroups are identified by maximizing the expected utility where the expectation is taken with respect to the posterior predictive distribution of the response, and the maximization is carried out over an a priori specified set of candidate subgroups. Our approach allows subgroups based on both quantitative and categorical covariates. We illustrate the approach using simulated data set study and a real data set. Copyright © 2017 John Wiley & Sons, Ltd.
Bayesian modelling of geostatistical malaria risk data
Directory of Open Access Journals (Sweden)
L. Gosoniu
2006-11-01
Full Text Available Bayesian geostatistical models applied to malaria risk data quantify the environment-disease relations, identify significant environmental predictors of malaria transmission and provide model-based predictions of malaria risk together with their precision. These models are often based on the stationarity assumption which implies that spatial correlation is a function of distance between locations and independent of location. We relax this assumption and analyse malaria survey data in Mali using a Bayesian non-stationary model. Model fit and predictions are based on Markov chain Monte Carlo simulation methods. Model validation compares the predictive ability of the non-stationary model with the stationary analogue. Results indicate that the stationarity assumption is important because it influences the significance of environmental factors and the corresponding malaria risk maps.
Bayesian modelling of geostatistical malaria risk data.
Gosoniu, L; Vounatsou, P; Sogoba, N; Smith, T
2006-11-01
Bayesian geostatistical models applied to malaria risk data quantify the environment-disease relations, identify significant environmental predictors of malaria transmission and provide model-based predictions of malaria risk together with their precision. These models are often based on the stationarity assumption which implies that spatial correlation is a function of distance between locations and independent of location. We relax this assumption and analyse malaria survey data in Mali using a Bayesian non-stationary model. Model fit and predictions are based on Markov chain Monte Carlo simulation methods. Model validation compares the predictive ability of the non-stationary model with the stationary analogue. Results indicate that the stationarity assumption is important because it influences the significance of environmental factors and the corresponding malaria risk maps.
Quantum-like Representation of Bayesian Updating
Asano, Masanari; Ohya, Masanori; Tanaka, Yoshiharu; Khrennikov, Andrei; Basieva, Irina
2011-03-01
Recently, applications of quantum mechanics to coginitive psychology have been discussed, see [1]-[11]. It was known that statistical data obtained in some experiments of cognitive psychology cannot be described by classical probability model (Kolmogorov's model) [12]-[15]. Quantum probability is one of the most advanced mathematical models for non-classical probability. In the paper of [11], we proposed a quantum-like model describing decision-making process in a two-player game, where we used the generalized quantum formalism based on lifting of density operators [16]. In this paper, we discuss the quantum-like representation of Bayesian inference, which has been used to calculate probabilities for decision making under uncertainty. The uncertainty is described in the form of quantum superposition, and Bayesian updating is explained as a reduction of state by quantum measurement.
Bayesian Cosmological inference beyond statistical isotropy
Souradeep, Tarun; Das, Santanu; Wandelt, Benjamin
2016-10-01
With advent of rich data sets, computationally challenge of inference in cosmology has relied on stochastic sampling method. First, I review the widely used MCMC approach used to infer cosmological parameters and present a adaptive improved implementation SCoPE developed by our group. Next, I present a general method for Bayesian inference of the underlying covariance structure of random fields on a sphere. We employ the Bipolar Spherical Harmonic (BipoSH) representation of general covariance structure on the sphere. We illustrate the efficacy of the method with a principled approach to assess violation of statistical isotropy (SI) in the sky maps of Cosmic Microwave Background (CMB) fluctuations. The general, principled, approach to a Bayesian inference of the covariance structure in a random field on a sphere presented here has huge potential for application to other many aspects of cosmology and astronomy, as well as, more distant areas of research like geosciences and climate modelling.
Machine learning a Bayesian and optimization perspective
Theodoridis, Sergios
2015-01-01
This tutorial text gives a unifying perspective on machine learning by covering both probabilistic and deterministic approaches, which rely on optimization techniques, as well as Bayesian inference, which is based on a hierarchy of probabilistic models. The book presents the major machine learning methods as they have been developed in different disciplines, such as statistics, statistical and adaptive signal processing and computer science. Focusing on the physical reasoning behind the mathematics, all the various methods and techniques are explained in depth, supported by examples and problems, giving an invaluable resource to the student and researcher for understanding and applying machine learning concepts. The book builds carefully from the basic classical methods to the most recent trends, with chapters written to be as self-contained as possible, making the text suitable for different courses: pattern recognition, statistical/adaptive signal processing, statistical/Bayesian learning, as well as shor...
Probabilistic forecasting and Bayesian data assimilation
Reich, Sebastian
2015-01-01
In this book the authors describe the principles and methods behind probabilistic forecasting and Bayesian data assimilation. Instead of focusing on particular application areas, the authors adopt a general dynamical systems approach, with a profusion of low-dimensional, discrete-time numerical examples designed to build intuition about the subject. Part I explains the mathematical framework of ensemble-based probabilistic forecasting and uncertainty quantification. Part II is devoted to Bayesian filtering algorithms, from classical data assimilation algorithms such as the Kalman filter, variational techniques, and sequential Monte Carlo methods, through to more recent developments such as the ensemble Kalman filter and ensemble transform filters. The McKean approach to sequential filtering in combination with coupling of measures serves as a unifying mathematical framework throughout Part II. Assuming only some basic familiarity with probability, this book is an ideal introduction for graduate students in ap...
Bayesian Peak Picking for NMR Spectra
Cheng, Yichen
2014-02-01
Protein structure determination is a very important topic in structural genomics, which helps people to understand varieties of biological functions such as protein-protein interactions, protein–DNA interactions and so on. Nowadays, nuclear magnetic resonance (NMR) has often been used to determine the three-dimensional structures of protein in vivo. This study aims to automate the peak picking step, the most important and tricky step in NMR structure determination. We propose to model the NMR spectrum by a mixture of bivariate Gaussian densities and use the stochastic approximation Monte Carlo algorithm as the computational tool to solve the problem. Under the Bayesian framework, the peak picking problem is casted as a variable selection problem. The proposed method can automatically distinguish true peaks from false ones without preprocessing the data. To the best of our knowledge, this is the first effort in the literature that tackles the peak picking problem for NMR spectrum data using Bayesian method.
Bayesian Model comparison of Higgs couplings
Bergstrom, Johannes
2014-01-01
We investigate the possibility of contributions from physics beyond the Standard Model (SM) to the Higgs couplings, in the light of the LHC data. The work is performed within an interim framework where the magnitude of the Higgs production and decay rates are rescaled though Higgs coupling scale factors. We perform Bayesian parameter inference on these scale factors, concluding that there is good compatibility with the SM. Furthermore, we carry out Bayesian model comparison on all models where any combination of scale factors can differ from their SM values and find that typically models with fewer free couplings are strongly favoured. We consider the evidence that each coupling individually equals the SM value, making the minimal assumptions on the other couplings. Finally, we make a comparison of the SM against a single "not-SM" model, and find that there is moderate to strong evidence for the SM.
The NIFTY way of Bayesian signal inference
Energy Technology Data Exchange (ETDEWEB)
Selig, Marco, E-mail: mselig@mpa-Garching.mpg.de [Max Planck Institut für Astrophysik, Karl-Schwarzschild-Straße 1, D-85748 Garching, Germany, and Ludwig-Maximilians-Universität München, Geschwister-Scholl-Platz 1, D-80539 München (Germany)
2014-12-05
We introduce NIFTY, 'Numerical Information Field Theory', a software package for the development of Bayesian signal inference algorithms that operate independently from any underlying spatial grid and its resolution. A large number of Bayesian and Maximum Entropy methods for 1D signal reconstruction, 2D imaging, as well as 3D tomography, appear formally similar, but one often finds individualized implementations that are neither flexible nor easily transferable. Signal inference in the framework of NIFTY can be done in an abstract way, such that algorithms, prototyped in 1D, can be applied to real world problems in higher-dimensional settings. NIFTY as a versatile library is applicable and already has been applied in 1D, 2D, 3D and spherical settings. A recent application is the D{sup 3}PO algorithm targeting the non-trivial task of denoising, deconvolving, and decomposing photon observations in high energy astronomy.
Software Health Management with Bayesian Networks
Mengshoel, Ole; Schumann, JOhann
2011-01-01
Most modern aircraft as well as other complex machinery is equipped with diagnostics systems for its major subsystems. During operation, sensors provide important information about the subsystem (e.g., the engine) and that information is used to detect and diagnose faults. Most of these systems focus on the monitoring of a mechanical, hydraulic, or electromechanical subsystem of the vehicle or machinery. Only recently, health management systems that monitor software have been developed. In this paper, we will discuss our approach of using Bayesian networks for Software Health Management (SWHM). We will discuss SWHM requirements, which make advanced reasoning capabilities for the detection and diagnosis important. Then we will present our approach to using Bayesian networks for the construction of health models that dynamically monitor a software system and is capable of detecting and diagnosing faults.
Integrative bayesian network analysis of genomic data.
Ni, Yang; Stingo, Francesco C; Baladandayuthapani, Veerabhadran
2014-01-01
Rapid development of genome-wide profiling technologies has made it possible to conduct integrative analysis on genomic data from multiple platforms. In this study, we develop a novel integrative Bayesian network approach to investigate the relationships between genetic and epigenetic alterations as well as how these mutations affect a patient's clinical outcome. We take a Bayesian network approach that admits a convenient decomposition of the joint distribution into local distributions. Exploiting the prior biological knowledge about regulatory mechanisms, we model each local distribution as linear regressions. This allows us to analyze multi-platform genome-wide data in a computationally efficient manner. We illustrate the performance of our approach through simulation studies. Our methods are motivated by and applied to a multi-platform glioblastoma dataset, from which we reveal several biologically relevant relationships that have been validated in the literature as well as new genes that could potentially be novel biomarkers for cancer progression.
Learning Bayesian networks using genetic algorithm
Institute of Scientific and Technical Information of China (English)
Chen Fei; Wang Xiufeng; Rao Yimei
2007-01-01
A new method to evaluate the fitness of the Bayesian networks according to the observed data is provided. The main advantage of this criterion is that it is suitable for both the complete and incomplete cases while the others not.Moreover it facilitates the computation greatly. In order to reduce the search space, the notation of equivalent class proposed by David Chickering is adopted. Instead of using the method directly, the novel criterion, variable ordering, and equivalent class are combined,moreover the proposed mthod avoids some problems caused by the previous one. Later, the genetic algorithm which allows global convergence, lack in the most of the methods searching for Bayesian network is applied to search for a good model in thisspace. To speed up the convergence, the genetic algorithm is combined with the greedy algorithm. Finally, the simulation shows the validity of the proposed approach.
A Bayesian nonparametric meta-analysis model.
Karabatsos, George; Talbott, Elizabeth; Walker, Stephen G
2015-03-01
In a meta-analysis, it is important to specify a model that adequately describes the effect-size distribution of the underlying population of studies. The conventional normal fixed-effect and normal random-effects models assume a normal effect-size population distribution, conditionally on parameters and covariates. For estimating the mean overall effect size, such models may be adequate, but for prediction, they surely are not if the effect-size distribution exhibits non-normal behavior. To address this issue, we propose a Bayesian nonparametric meta-analysis model, which can describe a wider range of effect-size distributions, including unimodal symmetric distributions, as well as skewed and more multimodal distributions. We demonstrate our model through the analysis of real meta-analytic data arising from behavioral-genetic research. We compare the predictive performance of the Bayesian nonparametric model against various conventional and more modern normal fixed-effects and random-effects models.
Bayesian image reconstruction: Application to emission tomography
Energy Technology Data Exchange (ETDEWEB)
Nunez, J.; Llacer, J.
1989-02-01
In this paper we propose a Maximum a Posteriori (MAP) method of image reconstruction in the Bayesian framework for the Poisson noise case. We use entropy to define the prior probability and likelihood to define the conditional probability. The method uses sharpness parameters which can be theoretically computed or adjusted, allowing us to obtain MAP reconstructions without the problem of the grey'' reconstructions associated with the pre Bayesian reconstructions. We have developed several ways to solve the reconstruction problem and propose a new iterative algorithm which is stable, maintains positivity and converges to feasible images faster than the Maximum Likelihood Estimate method. We have successfully applied the new method to the case of Emission Tomography, both with simulated and real data. 41 refs., 4 figs., 1 tab.
Bayesian inference for pulsar timing models
Vigeland, Sarah J
2013-01-01
The extremely regular, periodic radio emission from millisecond pulsars make them useful tools for studying neutron star astrophysics, general relativity, and low-frequency gravitational waves. These studies require that the observed pulse time of arrivals are fit to complicated timing models that describe numerous effects such as the astrometry of the source, the evolution of the pulsar's spin, the presence of a binary companion, and the propagation of the pulses through the interstellar medium. In this paper, we discuss the benefits of using Bayesian inference to obtain these timing solutions. These include the validation of linearized least-squares model fits when they are correct, and the proper characterization of parameter uncertainties when they are not; the incorporation of prior parameter information and of models of correlated noise; and the Bayesian comparison of alternative timing models. We describe our computational setup, which combines the timing models of tempo2 with the nested-sampling integ...
Structure Learning in Bayesian Sensorimotor Integration.
Directory of Open Access Journals (Sweden)
Tim Genewein
2015-08-01
Full Text Available Previous studies have shown that sensorimotor processing can often be described by Bayesian learning, in particular the integration of prior and feedback information depending on its degree of reliability. Here we test the hypothesis that the integration process itself can be tuned to the statistical structure of the environment. We exposed human participants to a reaching task in a three-dimensional virtual reality environment where we could displace the visual feedback of their hand position in a two dimensional plane. When introducing statistical structure between the two dimensions of the displacement, we found that over the course of several days participants adapted their feedback integration process in order to exploit this structure for performance improvement. In control experiments we found that this adaptation process critically depended on performance feedback and could not be induced by verbal instructions. Our results suggest that structural learning is an important meta-learning component of Bayesian sensorimotor integration.
Bayesian parameter estimation for effective field theories
Wesolowski, S; Furnstahl, R J; Phillips, D R; Thapaliya, A
2015-01-01
We present procedures based on Bayesian statistics for effective field theory (EFT) parameter estimation from data. The extraction of low-energy constants (LECs) is guided by theoretical expectations that supplement such information in a quantifiable way through the specification of Bayesian priors. A prior for natural-sized LECs reduces the possibility of overfitting, and leads to a consistent accounting of different sources of uncertainty. A set of diagnostic tools are developed that analyze the fit and ensure that the priors do not bias the EFT parameter estimation. The procedures are illustrated using representative model problems and the extraction of LECs for the nucleon mass expansion in SU(2) chiral perturbation theory from synthetic lattice data.
Bayesian data analysis tools for atomic physics
Trassinelli, Martino
2016-01-01
We present an introduction to some concepts of Bayesian data analysis in the context of atomic physics. Starting from basic rules of probability, we present the Bayes' theorem and its applications. In particular we discuss about how to calculate simple and joint probability distributions and the Bayesian evidence, a model dependent quantity that allows to assign probabilities to different hypotheses from the analysis of a same data set. To give some practical examples, these methods are applied to two concrete cases. In the first example, the presence or not of a satellite line in an atomic spectrum is investigated. In the second example, we determine the most probable model among a set of possible profiles from the analysis of a statistically poor spectrum. We show also how to calculate the probability distribution of the main spectral component without having to determine uniquely the spectrum modeling. For these two studies, we implement the program Nested fit to calculate the different probability distrib...
A Bayesian approach to person perception.
Clifford, C W G; Mareschal, I; Otsuka, Y; Watson, T L
2015-11-01
Here we propose a Bayesian approach to person perception, outlining the theoretical position and a methodological framework for testing the predictions experimentally. We use the term person perception to refer not only to the perception of others' personal attributes such as age and sex but also to the perception of social signals such as direction of gaze and emotional expression. The Bayesian approach provides a formal description of the way in which our perception combines current sensory evidence with prior expectations about the structure of the environment. Such expectations can lead to unconscious biases in our perception that are particularly evident when sensory evidence is uncertain. We illustrate the ideas with reference to our recent studies on gaze perception which show that people have a bias to perceive the gaze of others as directed towards themselves. We also describe a potential application to the study of the perception of a person's sex, in which a bias towards perceiving males is typically observed.
Bayesian analysis of multiple direct detection experiments
Arina, Chiara
2013-01-01
Bayesian methods offer a coherent and efficient framework for implementing uncertainties into induction problems. In this article, we review how this approach applies to the analysis of dark matter direct detection experiments. In particular we discuss the exclusion limit of XENON100 and the debated hints of detection under the hypothesis of a WIMP signal. Within parameter inference, marginalizing consistently over uncertainties to extract robust posterior probability distributions, we find that the claimed tension between XENON100 and the other experiments can be partially alleviated in isospin violating scenario, while elastic scattering model appears to be compatible with the classical approach. We then move to model comparison, for which Bayesian methods are particularly well suited. Firstly, we investigate the annual modulation seen in CoGeNT data, finding that there is weak evidence for a modulation. Modulation models due to other physics compare unfavorably with the WIMP models, paying the price for th...
Bayesianism and inference to the best explanation
Directory of Open Access Journals (Sweden)
Valeriano IRANZO
2008-01-01
Full Text Available Bayesianism and Inference to the best explanation (IBE are two different models of inference. Recently there has been some debate about the possibility of “bayesianizing” IBE. Firstly I explore several alternatives to include explanatory considerations in Bayes’s Theorem. Then I distinguish two different interpretations of prior probabilities: “IBE-Bayesianism” (IBE-Bay and “frequentist-Bayesianism” (Freq-Bay. After detailing the content of the latter, I propose a rule for assessing the priors. I also argue that Freq-Bay: (i endorses a role for explanatory value in the assessment of scientific hypotheses; (ii avoids a purely subjectivist reading of prior probabilities; and (iii fits better than IBE-Bayesianism with two basic facts about science, i.e., the prominent role played by empirical testing and the existence of many scientific theories in the past that failed to fulfil their promises and were subsequently abandoned.
Narrowband interference parameterization for sparse Bayesian recovery
Ali, Anum
2015-09-11
This paper addresses the problem of narrowband interference (NBI) in SC-FDMA systems by using tools from compressed sensing and stochastic geometry. The proposed NBI cancellation scheme exploits the frequency domain sparsity of the unknown signal and adopts a Bayesian sparse recovery procedure. This is done by keeping a few randomly chosen sub-carriers data free to sense the NBI signal at the receiver. As Bayesian recovery requires knowledge of some NBI parameters (i.e., mean, variance and sparsity rate), we use tools from stochastic geometry to obtain analytical expressions for the required parameters. Our simulation results validate the analysis and depict suitability of the proposed recovery method for NBI mitigation. © 2015 IEEE.
The Bayesian Who Knew Too Much
Benétreau-Dupin, Yann
2014-01-01
In several papers, John Norton has argued that Bayesianism cannot handle ignorance adequately due to its inability to distinguish between neutral and disconfirming evidence. He argued that this inability sows confusion in, e.g., anthropic reasoning in cosmology or the Doomsday argument, by allowing one to draw unwarranted conclusions from a lack of knowledge. Norton has suggested criteria for a candidate for representation of neutral support. Imprecise credences (families of credal probability functions) constitute a Bayesian-friendly framework that allows us to avoid inadequate neutral priors and better handle ignorance. The imprecise model generally agrees with Norton's representation of ignorance but requires that his criterion of self-duality be reformulated or abandoned
Yu, Jihnhee; Hutson, Alan D; Siddiqui, Adnan H; Kedron, Mary A
2016-02-01
In some small clinical trials, toxicity is not a primary endpoint; however, it often has dire effects on patients' quality of life and is even life-threatening. For such clinical trials, rigorous control of the overall incidence of adverse events is desirable, while simultaneously collecting safety information. In this article, we propose group sequential toxicity monitoring strategies to control overall toxicity incidents below a certain level as opposed to performing hypothesis testing, which can be incorporated into an existing study design based on the primary endpoint. We consider two sequential methods: a non-Bayesian approach in which stopping rules are obtained based on the 'future' probability of an excessive toxicity rate; and a Bayesian adaptation modifying the proposed non-Bayesian approach, which can use the information obtained at interim analyses. Through an extensive Monte Carlo study, we show that the Bayesian approach often provides better control of the overall toxicity rate than the non-Bayesian approach. We also investigate adequate toxicity estimation after the studies. We demonstrate the applicability of our proposed methods in controlling the symptomatic intracranial hemorrhage rate for treating acute ischemic stroke patients.
The Size-Weight Illusion is not anti-Bayesian after all: a unifying Bayesian account.
Peters, Megan A K; Ma, Wei Ji; Shams, Ladan
2016-01-01
When we lift two differently-sized but equally-weighted objects, we expect the larger to be heavier, but the smaller feels heavier. However, traditional Bayesian approaches with "larger is heavier" priors predict the smaller object should feel lighter; this Size-Weight Illusion (SWI) has thus been labeled "anti-Bayesian" and has stymied psychologists for generations. We propose that previous Bayesian approaches neglect the brain's inference process about density. In our Bayesian model, objects' perceived heaviness relationship is based on both their size and inferred density relationship: observers evaluate competing, categorical hypotheses about objects' relative densities, the inference about which is then used to produce the final estimate of weight. The model can qualitatively and quantitatively reproduce the SWI and explain other researchers' findings, and also makes a novel prediction, which we confirmed. This same computational mechanism accounts for other multisensory phenomena and illusions; that the SWI follows the same process suggests that competitive-prior Bayesian inference can explain human perception across many domains.
Minnesota Department of Natural Resources — This theme shows the USFS national forest boundaries in the state. This data was acquired from the GIS coordinators at both the Chippewa National Forest and the...
U.S. Geological Survey, Department of the Interior — Source data for forest stand age were obtained from the USDA Forest Inventory and Analysis (FIA) DataMart and were projected for future scenarios based on selected...
Institute of Scientific and Technical Information of China (English)
张松懋
1994-01-01
The syntactic parsing algorithm of weak precedence forest grammar has been introduced and the correctness and unambiguity of this algorithm have been proved. An example is given to the syntactic parsing procedure of weak precedence forest grammar.
Bayesian Particle Tracking of Traffic Flows
2014-01-01
We develop a Bayesian particle filter for tracking traffic flows that is capable of capturing non-linearities and discontinuities present in flow dynamics. Our model includes a hidden state variable that captures sudden regime shifts between traffic free flow, breakdown and recovery. We develop an efficient particle learning algorithm for real time on-line inference of states and parameters. This requires a two step approach, first, resampling the current particles, with a mixture predictive ...
Bayesian belief networks in business continuity.
Phillipson, Frank; Matthijssen, Edwin; Attema, Thomas
2014-01-01
Business continuity professionals aim to mitigate the various challenges to the continuity of their company. The goal is a coherent system of measures that encompass detection, prevention and recovery. Choices made in one part of the system affect other parts as well as the continuity risks of the company. In complex organisations, however, these relations are far from obvious. This paper proposes the use of Bayesian belief networks to expose these relations, and presents a modelling framework for this approach.
Bayesian Spatial Modelling with R-INLA
Finn Lindgren; Håvard Rue
2015-01-01
The principles behind the interface to continuous domain spatial models in the R- INLA software package for R are described. The integrated nested Laplace approximation (INLA) approach proposed by Rue, Martino, and Chopin (2009) is a computationally effective alternative to MCMC for Bayesian inference. INLA is designed for latent Gaussian models, a very wide and flexible class of models ranging from (generalized) linear mixed to spatial and spatio-temporal models. Combined with the stochastic...
Bayesian Probabilities and the Histories Algebra
Marlow, Thomas
2006-01-01
We attempt a justification of a generalisation of the consistent histories programme using a notion of probability that is valid for all complete sets of history propositions. This consists of introducing Cox's axioms of probability theory and showing that our candidate notion of probability obeys them. We also give a generalisation of Bayes' theorem and comment upon how Bayesianism should be useful for the quantum gravity/cosmology programmes.
Bayesian Estimation and Inference Using Stochastic Electronics.
Thakur, Chetan Singh; Afshar, Saeed; Wang, Runchun M; Hamilton, Tara J; Tapson, Jonathan; van Schaik, André
2016-01-01
In this paper, we present the implementation of two types of Bayesian inference problems to demonstrate the potential of building probabilistic algorithms in hardware using single set of building blocks with the ability to perform these computations in real time. The first implementation, referred to as the BEAST (Bayesian Estimation and Stochastic Tracker), demonstrates a simple problem where an observer uses an underlying Hidden Markov Model (HMM) to track a target in one dimension. In this implementation, sensors make noisy observations of the target position at discrete time steps. The tracker learns the transition model for target movement, and the observation model for the noisy sensors, and uses these to estimate the target position by solving the Bayesian recursive equation online. We show the tracking performance of the system and demonstrate how it can learn the observation model, the transition model, and the external distractor (noise) probability interfering with the observations. In the second implementation, referred to as the Bayesian INference in DAG (BIND), we show how inference can be performed in a Directed Acyclic Graph (DAG) using stochastic circuits. We show how these building blocks can be easily implemented using simple digital logic gates. An advantage of the stochastic electronic implementation is that it is robust to certain types of noise, which may become an issue in integrated circuit (IC) technology with feature sizes in the order of tens of nanometers due to their low noise margin, the effect of high-energy cosmic rays and the low supply voltage. In our framework, the flipping of random individual bits would not affect the system performance because information is encoded in a bit stream.