Surprise! Bayesian Weighting for De-Biasing Thematic Maps.
Correll, Michael; Heer, Jeffrey
2017-01-01
Thematic maps are commonly used for visualizing the density of events in spatial data. However, these maps can mislead by giving visual prominence to known base rates (such as population densities) or to artifacts of sample size and normalization (such as outliers arising from smaller, and thus more variable, samples). In this work, we adapt Bayesian surprise to generate maps that counter these biases. Bayesian surprise, which has shown promise for modeling human visual attention, weights information with respect to how it updates beliefs over a space of models. We introduce Surprise Maps, a visualization technique that weights event data relative to a set of spatia-temporal models. Unexpected events (those that induce large changes in belief over the model space) are visualized more prominently than those that follow expected patterns. Using both synthetic and real-world datasets, we demonstrate how Surprise Maps overcome some limitations of traditional event maps.
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.
Little, Anthony C
2014-11-01
Facial attractiveness has important social consequences. Despite a widespread belief that beauty cannot be defined, in fact, there is considerable agreement across individuals and cultures on what is found attractive. By considering that attraction and mate choice are critical components of evolutionary selection, we can better understand the importance of beauty. There are many traits that are linked to facial attractiveness in humans and each may in some way impart benefits to individuals who act on their preferences. If a trait is reliably associated with some benefit to the perceiver, then we would expect individuals in a population to find that trait attractive. Such an approach has highlighted face traits such as age, health, symmetry, and averageness, which are proposed to be associated with benefits and so associated with facial attractiveness. This view may postulate that some traits will be universally attractive; however, this does not preclude variation. Indeed, it would be surprising if there existed a template of a perfect face that was not affected by experience, environment, context, or the specific needs of an individual. Research on facial attractiveness has documented how various face traits are associated with attractiveness and various factors that impact on an individual's judgments of facial attractiveness. Overall, facial attractiveness is complex, both in the number of traits that determine attraction and in the large number of factors that can alter attraction to particular faces. A fuller understanding of facial beauty will come with an understanding of how these various factors interact with each other. WIREs Cogn Sci 2014, 5:621-634. doi: 10.1002/wcs.1316 CONFLICT OF INTEREST: The author has declared no conflicts of interest for this article. For further resources related to this article, please visit the WIREs website.
Astronauts Cady Coleman and Paolo Nespoli perform the Pepper Oil Surprise experiment from Potlatch Elementary School in Potlatch, Idaho. This research investigates the interaction of liquid pepper/...
Barto, Andrew; Mirolli, Marco; Baldassarre, Gianluca
2013-01-01
Novelty and surprise play significant roles in animal behavior and in attempts to understand the neural mechanisms underlying it. They also play important roles in technology, where detecting observations that are novel or surprising is central to many applications, such as medical diagnosis, text processing, surveillance, and security. Theories of motivation, particularly of intrinsic motivation, place novelty and surprise among the primary factors that arouse interest, motivate exploratory or avoidance behavior, and drive learning. In many of these studies, novelty and surprise are not distinguished from one another: the words are used more-or-less interchangeably. However, while undeniably closely related, novelty and surprise are very different. The purpose of this article is first to highlight the differences between novelty and surprise and to discuss how they are related by presenting an extensive review of mathematical and computational proposals related to them, and then to explore the implications of this for understanding behavioral and neuroscience data. We argue that opportunities for improved understanding of behavior and its neural basis are likely being missed by failing to distinguish between novelty and surprise. PMID:24376428
2010-09-24
SEP 2010 2. REPORT TYPE 3. DATES COVERED 00-00-2010 to 00-00-2010 4. TITLE AND SUBTITLE More Supernova Surprises 5a. CONTRACT NUMBER 5b. GRANT...PERSPECTIVES More Supernova Surprises ASTRONOMY J. Martin Laming Spectroscopic observations of the supernova SN1987A are providing a new window into high...a core-collapse supernova ) have stretched and motivated research that has expanded our knowledge of astrophysics. The brightest such event in
Transformation and Strategic Surprise
2005-04-01
not the enemy. Only in the rarest of cases is a strategic or operational level surprise itself so damaging that the defender is rendered incapable of...aptly perhaps a way with war, which has deprived its warriors, and the country, of political rewards earned and deserved by their blood . Given that our
Overpeck, J.T.
1996-03-29
Over the last decade, paleoclimatic data from ice cores and sediments have shown that the climate system is capable of switching between significantly different modes, suggesting that climatic surprises may lie ahead. Most attention in the growing area of abrupt climatic change research continues to be focused on large changes observed during glacial periods. The weight of paleoclimatic evidence now suggests that conforting conclusions of benign warm climate variability may be incorrect. The article goes on to discuss the evidence for this. 17 refs.
Surprises in astrophysical gasdynamics.
Balbus, Steven A; Potter, William J
2016-06-01
Much of astrophysics consists of the study of ionized gas under the influence of gravitational and magnetic fields. Thus, it is not possible to understand the astrophysical universe without a detailed knowledge of the dynamics of magnetized fluids. Fluid dynamics is, however, a notoriously tricky subject, in which it is all too easy for one's a priori intuition to go astray. In this review, we seek to guide the reader through a series of illuminating yet deceptive problems, all with an enlightening twist. We cover a broad range of topics including the instabilities acting in accretion discs, the hydrodynamics governing the convective zone of the Sun, the magnetic shielding of a cooling galaxy cluster, and the behaviour of thermal instabilities and evaporating clouds. The aim of this review is to surprise and intrigue even veteran astrophysical theorists with an idiosyncratic choice of problems and counterintuitive results. At the same time, we endeavour to bring forth the fundamental ideas, to set out important assumptions, and to describe carefully whatever novel techniques may be appropriate to the problem at hand. By beginning at the beginning, and analysing a wide variety of astrophysical settings, we seek not only to make this review suitable for fluid dynamic veterans, but to engage novice recruits as well with what we hope will be an unusual and instructive introduction to the subject.
NASA Technical Reports Server (NTRS)
Lowman, Paul D., Jr.; Smith, David E. (Technical Monitor)
2001-01-01
This paper suggests that a new "Sputnik surprise" in the form of a joint Chinese-Russian lunar base program may emerge in this decade. The Moon as a whole has been shown to be territory of strategic value, with discovery of large amounts of hydrogen (probably water ice) at the lunar poles and helium 3 everywhere in the soil, in addition to the Moon's scientific value as an object of study and as a platform for astronomy. There is thus good reason for a return to the Moon, robotically or manned. Relations between China and Russia have thawed since the mid-1990s, and the two countries have a formal space cooperation pact. It is argued here that a manned lunar program would be feasible within 5 years, using modern technology and proven spacecraft and launch vehicles. The combination of Russian lunar hardware with Chinese space technology would permit the two countries together to take the lead in solar system exploration in the 21st century.
Surprises in astrophysical gasdynamics
NASA Astrophysics Data System (ADS)
Balbus, Steven A.; Potter, William J.
2016-06-01
Much of astrophysics consists of the study of ionized gas under the influence of gravitational and magnetic fields. Thus, it is not possible to understand the astrophysical universe without a detailed knowledge of the dynamics of magnetized fluids. Fluid dynamics is, however, a notoriously tricky subject, in which it is all too easy for one’s a priori intuition to go astray. In this review, we seek to guide the reader through a series of illuminating yet deceptive problems, all with an enlightening twist. We cover a broad range of topics including the instabilities acting in accretion discs, the hydrodynamics governing the convective zone of the Sun, the magnetic shielding of a cooling galaxy cluster, and the behaviour of thermal instabilities and evaporating clouds. The aim of this review is to surprise and intrigue even veteran astrophysical theorists with an idiosyncratic choice of problems and counterintuitive results. At the same time, we endeavour to bring forth the fundamental ideas, to set out important assumptions, and to describe carefully whatever novel techniques may be appropriate to the problem at hand. By beginning at the beginning, and analysing a wide variety of astrophysical settings, we seek not only to make this review suitable for fluid dynamic veterans, but to engage novice recruits as well with what we hope will be an unusual and instructive introduction to the subject.
Detecting communities using asymptotical surprise
NASA Astrophysics Data System (ADS)
Traag, V. A.; Aldecoa, R.; Delvenne, J.-C.
2015-08-01
Nodes in real-world networks are repeatedly observed to form dense clusters, often referred to as communities. Methods to detect these groups of nodes usually maximize an objective function, which implicitly contains the definition of a community. We here analyze a recently proposed measure called surprise, which assesses the quality of the partition of a network into communities. In its current form, the formulation of surprise is rather difficult to analyze. We here therefore develop an accurate asymptotic approximation. This allows for the development of an efficient algorithm for optimizing surprise. Incidentally, this leads to a straightforward extension of surprise to weighted graphs. Additionally, the approximation makes it possible to analyze surprise more closely and compare it to other methods, especially modularity. We show that surprise is (nearly) unaffected by the well-known resolution limit, a particular problem for modularity. However, surprise may tend to overestimate the number of communities, whereas they may be underestimated by modularity. In short, surprise works well in the limit of many small communities, whereas modularity works better in the limit of few large communities. In this sense, surprise is more discriminative than modularity and may find communities where modularity fails to discern any structure.
A Gentle Introduction to Bayesian Analysis: Applications to Developmental Research
ERIC Educational Resources Information Center
van de Schoot, Rens; Kaplan, David; Denissen, Jaap; Asendorpf, Jens B.; Neyer, Franz J.; van Aken, Marcel A. G.
2014-01-01
Bayesian statistical methods are becoming ever more popular in applied and fundamental research. In this study a gentle introduction to Bayesian analysis is provided. It is shown under what circumstances it is attractive to use Bayesian estimation, and how to interpret properly the results. First, the ingredients underlying Bayesian methods are…
Uncertainty and Surprise: An Introduction
NASA Astrophysics Data System (ADS)
McDaniel, Reuben R.; Driebe, Dean J.
Much of the traditional scientific and applied scientific work in the social and natural sciences has been built on the supposition that the unknowability of situations is the result of a lack of information. This has led to an emphasis on uncertainty reduction through ever-increasing information seeking and processing, including better measurement and observational instrumentation. Pending uncertainty reduction through better information, efforts are devoted to uncertainty management and hierarchies of controls. A central goal has been the avoidance of surprise.
[Bayesian statistic: an approach fitted to clinic].
Meyer, N; Vinzio, S; Goichot, B
2009-03-01
Bayesian statistic has known a growing success though quite limited. This is surprising since Bayes' theorem on which this paradigm relies is frequently used by the clinicians. There is a direct link between the routine diagnostic test and the Bayesian statistic. This link is the Bayes' theorem which allows one to compute positive and negative predictive values of a test. The principle of this theorem is extended to simple statistical situations as an introduction to Bayesian statistic. The conceptual simplicity of Bayesian statistic should make for a greater acceptance in the biomedical world.
ERIC Educational Resources Information Center
Kaplan, Jay
1979-01-01
The artcile answers some questions frequently asked by growing numbers of bird and animal feeders regarding what types of feeders and seed to use and what kinds of birds can be attracted to a given area. It discusses problems which can arise from this enjoyable year-round recreation. (SB)
NASA Astrophysics Data System (ADS)
Movassagh, Ramis
2016-02-01
We prove that the complex conjugate (c.c.) eigenvalues of a smoothly varying real matrix attract (Eq. 15). We offer a dynamical perspective on the motion and interaction of the eigenvalues in the complex plane, derive their governing equations and discuss applications. C.c. pairs closest to the real axis, or those that are ill-conditioned, attract most strongly and can collide to become exactly real. As an application we consider random perturbations of a fixed matrix M. If M is Normal, the total expected force on any eigenvalue is shown to be only the attraction of its c.c. (Eq. 24) and when M is circulant the strength of interaction can be related to the power spectrum of white noise. We extend this by calculating the expected force (Eq. 41) for real stochastic processes with zero-mean and independent intervals. To quantify the dominance of the c.c. attraction, we calculate the variance of other forces. We apply the results to the Hatano-Nelson model and provide other numerical illustrations. It is our hope that the simple dynamical perspective herein might help better understanding of the aggregation and low density of the eigenvalues of real random matrices on and near the real line respectively. In the appendix we provide a Matlab code for plotting the trajectories of the eigenvalues.
Porter, Michael E; Lorsch, Jay W; Nohria, Nitin
2004-10-01
As a newly minted CEO, you may think you finally have the power to set strategy, the authority to make things happen, and full access to the finer points of your business. But if you expect the job to be as simple as that, you're in for an awakening. Even though you bear full responsibility for your company's well-being, you are a few steps removed from many of the factors that drive results. You have more power than anybody else in the corporation, but you need to use it with extreme caution. In their workshops for new CEOs, held at Harvard Business School in Boston, the authors have discovered that nothing--not even running a large business within the company--fully prepares a person to be the chief executive. The seven most common surprises are: You can't run the company. Giving orders is very costly. It is hard to know what is really going on. You are always sending a message. You are not the boss. Pleasing shareholders is not the goal. You are still only human. These surprises carry some important and subtle lessons. First, you must learn to manage organizational context rather than focus on daily operations. Second, you must recognize that your position does not confer the right to lead, nor does it guarantee the loyalty of the organization. Finally, you must remember that you are subject to a host of limitations, even though others might treat you as omnipotent. How well and how quickly you understand, accept, and confront the seven surprises will have a lot to do with your success or failure as a CEO.
Bayesian clinical trials in action.
Lee, J Jack; Chu, Caleb T
2012-11-10
Although the frequentist paradigm has been the predominant approach to clinical trial design since the 1940s, it has several notable limitations. Advancements in computational algorithms and computer hardware have greatly enhanced the alternative Bayesian paradigm. Compared with its frequentist counterpart, the Bayesian framework has several unique advantages, and its incorporation into clinical trial design is occurring more frequently. Using an extensive literature review to assess how Bayesian methods are used in clinical trials, we find them most commonly used for dose finding, efficacy monitoring, toxicity monitoring, diagnosis/decision making, and studying pharmacokinetics/pharmacodynamics. The additional infrastructure required for implementing Bayesian methods in clinical trials may include specialized software programs to run the study design, simulation and analysis, and web-based applications, all of which are particularly useful for timely data entry and analysis. Trial success requires not only the development of proper tools but also timely and accurate execution of data entry, quality control, adaptive randomization, and Bayesian computation. The relative merit of the Bayesian and frequentist approaches continues to be the subject of debate in statistics. However, more evidence can be found showing the convergence of the two camps, at least at the practical level. Ultimately, better clinical trial methods lead to more efficient designs, lower sample sizes, more accurate conclusions, and better outcomes for patients enrolled in the trials. Bayesian methods offer attractive alternatives for better trials. More Bayesian trials should be designed and conducted to refine the approach and demonstrate their real benefit in action.
BMDS: A Collection of R Functions for Bayesian Multidimensional Scaling
ERIC Educational Resources Information Center
Okada, Kensuke; Shigemasu, Kazuo
2009-01-01
Bayesian multidimensional scaling (MDS) has attracted a great deal of attention because: (1) it provides a better fit than do classical MDS and ALSCAL; (2) it provides estimation errors of the distances; and (3) the Bayesian dimension selection criterion, MDSIC, provides a direct indication of optimal dimensionality. However, Bayesian MDS is not…
Bayesian Clinical Trials in Action
Lee, J. Jack; Chu, Caleb T.
2012-01-01
Although the frequentist paradigm has been the predominant approach to clinical trial design since the 1940s, it has several notable limitations. The alternative Bayesian paradigm has been greatly enhanced by advancements in computational algorithms and computer hardware. Compared to its frequentist counterpart, the Bayesian framework has several unique advantages, and its incorporation into clinical trial design is occurring more frequently. Using an extensive literature review to assess how Bayesian methods are used in clinical trials, we find them most commonly used for dose finding, efficacy monitoring, toxicity monitoring, diagnosis/decision making, and for studying pharmacokinetics/pharmacodynamics. The additional infrastructure required for implementing Bayesian methods in clinical trials may include specialized software programs to run the study design, simulation, and analysis, and Web-based applications, which are particularly useful for timely data entry and analysis. Trial success requires not only the development of proper tools but also timely and accurate execution of data entry, quality control, adaptive randomization, and Bayesian computation. The relative merit of the Bayesian and frequentist approaches continues to be the subject of debate in statistics. However, more evidence can be found showing the convergence of the two camps, at least at the practical level. Ultimately, better clinical trial methods lead to more efficient designs, lower sample sizes, more accurate conclusions, and better outcomes for patients enrolled in the trials. Bayesian methods offer attractive alternatives for better trials. More such trials should be designed and conducted to refine the approach and demonstrate its real benefit in action. PMID:22711340
NASA Technical Reports Server (NTRS)
2004-01-01
This image composite shows two of the Mars Exploration Rover Opportunity's magnets, the 'capture' magnet (upper portion of left panel) and the 'filter' magnet (lower portion of left panel). Scientists use these tools to study the origins of martian dust in the atmosphere. The left panel was taken by the rover's panoramic camera. The four panels to the right, taken by the microscopic imager, show close-up views of the two magnets. The bull's-eye appearance of the capture magnet is a result of alternating magnetic fields, which are used to increase overall magnetic force. The filter magnet lacks these alternating fields and consequently produces a weaker magnetic force. This weaker force selectively attracts only strong magnetic particles.
Scientists were surprised by the large dark particles on the magnets because airborne particles are smaller in size. They theorize that these spots might be aggregates of small particles that clump together in a magnetic field.
Some Surprising Introductory Physics Facts and Numbers
ERIC Educational Resources Information Center
Mallmann, A. James
2016-01-01
In the entertainment world, people usually like, and find memorable, novels, short stories, and movies with surprise endings. This suggests that classroom teachers might want to present to their students examples of surprising facts associated with principles of physics. Possible benefits of finding surprising facts about principles of physics are…
Young Galaxy's Magnetism Surprises Astronomers
NASA Astrophysics Data System (ADS)
2008-10-01
Astronomers have made the first direct measurement of the magnetic field in a young, distant galaxy, and the result is a big surprise. Looking at a faraway protogalaxy seen as it was 6.5 billion years ago, the scientists measured a magnetic field at least 10 times stronger than that of our own Milky Way. They had expected just the opposite. The GBT Robert C. Byrd Green Bank Telescope CREDIT: NRAO/AUI/NSF The scientists made the discovery using the National Science Foundation's ultra-sensitive Robert C. Byrd Green Bank Telescope (GBT) in West Virginia. "This new measurement indicates that magnetic fields may play a more important role in the formation and evolution of galaxies than we have realized," said Arthur Wolfe, of the University of California-San Diego (UCSD). At its great distance, the protogalaxy is seen as it was when the Universe was about half its current age. According to the leading theory, cosmic magnetic fields are generated by the dynamos of rotating galaxies -- a process that would produce stronger fields with the passage of time. In this scenario, the magnetic fields should be weaker in the earlier Universe, not stronger. The new, direct magnetic-field measurement comes on the heels of a July report by Swiss and American astronomers who made indirect measurements that also implied strong magnetic fields in the early Universe. "Our results present a challenge to the dynamo model, but they do not rule it out," Wolfe said. There are other possible explanations for the strong magnetic field seen in the one protogalaxy Wolfe's team studied. "We may be seeing the field close to the central region of a massive galaxy, and we know such fields are stronger toward the centers of nearby galaxies. Also, the field we see may have been amplified by a shock wave caused by the collision of two galaxies," he said. The protogalaxy studied with the GBT, called DLA-3C286, consists of gas with little or no star formation occurring in it. The astronomers suspect that
Evaluative Appraisals of Environmental Mystery and Surprise
ERIC Educational Resources Information Center
Nasar, Jack L.; Cubukcu, Ebru
2011-01-01
This study used a desktop virtual environment (VE) of 15 large-scale residential streets to test the effects of environmental mystery and surprise on response. In theory, mystery and surprise should increase interest and visual appeal. For each VE, participants walked through an approach street and turned right onto a post-turn street. We designed…
NASA Technical Reports Server (NTRS)
Denning, Peter J.
1989-01-01
In 1983 and 1984, the Infrared Astronomical Satellite (IRAS) detected 5,425 stellar objects and measured their infrared spectra. In 1987 a program called AUTOCLASS used Bayesian inference methods to discover the classes present in these data and determine the most probable class of each object, revealing unknown phenomena in astronomy. AUTOCLASS has rekindled the old debate on the suitability of Bayesian methods, which are computationally intensive, interpret probabilities as plausibility measures rather than frequencies, and appear to depend on a subjective assessment of the probability of a hypothesis before the data were collected. Modern statistical methods have, however, recently been shown to also depend on subjective elements. These debates bring into question the whole tradition of scientific objectivity and offer scientists a new way to take responsibility for their findings and conclusions.
Some Surprising Introductory Physics Facts and Numbers
NASA Astrophysics Data System (ADS)
Mallmann, A. James
2016-04-01
In the entertainment world, people usually like, and find memorable, novels, short stories, and movies with surprise endings. This suggests that classroom teachers might want to present to their students examples of surprising facts associated with principles of physics. Possible benefits of finding surprising facts about principles of physics are opportunities to expand beyond traditional presentations—and, in some cases, to achieve a deeper and broader understanding of those principles. I believe, moreover, that some of the facts presented here may inspire physics teachers to produce some challenge problems for students.
Surprise: a belief or an emotion?
Mellers, Barbara; Fincher, Katrina; Drummond, Caitlin; Bigony, Michelle
2013-01-01
Surprise is a fundamental link between cognition and emotion. It is shaped by cognitive assessments of likelihood, intuition, and superstition, and it in turn shapes hedonic experiences. We examine this connection between cognition and emotion and offer an explanation called decision affect theory. Our theory predicts the affective consequences of mistaken beliefs, such as overconfidence and hindsight. It provides insight about why the pleasure of a gain can loom larger than the pain of a comparable loss. Finally, it explains cross-cultural differences in emotional reactions to surprising events. By changing the nature of the unexpected (from chance to good luck), one can alter the emotional reaction to surprising events.
A toolkit for detecting technical surprise.
Trahan, Michael Wayne; Foehse, Mark C.
2010-10-01
The detection of a scientific or technological surprise within a secretive country or institute is very difficult. The ability to detect such surprises would allow analysts to identify the capabilities that could be a military or economic threat to national security. Sandia's current approach utilizing ThreatView has been successful in revealing potential technological surprises. However, as data sets become larger, it becomes critical to use algorithms as filters along with the visualization environments. Our two-year LDRD had two primary goals. First, we developed a tool, a Self-Organizing Map (SOM), to extend ThreatView and improve our understanding of the issues involved in working with textual data sets. Second, we developed a toolkit for detecting indicators of technical surprise in textual data sets. Our toolkit has been successfully used to perform technology assessments for the Science & Technology Intelligence (S&TI) program.
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 AG
2014-01-01
Bayesian statistical methods are becoming ever more popular in applied and fundamental research. In this study a gentle introduction to Bayesian analysis is provided. It is shown under what circumstances it is attractive to use Bayesian estimation, and how to interpret properly the results. First, the ingredients underlying Bayesian methods are introduced using a simplified example. Thereafter, the advantages and pitfalls of the specification of prior knowledge are discussed. To illustrate Bayesian methods explained in this study, in a second example a series of studies that examine the theoretical framework of dynamic interactionism are considered. In the Discussion the advantages and disadvantages of using Bayesian statistics are reviewed, and guidelines on how to report on Bayesian statistics are provided. PMID:24116396
Bayesian analysis of rare events
NASA Astrophysics Data System (ADS)
Straub, Daniel; Papaioannou, Iason; Betz, Wolfgang
2016-06-01
In many areas of engineering and science there is an interest in predicting the probability of rare events, in particular in applications related to safety and security. Increasingly, such predictions are made through computer models of physical systems in an uncertainty quantification framework. Additionally, with advances in IT, monitoring and sensor technology, an increasing amount of data on the performance of the systems is collected. This data can be used to reduce uncertainty, improve the probability estimates and consequently enhance the management of rare events and associated risks. Bayesian analysis is the ideal method to include the data into the probabilistic model. It ensures a consistent probabilistic treatment of uncertainty, which is central in the prediction of rare events, where extrapolation from the domain of observation is common. We present a framework for performing Bayesian updating of rare event probabilities, termed BUS. It is based on a reinterpretation of the classical rejection-sampling approach to Bayesian analysis, which enables the use of established methods for estimating probabilities of rare events. By drawing upon these methods, the framework makes use of their computational efficiency. These methods include the First-Order Reliability Method (FORM), tailored importance sampling (IS) methods and Subset Simulation (SuS). In this contribution, we briefly review these methods in the context of the BUS framework and investigate their applicability to Bayesian analysis of rare events in different settings. We find that, for some applications, FORM can be highly efficient and is surprisingly accurate, enabling Bayesian analysis of rare events with just a few model evaluations. In a general setting, BUS implemented through IS and SuS is more robust and flexible.
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 closely accords with the mechanisms of generalized Darwinian process proposed both by Dawkins, in terms of replicators and vehicles, and Campbell, in terms of inferential systems. Bayesian inference is an algorithm for the accumulation of evidence-based knowledge. This algorithm is now seen to operate over a wide range of evolutionary processes, including natural selection, the evolution of mental models and cultural evolutionary processes, notably including science itself. The variational principle of free energy minimization may thus serve as a unifying mathematical framework for universal Darwinism, the study of evolutionary processes operating throughout nature.
[Some recent surprises in global demography].
Poursin, J
1994-01-01
The author points out that, despite the fact that the inherent inertia in demographic phenomena should facilitate the preparation of accurate population projections, several recently identified trends have come as a surprise to many demographers. These trends include the recent Nigerian census indicating that the population is much smaller than had been estimated, increases in U.S. projections for the year 2050, and the Chinese paradox involving a rapid decline in fertility as the population continues to grow too fast. The implications of these surprises for future projections are assessed.
Some Surprising Errors in Numerical Differentiation
ERIC Educational Resources Information Center
Gordon, Sheldon P.
2012-01-01
Data analysis methods, both numerical and visual, are used to discover a variety of surprising patterns in the errors associated with successive approximations to the derivatives of sinusoidal and exponential functions based on the Newton difference-quotient. L'Hopital's rule and Taylor polynomial approximations are then used to explain why these…
Expect Surprises with 1-to-1 Laptops
ERIC Educational Resources Information Center
Tusch, Erich G.
2012-01-01
The prospect of radically changing teaching and learning by issuing a laptop computer to every student and teacher is an exciting one, but it carried big risks and would take time and thorough planning to execute well. But even thorough planning can't prevent the unanticipated. In this article, the author counts six major surprises during his time…
Surprising Connections between Partitions and Divisors
ERIC Educational Resources Information Center
Osler, Thomas J.; Hassen, Abdulkadir; Chandrupatla, Tirupathi R.
2007-01-01
The sum of the divisors of a positive integer is one of the most interesting concepts in multiplicative number theory, while the number of ways of expressing a number as a sum is a primary topic in additive number theory. In this article, we describe some of the surprising connections between and similarities of these two concepts.
Building classifiers using Bayesian networks
Friedman, N.; Goldszmidt, M.
1996-12-31
Recent work in supervised learning has shown that a surprisingly simple Bayesian classifier with strong assumptions of independence among features, called naive Bayes, is competitive with state of the art classifiers such as C4.5. This fact raises the question of whether a classifier with less restrictive assumptions can perform even better. In this paper we examine and evaluate approaches for inducing classifiers from data, based on recent results in the theory of learning Bayesian networks. Bayesian networks are factored representations of probability distributions that generalize the naive Bayes classifier and explicitly represent statements about independence. Among these approaches we single out a method we call Tree Augmented Naive Bayes (TAN), which outperforms naive Bayes, yet at the same time maintains the computational simplicity (no search involved) and robustness which are characteristic of naive Bayes. We experimentally tested these approaches using benchmark problems from the U. C. Irvine repository, and compared them against C4.5, naive Bayes, and wrapper-based feature selection methods.
NASA Astrophysics Data System (ADS)
Isakson, Steve Wesley
2001-12-01
Well-known principles of physics explain why resolution restrictions occur in images produced by optical diffraction-limited systems. The limitations involved are present in all diffraction-limited imaging systems, including acoustical and microwave. In most circumstances, however, prior knowledge about the object and the imaging system can lead to resolution improvements. In this dissertation I outline a method to incorporate prior information into the process of reconstructing images to superresolve the object beyond the above limitations. This dissertation research develops the details of this methodology. The approach can provide the most-probable global solution employing a finite number of steps in both far-field and near-field images. In addition, in order to overcome the effects of noise present in any imaging system, this technique provides a weighted image that quantifies the likelihood of various imaging solutions. By utilizing Bayesian probability, the procedure is capable of incorporating prior information about both the object and the noise to overcome the resolution limitation present in many imaging systems. Finally I will present an imaging system capable of detecting the evanescent waves missing from far-field systems, thus improving the resolution further.
Radar Design to Protect Against Surprise
Doerry, Armin W.
2015-02-01
Technological and doctrinal surprise is about rendering preparations for conflict as irrelevant or ineffective . For a sensor, this means essentially rendering the sensor as irrelevant or ineffective in its ability to help determine truth. Recovery from this sort of surprise is facilitated by flexibility in our own technology and doctrine. For a sensor, this mean s flexibility in its architecture, design, tactics, and the designing organizations ' processes. - 4 - Acknowledgements This report is the result of a n unfunded research and development activity . Sandia National Laboratories is a multi - program laboratory manage d and operated by Sandia Corporation, a wholly owned subsidiary of Lockheed Martin Corporation, for the U.S. Department of Energy's National Nuclear Security Administration under contract DE - AC04 - 94AL85000.
Mirativity as Surprise: Evidentiality, Information, and Deixis.
Peterson, Tyler
2016-12-01
The goal of this paper is to investigate the linguistic, psychological and cognitive properties of utterances that express the surprise of the speaker, with a focus on how grammatical evidentials are used for this purpose. This is often labeled in the linguistics literature as mirativity. While there has been a flurry of recent interest in mirativity, we still lack an understanding of how and why evidentials are used this way, and an explanation of this effect. In this paper I take steps to filling this gap by showing how the mirativity associated with grammatical evidentials is one of the many linguistic reflexes of the more general cognitive process of surprise. I approach this by analyzing mirativity, and the language of surprise more generally, in a schema-theoretic framework enriched with the notion of new environmental information. I elaborate on the field methodological issues involved with testing the mirative use of an evidential and why they are used this way by connecting mirative evidentials to the broader phenomenon of deixis.
Bayesian Confirmation and Interpretation.
ERIC Educational Resources Information Center
Ellett, Frederick S., Jr.
1984-01-01
The author briefly characterizes two ways to confirm the empirical part of educational theories: the hypothetico-deductive method and the Bayesian method. It is argued that the Bayesian approach can be justified. (JMK)
Previously seen and expected stimuli elicit surprise in the context of visual search.
Retell, James D; Becker, Stefanie I; Remington, Roger W
2016-04-01
In the context of visual search, surprise is the phenomenon by which a previously unseen and unexpected stimulus exogenously attracts spatial attention. Capture by such a stimulus occurs, by definition, independent of task goals and is thought to be dependent on the extent to which the stimulus deviates from expectations. However, the relative contributions of prior-exposure and explicit knowledge of an unexpected event to the surprise response have not yet been systematically investigated. Here observers searched for a specific color while ignoring irrelevant cues of different colors presented prior to the target display. After a brief familiarization period, we presented an irrelevant motion cue to elicit surprise. Across conditions we varied prior exposure to the motion stimulus - seen versus unseen - and top-down expectations of occurrence - expected versus unexpected - to assess the extent to which each of these factors contributes to surprise. We found no attenuation of the surprise response when observers were pre-exposed to the motion cue and or had explicit knowledge of its occurrence. Our results show that it is neither sufficient nor necessary that a stimulus be new and unannounced to elicit surprise and suggest that the expectations that determine the surprise response are highly context specific.
Pupil size tracks perceptual content and surprise.
Kloosterman, Niels A; Meindertsma, Thomas; van Loon, Anouk M; Lamme, Victor A F; Bonneh, Yoram S; Donner, Tobias H
2015-04-01
Changes in pupil size at constant light levels reflect the activity of neuromodulatory brainstem centers that control global brain state. These endogenously driven pupil dynamics can be synchronized with cognitive acts. For example, the pupil dilates during the spontaneous switches of perception of a constant sensory input in bistable perceptual illusions. It is unknown whether this pupil dilation only indicates the occurrence of perceptual switches, or also their content. Here, we measured pupil diameter in human subjects reporting the subjective disappearance and re-appearance of a physically constant visual target surrounded by a moving pattern ('motion-induced blindness' illusion). We show that the pupil dilates during the perceptual switches in the illusion and a stimulus-evoked 'replay' of that illusion. Critically, the switch-related pupil dilation encodes perceptual content, with larger amplitude for disappearance than re-appearance. This difference in pupil response amplitude enables prediction of the type of report (disappearance vs. re-appearance) on individual switches (receiver-operating characteristic: 61%). The amplitude difference is independent of the relative durations of target-visible and target-invisible intervals and subjects' overt behavioral report of the perceptual switches. Further, we show that pupil dilation during the replay also scales with the level of surprise about the timing of switches, but there is no evidence for an interaction between the effects of surprise and perceptual content on the pupil response. Taken together, our results suggest that pupil-linked brain systems track both the content of, and surprise about, perceptual events.
Surprises from an unusual CLC homolog.
Phillips, Sabrina; Brammer, Ashley E; Rodriguez, Luis; Lim, Hyun-Ho; Stary-Weinzinger, Anna; Matulef, Kimberly
2012-11-07
The chloride channel (CLC) family is distinctive in that some members are Cl(-) ion channels and others are Cl(-)/H(+) antiporters. The molecular mechanism that couples H(+) and Cl(-) transport in the antiporters remains unknown. Our characterization of a novel bacterial homolog from Citrobacter koseri, CLC-ck2, has yielded surprising discoveries about the requirements for both Cl(-) and H(+) transport in CLC proteins. First, even though CLC-ck2 lacks conserved amino acids near the Cl(-)-binding sites that are part of the CLC selectivity signature sequence, this protein catalyzes Cl(-) transport, albeit slowly. Ion selectivity in CLC-ck2 is similar to that in CLC-ec1, except that SO(4)(2-) strongly competes with Cl(-) uptake through CLC-ck2 but has no effect on CLC-ec1. Second, and even more surprisingly, CLC-ck2 is a Cl(-)/H(+) antiporter, even though it contains an isoleucine at the Glu(in) position that was previously thought to be a critical part of the H(+) pathway. CLC-ck2 is the first known antiporter that contains a nonpolar residue at this position. Introduction of a glutamate at the Glu(in) site in CLC-ck2 does not increase H(+) flux. Like other CLC antiporters, mutation of the external glutamate gate (Glu(ex)) in CLC-ck2 prevents H(+) flux. Hence, Glu(ex), but not Glu(in), is critical for H(+) permeation in CLC proteins.
ERIC Educational Resources Information Center
Burns, Joseph C.; Buzzelli, Cary
1992-01-01
Describes a unit on magnetism that utilizes hands-on activities in which students make hypotheses for discrepant behavior, discover whether a magnet attracts one object through another, measure the strength of magnets, explore levitating paper clips, and play a game dependent on magnetic attraction. (MDH)
American Cockroach Sex Attractant.
Jacobson, M; Beroza, M
1965-02-12
The structure (2,2-dimethyl-3-isopropylidenecyclopropyl propionate) previously assigned to the sex attractant of the American cockroach has now been shown by additional physical and chemical data and biological inactivity of the synthetic preparation to be incorrect. The structure of this attractant remains to be determined.
Intelligence and Physical Attractiveness
ERIC Educational Resources Information Center
Kanazawa, Satoshi
2011-01-01
This brief research note aims to estimate the magnitude of the association between general intelligence and physical attractiveness with large nationally representative samples from two nations. In the United Kingdom, attractive children are more intelligent by 12.4 IQ points (r=0.381), whereas in the United States, the correlation between…
Deciphering Network Community Structure by Surprise
Aldecoa, Rodrigo; Marín, Ignacio
2011-01-01
The analysis of complex networks permeates all sciences, from biology to sociology. A fundamental, unsolved problem is how to characterize the community structure of a network. Here, using both standard and novel benchmarks, we show that maximization of a simple global parameter, which we call Surprise (S), leads to a very efficient characterization of the community structure of complex synthetic networks. Particularly, S qualitatively outperforms the most commonly used criterion to define communities, Newman and Girvan's modularity (Q). Applying S maximization to real networks often provides natural, well-supported partitions, but also sometimes counterintuitive solutions that expose the limitations of our previous knowledge. These results indicate that it is possible to define an effective global criterion for community structure and open new routes for the understanding of complex networks. PMID:21909420
Surprises and mysteries in urban soils
NASA Astrophysics Data System (ADS)
Groffman, P. M.
2015-12-01
In the Baltimore Ecosystem Study, one of two urban long-term ecological research (LTER) projects funded by the U.S. National Science Foundation, we are using "the watershed approach" to integrate ecological, physical and social sciences. Urban and suburban watershed input/output budgets for nitrogen have shown surprisingly high retention which has led to detailed analysis of sources and sinks in soils these watersheds. Home lawns, thought to be major sources of reactive nitrogen in suburban watersheds, have more complex coupled carbon and nitrogen dynamics than previously thought, and are likely the site of much nitrogen retention. Riparian zones, thought to be an important sink for reactive nitrogen in many watersheds, have turned out be nitrogen sources in urban watersheds due to hydrologic changes that disconnect streams from their surrounding landscape. Urban effects on atmospheric carbon dioxide levels and nitrogen deposition have strong effects on soil nitrogen cycling processes and soil:atmosphere fluxes of nitrous oxide, carbon dioxide and methane. Efforts to manage urban soils and watersheds through geomorphic stream restoration, creation of stormwater management features and changes in lawn and forest management can have significant effects on watershed carbon and nitrogen dynamics. Urban soils present a basic and applied science frontier that challenges our understanding of biological, physical, chemical and social science processes. The watershed approach provides an effective platform for integrating these disciplines and for articulating critical questions that arise from surprising results. This approach can help us to meet the challenge of urban soils, which is critical to achieving sustainability goals in cities across the world.
Inter-DNA Attraction Mediated by Divalent Counterions
Qiu Xiangyun; Andresen, Kurt; Kwok, Lisa W.; Lamb, Jessica S.; Park, Hye Yoon; Pollack, Lois
2007-07-20
Can nonspecifically bound divalent counterions induce attraction between DNA strands? Here, we present experimental evidence demonstrating attraction between short DNA strands mediated by Mg{sup 2+} ions. Solution small angle x-ray scattering data collected as a function of DNA concentration enable model independent extraction of the second virial coefficient. As the [Mg{sup 2+}] increases, this coefficient turns from positive to negative reflecting the transition from repulsive to attractive inter-DNA interaction. This surprising observation is corroborated by independent light scattering experiments. The dependence of the observed attraction on experimental parameters including DNA length provides valuable clues to its origin.
The conceptualization model problem—surprise
NASA Astrophysics Data System (ADS)
Bredehoeft, John
2005-03-01
The foundation of model analysis is the conceptual model. Surprise is defined as new data that renders the prevailing conceptual model invalid; as defined here it represents a paradigm shift. Limited empirical data indicate that surprises occur in 20-30% of model analyses. These data suggest that groundwater analysts have difficulty selecting the appropriate conceptual model. There is no ready remedy to the conceptual model problem other than (1) to collect as much data as is feasible, using all applicable methods—a complementary data collection methodology can lead to new information that changes the prevailing conceptual model, and (2) for the analyst to remain open to the fact that the conceptual model can change dramatically as more information is collected. In the final analysis, the hydrogeologist makes a subjective decision on the appropriate conceptual model. The conceptualization problem does not render models unusable. The problem introduces an uncertainty that often is not widely recognized. Conceptual model uncertainty is exacerbated in making long-term predictions of system performance. C'est le modèle conceptuel qui se trouve à base d'une analyse sur un modèle. On considère comme une surprise lorsque le modèle est invalidé par des données nouvelles; dans les termes définis ici la surprise est équivalente à un change de paradigme. Des données empiriques limitées indiquent que les surprises apparaissent dans 20 à 30% des analyses effectuées sur les modèles. Ces données suggèrent que l'analyse des eaux souterraines présente des difficultés lorsqu'il s'agit de choisir le modèle conceptuel approprié. Il n'existe pas un autre remède au problème du modèle conceptuel que: (1) rassembler autant des données que possible en utilisant toutes les méthodes applicables—la méthode des données complémentaires peut conduire aux nouvelles informations qui vont changer le modèle conceptuel, et (2) l'analyste doit rester ouvert au fait
NASA Astrophysics Data System (ADS)
Hobson, Michael P.; Jaffe, Andrew H.; Liddle, Andrew R.; Mukherjee, Pia; Parkinson, David
2009-12-01
Preface; Part I. Methods: 1. Foundations and algorithms John Skilling; 2. Simple applications of Bayesian methods D. S. Sivia and Steve Rawlings; 3. Parameter estimation using Monte Carlo sampling Antony Lewis and Sarah Bridle; 4. Model selection and multi-model interference Andrew R. Liddle, Pia Mukherjee and David Parkinson; 5. Bayesian experimental design and model selection forecasting Roberto Trotta, Martin Kunz, Pia Mukherjee and David Parkinson; 6. Signal separation in cosmology M. P. Hobson, M. A. J. Ashdown and V. Stolyarov; Part II. Applications: 7. Bayesian source extraction M. P. Hobson, Graça Rocha and R. Savage; 8. Flux measurement Daniel Mortlock; 9. Gravitational wave astronomy Neil Cornish; 10. Bayesian analysis of cosmic microwave background data Andrew H. Jaffe; 11. Bayesian multilevel modelling of cosmological populations Thomas J. Loredo and Martin A. Hendry; 12. A Bayesian approach to galaxy evolution studies Stefano Andreon; 13. Photometric redshift estimation: methods and applications Ofer Lahav, Filipe B. Abdalla and Manda Banerji; Index.
NASA Astrophysics Data System (ADS)
Hobson, Michael P.; Jaffe, Andrew H.; Liddle, Andrew R.; Mukherjee, Pia; Parkinson, David
2014-02-01
Preface; Part I. Methods: 1. Foundations and algorithms John Skilling; 2. Simple applications of Bayesian methods D. S. Sivia and Steve Rawlings; 3. Parameter estimation using Monte Carlo sampling Antony Lewis and Sarah Bridle; 4. Model selection and multi-model interference Andrew R. Liddle, Pia Mukherjee and David Parkinson; 5. Bayesian experimental design and model selection forecasting Roberto Trotta, Martin Kunz, Pia Mukherjee and David Parkinson; 6. Signal separation in cosmology M. P. Hobson, M. A. J. Ashdown and V. Stolyarov; Part II. Applications: 7. Bayesian source extraction M. P. Hobson, Graça Rocha and R. Savage; 8. Flux measurement Daniel Mortlock; 9. Gravitational wave astronomy Neil Cornish; 10. Bayesian analysis of cosmic microwave background data Andrew H. Jaffe; 11. Bayesian multilevel modelling of cosmological populations Thomas J. Loredo and Martin A. Hendry; 12. A Bayesian approach to galaxy evolution studies Stefano Andreon; 13. Photometric redshift estimation: methods and applications Ofer Lahav, Filipe B. Abdalla and Manda Banerji; Index.
Attention Alters Perceived Attractiveness.
Störmer, Viola S; Alvarez, George A
2016-04-01
Can attention alter the impression of a face? Previous studies showed that attention modulates the appearance of lower-level visual features. For instance, attention can make a simple stimulus appear to have higher contrast than it actually does. We tested whether attention can also alter the perception of a higher-order property-namely, facial attractiveness. We asked participants to judge the relative attractiveness of two faces after summoning their attention to one of the faces using a briefly presented visual cue. Across trials, participants judged the attended face to be more attractive than the same face when it was unattended. This effect was not due to decision or response biases, but rather was due to changes in perceptual processing of the faces. These results show that attention alters perceived facial attractiveness, and broadly demonstrate that attention can influence higher-level perception and may affect people's initial impressions of one another.
Adolescent attraction to cults.
Hunter, E
1998-01-01
This article details the reasons behind adolescents' attraction to cults. It is recommended that parents, teachers, and counselors familiarize themselves with the warning signs. Suggestions are offered on how to make adolescents less vulnerable to cult overtures.
Astronauts Cady Coleman and Ron Garan perform the Attracting Water Drops experiment from Chabad Hebrew Academy in San Diego, Calif. This research determines if a free-floating water drop can be att...
ISS GN and C - First Year Surprises
NASA Technical Reports Server (NTRS)
Begley, Michael
2002-01-01
Assembly of the International Space Station (ISS) began in late 1998 with the joining of the first two US and Russ ian elements. For more than two years, the outpost was served by two Russian Guidance, Navigation, and Control (GN&C) systems. The station requires orbital translation and attitude control functions for its 100+ configurations, from the nascent two-module station to the half million kilogram completed station owned and operated by seventeen nations. With the launch of the US Laboratory module in February 2001, the integration of the US GN&C system with its Russian counterpart laid the foundation for such a robust system. In its first year of combined operation, the ISS GN&C system has performed admirably, even better than many expected, but there have been surprises. Loss of command capability, loss of communication between segments, a control system force-fight, and "non-propulsive vents" that weren't - such events have repeatedly underscored the importance of thorough program integration, testing, and operation, both across subsystem boundaries and across international borders.
Surprises from Saturn: Implications for Other Environments
NASA Astrophysics Data System (ADS)
Coates, A. J.
2014-05-01
The exploration of Saturn by Cassini has provided many surprises regarding: Saturn's rapidly rotating magnetosphere, interactions with its diverse moons, and interactions with the solar wind. Enceladus, orbiting at 4 Saturn radii (RS), was found to have plumes of water vapour and ice which are the dominant source for the inner magnetosphere. Charged water clusters, charged dust and photoelectrons provide key populations in the 'dusty plasma' observed. Direct pickup is seen near Enceladus and field-aligned currents create a spot in Saturn's aurora. At Titan, orbiting at 20 RS, unexpected heavy negative and positive ions are seen in the ionosphere, which provide the source for Titan's haze. Ionospheric plasma is seen in Titan's tail, enabling ion escape to be estimated at 7 tonnes per day. Saturn's ring ionosphere was seen early in the mission and a return will be made in 2017. In addition, highly accelerated electrons are seen at Saturn's high Mach number (MA˜100) quasi-parallel bow shock. Here we review some of these key new results, and discuss the implications for other solar system objects.
Mining for Surprise Events within Text Streams
Whitney, Paul D.; Engel, David W.; Cramer, Nicholas O.
2009-04-30
This paper summarizes algorithms and analysis methodology for mining the evolving content in text streams. Text streams include news, press releases from organizations, speeches, Internet blogs, etc. These data are a fundamental source for detecting and characterizing strategic intent of individuals and organizations as well as for detecting abrupt or surprising events within communities. Specifically, an analyst may need to know if and when the topic within a text stream changes. Much of the current text feature methodology is focused on understanding and analyzing a single static collection of text documents. Corresponding analytic activities include summarizing the contents of the collection, grouping the documents based on similarity of content, and calculating concise summaries of the resulting groups. The approach reported here focuses on taking advantage of the temporal characteristics in a text stream to identify relevant features (such as change in content), and also on the analysis and algorithmic methodology to communicate these characteristics to a user. We present a variety of algorithms for detecting essential features within a text stream. A critical finding is that the characteristics used to identify features in a text stream are uncorrelated with the characteristics used to identify features in a static document collection. Our approach for communicating the information back to the user is to identify feature (word/phrase) groups. These resulting algorithms form the basis of developing software tools for a user to analyze and understand the content of text streams. We present analysis using both news information and abstracts from technical articles, and show how these algorithms provide understanding of the contents of these text streams.
Surprise as an Interactional Achievement: Reaction Tokens in Conversation
ERIC Educational Resources Information Center
Wilkinson, Sue; Kitzinger, Celia
2006-01-01
The expression of surprise--at something unexpected--is a key form of emotional display. Focusing on displays of surprise performed by means of reaction tokens (akin to Goffman's "response cries"), such as "wow, gosh, oh my god, ooh!, phew," we use an ethnomethodological, conversation-analytic approach to analyze surprise in talk-in-interaction.…
ERIC Educational Resources Information Center
Yuan, Ying; MacKinnon, David P.
2009-01-01
In this article, we propose Bayesian analysis of mediation effects. Compared with conventional frequentist mediation analysis, the Bayesian approach has several advantages. First, it allows researchers to incorporate prior information into the mediation analysis, thus potentially improving the efficiency of estimates. Second, under the Bayesian…
NASA Astrophysics Data System (ADS)
von der Linden, Wolfgang; Dose, Volker; von Toussaint, Udo
2014-06-01
Preface; Part I. Introduction: 1. The meaning of probability; 2. Basic definitions; 3. Bayesian inference; 4. Combinatrics; 5. Random walks; 6. Limit theorems; 7. Continuous distributions; 8. The central limit theorem; 9. Poisson processes and waiting times; Part II. Assigning Probabilities: 10. Transformation invariance; 11. Maximum entropy; 12. Qualified maximum entropy; 13. Global smoothness; Part III. Parameter Estimation: 14. Bayesian parameter estimation; 15. Frequentist parameter estimation; 16. The Cramer-Rao inequality; Part IV. Testing Hypotheses: 17. The Bayesian way; 18. The frequentist way; 19. Sampling distributions; 20. Bayesian vs frequentist hypothesis tests; Part V. Real World Applications: 21. Regression; 22. Inconsistent data; 23. Unrecognized signal contributions; 24. Change point problems; 25. Function estimation; 26. Integral equations; 27. Model selection; 28. Bayesian experimental design; Part VI. Probabilistic Numerical Techniques: 29. Numerical integration; 30. Monte Carlo methods; 31. Nested sampling; Appendixes; References; Index.
A Shocking Surprise in Stephan's Quintet
NASA Technical Reports Server (NTRS)
2006-01-01
surprised not only by the turbulence of the gas, but by the incredible strength of the emission. The reason the molecular hydrogen emission is so powerful is not yet completely understood.
Stephan's Quintet is located 300 million light-years away in the Pegasus constellation.
This image is composed of three data sets: near-infrared light (blue) and visible light called H-alpha (green) from the Calar Alto Observatory in Spain, operated by the Max Planck Institute in Germany; and 8-micron infrared light (red) from Spitzer's infrared array camera.
NASA Astrophysics Data System (ADS)
Borg, Anne; Sui, Manling
2013-03-01
Large regional differences remain in the number of girls studying physics and the number of female physicists in academic positions. While many countries struggle with attracting female students to university studies in physics, climbing the academic ladder is the main challenge for these women. Furthermore, for many female physicists the working climate is not very supportive. The workshop Attracting Girls to Physics, organized as part of the 4th IUPAP International Conference on Women in Physics, South Africa 2011, addressed attitudes among education-seeking teenagers and approaches for attracting young girls to physics through successful recruitment plans, including highlighting the broad spectrum of career opportunities for those with physics qualifications. The current paper presents findings, examples of best practices, and recommendations resulting from this workshop.
NASA Astrophysics Data System (ADS)
Sandow, Barbara; Marks, Ann; Borg, Anne
2009-04-01
In most countries the number of girls studying physics, as well female physicists in academic positions, is still low. Active recruitment at all levels is essential to change this situation. In some countries a large proportion of students are female, but career progression is difficult. Highlighting the broad spectrum of career opportunities for those with physics qualifications is a major approach in attracting girls to physics. This paper presents findings, examples of best practices, and recommendations resulting from the workshop, Attracting Girls to Physics, organized as part of the Third IUPAP International Conference on Women in Physics, Seoul, 2008.
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.
Attracting Philosophy Students--1.
ERIC Educational Resources Information Center
Coole, Walter A., Ed.
This is the first in a series of occasional papers designed as a vehicle for the collection and dissemination of ideas for increasing philosophy course enrollments in two-year colleges. A project of the Subcommittee on Attracting Philosophy Students of the American Philosophical Association's Committee on Teaching Philosophy in Two-Year Colleges,…
ERIC Educational Resources Information Center
Leyden, Michael B.
1994-01-01
Discusses the properties of neodymium magnets and magnets in general and how magnets can be used to teach students important scientific principles, such as attraction, repulsion, and polarity; the role of magnetic forces in electronic communications and computers; the magnetic properties of the earth and compasses; and the relationship between…
Adolescent Attraction to Cults.
ERIC Educational Resources Information Center
Hunter, Eagan
1998-01-01
Details the reasons behind adolescents' attraction to cults. and distinguishes functions of cults and the term "cult." Identifies various cults, and describes the process of involvement. Notes that in the absence of authentic, stabilizing standards, some youth are especially vulnerable. Provides recommendations for adults working with…
Bayesian Correlation Analysis for Sequence Count Data
Lau, Nelson; Perkins, Theodore J.
2016-01-01
Evaluating the similarity of different measured variables is a fundamental task of statistics, and a key part of many bioinformatics algorithms. Here we propose a Bayesian scheme for estimating the correlation between different entities’ measurements based on high-throughput sequencing data. These entities could be different genes or miRNAs whose expression is measured by RNA-seq, different transcription factors or histone marks whose expression is measured by ChIP-seq, or even combinations of different types of entities. Our Bayesian formulation accounts for both measured signal levels and uncertainty in those levels, due to varying sequencing depth in different experiments and to varying absolute levels of individual entities, both of which affect the precision of the measurements. In comparison with a traditional Pearson correlation analysis, we show that our Bayesian correlation analysis retains high correlations when measurement confidence is high, but suppresses correlations when measurement confidence is low—especially for entities with low signal levels. In addition, we consider the influence of priors on the Bayesian correlation estimate. Perhaps surprisingly, we show that naive, uniform priors on entities’ signal levels can lead to highly biased correlation estimates, particularly when different experiments have widely varying sequencing depths. However, we propose two alternative priors that provably mitigate this problem. We also prove that, like traditional Pearson correlation, our Bayesian correlation calculation constitutes a kernel in the machine learning sense, and thus can be used as a similarity measure in any kernel-based machine learning algorithm. We demonstrate our approach on two RNA-seq datasets and one miRNA-seq dataset. PMID:27701449
Bayesian Correlation Analysis for Sequence Count Data.
Sánchez-Taltavull, Daniel; Ramachandran, Parameswaran; Lau, Nelson; Perkins, Theodore J
2016-01-01
Evaluating the similarity of different measured variables is a fundamental task of statistics, and a key part of many bioinformatics algorithms. Here we propose a Bayesian scheme for estimating the correlation between different entities' measurements based on high-throughput sequencing data. These entities could be different genes or miRNAs whose expression is measured by RNA-seq, different transcription factors or histone marks whose expression is measured by ChIP-seq, or even combinations of different types of entities. Our Bayesian formulation accounts for both measured signal levels and uncertainty in those levels, due to varying sequencing depth in different experiments and to varying absolute levels of individual entities, both of which affect the precision of the measurements. In comparison with a traditional Pearson correlation analysis, we show that our Bayesian correlation analysis retains high correlations when measurement confidence is high, but suppresses correlations when measurement confidence is low-especially for entities with low signal levels. In addition, we consider the influence of priors on the Bayesian correlation estimate. Perhaps surprisingly, we show that naive, uniform priors on entities' signal levels can lead to highly biased correlation estimates, particularly when different experiments have widely varying sequencing depths. However, we propose two alternative priors that provably mitigate this problem. We also prove that, like traditional Pearson correlation, our Bayesian correlation calculation constitutes a kernel in the machine learning sense, and thus can be used as a similarity measure in any kernel-based machine learning algorithm. We demonstrate our approach on two RNA-seq datasets and one miRNA-seq dataset.
Model Diagnostics for Bayesian Networks
ERIC Educational Resources Information Center
Sinharay, Sandip
2006-01-01
Bayesian networks are frequently used in educational assessments primarily for learning about students' knowledge and skills. There is a lack of works on assessing fit of Bayesian networks. This article employs the posterior predictive model checking method, a popular Bayesian model checking tool, to assess fit of simple Bayesian networks. A…
Oldest Known Objects May Be Surprisingly Immature
NASA Astrophysics Data System (ADS)
2008-04-01
Some of the oldest objects in the Universe may still have a long way to go, according to a new study using NASA’s Chandra X-ray Observatory. These new results indicate that globular clusters might be surprisingly less mature in their development than previously thought. Globular clusters, dense bunches of up to millions of stars found in all galaxies, are among the oldest known objects in the Universe, with most estimates of their ages ranging from 9 to 13 billions of years old. As such they contain some of the first stars to form in a galaxy and understanding their evolution is critical to understanding the evolution of galaxies. Animation The Evolution of a Globular Cluster "For many years, globular clusters have been used as wonderful natural laboratories to study the evolution and interaction of stars," said John Fregeau of Northwestern University, who conducted the study. "So, it’s exciting to discover something that may be new and fundamental about the way they evolve." Conventional wisdom is that globular clusters pass through three phases of evolution or development of their structure, corresponding to adolescence, middle age, and old age. These "ages" refer to the evolutionary state of the cluster, not the physical ages of the individual stars. People Who Read This Also Read... Milky Way's Super-efficient Particle Accelerators Caught in The Act Discovery of Most Recent Supernova in Our Galaxy Action Replay of Powerful Stellar Explosion Jet Power and Black Hole Assortment Revealed in New Chandra Image In the adolescent phase, the stars near the center of the cluster collapse inward. Middle age refers to a phase when the interactions of double stars near the center of the cluster prevents it from further collapse. Finally, old age describes when binaries in the center of the cluster are disrupted or ejected, and the center of the cluster collapses inwards. For years, it has been thought that most globular clusters are middle- aged with a few being toward
Dissociating Averageness and Attractiveness: Attractive Faces Are Not Always Average
ERIC Educational Resources Information Center
DeBruine, Lisa M.; Jones, Benedict C.; Unger, Layla; Little, Anthony C.; Feinberg, David R.
2007-01-01
Although the averageness hypothesis of facial attractiveness proposes that the attractiveness of faces is mostly a consequence of their averageness, 1 study has shown that caricaturing highly attractive faces makes them mathematically less average but more attractive. Here the authors systematically test the averageness hypothesis in 5 experiments…
Corrugator activity confirms immediate negative affect in surprise
Topolinski, Sascha; Strack, Fritz
2015-01-01
The emotion of surprise entails a complex of immediate responses, such as cognitive interruption, attention allocation to, and more systematic processing of the surprising stimulus. All these processes serve the ultimate function to increase processing depth and thus cognitively master the surprising stimulus. The present account introduces phasic negative affect as the underlying mechanism responsible for this switch in operating mode. Surprising stimuli are schema-discrepant and thus entail cognitive disfluency, which elicits immediate negative affect. This affect in turn works like a phasic cognitive tuning switching the current processing mode from more automatic and heuristic to more systematic and reflective processing. Directly testing the initial elicitation of negative affect by surprising events, the present experiment presented high and low surprising neutral trivia statements to N = 28 participants while assessing their spontaneous facial expressions via facial electromyography. High compared to low surprising trivia elicited higher corrugator activity, indicative of negative affect and mental effort, while leaving zygomaticus (positive affect) and frontalis (cultural surprise expression) activity unaffected. Future research shall investigate the mediating role of negative affect in eliciting surprise-related outcomes. PMID:25762956
The Orion Nebula: Still Full of Surprises
NASA Astrophysics Data System (ADS)
2011-01-01
shows the glowing hydrogen gas, were coloured red. Light in the yellow-green part of the spectrum is coloured green, blue light is coloured blue and light that passed through an ultraviolet filter has been coloured purple. The exposure times were about 52 minutes through each filter. This image was processed by ESO using the observational data found by Igor Chekalin (Russia) [1], who participated in ESO's Hidden Treasures 2010 astrophotography competition [2], organised by ESO in October-November 2010, for everyone who enjoys making beautiful images of the night sky using real astronomical data. Notes [1] Igor searched through ESO's archive and identified datasets that he used to compose his image of Messier 42, which was the seventh highest ranked entry in the competition, out of almost 100 entries. His original work can be seen here. Igor Chekalin was awarded the first prize of the competition for his composition of Messier 78, and he also submitted an image of NGC3169, NGC3166 and SN 2003cg, which was ranked second highest. [2] ESO's Hidden Treasures 2010 competition gave amateur astronomers the opportunity to search through ESO's vast archives of astronomical data, hoping to find a well-hidden gem that needed polishing by the entrants. Participants submitted nearly 100 entries and ten skilled people were awarded some extremely attractive prizes, including an all expenses paid trip for the overall winner to ESO's Very Large Telescope (VLT) on Cerro Paranal, in Chile, the world's most advanced optical telescope. The ten winners submitted a total of 20 images that were ranked as the highest entries in the competition out of the near 100 images. More information ESO, the European Southern Observatory, is the foremost intergovernmental astronomy organisation in Europe and the world's most productive astronomical observatory. It is supported by 15 countries: Austria, Belgium, Brazil, the Czech Republic, Denmark, France, Finland, Germany, Italy, the Netherlands, Portugal
Bayesian estimation of the shape skeleton.
Feldman, Jacob; Singh, Manish
2006-11-21
Skeletal representations of shape have attracted enormous interest ever since their introduction by Blum [Blum H (1973) J Theor Biol 38:205-287], because of their potential to provide a compact, but meaningful, shape representation, suitable for both neural modeling and computational applications. But effective computation of the shape skeleton remains a notorious unsolved problem; existing approaches are extremely sensitive to noise and give counterintuitive results with simple shapes. In conventional approaches, the skeleton is defined by a geometric construction and computed by a deterministic procedure. We introduce a Bayesian probabilistic approach, in which a shape is assumed to have "grown" from a skeleton by a stochastic generative process. Bayesian estimation is used to identify the skeleton most likely to have produced the shape, i.e., that best "explains" it, called the maximum a posteriori skeleton. Even with natural shapes with substantial contour noise, this approach provides a robust skeletal representation whose branches correspond to the natural parts of the shape.
NASA Astrophysics Data System (ADS)
Sanders, Duncan A.; Swift, Michael R.; Bowley, R. M.; King, P. J.
2004-11-01
We present event-driven simulation results for single and multiple intruders in a vertically vibrated granular bed. Under our vibratory conditions, the mean vertical position of a single intruder is governed primarily by a buoyancylike effect. Multiple intruders also exhibit buoyancy governed behavior; however, multiple neutrally buoyant intruders cluster spontaneously and undergo horizontal segregation. These effects can be understood by considering the dynamics of two neutrally buoyant intruders. We have measured an attractive force between such intruders which has a range of five intruder diameters, and we provide a mechanistic explanation for the origins of this force.
Biobutanol: an attractive biofuel.
Dürre, Peter
2007-12-01
Biofuels are an attractive means to prevent a further increase of carbon dioxide emissions. Currently, gasoline is blended with ethanol at various percentages. However, butanol has several advantages over ethanol, such as higher energy content, lower water absorption, better blending ability, and use in conventional combustion engines without modification. Like ethanol, it can be produced fermentatively or petrochemically. Current crude oil prices render the biotechnological process economic again. The best-studied bacterium to perform a butanol fermentation is Clostridium acetobutylicum. Its genome has been sequenced, and the regulation of solvent formation is under intensive investigation. This opens the possibility to engineer recombinant strains with superior biobutanol-producing ability.
Surprise in Schools: Martin Buber and Dialogic Schooling
ERIC Educational Resources Information Center
Stern, Julian
2013-01-01
The philosopher Martin Buber described the central role of surprise in education. Surprise is not an alternative to planning and order in schools, and it is not even an alternative to repetitive practice. It is, instead, that which must be allowed to occur in any dialogic encounter. Schooling that is creative and filled with hope will also be…
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.
NASA Astrophysics Data System (ADS)
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.
Bayesian least squares deconvolution
NASA Astrophysics Data System (ADS)
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.
BIE: Bayesian Inference Engine
NASA Astrophysics Data System (ADS)
Weinberg, Martin D.
2013-12-01
The Bayesian Inference Engine (BIE) is an object-oriented library of tools written in C++ designed explicitly to enable Bayesian update and model comparison for astronomical problems. To facilitate "what if" exploration, BIE provides a command line interface (written with Bison and Flex) to run input scripts. The output of the code is a simulation of the Bayesian posterior distribution from which summary statistics e.g. by taking moments, or determine confidence intervals and so forth, can be determined. All of these quantities are fundamentally integrals and the Markov Chain approach produces variates heta distributed according to P( heta|D) so moments are trivially obtained by summing of the ensemble of variates.
Defense Science Board Summer Study on Strategic Surprise
2015-07-01
DSB Summer Study Report on Strategic Surprise July 2015 This page intentionally blank REPORT OF THE DEFENSE SCIENCE BOARD... STUDY ON Strategic Surprise July 2015 Office of the Under Secretary of Defense for Acquisition, Technology, and Logistics Washington, D.C...official position of the Department of Defense (DoD). The Defense Science Board Study on Strategic Surprise completed its information-gathering in
Bayesian Exploratory Factor Analysis
Conti, Gabriella; Frühwirth-Schnatter, Sylvia; Heckman, James J.; Piatek, Rémi
2014-01-01
This paper develops and applies a Bayesian approach to Exploratory Factor Analysis that improves on ad hoc classical approaches. Our framework relies on dedicated factor models and simultaneously determines the number of factors, the allocation of each measurement to a unique factor, and the corresponding factor loadings. Classical identification criteria are applied and integrated into our Bayesian procedure to generate models that are stable and clearly interpretable. A Monte Carlo study confirms the validity of the approach. The method is used to produce interpretable low dimensional aggregates from a high dimensional set of psychological measurements. PMID:25431517
Perceived Attractiveness and Classroom Interactions
ERIC Educational Resources Information Center
Algozzine, Bob
1977-01-01
Adams and Cohen (1974) demonstrated that facial attractiveness was a salient factor in differential student-teacher interactions. This research investigates further the interaction between teachers and children perceived to be attractive or unattractive by those teachers. It was hypothesized that attractive children would exhibit more "positive,"…
'Surprise' Designer Drugs Detected in NYC Hair Samples
... 164500.html 'Surprise' Designer Drugs Detected in NYC Hair Samples Stimulant-taking party-goers don't always ... in 2015. For the new study, researchers collected hair samples from 80 young adults outside nightclubs and ...
Quantifying male attractiveness.
McNamara, John M; Houston, Alasdair I; Marques Dos Santos, Miguel; Kokko, Hanna; Brooks, Rob
2003-01-01
Genetic models of sexual selection are concerned with a dynamic process in which female preference and male trait values coevolve. We present a rigorous method for characterizing evolutionary endpoints of this process in phenotypic terms. In our phenotypic characterization the mate-choice strategy of female population members determines how attractive females should find each male, and a population is evolutionarily stable if population members are actually behaving in this way. This provides a justification of phenotypic explanations of sexual selection and the insights into sexual selection that they provide. Furthermore, the phenotypic approach also has enormous advantages over a genetic approach when computing evolutionarily stable mate-choice strategies, especially when strategies are allowed to be complex time-dependent preference rules. For simplicity and clarity our analysis deals with haploid mate-choice genetics and a male trait that is inherited phenotypically, for example by vertical cultural transmission. The method is, however, easily extendible to other cases. An example illustrates that the sexy son phenomenon can occur when there is phenotypic inheritance of the male trait. PMID:14561306
Roelofs, W L
1995-01-01
The chemical communication system used to attract mates involves not only the overt chemical signals but also indirectly a great deal of chemistry in the emitter and receiver. As an example, in emitting female moths, this includes enzymes (and cofactors, mRNA, genes) of the pheromone biosynthetic pathways, hormones (and genes) involved in controlling pheromone production, receptors and second messengers for the hormones, and host plant cues that control release of the hormone. In receiving male moths, this includes the chemistry of pheromone transportation in antennal olfactory hairs (binding proteins and sensillar esterases) and the chemistry of signal transduction, which includes specific dendritic pheromone receptors and a rapid inositol triphosphate second messenger signal. A fluctuating plume structure is an integral part of the signal since the antennal receptors need intermittent stimulation to sustain upwind flight. Input from the hundreds of thousands of sensory cells is processed and integrated with other modalities in the central nervous system, but many unknown factors modulate the information before it is fed to motor neurons for behavioral responses. An unknown brain control center for pheromone perception is discussed relative to data from behavioral-threshold studies showing modulation by biogenic amines, such as octopamine and serotonin, from genetic studies on pheromone discrimination, and from behavioral and electrophysiological studies with behavioral antagonists. Images Fig. 1 PMID:7816846
NASA Astrophysics Data System (ADS)
Hosny, Hala M.; Kahil, Heba M.
2005-10-01
From our national statistics, it is evident that in the population of physicists there are considerably fewer women than men. Our role is to attract girls to physics and thus decrease this gap. The institutional structure in Egypt provides an equal opportunity for girls to study sciences, including physics. It is reckoned that girls refrain from studying physics due to a group of social and economic factors. We will discuss teaching physics at schools and present some ideas to develop it. The media should play a role in placing female physicists in the spotlight. Unfortunately, careers that require intellectual skills are considered men's careers. This necessitates that society changes the way it sees women and trusts more in their skills and talents. We therefore call for the cooperation of governmental and nongovernmental bodies, together with universities and the production sectors involved. This will ultimately lead to enhancing the entrepreneurial projects related to physics and technology on the one hand, and will encourage girls to find challenging opportunities on the other.
A structured approach to Bayesian data fusion
NASA Astrophysics Data System (ADS)
Rubin, Y. N.; Chen, J.; Hubbard, S.; Kowalsky, M. B.; Woodbury, A.
2002-12-01
Stochastic formulations of the inverse problem proved to be a powerful tool for data fusion. Bayesian-based methods are particularly attractive due to their generality and structure. A Bayesian method requires defining a prior pdf for the model parameters and a likelihood function to relate between model parameters and observations. A systematic approach for defining these two functions is needed, which departs from the customary, almost-by-default choice of normal-based models. This talk gives an overview of recent trends in Bayesian model construction. The first part of the talk focuses on identifying a prior using the information-based approach of Woodbury and Ulrych, with an application to the Cape Cod large scale tracer transport field experiment. Here we show how the tracer data can augment direct measurements of the hydraulic conductivity. In the second part, we focus on the likelihood function, and present two different concepts. The first concept defines a non-stationary, multivariate normal likelihood function, and the second employs neural networks and identifies a non-normal likelihood function. Both concepts are employed to fuse geophysical data with conventional well logs.
The Bayesian Inventory Problem
1984-05-01
Bayesian Approach to Demand Estimation and Inventory Provisioning," Naval Research Logistics Quarterly. Vol 20, 1973, (p607-624). 4 DeGroot , Morris H...page is blank APPENDIX A SUFFICIENT STATISTICS A convenient reference for moat of this material is DeGroot (41. Su-pose that we are sampling from a
Spectral Bayesian Knowledge Tracing
ERIC Educational Resources Information Center
Falakmasir, Mohammad; Yudelson, Michael; Ritter, Steve; Koedinger, Ken
2015-01-01
Bayesian Knowledge Tracing (BKT) has been in wide use for modeling student skill acquisition in Intelligent Tutoring Systems (ITS). BKT tracks and updates student's latent mastery of a skill as a probability distribution of a binary variable. BKT does so by accounting for observed student successes in applying the skill correctly, where success is…
ERIC Educational Resources Information Center
Gustafson, S. C.; Costello, C. S.; Like, E. C.; Pierce, S. J.; Shenoy, K. N.
2009-01-01
Bayesian estimation of a threshold time (hereafter simply threshold) for the receipt of impulse signals is accomplished given the following: 1) data, consisting of the number of impulses received in a time interval from zero to one and the time of the largest time impulse; 2) a model, consisting of a uniform probability density of impulse time…
Herndon, N
1992-08-01
In 1989, Pro-Pater, a private, nonprofit family planning organization in Brazil, used attractive ads with the message Vasectomy, An Act of Love to promote vasectomy. The number of vasectomies performed/day at Pro-Pater clinics increased from 11 to 20 during the publicity campaign and fell after the ads stopped but continued at higher levels. Word of mouth communication among friends, neighbors, and relatives who had vasectomies maintained these high levels. This type of communication reduced the fear that often involves vasectomies because men hear from men they know and trust that vasectomies are harmless and do not deprive them of potency. In Sao Paulo, the percentage of men familiar with vasectomies and how they are performed increased after the campaign, but in Salvador, knowledge did not increase even though the number of vasectomies in Pro-Pater clinics increased. Organizations in Colombia and Guatemala have also been effective in educating men about vasectomies. These successes were especially relevant in Latin American where machismo has been an obstacle of family planning programs. The no-scalpel technique 1st introduced in China in 1974 reduces the fear of vasectomy and has fewer complications than the conventional technique. Further trained physicians can perform the no-scalpel technique in about 10 minutes compared with 15 minutes for the conventional technique. In 1987 during a 1-day festival in Thailand, physicians averaged 57 no-scalpel vasectomies/day compared with only 33 for conventional vasectomies. This technique has not spread to Guatemala, Brazil, Colombia, the US, and some countries in Asia and Africa. Extensive research does not indicate that vasectomy has an increased risk of testicular cancer, prostate cancer, and myocardial infarction. Physicians are working on ways to improve vasectomy.
Surprise maximization reveals the community structure of complex networks
Aldecoa, Rodrigo; Marín, Ignacio
2013-01-01
How to determine the community structure of complex networks is an open question. It is critical to establish the best strategies for community detection in networks of unknown structure. Here, using standard synthetic benchmarks, we show that none of the algorithms hitherto developed for community structure characterization perform optimally. Significantly, evaluating the results according to their modularity, the most popular measure of the quality of a partition, systematically provides mistaken solutions. However, a novel quality function, called Surprise, can be used to elucidate which is the optimal division into communities. Consequently, we show that the best strategy to find the community structure of all the networks examined involves choosing among the solutions provided by multiple algorithms the one with the highest Surprise value. We conclude that Surprise maximization precisely reveals the community structure of complex networks. PMID:23320141
Revisiting A Surprising Demonstration of Total Internal Reflection
NASA Astrophysics Data System (ADS)
Lee, Jiwon; Cha, Yu Wha; Jung, Yeon Su; Oh, Eun Ju; Moon, Ye Lin; Kim, Jung Bog
2016-10-01
Melton demonstrated a surprising disappearance using total internal reflection. When he put a Florence flask filled with marbles into a water tank and looked straight down from directly above the flask, he was only able to see marbles above a certain water level. When he added more water into the tank above the top line of the marbles, all of the marbles disappeared. He explained this phenomenon as due to a combination of both refraction and total internal reflection. Here, we wanted to develop this surprising idea to create more surprises. However, in our case, we only took the refraction effect from Melton's idea to demonstrate our magic. This idea is supported by various perspectives. For instance, Viss and Sikkema demonstrated the critical angle without using total internal reflection, and James showed the novel optical properties of a submerged light bulb.
Hierarchical Approximate Bayesian Computation
Turner, Brandon M.; Van Zandt, Trisha
2013-01-01
Approximate Bayesian computation (ABC) is a powerful technique for estimating the posterior distribution of a model’s parameters. It is especially important when the model to be fit has no explicit likelihood function, which happens for computational (or simulation-based) models such as those that are popular in cognitive neuroscience and other areas in psychology. However, ABC is usually applied only to models with few parameters. Extending ABC to hierarchical models has been difficult because high-dimensional hierarchical models add computational complexity that conventional ABC cannot accommodate. In this paper we summarize some current approaches for performing hierarchical ABC and introduce a new algorithm called Gibbs ABC. This new algorithm incorporates well-known Bayesian techniques to improve the accuracy and efficiency of the ABC approach for estimation of hierarchical models. We then use the Gibbs ABC algorithm to estimate the parameters of two models of signal detection, one with and one without a tractable likelihood function. PMID:24297436
Quantum Bayesian implementation
NASA Astrophysics Data System (ADS)
Wu, Haoyang
2013-02-01
Mechanism design is a reverse problem of game theory. Nash implementation and Bayesian implementation are two important parts of mechanism design theory. The former one corresponds to a setting with complete information, whereas the latter one corresponds to a setting with incomplete information. A recent work Wu (Int J Quantum Inf 9:615-623, 2011) shows that when an additional condition is satisfied, the traditional sufficient conditions for Nash implementation will fail in a quantum domain. Inspired by this work, in this paper we will propose that the traditional sufficient conditions for Bayesian implementation will also fail if agents use quantum strategies to send messages to the designer through channels (e.g., Internet, cable etc) and two additional conditions are satisfied.
Personality Mediators of Interpersonal Attraction.
ERIC Educational Resources Information Center
Johnson, Charles D.; And Others
The current study was an examination of the effect of personality variables on the relationship between attitude disagreement and attraction. Attraction was measured in a neutral situation, designed to maximize any existing affective predispositions toward attitude agreement-disagreements. Subjects were placed in an ambiguous face-to-face…
Physical Attractiveness and Counseling Skills.
ERIC Educational Resources Information Center
Vargas, Alice M.; Borkowski, John G.
1982-01-01
Searched for interaction between quality of counseling skills (presence or absence of empathy, genuineness, and positive regard) and physical attractiveness as determinants of counseling effectiveness. Attractiveness influenced perceived effectiveness of counselor's skill. Analyses of expectancy data revealed that only with good skills did…
AIM: Attracting Women into Sciences.
ERIC Educational Resources Information Center
Hartman, Icial S.
1995-01-01
Addresses how to attract more college women into the sciences. Attracting Women into Sciences (AIM) is a comprehensive approach that begins with advising, advertising, and ambiguity. The advising process includes dispelling stereotypes and reviewing the options open to a female basic science major. Interaction, involvement and instruction, finding…
Avoiding surprises when implementing a single quality system.
Donawa, Maria
2009-01-01
European medical device manufacturers are sometimes surprised to learn that operating ISO 13485 alone is not sufficient to meet United States (US) quality system requirements. This article discusses important considerations for meeting US and European requirements when operating under a single quality system.
Reconsiderations: Donald Murray and the Pedagogy of Surprise
ERIC Educational Resources Information Center
Ballenger, Bruce
2008-01-01
Toward the end of his life, Donald Murray felt that his approach to writing instruction was no longer appreciated by journals in his field. Nevertheless, his emphasis on encouraging students to surprise themselves through informal writing still has considerable value. (Contains 1 note.)
Surprising yields with no-till cropping systems
Technology Transfer Automated Retrieval System (TEKTRAN)
Producers using no-till systems have found that crop yields often exceed their expectation based on nutrient and water supply. For example, corn yields 7% higher in a no-till system in central South Dakota than in a tilled system in eastern South Dakota. This is surprising because rainfall is 5 in...
Surprising yields with no-till cropping systems
Technology Transfer Automated Retrieval System (TEKTRAN)
Producers using no-till practices have observed that crop yields can greatly exceed expectations based on nutrient and water supply. For example, Ralph Holzwarth, who farms near Gettysburg, SD, has averaged 150 bu/ac of corn on his farm for the past 6 years. We were surprised with this yield, as c...
Revisit: A Surprising Demonstration of Total Internal Reflection
ERIC Educational Resources Information Center
Lee, Jiwon; Cha, Yu Wha; Jung, Yeon Su; Oh, Eun Ju; Moon, Ye Lin; Kim, Jung Bog
2016-01-01
Melton demonstrated a surprising disappearance using total internal reflection. When he put a Florence flask filled with marbles into a water tank and looked straight down from directly above the flask, he was only able to see marbles above a certain water level. When he added more water into the tank above the top line of the marbles, all of the…
African perceptions of female attractiveness.
Coetzee, Vinet; Faerber, Stella J; Greeff, Jaco M; Lefevre, Carmen E; Re, Daniel E; Perrett, David I
2012-01-01
Little is known about mate choice preferences outside Western, educated, industrialised, rich and democratic societies, even though these Western populations may be particularly unrepresentative of human populations. To our knowledge, this is the first study to test which facial cues contribute to African perceptions of African female attractiveness and also the first study to test the combined role of facial adiposity, skin colour (lightness, yellowness and redness), skin homogeneity and youthfulness in the facial attractiveness preferences of any population. Results show that youthfulness, skin colour, skin homogeneity and facial adiposity significantly and independently predict attractiveness in female African faces. Younger, thinner women with a lighter, yellower skin colour and a more homogenous skin tone are considered more attractive. These findings provide a more global perspective on human mate choice and point to a universal role for these four facial cues in female facial attractiveness.
Using Bayesian analysis in repeated preclinical in vivo studies for a more effective use of animals.
Walley, Rosalind; Sherington, John; Rastrick, Joe; Detrait, Eric; Hanon, Etienne; Watt, Gillian
2016-05-01
Whilst innovative Bayesian approaches are increasingly used in clinical studies, in the preclinical area Bayesian methods appear to be rarely used in the reporting of pharmacology data. This is particularly surprising in the context of regularly repeated in vivo studies where there is a considerable amount of data from historical control groups, which has potential value. This paper describes our experience with introducing Bayesian analysis for such studies using a Bayesian meta-analytic predictive approach. This leads naturally either to an informative prior for a control group as part of a full Bayesian analysis of the next study or using a predictive distribution to replace a control group entirely. We use quality control charts to illustrate study-to-study variation to the scientists and describe informative priors in terms of their approximate effective numbers of animals. We describe two case studies of animal models: the lipopolysaccharide-induced cytokine release model used in inflammation and the novel object recognition model used to screen cognitive enhancers, both of which show the advantage of a Bayesian approach over the standard frequentist analysis. We conclude that using Bayesian methods in stable repeated in vivo studies can result in a more effective use of animals, either by reducing the total number of animals used or by increasing the precision of key treatment differences. This will lead to clearer results and supports the "3Rs initiative" to Refine, Reduce and Replace animals in research. Copyright © 2016 John Wiley & Sons, Ltd.
Bayesian Integrated Microbial Forensics
Jarman, Kristin H.; Kreuzer-Martin, Helen W.; Wunschel, David S.; Valentine, Nancy B.; Cliff, John B.; Petersen, Catherine E.; Colburn, Heather A.; Wahl, Karen L.
2008-06-01
In the aftermath of the 2001 anthrax letters, researchers have been exploring ways to predict the production environment of unknown source microorganisms. Different mass spectral techniques are being developed to characterize components of a microbe’s culture medium including water, carbon and nitrogen sources, metal ions added, and the presence of agar. Individually, each technique has the potential to identify one or two ingredients in a culture medium recipe. However, by integrating data from multiple mass spectral techniques, a more complete characterization is possible. We present a Bayesian statistical approach to integrated microbial forensics and illustrate its application on spores grown in different culture media.
Bayesian Approach for Inconsistent Information
Stein, M.; Beer, M.; Kreinovich, V.
2013-01-01
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. PMID:24089579
Searching Algorithm Using Bayesian Updates
ERIC Educational Resources Information Center
Caudle, Kyle
2010-01-01
In late October 1967, the USS Scorpion was lost at sea, somewhere between the Azores and Norfolk Virginia. Dr. Craven of the U.S. Navy's Special Projects Division is credited with using Bayesian Search Theory to locate the submarine. Bayesian Search Theory is a straightforward and interesting application of Bayes' theorem which involves searching…
Uncertainty and Surprise: Ideas from the Open Discussion
NASA Astrophysics Data System (ADS)
Jordan, Michelle E.
Approximately one hundred participants met for three days at a conference entitled "Uncertainty and Surprise: Questions on Working with the Unexpected and Unknowable." There were a diversity of conference participants ranging from researchers in the natural sciences and researchers in the social sciences (business professors, physicists, ethnographers, nursing school deans) to practitioners and executives in public policy and management (business owners, health care managers, high tech executives), all of whom had varying levels of experience and expertise in dealing with uncertainty and surprise. One group held the traditional, statistical view that uncertainty comes from variance and events that are described by usually unimodal probability law. A second group was comfortable on the one hand with phase diagrams and the phase transitions that come from systems with multi-modal distributions, and on the other hand, with deterministic chaos. A third group was comfortable with the emergent events from evolutionary processes that may not have any probability laws at all.
Positive affect, surprise, and fatigue are correlates of network flexibility.
Betzel, Richard F; Satterthwaite, Theodore D; Gold, Joshua I; Bassett, Danielle S
2017-03-31
Advances in neuroimaging have made it possible to reconstruct functional networks from the activity patterns of brain regions distributed across the cerebral cortex. Recent work has shown that flexible reconfiguration of human brain networks over short timescales supports cognitive flexibility and learning. However, modulating network flexibility to enhance learning requires an understanding of an as-yet unknown relationship between flexibility and brain state. Here, we investigate the relationship between network flexibility and affect, leveraging an unprecedented longitudinal data set. We demonstrate that indices associated with positive mood and surprise are both associated with network flexibility - positive mood portends a more flexible brain while increased levels of surprise portend a less flexible brain. In both cases, these relationships are driven predominantly by a subset of brain regions comprising the somatomotor system. Our results simultaneously suggest a network-level mechanism underlying learning deficits in mood disorders as well as a potential target - altering an individual's mood or task novelty - to improve learning.
Infants’ Looking to Surprising Events: When Eye-Tracking Reveals More than Looking Time
Yeung, H. Henny; Denison, Stephanie; Johnson, Scott P.
2016-01-01
Research on infants’ reasoning abilities often rely on looking times, which are longer to surprising and unexpected visual scenes compared to unsurprising and expected ones. Few researchers have examined more precise visual scanning patterns in these scenes, and so, here, we recorded 8- to 11-month-olds’ gaze with an eye tracker as we presented a sampling event whose outcome was either surprising, neutral, or unsurprising: A red (or yellow) ball was drawn from one of three visible containers populated 0%, 50%, or 100% with identically colored balls. When measuring looking time to the whole scene, infants were insensitive to the likelihood of the sampling event, replicating failures in similar paradigms. Nevertheless, a new analysis of visual scanning showed that infants did spend more time fixating specific areas-of-interest as a function of the event likelihood. The drawn ball and its associated container attracted more looking than the other containers in the 0% condition, but this pattern was weaker in the 50% condition, and even less strong in the 100% condition. Results suggest that measuring where infants look may be more sensitive than simply how much looking there is to the whole scene. The advantages of eye tracking measures over traditional looking measures are discussed. PMID:27926920
Infants' Looking to Surprising Events: When Eye-Tracking Reveals More than Looking Time.
Yeung, H Henny; Denison, Stephanie; Johnson, Scott P
2016-01-01
Research on infants' reasoning abilities often rely on looking times, which are longer to surprising and unexpected visual scenes compared to unsurprising and expected ones. Few researchers have examined more precise visual scanning patterns in these scenes, and so, here, we recorded 8- to 11-month-olds' gaze with an eye tracker as we presented a sampling event whose outcome was either surprising, neutral, or unsurprising: A red (or yellow) ball was drawn from one of three visible containers populated 0%, 50%, or 100% with identically colored balls. When measuring looking time to the whole scene, infants were insensitive to the likelihood of the sampling event, replicating failures in similar paradigms. Nevertheless, a new analysis of visual scanning showed that infants did spend more time fixating specific areas-of-interest as a function of the event likelihood. The drawn ball and its associated container attracted more looking than the other containers in the 0% condition, but this pattern was weaker in the 50% condition, and even less strong in the 100% condition. Results suggest that measuring where infants look may be more sensitive than simply how much looking there is to the whole scene. The advantages of eye tracking measures over traditional looking measures are discussed.
The June surprises: balls, strikes, and the fog of war.
Fried, Charles
2013-04-01
At first, few constitutional experts took seriously the argument that the Patient Protection and Affordable Care Act exceeded Congress's power under the commerce clause. The highly political opinions of two federal district judges - carefully chosen by challenging plaintiffs - of no particular distinction did not shake that confidence that the act was constitutional. This disdain for the challengers' arguments was only confirmed when the act was upheld by two highly respected conservative court of appeals judges in two separate circuits. But after the hostile, even mocking questioning of the government's advocate in the Supreme Court by the five Republican-appointed justices, the expectation was that the act would indeed be struck down on that ground. So it came as no surprise when the five opined the act did indeed exceed Congress's commerce clause power. But it came as a great surprise when Chief Justice John Roberts, joined by the four Democrat-appointed justices, ruled that the act could be sustained as an exercise of Congress's taxing power - a ground urged by the government almost as an afterthought. It was further surprising, even shocking, that Justices Antonin Scalia, Anthony Kennedy, Clarence Thomas, and Samuel Alito not only wrote a joint opinion on the commerce clause virtually identical to that of their chief, but that in writing it they did not refer to or even acknowledge his opinion. Finally surprising was the fact that Justices Ruth Bader Ginsburg and Stephen Breyer joined the chief in holding that aspects of the act's Medicaid expansion were unconstitutional. This essay ponders and tries to unravel some of these puzzles.
Predictable surprises: the disasters you should have seen coming.
Watkins, Michael D; Bazerman, Max H
2003-03-01
Think hard about the problems in your organization or about potential upheavals in the markets in which you operate. Could some of those problems--ones no one is attending to--turn into disasters? If you're like most executives, you'll sheepishly answer yes. As Harvard Business School professors Michael Watkins and Max Bazerman illustrate in this timely article, most of the "unexpected" events that buffet companies should have been anticipated--they're "predictable surprises." Such disasters take many forms, from financial scandals to disruptions in operations, from organizational upheavals to product failures. Some result in short-term losses or distractions, while others cause damage that takes years to repair. Some are truly catastrophic--the events of September 11, 2001, are a tragic example of a predictable surprise. The bad news is that all companies, including your own, are vulnerable to predictable surprises. The good news is that recent research helps explain why that's so and what companies can do to minimize their risk. The authors contend that organizations' inability to prepare for predictable surprises can be traced to three sets of vulnerabilities: psychological, organizational, and political. To address these vulnerabilities, the authors recommend the RPM approach. More than just the usual environmental scanning and contingency planning, RPM requires a chain of actions--recognizing, prioritizing, and mobilizing--that companies must meticulously adhere to. Failure to apply any one of these steps, the authors say, can leave an organization vulnerable. Given the extraordinarily high stakes involved, it should be every business leader's core responsibility to apply the RPM approach, the authors conclude.
False memory following rapidly presented lists: the element of surprise.
Whittlesea, Bruce W A; Masson, Michael E J; Hughes, Andrea D
2005-06-01
This article examines a false memory phenomenon, the Deese-Roediger-McDermott (DRM) effect, consisting of high false alarms for a prototype word (e.g., SLEEP) following a study list consisting of its associates (NIGHT, DREAM, etc.). This false recognition is thought to occur because prototypes, although not presented within a study list, are highly activated by their semantic association with words that are in the list. The authors present an alternative explanation of the effect, based on the discrepancy-attribution hypothesis. According to that account, false (and true) familiarity results when a comparison between expectations and outcomes within a processing episode causes surprise. Experiment 1 replicates the DRM effect. Experiment 2 shows that a similar effect can occur when participants are shown lists of unrelated words and are then surprised by a recognition target. Experiments 3 and 4 show that the DRM effect itself is abolished when participants are prevented from being surprised by prototypes presented as recognition targets. It is proposed that the DRM effect is best understood through the principles of construction, evaluation, and attribution.
Attraction between hydrated hydrophilic surfaces
NASA Astrophysics Data System (ADS)
Kanduč, Matej; Schneck, Emanuel; Netz, Roland R.
2014-08-01
According to common knowledge, hydrophilic surfaces repel via hydration forces while hydrophobic surfaces attract, but mounting experimental evidence suggests that also hydrophilic surfaces can attract. Using all-atom molecular dynamics simulations at prescribed water chemical potential we study the crossover from hydration repulsion to hydrophobic attraction for planar polar surfaces of varying stiffness and hydrogen-bonding capability. Rescaling the partial charges of the polar surface groups, we cover the complete spectrum from very hydrophobic surfaces (characterized by contact angles θ ≃ 135°) to hydrophilic surfaces exhibiting complete wetting (θ = 0°). Indeed, for a finite range θadh < θ < 90°, we find a regime where hydrophilic surfaces attract at sub-nanometer separation and stably adhere without intervening water. The adhesive contact angle θadh depends on surface type and lies in the range 65° < θadh < 80°, in good agreement with experiments. Analysis of the total number of hydrogen bonds (HBs) formed by water and surface groups rationalizes this crossover between hydration repulsion and hydrophilic attraction in terms of a subtle balance: Highly polar surfaces repel because of strongly bound hydration water, less polar hydrophilic surfaces attract because water-water HBs are preferred over surface-water HBs. Such solvent reorganization forces presumably underlie also other important phenomena, such as selective ion adsorption to interfaces as well as ion pair formation.
Adaptive Dynamic Bayesian Networks
Ng, B M
2007-10-26
A discrete-time Markov process can be compactly modeled as a dynamic Bayesian network (DBN)--a graphical model with nodes representing random variables and directed edges indicating causality between variables. Each node has a probability distribution, conditional on the variables represented by the parent nodes. A DBN's graphical structure encodes fixed conditional dependencies between variables. But in real-world systems, conditional dependencies between variables may be unknown a priori or may vary over time. Model errors can result if the DBN fails to capture all possible interactions between variables. Thus, we explore the representational framework of adaptive DBNs, whose structure and parameters can change from one time step to the next: a distribution's parameters and its set of conditional variables are dynamic. This work builds on recent work in nonparametric Bayesian modeling, such as hierarchical Dirichlet processes, infinite-state hidden Markov networks and structured priors for Bayes net learning. In this paper, we will explain the motivation for our interest in adaptive DBNs, show how popular nonparametric methods are combined to formulate the foundations for adaptive DBNs, and present preliminary results.
The Bayesian Covariance Lasso.
Khondker, Zakaria S; Zhu, Hongtu; Chu, Haitao; Lin, Weili; Ibrahim, Joseph G
2013-04-01
Estimation of sparse covariance matrices and their inverse subject to positive definiteness constraints has drawn a lot of attention in recent years. The abundance of high-dimensional data, where the sample size (n) is less than the dimension (d), requires shrinkage estimation methods since the maximum likelihood estimator is not positive definite in this case. Furthermore, when n is larger than d but not sufficiently larger, shrinkage estimation is more stable than maximum likelihood as it reduces the condition number of the precision matrix. Frequentist methods have utilized penalized likelihood methods, whereas Bayesian approaches rely on matrix decompositions or Wishart priors for shrinkage. In this paper we propose a new method, called the Bayesian Covariance Lasso (BCLASSO), for the shrinkage estimation of a precision (covariance) matrix. We consider a class of priors for the precision matrix that leads to the popular frequentist penalties as special cases, develop a Bayes estimator for the precision matrix, and propose an efficient sampling scheme that does not precalculate boundaries for positive definiteness. The proposed method is permutation invariant and performs shrinkage and estimation simultaneously for non-full rank data. Simulations show that the proposed BCLASSO performs similarly as frequentist methods for non-full rank data.
Khondker, Zakaria S; Zhu, Hongtu; Chu, Haitao; Lin, Weili; Ibrahim, Joseph G.
2012-01-01
Estimation of sparse covariance matrices and their inverse subject to positive definiteness constraints has drawn a lot of attention in recent years. The abundance of high-dimensional data, where the sample size (n) is less than the dimension (d), requires shrinkage estimation methods since the maximum likelihood estimator is not positive definite in this case. Furthermore, when n is larger than d but not sufficiently larger, shrinkage estimation is more stable than maximum likelihood as it reduces the condition number of the precision matrix. Frequentist methods have utilized penalized likelihood methods, whereas Bayesian approaches rely on matrix decompositions or Wishart priors for shrinkage. In this paper we propose a new method, called the Bayesian Covariance Lasso (BCLASSO), for the shrinkage estimation of a precision (covariance) matrix. We consider a class of priors for the precision matrix that leads to the popular frequentist penalties as special cases, develop a Bayes estimator for the precision matrix, and propose an efficient sampling scheme that does not precalculate boundaries for positive definiteness. The proposed method is permutation invariant and performs shrinkage and estimation simultaneously for non-full rank data. Simulations show that the proposed BCLASSO performs similarly as frequentist methods for non-full rank data. PMID:24551316
Bayesian Inference for Nonnegative Matrix Factorisation Models
Cemgil, Ali Taylan
2009-01-01
We describe nonnegative matrix factorisation (NMF) with a Kullback-Leibler (KL) error measure in a statistical framework, with a hierarchical generative model consisting of an observation and a prior component. Omitting the prior leads to the standard KL-NMF algorithms as special cases, where maximum likelihood parameter estimation is carried out via the Expectation-Maximisation (EM) algorithm. Starting from this view, we develop full Bayesian inference via variational Bayes or Monte Carlo. Our construction retains conjugacy and enables us to develop more powerful models while retaining attractive features of standard NMF such as monotonic convergence and easy implementation. We illustrate our approach on model order selection and image reconstruction. PMID:19536273
Heritability of Attractiveness to Mosquitoes
Fernández-Grandon, G. Mandela; Gezan, Salvador A.; Armour, John A. L.; Pickett, John A.; Logan, James G.
2015-01-01
Female mosquitoes display preferences for certain individuals over others, which is determined by differences in volatile chemicals produced by the human body and detected by mosquitoes. Body odour can be controlled genetically but the existence of a genetic basis for differential attraction to insects has never been formally demonstrated. This study investigated heritability of attractiveness to mosquitoes by evaluating the response of Aedes aegypti (=Stegomyia aegypti) mosquitoes to odours from the hands of identical and non-identical twins in a dual-choice assay. Volatiles from individuals in an identical twin pair showed a high correlation in attractiveness to mosquitoes, while non-identical twin pairs showed a significantly lower correlation. Overall, there was a strong narrow-sense heritability of 0.62 (SE 0.124) for relative attraction and 0.67 (0.354) for flight activity based on the average of ten measurements. The results demonstrate an underlying genetic component detectable by mosquitoes through olfaction. Understanding the genetic basis for attractiveness could create a more informed approach to repellent development. PMID:25901606
Bayesian supervised dimensionality reduction.
Gönen, Mehmet
2013-12-01
Dimensionality reduction is commonly used as a preprocessing step before training a supervised learner. However, coupled training of dimensionality reduction and supervised learning steps may improve the prediction performance. In this paper, we introduce a simple and novel Bayesian supervised dimensionality reduction method that combines linear dimensionality reduction and linear supervised learning in a principled way. We present both Gibbs sampling and variational approximation approaches to learn the proposed probabilistic model for multiclass classification. We also extend our formulation toward model selection using automatic relevance determination in order to find the intrinsic dimensionality. Classification experiments on three benchmark data sets show that the new model significantly outperforms seven baseline linear dimensionality reduction algorithms on very low dimensions in terms of generalization performance on test data. The proposed model also obtains the best results on an image recognition task in terms of classification and retrieval performances.
Bayesian Cherry Picking Revisited
NASA Astrophysics Data System (ADS)
Garrett, Anthony J. M.; Prozesky, Victor M.; Padayachee, J.
2004-04-01
Tins are marketed as containing nine cherries. To fill the tins, cherries are fed into a drum containing twelve holes through which air is sucked; either zero, one or two cherries stick in each hole. Dielectric measurements are then made on each hole. Three outcomes are distinguished: empty hole (which is reliable); one cherry (which indicates one cherry with high probability, or two cherries with a complementary low probability known from calibration); or an uncertain number (which also indicates one cherry or two, with known probabilities that are quite similar). A choice can be made from which holes simultaneously to discharge contents into the tin. The sum and product rules of probability are applied in a Bayesian manner to find the distribution for the number of cherries in the tin. Based on this distribution, ways are discussed to optimise the number to nine cherries.
Bayesian classification theory
NASA Technical Reports Server (NTRS)
Hanson, Robin; Stutz, John; Cheeseman, Peter
1991-01-01
The task of inferring a set of classes and class descriptions most likely to explain a given data set can be placed on a firm theoretical foundation using Bayesian statistics. Within this framework and using various mathematical and algorithmic approximations, the AutoClass system searches for the most probable classifications, automatically choosing the number of classes and complexity of class descriptions. A simpler version of AutoClass has been applied to many large real data sets, has discovered new independently-verified phenomena, and has been released as a robust software package. Recent extensions allow attributes to be selectively correlated within particular classes, and allow classes to inherit or share model parameters though a class hierarchy. We summarize the mathematical foundations of AutoClass.
Bayesian inference in geomagnetism
NASA Technical Reports Server (NTRS)
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.
Selenium in San Francisco Bay - 30 Years of Surprises
NASA Astrophysics Data System (ADS)
Cutter, G. A.
2015-12-01
The trace element selenium exists in multiple oxidation states (VI, IV, 0, -II) and chemical forms within an oxidation state, and this chemical speciation affects its bio-availability and geochemical cycling. The interactions between the physical circulation and riverine inputs, changing ecosystem components, and industrial inputs to the San Francisco Bay have had profound and surprising influences on the biogeochemical behavior of selenium in this estuary. In the mid-1980s dissolved selenium was relatively elevated and enriched in selenite (SeIV) in the mid-estuary, occurrences that were quantitatively linked to inputs from oil refinery effluents. Suspended particulate selenium concentrations were at a level considered problematic for filter feeding clams with high assimilation efficiencies. By 1999 oil refineries had implemented selenium removal processes that dramatically dropped the concentrations of total dissolved selenium and selenite by over 65% in the estuarine water column. Surprisingly, the concentrations of selenium in suspended particles did not drop as dramatically. We suspect that changes in the ecosystem, including the abundance of certain phytoplankton species and changes in benthic grazing affect the abundance of selenium in suspended particles. These and other changes within the San Francisco Bay system have been simulated in numerical models that reveal other surprising aspects of selenium cycling in this estuary. Data and models will be discussed in this presentation, and implications for other trace elements presented.
Aversion and attraction through olfaction
Li, Qian; Liberles, Stephen D.
2015-01-01
Sensory cues that predict reward or punishment are fundamental drivers of animal behavior. For example, attractive odors of palatable food or a potential mate predict reward while aversive odors of pathogen-laced food or a predator predict punishment. Aversive and attractive odors can be detected by intermingled sensory neurons that express highly related olfactory receptors and display similar central projections. These findings raise basic questions of how innate odor valence is extracted from olfactory circuits, how such circuits are developmentally endowed and modulated by state, and the relationship between innate and learned odor responses. Here, we review odors, receptors, and neural circuits associated with stimulus valence, discussing salient principles derived from studies on nematodes, insects, and vertebrates. Understanding the organization of neural circuitry that mediates odor aversion and attraction will provide key insights into how the brain functions. PMID:25649823
Surprises in operations on the inguinal area in young children.
MARKS, R M
1962-08-01
In surgical operations in the inguinal area in infants and children many unusual pathologic states were observed that were at first thought to be simple hernia. Among the conditions observed, in addition to complicated hernias and other anomalies of the processus vaginalis, were male pseudo-hermaphroditism, ectopic spleen, ectopic adrenal with neuroblastoma, diverticulum of the bladder, inguinal adenitis and suppurative iliac adenitis. In light of the sometimes surprising contents of the hernia sac, good exposure and careful identification of all anatomic structures is mandatory.
Defense Science Board (DSB) Summer Study Report on Strategic Surprise
2015-07-01
cyber; communications and positioning, navigation, and timing (PNT); counterintelligence; and logistics resilience . This report provides...Warfare • Cyber • Communications and Positioning, Navigation, and Timing (PNT) • Counterintelligence • Logistics Resilience To determine the... resilient logistics systems Strategies Some of the strategic surprises the study considered were an attack on the homeland using WMDs. Such an attack
Effective writing that attracts patients.
Baum, Neil
2015-01-01
Doctors today not only must communicate verbally, they must also realize that the written word is important to their ability to connect with the patients that they already have and also to attract new patients. Doctors will be expected to write blogs, to create content for their Web sites, to write articles for local publications, and even to learn to express themselves in 140 characters or less (i.e., Twitter). This article presents 10 rules for selecting the right words to enhance your communication with existing patients and potentially to attract new patients to your practice.
NASA Astrophysics Data System (ADS)
Rajabi, Mohammad Mahdi; Ataie-Ashtiani, Behzad
2016-05-01
Bayesian inference has traditionally been conceived as the proper framework for the formal incorporation of expert knowledge in parameter estimation of groundwater models. However, conventional Bayesian inference is incapable of taking into account the imprecision essentially embedded in expert provided information. In order to solve this problem, a number of extensions to conventional Bayesian inference have been introduced in recent years. One of these extensions is 'fuzzy Bayesian inference' which is the result of integrating fuzzy techniques into Bayesian statistics. Fuzzy Bayesian inference has a number of desirable features which makes it an attractive approach for incorporating expert knowledge in the parameter estimation process of groundwater models: (1) it is well adapted to the nature of expert provided information, (2) it allows to distinguishably model both uncertainty and imprecision, and (3) it presents a framework for fusing expert provided information regarding the various inputs of the Bayesian inference algorithm. However an important obstacle in employing fuzzy Bayesian inference in groundwater numerical modeling applications is the computational burden, as the required number of numerical model simulations often becomes extremely exhaustive and often computationally infeasible. In this paper, a novel approach of accelerating the fuzzy Bayesian inference algorithm is proposed which is based on using approximate posterior distributions derived from surrogate modeling, as a screening tool in the computations. The proposed approach is first applied to a synthetic test case of seawater intrusion (SWI) in a coastal aquifer. It is shown that for this synthetic test case, the proposed approach decreases the number of required numerical simulations by an order of magnitude. Then the proposed approach is applied to a real-world test case involving three-dimensional numerical modeling of SWI in Kish Island, located in the Persian Gulf. An expert
Estimations of expectedness and potential surprise in possibility theory
NASA Technical Reports Server (NTRS)
Prade, Henri; Yager, Ronald R.
1992-01-01
This note investigates how various ideas of 'expectedness' can be captured in the framework of possibility theory. Particularly, we are interested in trying to introduce estimates of the kind of lack of surprise expressed by people when saying 'I would not be surprised that...' before an event takes place, or by saying 'I knew it' after its realization. In possibility theory, a possibility distribution is supposed to model the relative levels of mutually exclusive alternatives in a set, or equivalently, the alternatives are assumed to be rank-ordered according to their level of possibility to take place. Four basic set-functions associated with a possibility distribution, including standard possibility and necessity measures, are discussed from the point of view of what they estimate when applied to potential events. Extensions of these estimates based on the notions of Q-projection or OWA operators are proposed when only significant parts of the possibility distribution are retained in the evaluation. The case of partially-known possibility distributions is also considered. Some potential applications are outlined.
10 years of surprises at Saturn: CAPS and INMS highlights
NASA Astrophysics Data System (ADS)
Coates, A. J.; Waite, J. H.
2014-04-01
The Cassini mission at Saturn has provided many surprises on Saturn's rapidly rotating magnetosphere and its interaction with the diverse moons, as well as its interaction with the solar wind. One of the early discoveries was the water-rich composition of the magnetosphere. Its structure and dynamics indicate remarkable injections, periodicities and interchange events. Enceladus, orbiting at 4 RS, was found to have plumes of water vapour and ice which are the dominant source for the inner magnetosphere. Charged water clusters, charged dust and photoelectrons provide key populations in the 'dusty plasma' seen here, as well as chemical complexity in the plume material. Direct pickup is seen near Enceladus and field aligned currents create a spot in Saturn's aurora. At Titan, orbiting at 20 RS, heavy negative and positive ions are seen in the ionosphere, as well as neutrals, all of which have surprising chemical complexity. These provide the source for Titan's haze. Ionospheric plasma is seen in Titan's tail, enabling ion escape to be estimated at 7 tonnes per day. Saturn's ring ionosphere was seen early in the mission, which was oxygen rich and produced photoelectrons; a return will be made in 2017. At Rhea, pickup positive and negative ions indicated weak atmospheres sustained by energetic particle impact, seen in the neutrals also. A weak atmosphere was also seen at Dione. The exosphere production process operates at Jupiter's moons also. Here we review some of the key new results, and discuss the implications for other solar system contexts.
Sparsity and the Bayesian perspective
NASA Astrophysics Data System (ADS)
Starck, J.-L.; Donoho, D. L.; Fadili, M. J.; Rassat, A.
2013-04-01
Sparsity has recently been introduced in cosmology for weak-lensing and cosmic microwave background (CMB) data analysis for different applications such as denoising, component separation, or inpainting (i.e., filling the missing data or the mask). Although it gives very nice numerical results, CMB sparse inpainting has been severely criticized by top researchers in cosmology using arguments derived from a Bayesian perspective. In an attempt to understand their point of view, we realize that interpreting a regularization penalty term as a prior in a Bayesian framework can lead to erroneous conclusions. This paper is by no means against the Bayesian approach, which has proven to be very useful for many applications, but warns against a Bayesian-only interpretation in data analysis, which can be misleading in some cases.
Attracting Birds to Your Backyard.
ERIC Educational Resources Information Center
Joyce, Brian
1994-01-01
Discusses methods for drawing birds to outdoor education areas, including the use of wild and native vegetation. Lists specific garden plants suitable for attracting birds in each season. Includes a guide to commercial bird seed and instructions for building homemade birdfeeders and nestboxes. (LZ)
Technology Transfer Automated Retrieval System (TEKTRAN)
Pear psylla, Cacopsylla pyricola (Förster) (Hemiptera: Psyllidae), a major economic pest of pears, have been shown to use a female-produced sex attractant pheromone. We compared the chemical profiles obtained from solvent extracts of diapausing and post-diapause winterform males and females, with g...
Deceptive copulation calls attract female visitors to peacock leks.
Dakin, Roslyn; Montgomerie, Robert
2014-04-01
Theory holds that dishonest signaling can be stable if it is rare. We report here that some peacocks perform specialized copulation calls (hoots) when females are not present and the peacocks are clearly not attempting to copulate. Because these solo hoots are almost always given out of view of females, they may be dishonest signals of male mating attempts. These dishonest calls are surprisingly common, making up about a third of all hoot calls in our study populations. Females are more likely to visit males after they give a solo hoot call, and we confirm using a playback experiment that females are attracted to the sound of the hoot. Our findings suggest that both sexes use the hoot call tactically: females to locate potential mates and males to attract female visitors. We suggest that the solo hoot may be a deceptive signal that is acquired and maintained through reward-based learning.
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.
Technology Transfer Automated Retrieval System (TEKTRAN)
The United States Department of Agriculture (USDA) has developed repellents and insecticides for the U.S. military since 1942. A small component of this research program has aimed at the discovery of attractants that can be used to produce potent lures for haematophagous arthropods, with a primary f...
29 years of surprises from hotspots: A personal perspective
NASA Astrophysics Data System (ADS)
Students Of Eao, .; Okal, E. A.
2003-12-01
I arrived at Caltech on 26 August 1974, to begin my graduate studies at the Seismo Lab, then under the Directorship of Don L. Anderson. These were the days, among other topics, of Don's famous multilingual footnote on the "definition..., antecedents..., supporters and detractors" of the concept of "plume" [GSA Bull., 86, p. 1593, 1975], and even though I was not to set foot on a hotspot island until my first trip to Tahiti in December 1977 (those stopovers at Keflavik on the 199-dollar Loftleidir runs did not really count), I quickly acquired a mild form of Don's contagious fascination for the activity and structure of hotspots. As a tribute to Don, I have chosen to recap here a few surprising results obtained, with the help of my students, past and present, over several decades of work on the seismological sources and structures in the neighborhood of hotspot islands.
Surprisingly Low Limits of Selection in Plant Domestication
Allaby, Robin G.; Kitchen, James L.; Fuller, Dorian Q.
2015-01-01
Current debate concerns the pace at which domesticated plants emerged from cultivated wild populations and how many genes were involved. Using an individual-based model, based on the assumptions of Haldane and Maynard Smith, respectively, we estimate that a surprisingly low number of 50–100 loci are the most that could be under selection in a cultivation regime at the selection strengths observed in the archaeological record. This finding is robust to attempts to rescue populations from extinction through selection from high standing genetic variation, gene flow, and the Maynard Smith-based model of threshold selection. Selective sweeps come at a cost, reducing the capacity of plants to adapt to new environments, which may contribute to the explanation of why selective sweeps have not been detected more frequently and why expansion of the agrarian package during the Neolithic was so frequently associated with collapse. PMID:27081302
Measured Zero Net Energy Performance: Results, Lessons, and Surprises
Brown, Carrie; LaRue, Anna; Pigman, Margaret; Roberts, Jon; Kaneda, David; Connelly, Dylan; Elliott, John; Pless, Shanti; Pande, Abhijeet; Dean, Edward; Anbarlilar, Can
2016-08-26
As more and more zero net energy (ZNE) buildings are built and monitored, we can learn from both careful case studies of individual projects as well as a broader perspective of trends over time. In a forum sponsored by Pacific Gas and Electric Company (PG&E), eight expert speakers discussed: results and lessons from monitoring occupied ZNE buildings; best practices for setting performance targets and getting actionable performance information, and; things that have surprised them about monitored ZNE buildings. This paper distills the content of the forum by laying out the most common hurdles that are encountered in setting up monitoring projects, frequent performance issues that the monitoring uncovers, and lessons learned that can be applied to future projects.
Bayesian Error Estimation Functionals
NASA Astrophysics Data System (ADS)
Jacobsen, Karsten W.
The challenge of approximating the exchange-correlation functional in Density Functional Theory (DFT) has led to the development of numerous different approximations of varying accuracy on different calculated properties. There is therefore a need for reliable estimation of prediction errors within the different approximation schemes to DFT. The Bayesian Error Estimation Functionals (BEEF) have been developed with this in mind. The functionals are constructed by fitting to experimental and high-quality computational databases for molecules and solids including chemisorption and van der Waals systems. This leads to reasonably accurate general-purpose functionals with particual focus on surface science. The fitting procedure involves considerations on how to combine different types of data, and applies Tikhonov regularization and bootstrap cross validation. The methodology has been applied to construct GGA and metaGGA functionals with and without inclusion of long-ranged van der Waals contributions. The error estimation is made possible by the generation of not only a single functional but through the construction of a probability distribution of functionals represented by a functional ensemble. The use of the functional ensemble is illustrated on compound heat of formation and by investigations of the reliability of calculated catalytic ammonia synthesis rates.
NASA Astrophysics Data System (ADS)
Sanders, D. A.; Swift, M. R.; Bowley, R. M.; King, P. J.
2006-02-01
Simulations of intruder particles in a vertically vibrated granular bed suggest that neutrally-buoyant intruders are attracted to one another (Phys. Rev. Lett., 93 (2004) 208002). The simulations, however, ignore important physical effects such as friction and convection which are known to influence intruder behaviour. Here, we present experimental evidence for this intruder-intruder interaction, obtained by monitoring the position of neutrally-buoyant metallic disks in a vibrated bed of glass spheres. An effective long-range attraction is shown to exist between a pair of intruders for a range of driving conditions. If further intruder particles are added, a tightly bound cluster of intruders can form. These results highlight the difficulty of retaining well-mixed granular beds under vertical vibration.
Facial attractiveness: evolutionary based research
Little, Anthony C.; Jones, Benedict C.; DeBruine, Lisa M.
2011-01-01
Face preferences affect a diverse range of critical social outcomes, from mate choices and decisions about platonic relationships to hiring decisions and decisions about social exchange. Firstly, we review the facial characteristics that influence attractiveness judgements of faces (e.g. symmetry, sexually dimorphic shape cues, averageness, skin colour/texture and cues to personality) and then review several important sources of individual differences in face preferences (e.g. hormone levels and fertility, own attractiveness and personality, visual experience, familiarity and imprinting, social learning). The research relating to these issues highlights flexible, sophisticated systems that support and promote adaptive responses to faces that appear to function to maximize the benefits of both our mate choices and more general decisions about other types of social partners. PMID:21536551
Can Pensions Help Attract Teachers?
ERIC Educational Resources Information Center
Kimball, Steven M.; Heneman, Herbert G.,III; Kellor, Eileen M.
2005-01-01
Every year there is a substantial flow of people into teaching roles as entrants or as movers from one school to another. Each such move involves attraction of the person to the job. Data for 1999-2000 reveal several important findings about teacher staffing. In 1999-2000, out of a teaching workforce of about 3.45 million, there were about 535,000…
Glantz, M.H.; Moore, C.M.; Streets, D.G.; Bhatti, N.; Rosa, C.H.; Stewart, T.R.
1998-01-01
This report examines the concept of climate surprise and its implications for environmental policymaking. Although most integrated assessment models of climate change deal with average values of change, it is usually the extreme events or surprises that cause the most damage to human health and property. Current models do not help the policymaker decide how to deal with climate surprises. This report examines the literature of surprise in many aspects of human society: psychology, military, health care, humor, agriculture, etc. It draws together various ways to consider the concept of surprise and examines different taxonomies of surprise that have been proposed. In many ways, surprise is revealed to be a subjective concept, triggered by such factors as prior experience, belief system, and level of education. How policymakers have reacted to specific instances of climate change or climate surprise in the past is considered, particularly with regard to the choices they made between proactive and reactive measures. Finally, the report discusses techniques used in the current generation of assessment models and makes suggestions as to how climate surprises might be included in future models. The report concludes that some kinds of surprises are simply unpredictable, but there are several types that could in some way be anticipated and assessed, and their negative effects forestalled.
Male facial anthropometry and attractiveness.
Soler, Caries; Kekäläinen, Jukka; Núñez, Manuel; Sancho, María; Núñez, Javier; Yaber, Iván; Gutiérrez, Ricardo
2012-01-01
The symmetry and masculinity of the face are often considered important elements of male facial attractiveness. However, facial preferences are rarely studied on natural faces. We studied the effect of these traits and facial metric parameters on facial attractiveness in Spanish and Colombian raters. In total, 13 metric and 11 asymmetry parameters from natural, unmanipulated frontal face photographs of 50 Spanish men were measured with the USIA semiautomatic anthropometric software. All raters (women and men) were asked to rank these images as potential long-term partners for females. In both sexes, facial attractiveness was negatively associated with facial masculinity, and preference was not associated with facial symmetry. In Spanish raters, both sexes preferred male traits that were larger in the right side of the face, which may reflect a human tendency to prefer a certain degree of facial asymmetry. We did not find such preference in Colombian raters, but they did show stronger preference for facial femininity than Spanish raters. Present results suggest that facial relative femininity, which is expected to signal, eg good parenting and cooperation skills, may be an important signal of mate quality when females seek long-term partners. Facial symmetry appears unimportant in such long-term mating preferences.
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.
Conformation-dependent DNA attraction
NASA Astrophysics Data System (ADS)
Li, Weifeng; Nordenskiöld, Lars; Zhou, Ruhong; Mu, Yuguang
2014-05-01
Understanding how DNA molecules interact with other biomolecules is related to how they utilize their functions and is therefore critical for understanding their structure-function relationships. For a long time, the existence of Z-form DNA (a left-handed double helical version of DNA, instead of the common right-handed B-form) has puzzled the scientists, and the definitive biological significance of Z-DNA has not yet been clarified. In this study, the effects of DNA conformation in DNA-DNA interactions are explored by molecular dynamics simulations. Using umbrella sampling, we find that for both B- and Z-form DNA, surrounding Mg2+ ions always exert themselves to screen the Coulomb repulsion between DNA phosphates, resulting in very weak attractive force. On the contrary, a tight and stable bound state is discovered for Z-DNA in the presence of Mg2+ or Na+, benefiting from their hydrophobic nature. Based on the contact surface and a dewetting process analysis, a two-stage binding process of Z-DNA is outlined: two Z-DNA first attract each other through charge screening and Mg2+ bridges to phosphate groups in the same way as that of B-DNA, after which hydrophobic contacts of the deoxyribose groups are formed via a dewetting effect, resulting in stable attraction between two Z-DNA molecules. The highlighted hydrophobic nature of Z-DNA interaction from the current study may help to understand the biological functions of Z-DNA in gene transcription.Understanding how DNA molecules interact with other biomolecules is related to how they utilize their functions and is therefore critical for understanding their structure-function relationships. For a long time, the existence of Z-form DNA (a left-handed double helical version of DNA, instead of the common right-handed B-form) has puzzled the scientists, and the definitive biological significance of Z-DNA has not yet been clarified. In this study, the effects of DNA conformation in DNA-DNA interactions are explored by
The surprising diversity of clostridial hydrogenases: a comparative genomic perspective.
Calusinska, Magdalena; Happe, Thomas; Joris, Bernard; Wilmotte, Annick
2010-06-01
Among the large variety of micro-organisms capable of fermentative hydrogen production, strict anaerobes such as members of the genus Clostridium are the most widely studied. They can produce hydrogen by a reversible reduction of protons accumulated during fermentation to dihydrogen, a reaction which is catalysed by hydrogenases. Sequenced genomes provide completely new insights into the diversity of clostridial hydrogenases. Building on previous reports, we found that [FeFe] hydrogenases are not a homogeneous group of enzymes, but exist in multiple forms with different modular structures and are especially abundant in members of the genus Clostridium. This unusual diversity seems to support the central role of hydrogenases in cell metabolism. In particular, the presence of multiple putative operons encoding multisubunit [FeFe] hydrogenases highlights the fact that hydrogen metabolism is very complex in this genus. In contrast with [FeFe] hydrogenases, their [NiFe] hydrogenase counterparts, widely represented in other bacteria and archaea, are found in only a few clostridial species. Surprisingly, a heteromultimeric Ech hydrogenase, known to be an energy-converting [NiFe] hydrogenase and previously described only in methanogenic archaea and some sulfur-reducing bacteria, was found to be encoded by the genomes of four cellulolytic strains: Clostridum cellulolyticum, Clostridum papyrosolvens, Clostridum thermocellum and Clostridum phytofermentans.
A Well-Known But Still Surprising Generator
NASA Astrophysics Data System (ADS)
Haugland, Ole Anton
2014-12-01
The bicycle generator is often mentioned as an example of a method to produce electric energy. It is cheap and easily accessible, so it is a natural example to use in teaching. There are different types, but I prefer the old side-wall dynamo. The most common explanation of its working principle seems to be something like the illustration in Fig. 1. The illustration is taken from a popular textbook in the Norwegian junior high school.1 Typically it is explained as a system of a moving magnet or coils that directly results in a varying magnetic field through the coils. According to Faraday's law a voltage is induced in the coils. Simple and easy! A few times I have had a chance to glimpse into a bicycle generator, and I was somewhat surprised to sense that the magnet rotated parallel to the turns of the coil. How could the flux through the coil change and induce a voltage when the magnet rotated parallel to the turns of the coil? When teaching electromagnetic induction I have showed the students a dismantled generator and asked them how this could work. They naturally found that this was more difficult to understand than the principle illustrated in Fig. 1. Other authors in this journal have discussed even more challenging questions concerning electric generators.2,3
Atom Surprise: Using Theatre in Primary Science Education
NASA Astrophysics Data System (ADS)
Peleg, Ran; Baram-Tsabari, Ayelet
2011-10-01
Early exposure to science may have a lifelong effect on children's attitudes towards science and their motivation to learn science in later life. Out-of-class environments can play a significant role in creating favourable attitudes, while contributing to conceptual learning. Educational science theatre is one form of an out-of-class environment, which has received little research attention. This study aims to describe affective and cognitive learning outcomes of watching such a play and to point to connections between theatrical elements and specific outcomes. "Atom Surprise" is a play portraying several concepts on the topic of matter. A mixed methods approach was adopted to investigate the knowledge and attitudes of children (grades 1-6) from two different school settings who watched the play. Data were gathered using questionnaires and in-depth interviews. Analysis suggested that in both schools children's knowledge on the topic of matter increased after the play with younger children gaining more conceptual knowledge than their older peers. In the public school girls showed greater gains in conceptual knowledge than boys. No significant changes in students' general attitudes towards science were found, however, students demonstrated positive changes towards science learning. Theatrical elements that seemed to be important in children's recollection of the play were the narrative, props and stage effects, and characters. In the children's memory, science was intertwined with the theatrical elements. Nonetheless, children could distinguish well between scientific facts and the fictive narrative.
Surprising connections: the diverse world of magnetic resonance
NASA Astrophysics Data System (ADS)
Callaghan, Paul
2004-10-01
When Rutherford discovered the atomic nucleus he could not possibly have imagined that it might be a window to understanding molecular biology, or how the brain works. And yet so it has come to pass. It is the through the magnetism of the nucleus that these insights, and so much more, are possible. The phenomenon of ``Nuclear Magnetic Resonance'' has proven an essential tool in physics, it has revolutionised chemistry and biochemistry, it has made astonishing contributions to medicine, and is now making an impact in geophysics, chemical engineering and food technology. It is even finding applications in new security technologies and in testing fundamental ideas concerning quantum computing. But the story of Magnetic Resonance is much more than the application of a well-established method to new areas of science. The technique itself continues to evolve. Magnetic Resonance has now garnered 6 Nobel prizes, two of them in the last two years. For a technique that has been around for nearly 60 years, it is really quite extraordinary that such accolades are still being given to new developments in the methodology. This talk will explain why the nuclear spin is so ubiquitous and interdisciplinary, and so rich in its fundamental physics. It will illustrate how unpredictable and surprising are the consequences of a major scientific discovery. For funding agencies determined to direct research activities towards predicted benefits, the conclusion drawn may provide a salutary lesson.
Surprisingly Rapid Orbital Evolution: A Compendium of Solar Type Binaries
NASA Astrophysics Data System (ADS)
Samec, Ronald George
2015-08-01
Solar type binaries are believed to be undergoing steady but slow angular momentum losses due to magnetic braking (Réville et al. 2015, Jiang et al. 2014) as stellar winds leave radially away on semi-rigid (out to the Alfvén radius) bipolar field lines: There is an outward radial flow of ions along the rotating magnetic fields. This is happening simultaneously as the gravitationally locked binary rotates about its center of mass. The stream of ions spiral outward resulting in a resistant torque, causing a decay in the orbital radius along with a period decrease due to Kepler’s laws. My past studies have included more than 25 binaries that appear to be undergoing magnetic braking. I have extended the number of systems to 75+ in this group by perusing the literature of modern precision synthetic light curve studies. Several interesting facts arise including their surprisingly rapid orbital evolution, much faster than would be suggested by the theory. Further results are presented in this study.
Tetrasomic Recombination Is Surprisingly Frequent in Allotetraploid Arachis
Leal-Bertioli, Soraya; Shirasawa, Kenta; Abernathy, Brian; Moretzsohn, Marcio; Chavarro, Carolina; Clevenger, Josh; Ozias-Akins, Peggy; Jackson, Scott; Bertioli, David
2015-01-01
Arachis hypogaea L. (cultivated peanut) is an allotetraploid (2n = 4x = 40) with an AABB genome type. Based on cytogenetic studies it has been assumed that peanut and wild-derived induced AABB allotetraploids have classic allotetraploid genetic behavior with diploid-like disomic recombination only between homologous chromosomes, at the exclusion of recombination between homeologous chromosomes. Using this assumption, numerous linkage map and quantitative trait loci studies have been carried out. Here, with a systematic analysis of genotyping and gene expression data, we show that this assumption is not entirely valid. In fact, autotetraploid-like tetrasomic recombination is surprisingly frequent in recombinant inbred lines generated from a cross of cultivated peanut and an induced allotetraploid derived from peanut’s most probable ancestral species. We suggest that a better, more predictive genetic model for peanut is that of a “segmental allotetraploid” with partly disomic, partly tetrasomic genetic behavior. This intermediate genetic behavior has probably had a previously overseen, but significant, impact on the genome and genetics of cultivated peanut. PMID:25701284
Bayesian computation via empirical likelihood
Mengersen, Kerrie L.; Pudlo, Pierre; Robert, Christian P.
2013-01-01
Approximate Bayesian computation has become an essential tool for the analysis of complex stochastic models when the likelihood function is numerically unavailable. However, the well-established statistical method of empirical likelihood provides another route to such settings that bypasses simulations from the model and the choices of the approximate Bayesian computation parameters (summary statistics, distance, tolerance), while being convergent in the number of observations. Furthermore, bypassing model simulations may lead to significant time savings in complex models, for instance those found in population genetics. The Bayesian computation with empirical likelihood algorithm we develop in this paper also provides an evaluation of its own performance through an associated effective sample size. The method is illustrated using several examples, including estimation of standard distributions, time series, and population genetics models. PMID:23297233
Bayesian anatomy of galaxy structure
NASA Astrophysics Data System (ADS)
Yoon, Ilsang
In this thesis I develop Bayesian approach to model galaxy surface brightness and apply it to a bulge-disc decomposition analysis of galaxies in near-infrared band, from Two Micron All Sky Survey (2MASS). The thesis has three main parts. First part is a technical development of Bayesian galaxy image decomposition package GALPHAT based on Markov chain Monte Carlo algorithm. I implement a fast and accurate galaxy model image generation algorithm to reduce computation time and make Bayesian approach feasible for real science analysis using large ensemble of galaxies. I perform a benchmark test of G ALPHAT and demonstrate significant improvement in parameter estimation with a correct statistical confidence. Second part is a performance test for full Bayesian application to galaxy bulge-disc decomposition analysis including not only the parameter estimation but also the model comparison to classify different galaxy population. The test demonstrates that GALPHAT has enough statistical power to make a reliable model inference using galaxy photometric survey data. Bayesian prior update is also tested for parameter estimation and Bayes factor model comparison and it shows that informative prior significantly improves the model inference in every aspects. Last part is a Bayesian bulge-disc decomposition analysis using 2MASS Ks-band selected samples. I characterise the luminosity distributions in spheroids, bulges and discs separately in the local Universe and study the galaxy morphology correlation, by full utilizing the ensemble parameter posterior of the entire galaxy samples. It shows that to avoid a biased inference, the parameter covariance and model degeneracy has to be carefully characterized by the full probability distribution.
Mcl-1-Bim complexes accommodate surprising point mutations via minor structural changes
Fire, Emiko; Gullá, Stefano V.; Grant, Robert A.; Keating, Amy E.
2010-06-25
Mcl-1 is an antiapoptotic Bcl-2-family protein that protects cells against death. Structures of Mcl-1, and of other anti-apoptotic Bcl-2 proteins, reveal a surface groove into which the {alpha}-helical BH3 regions of certain proapoptotic proteins can bind. Despite high overall structural conservation, differences in this groove afford binding specificity that is important for the mechanism of Bcl-2 family function. We report the crystal structure of human Mcl-1 bound to a BH3 peptide derived from human Bim and the structures for three complexes that accommodate large physicochemical changes at conserved Bim sites. The mutations had surprisingly modest effects on complex stability, and the structures show that Mcl-1 can undergo small changes to accommodate the mutant ligands. For example, a shift in a leucine side chain fills a hole left by an isoleucine-to-alanine mutation at the first hydrophobic buried position of Bim BH3. Larger changes are also observed, with shifting of helix {alpha}3 accommodating an isoleucine-to-tyrosine mutation at this same position. We surveyed the variation in available Mcl-1 and Bcl-x{sub L} structures and observed moderate flexibility that is likely critical for facilitating interactions of diverse BH3-only proteins with Mcl-1. With the antiapoptotic Bcl-2 family members attracting significant attention as therapeutic targets, these structures contribute to our growing understanding of how specificity is achieved and can help to guide the design of novel inhibitors that target Mcl-1.
Bayesian Statistics: A Place in Educational Research?
ERIC Educational Resources Information Center
Diamond, James
The use of Bayesian statistics as the basis of classical analysis of data is described. Bayesian analysis is a set of procedures for changing opinions about a given phenomenon based upon rational observation of a set of data. The Bayesian arrives at a set of prior beliefs regarding some states of nature; he observes data in a study and then…
Bayesian Model Averaging for Propensity Score Analysis
ERIC Educational Resources Information Center
Kaplan, David; Chen, Jianshen
2013-01-01
The purpose of this study is to explore Bayesian model averaging in the propensity score context. Previous research on Bayesian propensity score analysis does not take into account model uncertainty. In this regard, an internally consistent Bayesian framework for model building and estimation must also account for model uncertainty. The…
A Bayesian Nonparametric Approach to Test Equating
ERIC Educational Resources Information Center
Karabatsos, George; Walker, Stephen G.
2009-01-01
A Bayesian nonparametric model is introduced for score equating. It is applicable to all major equating designs, and has advantages over previous equating models. Unlike the previous models, the Bayesian model accounts for positive dependence between distributions of scores from two tests. The Bayesian model and the previous equating models are…
Dracunculiasis eradication--finishing the job before surprises arise.
Visser, Benjamin Jelle
2012-07-01
Dracunculiasis (Guinea worm disease) is a preventable waterborne parasitic disease that affects the poorest people living in remote rural areas in sub-Saharan African countries, who do not have access to safe drinking water. The Guinea Worm Eradication Program, a 25-year old campaign to rid the world of Guinea Worm disease has now reached its final stage accelerating to zero cases in all endemic countries. During the 19th and 20th centuries, dracunculiasis was common in much of Southern Asia and the African continent. The overall number of cases has been reduced tremendously by ≥99%, from the 3.32 million cases estimated to have occurred in 1986 in Africa to only 1,797 cases reported in 2010 reported in only five countries (Sudan, Mali, Ethiopia, Chad and Ghana) and Asia free of the disease. This achievement is unique in its kind--the only previously eradicated disease is smallpox, a viral infection for which vaccination was possible--and it has been achieved through primary community-based prevention and health education programs. Most efforts need to be taken in two countries, South Sudan (comprising 94% or 1,698 out of 1,797 of the cases reported world-wide in 2010) and Mali because of frequent movements of nomads in a vast area inside and outside Mali's borders. All factors favourable to dracunculiasis eradication are available including adequate financial resources, community and political support and high levels of advocacy. Thus there is no reason that this disabling parasitic disease cannot be eradicated soon before surprises arise such as new civil conflicts in currently endemic countries.
Increased or Reversed? The Effect of Surprise on Hindsight Bias Depends on the Hindsight Component
ERIC Educational Resources Information Center
Nestler, Steffen; Egloff, Boris
2009-01-01
Two diverging hypotheses concerning the influence of surprising events on hindsight effects have been proposed: Although some authors believe that surprising events lead to a reversal of hindsight bias, others have proposed that surprise increases hindsight bias. Drawing on the separate-components view of the hindsight bias (which argues that…
Cross, Nicole; Kiefner-Burmeister, Allison; Rossi, James; Borushok, Jessica; Hinman, Nova; Burmeister, Jacob; Carels, Robert A
2016-04-11
The current study examined the influence of facial attractiveness and weight status on personality trait attributions (e.g., honest, friendly) among more and less facially attractive as well as thin and overweight models. Participants viewed pictures of one of four types of models (overweight/less attractive, overweight/more attractive, thin/less attractive, thin/more attractive) and rated their attractiveness (facial, body, overall) and personality on 15 traits. Facial attractiveness and weight status additively impacted personality trait ratings. In mediation analyses, the facial attractiveness condition was no longer associated with personality traits after controlling for perceived facial attractiveness in 12 personality traits. Conversely, the thin and overweight condition was no longer associated with personality traits after controlling for perceived body attractiveness in only 2 personality traits. Post hoc moderation analysis indicated that weight status differently influenced the association between body attractiveness and personality trait attribution. Findings bear implications for attractiveness bias, weight bias, and discrimination research.
Fast Gibbs sampling for high-dimensional Bayesian inversion
NASA Astrophysics Data System (ADS)
Lucka, Felix
2016-11-01
Solving ill-posed inverse problems by Bayesian inference has recently attracted considerable attention. Compared to deterministic approaches, the probabilistic representation of the solution by the posterior distribution can be exploited to explore and quantify its uncertainties. In applications where the inverse solution is subject to further analysis procedures can be a significant advantage. Alongside theoretical progress, various new computational techniques allow us to sample very high dimensional posterior distributions: in (Lucka 2012 Inverse Problems 28 125012), and a Markov chain Monte Carlo posterior sampler was developed for linear inverse problems with {{\\ell }}1-type priors. In this article, we extend this single component (SC) Gibbs-type sampler to a wide range of priors used in Bayesian inversion, such as general {{\\ell }}pq priors with additional hard constraints. In addition, a fast computation of the conditional, SC densities in an explicit, parameterized form, a fast, robust and exact sampling from these one-dimensional densities is key to obtain an efficient algorithm. We demonstrate that a generalization of slice sampling can utilize their specific structure for this task and illustrate the performance of the resulting slice-within-Gibbs samplers by different computed examples. These new samplers allow us to perform sample-based Bayesian inference in high-dimensional scenarios with certain priors for the first time, including the inversion of computed tomography data with the popular isotropic total variation prior.
Molecular attraction of condensed bodies
NASA Astrophysics Data System (ADS)
Derjaguin, B. V.; Abrikosova, I. I.; Lifshitz, E. M.
2015-09-01
From the Editorial Board. As a contribution to commemorating the 100th anniversary of the birth of Evgenii Mikhailovich Lifshitz, it was found appropriate by the Editorial Board of Uspekhi Fizicheskikh Nauk (UFN) [Physics-Uspekhi] journal that the materials of the jubilee-associated Scientific Session of the Physical Sciences Division of the Russian Academy of Sciences published in this issue (pp. 877-905) be augmented by the review paper "Molecular attraction of condensed bodies" reproduced from a 1958 UFN issue. Included in this review, in addition to an account by Evgenii Mikhailovich Lifshitz of his theory of molecular attractive forces between condensed bodies (first published in Zhurnal Eksperimental'noi i Teoreticheskoi Fiziki (ZhETF) in 1955 and in its English translation Journal of Experimental and Theoretical Physics (JETP) in 1956), is a summary of a series of experimental studies beginning in 1949 by Irina Igorevna Abrikosova at the Institute of Physical Chemistry of the Academy of Sciences of the USSR in a laboratory led by Boris Vladimirovich Derjaguin (1902-1994), a Corresponding Member of the USSR Academy of Sciences. In 1958, however, UFN was not yet available in English translation, so the material of the review is insufficiently accessible to the present-day English-speaking reader. This is the reason why the UFN Editorial Board decided to contribute to celebrating the 100th anniversary of E M Lifshitz's birthday by reproducing on the journal's pages a 1958 review paper which contains both E M Lifshitz's theory itself and the experimental data that underpinned it (for an account of how Evgenii Mikhailovich Lifshitz was enlisted to explain the experimental results of I I Abrikosova and B V Derjaguin, see the letter to the editors N P Danilova on page 925 of this jubilee collection of publications).
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...
Word Learning as Bayesian Inference
ERIC Educational Resources Information Center
Xu, Fei; Tenenbaum, Joshua B.
2007-01-01
The authors present a Bayesian framework for understanding how adults and children learn the meanings of words. The theory explains how learners can generalize meaningfully from just one or a few positive examples of a novel word's referents, by making rational inductive inferences that integrate prior knowledge about plausible word meanings with…
Bayesian robust principal component analysis.
Ding, Xinghao; He, Lihan; Carin, Lawrence
2011-12-01
A hierarchical Bayesian model is considered for decomposing a matrix into low-rank and sparse components, assuming the observed matrix is a superposition of the two. The matrix is assumed noisy, with unknown and possibly non-stationary noise statistics. The Bayesian framework infers an approximate representation for the noise statistics while simultaneously inferring the low-rank and sparse-outlier contributions; the model is robust to a broad range of noise levels, without having to change model hyperparameter settings. In addition, the Bayesian framework allows exploitation of additional structure in the matrix. For example, in video applications each row (or column) corresponds to a video frame, and we introduce a Markov dependency between consecutive rows in the matrix (corresponding to consecutive frames in the video). The properties of this Markov process are also inferred based on the observed matrix, while simultaneously denoising and recovering the low-rank and sparse components. We compare the Bayesian model to a state-of-the-art optimization-based implementation of robust PCA; considering several examples, we demonstrate competitive performance of the proposed model.
Bayesian Alternation during Tactile Augmentation
Goeke, Caspar M.; Planera, Serena; Finger, Holger; König, Peter
2016-01-01
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 (WTA) 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
AO 0235+164 and Surrounding Field: Surprising HST Results
NASA Technical Reports Server (NTRS)
Burbidge, E. M.; Beaver, E. A.; Cohen, Ross D.; Junkkarinen, V. T.; Lyons, R. W.
1996-01-01
Results obtained with the Hubble Space Telescope on the highly variable radio, x-ray, and gamma-ray emitting QSO (or BL Lac object) AO 0235 + 164 are presented and analyzed. WFPC2 images were obtained in 1994 June, when AO 0235 + 164 was bright (m approx. 17), and the results are described in Sec. 3. After subtraction of the PSF of the QSO, hereafter called AO following the nomenclature of Yanny et al. (1989), the companion object named A, 2 sec south of AO, is discovered not to be an elliptical galaxy as hypothesized earlier, but to be an AGN object, with a central UV-bright point-source nucleus and faint surrounding nebulosity extending to AO. The second companion object 1.3 sec east of AO discovered by Yanny et al. (1989) and named object Al, appears more like a normal spiral galaxy. We have measured the positions, luminosities, and colors of some 30 faint objects in the field around AO 0235 + 16; most are extended and may be star-forming galaxies in a loose group or cluster. Our most surprising result of the HST observations comes from FOS spectra obtained in 1995 July, discussed in Sec. 4. Because of a positioning error of the telescope and AO's faintness at that time (m approx. 20), object A was observed instead of the intended target AO. Serendipitously, we discovered A to have broad deep BALQSO-type absorptions of C IV, Si IV, N V shortward of broad emissions. A is thus ejecting high velocity, highly ionized gas into the surrounding IGM. We discuss in Sec. 5 the relationship of the objects in the central 10 sec X 1O sec region around AO, where redshifts z(sub e) = 0.94, z(sub a) = 0.524, 0.851 in AO, (sub e) = 0.524 and Z(sub BAL)=0.511 in A, are found. We hypothesize that some of the 30 faint objects in the 77 sec. x 77 sec. field may be part of a large star-forming region at z approx. 0.5, as suggested for a few objects by Yanny et al. (1989). The proximity of two highly active extragalactic objects, AO 0235+164 and its AGN companion A, is remarkable and
Stars Form Surprisingly Close to Milky Way's Black Hole
NASA Astrophysics Data System (ADS)
2005-10-01
The supermassive black hole at the center of the Milky Way has surprisingly helped spawn a new generation of stars, according to observations from NASA's Chandra X-ray Observatory. This novel mode of star formation may solve several mysteries about the supermassive black holes that reside at the centers of nearly all galaxies. "Massive black holes are usually known for violence and destruction," said Sergei Nayakshin of the University of Leicester, United Kingdom, and coauthor of a paper on this research in an upcoming issue of the Monthly Notices of the Royal Astronomical Society. "So it's remarkable that this black hole helped create new stars, not just destroy them." Black holes have earned their fearsome reputation because any material -- including stars -- that falls within the so-called event horizon is never seen again. However, these new results indicate that the immense disks of gas known to orbit many black holes at a "safe" distance from the event horizon can help nurture the formation of new stars. Animation of Stars Forming Around Black Hole Animation of Stars Forming Around Black Hole This conclusion came from new clues that could only be revealed in X-rays. Until the latest Chandra results, astronomers have disagreed about the origin of a mysterious group of massive stars discovered by infrared astronomers to be orbiting less than a light year from the Milky Way's central black hole, a.k.a. Sagittarius A*, or Sgr A*. At such close distances to Sgr A*, the standard model for star formation predicts that gas clouds from which stars form should have been ripped apart by tidal forces from the black hole. Two models to explain this puzzle have been proposed. In the disk model, the gravity of a dense disk of gas around Sgr A* offsets the tidal forces and allows stars to form; in the migration model, the stars formed in a star cluster far away from the black hole and migrated in to form the ring of massive stars. The migration scenario predicts about a
van Osch, Yvette; Blanken, Irene; Meijs, Maartje H J; van Wolferen, Job
2015-04-01
We tested whether the perceived physical attractiveness of a group is greater than the average attractiveness of its members. In nine studies, we find evidence for the so-called group attractiveness effect (GA-effect), using female, male, and mixed-gender groups, indicating that group impressions of physical attractiveness are more positive than the average ratings of the group members. A meta-analysis on 33 comparisons reveals that the effect is medium to large (Cohen's d = 0.60) and moderated by group size. We explored two explanations for the GA-effect: (a) selective attention to attractive group members, and (b) the Gestalt principle of similarity. The results of our studies are in favor of the selective attention account: People selectively attend to the most attractive members of a group and their attractiveness has a greater influence on the evaluation of the group.
Bayesian inferences about the self (and others): A review
Moutoussis, Michael; Fearon, Pasco; El-Deredy, Wael; Dolan, Raymond J.; Friston, Karl J.
2014-01-01
Viewing the brain as an organ of approximate Bayesian inference can help us understand how it represents the self. We suggest that inferred representations of the self have a normative function: to predict and optimise the likely outcomes of social interactions. Technically, we cast this predict-and-optimise as maximising the chance of favourable outcomes through active inference. Here the utility of outcomes can be conceptualised as prior beliefs about final states. Actions based on interpersonal representations can therefore be understood as minimising surprise – under the prior belief that one will end up in states with high utility. Interpersonal representations thus serve to render interactions more predictable, while the affective valence of interpersonal inference renders self-perception evaluative. Distortions of self-representation contribute to major psychiatric disorders such as depression, personality disorder and paranoia. The approach we review may therefore operationalise the study of interpersonal representations in pathological states. PMID:24583455
Are seismic hazard assessment errors and earthquake surprises unavoidable?
NASA Astrophysics Data System (ADS)
Kossobokov, Vladimir
2013-04-01
Why earthquake occurrences bring us so many surprises? The answer seems evident if we review the relationships that are commonly used to assess seismic hazard. The time-span of physically reliable Seismic History is yet a small portion of a rupture recurrence cycle at an earthquake-prone site, which makes premature any kind of reliable probabilistic statements about narrowly localized seismic hazard. Moreover, seismic evidences accumulated to-date demonstrate clearly that most of the empirical relations commonly accepted in the early history of instrumental seismology can be proved erroneous when testing statistical significance is applied. Seismic events, including mega-earthquakes, cluster displaying behaviors that are far from independent or periodic. Their distribution in space is possibly fractal, definitely, far from uniform even in a single segment of a fault zone. Such a situation contradicts generally accepted assumptions used for analytically tractable or computer simulations and complicates design of reliable methodologies for realistic earthquake hazard assessment, as well as search and definition of precursory behaviors to be used for forecast/prediction purposes. As a result, the conclusions drawn from such simulations and analyses can MISLEAD TO SCIENTIFICALLY GROUNDLESS APPLICATION, which is unwise and extremely dangerous in assessing expected societal risks and losses. For example, a systematic comparison of the GSHAP peak ground acceleration estimates with those related to actual strong earthquakes, unfortunately, discloses gross inadequacy of this "probabilistic" product, which appears UNACCEPTABLE FOR ANY KIND OF RESPONSIBLE SEISMIC RISK EVALUATION AND KNOWLEDGEABLE DISASTER PREVENTION. The self-evident shortcomings and failures of GSHAP appeals to all earthquake scientists and engineers for an urgent revision of the global seismic hazard maps from the first principles including background methodologies involved, such that there becomes: (a) a
Carbon Dioxide: Surprising Effects on Decision Making and Neurocognitive Performance
NASA Technical Reports Server (NTRS)
James, John T.
2013-01-01
The occupants of modern submarines and the International Space Station (ISS) have much in common as far as their air quality is concerned. Air is polluted by materials offgassing, use of utility compounds, leaks of systems chemicals, and anthropogenic sources. The primary anthropogenic compound of concern to submariners and astronauts has been carbon dioxide (CO2). NASA and the US Navy rely on the National Research Council Committee on Toxicology (NRC-COT) to help formulate exposure levels to CO2 that are thought to be safe for exposures of 3-6 months. NASA calls its limits Spacecraft Maximum Allowable Concentrations (SMACs). Years of experience aboard the ISS and a recent publication on deficits in decision making in ground-based subjects exposed briefly to 0.25% CO2 suggest that exposure levels that have been presumed acceptable to preserve health and performance need to be reevaluated. The current CO2 exposure limits for 3-6 months set by NASA and the UK Navy are 0.7%, and the limit for US submariners is 0.5%, although the NRC-COT recommended a 90-day level of 0.8% as safe a few years ago. NASA has set a 1000-day SMAC at 0.5% for exploration-class missions. Anecdotal experience with ISS operations approaching the current 180-day SMAC of 0.7% suggest that this limit is too high. Temporarily, NASA has limited exposures to 0.5% until further peer-reviewed data become available. In the meantime, a study published last year in the journal Environmental Health Perspectives (Satish U, et al. 2012) demonstrated that complexdecision- making performance is somewhat affected at 0.1% CO2 and becomes "dysfunctional" for at least half of the 9 indices of performance at concentrations approaching 0.25% CO2. The investigators used the Strategic Management Simulation (SMS) method of testing for decisionmaking ability, and the results were so surprising to the investigators that they declared that their findings need to be independently confirmed. NASA has responded to the
High Heels Increase Women's Attractiveness.
Guéguen, Nicolas
2015-11-01
Research has found that the appearance of women's apparel helps increase their attractiveness as rated by men and that men care more about physical features in potential opposite-sex mates. However, the effect of sartorial appearance has received little interest from scientists. In a series of studies, the length of women's shoe heels was examined. A woman confederate wearing black shoes with 0, 5, or 9 cm heels asked men for help in various circumstances. In Study 1, she asked men to respond to a short survey on gender equality. In Study 2, the confederate asked men and women to participate in a survey on local food habit consumption. In Study 3, men and women in the street were observed while walking in back of the female confederate who dropped a glove apparently unaware of her loss. It was found that men's helping behavior increased as soon as heel length increased. However, heel length had no effect on women's helping behavior. It was also found that men spontaneously approached women more quickly when they wore high-heeled shoes (Study 4). Change in gait, foot-size judgment, and misattribution of sexiness and sexual intent were used as possible explanations.
Attracting Girls into Physics (abstract)
NASA Astrophysics Data System (ADS)
Gadalla, Afaf
2009-04-01
A recent international study of women in physics showed that enrollment in physics and science is declining for both males and females and that women are severely underrepresented in careers requiring a strong physics background. The gender gap begins early in the pipeline, from the first grade. Girls are treated differently than boys at home and in society in ways that often hinder their chances for success. They have fewer freedoms, are discouraged from accessing resources or being adventurous, have far less exposure to problem solving, and are not encouraged to choose their lives. In order to motivate more girl students to study physics in the Assiut governorate of Egypt, the Assiut Alliance for the Women and Assiut Education District collaborated in renovating the education of physics in middle and secondary school classrooms. A program that helps in increasing the number of girls in science and physics has been designed in which informal groupings are organized at middle and secondary schools to involve girls in the training and experiences needed to attract and encourage girls to learn physics. During implementation of the program at some schools, girls, because they had not been trained in problem-solving as boys, appeared not to be as facile in abstracting the ideas of physics, and that was the primary reason for girls dropping out of science and physics. This could be overcome by holding a topical physics and technology summer school under the supervision of the Assiut Alliance for the Women.
Bayesian Model Averaging for Propensity Score Analysis.
Kaplan, David; Chen, Jianshen
2014-01-01
This article considers Bayesian model averaging as a means of addressing uncertainty in the selection of variables in the propensity score equation. We investigate an approximate Bayesian model averaging approach based on the model-averaged propensity score estimates produced by the R package BMA but that ignores uncertainty in the propensity score. We also provide a fully Bayesian model averaging approach via Markov chain Monte Carlo sampling (MCMC) to account for uncertainty in both parameters and models. A detailed study of our approach examines the differences in the causal estimate when incorporating noninformative versus informative priors in the model averaging stage. We examine these approaches under common methods of propensity score implementation. In addition, we evaluate the impact of changing the size of Occam's window used to narrow down the range of possible models. We also assess the predictive performance of both Bayesian model averaging propensity score approaches and compare it with the case without Bayesian model averaging. Overall, results show that both Bayesian model averaging propensity score approaches recover the treatment effect estimates well and generally provide larger uncertainty estimates, as expected. Both Bayesian model averaging approaches offer slightly better prediction of the propensity score compared with the Bayesian approach with a single propensity score equation. Covariate balance checks for the case study show that both Bayesian model averaging approaches offer good balance. The fully Bayesian model averaging approach also provides posterior probability intervals of the balance indices.
Attractive faces temporally modulate visual attention
Nakamura, Koyo; Kawabata, Hideaki
2014-01-01
Facial attractiveness is an important biological and social signal on social interaction. Recent research has demonstrated that an attractive face captures greater spatial attention than an unattractive face does. Little is known, however, about the temporal characteristics of visual attention for facial attractiveness. In this study, we investigated the temporal modulation of visual attention induced by facial attractiveness by using a rapid serial visual presentation. Fourteen male faces and two female faces were successively presented for 160 ms, respectively, and participants were asked to identify two female faces embedded among a series of multiple male distractor faces. Identification of a second female target (T2) was impaired when a first target (T1) was attractive compared to neutral or unattractive faces, at 320 ms stimulus onset asynchrony (SOA); identification was improved when T1 was attractive compared to unattractive faces at 640 ms SOA. These findings suggest that the spontaneous appraisal of facial attractiveness modulates temporal attention. PMID:24994994
Romantic attraction and adolescent smoking trajectories.
Pollard, Michael S; Tucker, Joan S; Green, Harold D; Kennedy, David P; Go, Myong-Hyun
2011-12-01
Research on sexual orientation and substance use has established that lesbian, gay, and bisexual (LGB) individuals are more likely to smoke than heterosexuals. This analysis furthers the examination of smoking behaviors across sexual orientation groups by describing how same- and opposite-sex romantic attraction, and changes in romantic attraction, are associated with distinct six-year developmental trajectories of smoking. The National Longitudinal Study of Adolescent Health dataset is used to test our hypotheses. Multinomial logistic regressions predicting smoking trajectory membership as a function of romantic attraction were separately estimated for men and women. Romantic attraction effects were found only for women. The change from self-reported heterosexual attraction to lesbian or bisexual attraction was more predictive of higher smoking trajectories than was a consistent lesbian or bisexual attraction, with potentially important differences between the smoking patterns of these two groups.
A statistical model of facial attractiveness.
Said, Christopher P; Todorov, Alexander
2011-09-01
Previous research has identified facial averageness and sexual dimorphism as important factors in facial attractiveness. The averageness and sexual dimorphism accounts provide important first steps in understanding what makes faces attractive, and should be valued for their parsimony. However, we show that they explain relatively little of the variance in facial attractiveness, particularly for male faces. As an alternative to these accounts, we built a regression model that defines attractiveness as a function of a face's position in a multidimensional face space. The model provides much more predictive power than the averageness and sexual dimorphism accounts and reveals previously unreported components of attractiveness. The model shows that averageness is attractive in some dimensions but not in others and resolves previous contradictory reports about the effects of sexual dimorphism on the attractiveness of male faces.
Surprise Discovery of Highly Developed Structure in the Young Universe
NASA Astrophysics Data System (ADS)
2005-03-01
ESO-VLT and ESA XMM-Newton Together Discover Earliest Massive Cluster of Galaxies Known Summary Combining observations with ESO's Very Large Telescope and ESA's XMM-Newton X-ray observatory, astronomers have discovered the most distant, very massive structure in the Universe known so far. It is a remote cluster of galaxies that is found to weigh as much as several thousand galaxies like our own Milky Way and is located no less than 9,000 million light-years away. The VLT images reveal that it contains reddish and elliptical, i.e. old, galaxies. Interestingly, the cluster itself appears to be in a very advanced state of development. It must therefore have formed when the Universe was less than one third of its present age. The discovery of such a complex and mature structure so early in the history of the Universe is highly surprising. Indeed, until recently it would even have been deemed impossible. PR Photo 05a/05: Discovery X-Ray Image of the Distant Cluster (ESA XMM-Netwon) PR Photo 05b/05: False Colour Image of XMMU J2235.3-2557 (FORS/VLT and ESA XMM-Newton) Serendipitous discovery ESO PR Photo 05a/05 ESO PR Photo 05a/05 Discovery X-Ray Image of the Distant Cluster (ESA XMM-Newton) [Preview - JPEG: 400 x 421 pix - 106k] [Normal - JPEG: 800 x 842 pix - 843k] [Full Res - JPEG: 2149 x 2262 pix - 2.5M] Caption: ESO PR Photo 05a/05 is a reproduction of the XMM-Newton observations of the nearby active galaxy NGC7314 (bright object in the centre) from which the newly found distant cluster (white box) was serendipitously identified. The circular field-of-view of XMM-Newton is half-a-degree in diameter, or about the same angular size as the Full Moon. The inset shows the diffuse X-ray emission from the distant cluster XMMU J2235.3-2557. Clusters of galaxies are gigantic structures containing hundreds to thousands of galaxies. They are the fundamental building blocks of the Universe and their study thus provides unique information about the underlying architecture of the
Bayesian Inference on Proportional Elections
Brunello, Gabriel Hideki Vatanabe; Nakano, Eduardo Yoshio
2015-01-01
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. PMID:25786259
Bayesian seismology of the Sun
NASA Astrophysics Data System (ADS)
Gruberbauer, M.; Guenther, D. B.
2013-06-01
We perform a Bayesian grid-based analysis of the solar l = 0, 1, 2 and 3 p modes obtained via BiSON in order to deliver the first Bayesian asteroseismic analysis of the solar composition problem. We do not find decisive evidence to prefer either of the contending chemical compositions, although the revised solar abundances (AGSS09) are more probable in general. We do find indications for systematic problems in standard stellar evolution models, unrelated to the consequences of inadequate modelling of the outer layers on the higher order modes. The seismic observables are best fitted by solar models that are several hundred million years older than the meteoritic age of the Sun. Similarly, meteoritic age calibrated models do not adequately reproduce the observed seismic observables. Our results suggest that these problems will affect any asteroseismic inference that relies on a calibration to the Sun.
Pedestrian dynamics via Bayesian networks
NASA Astrophysics Data System (ADS)
Venkat, Ibrahim; Khader, Ahamad Tajudin; Subramanian, K. G.
2014-06-01
Studies on pedestrian dynamics have vital applications in crowd control management relevant to organizing safer large scale gatherings including pilgrimages. Reasoning pedestrian motion via computational intelligence techniques could be posed as a potential research problem within the realms of Artificial Intelligence. In this contribution, we propose a "Bayesian Network Model for Pedestrian Dynamics" (BNMPD) to reason the vast uncertainty imposed by pedestrian motion. With reference to key findings from literature which include simulation studies, we systematically identify: What are the various factors that could contribute to the prediction of crowd flow status? The proposed model unifies these factors in a cohesive manner using Bayesian Networks (BNs) and serves as a sophisticated probabilistic tool to simulate vital cause and effect relationships entailed in the pedestrian domain.
Bayesian estimation of turbulent motion.
Héas, Patrick; Herzet, Cédric; Mémin, Etienne; Heitz, Dominique; Mininni, Pablo D
2013-06-01
Based on physical laws describing the multiscale structure of turbulent flows, this paper proposes a regularizer for fluid motion estimation from an image sequence. Regularization is achieved by imposing some scale invariance property between histograms of motion increments computed at different scales. By reformulating this problem from a Bayesian perspective, an algorithm is proposed to jointly estimate motion, regularization hyperparameters, and to select the most likely physical prior among a set of models. Hyperparameter and model inference are conducted by posterior maximization, obtained by marginalizing out non--Gaussian motion variables. The Bayesian estimator is assessed on several image sequences depicting synthetic and real turbulent fluid flows. Results obtained with the proposed approach exceed the state-of-the-art results in fluid flow estimation.
Deep Learning and Bayesian Methods
NASA Astrophysics Data System (ADS)
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 inference for agreement measures.
Vidal, Ignacio; de Castro, Mário
2016-08-25
The agreement of different measurement methods is an important issue in several disciplines like, for example, Medicine, Metrology, and Engineering. In this article, some agreement measures, common in the literature, were analyzed from a Bayesian point of view. Posterior inferences for such agreement measures were obtained based on well-known Bayesian inference procedures for the bivariate normal distribution. As a consequence, a general, simple, and effective method is presented, which does not require Markov Chain Monte Carlo methods and can be applied considering a great variety of prior distributions. Illustratively, the method was exemplified using five objective priors for the bivariate normal distribution. A tool for assessing the adequacy of the model is discussed. Results from a simulation study and an application to a real dataset are also reported.
Extreme dry spells: Problem of rounding and Bayesian solution
NASA Astrophysics Data System (ADS)
Cindric Kalin, Ksenija; Pasaric, Zoran
2016-04-01
Two theoretically justified models of extremes are applied to dry spell (DS) series: The generalized Pareto distribution is applied to peak-over-threshold data (POT-GP), and the Generalized Extreme Value distribution is applied to the annual maxima (AM-GEV). DS data are categorized according to three precipitation-per-day thresholds (1, 5 and 10 mm). The well-known classical methods for parameter estimation (L-moments and Maximum Likelihood) are applied both to measured and to simulated DS time series. When applied within the GEV model, both methods yield very similar results. Somewhat surprisingly, in the case of the GP model, these methods lead to substantially different estimates of parameters, as well as return values. This is found to be a consequence of the fact that DS values are recorded discretely as a whole number of days, whereas the classical extreme value distributions are intended for continuous data. The inference is further evaluated within the Bayesian paradigm, where the process of rounding can be incorporated in a straightforward manner. The study confirmed precautionary estimations when applying the AM-GEV model in comparison with the simpler AM-Gumbel model. Regarding POT-GP modelling, the Bayesian approach reveals a high uncertainty that can occur in parameter estimations when very high thresholds are considered. It is found that there are no clear criteria in the assessment of some optimal threshold, nor is there a necessity for its detection. Instead, Bayesian inference provides a reasonable overall picture of the range of thresholds compatible with the GP-model. Furthermore, it is concluded that when using rounded data, all three GP parameters should be assessed. The location estimates should be compatible with the theoretical value of 0.5. Although the present study is performed mainly on the DS series from two stations in Croatia spanning the period of 1961-2010, the authors believe that the methodology developed here is applicable to
Supermagnetic Neutron Star Surprises Scientists, Forces Revision of Theories
NASA Astrophysics Data System (ADS)
2006-08-01
magnetars because their magnetic fields are 100-1,000 times stronger than those of typical pulsars. It is the decay of those incredibly strong fields that powers their strange X-ray emission. "The magnetic field from a magnetar would make an aircraft carrier spin around and point north quicker than a compass needle moves on Earth," said David Helfand, of Columbia University. A magnetar's field is 1,000 trillion times stronger than Earth's, Helfand pointed out. The new object -- named XTE J1810-197 -- was first discovered by NASA's Rossi X-ray Timing Explorer when it emitted a strong burst of X-rays in 2003. While the X-rays were fading in 2004, Jules Halpern of Columbia University and collaborators identified the magnetar as a radio-wave emitter using the National Science Foundation's (NSF) Very Large Array (VLA) radio telescope in New Mexico. Any radio emission is highly unusual for a magnetar. Because magnetars had not been seen to regularly emit radio waves, the scientists presumed that the radio emission was caused by a cloud of particles thrown off the neutron star at the time of its X-ray outburst, an idea they soon would realize was wrong. With knowledge that the magnetar emitted some form of radio waves, Camilo and his colleagues observed it with the Parkes radio telescope in Australia in March and immediately detected astonishingly strong radio pulsations every 5.5 seconds, corresponding to the previously-determined rotation rate of the neutron star. As they continued to observe XTE J1810-197, the scientists got more surprises. Whereas most pulsars become weaker at higher radio frequencies, XTE J1810-197 does not, remaining a strong emitter at frequencies up to 140 GHz, the highest frequency ever detected from a radio pulsar. In addition, unlike normal pulsars, the object's radio emission fluctuates in strength from day to day, and the shape of the pulsations changes as well. These variations likely indicate that the magnetic fields around the pulsar are changing
Chandra Finds Surprising Black Hole Activity In Galaxy Cluster
NASA Astrophysics Data System (ADS)
2002-09-01
Scientists at the Carnegie Observatories in Pasadena, California, have uncovered six times the expected number of active, supermassive black holes in a single viewing of a cluster of galaxies, a finding that has profound implications for theories as to how old galaxies fuel the growth of their central black holes. The finding suggests that voracious, central black holes might be as common in old, red galaxies as they are in younger, blue galaxies, a surprise to many astronomers. The team made this discovery with NASA'S Chandra X-ray Observatory. They also used Carnegie's 6.5-meter Walter Baade Telescope at the Las Campanas Observatory in Chile for follow-up optical observations. "This changes our view of galaxy clusters as the retirement homes for old and quiet black holes," said Dr. Paul Martini, lead author on a paper describing the results that appears in the September 10 issue of The Astrophysical Journal Letters. "The question now is, how do these black holes produce bright X-ray sources, similar to what we see from much younger galaxies?" Typical of the black hole phenomenon, the cores of these active galaxies are luminous in X-ray radiation. Yet, they are obscured, and thus essentially undetectable in the radio, infrared and optical wavebands. "X rays can penetrate obscuring gas and dust as easily as they penetrate the soft tissue of the human body to look for broken bones," said co-author Dr. Dan Kelson. "So, with Chandra, we can peer through the dust and we have found that even ancient galaxies with 10-billion-year-old stars can have central black holes still actively pulling in copious amounts of interstellar gas. This activity has simply been hidden from us all this time. This means these galaxies aren't over the hill after all and our theories need to be revised." Scientists say that supermassive black holes -- having the mass of millions to billions of suns squeezed into a region about the size of our Solar System -- are the engines in the cores of
Elements of Bayesian experimental design
Sivia, D.S.
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 Treaty Monitoring: Preliminary Report
2011-09-01
J. Russell, P. Kidwell , and E. Sudderth (2011b). Global seismic monitoring: A Bayesian approach. In Proc. AAAI-11, San Francisco. Arora, N. S., S. J...Russell, P. Kidwell , and E. Sudderth (2011a). Global seismic monitoring as probabilistic inference. In Advances in Neural Information Processing...American Geophysical Union, 90(52), Fall Meeting Supplement, Abstract S31B-1713. Arora, N., Russell, S., de Salvo Braz, R ., and Sudderth, E. (2010b
Space Shuttle RTOS Bayesian Network
NASA Technical Reports Server (NTRS)
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
Bayesian analysis for kaon photoproduction
Marsainy, T. Mart, T.
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.
Lü, Fan; Bize, Ariane; Guillot, Alain; Monnet, Véronique; Madigou, Céline; Chapleur, Olivier; Mazéas, Laurent; He, Pinjing; Bouchez, Théodore
2014-01-01
Cellulose is the most abundant biopolymer on Earth. Optimising energy recovery from this renewable but recalcitrant material is a key issue. The metaproteome expressed by thermophilic communities during cellulose anaerobic digestion was investigated in microcosms. By multiplying the analytical replicates (65 protein fractions analysed by MS/MS) and relying solely on public protein databases, more than 500 non-redundant protein functions were identified. The taxonomic community structure as inferred from the metaproteomic data set was in good overall agreement with 16S rRNA gene tag pyrosequencing and fluorescent in situ hybridisation analyses. Numerous functions related to cellulose and hemicellulose hydrolysis and fermentation catalysed by bacteria related to Caldicellulosiruptor spp. and Clostridium thermocellum were retrieved, indicating their key role in the cellulose-degradation process and also suggesting their complementary action. Despite the abundance of acetate as a major fermentation product, key methanogenesis enzymes from the acetoclastic pathway were not detected. In contrast, enzymes from the hydrogenotrophic pathway affiliated to Methanothermobacter were almost exclusively identified for methanogenesis, suggesting a syntrophic acetate oxidation process coupled to hydrogenotrophic methanogenesis. Isotopic analyses confirmed the high dominance of the hydrogenotrophic methanogenesis. Very surprising was the identification of an abundant proteolytic activity from Coprothermobacter proteolyticus strains, probably acting as scavenger and/or predator performing proteolysis and fermentation. Metaproteomics thus appeared as an efficient tool to unravel and characterise metabolic networks as well as ecological interactions during methanisation bioprocesses. More generally, metaproteomics provides direct functional insights at a limited cost, and its attractiveness should increase in the future as sequence databases are growing exponentially. PMID:23949661
Bayesian inference for radio observations
NASA Astrophysics Data System (ADS)
Lochner, Michelle; Natarajan, Iniyan; Zwart, Jonathan T. L.; Smirnov, Oleg; Bassett, Bruce A.; Oozeer, Nadeem; Kunz, Martin
2015-06-01
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 inadequate uncertainty estimates and biased results because any correlations between parameters are ignored. 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 realization 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. This enables it to derive both correlations and accurate uncertainties, making use of the flexible software MEQTREES to model the sky and telescope simultaneously. We demonstrate BIRO with two simulated sets of Westerbork Synthesis Radio Telescope data sets. In the first, we perform joint estimates of 103 scientific (flux densities of sources) and instrumental (pointing errors, beamwidth and noise) parameters. In the second example, we perform source separation with BIRO. Using the Bayesian evidence, we can accurately select between a single point source, two point sources and an extended Gaussian source, allowing for `super-resolution' on scales much smaller than the synthesized beam.
Quantum Inference on Bayesian Networks
NASA Astrophysics Data System (ADS)
Yoder, Theodore; Low, Guang Hao; Chuang, Isaac
2014-03-01
Because quantum physics is naturally probabilistic, it seems reasonable to expect physical systems to describe probabilities and their evolution in a natural fashion. Here, we use quantum computation to speedup sampling from a graphical probability model, the Bayesian network. A specialization of this sampling problem is approximate Bayesian inference, where the distribution on query variables is sampled given the values e of evidence variables. Inference is a key part of modern machine learning and artificial intelligence tasks, but is known to be NP-hard. Classically, a single unbiased sample is obtained from a Bayesian network on n variables with at most m parents per node in time (nmP(e) - 1 / 2) , depending critically on P(e) , the probability the evidence might occur in the first place. However, by implementing a quantum version of rejection sampling, we obtain a square-root speedup, taking (n2m P(e) -1/2) time per sample. The speedup is the result of amplitude amplification, which is proving to be broadly applicable in sampling and machine learning tasks. In particular, we provide an explicit and efficient circuit construction that implements the algorithm without the need for oracle access.
Park, Gewnhi; Vasey, Michael W.; Kim, Grace; Hu, Dixie D.; Thayer, Julian F.
2016-01-01
The current research examines whether trait anxiety is associated with negative interpretation bias when resolving valence ambiguity of surprised faces. To further isolate the neuro-cognitive mechanism, we presented angry, happy, and surprised faces at broad spatial frequency (BSF), high spatial frequency (HSF), and low spatial frequency (LSF) and asked participants to determine the valence of each face. High trait anxiety was associated with more negative interpretations of BSF (i.e., intact) surprised faces. However, the modulation of trait anxiety on the negative interpretation of surprised faces disappeared at HSF and LSF. The current study provides evidence that trait anxiety modulates negative interpretations of BSF surprised faces. However, the negative interpretation of LSF surprised faces appears to be a robust default response that occurs regardless of individual differences in trait anxiety. PMID:27536266
Park, Gewnhi; Vasey, Michael W; Kim, Grace; Hu, Dixie D; Thayer, Julian F
2016-01-01
The current research examines whether trait anxiety is associated with negative interpretation bias when resolving valence ambiguity of surprised faces. To further isolate the neuro-cognitive mechanism, we presented angry, happy, and surprised faces at broad spatial frequency (BSF), high spatial frequency (HSF), and low spatial frequency (LSF) and asked participants to determine the valence of each face. High trait anxiety was associated with more negative interpretations of BSF (i.e., intact) surprised faces. However, the modulation of trait anxiety on the negative interpretation of surprised faces disappeared at HSF and LSF. The current study provides evidence that trait anxiety modulates negative interpretations of BSF surprised faces. However, the negative interpretation of LSF surprised faces appears to be a robust default response that occurs regardless of individual differences in trait anxiety.
Miscalibrations in judgements of attractiveness with cosmetics.
Jones, Alex L; Kramer, Robin S S; Ward, Robert
2014-10-01
Women use cosmetics to enhance their attractiveness. How successful they are in doing so remains unknown--how do men and women respond to cosmetics use in terms of attractiveness? There are a variety of miscalibrations where attractiveness is concerned--often, what one sex thinks the opposite sex finds attractive is incorrect. Here, we investigated observer perceptions about attractiveness and cosmetics, as well as their understanding of what others would find attractive. We used computer graphic techniques to allow observers to vary the amount of cosmetics applied to a series of female faces. We asked observers to optimize attractiveness for themselves, for what they thought women in general would prefer, and what they thought men in general would prefer. We found that men and women agree on the amount of cosmetics they find attractive, but overestimate the preferences of women and, when considering the preferences of men, overestimate even more. We also find that models' self-applied cosmetics are far in excess of individual preferences. These findings suggest that attractiveness perceptions with cosmetics are a form of pluralistic ignorance, whereby women tailor their cosmetics use to an inaccurate perception of others' preferences. These findings also highlight further miscalibrations of attractiveness ideals.
Facial shape and judgements of female attractiveness.
Perrett, D I; May, K A; Yoshikawa, S
1994-03-17
The finding that photographic and digital composites (blends) of faces are considered to be attractive has led to the claim that attractiveness is averageness. This would encourage stabilizing selection, favouring phenotypes with an average facial structure. The 'averageness hypothesis' would account for the low distinctiveness of attractive faces but is difficult to reconcile with the finding that some facial measurements correlate with attractiveness. An average face shape is attractive but may not be optimally attractive. Human preferences may exert directional selection pressures, as with the phenomena of optimal outbreeding and sexual selection for extreme characteristics. Using composite faces, we show here that, contrary to the averageness hypothesis, the mean shape of a set of attractive faces is preferred to the mean shape of the sample from which the faces were selected. In addition, attractive composites can be made more attractive by exaggerating the shape differences from the sample mean. Japanese and caucasian observers showed the same direction of preferences for the same facial composites, suggesting that aesthetic judgements of face shape are similar across different cultural backgrounds. Our finding that highly attractive facial configurations are not average shows that preferences could exert a directional selection pressure on the evolution of human face shape.
A Neural Mechanism for Surprise-related Interruptions of Visuospatial Working Memory.
Wessel, Jan R
2016-11-30
Surprising perceptual events recruit a fronto-basal ganglia mechanism for inhibition, which suppresses motor activity following surprise. A recent study found that this inhibitory mechanism also disrupts the maintenance of verbal working memory (WM) after surprising tones. However, it is unclear whether this same mechanism also relates to surprise-related interruptions of non-verbal WM. We tested this hypothesis using a change-detection task, in which surprising tones impaired visuospatial WM. Participants also performed a stop-signal task (SST). We used independent component analysis and single-trial scalp-electroencephalogram to test whether the same inhibitory mechanism that reflects motor inhibition in the SST relates to surprise-related visuospatial WM decrements, as was the case for verbal WM. As expected, surprising tones elicited activity of the inhibitory mechanism, and this activity correlated strongly with the trial-by-trial level of surprise. However, unlike for verbal WM, the activity of this mechanism was unrelated to visuospatial WM accuracy. Instead, inhibition-independent activity that immediately succeeded the inhibitory mechanism was increased when visuospatial WM was disrupted. This shows that surprise-related interruptions of visuospatial WM are not effected by the same inhibitory mechanism that interrupts verbal WM, and instead provides evidence for a 2-stage model of distraction.
Bayesian networks for evaluating forensic DNA profiling evidence: a review and guide to literature.
Biedermann, A; Taroni, F
2012-03-01
Almost 30 years ago, Bayesian networks (BNs) were developed in the field of artificial intelligence as a framework that should assist researchers and practitioners in applying the theory of probability to inference problems of more substantive size and, thus, to more realistic and practical problems. Since the late 1980s, Bayesian networks have also attracted researchers in forensic science and this tendency has considerably intensified throughout the last decade. This review article provides an overview of the scientific literature that describes research on Bayesian networks as a tool that can be used to study, develop and implement probabilistic procedures for evaluating the probative value of particular items of scientific evidence in forensic science. Primary attention is drawn here to evaluative issues that pertain to forensic DNA profiling evidence because this is one of the main categories of evidence whose assessment has been studied through Bayesian networks. The scope of topics is large and includes almost any aspect that relates to forensic DNA profiling. Typical examples are inference of source (or, 'criminal identification'), relatedness testing, database searching and special trace evidence evaluation (such as mixed DNA stains or stains with low quantities of DNA). The perspective of the review presented here is not exclusively restricted to DNA evidence, but also includes relevant references and discussion on both, the concept of Bayesian networks as well as its general usage in legal sciences as one among several different graphical approaches to evidence evaluation.
A local approach for focussed Bayesian fusion
NASA Astrophysics Data System (ADS)
Sander, Jennifer; Heizmann, Michael; Goussev, Igor; Beyerer, Jürgen
2009-04-01
Local Bayesian fusion approaches aim to reduce high storage and computational costs of Bayesian fusion which is separated from fixed modeling assumptions. Using the small world formalism, we argue why this proceeding is conform with Bayesian theory. Then, we concentrate on the realization of local Bayesian fusion by focussing the fusion process solely on local regions that are task relevant with a high probability. The resulting local models correspond then to restricted versions of the original one. In a previous publication, we used bounds for the probability of misleading evidence to show the validity of the pre-evaluation of task specific knowledge and prior information which we perform to build local models. In this paper, we prove the validity of this proceeding using information theoretic arguments. For additional efficiency, local Bayesian fusion can be realized in a distributed manner. Here, several local Bayesian fusion tasks are evaluated and unified after the actual fusion process. For the practical realization of distributed local Bayesian fusion, software agents are predestinated. There is a natural analogy between the resulting agent based architecture and criminal investigations in real life. We show how this analogy can be used to improve the efficiency of distributed local Bayesian fusion additionally. Using a landscape model, we present an experimental study of distributed local Bayesian fusion in the field of reconnaissance, which highlights its high potential.
What's that sound? Auditory area CLM encodes stimulus surprise, not intensity or intensity changes.
Gill, Patrick; Woolley, Sarah M N; Fremouw, Thane; Theunissen, Frédéric E
2008-06-01
High-level sensory neurons encoding natural stimuli are not well described by linear models operating on the time-varying stimulus intensity. Here we show that firing rates of neurons in a secondary sensory forebrain area can be better modeled by linear functions of how surprising the stimulus is. We modeled auditory neurons in the caudal lateral mesopallium (CLM) of adult male zebra finches under urethane anesthesia with linear filters convolved not with stimulus intensity, but with stimulus surprise. Surprise was quantified as the logarithm of the probability of the stimulus given the local recent stimulus history and expectations based on conspecific song. Using our surprise method, the predictions of neural responses to conspecific song improved by 67% relative to those obtained using stimulus intensity. Similar prediction improvements cannot be replicated by assuming CLM performs derivative detection. The explanatory power of surprise increased from the midbrain through the primary forebrain and to CLM. When the stimulus presented was a random synthetic ripple noise, CLM neurons (but not neurons in lower auditory areas) were best described as if they were expecting conspecific song, finding the inconsistencies between birdsong and noise surprising. In summary, spikes in CLM neurons indicate stimulus surprise more than they indicate stimulus intensity features. The concept of stimulus surprise may be useful for modeling neural responses in other higher-order sensory areas whose functions have been poorly understood.
Distinct medial temporal networks encode surprise during motivation by reward versus punishment.
Murty, Vishnu P; LaBar, Kevin S; Adcock, R Alison
2016-10-01
Adaptive motivated behavior requires predictive internal representations of the environment, and surprising events are indications for encoding new representations of the environment. The medial temporal lobe memory system, including the hippocampus and surrounding cortex, encodes surprising events and is influenced by motivational state. Because behavior reflects the goals of an individual, we investigated whether motivational valence (i.e., pursuing rewards versus avoiding punishments) also impacts neural and mnemonic encoding of surprising events. During functional magnetic resonance imaging (fMRI), participants encountered perceptually unexpected events either during the pursuit of rewards or avoidance of punishments. Despite similar levels of motivation across groups, reward and punishment facilitated the processing of surprising events in different medial temporal lobe regions. Whereas during reward motivation, perceptual surprises enhanced activation in the hippocampus, during punishment motivation surprises instead enhanced activation in parahippocampal cortex. Further, we found that reward motivation facilitated hippocampal coupling with ventromedial PFC, whereas punishment motivation facilitated parahippocampal cortical coupling with orbitofrontal cortex. Behaviorally, post-scan testing revealed that reward, but not punishment, motivation resulted in greater memory selectivity for surprising events encountered during goal pursuit. Together these findings demonstrate that neuromodulatory systems engaged by anticipation of reward and punishment target separate components of the medial temporal lobe, modulating medial temporal lobe sensitivity and connectivity. Thus, reward and punishment motivation yield distinct neural contexts for learning, with distinct consequences for how surprises are incorporated into predictive mnemonic models of the environment.
Finding the SurPriSe: A Case Study of a Faculty Learning Community
ERIC Educational Resources Information Center
Michel, Roberta M.
2014-01-01
This article details a faculty learning community (FLC) that started in 2009 on the campus of a Midwestern University and has evolved into an interdisciplinary research, teaching and social community of practice and learning called SurPriSe. SurPriSe is an acronym that reflects the interest area of the FLC; Sur for surveillance, Pri for privacy,…
Attention in a Bayesian Framework
Whiteley, Louise; 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 settings, where cues shape expectations about a small number of upcoming stimuli and thus convey “prior” information about clearly defined objects. While operationally consistent with the experiments it seeks to describe, this view of attention as prior seems to miss many essential elements of both its selective and integrative roles, and thus cannot be easily extended to complex environments. We suggest that the resource bottleneck stems from the computational intractability of exact perceptual inference in complex settings, and that attention reflects an evolved mechanism for approximate inference which can be shaped to refine the local accuracy of perception. We show that this approach extends the simple picture of attention as prior, so as to provide a unified and computationally driven account of both selective and integrative attentional phenomena. PMID:22712010
Bayesian Methods and Universal Darwinism
NASA Astrophysics Data System (ADS)
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 estimation of genomic distance.
Durrett, Richard; Nielsen, Rasmus; York, Thomas L
2004-01-01
We present a Bayesian approach to the problem of inferring the number of inversions and translocations separating two species. The main reason for developing this method is that it will allow us to test hypotheses about the underlying mechanisms, such as the distribution of inversion track lengths or rate constancy among lineages. Here, we apply these methods to comparative maps of eggplant and tomato, human and cat, and human and cattle with 170, 269, and 422 markers, respectively. In the first case the most likely number of events is larger than the parsimony value. In the last two cases the parsimony solutions have very small probability. PMID:15020449
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.
Software For Multivariate Bayesian Classification
NASA Technical Reports Server (NTRS)
Saul, Ronald; Laird, Philip; Shelton, Robert
1996-01-01
PHD general-purpose classifier computer program. Uses Bayesian methods to classify vectors of real numbers, based on combination of statistical techniques that include multivariate density estimation, Parzen density kernels, and EM (Expectation Maximization) algorithm. By means of simple graphical interface, user trains classifier to recognize two or more classes of data and then use it to identify new data. Written in ANSI C for Unix systems and optimized for online classification applications. Embedded in another program, or runs by itself using simple graphical-user-interface. Online help files makes program easy to use.
Sexual Attraction and Harassment: Management's New Problems.
ERIC Educational Resources Information Center
Driscoll, Jeanne Bosson
1981-01-01
Both sexual attraction and harassment must be dealt with if men and women are to develop truly productive working relationships. Key issues include policies on sexual attraction and harassment, availability of professional resources on the subjects, training, and the role of personnel specialists. (CT)
Serial dependence in the perception of attractiveness
Xia, Ye; Leib, Allison Yamanashi; Whitney, David
2016-01-01
The perception of attractiveness is essential for choices of food, object, and mate preference. Like perception of other visual features, perception of attractiveness is stable despite constant changes of image properties due to factors like occlusion, visual noise, and eye movements. Recent results demonstrate that perception of low-level stimulus features and even more complex attributes like human identity are biased towards recent percepts. This effect is often called serial dependence. Some recent studies have suggested that serial dependence also exists for perceived facial attractiveness, though there is also concern that the reported effects are due to response bias. Here we used an attractiveness-rating task to test the existence of serial dependence in perceived facial attractiveness. Our results demonstrate that perceived face attractiveness was pulled by the attractiveness level of facial images encountered up to 6 s prior. This effect was not due to response bias and did not rely on the previous motor response. This perceptual pull increased as the difference in attractiveness between previous and current stimuli increased. Our results reconcile previously conflicting findings and extend previous work, demonstrating that sequential dependence in perception operates across different levels of visual analysis, even at the highest levels of perceptual interpretation. PMID:28006077
Electron attraction mediated by Coulomb repulsion
NASA Astrophysics Data System (ADS)
Hamo, A.; Benyamini, A.; Shapir, I.; Khivrich, I.; Waissman, J.; Kaasbjerg, K.; Oreg, Y.; von Oppen, F.; Ilani, S.
2016-07-01
One of the defining properties of electrons is their mutual Coulomb repulsion. However, in solids this basic property may change; for example, in superconductors, the coupling of electrons to lattice vibrations makes the electrons attract one another, leading to the formation of bound pairs. Fifty years ago it was proposed that electrons can be made attractive even when all of the degrees of freedom in the solid are electronic, by exploiting their repulsion from other electrons. This attraction mechanism, termed ‘excitonic’, promised to achieve stronger and more exotic superconductivity. Yet, despite an extensive search, experimental evidence for excitonic attraction has yet to be found. Here we demonstrate this attraction by constructing, from the bottom up, the fundamental building block of the excitonic mechanism. Our experiments are based on quantum devices made from pristine carbon nanotubes, combined with cryogenic precision manipulation. Using this platform, we demonstrate that two electrons can be made to attract each other using an independent electronic system as the ‘glue’ that mediates attraction. Owing to its tunability, our system offers insights into the underlying physics, such as the dependence of the emergent attraction on the underlying repulsion, and the origin of the pairing energy. We also demonstrate transport signatures of excitonic pairing. This experimental demonstration of excitonic pairing paves the way for the design of exotic states of matter.
Reciprocity of Interpersonal Attraction: A Confirmed Hypothesis.
ERIC Educational Resources Information Center
La Voie, Lawrence; Kenny, David A.
An increase in reciprocity of interpersonal attraction during the early acquaintance period followed by continuing social reciprocity are propositions that are central principles of several social psychological viewpoints. However, there is little empirical evidence of increasing reciprocity of interpersonal attraction over time. Two potential…
Electron attraction mediated by Coulomb repulsion.
Hamo, A; Benyamini, A; Shapir, I; Khivrich, I; Waissman, J; Kaasbjerg, K; Oreg, Y; von Oppen, F; Ilani, S
2016-07-21
One of the defining properties of electrons is their mutual Coulomb repulsion. However, in solids this basic property may change; for example, in superconductors, the coupling of electrons to lattice vibrations makes the electrons attract one another, leading to the formation of bound pairs. Fifty years ago it was proposed that electrons can be made attractive even when all of the degrees of freedom in the solid are electronic, by exploiting their repulsion from other electrons. This attraction mechanism, termed 'excitonic', promised to achieve stronger and more exotic superconductivity. Yet, despite an extensive search, experimental evidence for excitonic attraction has yet to be found. Here we demonstrate this attraction by constructing, from the bottom up, the fundamental building block of the excitonic mechanism. Our experiments are based on quantum devices made from pristine carbon nanotubes, combined with cryogenic precision manipulation. Using this platform, we demonstrate that two electrons can be made to attract each other using an independent electronic system as the 'glue' that mediates attraction. Owing to its tunability, our system offers insights into the underlying physics, such as the dependence of the emergent attraction on the underlying repulsion, and the origin of the pairing energy. We also demonstrate transport signatures of excitonic pairing. This experimental demonstration of excitonic pairing paves the way for the design of exotic states of matter.
An innovative mosquito trap for testing attractants
Technology Transfer Automated Retrieval System (TEKTRAN)
We describe a simple trap modification for testing or using attractants to collect flying mosquitoes. The trap also can test the effectiveness of spatial repellents. The proposed design may facilitate standardized testing of mosquito attractants and repellents. The trap uses a standard Centers f...
Aging and Attractiveness: Marriage Makes a Difference.
ERIC Educational Resources Information Center
Giesen, Carol Boellhoff
1989-01-01
Examined women's agreement with double standard of aging. Women (N=32) aged 28 to 63 shared definitions of attractiveness, femininity, and sexual appeal. Findings showed attractiveness was defined primarily by appearance, femininity by behavior and inferred traits, and sexual appeal by both. Found age differences among married women, but few age…
Expression of Power and Heterosexual Attraction.
ERIC Educational Resources Information Center
DeBlasio, Cynthia L.; Ellyson, Steve L.
Facial attractiveness has been the focus of considerable research in social psychology. Nonverbal behaviors emitted by the face may affect the perceived attractiveness of males and females differently. Visual behavior has particularly important functions in regulating social interaction and in establishing and conveying social power. Power and…
Sexual Attractiveness of Males and Females.
ERIC Educational Resources Information Center
Taylor, Peggy; And Others
The most important characteristics for females judging the attractiveness of males, and for males judging females, were eyes, body build and facial complexion. Previously, females tended to place less importance on physical components of attraction for both themselves and men. Possible interpretations are: (1) women have become more egalitarian…
Brain Systems for Assessing Facial Attractiveness
ERIC Educational Resources Information Center
Winston, Joel S.; O'Doherty, John; Kilner, James M.; Perrett, David I.; Dolan, Raymond J.
2007-01-01
Attractiveness is a facial attribute that shapes human affiliative behaviours. In a previous study we reported a linear response to facial attractiveness in orbitofrontal cortex (OFC), a region involved in reward processing. There are strong theoretical grounds for the hypothesis that coding stimulus reward value also involves the amygdala. The…
Visual perception of male body attractiveness.
Fan, J; Dai, W; Liu, F; Wu, J
2005-02-07
Based on 69 scanned Chinese male subjects and 25 Caucasian male subjects, the present study showed that the volume height index (VHI) is the most important visual cue to male body attractiveness of young Chinese viewers among the many body parameters examined in the study. VHI alone can explain ca. 73% of the variance of male body attractiveness ratings. The effect of VHI can be fitted with two half bell-shaped exponential curves with an optimal VHI at 17.6 l m(-2) and 18.0 l m(-2) for female raters and male raters, respectively. In addition to VHI, other body parameters or ratios can have small, but significant effects on male body attractiveness. Body proportions associated with fitness will enhance male body attractiveness. It was also found that there is an optimal waist-to-hip ratio (WHR) at 0.8 and deviations from this optimal WHR reduce male body attractiveness.
Bayesian learning theory applied to human cognition.
Jacobs, Robert A; Kruschke, John K
2011-01-01
Probabilistic models based on Bayes' rule are an increasingly popular approach to understanding human cognition. Bayesian models allow immense representational latitude and complexity. Because they use normative Bayesian mathematics to process those representations, they define optimal performance on a given task. This article focuses on key mechanisms of Bayesian information processing, and provides numerous examples illustrating Bayesian approaches to the study of human cognition. We start by providing an overview of Bayesian modeling and Bayesian networks. We then describe three types of information processing operations-inference, parameter learning, and structure learning-in both Bayesian networks and human cognition. This is followed by a discussion of the important roles of prior knowledge and of active learning. We conclude by outlining some challenges for Bayesian models of human cognition that will need to be addressed by future research. WIREs Cogn Sci 2011 2 8-21 DOI: 10.1002/wcs.80 For further resources related to this article, please visit the WIREs website.
Modeling Diagnostic Assessments with Bayesian Networks
ERIC Educational Resources Information Center
Almond, Russell G.; DiBello, Louis V.; Moulder, Brad; Zapata-Rivera, Juan-Diego
2007-01-01
This paper defines Bayesian network models and examines their applications to IRT-based cognitive diagnostic modeling. These models are especially suited to building inference engines designed to be synchronous with the finer grained student models that arise in skills diagnostic assessment. Aspects of the theory and use of Bayesian network models…
Optional stopping: no problem for Bayesians.
Rouder, Jeffrey N
2014-04-01
Optional stopping refers to the practice of peeking at data and then, based on the results, deciding whether or not to continue an experiment. In the context of ordinary significance-testing analysis, optional stopping is discouraged, because it necessarily leads to increased type I error rates over nominal values. This article addresses whether optional stopping is problematic for Bayesian inference with Bayes factors. Statisticians who developed Bayesian methods thought not, but this wisdom has been challenged by recent simulation results of Yu, Sprenger, Thomas, and Dougherty (2013) and Sanborn and Hills (2013). In this article, I show through simulation that the interpretation of Bayesian quantities does not depend on the stopping rule. Researchers using Bayesian methods may employ optional stopping in their own research and may provide Bayesian analysis of secondary data regardless of the employed stopping rule. I emphasize here the proper interpretation of Bayesian quantities as measures of subjective belief on theoretical positions, the difference between frequentist and Bayesian interpretations, and the difficulty of using frequentist intuition to conceptualize the Bayesian approach.
Accurate Biomass Estimation via Bayesian Adaptive Sampling
NASA Technical Reports Server (NTRS)
Wheeler, Kevin R.; Knuth, Kevin H.; Castle, Joseph P.; Lvov, Nikolay
2005-01-01
The following concepts were introduced: a) Bayesian adaptive sampling for solving biomass estimation; b) Characterization of MISR Rahman model parameters conditioned upon MODIS landcover. c) Rigorous non-parametric Bayesian approach to analytic mixture model determination. d) Unique U.S. asset for science product validation and verification.
The Bayesian Revolution Approaches Psychological Development
ERIC Educational Resources Information Center
Shultz, Thomas R.
2007-01-01
This commentary reviews five articles that apply Bayesian ideas to psychological development, some with psychology experiments, some with computational modeling, and some with both experiments and modeling. The reviewed work extends the current Bayesian revolution into tasks often studied in children, such as causal learning and word learning, and…
Properties of the Bayesian Knowledge Tracing Model
ERIC Educational Resources Information Center
van de Sande, Brett
2013-01-01
Bayesian Knowledge Tracing is used very widely to model student learning. It comes in two different forms: The first form is the Bayesian Knowledge Tracing "hidden Markov model" which predicts the probability of correct application of a skill as a function of the number of previous opportunities to apply that skill and the model…
Bayesian Statistics for Biological Data: Pedigree Analysis
ERIC Educational Resources Information Center
Stanfield, William D.; Carlton, Matthew A.
2004-01-01
The use of Bayes' formula is applied to the biological problem of pedigree analysis to show that the Bayes' formula and non-Bayesian or "classical" methods of probability calculation give different answers. First year college students of biology can be introduced to the Bayesian statistics.
Using Bayesian Networks to Improve Knowledge Assessment
ERIC Educational Resources Information Center
Millan, Eva; Descalco, Luis; Castillo, Gladys; Oliveira, Paula; Diogo, Sandra
2013-01-01
In this paper, we describe the integration and evaluation of an existing generic Bayesian student model (GBSM) into an existing computerized testing system within the Mathematics Education Project (PmatE--Projecto Matematica Ensino) of the University of Aveiro. This generic Bayesian student model had been previously evaluated with simulated…
Advances in Bayesian Modeling in Educational Research
ERIC Educational Resources Information Center
Levy, Roy
2016-01-01
In this article, I provide a conceptually oriented overview of Bayesian approaches to statistical inference and contrast them with frequentist approaches that currently dominate conventional practice in educational research. The features and advantages of Bayesian approaches are illustrated with examples spanning several statistical modeling…
Bayesian Decision Theoretical Framework for Clustering
ERIC Educational Resources Information Center
Chen, Mo
2011-01-01
In this thesis, we establish a novel probabilistic framework for the data clustering problem from the perspective of Bayesian decision theory. The Bayesian decision theory view justifies the important questions: what is a cluster and what a clustering algorithm should optimize. We prove that the spectral clustering (to be specific, the…
Bayesian inference in physics: case studies
NASA Astrophysics Data System (ADS)
Dose, V.
2003-09-01
This report describes the Bayesian approach to probability theory with emphasis on the application to the evaluation of experimental data. A brief summary of Bayesian principles is given, with a discussion of concepts, terminology and pitfalls. The step from Bayesian principles to data processing involves major numerical efforts. We address the presently employed procedures of numerical integration, which are mainly based on the Monte Carlo method. The case studies include examples from electron spectroscopies, plasma physics, ion beam analysis and mass spectrometry. Bayesian solutions to the ubiquitous problem of spectrum restoration are presented and advantages and limitations are discussed. Parameter estimation within the Bayesian framework is shown to allow for the incorporation of expert knowledge which in turn allows the treatment of under-determined problems which are inaccessible by the traditional maximum likelihood method. A unique and extremely valuable feature of Bayesian theory is the model comparison option. Bayesian model comparison rests on Ockham's razor which limits the complexity of a model to the amount necessary to explain the data without fitting noise. Finally we deal with the treatment of inconsistent data. They arise frequently in experimental work either from incorrect estimation of the errors associated with a measurement or alternatively from distortions of the measurement signal by some unrecognized spurious source. Bayesian data analysis sometimes meets with spectacular success. However, the approach cannot do wonders, but it does result in optimal robust inferences on the basis of all available and explicitly declared information.
An Internet study of men sexually attracted to children: Sexual attraction patterns.
Bailey, J Michael; Hsu, Kevin J; Bernhard, Paula A
2016-10-01
To our knowledge, this is the first large study of the attractions of child-attracted men recruited in any manner other than their being charged with legal offenses. We recruited 1,189 men from websites for adults attracted to children. Men in our sample were highly attracted to children, and they were much less attracted to adults, especially to adult men. However, men varied with respect to which combination of gender and age they found most attractive. Men in our sample were especially attracted to pubescent boys and prepubescent girls. Their self-reported attraction patterns closely tracked the age/gender gradient of sexual arousal established in prior research. Consistent with the gradient, men most attracted to prepubescent children were especially likely to have bisexual attractions to children. Pedohebephilia-attraction to sexually immature children-is best considered a collection of related if distinct sexual orientations, which vary in the particular combination of gender and sexual maturity that elicits greatest sexual attraction. Finally, our study reveals the potential power and efficiency of studying highly cooperative child-attracted men recruited via the Internet. (PsycINFO Database Record
How facial attractiveness affects sustained attention.
Li, Jie; Oksama, Lauri; Hyönä, Jukka
2016-10-01
The present study investigated whether and how facial attractiveness affects sustained attention. We adopted a multiple-identity tracking paradigm, using attractive and unattractive faces as stimuli. Participants were required to track moving target faces amid distractor faces and report the final location of each target. In Experiment 1, the attractive and unattractive faces differed in both the low-level properties (i.e., luminance, contrast, and color saturation) and high-level properties (i.e., physical beauty and age). The results showed that the attractiveness of both the target and distractor faces affected the tracking performance: The attractive target faces were tracked better than the unattractive target faces; when the targets and distractors were both unattractive male faces, the tracking performance was poorer than when they were of different attractiveness. In Experiment 2, the low-level properties of the facial images were equalized. The results showed that the attractive target faces were still tracked better than unattractive targets while the effects related to distractor attractiveness ceased to exist. Taken together, the results indicate that during attentional tracking the high-level properties related to the attractiveness of the target faces can be automatically processed, and then they can facilitate the sustained attention on the attractive targets, either with or without the supplement of low-level properties. On the other hand, only low-level properties of the distractor faces can be processed. When the distractors share similar low-level properties with the targets, they can be grouped together, so that it would be more difficult to sustain attention on the individual targets.
Hepatitis disease detection using Bayesian theory
NASA Astrophysics Data System (ADS)
Maseleno, Andino; Hidayati, Rohmah Zahroh
2017-02-01
This paper presents hepatitis disease diagnosis using a Bayesian theory for better understanding of the theory. In this research, we used a Bayesian theory for detecting hepatitis disease and displaying the result of diagnosis process. Bayesian algorithm theory is rediscovered and perfected by Laplace, the basic idea is using of the known prior probability and conditional probability density parameter, based on Bayes theorem to calculate the corresponding posterior probability, and then obtained the posterior probability to infer and make decisions. Bayesian methods combine existing knowledge, prior probabilities, with additional knowledge derived from new data, the likelihood function. The initial symptoms of hepatitis which include malaise, fever and headache. The probability of hepatitis given the presence of malaise, fever, and headache. The result revealed that a Bayesian theory has successfully identified the existence of hepatitis disease.
Estimating Bayesian Phylogenetic Information Content
Lewis, Paul O.; Chen, Ming-Hui; Kuo, Lynn; Lewis, Louise A.; Fučíková, Karolina; Neupane, Suman; Wang, Yu-Bo; Shi, Daoyuan
2016-01-01
Measuring the phylogenetic information content of data has a long history in systematics. Here we explore a Bayesian approach to information content estimation. The entropy of the posterior distribution compared with the entropy of the prior distribution provides a natural way to measure information content. If the data have no information relevant to ranking tree topologies beyond the information supplied by the prior, the posterior and prior will be identical. Information in data discourages consideration of some hypotheses allowed by the prior, resulting in a posterior distribution that is more concentrated (has lower entropy) than the prior. We focus on measuring information about tree topology using marginal posterior distributions of tree topologies. We show that both the accuracy and the computational efficiency of topological information content estimation improve with use of the conditional clade distribution, which also allows topological information content to be partitioned by clade. We explore two important applications of our method: providing a compelling definition of saturation and detecting conflict among data partitions that can negatively affect analyses of concatenated data. [Bayesian; concatenation; conditional clade distribution; entropy; information; phylogenetics; saturation.] PMID:27155008
Bayesian Models of Individual Differences
Powell, Georgie; Meredith, Zoe; McMillin, Rebecca; Freeman, Tom C. A.
2016-01-01
According to Bayesian models, perception and cognition depend on the optimal combination of noisy incoming evidence with prior knowledge of the world. Individual differences in perception should therefore be jointly determined by a person’s sensitivity to incoming evidence and his or her prior expectations. It has been proposed that individuals with autism have flatter prior distributions than do nonautistic individuals, which suggests that prior variance is linked to the degree of autistic traits in the general population. We tested this idea by studying how perceived speed changes during pursuit eye movement and at low contrast. We found that individual differences in these two motion phenomena were predicted by differences in thresholds and autistic traits when combined in a quantitative Bayesian model. Our findings therefore support the flatter-prior hypothesis and suggest that individual differences in prior expectations are more systematic than previously thought. In order to be revealed, however, individual differences in sensitivity must also be taken into account. PMID:27770059
[Pulmonary nodule: a bayesian approach].
Meert, A-P
2010-01-01
A solitary pulmonary nodule is a common clinical problem. It is usually detected incidentally. The prevalence of solitary pulmonary nodule (SPN) in the lung cancer screening study varies from 8 to 50% (with a prevalence of malignant nodule from 1 to 13%). The bayesian approach can help us to identify promptly malignant nodule in order to treat them surgically and to avoid surgery for benign nodules. Therefore, it is needed to estimate the probability of cancer (Pca) in the SPN. Likelihood ratio (LR) for overall prevalence of malignancy and for different clinical and radiological information (age, smoking exposure, symptoms, cancer history, nodule size, spiculation, calcification, location, growth...) can be obtained from the literature. The odds of cancer-malignancy (odds ca) can be calculated by multiplying all of these LRs together. The Pca = odds ca/1+odds ca. Using this bayeasian approach, the probability of cancer based on an abnormal or normal fluoro-2-deoxy-D-glucose-positron emission tomography (FDG-PET) scan has been estimated. Sensitivity, specificity, positive predictive value and negative predictive value of PET scan are respectively about 90%, 83%, 92% and 90%. Moreover, the LR for malignancy are higher with an abnormal PET scan when compared to most clinical and radiological LRs. Today, the Bayesian approach of SPN must include PET scan.
Bayesian Spectroscopy and Target Tracking
Cunningham, C
2001-05-01
Statistical analysis gives a paradigm for detection and tracking of weak-signature sources that are moving among a network of detectors. The detector platforms compute and exchange information with near-neighbors in the form of Bayesian probabilities for possible sources. This can shown to be an optimal scheme for the use of detector information and communication resources. Here, we apply that paradigm to the detection and discrimination of radiation sources using multi-channel gamma-ray spectra. We present algorithms for the reduction of detector data to probability estimates and the fusion of estimates among multiple detectors. A primary result is the development of a goodness-of-fit metric, similar to {chi}{sup 2}, for template matching that is statistically valid for spectral channels with low expected counts. Discrimination of a target source from other false sources and detection of imprecisely known spectra are the main applications considered. We use simulated NaI spectral data to demonstrate the Bayesian algorithm compare it to other techniques. Results of simulations of a network of spectrometers are presented, showing its capability to distinguish intended targets from nuisance sources.
Facial attractiveness: beauty and the machine.
Eisenthal, Yael; Dror, Gideon; Ruppin, Eytan
2006-01-01
This work presents a novel study of the notion of facial attractiveness in a machine learning context. To this end, we collected human beauty ratings for data sets of facial images and used various techniques for learning the attractiveness of a face. The trained predictor achieves a significant correlation of 0.65 with the average human ratings. The results clearly show that facial beauty is a universal concept that a machine can learn. Analysis of the accuracy of the beauty prediction machine as a function of the size of the training data indicates that a machine producing human-like attractiveness rating could be obtained given a moderately larger data set.
ERIC Educational Resources Information Center
Morton, Stephie
2007-01-01
In this article, the author discusses an art adventure with her third, fourth, and fifth grade enrichment kids to the Fort Collins Museum of Contemporary Art in Colorado. The author demonstrates and teaches her students how to use the art tissue paper and oil pastel complementing the creative spirit of the Jaune Quick-to-See Smith work presented…
Jakribettu, RP; Boloor, R; D’Souza, R; Aithala, S
2014-01-01
Melioidosis is a zoonosis caused by the accidental pathogen Burkholderia pseudomallei, which is endemic in Southeast Asia and northern Australia. The mortality of melioidosis is 20-50% even with treatment. Suppurative lymphadenitis caused by melioidosis has been rarely encountered by clinicians practicing in endemic areas. In the majority of previously described patients, the infected lymph nodes were in the head and neck region, except for four patients who presented with unilateral, inguinal lymphadenitis. Hence, we report a case of unilateral suppurative inguinal lymphadenitis caused by B. pseudomallei in a 48-year-old lady who presented with groin swelling of 2 months duration. PMID:24669344
ERIC Educational Resources Information Center
Holland, George Adam
2006-01-01
This paper considers the possibility of practicums in graduate programs for information management students. The benefits of such practicums are identified and explored and possible drawbacks discussed.
2016-10-01
Ushered in with the rampage of Hurricane Matthew, later days brightened in this month that has often been harbinger of both good and bad news for Cuba and the world. Hurricane Matthew ripped through Eastern Cuba, devastating the historic town of Baracoa (Cuba's first capital, founded in 1511) and the village of Maisí, where the morning sun first rises over Cuban territory. Wind and flood leveled hundreds of homes, brought down the power grid and destroyed crops. Yet there was no loss of human life, unlike in neighboring Haiti and other countries in Matthew's path, and unlike in Cuba in 1963, when Hurricane Flora caused more than 1200 deaths. In Haiti, efforts of health workers-including hundreds of Haitian graduates from Cuba's Latin American Medical School and 600 Cuban health professionals already there-were bolstered by dozens of specially trained Cuban disaster medical personnel in the wake of the storm.
ERIC Educational Resources Information Center
Stuewer, Roger H.
2006-01-01
The capsule histories of physics that students learn in their physics courses stem basically, I believe, from a linear view of history--that physicists in making fundamental discoveries follow a Royal Road to them, as Hermann von Helmholtz put it in 1892. The actual routes they follow, however, are generally nonlinear, and when historians display…
Attracting and retaining nurses in HIV care.
Puplampu, Gideon L; Olson, Karin; Ogilvie, Linda; Mayan, Maria
2014-01-01
Attracting and retaining nurses in HIV care is essential to treatment success, preventing the spread of HIV, slowing its progression, and improving the quality of life of people living with HIV. Despite the wealth of studies examining HIV care, few have focused on the factors that influenced nurses' choices to specialize in HIV care. We examined the factors that attracted and retained eight nurses currently working in HIV care in two large Canadian cities. Participants were primarily women between the ages of 20 and 60 years. Interviews were conducted between November 2010 and September 2011 using interpretive description, a qualitative design. Factors that influenced participants to focus their careers in HIV care included both attracting factors and retaining factors. Although more research is needed, this exploration of attracting and retaining factors may motivate others to specialize in HIV nursing, and thus help to promote adequate support for individuals suffering from the disease.
Electrostatic attraction between overall neutral surfaces.
Adar, Ram M; Andelman, David; Diamant, Haim
2016-08-01
Two overall neutral surfaces with positively and negatively charged domains ("patches") have been shown in recent experiments to exhibit long-range attraction when immersed in an ionic solution. Motivated by the experiments, we calculate analytically the osmotic pressure between such surfaces within the Poisson-Boltzmann framework, using a variational principle for the surface-averaged free energy. The electrostatic potential, calculated beyond the linear Debye-Hückel theory, yields an overall attraction at large intersurface separations, over a wide range of the system's controlled length scales. In particular, the attraction is stronger and occurs at smaller separations for surface patches of larger size and charge density. In this large patch limit, we find that the attraction-repulsion crossover separation is inversely proportional to the square of the patch-charge density and to the Debye screening length.
Young Children's Stereotyping of Facial Attractiveness
ERIC Educational Resources Information Center
Dion, Karen K.
1973-01-01
When shown photographs, young children preferred children with attractive faces as potential friends, and attributed prosocial behaviors to them. They disliked unattractive faces and attributed antisocial behaviors to them. (ST)
Agthe, Maria; Spörrle, Matthias; Maner, Jon K
2011-08-01
Previous studies of organizational decision making demonstrate an abundance of positive biases directed toward highly attractive individuals. The current research, in contrast, suggests that when the person being evaluated is of the same sex as the evaluator, attractiveness hurts, rather than helps. Three experiments assessing evaluations of potential job candidates (Studies 1 and 3) and university applicants (Study 2) demonstrated positive biases toward highly attractive other-sex targets but negative biases toward highly attractive same-sex targets. This pattern was mediated by variability in participants' desire to interact with versus avoid the target individual (Studies 1 and 2) and was moderated by participants' level of self-esteem (Study 3); the derogation of attractive same-sex targets was not observed among people with high self-esteem. Findings demonstrate an important exception to the positive effects of attractiveness in organizational settings and suggest that negative responses to attractive same-sex targets stem from perceptions of self-threat.
Personius, Stephen F.; Crone, Anthony J.; Machette, Michael N.; Mahan, Shannon; Lidke, David J.
2009-01-01
The 86-km-long Surprise Valley normal fault forms part of the active northwestern margin of the Basin and Range province in northeastern California. We use trench mapping and radiocarbon, luminescence, and tephra dating to estimate displacements and timing of the past five surface-rupturing earthquakes on the central part of the fault near Cedarville. A Bayesian OxCal analysis of timing constraints indicates earthquake times of 18.2 ± 2.6, 10.9 ± 3.2, 8.5 ± 0.5, 5.8 ± 1.5, and 1.2 ± 0.1 ka. These data yield recurrence intervals of 7.3 ± 4.1, 2.5 ± 3.2, 2.7 ± 1.6, and 4.5 ± 1.5 ka and an elapsed time of 1.2 ± 0.1 ka since the latest surface-rupturing earthquake. Our best estimate of latest Quaternary vertical slip rate is 0.6 ?? 0.1 mm/a. This late Quaternary rate is remarkably similar to long-term (8-14 Ma) minimum vertical slip rates (>0.4-0.5 ± 0.3 mm/a) calculated from recently acquired seismic reflection and chronologic and structural data in Surprise Valley and the adjacent Warner Mountains. However, our slip rate yields estimates of extension that are lower than recent campaign GPS determinations by factors of 1.5-4 unless the fault has an unusually shallow (30°-35°) dip as suggested by recently acquired seismic reflection data. Coseismic displacements of 2-4.5 ± 1 m documented in the trench and probable rupture lengths of 53-65 km indicate a history of latest Quaternary earthquakes of M 6.8-7.3 on the central part of the. Surprise Valley fault.
Attractive and repulsive magnetic suspension systems overview
NASA Technical Reports Server (NTRS)
Cope, David B.; Fontana, Richard R.
1992-01-01
Magnetic suspension systems can be used in a wide variety of applications. The decision of whether to use an attractive or repulsive suspension system for a particular application is a fundamental one which must be made during the design process. As an aid to the designer, we compare and contrast attractive and repulsive magnetic suspension systems and indicate whether and under what conditions one or the other system is preferred.
Cascaded Bayesian processes: an account of bias in orientation perception.
Langley, Keith; Lefebvre, Veronique; Anderson, Stephen J
2009-10-01
Following adaptation to an oriented (1-d) signal in central vision, the orientation of subsequently viewed test signals may appear repelled away from or attracted towards the adapting orientation. Small angular differences between the adaptor and test yield 'repulsive' shifts, while large angular differences yield 'attractive' shifts. In peripheral vision, however, both small and large angular differences yield repulsive shifts. To account for these tilt after-effects (TAEs), a cascaded model of orientation estimation that is optimized using hierarchical Bayesian methods is proposed. The model accounts for orientation bias through adaptation-induced losses in information that arise because of signal uncertainties and neural constraints placed upon the propagation of visual information. Repulsive (direct) TAEs arise at early stages of visual processing from adaptation of orientation-selective units with peak sensitivity at the orientation of the adaptor (theta). Attractive (indirect) TAEs result from adaptation of second-stage units with peak sensitivity at theta and theta+90 degrees , which arise from an efficient stage of linear compression that pools across the responses of the first-stage orientation-selective units. A spatial orientation vector is estimated from the transformed oriented unit responses. The change from attractive to repulsive TAEs in peripheral vision can be explained by the differing harmonic biases resulting from constraints on signal power (in central vision) versus signal uncertainties in orientation (in peripheral vision). The proposed model is consistent with recent work by computational neuroscientists in supposing that visual bias reflects the adjustment of a rational system in the light of uncertain signals and system constraints.
Netrin1-DCC-Mediated Attraction Guides Post-Crossing Commissural Axons in the Hindbrain
Shoja-Taheri, Farnaz; DeMarco, Arielle
2015-01-01
Commissural axons grow along precise trajectories that are guided by several cues secreted from the ventral midline. After initial attraction to the floor plate using Netrin1 activation of its main attractive receptor, DCC (deleted in colorectal cancer), axons cross the ventral midline, and many turn to grow longitudinally on the contralateral side. After crossing the midline, axons are thought to lose their responsiveness to Netrin1 and become sensitive to midline Slit-Robo repulsion. We aimed to address the in vivo significance of Netrin1 in guiding post-crossing axon trajectories in mouse embryos. Surprisingly, in contrast to the spinal cord, Netrin1 and DCC mutants had abundant commissural axons crossing in the hindbrain. In Netrin1 and DCC mutants, many post-crossing axons made normal turns to grow longitudinally, but projected abnormally at angles away from the midline. In addition, exposure of cultured hindbrain explants to ectopic Netrin1 caused attractive deflection of post-crossing axons. Thus, Netrin1-DCC signaling is not required to attract pre-crossing axons toward the hindbrain floor plate, but is active in post-crossing guidance. Also in contrast with spinal cord, analysis of hindbrain post-crossing axons in Robo1/2 mutant embryos showed that Slit-Robo repulsive signaling was not required for post-crossing trajectories. Our findings show that Netrin1-DCC attractive signaling, but not Slit-Robo repulsive signaling, remains active in hindbrain post-crossing commissural axons to guide longitudinal trajectories, suggesting surprising regional diversity in commissural axon guidance mechanisms. SIGNIFICANCE STATEMENT The left and right sides of the brainstem and spinal cord are connected primarily by axon fibers that grow across the ventral midline, and then away on the other side to their targets. Based on spinal cord, axons are initially attracted by diffusible attractive protein signals to approach and cross the midline, and then are thought to switch
Bayesian Kernel Mixtures for Counts.
Canale, Antonio; Dunson, David B
2011-12-01
Although Bayesian nonparametric mixture models for continuous data are well developed, there is a limited literature on related approaches for count data. A common strategy is to use a mixture of Poissons, which unfortunately is quite restrictive in not accounting for distributions having variance less than the mean. Other approaches include mixing multinomials, which requires finite support, and using a Dirichlet process prior with a Poisson base measure, which does not allow smooth deviations from the Poisson. As a broad class of alternative models, we propose to use nonparametric mixtures of rounded continuous kernels. An efficient Gibbs sampler is developed for posterior computation, and a simulation study is performed to assess performance. Focusing on the rounded Gaussian case, we generalize the modeling framework to account for multivariate count data, joint modeling with continuous and categorical variables, and other complications. The methods are illustrated through applications to a developmental toxicity study and marketing data. This article has supplementary material online.
Bayesian Networks for Social Modeling
Whitney, Paul D.; White, Amanda M.; Walsh, Stephen J.; Dalton, Angela C.; Brothers, Alan J.
2011-03-28
This paper describes a body of work developed over the past five years. The work addresses the use of Bayesian network (BN) models for representing and predicting social/organizational behaviors. The topics covered include model construction, validation, and use. These topics show the bulk of the lifetime of such model, beginning with construction, moving to validation and other aspects of model ‘critiquing’, and finally demonstrating how the modeling approach might be used to inform policy analysis. To conclude, we discuss limitations of using BN for this activity and suggest remedies to address those limitations. The primary benefits of using a well-developed computational, mathematical, and statistical modeling structure, such as BN, are 1) there are significant computational, theoretical and capability bases on which to build 2) ability to empirically critique the model, and potentially evaluate competing models for a social/behavioral phenomena.
Bayesian Inference of Galaxy Morphology
NASA Astrophysics Data System (ADS)
Yoon, Ilsang; Weinberg, M.; Katz, N.
2011-01-01
Reliable inference on galaxy morphology from quantitative analysis of ensemble galaxy images is challenging but essential ingredient in studying galaxy formation and evolution, utilizing current and forthcoming large scale surveys. To put galaxy image decomposition problem in broader context of statistical inference problem and derive a rigorous statistical confidence levels of the inference, I developed a novel galaxy image decomposition tool, GALPHAT (GALaxy PHotometric ATtributes) that exploits recent developments in Bayesian computation to provide full posterior probability distributions and reliable confidence intervals for all parameters. I will highlight the significant improvements in galaxy image decomposition using GALPHAT, over the conventional model fitting algorithms and introduce the GALPHAT potential to infer the statistical distribution of galaxy morphological structures, using ensemble posteriors of galaxy morphological parameters from the entire galaxy population that one studies.
Malaria Mosquitoes Attracted by Fatal Fungus
George, Justin; Jenkins, Nina E.; Blanford, Simon; Thomas, Matthew B.; Baker, Thomas C.
2013-01-01
Insect-killing fungi such as Beauveria bassiana are being evaluated as possible active ingredients for use in novel biopesticides against mosquito vectors that transmit malaria. Fungal pathogens infect through contact and so applications of spores to surfaces such as walls, nets, or other resting sites provide possible routes to infect mosquitoes in and around domestic dwellings. However, some insects can detect and actively avoid fungal spores to reduce infection risk. If true for mosquitoes, such behavior could render the biopesticide approach ineffective. Here we find that the spores of B. bassiana are highly attractive to females of Anopheles stephensi, a major anopheline mosquito vector of human malaria in Asia. We further find that An. stephensi females are preferentially attracted to dead and dying caterpillars infected with B. bassiana, landing on them and subsequently becoming infected with the fungus. Females are also preferentially attracted to cloth sprayed with oil-formulated B. bassiana spores, with 95% of the attracted females becoming infected after a one-minute visit on the cloth. This is the first report of an insect being attracted to a lethal fungal pathogen. The exact mechanisms involved in this behavior remain unclear. Nonetheless, our results indicate that biopesticidal formulations comprising B. bassiana spores will be conducive to attraction and on-source visitation by malaria vectors. PMID:23658757
Ailing Voters Advance Attractive Congressional Candidates
Franklin, Robert G.; Palumbo, Rocco
2015-01-01
Among many benefits of facial attractiveness, there is evidence that more attractive politicians are more likely to be elected. Recent research found this effect to be most pronounced in congressional districts with high disease threat—a result attributed to an adaptive disease avoidance mechanism, whereby the association of low attractiveness with poor health is particularly worrisome to voters who feel vulnerable to disease. We provided a more direct test of this explanation by examining the effects of individuals’ own health and age. Supporting a disease avoidance mechanism, less healthy participants showed a stronger preference for more attractive contenders in U.S. Senate races than their healthier peers, and this effect was stronger for older participants, who were generally less healthy than younger participants. Stronger effects of health for older participants partly reflected the absence of positive bias toward attractive candidates among the healthiest, suggesting that healthy older adults may be unconcerned about disease threat or sufficiently wise to ignore attractiveness. PMID:25562113
Social attraction mediated by fruit flies' microbiome.
Venu, Isvarya; Durisko, Zachary; Xu, Jianping; Dukas, Reuven
2014-04-15
Larval and adult fruit flies are attracted to volatiles emanating from food substrates that have been occupied by larvae. We tested whether such volatiles are emitted by the larval gut bacteria by conducting tests under bacteria-free (axenic) conditions. We also tested attraction to two bacteria species, Lactobacillus brevis, which we cultured from larvae in our lab, and L. plantarum, a common constituent of fruit flies' microbiome in other laboratory populations and in wild fruit flies. Neither larvae nor adults showed attraction to axenic food that had been occupied by axenic larvae, but both showed the previously reported attraction to standard food that had been occupied by larvae with an intact microbiome. Larvae also showed significant attraction to volatiles from axenic food and larvae to which we added only either L. brevis or L. plantarum, and volatiles from L. brevis reared on its optimal growth medium. Controlled learning experiments indicated that larvae experienced with both standard and axenic used food do not perceive either as superior, while focal larvae experienced with simulated used food, which contains burrows, perceive it as superior to unused food. Our results suggest that flies rely on microbiome-derived volatiles for long-distance attraction to suitable food patches. Under natural settings, fruits often contain harmful fungi and bacteria, and both L. brevis and L. plantarum produce compounds that suppress the growth of some antagonistic fungi and bacteria. The larval microbiome volatiles may therefore lead prospective fruit flies towards substrates with a hospitable microbial environment.
Bayesian model selection and isocurvature perturbations
NASA Astrophysics Data System (ADS)
Beltrán, María; García-Bellido, Juan; Lesgourgues, Julien; Liddle, Andrew R.; Slosar, Anže
2005-03-01
Present cosmological data are well explained assuming purely adiabatic perturbations, but an admixture of isocurvature perturbations is also permitted. We use a Bayesian framework to compare the performance of cosmological models including isocurvature modes with the purely adiabatic case; this framework automatically and consistently penalizes models which use more parameters to fit the data. We compute the Bayesian evidence for fits to a data set comprised of WMAP and other microwave anisotropy data, the galaxy power spectrum from 2dFGRS and SDSS, and Type Ia supernovae luminosity distances. We find that Bayesian model selection favors the purely adiabatic models, but so far only at low significance.
Rare earth element content of thermal fluids from Surprise Valley, California
Andrew Fowler
2015-09-23
Rare earth element measurements for thermal fluids from Surprise Valley, California. Samples were collected in acid washed HDPE bottles and acidified with concentrated trace element clean (Fisher Scientific) nitric acid. Samples were pre-concentratated by a factor of approximately 10 using chelating resin with and IDA functional group and measured on magnetic sector ICP-MS. Samples include Seyferth Hot Springs, Surprise Valley Resort Mineral Well, Leonard's Hot Spring, and Lake City Mud Volcano Boiling Spring.
Surprisingly Intense Neutron Emission from a Flare Behind the Limb of the Sun
1998-01-01
Surprisingly Intense Neutron Emission from a Flare Behind the Limb of the Sun R. J. Murphy and G. H. Share E.O. Hulburt Center for Space Research...detectable -ray and neutron emissions occur on the visible disk of the Sun . While it is generally believed that particle acceleration in ares takes...Surprisingly Intense Neutron Emission from a Flare Behind the Limb of the Sun 5a. CONTRACT NUMBER 5b. GRANT NUMBER 5c. PROGRAM ELEMENT NUMBER 6
BACTERIAL ATTRACTION AND QUORUM SENSING INHIBITION IN CAENORHABDITIS ELEGANS EXUDATES
KAPLAN, FATMA; BADRI, DAYAKAR V.; ZACHARIAH, CHERIAN; AJREDINI, RAMADAN; SANDOVAL, FRANCISCO J; ROJE, SANJA; LEVINE, LANFANG H.; ZHANG, FENGLI; ROBINETTE, STEVEN L.; ALBORN, HANS T.; ZHAO, WEI; STADLER, MICHAEL; NIMALENDRAN, RATHIKA; DOSSEY, AARON T.; BRÜSCHWEILER, RAFAEL; VIVANCO, JORGE M.; EDISON, ARTHUR S.
2014-01-01
Caenorhabditis elegans, a bacterivorous nematode, lives in complex rotting fruit, soil, and compost environments, and chemical interactions are required for mating, monitoring population density, recognition of food, avoidance of pathogenic microbes, and other essential ecological functions. Despite being one of the best-studied model organisms in biology, relatively little is known about the signals that C. elegans uses to chemically interact with its environment or as defense. C. elegans exudates were analyzed using several analytical methods and found to contain 36 common metabolites including organic acids, amino acids and sugars, all in relatively high abundance. Furthermore, the concentrations of amino acids in the exudates were dependent on developmental stage. The C. elegans exudates were tested for bacterial chemotaxis using Pseudomonas putida (KT2440), a plant growth promoting rhizobacterium, Pseudomonas aeruginosa (PAO1), a soil bacterium pathogenic to C. elegans, and E. coli (OP50), a non-motile bacterium tested as a control. The C. elegans exudates attracted the two Psuedomonas species, but had no detectable antibacterial activity against P. aeruginosa. To our surprise, the exudates of young adult and adult life stages of C. elegans exudates inhibited quorum sensing in the reporter system based on the LuxR bacterial quorum sensing (QS) system, which regulates bacterial virulence and other factors in Vibrio fischeri. We were able to fractionate the QS inhibition and bacterial chemotaxis activities, demonstrating that these activities are chemically distinct. Our results demonstrate that C. elegans can attract its bacterial food and has the potential of partially regulating the virulence of bacterial pathogens by inhibiting specific QS systems. PMID:19649780
Unconscious processing of facial attractiveness: invisible attractive faces orient visual attention.
Hung, Shao-Min; Nieh, Chih-Hsuan; Hsieh, Po-Jang
2016-11-16
Past research has proven human's extraordinary ability to extract information from a face in the blink of an eye, including its emotion, gaze direction, and attractiveness. However, it remains elusive whether facial attractiveness can be processed and influences our behaviors in the complete absence of conscious awareness. Here we demonstrate unconscious processing of facial attractiveness with three distinct approaches. In Experiment 1, the time taken for faces to break interocular suppression was measured. The results showed that attractive faces enjoyed the privilege of breaking suppression and reaching consciousness earlier. In Experiment 2, we further showed that attractive faces had lower visibility thresholds, again suggesting that facial attractiveness could be processed more easily to reach consciousness. Crucially, in Experiment 3, a significant decrease of accuracy on an orientation discrimination task subsequent to an invisible attractive face showed that attractive faces, albeit suppressed and invisible, still exerted an effect by orienting attention. Taken together, for the first time, we show that facial attractiveness can be processed in the complete absence of consciousness, and an unconscious attractive face is still capable of directing our attention.
Unconscious processing of facial attractiveness: invisible attractive faces orient visual attention
Hung, Shao-Min; Nieh, Chih-Hsuan; Hsieh, Po-Jang
2016-01-01
Past research has proven human’s extraordinary ability to extract information from a face in the blink of an eye, including its emotion, gaze direction, and attractiveness. However, it remains elusive whether facial attractiveness can be processed and influences our behaviors in the complete absence of conscious awareness. Here we demonstrate unconscious processing of facial attractiveness with three distinct approaches. In Experiment 1, the time taken for faces to break interocular suppression was measured. The results showed that attractive faces enjoyed the privilege of breaking suppression and reaching consciousness earlier. In Experiment 2, we further showed that attractive faces had lower visibility thresholds, again suggesting that facial attractiveness could be processed more easily to reach consciousness. Crucially, in Experiment 3, a significant decrease of accuracy on an orientation discrimination task subsequent to an invisible attractive face showed that attractive faces, albeit suppressed and invisible, still exerted an effect by orienting attention. Taken together, for the first time, we show that facial attractiveness can be processed in the complete absence of consciousness, and an unconscious attractive face is still capable of directing our attention. PMID:27848992
Photogrammetric Analysis of Attractiveness in Indian Faces
Duggal, Shveta; Kapoor, DN; Verma, Santosh; Sagar, Mahesh; Lee, Yung-Seop; Moon, Hyoungjin
2016-01-01
Background The objective of this study was to assess the attractive facial features of the Indian population. We tried to evaluate subjective ratings of facial attractiveness and identify which facial aesthetic subunits were important for facial attractiveness. Methods A cross-sectional study was conducted of 150 samples (referred to as candidates). Frontal photographs were analyzed. An orthodontist, a prosthodontist, an oral surgeon, a dentist, an artist, a photographer and two laymen (estimators) subjectively evaluated candidates' faces using visual analog scale (VAS) scores. As an objective method for facial analysis, we used balanced angular proportional analysis (BAPA). Using SAS 10.1 (SAS Institute Inc.), the Turkey's studentized range test and Pearson correlation analysis were performed to detect between-group differences in VAS scores (Experiment 1), to identify correlations between VAS scores and BAPA scores (Experiment 2), and to analyze the characteristic features of facial attractiveness and gender differences (Experiment 3); the significance level was set at P=0.05. Results Experiment 1 revealed some differences in VAS scores according to professional characteristics. In Experiment 2, BAPA scores were found to behave similarly to subjective ratings of facial beauty, but showed a relatively weak correlation coefficient with the VAS scores. Experiment 3 found that the decisive factors for facial attractiveness were different for men and women. Composite images of attractive Indian male and female faces were constructed. Conclusions Our photogrammetric study, statistical analysis, and average composite faces of an Indian population provide valuable information about subjective perceptions of facial beauty and attractive facial structures in the Indian population. PMID:27019809
Detecting Exoplanets using Bayesian Object Detection
NASA Astrophysics Data System (ADS)
Feroz, Farhan
2015-08-01
Detecting objects from noisy data-sets is common practice in astrophysics. Object detection presents a particular challenge in terms of statistical inference, not only because of its multi-modal nature but also because it combines both the parameter estimation (for characterizing objects) and model selection problems (in order to quantify the detection). Bayesian inference provides a mathematically rigorous solution to this problem by calculating marginal posterior probabilities of models with different number of sources, but the use of this method in astrophysics has been hampered by the computational cost of evaluating the Bayesian evidence. Nonetheless, Bayesian model selection has the potential to improve the interpretation of existing observational data. I will discuss several Bayesian approaches to object detection problems, both in terms of their theoretical framework and also the practical details about carrying out the computation. I will also describe some recent applications of these methods in the detection of exoplanets.
Bayesian Comparison of Two Regression Lines.
ERIC Educational Resources Information Center
Tsutakawa, Robert K.
1978-01-01
A Bayesian solution is presented for the Johnson-Neyman problem (whether or not the distance between two regression lines is statistically significant over a finite interval of the independent variable). (Author/CTM)
The Bayesian boom: good thing or bad?
Hahn, Ulrike
2014-01-01
A series of high-profile critiques of Bayesian models of cognition have recently sparked controversy. These critiques question the contribution of rational, normative considerations in the study of cognition. The present article takes central claims from these critiques and evaluates them in light of specific models. Closer consideration of actual examples of Bayesian treatments of different cognitive phenomena allows one to defuse these critiques showing that they cannot be sustained across the diversity of applications of the Bayesian framework for cognitive modeling. More generally, there is nothing in the Bayesian framework that would inherently give rise to the deficits that these critiques perceive, suggesting they have been framed at the wrong level of generality. At the same time, the examples are used to demonstrate the different ways in which consideration of rationality uniquely benefits both theory and practice in the study of cognition. PMID:25152738
Penis size interacts with body shape and height to influence male attractiveness.
Mautz, Brian S; Wong, Bob B M; Peters, Richard A; Jennions, Michael D
2013-04-23
Compelling evidence from many animal taxa indicates that male genitalia are often under postcopulatory sexual selection for characteristics that increase a male's relative fertilization success. There could, however, also be direct precopulatory female mate choice based on male genital traits. Before clothing, the nonretractable human penis would have been conspicuous to potential mates. This observation has generated suggestions that human penis size partly evolved because of female choice. Here we show, based upon female assessment of digitally projected life-size, computer-generated images, that penis size interacts with body shape and height to determine male sexual attractiveness. Positive linear selection was detected for penis size, but the marginal increase in attractiveness eventually declined with greater penis size (i.e., quadratic selection). Penis size had a stronger effect on attractiveness in taller men than in shorter men. There was a similar increase in the positive effect of penis size on attractiveness with a more masculine body shape (i.e., greater shoulder-to-hip ratio). Surprisingly, larger penis size and greater height had almost equivalent positive effects on male attractiveness. Our results support the hypothesis that female mate choice could have driven the evolution of larger penises in humans. More broadly, our results show that precopulatory sexual selection can play a role in the evolution of genital traits.
Learning genetic epistasis using Bayesian network scoring criteria
2011-01-01
Background Gene-gene epistatic interactions likely play an important role in the genetic basis of many common diseases. Recently, machine-learning and data mining methods have been developed for learning epistatic relationships from data. A well-known combinatorial method that has been successfully applied for detecting epistasis is Multifactor Dimensionality Reduction (MDR). Jiang et al. created a combinatorial epistasis learning method called BNMBL to learn Bayesian network (BN) epistatic models. They compared BNMBL to MDR using simulated data sets. Each of these data sets was generated from a model that associates two SNPs with a disease and includes 18 unrelated SNPs. For each data set, BNMBL and MDR were used to score all 2-SNP models, and BNMBL learned significantly more correct models. In real data sets, we ordinarily do not know the number of SNPs that influence phenotype. BNMBL may not perform as well if we also scored models containing more than two SNPs. Furthermore, a number of other BN scoring criteria have been developed. They may detect epistatic interactions even better than BNMBL. Although BNs are a promising tool for learning epistatic relationships from data, we cannot confidently use them in this domain until we determine which scoring criteria work best or even well when we try learning the correct model without knowledge of the number of SNPs in that model. Results We evaluated the performance of 22 BN scoring criteria using 28,000 simulated data sets and a real Alzheimer's GWAS data set. Our results were surprising in that the Bayesian scoring criterion with large values of a hyperparameter called α performed best. This score performed better than other BN scoring criteria and MDR at recall using simulated data sets, at detecting the hardest-to-detect models using simulated data sets, and at substantiating previous results using the real Alzheimer's data set. Conclusions We conclude that representing epistatic interactions using BN models
Schneider, Jutta M.
2016-01-01
Background. In many insects and spider species, females attract males with volatile sex pheromones, but we know surprisingly little about the costs and benefits of female pheromone emission. Here, we test the hypothesis that mate attraction by females is dynamic and strategic in the sense that investment in mate attraction is matched to the needs of the female. We use the orb-web spider Argiope bruennichi in which females risk the production of unfertilised egg clutches if they do not receive a copulation within a certain time-frame. Methods. We designed field experiments to compare mate attraction by recently matured (young) females with females close to oviposition (old). In addition, we experimentally separated the potential sources of pheromone transmission, namely the female body and the web silk. Results. In accordance with the hypothesis of strategic pheromone production, the probability of mate attraction and the number of males attracted differed between age classes. While the bodies and webs of young females were hardly found by males, the majority of old females attracted up to two males within two hours. Old females not only increased pheromone emission from their bodies but also from their webs. Capture webs alone spun by old females were significantly more efficient in attracting males than webs of younger females. Discussion. Our results suggest that females modulate their investment in signalling according to the risk of remaining unmated and that they thereby economize on the costs associated with pheromone production and emission. PMID:27114864
Cory, Anna-Lena; Schneider, Jutta M
2016-01-01
Background. In many insects and spider species, females attract males with volatile sex pheromones, but we know surprisingly little about the costs and benefits of female pheromone emission. Here, we test the hypothesis that mate attraction by females is dynamic and strategic in the sense that investment in mate attraction is matched to the needs of the female. We use the orb-web spider Argiope bruennichi in which females risk the production of unfertilised egg clutches if they do not receive a copulation within a certain time-frame. Methods. We designed field experiments to compare mate attraction by recently matured (young) females with females close to oviposition (old). In addition, we experimentally separated the potential sources of pheromone transmission, namely the female body and the web silk. Results. In accordance with the hypothesis of strategic pheromone production, the probability of mate attraction and the number of males attracted differed between age classes. While the bodies and webs of young females were hardly found by males, the majority of old females attracted up to two males within two hours. Old females not only increased pheromone emission from their bodies but also from their webs. Capture webs alone spun by old females were significantly more efficient in attracting males than webs of younger females. Discussion. Our results suggest that females modulate their investment in signalling according to the risk of remaining unmated and that they thereby economize on the costs associated with pheromone production and emission.
Optimal online learning: a Bayesian approach
NASA Astrophysics Data System (ADS)
Solla, Sara A.; Winther, Ole
1999-09-01
A recently proposed Bayesian approach to online learning is applied to learning a rule defined as a noisy single layer perceptron. In the Bayesian online approach, the exact posterior distribution is approximated by a simple parametric posterior that is updated online as new examples are incorporated to the dataset. In the case of binary weights, the approximate posterior is chosen to be a biased binary distribution. The resulting online algorithm is shown to outperform several other online approaches to this problem.
ProFit: Bayesian galaxy fitting tool
NASA Astrophysics Data System (ADS)
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.
Variational Bayesian Approximation methods for inverse problems
NASA Astrophysics Data System (ADS)
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.
Chemical visualization of an attractant peptide, LURE.
Goto, Hiroaki; Okuda, Satohiro; Mizukami, Akane; Mori, Hitoshi; Sasaki, Narie; Kurihara, Daisuke; Higashiyama, Tetsuya
2011-01-01
The pollen tube attractant peptide LUREs of Torenia fournieri are diffusible peptides that attract pollen tubes in vitro. Here, we report a method enabling the direct visualization of a LURE peptide without inhibiting its attraction activity by conjugating it with the Alexa Fluor 488 fluorescent dye. After purifying and refolding the recombinant LURE2 with a polyhistidine tag, its amino groups were targeted for conjugation with the Alexa Fluor dye. Labeling of LURE2 was confirmed by its fluorescence and mass spectrometry. In our in vitro assay using gelatin beads, Alexa Fluor 488-labeled LURE2 appeared to have the same activity as unlabeled LURE2. Using the labeled LURE2, the relationship between the spatiotemporal change of distribution and activity of LURE2 was examined. LURE2 attracted pollen tubes when embedded in gelatin beads, but hardly at all when in agarose beads. Direct visualization suggested that the significant difference between these conditions was the retention of LURE2 in the gelatin bead, which might delay diffusion of LURE2 from the bead. Direct visualization of LURE peptide may open the way to studying the spatiotemporal dynamics of LURE in pollen tube attraction.
Human body odour, symmetry and attractiveness.
Rikowski, A; Grammer, K
1999-05-07
Several studies have found body and facial symmetry as well as attractiveness to be human mate choice criteria. These characteristics are presumed to signal developmental stability. Human body odour has been shown to influence female mate choice depending on the immune system, but the question of whether smell could signal general mate quality, as do other cues, was not addressed in previous studies. We compared ratings of body odour, attractiveness, and measurements of facial and body asymmetry of 16 male and 19 female subjects. Subjects wore a T-shirt for three consecutive nights under controlled conditions. Opposite-sex raters judged the odour of the T-shirts and another group evaluated portraits of the subjects for attractiveness. We measured seven bilateral traits of the subject's body to assess body asymmetry. Facial asymmetry was examined by distance measurements of portrait photographs. The results showed a significant positive correlation between facial attractiveness and sexiness of body odour for female subjects. We found positive relationships between body odour and attractiveness and negative ones between smell and body asymmetry for males only if female odour raters were in the most fertile phase of their menstrual cycle. The outcomes are discussed in the light of different male and female reproductive strategies.
Dissociable effects of surprise and model update in parietal and anterior cingulate cortex
O’Reilly, Jill X.; Schüffelgen, Urs; Cuell, Steven F.; Behrens, Timothy E. J.; Mars, Rogier B.; Rushworth, Matthew F. S.
2013-01-01
Brains use predictive models to facilitate the processing of expected stimuli or planned actions. Under a predictive model, surprising (low probability) stimuli or actions necessitate the immediate reallocation of processing resources, but they can also signal the need to update the underlying predictive model to reflect changes in the environment. Surprise and updating are often correlated in experimental paradigms but are, in fact, distinct constructs that can be formally defined as the Shannon information (IS) and Kullback–Leibler divergence (DKL) associated with an observation. In a saccadic planning task, we observed that distinct behaviors and brain regions are associated with surprise/IS and updating/DKL. Although surprise/IS was associated with behavioral reprogramming as indexed by slower reaction times, as well as with activity in the posterior parietal cortex [human lateral intraparietal area (LIP)], the anterior cingulate cortex (ACC) was specifically activated during updating of the predictive model (DKL). A second saccade-sensitive region in the inferior posterior parietal cortex (human 7a), which has connections to both LIP and ACC, was activated by surprise and modulated by updating. Pupillometry revealed a further dissociation between surprise and updating with an early positive effect of surprise and late negative effect of updating on pupil area. These results give a computational account of the roles of the ACC and two parietal saccade regions, LIP and 7a, by which their involvement in diverse tasks can be understood mechanistically. The dissociation of functional roles between regions within the reorienting/reprogramming network may also inform models of neurological phenomena, such as extinction and Balint syndrome, and neglect. PMID:23986499
Prior probabilities modulate cortical surprise responses: A study of event-related potentials.
Seer, Caroline; Lange, Florian; Boos, Moritz; Dengler, Reinhard; Kopp, Bruno
2016-07-01
The human brain predicts events in its environment based on expectations, and unexpected events are surprising. When probabilistic contingencies in the environment are precisely instructed, the individual can form expectations based on quantitative probabilistic information ('inference-based learning'). In contrast, when probabilistic contingencies are imprecisely instructed, expectations are formed based on the individual's cumulative experience ('experience-based learning'). Here, we used the urn-ball paradigm to investigate how variations in prior probabilities and in the precision of information about these priors modulate choice behavior and event-related potential (ERP) correlates of surprise. In the urn-ball paradigm, participants are repeatedly forced to infer hidden states responsible for generating observable events, given small samples of factual observations. We manipulated prior probabilities of the states, and we rendered the priors calculable or incalculable, respectively. The analysis of choice behavior revealed that the tendency to consider prior probabilities when making decisions about hidden states was stronger when prior probabilities were calculable, at least in some of our participants. Surprise-related P3b amplitudes were observed in both the calculable and the incalculable prior probability condition. In contrast, calculability of prior probabilities modulated anteriorly distributed ERP amplitudes: when prior probabilities were calculable, surprising events elicited enhanced P3a amplitudes. However, when prior probabilities were incalculable, surprise was associated with enhanced N2 amplitudes. Furthermore, interindividual variability in reliance on prior probabilities was associated with attenuated P3b surprise responses under calculable in comparison to incalculable prior probabilities. Our results suggest two distinct neural systems for probabilistic learning that are recruited depending on contextual cues such as the precision of
Philosophy and the practice of Bayesian statistics
Gelman, Andrew; Shalizi, Cosma Rohilla
2015-01-01
A substantial school in the philosophy of science identifies Bayesian inference with inductive inference and even rationality as such, and seems to be strengthened by the rise and practical success of Bayesian statistics. We argue that the most successful forms of Bayesian statistics do not actually support that particular philosophy but rather accord much better with sophisticated forms of hypothetico-deductivism. We examine the actual role played by prior distributions in Bayesian models, and the crucial aspects of model checking and model revision, which fall outside the scope of Bayesian confirmation theory. We draw on the literature on the consistency of Bayesian updating and also on our experience of applied work in social science. Clarity about these matters should benefit not just philosophy of science, but also statistical practice. At best, the inductivist view has encouraged researchers to fit and compare models without checking them; at worst, theorists have actively discouraged practitioners from performing model checking because it does not fit into their framework. PMID:22364575
Philosophy and the practice of Bayesian statistics.
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.
Self-attracting walk on heterogeneous networks.
Kim, Kanghun; Kyoung, Jaegu; Lee, D-S
2016-05-01
Understanding human mobility in cyberspace becomes increasingly important in this information era. While human mobility, memory-dependent and subdiffusive, is well understood in Euclidean space, it remains elusive in random heterogeneous networks like the World Wide Web. Here we study the diffusion characteristics of self-attracting walks, in which a walker is more likely to move to the locations visited previously than to unvisited ones, on scale-free networks. Under strong attraction, the number of distinct visited nodes grows linearly in time with larger coefficients in more heterogeneous networks. More interestingly, crossovers to sublinear growths occur in strongly heterogeneous networks. To understand these phenomena, we investigate the characteristic volumes and topology of the cluster of visited nodes and find that the reinforced attraction to hubs results in expediting exploration first but delaying later, as characterized by the scaling exponents that we derive. Our findings and analysis method can be useful for understanding various diffusion processes mediated by human.
Pollen tube guidance by attractant molecules: LUREs.
Okuda, Satohiro; Higashiyama, Tetsuya
2010-01-01
Sexual reproduction in flowering plants requires pollen-tube guidance, which is thought to be mediated by chemoattractants derived from target ovules. To date, however, no convincing evidence has been reported of a particular molecule being the true attractant. Emerging data indicate that two synergid cells, which are on either side of the egg cell, emit a diffusible, species-specific signal to attract the pollen tube at the last step of pollen-tube guidance. Recently, it was demonstrated that LUREs (LURE1 and LURE2), cysteine-rich polypeptides secreted from the synergid cell, are the key molecules in pollen-tube guidance. In this review, we summarize the mechanism of pollen-tube guidance, with special focus on gametophytic guidance and the attractants.
Self-attracting walk on heterogeneous networks
NASA Astrophysics Data System (ADS)
Kim, Kanghun; Kyoung, Jaegu; Lee, D.-S.
2016-05-01
Understanding human mobility in cyberspace becomes increasingly important in this information era. While human mobility, memory-dependent and subdiffusive, is well understood in Euclidean space, it remains elusive in random heterogeneous networks like the World Wide Web. Here we study the diffusion characteristics of self-attracting walks, in which a walker is more likely to move to the locations visited previously than to unvisited ones, on scale-free networks. Under strong attraction, the number of distinct visited nodes grows linearly in time with larger coefficients in more heterogeneous networks. More interestingly, crossovers to sublinear growths occur in strongly heterogeneous networks. To understand these phenomena, we investigate the characteristic volumes and topology of the cluster of visited nodes and find that the reinforced attraction to hubs results in expediting exploration first but delaying later, as characterized by the scaling exponents that we derive. Our findings and analysis method can be useful for understanding various diffusion processes mediated by human.
Messages about physical attractiveness in animated cartoons.
Klein, Hugh; Shiffman, Kenneth S
2006-12-01
Relying upon a content analysis of one specific type of medium to which young people are exposed beginning at an early age, on a regular basis, and for many years (i.e., animated cartoons), the present study examines what types of messages are provided about being physically unattractive, physically attractive, and ordinary-looking. This research concerns itself with identifying the characteristics that tend to be associated with being good-looking or unattractive, and then discussing the implications of the findings. Results indicate that many variables were found to differ based on cartoon characters' physical attractiveness, including gender, age, intelligence, body weight, emotional states experienced, prosocial behaviors, antisocial behaviors, and overall goodness/badness. Whenever differences were found, the overriding tendency was for cartoons to provide positive messages about being attractive and negative messages about being unattractive.
Shukla-Eliasson attractive force: Revisited
NASA Astrophysics Data System (ADS)
Akbari-Moghanjoughi, M.; Akbari-Moghanjoughi
2013-04-01
By investigating the dielectric response of the Fermi-Dirac plasma in the linear limit and evaluating the electrostatic potential around the positive stationary test charge, we find that the Shukla-Eliasson attractive force is present for the plasma density range expected in the interiors of large planets for a wide range of plasma atomic number. This research, which is based on the generalized electron Fermi-momentum, further confirms the existence of the newly discovered Lennard-Jones-like attractive potential and its inevitable role in plasma crystallization in the cores of planets. Moreover, it is observed that the characteristics of the attractive potential are strongly sensitive to the variation of plasma density and composition. Current research can also have applications in the study of strong laser-matter interactions and inertially confined plasmas.
Attraction between like-charged monovalent ions.
Zangi, Ronen
2012-05-14
Ions with like-charges repel each other with a magnitude given by the Coulomb law. The repulsion is also known to persist in aqueous solutions albeit factored by the medium's dielectric constant. In this paper, we report results from molecular dynamics simulations of alkali halides salt solutions indicating an effective attraction between some of the like-charged monovalent ions. The attraction is observed between anions, as well as between cations, leading to the formation of dimers with lifetimes on the order of few picoseconds. Two mechanisms have been identified to drive this counterintuitive attraction. The first is exhibited by high-charge density ions, such as fluoride, at low salt concentrations, yielding effective attractions with magnitude up to the order of 1-2 kT. In this case, the stronger local electric field generated when the two ions are in contact augments the alignment of neighboring waters toward the ions. This results in a gain of substantial favorable ion-water interaction energy. For fluorides, this interaction constitutes the major change among the different energy components compensating for the anion-anion repulsion, and therefore, rendering like-charge association possible. The second mechanism involves mediation by counterions, the attractions increase with salt concentration and are characterized by small magnitudes. In particular, clusters of ion triplets, in which a counterion is either bridging the two like-charged ions or is paired to only one of them, are formed. Although these two mechanisms may not yield net attractions in many cases, they might still be operational and significant, explaining effective repulsions between like-charged ions with magnitudes much smaller than expected based on continuum electrostatics.
Szymkowiak, Jakub; Kuczyński, Lechosław
2015-01-01
Songbirds that follow a conspecific attraction strategy in the habitat selection process prefer to settle in habitat patches already occupied by other individuals. This largely affects the patterns of their spatio-temporal distribution and leads to clustered breeding. Although making informed settlement decisions is expected to be beneficial for individuals, such territory clusters may potentially provide additional fitness benefits (e.g., through the dilution effect) or costs (e.g., possibly facilitating nest localization if predators respond functionally to prey distribution). Thus, we hypothesized that the fitness consequences of following a conspecific attraction strategy may largely depend on the composition of the predator community. We developed an agent-based model in which we simulated the settling behavior of birds that use a conspecific attraction strategy and breed in a multi-predator landscape with predators that exhibited different foraging strategies. Moreover, we investigated whether Bayesian updating of prior settlement decisions according to the perceived predation risk may improve the fitness of birds that rely on conspecific cues. Our results provide evidence that the fitness consequences of conspecific attraction are predation-related. We found that in landscapes dominated by predators able to respond functionally to prey distribution, clustered breeding led to fitness costs. However, this cost could be reduced if birds performed Bayesian updating of prior settlement decisions and perceived nesting with too many neighbors as a threat. Our results did not support the hypothesis that in landscapes dominated by incidental predators, clustered breeding as a byproduct of conspecific attraction provides fitness benefits through the dilution effect. We suggest that this may be due to the spatial scale of songbirds' aggregative behavior. In general, we provide evidence that when considering the fitness consequences of conspecific attraction for
Nessler, Bernhard; Pfeiffer, Michael; Buesing, Lars; Maass, Wolfgang
2013-01-01
The principles by which networks of neurons compute, and how spike-timing dependent plasticity (STDP) of synaptic weights generates and maintains their computational function, are unknown. Preceding work has shown that soft winner-take-all (WTA) circuits, where pyramidal neurons inhibit each other via interneurons, are a common motif of cortical microcircuits. We show through theoretical analysis and computer simulations that Bayesian computation is induced in these network motifs through STDP in combination with activity-dependent changes in the excitability of neurons. The fundamental components of this emergent Bayesian computation are priors that result from adaptation of neuronal excitability and implicit generative models for hidden causes that are created in the synaptic weights through STDP. In fact, a surprising result is that STDP is able to approximate a powerful principle for fitting such implicit generative models to high-dimensional spike inputs: Expectation Maximization. Our results suggest that the experimentally observed spontaneous activity and trial-to-trial variability of cortical neurons are essential features of their information processing capability, since their functional role is to represent probability distributions rather than static neural codes. Furthermore it suggests networks of Bayesian computation modules as a new model for distributed information processing in the cortex. PMID:23633941
Multi-static passive SAR imaging based on Bayesian compressive sensing
NASA Astrophysics Data System (ADS)
Wu, Qisong; Zhang, Yimin D.; Amin, Moeness G.; Himed, Braham
2014-05-01
Passive radar systems, which utilize broadcast and navigation signals as sources of opportunity, have attracted significant interests in recent years due to their low cost, covertness, and the availability of different illuminator sources. In this paper, we propose a novel method for synthetic aperture imaging in multi-static passive radar systems based on a group sparse Bayesian learning technique. In particular, the problem of imaging sparse targets is formulated as a group sparse signal reconstruction problem, which is solved using a complex multi- task Bayesian compressive sensing (CMT-BCS) method to achieve a high resolution. The proposed approach significantly improves the imaging resolution beyond the range resolution. Compared to the other group sparse signal reconstruction methods, such as the block orthogonal matching pursuit (BOMP) and group Lasso, the CMT-BCS provides significant performance improvement for the reconstruction of sparse targets in the redundant dictionary with high coherence. Simulations results demonstrate the superior performance of the proposed approach.
Lane formation in a driven attractive fluid
NASA Astrophysics Data System (ADS)
Wächtler, C. W.; Kogler, F.; Klapp, S. H. L.
2016-11-01
We investigate nonequilibrium lane formation in a generic model of a fluid with attractive interactions, that is, a two-dimensional Lennard-Jones fluid composed of two particle species driven in opposite directions. Performing Brownian dynamics simulations for a wide range of parameters, supplemented by a stability analysis based on dynamical density functional theory, we identify generic features of lane formation in the presence of attraction, including structural properties. In fact, we find a variety of states (as compared to purely repulsive systems), as well as a close relation between laning and long-wavelength instabilities of the homogeneous phase such as demixing and condensation.
Glassy states in attractive micellar systems
NASA Astrophysics Data System (ADS)
Mallamace, F.; Broccio, M.; Faraone, A.; Chen, W. R.; Chen, S.-H.
2004-08-01
Recent mode coupling theory (MCT) calculations show that in attractive colloids one may observe a new type of glass originating from clustering effects, as a result of the attractive interaction. This happens in addition to the known glass-forming mechanism due to cage effects in the hard sphere system. MCT also indicates that, within a certain volume fraction range, varying the external control parameter, the effective temperature, makes the glass-to-liquid-to-glass re-entrance and the glass-to-glass transitions possible. Here we present experimental evidence and details on this complex phase behavior in a three-block copolymer micellar system.
Lane formation in a driven attractive fluid.
Wächtler, C W; Kogler, F; Klapp, S H L
2016-11-01
We investigate nonequilibrium lane formation in a generic model of a fluid with attractive interactions, that is, a two-dimensional Lennard-Jones fluid composed of two particle species driven in opposite directions. Performing Brownian dynamics simulations for a wide range of parameters, supplemented by a stability analysis based on dynamical density functional theory, we identify generic features of lane formation in the presence of attraction, including structural properties. In fact, we find a variety of states (as compared to purely repulsive systems), as well as a close relation between laning and long-wavelength instabilities of the homogeneous phase such as demixing and condensation.
Pupil dilation signals uncertainty and surprise in a learning gambling task
Lavín, Claudio; San Martín, René; Rosales Jubal, Eduardo
2014-01-01
Pupil dilation under constant illumination is a physiological marker where modulation is related to several cognitive functions involved in daily decision making. There is evidence for a role of pupil dilation change during decision-making tasks associated with uncertainty, reward-prediction errors and surprise. However, while some work suggests that pupil dilation is mainly modulated by reward predictions, others point out that this marker is related to uncertainty signaling and surprise. Supporting the latter hypothesis, the neural substrate of this marker is related to noradrenaline (NA) activity which has been also related to uncertainty signaling. In this work we aimed to test whether pupil dilation is a marker for uncertainty and surprise in a learning task. We recorded pupil dilation responses in 10 participants performing the Iowa Gambling Task (IGT), a decision-making task that requires learning and constant monitoring of outcomes’ feedback, which are important variables within the traditional study of human decision making. Results showed that pupil dilation changes were modulated by learned uncertainty and surprise regardless of feedback magnitudes. Interestingly, greater pupil dilation changes were found during positive feedback (PF) presentation when there was lower uncertainty about a future negative feedback (NF); and by surprise during NF presentation. These results support the hypothesis that pupil dilation is a marker of learned uncertainty, and may be used as a marker of NA activity facing unfamiliar situations in humans. PMID:24427126
Pupil dilation signals uncertainty and surprise in a learning gambling task.
Lavín, Claudio; San Martín, René; Rosales Jubal, Eduardo
2013-01-01
Pupil dilation under constant illumination is a physiological marker where modulation is related to several cognitive functions involved in daily decision making. There is evidence for a role of pupil dilation change during decision-making tasks associated with uncertainty, reward-prediction errors and surprise. However, while some work suggests that pupil dilation is mainly modulated by reward predictions, others point out that this marker is related to uncertainty signaling and surprise. Supporting the latter hypothesis, the neural substrate of this marker is related to noradrenaline (NA) activity which has been also related to uncertainty signaling. In this work we aimed to test whether pupil dilation is a marker for uncertainty and surprise in a learning task. We recorded pupil dilation responses in 10 participants performing the Iowa Gambling Task (IGT), a decision-making task that requires learning and constant monitoring of outcomes' feedback, which are important variables within the traditional study of human decision making. Results showed that pupil dilation changes were modulated by learned uncertainty and surprise regardless of feedback magnitudes. Interestingly, greater pupil dilation changes were found during positive feedback (PF) presentation when there was lower uncertainty about a future negative feedback (NF); and by surprise during NF presentation. These results support the hypothesis that pupil dilation is a marker of learned uncertainty, and may be used as a marker of NA activity facing unfamiliar situations in humans.
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. PMID:26902889
Facial Features: What Women Perceive as Attractive and What Men Consider Attractive
Muñoz-Reyes, José Antonio; Iglesias-Julios, Marta; Pita, Miguel; Turiegano, Enrique
2015-01-01
Attractiveness plays an important role in social exchange and in the ability to attract potential mates, especially for women. Several facial traits have been described as reliable indicators of attractiveness in women, but very few studies consider the influence of several measurements simultaneously. In addition, most studies consider just one of two assessments to directly measure attractiveness: either self-evaluation or men's ratings. We explored the relationship between these two estimators of attractiveness and a set of facial traits in a sample of 266 young Spanish women. These traits are: facial fluctuating asymmetry, facial averageness, facial sexual dimorphism, and facial maturity. We made use of the advantage of having recently developed methodologies that enabled us to measure these variables in real faces. We also controlled for three other widely used variables: age, body mass index and waist-to-hip ratio. The inclusion of many different variables allowed us to detect any possible interaction between the features described that could affect attractiveness perception. Our results show that facial fluctuating asymmetry is related both to self-perceived and male-rated attractiveness. Other facial traits are related only to one direct attractiveness measurement: facial averageness and facial maturity only affect men's ratings. Unmodified faces are closer to natural stimuli than are manipulated photographs, and therefore our results support the importance of employing unmodified faces to analyse the factors affecting attractiveness. We also discuss the relatively low equivalence between self-perceived and male-rated attractiveness and how various anthropometric traits are relevant to them in different ways. Finally, we highlight the need to perform integrated-variable studies to fully understand female attractiveness. PMID:26161954
Bayesian Vision for Shape Recovery
NASA Astrophysics Data System (ADS)
Jalobeanu, André
2004-11-01
We present a new Bayesian vision technique that aims at recovering a shape from two or more noisy observations taken under similar lighting conditions. The shape is parametrized by a piecewise linear height field, textured by a piecewise linear irradiance field, and we assume Gaussian Markovian priors for both shape vertices and irradiance variables. The modeled observation process, equivalent to rendering, is modeled by a non-affine projection (e.g. perspective projection) followed by a convolution with a piecewise linear point spread function, and contamination by additive Gaussian noise. We assume that the observation parameters are calibrated beforehand. The major novelty of the proposed method consists of marginalizing out the irradiances considered as nuisance parameters, which is achieved by a hierarchy of approximations. This reduces the inference to minimizing an energy that only depends on the shape vertices, and therefore allows an efficient Iterated Conditional Mode (ICM) optimization scheme to be implemented. A Gaussian approximation of the posterior shape density is computed, thus providing estimates of both the geometry and its uncertainty. We illustrate the effectiveness of the new method by shape reconstruction results in a 2D case. A 3D version is currently under development and aims at recovering a surface from multiple images, reconstructing the topography by marginalizing out both albedo and shading.
Bayesian Vision for Shape Recovery
NASA Technical Reports Server (NTRS)
Jalobeanu, Andre
2004-01-01
We present a new Bayesian vision technique that aims at recovering a shape from two or more noisy observations taken under similar lighting conditions. The shape is parametrized by a piecewise linear height field, textured by a piecewise linear irradiance field, and we assume Gaussian Markovian priors for both shape vertices and irradiance variables. The observation process. also known as rendering, is modeled by a non-affine projection (e.g. perspective projection) followed by a convolution with a piecewise linear point spread function. and contamination by additive Gaussian noise. We assume that the observation parameters are calibrated beforehand. The major novelty of the proposed method consists of marginalizing out the irradiances considered as nuisance parameters, which is achieved by Laplace approximations. This reduces the inference to minimizing an energy that only depends on the shape vertices, and therefore allows an efficient Iterated Conditional Mode (ICM) optimization scheme to be implemented. A Gaussian approximation of the posterior shape density is computed, thus providing estimates both the geometry and its uncertainty. We illustrate the effectiveness of the new method by shape reconstruction results in a 2D case. A 3D version is currently under development and aims at recovering a surface from multiple images, reconstructing the topography by marginalizing out both albedo and shading.
Bayesian inference for OPC modeling
NASA Astrophysics Data System (ADS)
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 estimation of dose thresholds
NASA Technical Reports Server (NTRS)
Groer, P. G.; Carnes, B. A.
2003-01-01
An example is described of Bayesian estimation of radiation absorbed dose thresholds (subsequently simply referred to as dose thresholds) using a specific parametric model applied to a data set on mice exposed to 60Co gamma rays and fission neutrons. A Weibull based relative risk model with a dose threshold parameter was used to analyse, as an example, lung cancer mortality and determine the posterior density for the threshold dose after single exposures to 60Co gamma rays or fission neutrons from the JANUS reactor at Argonne National Laboratory. The data consisted of survival, censoring times and cause of death information for male B6CF1 unexposed and exposed mice. The 60Co gamma whole-body doses for the two exposed groups were 0.86 and 1.37 Gy. The neutron whole-body doses were 0.19 and 0.38 Gy. Marginal posterior densities for the dose thresholds for neutron and gamma radiation were calculated with numerical integration and found to have quite different shapes. The density of the threshold for 60Co is unimodal with a mode at about 0.50 Gy. The threshold density for fission neutrons declines monotonically from a maximum value at zero with increasing doses. The posterior densities for all other parameters were similar for the two radiation types.
Benchmarking for Bayesian Reinforcement Learning
Ernst, Damien; Couëtoux, Adrien
2016-01-01
In the Bayesian Reinforcement Learning (BRL) setting, agents try to maximise the collected rewards while interacting with their environment while using some prior knowledge that is accessed beforehand. Many BRL algorithms have already been proposed, but the benchmarks used to compare them are only relevant for specific cases. The paper addresses this problem, and provides a new BRL comparison methodology along with the corresponding open source library. In this methodology, a comparison criterion that measures the performance of algorithms on large sets of Markov Decision Processes (MDPs) drawn from some probability distributions is defined. In order to enable the comparison of non-anytime algorithms, our methodology also includes a detailed analysis of the computation time requirement of each algorithm. Our library is released with all source code and documentation: it includes three test problems, each of which has two different prior distributions, and seven state-of-the-art RL algorithms. Finally, our library is illustrated by comparing all the available algorithms and the results are discussed. PMID:27304891
Benchmarking for Bayesian Reinforcement Learning.
Castronovo, Michael; Ernst, Damien; Couëtoux, Adrien; Fonteneau, Raphael
2016-01-01
In the Bayesian Reinforcement Learning (BRL) setting, agents try to maximise the collected rewards while interacting with their environment while using some prior knowledge that is accessed beforehand. Many BRL algorithms have already been proposed, but the benchmarks used to compare them are only relevant for specific cases. The paper addresses this problem, and provides a new BRL comparison methodology along with the corresponding open source library. In this methodology, a comparison criterion that measures the performance of algorithms on large sets of Markov Decision Processes (MDPs) drawn from some probability distributions is defined. In order to enable the comparison of non-anytime algorithms, our methodology also includes a detailed analysis of the computation time requirement of each algorithm. Our library is released with all source code and documentation: it includes three test problems, each of which has two different prior distributions, and seven state-of-the-art RL algorithms. Finally, our library is illustrated by comparing all the available algorithms and the results are discussed.
Normativity, interpretation, and Bayesian models
Oaksford, Mike
2014-01-01
It has been suggested that evaluative normativity should be expunged from the psychology of reasoning. A broadly Davidsonian response to these arguments is presented. It is suggested that two distinctions, between different types of rationality, are more permeable than this argument requires and that the fundamental objection is to selecting theories that make the most rational sense of the data. It is argued that this is inevitable consequence of radical interpretation where understanding others requires assuming they share our own norms of reasoning. This requires evaluative normativity and it is shown that when asked to evaluate others’ arguments participants conform to rational Bayesian norms. It is suggested that logic and probability are not in competition and that the variety of norms is more limited than the arguments against evaluative normativity suppose. Moreover, the universality of belief ascription suggests that many of our norms are universal and hence evaluative. It is concluded that the union of evaluative normativity and descriptive psychology implicit in Davidson and apparent in the psychology of reasoning is a good thing. PMID:24860519
Stereotyping Physical Attractiveness: A Sociocultural Perspective.
ERIC Educational Resources Information Center
Dion, Karen K.; And Others
1990-01-01
Studies the tendency to stereotype physical attractiveness and identification in a collectivist culture using a group of 53 Chinese Canadian college students. Finds that introverts tended to be more prone to stereotyping than extroverts. Subjects with the highest cultural involvement were least prone to stereotyping with regard to social…
Visual cues to female physical attractiveness.
Tovée, M J; Maisey, D S; Emery, J L; Cornelissen, P L
1999-01-01
Evolutionary psychology suggests that a woman's sexual attractiveness is based on cues of health and reproductive potential. In recent years, research has focused on the ratio of the width of the waist to the width of the hips (the waist-to-hip ratio (WHR). A low WHR (i.e. a curvaceous body) is believed to correspond to the optimal fat distribution for high fertility, and so this shape should be highly attractive. In this paper we present evidence that weight scaled for height (the body mass index (BMI)) is the primary determinant of sexual attractiveness rather than WHR. BMI is also strongly linked to health and reproductive potential. Furthermore, we show how covariation of apparent BMI and WHR in previous studies led to the overestimation of the importance of WHR in the perception of female attractiveness. Finally, we show how visual cues, such as the perimeter-area ratio (PAR), can provide an accurate and reliable index of an individual's BMI and could be used by an observer to differentiate between potential partners. PMID:10097394
Floral attractants for monitoring pest moths
Technology Transfer Automated Retrieval System (TEKTRAN)
Many species of moths, including pest species, are known to be attracted to volatile compounds emitted by flowers. Some of the flower species studied included glossy abelia, night-blooming jessamine, three species of Gaura, honeysuckle, lesser butterfly orchid, and Oregongrape. The volatiles relea...
Placemaking: Attracting and Retaining Today's Students
ERIC Educational Resources Information Center
Knight, Brent
2016-01-01
Research suggests that the appearance of a college campus--both inside and out--is a significant criterion in college selection. As community colleges are finding it increasingly important to attract and retain students, placemaking is becoming an effective and efficient platform to support recruitment and retention. Placemaking is imagining and…
Stragegies for Attracting and Retaining Teachers
ERIC Educational Resources Information Center
Bland, Paul; Church, Edwin; Luo, Mingchu
2014-01-01
Attracting and retaining high quality teachers is a challenge for many school districts. This is especially true in a time of increased accountability and limited resources. This report details best practice in the training, hiring, improvement, and retention of high quality teaching staff. The authors explain how school leaders can attract…
The shape and dynamics of local attraction
NASA Astrophysics Data System (ADS)
Strömbom, D.; Siljestam, M.; Park, J.; Sumpter, D. J. T.
2015-11-01
Moving animal groups, such as flocks of birds or schools of fish, exhibit a varity of self-organized complex dynamical behaviors and shapes. This kind of flocking behavior has been studied using self-propelled particle models, in which the "particles" interact with their nearest neighbors through repulsion, attraction and alignment responses. In particular, it has been shown that models based on attraction alone can generate a range of dynamic groups in 2D, with periodic boundary conditions, and in the absence of repulsion. Here we investigate the effects of changing these conditions on the type of groups observed in the model. We show that replacing the periodic boundary conditions with a weak global attaction term in 2D, and extending the model to 3D does not significantly change the type of groups observed. We also provide a description of how attraction strength and blind angle determine the groups generated in the 3D version of the model. Finally, we show that adding repulsion do change the type of groups oberved, making them appear and behave more like real moving animal groups. Our results suggest that many biological instances of collective motion may be explained without assuming that animals explicitly align with each other. Instead, complex collective motion is explained by the interplay of attraction and repulsion forces. Supplementary material in the form of four mp4 files available from the Journal web page at http://dx.doi.org/10.1140/epjst/e2015-50093-5
Ordinal Position, Approval Motivation, and Interpersonal Attraction
ERIC Educational Resources Information Center
Nowicki, Stephen, Jr.
1971-01-01
Results of the study suggest that birth-order effects might be included within the wider framework of approval-dependency theory. Females tend to account for a significant share of birth-order effects. More particularly, firstborn females accounted for much of the differences in expressed attraction as well as need for social approval. (Author)
Radial Motion of Two Mutually Attracting Particles
ERIC Educational Resources Information Center
Mungan, Carl E.
2009-01-01
A pair of masses or opposite-sign charges released from rest will move directly toward each other under the action of the inverse-distance-squared force of attraction between them. An exact expression for the separation distance as a function of time can only be found by numerically inverting the solution of a differential equation. A simpler,…
Effects of sexual dimorphism on facial attractiveness.
Perrett, D I; Lee, K J; Penton-Voak, I; Rowland, D; Yoshikawa, S; Burt, D M; Henzi, S P; Castles, D L; Akamatsu, S
1998-08-27
Testosterone-dependent secondary sexual characteristics in males may signal immunological competence and are sexually selected for in several species. In humans, oestrogen-dependent characteristics of the female body correlate with health and reproductive fitness and are found attractive. Enhancing the sexual dimorphism of human faces should raise attractiveness by enhancing sex-hormone-related cues to youth and fertility in females, and to dominance and immunocompetence in males. Here we report the results of asking subjects to choose the most attractive faces from continua that enhanced or diminished differences between the average shape of female and male faces. As predicted, subjects preferred feminized to average shapes of a female face. This preference applied across UK and Japanese populations but was stronger for within-population judgements, which indicates that attractiveness cues are learned. Subjects preferred feminized to average or masculinized shapes of a male face. Enhancing masculine facial characteristics increased both perceived dominance and negative attributions (for example, coldness or dishonesty) relevant to relationships and paternal investment. These results indicate a selection pressure that limits sexual dimorphism and encourages neoteny in humans.
Effects of bowing on perception of attractiveness.
Osugi, Takayuki; Kawahara, Jun I
2015-07-01
Bowing is a greeting behavior. The present study examined the modulation effect of bowing on perception of attractiveness. In each trial, a portrait digitized from university yearbooks was presented on a computer screen. The portrait was mildly tilted toward participants to simulate a greeting bow (25-degree angle). Participants evaluated the subjective attractiveness of the face using a visual analog scale (0-100). The mean attractiveness judgment of the bowing portrait was significantly higher relative to that of the bending-backward or standing-still control conditions (Experiment 1). Additional control experiments revealed that alternative accounts relying on apparent spatial proximity and physical characteristics could not solely explain the effect of bowing (Experiment 2) and indicated that the effect was specific to objects perceived as faces (Experiment 3). Furthermore, observers' in-return bowing behavior did not reduce the bowing effect (Experiment 4), and bowing motion increased the ratings of subjective politeness and submissiveness (Experiment 5). Finally, tilting the 3D faces elicited the same effect from observers as did tilting the still photos (Experiment 6). These results suggest that a tilting motion of portraits (or images of face-like objects) mimicking bowing enhances perceived attractiveness, at least as measured in a culture familiar with greeting by bowing.
Vortex attraction and the formation of sunspots
NASA Technical Reports Server (NTRS)
Parker, E. N.
1992-01-01
A downdraft vortex ring in a stratified atmosphere exhibits universal attraction for nearby vertical magnetic flux bundles. It is speculated that the magnetic fields emerging through the surface of the sun are individually encircled by one or more subsurface vortex rings, providing an important part of the observed clustering of magnetic fibrils to form pores and sunspots.
Agreement Attraction in Comprehension: Representations and Processes
ERIC Educational Resources Information Center
Wagers, Matthew W.; Lau, Ellen F.; Phillips, Colin
2009-01-01
Much work has demonstrated so-called attraction errors in the production of subject-verb agreement (e.g., "The key to the cabinets are on the table", [Bock, J. K., & Miller, C. A. (1991). "Broken agreement." "Cognitive Psychology, 23", 45-93]), in which a verb erroneously agrees with an intervening noun. Six self-paced reading experiments examined…
Scottish Visitor Attractions: Managerial Competence Requirements
ERIC Educational Resources Information Center
Watson, Sandra; McCracken, Martin; Hughes, Moira
2004-01-01
This paper presents the findings from a study into managerial competence in the Scottish visitor attraction sector. It provides an insight into the range, diversity and perceived importance of current and future competences highlighting differences based on gender, age, size, level of training and location. Although the main findings reveal a…
Salience and Attention in Surprisal-Based Accounts of Language Processing
Zarcone, Alessandra; van Schijndel, Marten; Vogels, Jorrig; Demberg, Vera
2016-01-01
The notion of salience has been singled out as the explanatory factor for a diverse range of linguistic phenomena. In particular, perceptual salience (e.g., visual salience of objects in the world, acoustic prominence of linguistic sounds) and semantic-pragmatic salience (e.g., prominence of recently mentioned or topical referents) have been shown to influence language comprehension and production. A different line of research has sought to account for behavioral correlates of cognitive load during comprehension as well as for certain patterns in language usage using information-theoretic notions, such as surprisal. Surprisal and salience both affect language processing at different levels, but the relationship between the two has not been adequately elucidated, and the question of whether salience can be reduced to surprisal / predictability is still open. Our review identifies two main challenges in addressing this question: terminological inconsistency and lack of integration between high and low levels of representations in salience-based accounts and surprisal-based accounts. We capitalize upon work in visual cognition in order to orient ourselves in surveying the different facets of the notion of salience in linguistics and their relation with models of surprisal. We find that work on salience highlights aspects of linguistic communication that models of surprisal tend to overlook, namely the role of attention and relevance to current goals, and we argue that the Predictive Coding framework provides a unified view which can account for the role played by attention and predictability at different levels of processing and which can clarify the interplay between low and high levels of processes and between predictability-driven expectation and attention-driven focus. PMID:27375525
Probabilistic alternatives to Bayesianism: the case of explanationism
Douven, Igor; Schupbach, Jonah N.
2015-01-01
There has been a probabilistic turn in contemporary cognitive science. Far and away, most of the work in this vein is Bayesian, at least in name. Coinciding with this development, philosophers have increasingly promoted Bayesianism as the best normative account of how humans ought to reason. In this paper, we make a push for exploring the probabilistic terrain outside of Bayesianism. Non-Bayesian, but still probabilistic, theories provide plausible competitors both to descriptive and normative Bayesian accounts. We argue for this general idea via recent work on explanationist models of updating, which are fundamentally probabilistic but assign a substantial, non-Bayesian role to explanatory considerations. PMID:25964769
Plant Volatile Analogues Strengthen Attractiveness to Insect
Sun, Yufeng; Yu, Hao; Zhou, Jing-Jiang; Pickett, John A.; Wu, Kongming
2014-01-01
Green leaf bug Apolygus lucorum (Meyer-Dür) is one of the major pests in agriculture. Management of A. lucorum was largely achieved by using pesticides. However, the increasing population of A. lucorum since growing Bt cotton widely and the increased awareness of ecoenvironment and agricultural product safety makes their population-control very challenging. Therefore this study was conducted to explore a novel ecological approach, synthetic plant volatile analogues, to manage the pest. Here, plant volatile analogues were first designed and synthesized by combining the bioactive components of β-ionone and benzaldehyde. The stabilities of β-ionone, benzaldehyde and analogue 3 g were tested. The electroantennogram (EAG) responses of A. lucorum adult antennae to the analogues were recorded. And the behavior assay and filed experiment were also conducted. In this study, thirteen analogues were acquired. The analogue 3 g was demonstrated to be more stable than β-ionone and benzaldehyde in the environment. Many of the analogues elicited EAG responses, and the EAG response values to 3 g remained unchanged during seven-day period. 3 g was also demonstrated to be attractive to A. lucorum adults in the laboratory behavior experiment and in the field. Its attractiveness persisted longer than β-ionone and benzaldehyde. This indicated that 3 g can strengthen attractiveness to insect and has potential as an attractant. Our results suggest that synthetic plant volatile analogues can strengthen attractiveness to insect. This is the first published study about synthetic plant volatile analogues that have the potential to be used in pest control. Our results will support a new ecological approach to pest control and it will be helpful to ecoenvironment and agricultural product safety. PMID:24911460
Differences in Expressivity Based on Attractiveness: Target or Perceiver Effects?
Rennels, Jennifer L.; Kayl, Andrea J.
2015-01-01
A significant association exists between adults’ expressivity and facial attractiveness, but it is unclear whether the association is linear or significant only at the extremes of attractiveness. It is also unclear whether attractive persons actually display more positive expressivity than unattractive persons (target effects) or whether high and low attractiveness influences expressivity valence judgments (perceiver effects). Experiment 1 demonstrated adult ratings of attractiveness were predictive of expressivity valence only for high and low attractive females and medium attractive males. Experiment 2 showed that low attractive females actually display more negative expressivity than medium and high attractive females, but there were no target effects for males. Also, attractiveness influenced expressivity valence judgments (perceiver effects) for both females and males. Our findings demonstrate that low attractive females are at a particular disadvantage during social interactions due to their low attractiveness, actual displays of negative expressivity, and perceptions of their negative expressivity. PMID:26366010
Facial Diversity and Infant Preferences for Attractive Faces.
ERIC Educational Resources Information Center
Langlois, Judith H.; And Others
1991-01-01
Three studies examined infant preferences for attractive faces of White males, White females, Black females, and infants. Infants viewed pairs of faces rated for attractiveness by adults. Preferences for attractive faces were found for all facial types. (BC)
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.
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
The Bayesian t-test and beyond.
Gönen, Mithat
2010-01-01
In this chapter we will explore Bayesian alternatives to the t-test. We saw in Chapter 1 how t-test can be used to test whether the expected outcomes of the two groups are equal or not. In Chapter 3 we saw how to make inferences from a Bayesian perspective in principle. In this chapter we will put these together to develop a Bayesian procedure for a t-test. This procedure depends on the data only through the t-statistic. It requires prior inputs and we will discuss how to assign them. We will use an example from a microarray study as to demonstrate the practical issues. The microarray study is an important application for the Bayesian t-test as it naturally brings up the question of simultaneous t-tests. It turns out that the Bayesian procedure can easily be extended to carry several t-tests on the same data set, provided some attention is paid to the concept of the correlation between tests.
On Bayesian Inductive Inference & Predictive Estimation
NASA Technical Reports Server (NTRS)
Cheeseman, Peter; Stutz, John; Smelyanskiy, Vadim
2004-01-01
We investigate Bayesian inference and the Principle of Maximum Entropy (PME) as methods for doing inference under uncertainty. This investigation is primarily through concrete examples that have been previously investigated in the literature. We find that it is possible to do Bayesian inference and PME inference using the same information, despite claims to the contrary, but that the results are not directly comparable. This is because Bayesian inference yields a probability density function (pdf) over the unknown model parameters, whereas PME yields point estimates. If mean estimates are extracted from the Bayesian pdfs, the resulting parameter estimates can differ radically from the PME values and also from the Maximum Likelihood values. We conclude that these differences are due to the Bayesian inference not assuming anything beyond the given prior probabilities and the data, whereas PME implicitly assumes that the given constraints are the only constraints that are operating. Since this assumption can be wrong, PME values may have to be revised when subsequent data shows evidence for more constraints. The entropy concentration previously "proved" by E. T. Jaynes is shown to be in error. Further, we show that PME is a generalized form of independence assumption, and so can be a very powerful method of inference when the variables being investigated are largely independent of each other.
Bayesian Methods for Medical Test Accuracy
Broemeling, Lyle D.
2011-01-01
Bayesian methods for medical test accuracy are presented, beginning with the basic measures for tests with binary scores: true positive fraction, false positive fraction, positive predictive values, and negative predictive value. The Bayesian approach is taken because of its efficient use of prior information, and the analysis is executed with a Bayesian software package WinBUGS®. The ROC (receiver operating characteristic) curve gives the intrinsic accuracy of medical tests that have ordinal or continuous scores, and the Bayesian approach is illustrated with many examples from cancer and other diseases. Medical tests include X-ray, mammography, ultrasound, computed tomography, magnetic resonance imaging, nuclear medicine and tests based on biomarkers, such as blood glucose values for diabetes. The presentation continues with more specialized methods suitable for measuring the accuracies of clinical studies that have verification bias, and medical tests without a gold standard. Lastly, the review is concluded with Bayesian methods for measuring the accuracy of the combination of two or more tests. PMID:26859485
Computationally efficient Bayesian inference for inverse problems.
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.
Understanding the Scalability of Bayesian Network Inference Using Clique Tree Growth Curves
NASA Technical Reports Server (NTRS)
Mengshoel, Ole J.
2010-01-01
One of the main approaches to performing computation in Bayesian networks (BNs) is clique tree clustering and propagation. The clique tree approach consists of propagation in a clique tree compiled from a Bayesian network, and while it was introduced in the 1980s, there is still a lack of understanding of how clique tree computation time depends on variations in BN size and structure. In this article, we improve this understanding by developing an approach to characterizing clique tree growth as a function of parameters that can be computed in polynomial time from BNs, specifically: (i) the ratio of the number of a BN s non-root nodes to the number of root nodes, and (ii) the expected number of moral edges in their moral graphs. Analytically, we partition the set of cliques in a clique tree into different sets, and introduce a growth curve for the total size of each set. For the special case of bipartite BNs, there are two sets and two growth curves, a mixed clique growth curve and a root clique growth curve. In experiments, where random bipartite BNs generated using the BPART algorithm are studied, we systematically increase the out-degree of the root nodes in bipartite Bayesian networks, by increasing the number of leaf nodes. Surprisingly, root clique growth is well-approximated by Gompertz growth curves, an S-shaped family of curves that has previously been used to describe growth processes in biology, medicine, and neuroscience. We believe that this research improves the understanding of the scaling behavior of clique tree clustering for a certain class of Bayesian networks; presents an aid for trade-off studies of clique tree clustering using growth curves; and ultimately provides a foundation for benchmarking and developing improved BN inference and machine learning algorithms.
ERIC Educational Resources Information Center
Kingwell, Gail
A stylistics-based approach to teaching poetry in the English as a foreign language classroom is examined. Since students may not have the linguistic skills to appreciate a poem, an analytical framework is proposed that includes the elements of repetition, confusion, and surprise. Reference is made to two poems, "In a Season of Unemployment"…
Charting unknown waters—On the role of surprise in flood risk assessment and management
NASA Astrophysics Data System (ADS)
Merz, B.; Vorogushyn, S.; Lall, U.; Viglione, A.; Blöschl, G.
2015-08-01
Unexpected incidents, failures, and disasters are abundant in the history of flooding events. In this paper, we introduce the metaphors of terra incognita and terra maligna to illustrate unknown and wicked flood situations, respectively. We argue that surprise is a neglected element in flood risk assessment and management. Two sources of surprise are identified: (1) the complexity of flood risk systems, represented by nonlinearities, interdependencies, and nonstationarities and (2) cognitive biases in human perception and decision making. Flood risk assessment and management are particularly prone to cognitive biases due to the rarity and uniqueness of extremes, and the nature of human risk perception. We reflect on possible approaches to better understanding and reducing the potential for surprise and its adverse consequences which may be supported by conceptually charting maps that separate terra incognita from terra cognita, and terra maligna from terra benigna. We conclude that flood risk assessment and management should account for the potential for surprise and devastating consequences which will require a shift in thinking.
Bagpipes and Artichokes: Surprise as a Stimulus to Learning in the Elementary Music Classroom
ERIC Educational Resources Information Center
Jacobi, Bonnie Schaffhauser
2016-01-01
Incorporating surprise into music instruction can stimulate student attention, curiosity, and interest. Novelty focuses attention in the reticular activating system, increasing the potential for brain memory storage. Elementary ages are ideal for introducing novel instruments, pieces, composers, or styles of music. Young children have fewer…
Properties of magnetically attractive experimental resin composites.
Hirano, S; Yasukawa, H; Nomoto, R; Moriyama, K; Hirasawa, T
1996-12-01
SUS444 stainless steel filled chemically cured resin composites that can attract magnet were fabricated. The filler was treated with various concentrations of silane. The experimental composite was easy to handle and showed a good shelf life. The maximal properties obtained are as follows; The attraction force to a magnetic attachment was 1/3-1/4 lower than the commercially available magnet-keeper system for dental magnetic attachment. Flexural strength and Knoop hardness of the composite were 76MPa (7.7 kgf/mm2) and 64 KHN. These values were lower than the commercially available chemically cured composite used as a reference. Eluted metal from the composite in 1% lactic acid solution for 7 days showed 0.7 mg/cm2, but in 0.9% NaCl solution for 7 days, it could not be detected.
Homosexual behaviour increases male attractiveness to females
Bierbach, David; Jung, Christian T.; Hornung, Simon; Streit, Bruno; Plath, Martin
2013-01-01
Male homosexual behaviour—although found in most extant clades across the Animal Kingdom—remains a conundrum, as same-sex mating should decrease male reproductive fitness. In most species, however, males that engage in same-sex sexual behaviour also mate with females, and in theory, same-sex mating could even increase male reproductive fitness if males improve their chances of future heterosexual mating. Females regularly use social information to choose a mate; e.g. male attractiveness increases after a male has interacted sexually with a female (mate choice copying). Here, we demonstrate that males of the tropical freshwater fish Poecilia mexicana increase their attractiveness to females not only by opposite-sex, but likewise, through same-sex interactions. Hence, direct benefits for males of exhibiting homosexual behaviour may help explain its occurrence and persistence in species in which females rely on mate choice copying as one component of mate quality assessment. PMID:23234866
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.
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
Feature selection using sparse Bayesian inference
NASA Astrophysics Data System (ADS)
Brandes, T. Scott; Baxter, James R.; Woodworth, Jonathan
2014-06-01
A process for selecting a sparse subset of features that maximize discrimination between target classes is described in a Bayesian framework. Demonstrated on high range resolution radar (HRR) signature data, this has the effect of selecting the most informative range bins for a classification task. The sparse Bayesian classifier (SBC) model is directly compared against Fisher's linear discriminant analysis (LDA), showing a clear performance gain with the Bayesian framework using HRRs from the publicly available MSTAR data set. The discriminative power of the selected features from the SBC is shown to be particularly dominant over LDA when only a few features are selected or when there is a shift in training and testing data sets, as demonstrated by training on a specific target type and testing on a slightly different target type.
Learning Bayesian Networks from Correlated Data
NASA Astrophysics Data System (ADS)
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 analysis of MEG visual evoked responses
NASA Astrophysics Data System (ADS)
Schmidt, David M.; George, John S.; Wood, C. C.
1999-05-01
We have 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 fit the data and prior expectations about the nature of probable solutions made explicit by a Bayesian formalism. In addition, we 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, we analyzed MEG data from a visual evoked response experiment. We 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. We also examined the changing pattern of cortical activation as a function of time.
Bayesian analysis of MEG visual evoked responses
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.
Polyisocyanurate's high R-value attracting users
Fleming, J.
1982-05-31
The higher insulating value of polyisocyanurate rigid foam boards that can be installed over existing walls is attracting customers despite their 20% higher cost per square foot than fiberglass insulation. Other plastic foam boards compare in cost, but have a lower R value. The less flammable polycyanurate boards do not require additional perlite or other fire-retardant boards to meet building fire codes. A directory lists 81 major suppliers of roof and wall insulation. (DCK)
Acarine attractants: Chemoreception, bioassay, chemistry and control.
Carr, Ann L; Roe, Michael
2016-07-01
The Acari are of significant economic importance in crop production and human and animal health. Acaricides are essential for the control of these pests, but at the same time, the number of available pesticides is limited, especially for applications in animal production. The Acari consist of two major groups, the mites that demonstrate a wide variety of life strategies, i.e., herbivory, predation and ectoparasitism, and ticks which have evolved obligatory hematophagy. The major sites of chemoreception in the acarines are the chelicerae, palps and tarsi on the forelegs. A unifying name, the "foretarsal sensory organ" (FSO), is proposed for the first time in this review for the sensory site on the forelegs of all acarines. The FSO has multiple sensory functions including olfaction, gustation, and heat detection. Preliminary transcriptomic data in ticks suggest that chemoreception in the FSO is achieved by a different mechanism from insects. There are a variety of laboratory and field bioassay methods that have been developed for the identification and characterization of attractants but minimal techniques for electrophysiology studies. Over the past three to four decades, significant progress has been made in the chemistry and analysis of function for acarine attractants in mites and ticks. In mites, attractants include aggregation, immature female, female sex and alarm pheromones; in ticks, the attraction-aggregation-attachment, assembly and sex pheromones; in mites and ticks host kairomones and plant allomones; and in mites, fungal allomones. There are still large gaps in our knowledge of chemical communication in the acarines compared to insects, especially relative to acarine pheromones, and more so for mites than ticks. However, the use of lure-and-kill and lure-enhanced biocontrol strategies has been investigated for tick and mite control, respectively, with significant environmental advantages which warrant further study.
Stochastic basins of attraction for metastable states
NASA Astrophysics Data System (ADS)
Serdukova, Larissa; Zheng, Yayun; Duan, Jinqiao; Kurths, Jürgen
2016-07-01
Basin of attraction of a stable equilibrium point is an effective concept for stability analysis in deterministic systems; however, it does not contain information on the external perturbations that may affect it. Here we introduce the concept of stochastic basin of attraction (SBA) by incorporating a suitable probabilistic notion of basin. We define criteria for the size of the SBA based on the escape probability, which is one of the deterministic quantities that carry dynamical information and can be used to quantify dynamical behavior of the corresponding stochastic basin of attraction. SBA is an efficient tool to describe the metastable phenomena complementing the known exit time, escape probability, or relaxation time. Moreover, the geometric structure of SBA gives additional insight into the system's dynamical behavior, which is important for theoretical and practical reasons. This concept can be used not only in models with small noise intensity but also with noise whose amplitude is proportional or in general is a function of an order parameter. As an application of our main results, we analyze a three potential well system perturbed by two types of noise: Brownian motion and non-Gaussian α-stable Lévy motion. Our main conclusions are that the thermal fluctuations stabilize the metastable system with an asymmetric three-well potential but have the opposite effect for a symmetric one. For Lévy noise with larger jumps and lower jump frequencies ( α = 0.5 ) metastability is enhanced for both symmetric and asymmetric potentials.
Mapping female bodily features of attractiveness
Bovet, Jeanne; Lao, Junpeng; Bartholomée, Océane; Caldara, Roberto; Raymond, Michel
2016-01-01
“Beauty is bought by judgment of the eye” (Shakespeare, Love’s Labour’s Lost), but the bodily features governing this critical biological choice are still debated. Eye movement studies have demonstrated that males sample coarse body regions expanding from the face, the breasts and the midriff, while making female attractiveness judgements with natural vision. However, the visual system ubiquitously extracts diagnostic extra-foveal information in natural conditions, thus the visual information actually used by men is still unknown. We thus used a parametric gaze-contingent design while males rated attractiveness of female front- and back-view bodies. Males used extra-foveal information when available. Critically, when bodily features were only visible through restricted apertures, fixations strongly shifted to the hips, to potentially extract hip-width and curvature, then the breast and face. Our hierarchical mapping suggests that the visual system primary uses hip information to compute the waist-to-hip ratio and the body mass index, the crucial factors in determining sexual attractiveness and mate selection. PMID:26791105
The Attraction Effect in Information Visualization.
Dimara, Evanthia; Bezerianos, Anastasia; Dragicevic, Pierre
2017-01-01
The attraction effect is a well-studied cognitive bias in decision making research, where one's choice between two alternatives is influenced by the presence of an irrelevant (dominated) third alternative. We examine whether this cognitive bias, so far only tested with three alternatives and simple presentation formats such as numerical tables, text and pictures, also appears in visualizations. Since visualizations can be used to support decision making - e.g., when choosing a house to buy or an employee to hire - a systematic bias could have important implications. In a first crowdsource experiment, we indeed partially replicated the attraction effect with three alternatives presented as a numerical table, and observed similar effects when they were presented as a scatterplot. In a second experiment, we investigated if the effect extends to larger sets of alternatives, where the number of alternatives is too large for numerical tables to be practical. Our findings indicate that the bias persists for larger sets of alternatives presented as scatterplots. We discuss implications for future research on how to further study and possibly alleviate the attraction effect.
Stochastic basins of attraction for metastable states.
Serdukova, Larissa; Zheng, Yayun; Duan, Jinqiao; Kurths, Jürgen
2016-07-01
Basin of attraction of a stable equilibrium point is an effective concept for stability analysis in deterministic systems; however, it does not contain information on the external perturbations that may affect it. Here we introduce the concept of stochastic basin of attraction (SBA) by incorporating a suitable probabilistic notion of basin. We define criteria for the size of the SBA based on the escape probability, which is one of the deterministic quantities that carry dynamical information and can be used to quantify dynamical behavior of the corresponding stochastic basin of attraction. SBA is an efficient tool to describe the metastable phenomena complementing the known exit time, escape probability, or relaxation time. Moreover, the geometric structure of SBA gives additional insight into the system's dynamical behavior, which is important for theoretical and practical reasons. This concept can be used not only in models with small noise intensity but also with noise whose amplitude is proportional or in general is a function of an order parameter. As an application of our main results, we analyze a three potential well system perturbed by two types of noise: Brownian motion and non-Gaussian α-stable Lévy motion. Our main conclusions are that the thermal fluctuations stabilize the metastable system with an asymmetric three-well potential but have the opposite effect for a symmetric one. For Lévy noise with larger jumps and lower jump frequencies ( α=0.5) metastability is enhanced for both symmetric and asymmetric potentials.
Particle identification in ALICE: a Bayesian approach
NASA Astrophysics Data System (ADS)
Adam, J.; Adamová, D.; Aggarwal, M. M.; Aglieri Rinella, G.; Agnello, M.; Agrawal, N.; Ahammed, Z.; Ahmad, S.; Ahn, S. U.; Aiola, S.; Akindinov, A.; Alam, S. N.; Albuquerque, D. S. D.; Aleksandrov, D.; Alessandro, B.; Alexandre, D.; Alfaro Molina, R.; Alici, A.; Alkin, A.; Almaraz, J. R. M.; Alme, J.; Alt, T.; Altinpinar, S.; Altsybeev, I.; Alves Garcia Prado, C.; Andrei, C.; Andronic, A.; Anguelov, V.; Antičić, T.; Antinori, F.; Antonioli, P.; Aphecetche, L.; Appelshäuser, H.; Arcelli, S.; Arnaldi, R.; Arnold, O. W.; Arsene, I. C.; Arslandok, M.; Audurier, B.; Augustinus, A.; Averbeck, R.; Azmi, M. D.; Badalà, A.; Baek, Y. W.; Bagnasco, S.; Bailhache, R.; Bala, R.; Balasubramanian, S.; Baldisseri, A.; Baral, R. C.; Barbano, A. M.; Barbera, R.; Barile, F.; Barnaföldi, G. G.; Barnby, L. S.; Barret, V.; Bartalini, P.; Barth, K.; Bartke, J.; Bartsch, E.; Basile, M.; Bastid, N.; Basu, S.; Bathen, B.; Batigne, G.; Batista Camejo, A.; Batyunya, B.; Batzing, P. C.; Bearden, I. G.; Beck, H.; Bedda, C.; Behera, N. K.; Belikov, I.; Bellini, F.; Bello Martinez, H.; Bellwied, R.; Belmont, R.; Belmont-Moreno, E.; Belyaev, V.; Benacek, P.; Bencedi, G.; Beole, S.; Berceanu, I.; Bercuci, A.; Berdnikov, Y.; Berenyi, D.; Bertens, R. A.; Berzano, D.; Betev, L.; Bhasin, A.; Bhat, I. R.; Bhati, A. K.; Bhattacharjee, B.; Bhom, J.; Bianchi, L.; Bianchi, N.; Bianchin, C.; Bielčík, J.; Bielčíková, J.; Bilandzic, A.; Biro, G.; Biswas, R.; Biswas, S.; Bjelogrlic, S.; Blair, J. T.; Blau, D.; Blume, C.; Bock, F.; Bogdanov, A.; Bøggild, H.; Boldizsár, L.; Bombara, M.; Book, J.; Borel, H.; Borissov, A.; Borri, M.; Bossú, F.; Botta, E.; Bourjau, C.; Braun-Munzinger, P.; Bregant, M.; Breitner, T.; Broker, T. A.; Browning, T. A.; Broz, M.; Brucken, E. J.; Bruna, E.; Bruno, G. E.; Budnikov, D.; Buesching, H.; Bufalino, S.; Buncic, P.; Busch, O.; Buthelezi, Z.; Butt, J. B.; Buxton, J. T.; Cabala, J.; Caffarri, D.; Cai, X.; Caines, H.; Calero Diaz, L.; Caliva, A.; Calvo Villar, E.; Camerini, P.; Carena, F.; Carena, W.; Carnesecchi, F.; Castillo Castellanos, J.; Castro, A. J.; Casula, E. A. R.; Ceballos Sanchez, C.; Cepila, J.; Cerello, P.; Cerkala, J.; Chang, B.; Chapeland, S.; Chartier, M.; Charvet, J. L.; Chattopadhyay, S.; Chattopadhyay, S.; Chauvin, A.; Chelnokov, V.; Cherney, M.; Cheshkov, C.; Cheynis, B.; Chibante Barroso, V.; Chinellato, D. D.; Cho, S.; Chochula, P.; Choi, K.; Chojnacki, M.; Choudhury, S.; Christakoglou, P.; Christensen, C. H.; Christiansen, P.; Chujo, T.; Chung, S. U.; Cicalo, C.; Cifarelli, L.; Cindolo, F.; Cleymans, J.; Colamaria, F.; Colella, D.; Collu, A.; Colocci, M.; Conesa Balbastre, G.; Conesa del Valle, Z.; Connors, M. E.; Contreras, J. G.; Cormier, T. M.; Corrales Morales, Y.; Cortés Maldonado, I.; Cortese, P.; Cosentino, M. R.; Costa, F.; Crochet, P.; Cruz Albino, R.; Cuautle, E.; Cunqueiro, L.; Dahms, T.; Dainese, A.; Danisch, M. C.; Danu, A.; Das, D.; Das, I.; Das, S.; Dash, A.; Dash, S.; De, S.; De Caro, A.; de Cataldo, G.; de Conti, C.; de Cuveland, J.; De Falco, A.; De Gruttola, D.; De Marco, N.; De Pasquale, S.; Deisting, A.; Deloff, A.; Dénes, E.; Deplano, C.; Dhankher, P.; Di Bari, D.; Di Mauro, A.; Di Nezza, P.; Diaz Corchero, M. A.; Dietel, T.; Dillenseger, P.; Divià, R.; Djuvsland, Ø.; Dobrin, A.; Domenicis Gimenez, D.; Dönigus, B.; Dordic, O.; Drozhzhova, T.; Dubey, A. K.; Dubla, A.; Ducroux, L.; Dupieux, P.; Ehlers, R. J.; Elia, D.; Endress, E.; Engel, H.; Epple, E.; Erazmus, B.; Erdemir, I.; Erhardt, F.; Espagnon, B.; Estienne, M.; Esumi, S.; Eum, J.; Evans, D.; Evdokimov, S.; Eyyubova, G.; Fabbietti, L.; Fabris, D.; Faivre, J.; Fantoni, A.; Fasel, M.; Feldkamp, L.; Feliciello, A.; Feofilov, G.; Ferencei, J.; Fernández Téllez, A.; Ferreiro, E. G.; Ferretti, A.; Festanti, A.; Feuillard, V. J. G.; Figiel, J.; Figueredo, M. A. S.; Filchagin, S.; Finogeev, D.; Fionda, F. M.; Fiore, E. M.; Fleck, M. G.; Floris, M.; Foertsch, S.; Foka, P.; Fokin, S.; Fragiacomo, E.; Francescon, A.; Frankenfeld, U.; Fronze, G. G.; Fuchs, U.; Furget, C.; Furs, A.; Fusco Girard, M.; Gaardhøje, J. J.; Gagliardi, M.; Gago, A. M.; Gallio, M.; Gangadharan, D. R.; Ganoti, P.; Gao, C.; Garabatos, C.; Garcia-Solis, E.; Gargiulo, C.; Gasik, P.; Gauger, E. F.; Germain, M.; Gheata, A.; Gheata, M.; Ghosh, P.; Ghosh, S. K.; Gianotti, P.; Giubellino, P.; Giubilato, P.; Gladysz-Dziadus, E.; Glässel, P.; Goméz Coral, D. M.; Gomez Ramirez, A.; Gonzalez, A. S.; Gonzalez, V.; González-Zamora, P.; Gorbunov, S.; Görlich, L.; Gotovac, S.; Grabski, V.; Grachov, O. A.; Graczykowski, L. K.; Graham, K. L.; Grelli, A.; Grigoras, A.; Grigoras, C.; Grigoriev, V.; Grigoryan, A.; Grigoryan, S.; Grinyov, B.; Grion, N.; Gronefeld, J. M.; Grosse-Oetringhaus, J. F.; Grosso, R.; Guber, F.; Guernane, R.; Guerzoni, B.; Gulbrandsen, K.; Gunji, T.; Gupta, A.; Gupta, R.; Haake, R.; Haaland, Ø.; Hadjidakis, C.; Haiduc, M.; Hamagaki, H.; Hamar, G.; Hamon, J. C.; Harris, J. W.; Harton, A.; Hatzifotiadou, D.; Hayashi, S.; Heckel, S. T.; Hellbär, E.; Helstrup, H.; Herghelegiu, A.; Herrera Corral, G.; Hess, B. A.; Hetland, K. F.; Hillemanns, H.; Hippolyte, B.; Horak, D.; Hosokawa, R.; Hristov, P.; Humanic, T. J.; Hussain, N.; Hussain, T.; Hutter, D.; Hwang, D. S.; Ilkaev, R.; Inaba, M.; Incani, E.; Ippolitov, M.; Irfan, M.; Ivanov, M.; Ivanov, V.; Izucheev, V.; Jacazio, N.; Jacobs, P. M.; Jadhav, M. B.; Jadlovska, S.; Jadlovsky, J.; Jahnke, C.; Jakubowska, M. J.; Jang, H. J.; Janik, M. A.; Jayarathna, P. H. S. Y.; Jena, C.; Jena, S.; Jimenez Bustamante, R. T.; Jones, P. G.; Jusko, A.; Kalinak, P.; Kalweit, A.; Kamin, J.; Kang, J. H.; Kaplin, V.; Kar, S.; Karasu Uysal, A.; Karavichev, O.; Karavicheva, T.; Karayan, L.; Karpechev, E.; Kebschull, U.; Keidel, R.; Keijdener, D. L. D.; Keil, M.; Mohisin Khan, M.; Khan, P.; Khan, S. A.; Khanzadeev, A.; Kharlov, Y.; Kileng, B.; Kim, D. W.; Kim, D. J.; Kim, D.; Kim, H.; Kim, J. S.; Kim, M.; Kim, S.; Kim, T.; Kirsch, S.; Kisel, I.; Kiselev, S.; Kisiel, A.; Kiss, G.; Klay, J. L.; Klein, C.; Klein, J.; Klein-Bösing, C.; Klewin, S.; Kluge, A.; Knichel, M. L.; Knospe, A. G.; Kobdaj, C.; Kofarago, M.; Kollegger, T.; Kolojvari, A.; Kondratiev, V.; Kondratyeva, N.; Kondratyuk, E.; Konevskikh, A.; Kopcik, M.; Kostarakis, P.; Kour, M.; Kouzinopoulos, C.; Kovalenko, O.; Kovalenko, V.; Kowalski, M.; Koyithatta Meethaleveedu, G.; Králik, I.; Kravčáková, A.; Krivda, M.; Krizek, F.; Kryshen, E.; Krzewicki, M.; Kubera, A. M.; Kučera, V.; Kuhn, C.; Kuijer, P. G.; Kumar, A.; Kumar, J.; Kumar, L.; Kumar, S.; Kurashvili, P.; Kurepin, A.; Kurepin, A. B.; Kuryakin, A.; Kweon, M. J.; Kwon, Y.; La Pointe, S. L.; La Rocca, P.; Ladron de Guevara, P.; Lagana Fernandes, C.; Lakomov, I.; Langoy, R.; Lara, C.; Lardeux, A.; Lattuca, A.; Laudi, E.; Lea, R.; Leardini, L.; Lee, G. R.; Lee, S.; Lehas, F.; Lemmon, R. C.; Lenti, V.; Leogrande, E.; León Monzón, I.; León Vargas, H.; Leoncino, M.; Lévai, P.; Li, S.; Li, X.; Lien, J.; Lietava, R.; Lindal, S.; Lindenstruth, V.; Lippmann, C.; Lisa, M. A.; Ljunggren, H. M.; Lodato, D. F.; Loenne, P. I.; Loginov, V.; Loizides, C.; Lopez, X.; López Torres, E.; Lowe, A.; Luettig, P.; Lunardon, M.; Luparello, G.; Lutz, T. H.; Maevskaya, A.; Mager, M.; Mahajan, S.; Mahmood, S. M.; Maire, A.; Majka, R. D.; Malaev, M.; Maldonado Cervantes, I.; Malinina, L.; Mal'Kevich, D.; Malzacher, P.; Mamonov, A.; Manko, V.; Manso, F.; Manzari, V.; Marchisone, M.; Mareš, J.; Margagliotti, G. V.; Margotti, A.; Margutti, J.; Marín, A.; Markert, C.; Marquard, M.; Martin, N. A.; Martin Blanco, J.; Martinengo, P.; Martínez, M. I.; Martínez García, G.; Martinez Pedreira, M.; Mas, A.; Masciocchi, S.; Masera, M.; Masoni, A.; Mastroserio, A.; Matyja, A.; Mayer, C.; Mazer, J.; Mazzoni, M. A.; Mcdonald, D.; Meddi, F.; Melikyan, Y.; Menchaca-Rocha, A.; Meninno, E.; Mercado Pérez, J.; Meres, M.; Miake, Y.; Mieskolainen, M. M.; Mikhaylov, K.; Milano, L.; Milosevic, J.; Mischke, A.; Mishra, A. N.; Miśkowiec, D.; Mitra, J.; Mitu, C. M.; Mohammadi, N.; Mohanty, B.; Molnar, L.; Montaño Zetina, L.; Montes, E.; Moreira De Godoy, D. A.; Moreno, L. A. P.; Moretto, S.; Morreale, A.; Morsch, A.; Muccifora, V.; Mudnic, E.; Mühlheim, D.; Muhuri, S.; Mukherjee, M.; Mulligan, J. D.; Munhoz, M. G.; Munzer, R. H.; Murakami, H.; Murray, S.; Musa, L.; Musinsky, J.; Naik, B.; Nair, R.; Nandi, B. K.; Nania, R.; Nappi, E.; Naru, M. U.; Natal da Luz, H.; Nattrass, C.; Navarro, S. R.; Nayak, K.; Nayak, R.; Nayak, T. K.; Nazarenko, S.; Nedosekin, A.; Nellen, L.; Ng, F.; Nicassio, M.; Niculescu, M.; Niedziela, J.; Nielsen, B. S.; Nikolaev, S.; Nikulin, S.; Nikulin, V.; Noferini, F.; Nomokonov, P.; Nooren, G.; Noris, J. C. C.; Norman, J.; Nyanin, A.; Nystrand, J.; Oeschler, H.; Oh, S.; Oh, S. K.; Ohlson, A.; Okatan, A.; Okubo, T.; Olah, L.; Oleniacz, J.; Oliveira Da Silva, A. C.; Oliver, M. H.; Onderwaater, J.; Oppedisano, C.; Orava, R.; Oravec, M.; Ortiz Velasquez, A.; Oskarsson, A.; Otwinowski, J.; Oyama, K.; Ozdemir, M.; Pachmayer, Y.; Pagano, D.; Pagano, P.; Paić, G.; Pal, S. K.; Pan, J.; Pandey, A. K.; Papikyan, V.; Pappalardo, G. S.; Pareek, P.; Park, W. J.; Parmar, S.; Passfeld, A.; Paticchio, V.; Patra, R. N.; Paul, B.; Pei, H.; Peitzmann, T.; Pereira Da Costa, H.; Peresunko, D.; Pérez Lara, C. E.; Perez Lezama, E.; Peskov, V.; Pestov, Y.; Petráček, V.; Petrov, V.; Petrovici, M.; Petta, C.; Piano, S.; Pikna, M.; Pillot, P.; Pimentel, L. O. D. L.; Pinazza, O.; Pinsky, L.; Piyarathna, D. B.; Płoskoń, M.; Planinic, M.; Pluta, J.; Pochybova, S.; Podesta-Lerma, P. L. M.; Poghosyan, M. G.; Polichtchouk, B.; Poljak, N.; Poonsawat, W.; Pop, A.; Porteboeuf-Houssais, S.; Porter, J.; Pospisil, J.; Prasad, S. K.; Preghenella, R.; Prino, F.; Pruneau, C. A.; Pshenichnov, I.; Puccio, M.; Puddu, G.; Pujahari, P.; Punin, V.; Putschke, J.; Qvigstad, H.; Rachevski, A.; Raha, S.; Rajput, S.; Rak, J.; Rakotozafindrabe, A.; Ramello, L.; Rami, F.; Raniwala, R.; Raniwala, S.; Räsänen, S. S.; Rascanu, B. T.; Rathee, D.; Read, K. F.; Redlich, K.; Reed, R. J.; Rehman, A.; Reichelt, P.; Reidt, F.; Ren, X.; Renfordt, R.; Reolon, A. R.; Reshetin, A.; Reygers, K.; Riabov, V.; Ricci, R. A.; Richert, T.; Richter, M.; Riedler, P.; Riegler, W.; Riggi, F.; Ristea, C.; Rocco, E.; Rodríguez Cahuantzi, M.; Rodriguez Manso, A.; Røed, K.; Rogochaya, E.; Rohr, D.; Röhrich, D.; Ronchetti, F.; Ronflette, L.; Rosnet, P.; Rossi, A.; Roukoutakis, F.; Roy, A.; Roy, C.; Roy, P.; Rubio Montero, A. J.; Rui, R.; Russo, R.; Ryabinkin, E.; Ryabov, Y.; Rybicki, A.; Saarinen, S.; Sadhu, S.; Sadovsky, S.; Šafařík, K.; Sahlmuller, B.; Sahoo, P.; Sahoo, R.; Sahoo, S.; Sahu, P. K.; Saini, J.; Sakai, S.; Saleh, M. A.; Salzwedel, J.; Sambyal, S.; Samsonov, V.; Šándor, L.; Sandoval, A.; Sano, M.; Sarkar, D.; Sarkar, N.; Sarma, P.; Scapparone, E.; Scarlassara, F.; Schiaua, C.; Schicker, R.; Schmidt, C.; Schmidt, H. R.; Schuchmann, S.; Schukraft, J.; Schulc, M.; Schutz, Y.; Schwarz, K.; Schweda, K.; Scioli, G.; Scomparin, E.; Scott, R.; Šefčík, M.; Seger, J. E.; Sekiguchi, Y.; Sekihata, D.; Selyuzhenkov, I.; Senosi, K.; Senyukov, S.; Serradilla, E.; Sevcenco, A.; Shabanov, A.; Shabetai, A.; Shadura, O.; Shahoyan, R.; Shahzad, M. I.; Shangaraev, A.; Sharma, A.; Sharma, M.; Sharma, M.; Sharma, N.; Sheikh, A. I.; Shigaki, K.; Shou, Q.; Shtejer, K.; Sibiriak, Y.; Siddhanta, S.; Sielewicz, K. M.; Siemiarczuk, T.; Silvermyr, D.; Silvestre, C.; Simatovic, G.; Simonetti, G.; Singaraju, R.; Singh, R.; Singha, S.; Singhal, V.; Sinha, B. C.; Sinha, T.; Sitar, B.; Sitta, M.; Skaali, T. B.; Slupecki, M.; Smirnov, N.; Snellings, R. J. M.; Snellman, T. W.; Song, J.; Song, M.; Song, Z.; Soramel, F.; Sorensen, S.; Souza, R. D. de; Sozzi, F.; Spacek, M.; Spiriti, E.; Sputowska, I.; Spyropoulou-Stassinaki, M.; Stachel, J.; Stan, I.; Stankus, P.; Stenlund, E.; Steyn, G.; Stiller, J. H.; Stocco, D.; Strmen, P.; Suaide, A. A. P.; Sugitate, T.; Suire, C.; Suleymanov, M.; Suljic, M.; Sultanov, R.; Šumbera, M.; Sumowidagdo, S.; Szabo, A.; Szanto de Toledo, A.; Szarka, I.; Szczepankiewicz, A.; Szymanski, M.; Tabassam, U.; Takahashi, J.; Tambave, G. J.; Tanaka, N.; Tarhini, M.; Tariq, M.; Tarzila, M. G.; Tauro, A.; Tejeda Muñoz, G.; Telesca, A.; Terasaki, K.; Terrevoli, C.; Teyssier, B.; Thäder, J.; Thakur, D.; Thomas, D.; Tieulent, R.; Timmins, A. R.; Toia, A.; Trogolo, S.; Trombetta, G.; Trubnikov, V.; Trzaska, W. H.; Tsuji, T.; Tumkin, A.; Turrisi, R.; Tveter, T. S.; Ullaland, K.; Uras, A.; Usai, G. L.; Utrobicic, A.; Vala, M.; Valencia Palomo, L.; Vallero, S.; Van Der Maarel, J.; Van Hoorne, J. W.; van Leeuwen, M.; Vanat, T.; Vande Vyvre, P.; Varga, D.; Vargas, A.; Vargyas, M.; Varma, R.; Vasileiou, M.; Vasiliev, A.; Vauthier, A.; Vechernin, V.; Veen, A. M.; Veldhoen, M.; Velure, A.; Vercellin, E.; Vergara Limón, S.; Vernet, R.; Verweij, M.; Vickovic, L.; Viesti, G.; Viinikainen, J.; Vilakazi, Z.; Villalobos Baillie, O.; Villatoro Tello, A.; Vinogradov, A.; Vinogradov, L.; Vinogradov, Y.; Virgili, T.; Vislavicius, V.; Viyogi, Y. P.; Vodopyanov, A.; Völkl, M. A.; Voloshin, K.; Voloshin, S. A.; Volpe, G.; von Haller, B.; Vorobyev, I.; Vranic, D.; Vrláková, J.; Vulpescu, B.; Wagner, B.; Wagner, J.; Wang, H.; Wang, M.; Watanabe, D.; Watanabe, Y.; Weber, M.; Weber, S. G.; Weiser, D. F.; Wessels, J. P.; Westerhoff, U.; Whitehead, A. M.; Wiechula, J.; Wikne, J.; Wilk, G.; Wilkinson, J.; Williams, M. C. S.; Windelband, B.; Winn, M.; Yang, H.; Yang, P.; Yano, S.; Yasin, Z.; Yin, Z.; Yokoyama, H.; Yoo, I.-K.; Yoon, J. H.; Yurchenko, V.; Yushmanov, I.; Zaborowska, A.; Zaccolo, V.; Zaman, A.; Zampolli, C.; Zanoli, H. J. C.; Zaporozhets, S.; Zardoshti, N.; Zarochentsev, A.; Závada, P.; Zaviyalov, N.; Zbroszczyk, H.; Zgura, I. S.; Zhalov, M.; Zhang, H.; Zhang, X.; Zhang, Y.; Zhang, C.; Zhang, Z.; Zhao, C.; Zhigareva, N.; Zhou, D.; Zhou, Y.; Zhou, Z.; Zhu, H.; Zhu, J.; Zichichi, A.; Zimmermann, A.; Zimmermann, M. B.; Zinovjev, G.; Zyzak, M.
2016-05-01
We present a Bayesian approach to particle identification (PID) within the ALICE experiment. The aim is to more effectively combine the particle identification capabilities of its various detectors. After a brief explanation of the adopted methodology and formalism, the performance of the Bayesian PID approach for charged pions, kaons and protons in the central barrel of ALICE is studied. PID is performed via measurements of specific energy loss ( d E/d x) and time of flight. PID efficiencies and misidentification probabilities are extracted and compared with Monte Carlo simulations using high-purity samples of identified particles in the decay channels K0S → π-π+, φ→ K-K+, and Λ→ p π- in p-Pb collisions at √{s_{NN}}=5.02 TeV. In order to thoroughly assess the validity of the Bayesian approach, this methodology was used to obtain corrected pT spectra of pions, kaons, protons, and D0 mesons in pp collisions at √{s}=7 TeV. In all cases, the results using Bayesian PID were found to be consistent with previous measurements performed by ALICE using a standard PID approach. For the measurement of D0 → K-π+, it was found that a Bayesian PID approach gave a higher signal-to-background ratio and a similar or larger statistical significance when compared with standard PID selections, despite a reduced identification efficiency. Finally, we present an exploratory study of the measurement of Λc+ → p K-π+ in pp collisions at √{s}=7 TeV, using the Bayesian approach for the identification of its decay products.
Sparse Event Modeling with Hierarchical Bayesian Kernel Methods
2016-01-05
events (and subsequently, their likelihood of occurrence) based on historical evidence of the counts of previous event occurrences. The novel Bayesian...Aug-2014 22-May-2015 Approved for Public Release; Distribution Unlimited Final Report: Sparse Event Modeling with Hierarchical Bayesian Kernel Methods...Sparse Event Modeling with Hierarchical Bayesian Kernel Methods Report Title The research objective of this proposal was to develop a predictive Bayesian
From retrodiction to Bayesian quantum imaging
NASA Astrophysics Data System (ADS)
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.
Distributed Estimation using Bayesian Consensus Filtering
2014-06-06
22] and Bayesian programming [23]. This paper focuses on developing a consensus framework for distributed Bayesian filters. The statistics literature...denote the set of inclusive neighbors. Let N, R, and Rm×n be the sets of natural numbers (positive integers ), real numbers, and m by n matrices. Let λ and...the bounded integral (´ X |f(x)| pdµ(x) )1/p , where µ is a measure on X . II. PRELIMINARIES In this section, we first state four assumptions used
Current Challenges in Bayesian Model Choice
NASA Astrophysics Data System (ADS)
Clyde, M. A.; Berger, J. O.; Bullard, F.; Ford, E. B.; Jefferys, W. H.; Luo, R.; Paulo, R.; Loredo, T.
2007-11-01
Model selection (and the related issue of model uncertainty) arises in many astronomical problems, and, in particular, has been one of the focal areas of the Exoplanet working group under the SAMSI (Statistics and Applied Mathematical Sciences Institute) Astrostatistcs Exoplanet program. We provide an overview of the Bayesian approach to model selection and highlight the challenges involved in implementing Bayesian model choice in four stylized problems. We review some of the current methods used by statisticians and astronomers and present recent developments in the area. We discuss the applicability, computational challenges, and performance of suggested methods and conclude with recommendations and open questions.
Length Scales in Bayesian Automatic Adaptive Quadrature
NASA Astrophysics Data System (ADS)
Adam, Gh.; Adam, S.
2016-02-01
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.
Teaching Bayesian Statistics in a Health Research Methodology Program
ERIC Educational Resources Information Center
Pullenayegum, Eleanor M.; Thabane, Lehana
2009-01-01
Despite the appeal of Bayesian methods in health research, they are not widely used. This is partly due to a lack of courses in Bayesian methods at an appropriate level for non-statisticians in health research. Teaching such a course can be challenging because most statisticians have been taught Bayesian methods using a mathematical approach, and…
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.
Bayesian Just-So Stories in Psychology and Neuroscience
ERIC Educational Resources Information Center
Bowers, Jeffrey S.; Davis, Colin J.
2012-01-01
According to Bayesian theories in psychology and neuroscience, minds and brains are (near) optimal in solving a wide range of tasks. We challenge this view and argue that more traditional, non-Bayesian approaches are more promising. We make 3 main arguments. First, we show that the empirical evidence for Bayesian theories in psychology is weak.…
A SAS Interface for Bayesian Analysis with WinBUGS
ERIC Educational Resources Information Center
Zhang, Zhiyong; McArdle, John J.; Wang, Lijuan; Hamagami, Fumiaki
2008-01-01
Bayesian methods are becoming very popular despite some practical difficulties in implementation. To assist in the practical application of Bayesian methods, we show how to implement Bayesian analysis with WinBUGS as part of a standard set of SAS routines. This implementation procedure is first illustrated by fitting a multiple regression model…
40 CFR 503.33 - Vector attraction reduction.
Code of Federal Regulations, 2010 CFR
2010-07-01
... 40 Protection of Environment 29 2010-07-01 2010-07-01 false Vector attraction reduction. 503.33... STANDARDS FOR THE USE OR DISPOSAL OF SEWAGE SLUDGE Pathogens and Vector Attraction Reduction § 503.33 Vector attraction reduction. (a)(1) One of the vector attraction reduction requirements in § 503.33 (b)(1)...
NASA Astrophysics Data System (ADS)
Alonso, M. P.; Beamonte, M. A.; Gargallo, P.; Salvador, M. J.
2014-10-01
In this study, we measure jointly the labour and the residential accessibility of a basic spatial unit using a Bayesian Poisson gravity model with spatial effects. The accessibility measures are broken down into two components: the attractiveness component, which is related to its socio-economic and demographic characteristics, and the impedance component, which reflects the ease of communication within and between basic spatial units. For illustration purposes, the methodology is applied to a data set containing information about commuters from the Spanish region of Aragón. We identify the areas with better labour and residential accessibility, and we also analyse the attractiveness and the impedance components of a set of chosen localities which allows us to better understand their mobility patterns.
Attraction Effects in Honorific Agreement in Korean
Kwon, Nayoung; Sturt, Patrick
2016-01-01
Previous studies have suggested that sentence processing is mediated by content-addressable direct retrieval processes (McElree, 2000; McElree et al., 2003). However, the memory retrieval processes may differ as a function of the type of dependency. For example, while many studies have reported facilitatory intrusion effects associated with a structurally illicit antecedent during the processing of subject-verb number or person agreement and negative polarity items (Pearlmutter et al., 1999; Xiang et al., 2009; Dillon et al., 2013), studies investigating reflexives have not found consistent evidence of intrusion effects (Parker et al., 2015; Sturt and Kwon, 2015; cf. Nicol and Swinney, 1989; Sturt, 2003). Similarly, the memory retrieval processes could be also sensitive to cross-linguistic differences (cf. Lago et al., 2015). We report one self-paced reading experiment and one eye-tracking experiment that examine the processing of subject-verb honorific agreement, a dependency that is different from those that have been studied to date, in Korean, a typologically different language from those previously studied. The overall results suggest that the retrieval processes underlying the processing of subject-verb honorific agreement in Korean are susceptible to facilitatory intrusion effects from a structurally illicit but feature-matching subject, with a pattern that is similar to subject-verb agreement in English. In addition, the attraction effect was not limited to the ungrammatical sentences but was also found in grammatical sentences. The clear attraction effect in the grammatical sentences suggest that the attraction effect does not solely arise as the result of an error-driven process (cf. Wagers et al., 2009), but is likely also to result from general mechanisms of retrieval processes of activating of potential items in memory (Vasishth et al., 2008). PMID:27630594
Attraction Effects in Honorific Agreement in Korean.
Kwon, Nayoung; Sturt, Patrick
2016-01-01
Previous studies have suggested that sentence processing is mediated by content-addressable direct retrieval processes (McElree, 2000; McElree et al., 2003). However, the memory retrieval processes may differ as a function of the type of dependency. For example, while many studies have reported facilitatory intrusion effects associated with a structurally illicit antecedent during the processing of subject-verb number or person agreement and negative polarity items (Pearlmutter et al., 1999; Xiang et al., 2009; Dillon et al., 2013), studies investigating reflexives have not found consistent evidence of intrusion effects (Parker et al., 2015; Sturt and Kwon, 2015; cf. Nicol and Swinney, 1989; Sturt, 2003). Similarly, the memory retrieval processes could be also sensitive to cross-linguistic differences (cf. Lago et al., 2015). We report one self-paced reading experiment and one eye-tracking experiment that examine the processing of subject-verb honorific agreement, a dependency that is different from those that have been studied to date, in Korean, a typologically different language from those previously studied. The overall results suggest that the retrieval processes underlying the processing of subject-verb honorific agreement in Korean are susceptible to facilitatory intrusion effects from a structurally illicit but feature-matching subject, with a pattern that is similar to subject-verb agreement in English. In addition, the attraction effect was not limited to the ungrammatical sentences but was also found in grammatical sentences. The clear attraction effect in the grammatical sentences suggest that the attraction effect does not solely arise as the result of an error-driven process (cf. Wagers et al., 2009), but is likely also to result from general mechanisms of retrieval processes of activating of potential items in memory (Vasishth et al., 2008).
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
[Near fatal attraction of ingested magnets].
Munchak, Itamar; Yardeni, Dan; Jacobson, Jeffrey M; Soudack-Ben Nun, Michalle; Augarten, Arie
2013-03-01
We report a case of intestinal perforation in a 20 month old girl following the ingestion of 2 small magnets. Ingestion of multiple magnets constitutes a unique problem. Magnets in adjacent intestinal loops may forcefully attract each other and produce pressure necrosis of the bowel wall, leading to perforation, fistula formation or intestinal obstruction. Therefore, these children should be observed carefully. Early surgical intervention should be considered when clinical symptoms develop, especially when, on sequential abdominal radiographs, there is no change in the magnets' location. Since toys with small magnets are ubiquitous, efforts should be made to increase parents' awareness on the one hand, and to alert toy manufacturers on the other hand.
[Research as attractiveness parameter for young surgeons].
Vollmar, B
2012-04-01
Increasing concern has been expressed about the significant shortage of new trainees in surgery. As research in the context of surgical education and training is an essential element of attraction for the field of surgery, there is an urgent priority to implement clear room for research in the concepts of education and training. In this article the relevance of both the thesis accompanying the study and research training during surgical residency for the clinical self-image, personal satisfaction and academic development of young surgeons will be presented.
Faraone, N; Svensson, G P; Anderbrant, O
2017-01-01
The behavioral response of the larval parasitoid Spintherus dubius (Hymenoptera: Pteromalidae) to volatile compounds derived from its Apion weevil hosts was investigated in two-choice bioassays. Odor source candidates were the larval and adult stages of weevils, clover flowers, and feces from adult weevils. Despite S. dubius being a larval parasitoid, the odor of weevil larvae isolated from the clover flowers was not attractive to female parasitoids. Surprisingly, S. dubius females were instead attracted by the odor from the feces of adult weevils. The female parasitoids were similarly attracted to the feces produced by the two main hosts, the red clover weevil (A. trifolii) and the white clover weevil (A. fulvipes). Chemical analysis of the volatile composition of feces produced by the two hosts revealed qualitatively similar odor profiles, correlating with the observed attraction by the parasitoid towards both odor sources. Some of the identified volatile compounds are commonly present in clover plant headspace fractions and may function as a kairomone to facilitate orientation by S. dubius to Apion-infested clover flowers. Larval and adult weevils were not attractive for parasitoid females, whereas, for the white clover weevil-plant association, infested flowers were highly attractive. These data show the use by the clover weevil parasitoid of an alternative source of olfactory information for locating its host.
Surprising electronic structure of the BeH- dimer: a full-configuration-interaction study.
Verdicchio, Marco; Bendazzoli, Gian Luigi; Evangelisti, Stefano; Leininger, Thierry
2013-01-10
The electronic structure of the beryllium hydride anion, BeH(-), was investigated at valence full-configuration-interaction (FCI) level, using large cc-pV6Z basis sets. It appears that there is a deep change of the wave function nature as a function of the internuclear distance: the ion structure goes from a weakly bonded Be···H(-) complex, at long distance, to a rather strongly bonded system (more than 2 eV) at short distance, having a (:Be-H)(-) Lewis structure. In this case, it is the beryllium atom that formally bears the negative charge, a surprising result in view of the fact that it is the hydrogen atom that has a larger electronegativity. Even more surprisingly, at very short distances the average position of the total electronic charge is close to the beryllium atom but on the opposite side with respect to the hydrogen position.
Reasoned Decision Making Without Math? Adaptability and Robustness in Response to Surprise.
Smithson, Michael; Ben-Haim, Yakov
2015-10-01
Many real-world planning and decision problems are far too uncertain, too variable, and too complicated to support realistic mathematical models. Nonetheless, we explain the usefulness, in these situations, of qualitative insights from mathematical decision theory. We demonstrate the integration of info-gap robustness in decision problems in which surprise and ignorance are predominant and where personal and collective psychological factors are critical. We present practical guidelines for employing adaptable-choice strategies as a proxy for robustness against uncertainty. These guidelines include being prepared for more surprises than we intuitively expect, retaining sufficiently many options to avoid premature closure and conflicts among preferences, and prioritizing outcomes that are steerable, whose consequences are observable, and that do not entail sunk costs, resource depletion, or high transition costs. We illustrate these concepts and guidelines with the example of the medical management of the 2003 SARS outbreak in Vietnam.
Surprisal analysis of rotational-translational energy transfer - Non-linear versus linear rotors
NASA Technical Reports Server (NTRS)
Green, S.
1979-01-01
Surprisal versus energy gap analyses of state-to-state cross sections are presented for a number of linear rigid rotors excited by collisions with atoms for H2-H, H2-He, HCl-He, HCl-Ar, CO-He, CS-H2 (j=0) OCS-H2 (j=0) and HN2(+)-He, where (j=0) indicates that the hydrogen molecule was constrained to remain in its lowest level. Different systems exhibit wide variations in the slope of the surprisal plot and in certain cases, enough to indicate that the energy gap may not be the static dynamical constraint. Similar analyses are presented for nonlinear rotors excited by atoms for H2CO-He and H2O-He. For these, the data show a great deal of scatter, indicating that the reduced energy gap is probably not the appropriate independent variable.
Bayesian Unimodal Density Regression for Causal Inference
ERIC Educational Resources Information Center
Karabatsos, George; Walker, Stephen G.
2011-01-01
Karabatsos and Walker (2011) introduced a new Bayesian nonparametric (BNP) regression model. Through analyses of real and simulated data, they showed that the BNP regression model outperforms other parametric and nonparametric regression models of common use, in terms of predictive accuracy of the outcome (dependent) variable. The other,…
Decision generation tools and Bayesian inference
NASA Astrophysics Data System (ADS)
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.
Generalizability Theory and Bayesian Inference II.
ERIC Educational Resources Information Center
Davis, Charles E.
Bayesian techniques were developed for approximating the joint and marginal distributions of universe scores in single-facit-mixed-model designs with unknown covariance structure. Empirical results indicate that when compared with Cronbach's estimates, marginal means obtained through this procedure are substantially better predictors of subsequent…
Comprehension and computation in Bayesian problem solving
Johnson, Eric D.; Tubau, Elisabet
2015-01-01
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 inferences 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 vs. incorrect reasoners depart, and how individual differences might influence this time point. PMID:26283976
A Bayesian Approach to Sensor Characterization
NASA Technical Reports Server (NTRS)
Timucin, Dogan A.
2003-01-01
The physical model of a generic electro-optic sensor is derived and incorporated into a Bayesian framework for the estimation of key instrument parameters from calibration data. The sensor characterization thus achieved enables optimal subsequent removal of instrument effects from field data, leading to the highest possible accuracy in the retrieved physical quantities.
Neural network classification - A Bayesian interpretation
NASA Technical Reports Server (NTRS)
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.
Automatic Thesaurus Construction Using Bayesian Networks.
ERIC Educational Resources Information Center
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
ERIC Educational Resources Information Center
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…
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. PMID:25360109
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...Figure 1: Schematic diagram of the environmental parameterizations for the monostatic- scattering kernel and reflection- coefficient forward and inverse...frequencies. Left two columns: scattering data; right two columns: reflection- coefficient data. 3 layers, hence accounting for the uncertainty of
Incremental Bayesian Category Learning from Natural Language
ERIC Educational Resources Information Center
Frermann, Lea; Lapata, Mirella
2016-01-01
Models of category learning have been extensively studied in cognitive science and primarily tested on perceptual abstractions or artificial stimuli. In this paper, we focus on categories acquired from natural language stimuli, that is, words (e.g., "chair" is a member of the furniture category). We present a Bayesian model that, unlike…
Bayesian calibration for forensic age estimation.
Ferrante, Luigi; Skrami, Edlira; Gesuita, Rosaria; Cameriere, Roberto
2015-05-10
Forensic medicine is increasingly called upon to assess the age of individuals. Forensic age estimation is mostly required in relation to illegal immigration and identification of bodies or skeletal remains. A variety of age estimation methods are based on dental samples and use of regression models, where the age of an individual is predicted by morphological tooth changes that take place over time. From the medico-legal point of view, regression models, with age as the dependent random variable entail that age tends to be overestimated in the young and underestimated in the old. To overcome this bias, we describe a new full Bayesian calibration method (asymmetric Laplace Bayesian calibration) for forensic age estimation that uses asymmetric Laplace distribution as the probability model. The method was compared with three existing approaches (two Bayesian and a classical method) using simulated data. Although its accuracy was comparable with that of the other methods, the asymmetric Laplace Bayesian calibration appears to be significantly more reliable and robust in case of misspecification of the probability model. The proposed method was also applied to a real dataset of values of the pulp chamber of the right lower premolar measured on x-ray scans of individuals of known age.
A Bayesian approach to reliability and confidence
NASA Technical Reports Server (NTRS)
Barnes, Ron
1989-01-01
The historical evolution of NASA's interest in quantitative measures of reliability assessment is outlined. The introduction of some quantitative methodologies into the Vehicle Reliability Branch of the Safety, Reliability and Quality Assurance (SR and QA) Division at Johnson Space Center (JSC) was noted along with the development of the Extended Orbiter Duration--Weakest Link study which will utilize quantitative tools for a Bayesian statistical analysis. Extending the earlier work of NASA sponsor, Richard Heydorn, researchers were able to produce a consistent Bayesian estimate for the reliability of a component and hence by a simple extension for a system of components in some cases where the rate of failure is not constant but varies over time. Mechanical systems in general have this property since the reliability usually decreases markedly as the parts degrade over time. While they have been able to reduce the Bayesian estimator to a simple closed form for a large class of such systems, the form for the most general case needs to be attacked by the computer. Once a table is generated for this form, researchers will have a numerical form for the general solution. With this, the corresponding probability statements about the reliability of a system can be made in the most general setting. Note that the utilization of uniform Bayesian priors represents a worst case scenario in the sense that as researchers incorporate more expert opinion into the model, they will be able to improve the strength of the probability calculations.
Diagnosis of Subtraction Bugs Using Bayesian Networks
ERIC Educational Resources Information Center
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…
Bayesian Estimation Supersedes the "t" Test
ERIC Educational Resources Information Center
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…
Sensitivity to Sampling in Bayesian Word Learning
ERIC Educational Resources Information Center
Xu, Fei; Tenenbaum, Joshua B.
2007-01-01
We report a new study testing our proposal that word learning may be best explained as an approximate form of Bayesian inference (Xu & Tenenbaum, in press). Children are capable of learning word meanings across a wide range of communicative contexts. In different contexts, learners may encounter different sampling processes generating the examples…
Bayesian Meta-Analysis of Coefficient Alpha
ERIC Educational Resources Information Center
Brannick, Michael T.; Zhang, Nanhua
2013-01-01
The current paper describes and illustrates a Bayesian approach to the meta-analysis of coefficient alpha. Alpha is the most commonly used estimate of the reliability or consistency (freedom from measurement error) for educational and psychological measures. The conventional approach to meta-analysis uses inverse variance weights to combine…
An Integrated Bayesian Model for DIF Analysis
ERIC Educational Resources Information Center
Soares, Tufi M.; Goncalves, Flavio B.; Gamerman, Dani
2009-01-01
In this article, an integrated Bayesian model for differential item functioning (DIF) analysis is proposed. The model is integrated in the sense of modeling the responses along with the DIF analysis. This approach allows DIF detection and explanation in a simultaneous setup. Previous empirical studies and/or subjective beliefs about the item…
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
NASA Astrophysics Data System (ADS)
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.
Hierarchical Bayesian Models of Subtask Learning
ERIC Educational Resources Information Center
Anglim, Jeromy; Wynton, Sarah K. A.
2015-01-01
The current study used Bayesian hierarchical methods to challenge and extend previous work on subtask learning consistency. A general model of individual-level subtask learning was proposed focusing on power and exponential functions with constraints to test for inconsistency. To study subtask learning, we developed a novel computer-based booking…
Surprising patterns of CMOS susceptibility to ESD and implications on long-term reliability
Schwank, J.R.; Baker, R.P.; Armendariz, M.G.
1980-01-01
CMOS electrostatic discharge (ESD) failures in a product where, by design, the device input terminals are not accessible to ESD led to this study of device susceptibility and an analysis of the long-term reliability of devices in assemblies from that production line. Some surprising patterns of device susceptibility are established and it is shown that the probability of long-term failure in devices whose electrical characteristics have been degraded by electrostatic discharge is small.
Agent Based Study of Surprise Attacks:. Roles of Surveillance, Prompt Reaction and Intelligence
NASA Astrophysics Data System (ADS)
Shanahan, Linda; Sen, Surajit
Defending a confined territory from a surprise attack is seldom possible. We use molecular dynamics and statistical physics inspired agent-based simulations to explore the evolution and outcome of such attacks. The study suggests robust emergent behavior, which emphasizes the importance of accurate surveillance, automated and powerful attack response, building layout, and sheds light on the role of communication restrictions in defending such territories.
A Common Core for Active Conceptual Modeling for Learning from Surprises
NASA Astrophysics Data System (ADS)
Liddle, Stephen W.; Embley, David W.
The new field of active conceptual modeling for learning from surprises (ACM-L) may be helpful in preserving life, protecting property, and improving quality of life. The conceptual modeling community has developed sound theory and practices for conceptual modeling that, if properly applied, could help analysts model and predict more accurately. In particular, we need to associate more semantics with links, and we need fully reified high-level objects and relationships that have a clear, formal underlying semantics that follows a natural, ontological approach. We also need to capture more dynamic aspects in our conceptual models to more accurately model complex, dynamic systems. These concepts already exist, and the theory is well developed; what remains is to link them with the ideas needed to predict system evolution, thus enabling risk assessment and response planning. No single researcher or research group will be able to achieve this ambitious vision alone. As a starting point, we recommend that the nascent ACM-L community agree on a common core model that supports all aspects—static and dynamic—needed for active conceptual modeling in support of learning from surprises. A common core will more likely gain the traction needed to sustain the extended ACM-L research effort that will yield the advertised benefits of learning from surprises.
Melis, Theodore S.; Walters, Carl; Korman, Josh
2015-01-01
With a focus on resources of the Colorado River ecosystem below Glen Canyon Dam, the Glen Canyon Dam Adaptive Management Program has included a variety of experimental policy tests, ranging from manipulation of water releases from the dam to removal of non-native fish within Grand Canyon National Park. None of these field-scale experiments has yet produced unambiguous results in terms of management prescriptions. But there has been adaptive learning, mostly from unanticipated or surprising resource responses relative to predictions from ecosystem modeling. Surprise learning opportunities may often be viewed with dismay by some stakeholders who might not be clear about the purpose of science and modeling in adaptive management. However, the experimental results from the Glen Canyon Dam program actually represent scientific successes in terms of revealing new opportunities for developing better river management policies. A new long-term experimental management planning process for Glen Canyon Dam operations, started in 2011 by the U.S. Department of the Interior, provides an opportunity to refocus management objectives, identify and evaluate key uncertainties about the influence of dam releases, and refine monitoring for learning over the next several decades. Adaptive learning since 1995 is critical input to this long-term planning effort. Embracing uncertainty and surprise outcomes revealed by monitoring and ecosystem modeling will likely continue the advancement of resource objectives below the dam, and may also promote efficient learning in other complex programs.
A tutorial on Bayesian Normal linear regression
NASA Astrophysics Data System (ADS)
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.
Sire attractiveness influences offspring performance in guppies.
Evans, Jonathan P.; Kelley, Jennifer L.; Bisazza, Angelo; Finazzo, Elisabetta; Pilastro, Andrea
2004-01-01
According to the good-genes hypothesis, females choose among males to ensure the inheritance of superior paternal genes by their offspring. Despite increasing support for this prediction, in some cases differential (non-genetic) maternal effects may obscure or amplify the relationship between paternal attractiveness and offspring quality. Artificial insemination controls such effects because it uncouples mate choice from copulation, therefore denying females the opportunity of assessing male attractiveness. We adopted this technique in the live-bearing fish Poecilia reticulata and examined whether paternal coloration was associated with the behavioural performance of newborn offspring. Sexually receptive virgin females were inseminated with sperm taken individually from donor males that exhibited high variation in the area of orange pigmentation, a trait known to influence female choice in the study population. Our analysis of offspring performance focused on the anti-predator behaviour of newborn fish, including schooling by sibling pairs, the response (swimming speed) of these fishes to a simulated avian predator, and the time taken for a naive investigator to capture the offspring. Although we found no significant effect of sire coloration on either schooling or swimming speed, our analysis revealed a significant positive association between sire coloration and the ability of newborn offspring to evade capture. This finding supports the view that at least one aspect of anti-predator behaviour in newborn offspring is influenced by sire genotype, which in turn is revealed by the expression of secondary sexual traits. PMID:15451693
Colloidal gelation with variable attraction energy.
Zaccone, Alessio; Crassous, Jérôme J; Ballauff, Matthias
2013-03-14
We present an approximation scheme to the master kinetic equations for aggregation and gelation with thermal breakup in colloidal systems with variable attraction energy. With the cluster fractal dimension df as the only phenomenological parameter, rich physical behavior is predicted. The viscosity, the gelation time, and the cluster size are predicted in closed form analytically as a function of time, initial volume fraction, and attraction energy by combining the reversible clustering kinetics with an approximate hydrodynamic model. The fractal dimension df modulates the time evolution of cluster size, lag time and gelation time, and of the viscosity. The gelation transition is strongly nonequilibrium and time-dependent in the unstable region of the state diagram of colloids where the association rate is larger than the dissociation rate. Only upon approaching conditions where the initial association and the dissociation rates are comparable for all species (which is a condition for the detailed balance to be satisfied) aggregation can occur with df = 3. In this limit, homogeneous nucleation followed by Lifshitz-Slyozov coarsening is recovered. In this limited region of the state diagram the macroscopic gelation process is likely to be driven by large spontaneous fluctuations associated with spinodal decomposition.
Attractiveness of black Shannon trap for phlebotomines.
Galati, E A; Nunes, V L; Dorval, M E; Cristaldo, G; Rocha, H C; Gonçalves-Andrade, R M; Naufel, G
2001-07-01
A white Shannon-type trap was used for captures of female sand flies in the search for natural infection with flagellates, however, due to its low productivity and as a large number of phlebotomines settled on the researchers' black clothes, we decided to compare the relative attractiveness of black and white Shannon-type traps for sand flies. Several pairs of black and white traps were placed side by side in front of caves in four areas in the Serra da Bodoquena, Bonito county, State of Mato Grosso do Sul, Brazil, for a total of 12 observations and 44 h of capture. The experiment resulted in 889 phlebotomines captured, 801 on the black and 88 on the white trap, representing 13 species. The hourly Williams' means were 8.67 and 1.24, respectively, and the black/white ratio was 7.0:1.0. Lutzomyia almerioi, an anthropophilic species closely associated with caves, was predominant (89%). Only two other species, Nyssomyia whitmani and Psathyromyia punctigeniculata, also anthropophilic, were significantly attracted to the black rather than to the white trap (chi(2) test; p < or = 0.01). The difference between the diversity index of the two traps was not significant at level 0.05. The black trap in these circumstances was much more productive than the white, especially for anthropophilic species.
Attracting structures in volcanic ash transport
NASA Astrophysics Data System (ADS)
Peng, Jifeng
2009-11-01
Volcanic eruptions and ash clouds are a natural hazard that poses direct threats to aviation safety. They may also affect human and ecosystem health. Many transport and dispersion models have been developed to forecast trajectories of volcanic ash clouds, as well as to plan safety measures. Predictions based on these models are heavily dependent on initial parameters of ash clouds, e.g., location, height, particle size and density distribution, water vs. ash content, etc. However, these initial parameters are usually difficult to determine, leading to possible inaccurate predictions of ash clouds trajectories. In this study, a dynamical systems approach is combined with volcanic ash transport models to help improve prediction. A type of attracting structures in volcanic ash transport is identified. These structures act as attractors in volcanic ash transport, and they are independent of initial parameters of specific volcanic eruptions. The attracting structures are associated with hazard zones with high concentrations of volcanic ash. And the prediction in hazard maps can be used to plan flight route diversions and ground evacuations.
Attracting structures in volcanic ash transport
NASA Astrophysics Data System (ADS)
Peng, J.; Peterson, R.
2009-12-01
Volcanic eruptions and ash clouds are a natural hazard that poses direct threats to aviation safety. They may also affect human and ecosystem health. Many transport and dispersion models have been developed to forecast trajectories of volcanic ash clouds, as well as to plan safety measures. Predictions based on these models are heavily dependent on initial parameters of ash clouds, e.g., location, height, particle size and density distribution, water vs. ash content, etc. However, these initial parameters are usually difficult to determine, leading to possible inaccurate predictions of ash clouds trajectories. In this study, a dynamical systems approach is combined with volcanic ash transport models to help improve prediction. A type of attracting structures in volcanic ash transport is identified. These structures act as attractors in volcanic ash transport, and are largely independent of initial parameters of specific volcanic eruptions. The attracting structures are associated with hazard zones with high concentrations of volcanic ash. The prediction in hazard maps can be used to plan flight route diversions and ground evacuations.
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.
Orlovskis, Zigmunds; Hogenhout, Saskia A.
2016-01-01
Parasites can take over their hosts and trigger dramatic changes in host appearance and behavior that are typically interpreted as extended phenotypes that promote parasite survival and fitness. For example, Toxoplasma gondii is thought to manipulate the behaviors of infected rodents to aid transmission to cats and parasitic trematodes of the genus Ribeiroia alter limb development in their amphibian hosts to facilitate predation of the latter by birds. Plant parasites and pathogens also reprogram host development and morphology. However, whereas some parasite-induced morphological alterations may have a direct benefit to the fitness of the parasite and may therefore be adaptive, other host alterations may be side effects of parasite infections having no adaptive effects on parasite fitness. Phytoplasma parasites of plants often induce the development of leaf-like flowers (phyllody) in their host plants, and we previously found that the phytoplasma effector SAP54 generates these leaf-like flowers via the degradation of plant MADS-box transcription factors (MTFs), which regulate all major aspects of development in plants. Leafhoppers prefer to reproduce on phytoplasma-infected and SAP54-trangenic plants leading to the hypothesis that leafhopper vectors are attracted to plants with leaf-like flowers. Surprisingly, here we show that leafhopper attraction occurs independently of the presence of leaf-like flowers. First, the leafhoppers were also attracted to SAP54 transgenic plants without leaf-like flowers and to single leaves of these plants. Moreover, leafhoppers were not attracted to leaf-like flowers of MTF-mutant plants without the presence of SAP54. Thus, the primary role of SAP54 is to attract leafhopper vectors, which spread the phytoplasmas, and the generation of leaf-like flowers may be secondary or a side effect of the SAP54-mediated degradation of MTFs. PMID:27446117
Bayesian inference for identifying interaction rules in moving animal groups.
Mann, Richard P
2011-01-01
The emergence of similar collective patterns from different self-propelled particle models of animal groups points to a restricted set of "universal" classes for these patterns. While universality is interesting, it is often the fine details of animal interactions that are of biological importance. Universality thus presents a challenge to inferring such interactions from macroscopic group dynamics since these can be consistent with many underlying interaction models. We present a Bayesian framework for learning animal interaction rules from fine scale recordings of animal movements in swarms. We apply these techniques to the inverse problem of inferring interaction rules from simulation models, showing that parameters can often be inferred from a small number of observations. Our methodology allows us to quantify our confidence in parameter fitting. For example, we show that attraction and alignment terms can be reliably estimated when animals are milling in a torus shape, while interaction radius cannot be reliably measured in such a situation. We assess the importance of rate of data collection and show how to test different models, such as topological and metric neighbourhood models. Taken together our results both inform the design of experiments on animal interactions and suggest how these data should be best analysed.
Bayesian Switching Factor Analysis for Estimating Time-varying Functional Connectivity in fMRI.
Taghia, Jalil; Ryali, Srikanth; Chen, Tianwen; Supekar, Kaustubh; Cai, Weidong; Menon, Vinod
2017-03-03
There is growing interest in understanding the dynamical properties of functional interactions between distributed brain regions. However, robust estimation of temporal dynamics from functional magnetic resonance imaging (fMRI) data remains challenging due to limitations in extant multivariate methods for modeling time-varying functional interactions between multiple brain areas. Here, we develop a Bayesian generative model for fMRI time-series within the framework of hidden Markov models (HMMs). The model is a dynamic variant of the static factor analysis model (Ghahramani and Beal, 2000). We refer to this model as Bayesian switching factor analysis (BSFA) as it integrates factor analysis into a generative HMM in a unified Bayesian framework. In BSFA, brain dynamic functional networks are represented by latent states which are learnt from the data. Crucially, BSFA is a generative model which estimates the temporal evolution of brain states and transition probabilities between states as a function of time. An attractive feature of BSFA is the automatic determination of the number of latent states via Bayesian model selection arising from penalization of excessively complex models. Key features of BSFA are validated using extensive simulations on carefully designed synthetic data. We further validate BSFA using fingerprint analysis of multisession resting-state fMRI data from the Human Connectome Project (HCP). Our results show that modeling temporal dependencies in the generative model of BSFA results in improved fingerprinting of individual participants. Finally, we apply BSFA to elucidate the dynamic functional organization of the salience, central-executive, and default mode networks-three core neurocognitive systems with central role in cognitive and affective information processing (Menon, 2011). Across two HCP sessions, we demonstrate a high level of dynamic interactions between these networks and determine that the salience network has the highest temporal
Tweedy, Luke; Knecht, David A; Mackay, Gillian M; Insall, Robert H
2016-03-01
Chemotaxis is fundamentally important, but the sources of gradients in vivo are rarely well understood. Here, we analyse self-generated chemotaxis, in which cells respond to gradients they have made themselves by breaking down globally available attractants, using both computational simulations and experiments. We show that chemoattractant degradation creates steep local gradients. This leads to surprising results, in particular the existence of a leading population of cells that moves highly directionally, while cells behind this group are undirected. This leading cell population is denser than those following, especially at high attractant concentrations. The local gradient moves with the leading cells as they interact with their surroundings, giving directed movement that is unusually robust and can operate over long distances. Even when gradients are applied from external sources, attractant breakdown greatly changes cells' responses and increases robustness. We also consider alternative mechanisms for directional decision-making and show that they do not predict the features of population migration we observe experimentally. Our findings provide useful diagnostics to allow identification of self-generated gradients and suggest that self-generated chemotaxis is unexpectedly universal in biology and medicine.
Friedenberg, Jay
2012-01-01
Many studies over a period of more than a century have investigated the influence of the golden ratio on perceived geometric beauty. Surprisingly, very few of these studies used triangular shapes. In Experiment 1, we presented right triangles that differed in regard to their elongation determined by increasing the length of one side relative to another. Attractiveness ratings did not peak at the golden ratio, but there was a very strong influence of axis ratio overall. Participant ratings were a negative decreasing function of ratio. Triangles that pointed upward were judged as significantly more attractive than those that pointed down. We interpret these results according to a compactness hypothesis: triangles that are more compact are less likely to move or break and are thus considered more pleasing. Orientation also affects aesthetics. Upward-pointing triangles with a base parallel to the ground, regardless of their compactness, are also considered more perceptually stable and attractive. These findings were replicated across stimulus type in a second experiment with isosceles triangles and across testing procedure in a third experiment using a paired comparison technique. PMID:23145277
Attraction rules: germ cell migration in zebrafish.
Raz, Erez; Reichman-Fried, Michal
2006-08-01
The migration of zebrafish primordial germ cell towards the region where the gonad develops is guided by the chemokine SDF-1a. Recent studies show that soon after their specification, the cells undergo a series of morphological alterations before they become motile and are able to respond to attractive cues. As migratory cells, primordial germ cells move towards their target while correcting their path upon exiting a cyclic phase in which morphological cell polarity is lost. In the following stages, the cells gather at specific locations and move as cell clusters towards their final target. In all of these stages, zebrafish germ cells respond as individual cells to alterations in the shape of the sdf-1a expression domain, by directed migration towards their target - the position where the gonad develops.
Modelling of electron beam induced nanowire attraction
NASA Astrophysics Data System (ADS)
Bitzer, Lucas A.; Speich, Claudia; Schäfer, David; Erni, Daniel; Prost, Werner; Tegude, Franz J.; Benson, Niels; Schmechel, Roland
2016-04-01
Scanning electron microscope (SEM) induced nanowire (NW) attraction or bundling is a well known effect, which is mainly ascribed to structural or material dependent properties. However, there have also been recent reports of electron beam induced nanowire bending by SEM imaging, which is not fully explained by the current models, especially when considering the electro-dynamic interaction between NWs. In this article, we contribute to the understanding of this phenomenon, by introducing an electro-dynamic model based on capacitor and Lorentz force interaction, where the active NW bending is stimulated by an electromagnetic force between individual wires. The model includes geometrical, electrical, and mechanical NW parameters, as well as the influence of the electron beam source parameters and is validated using in-situ observations of electron beam induced GaAs nanowire (NW) bending by SEM imaging.
Attracting and retaining nurses in primary care.
Drennan, Vari; Andrews, Sarah; Sidhu, Rajinder; Peacock, Richard
2006-06-01
There is increasing demand for nurses to work in primary care. This is driven in part by the need to retain current levels but also by the modernisation plans for primary care services, which require new roles for nurses, new ways of working and more nurses in primary care settings. While campaigns for increased recruitment of hospital nurses and doctors has been largely successful in recent years, primary care has still to see the impact. This article reports on a Department of Health (England) funded project that aimed to identify strategies and exemplars to assist primary care trusts (PCTs) and the workforce development confederations (WDCs) in strategic health authorities in attracting and retaining nurses to primary care at registered nurse level. It reports on the range of initiatives identified, the perceived benefits and challenges. It concludes by proposing a strategic model for planning for the recruitment and retention of primary care nurses.
Basins of Attraction for Generative Justice
NASA Astrophysics Data System (ADS)
Eglash, Ron; Garvey, Colin
It has long been known that dynamic systems typically tend towards some state - an "attractor" - into which they finally settle. The introduction of chaos theory has modified our understanding of these attractors: we no longer think of the final "resting state" as necessarily being at rest. In this essay we consider the attractors of social ecologies: the networks of people, technologies and natural resources that makeup our built environments. Following the work of "communitarians" we posit that basins of attraction could be created for social ecologies that foster both environmental sustainability and social justice. We refer to this confluence as "generative justice"; a phrase which references both the "bottom-up", self-generating source of its adaptive meta stability, as well as its grounding in the ethics of egalitarian political theory.
Asymptotic Dynamics of Attractive-Repulsive Swarms
NASA Astrophysics Data System (ADS)
Leverentz, Andrew J.; Topaz, Chad M.; Bernoff, Andrew J.
2009-01-01
We classify and predict the asymptotic dynamics of a class of swarming models. The model consists of a conservation equation in one dimension describing the movement of a population density field. The velocity is found by convolving the density with a kernel describing attractive-repulsive social interactions. The kernel's first moment and its limiting behavior at the origin determine whether the population asymptotically spreads, contracts, or reaches steady state. For the spreading case, the dynamics approach those of the porous medium equation. The widening, compactly supported population has edges that behave like traveling waves whose speed, density, and slope we calculate. For the contracting case, the dynamics of the cumulative density approach those of Burgers' equation. We derive an analytical upper bound for the finite blow-up time after which the solution forms one or more delta-functions.
Bayesian network learning for natural hazard assessments
NASA Astrophysics Data System (ADS)
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
Bayesian networks in overlay recipe optimization
NASA Astrophysics Data System (ADS)
Binns, Lewis A.; Reynolds, Greg; Rigden, Timothy C.; Watkins, Stephen; Soroka, Andrew
2005-05-01
Currently, overlay measurements are characterized by "recipe", which defines both physical parameters such as focus, illumination et cetera, and also the software parameters such as algorithm to be used and regions of interest. Setting up these recipes requires both engineering time and wafer availability on an overlay tool, so reducing these requirements will result in higher tool productivity. One of the significant challenges to automating this process is that the parameters are highly and complexly correlated. At the same time, a high level of traceability and transparency is required in the recipe creation process, so a technique that maintains its decisions in terms of well defined physical parameters is desirable. Running time should be short, given the system (automatic recipe creation) is being implemented to reduce overheads. Finally, a failure of the system to determine acceptable parameters should be obvious, so a certainty metric is also desirable. The complex, nonlinear interactions make solution by an expert system difficult at best, especially in the verification of the resulting decision network. The transparency requirements tend to preclude classical neural networks and similar techniques. Genetic algorithms and other "global minimization" techniques require too much computational power (given system footprint and cost requirements). A Bayesian network, however, provides a solution to these requirements. Such a network, with appropriate priors, can be used during recipe creation / optimization not just to select a good set of parameters, but also to guide the direction of search, by evaluating the network state while only incomplete information is available. As a Bayesian network maintains an estimate of the probability distribution of nodal values, a maximum-entropy approach can be utilized to obtain a working recipe in a minimum or near-minimum number of steps. In this paper we discuss the potential use of a Bayesian network in such a capacity
NASA Astrophysics Data System (ADS)
Emery, A. F.; Valenti, E.; Bardot, D.
2007-01-01
Parameter estimation is generally based upon the maximum likelihood approach and often involves regularization. Typically it is desired that the results be unbiased and of minimum variance. However, it is often better to accept biased estimates that have minimum mean square error. Bayesian inference is an attractive approach that achieves this goal and incorporates regularization automatically. More importantly, it permits us to analyse experiments in which both the system response and the independent variables (time, sensor position, experimental conditions, etc) are corrupted by noise and in which the model includes nuisance variables. This paper describes the use of Bayesian inference for an apparently simple experiment which is, in fact, fundamentally difficult and is compounded by a nuisance variable. By presenting this analysis we hope that members of the inverse community will see the value of applying Bayesian inference.
Pheromones mediating copulation and attraction in Drosophila
Dweck, Hany K. M.; Ebrahim, Shimaa A. M.; Thoma, Michael; Mohamed, Ahmed A. M.; Keesey, Ian W.; Trona, Federica; Lavista-Llanos, Sofia; Svatoš, Aleš; Sachse, Silke; Knaden, Markus; Hansson, Bill S.
2015-01-01
Intraspecific olfactory signals known as pheromones play important roles in insect mating systems. In the model Drosophila melanogaster, a key part of the pheromone-detecting system has remained enigmatic through many years of research in terms of both its behavioral significance and its activating ligands. Here we show that Or47b-and Or88a-expressing olfactory sensory neurons (OSNs) detect the fly-produced odorants methyl laurate (ML), methyl myristate, and methyl palmitate. Fruitless (fruM)-positive Or47b-expressing OSNs detect ML exclusively, and Or47b- and Or47b-expressing OSNs are required for optimal male copulation behavior. In addition, activation of Or47b-expressing OSNs in the male is sufficient to provide a competitive mating advantage. We further find that the vigorous male courtship displayed toward oenocyte-less flies is attributed to an oenocyte-independent sustained production of the Or47b ligand, ML. In addition, we reveal that Or88a-expressing OSNs respond to all three compounds, and that these neurons are necessary and sufficient for attraction behavior in both males and females. Beyond the OSN level, information regarding the three fly odorants is transferred from the antennal lobe to higher brain centers in two dedicated neural lines. Finally, we find that both Or47b- and Or88a-based systems and their ligands are remarkably conserved over a number of drosophilid species. Taken together, our results close a significant gap in the understanding of the olfactory background to Drosophila mating and attraction behavior; while reproductive isolation barriers between species are created mainly by species-specific signals, the mating enhancing signal in several Drosophila species is conserved. PMID:25964351
Harrison, Marissa A; Shortall, Jennifer C; Dispenza, Franco; Gallup, Gordon G
2011-12-01
Facial attractiveness has been studied extensively, but little research has examined the stability of facial attractiveness of individuals across different stages of development. We conducted a study examining the relationship between facial attractiveness in infants (age 24 months and under) and the same individuals as young adults (age 16-18 years) using infant and adult photographs from high school yearbooks. Contrary to expectations, independent raters' assessments of infant facial attractiveness did not correlate with adult facial attractiveness. These results are discussed in terms of the adaptive function of heightened attractiveness in infancy, which likely evolved to elicit and maintain parental care.
Wragge-Morley, Alexander
2009-06-01
It could come as a shock to learn that some seventeenth-century men of science and learning thought that mountains were bad. Even more alarmingly, some thought that God had imposed them on the earth to punish man for his sins. By the end of the seventeenth century, surprisingly many English natural philosophers and theologians were engaged in a debate about whether mountains were 'good' or 'bad', useful or useless. At stake in this debate were not just the careers of its participants, but arguments about the best ways of looking at and reckoning with 'nature' itself.
Obidike, Stephen; Nwaeze, Obinna; Aftab, Fuad
2014-08-01
A lump in the scrotum is a common presentation in most surgical clinics. However, myoepithelial tumours may not be up on the list of differentials. Although they may look benign, myoepithelial tumours are rare and have malignant potential. Treatment of these tumours involved total excision and adequate follow-up in cases of malignancy. These groups of tumours have not been reported in the scrotum in the past, but their occurrence in the vagina may not come as a surprise bearing in mind the embryonic origin of both organs.
Don't get taken by surprise: planning for software obsolescence management at the ALMA Observatory
NASA Astrophysics Data System (ADS)
Schmid, Erich; Kosugi, George; Ibsen, Jorge; Griffith, Morgan
2016-07-01
ALMA is still a young and evolving observatory with a very active software development group that produces new and updated software components regularly. Yet we are coming to realize that - after well over a decade of development - not only our own software, but also technologies and tools we depend upon, as well as the hardware we interface with, are coming of age. Software obsolescence management is needed, but surprisingly is not something we can just borrow from other observatories, or any other comparable organization. Here we present the challenges, our approaches and some early experiences.
Bayesian active learning of neural firing rate maps with transformed gaussian process priors.
Park, Mijung; Weller, J Patrick; Horwitz, Gregory D; Pillow, Jonathan W
2014-08-01
A firing rate map, also known as a tuning curve, describes the nonlinear relationship between a neuron's spike rate and a low-dimensional stimulus (e.g., orientation, head direction, contrast, color). Here we investigate Bayesian active learning methods for estimating firing rate maps in closed-loop neurophysiology experiments. These methods can accelerate the characterization of such maps through the intelligent, adaptive selection of stimuli. Specifically, we explore the manner in which the prior and utility function used in Bayesian active learning affect stimulus selection and performance. Our approach relies on a flexible model that involves a nonlinearly transformed gaussian process (GP) prior over maps and conditionally Poisson spiking. We show that infomax learning, which selects stimuli to maximize the information gain about the firing rate map, exhibits strong dependence on the seemingly innocuous choice of nonlinear transformation function. We derive an alternate utility function that selects stimuli to minimize the average posterior variance of the firing rate map and analyze the surprising relationship between prior parameterization, stimulus selection, and active learning performance in GP-Poisson models. We apply these methods to color tuning measurements of neurons in macaque primary visual cortex.
Bayesian Cosmological inference beyond statistical isotropy
NASA Astrophysics Data System (ADS)
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.
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.
Social optimality in quantum Bayesian games
NASA Astrophysics Data System (ADS)
Iqbal, Azhar; Chappell, James M.; Abbott, Derek
2015-10-01
A significant aspect of the study of quantum strategies is the exploration of the game-theoretic solution concept of the Nash equilibrium in relation to the quantization of a game. Pareto optimality is a refinement on the set of Nash equilibria. A refinement on the set of Pareto optimal outcomes is known as social optimality in which the sum of players' payoffs is maximized. This paper analyzes social optimality in a Bayesian game that uses the setting of generalized Einstein-Podolsky-Rosen experiments for its physical implementation. We show that for the quantum Bayesian game a direct connection appears between the violation of Bell's inequality and the social optimal outcome of the game and that it attains a superior socially optimal outcome.
A Bayesian perspective on magnitude estimation.
Petzschner, Frederike H; Glasauer, Stefan; Stephan, Klaas E
2015-05-01
Our representation of the physical world requires judgments of magnitudes, such as loudness, distance, or time. Interestingly, magnitude estimates are often not veridical but subject to characteristic biases. These biases are strikingly similar across different sensory modalities, suggesting common processing mechanisms that are shared by different sensory systems. However, the search for universal neurobiological principles of magnitude judgments requires guidance by formal theories. Here, we discuss a unifying Bayesian framework for understanding biases in magnitude estimation. This Bayesian perspective enables a re-interpretation of a range of established psychophysical findings, reconciles seemingly incompatible classical views on magnitude estimation, and can guide future investigations of magnitude estimation and its neurobiological mechanisms in health and in psychiatric diseases, such as schizophrenia.
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.
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.
Software Health Management with Bayesian Networks
NASA Technical Reports Server (NTRS)
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.
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 Evidence Framework for Decision Tree Learning
NASA Astrophysics Data System (ADS)
Chatpatanasiri, Ratthachat; Kijsirikul, Boonserm
2005-11-01
This work is primary interested in the problem of, given the observed data, selecting a single decision (or classification) tree. Although a single decision tree has a high risk to be overfitted, the induced tree is easily interpreted. Researchers have invented various methods such as tree pruning or tree averaging for preventing the induced tree from overfitting (and from underfitting) the data. In this paper, instead of using those conventional approaches, we apply the Bayesian evidence framework of Gull, Skilling and Mackay to a process of selecting a decision tree. We derive a formal function to measure `the fitness' for each decision tree given a set of observed data. Our method, in fact, is analogous to a well-known Bayesian model selection method for interpolating noisy continuous-value data. As in regression problems, given reasonable assumptions, this derived score function automatically quantifies the principle of Ockham's razor, and hence reasonably deals with the issue of underfitting-overfitting tradeoff.
Bayesian parameter estimation for effective field theories
NASA Astrophysics Data System (ADS)
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.
Bayesian network modelling of upper gastrointestinal bleeding
NASA Astrophysics Data System (ADS)
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.
The NIFTY way of Bayesian signal inference
Selig, Marco
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.
Advanced Bayesian Method for Planetary Surface Navigation
NASA Technical Reports Server (NTRS)
Center, Julian
2015-01-01
Autonomous Exploration, Inc., has developed an advanced Bayesian statistical inference method that leverages current computing technology to produce a highly accurate surface navigation system. The method combines dense stereo vision and high-speed optical flow to implement visual odometry (VO) to track faster rover movements. The Bayesian VO technique improves performance by using all image information rather than corner features only. The method determines what can be learned from each image pixel and weighs the information accordingly. This capability improves performance in shadowed areas that yield only low-contrast images. The error characteristics of the visual processing are complementary to those of a low-cost inertial measurement unit (IMU), so the combination of the two capabilities provides highly accurate navigation. The method increases NASA mission productivity by enabling faster rover speed and accuracy. On Earth, the technology will permit operation of robots and autonomous vehicles in areas where the Global Positioning System (GPS) is degraded or unavailable.
Quantum-like Representation of Bayesian Updating
NASA Astrophysics Data System (ADS)
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 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.
Spectral likelihood expansions for Bayesian inference
NASA Astrophysics Data System (ADS)
Nagel, Joseph B.; Sudret, Bruno
2016-03-01
A spectral approach to Bayesian inference is presented. It pursues the emulation of the posterior probability density. The starting point is a series expansion of the likelihood function in terms of orthogonal polynomials. From this spectral likelihood expansion all statistical quantities of interest can be calculated semi-analytically. The posterior is formally represented as the product of a reference density and a linear combination of polynomial basis functions. Both the model evidence and the posterior moments are related to the expansion coefficients. This formulation avoids Markov chain Monte Carlo simulation and allows one to make use of linear least squares instead. The pros and cons of spectral Bayesian inference are discussed and demonstrated on the basis of simple applications from classical statistics and inverse modeling.
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. PMID:27047326
Maximum entropy and Bayesian methods. Proceedings.
NASA Astrophysics Data System (ADS)
Grandy, W. T., Jr.; Schick, L. H.
This volume contains a selection of papers presented at the Tenth Annual Workshop on Maximum Entropy and Bayesian Methods. The thirty-six papers included cover a wide range of applications in areas such as economics and econometrics, astronomy and astrophysics, general physics, complex systems, image reconstruction, and probability and mathematics. Together they give an excellent state-of-the-art overview of fundamental methods of data analysis.
Hierarchical Bayesian Approach to Locating Seismic Events
Johannesson, G; Myers, S C; Hanley, W G
2005-11-09
We propose a hierarchical Bayesian model for conducting inference on the location of multiple seismic events (earthquakes) given data on the arrival of various seismic phases to sensor locations. The model explicitly accounts for the uncertainty associated with a theoretical seismic-wave travel-time model used along with the uncertainty of the arrival data. Posterior inferences is carried out using Markov chain Monte Carlo (MCMC).
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.
Bayesian Networks for Modeling Dredging Decisions
2011-10-01
position unless so designated by other authorized documents. DESTROY THIS REPORT WHEN NO LONGER NEEDED. DO NOT RETURN IT TO THE ORIGINATOR. ERDC/EL TR...links within a network often do indicate causality and it is usually best to work from information about... work in this area. ERDC/EL TR-11-14 16 Table 1. Bayesian network applications reviewed in the literature. Author(s) Year Substantive issue
Bayesian Methods for Radiation Detection and Dosimetry
Peter G. Groer
2002-09-29
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 compartmental activities. From the estimated probability densities of the model parameters we were able to derive the densities for compartmental activities for a two compartment catenary model at different times. We also calculated the average activities and their standard deviation for a simple two compartment model.
Bayesian Inference for Skewed Stable Distributions
NASA Astrophysics Data System (ADS)
Shokripour, Mona; Nassiri, Vahid; Mohammadpour, Adel
2011-03-01
Stable distributions are a class of distributions which allow skewness and heavy tail. Non-Gaussian stable random variables play the role of normal distribution in the central limit theorem, for normalized sums of random variables with infinite variance. The lack of analytic formula for density and distribution functions of stable random variables has been a major drawback to the use of stable distributions, also in the case of inference in Bayesian framework. Buckle introduced priors for the parameters of stable random variables to obtain an analytic form of posterior distribution. However, many researchers tried to solve the problem, through the Markov chain Monte Carlo methods, e.g. [8] and their references. In this paper a new class of heavy-tailed distribution is introduced, called skewed stable. This class has two main advantages: It has many inferential advantages, since it is a member of exponential family, so the Bayesian inference can be drawn similar to the exponential family of distributions and modelling skew data with stable distributions is dominated by this family. Finally, Bayesian inference for skewed stable arc compared to the stable distributions through a few simulations study.
Bayesian Analysis of Individual Level Personality Dynamics
Cripps, Edward; Wood, Robert E.; Beckmann, Nadin; Lau, John; Beckmann, Jens F.; Cripps, Sally Ann
2016-01-01
A Bayesian technique with analyses of within-person processes at the level of the individual is presented. The approach is used to examine whether the patterns of within-person responses on a 12-trial simulation task are consistent with the predictions of ITA theory (Dweck, 1999). ITA theory states that the performance of an individual with an entity theory of ability is more likely to spiral down following a failure experience than the performance of an individual with an incremental theory of ability. This is because entity theorists interpret failure experiences as evidence of a lack of ability which they believe is largely innate and therefore relatively fixed; whilst incremental theorists believe in the malleability of abilities and interpret failure experiences as evidence of more controllable factors such as poor strategy or lack of effort. The results of our analyses support ITA theory at both the within- and between-person levels of analyses and demonstrate the benefits of Bayesian techniques for the analysis of within-person processes. These include more formal specification of the theory and the ability to draw inferences about each individual, which allows for more nuanced interpretations of individuals within a personality category, such as differences in the individual probabilities of spiraling. While Bayesian techniques have many potential advantages for the analyses of processes at the level of the individual, ease of use is not one of them for psychologists trained in traditional frequentist statistical techniques. PMID:27486415
Objective Bayesian model selection for Cox regression.
Held, Leonhard; Gravestock, Isaac; Sabanés Bové, Daniel
2016-12-20
There is now a large literature on objective Bayesian model selection in the linear model based on the g-prior. The methodology has been recently extended to generalized linear models using test-based Bayes factors. In this paper, we show that test-based Bayes factors can also be applied to the Cox proportional hazards model. If the goal is to select a single model, then both the maximum a posteriori and the median probability model can be calculated. For clinical prediction of survival, we shrink the model-specific log hazard ratio estimates with subsequent calculation of the Breslow estimate of the cumulative baseline hazard function. A Bayesian model average can also be employed. We illustrate the proposed methodology with the analysis of survival data on primary biliary cirrhosis patients and the development of a clinical prediction model for future cardiovascular events based on data from the Second Manifestations of ARTerial disease (SMART) cohort study. Cross-validation is applied to compare the predictive performance with alternative model selection approaches based on Harrell's c-Index, the calibration slope and the integrated Brier score. Finally, a novel application of Bayesian variable selection to optimal conditional prediction via landmarking is described. Copyright © 2016 John Wiley & Sons, Ltd.
A Bayesian sequential design with binary outcome.
Zhu, Han; Yu, Qingzhao; Mercante, Donald E
2017-03-02
Several researchers have proposed solutions to control type I error rate in sequential designs. The use of Bayesian sequential design becomes more common; however, these designs are subject to inflation of the type I error rate. We propose a Bayesian sequential design for binary outcome using an alpha-spending function to control the overall type I error rate. Algorithms are presented for calculating critical values and power for the proposed designs. We also propose a new stopping rule for futility. Sensitivity analysis is implemented for assessing the effects of varying the parameters of the prior distribution and maximum total sample size on critical values. Alpha-spending functions are compared using power and actual sample size through simulations. Further simulations show that, when total sample size is fixed, the proposed design has greater power than the traditional Bayesian sequential design, which sets equal stopping bounds at all interim analyses. We also find that the proposed design with the new stopping for futility rule results in greater power and can stop earlier with a smaller actual sample size, compared with the traditional stopping rule for futility when all other conditions are held constant. Finally, we apply the proposed method to a real data set and compare the results with traditional designs.
Network vulnerability assessment using Bayesian networks
NASA Astrophysics Data System (ADS)
Liu, Yu; Man, Hong
2005-03-01
While computer vulnerabilities have been continually reported in laundry-list format by most commercial scanners, a comprehensive network vulnerability assessment has been an increasing challenge to security analysts. Researchers have proposed a variety of methods to build attack trees with chains of exploits, based on which post-graph vulnerability analysis can be performed. The most recent approaches attempt to build attack trees by enumerating all potential attack paths, which are space consuming and result in poor scalability. This paper presents an approach to use Bayesian network to model potential attack paths. We call such graph as "Bayesian attack graph". It provides a more compact representation of attack paths than conventional methods. Bayesian inference methods can be conveniently used for probabilistic analysis. In particular, we use the Bucket Elimination algorithm for belief updating, and we use Maximum Probability Explanation algorithm to compute an optimal subset of attack paths relative to prior knowledge on attackers and attack mechanisms. We tested our model on an experimental network. Test results demonstrate the effectiveness of our approach.
Interactive, multiobjective Bayesian optimization of tokamak scenarios
NASA Astrophysics Data System (ADS)
Urban, Jakub; Artaud, Jean-François
2016-10-01
Bayesian optimization is applied to tokamak scenario optimizations. The key advantages are 1) a reduced number of objective function evaluations, 2) no need for derivatives, and 3) the possibility to include a prior knowledge. This is of a great value for optimizing tokamak scenarios, where several (competing) objectives with often unknown magnitudes exist and the number of parameters is large (>10). The first two properties imply that Bayesian optimization is well suited for heavy, complex objective functions. Reusing previous iterations as priors for next optimization steps effectively enables interactive, multiobjective optimizations, regardless of whether a human decision maker is included or not. We show that these features make Bayesian optimization an outstanding tool for optimizing tokamak scenarios. Objective functions and constraints, targeting, e.g., fusion gain, flux consumption, coils currents limits or q-profile, can be assembled interactively. The optimized parameter vector may include actuators like plasma current or heating waveforms. We demonstrate the capabilities on optimizing ITER and DEMO-like scenarios, simulated by the METIS code.
Hierarchical Bayesian model updating for structural identification
NASA Astrophysics Data System (ADS)
Behmanesh, Iman; Moaveni, Babak; Lombaert, Geert; Papadimitriou, Costas
2015-12-01
A new probabilistic finite element (FE) model updating technique based on Hierarchical Bayesian modeling is proposed for identification of civil structural systems under changing ambient/environmental conditions. The performance of the proposed technique is investigated for (1) uncertainty quantification of model updating parameters, and (2) probabilistic damage identification of the structural systems. Accurate estimation of the uncertainty in modeling parameters such as mass or stiffness is a challenging task. Several Bayesian model updating frameworks have been proposed in the literature that can successfully provide the "parameter estimation uncertainty" of model parameters with the assumption that there is no underlying inherent variability in the updating parameters. However, this assumption may not be valid for civil structures where structural mass and stiffness have inherent variability due to different sources of uncertainty such as changing ambient temperature, temperature gradient, wind speed, and traffic loads. Hierarchical Bayesian model updating is capable of predicting the overall uncertainty/variability of updating parameters by assuming time-variability of the underlying linear system. A general solution based on Gibbs Sampler is proposed to estimate the joint probability distributions of the updating parameters. The performance of the proposed Hierarchical approach is evaluated numerically for uncertainty quantification and damage identification of a 3-story shear building model. Effects of modeling errors and incomplete modal data are considered in the numerical study.
Bayesian model selection analysis of WMAP3
Parkinson, David; Mukherjee, Pia; Liddle, Andrew R.
2006-06-15
We present a Bayesian model selection analysis of WMAP3 data using our code CosmoNest. We focus on the density perturbation spectral index n{sub S} and the tensor-to-scalar ratio r, which define the plane of slow-roll inflationary models. We find that while the Bayesian evidence supports the conclusion that n{sub S}{ne}1, the data are not yet powerful enough to do so at a strong or decisive level. If tensors are assumed absent, the current odds are approximately 8 to 1 in favor of n{sub S}{ne}1 under our assumptions, when WMAP3 data is used together with external data sets. WMAP3 data on its own is unable to distinguish between the two models. Further, inclusion of r as a parameter weakens the conclusion against the Harrison-Zel'dovich case (n{sub S}=1, r=0), albeit in a prior-dependent way. In appendices we describe the CosmoNest code in detail, noting its ability to supply posterior samples as well as to accurately compute the Bayesian evidence. We make a first public release of CosmoNest, now available at www.cosmonest.org.
Müller, Günter C; Revay, Edita E; Schlein, Yosef
2011-03-01
Sugar is the main source of energy for the daily activities of sand flies. Considering its importance, there is surprisingly little information on sugar meal specific sources and sand fly attraction to plants, particularly in the field. In this study, we first needed to develop an effective sand fly trap that would be suitable for mass screening of potentially attractive flowering plants. Next, we used this trap to screen a total of 56 different flowering plant species and five plant species soiled with different types of honeydew. The plant baited traps together caught 21,978 P. papatasi. Out of the 56 types of flowering plants which were tested, 13 were shown to bait significantly more female sand flies, and 11 baited more male sand flies than the control. Based on an attraction index, the top three attractive plants in this study were the flowering plants Ochradenus baccatus, Prosopis farcta, and Tamirix nilotica. We believe that plants and phyto-chemicals have untapped potentials to attract sand flies. These could be used for control and, in combination with simple glue traps, as an alternative for existing monitoring systems.
Mammalian social odours: attraction and individual recognition
Brennan, Peter A; Kendrick, Keith M
2006-01-01
Mammalian social systems rely on signals passed between individuals conveying information including sex, reproductive status, individual identity, ownership, competitive ability and health status. Many of these signals take the form of complex mixtures of molecules sensed by chemosensory systems and have important influences on a variety of behaviours that are vital for reproductive success, such as parent–offspring attachment, mate choice and territorial marking. This article aims to review the nature of these chemosensory cues and the neural pathways mediating their physiological and behavioural effects. Despite the complexities of mammalian societies, there are instances where single molecules can act as classical pheromones attracting interest and approach behaviour. Chemosignals with relatively high volatility can be used to signal at a distance and are sensed by the main olfactory system. Most mammals also possess a vomeronasal system, which is specialized to detect relatively non-volatile chemosensory cues following direct contact. Single attractant molecules are sensed by highly specific receptors using a labelled line pathway. These act alongside more complex mixtures of signals that are required to signal individual identity. There are multiple sources of such individuality chemosignals, based on the highly polymorphic genes of the major histocompatibility complex (MHC) or lipocalins such as the mouse major urinary proteins. The individual profile of volatile components that make up an individual odour signature can be sensed by the main olfactory system, as the pattern of activity across an array of broadly tuned receptor types. In addition, the vomeronasal system can respond highly selectively to non-volatile peptide ligands associated with the MHC, acting at the V2r class of vomeronasal receptor. The ability to recognize individuals or their genetic relatedness plays an important role in mammalian social behaviour. Thus robust systems for olfactory
Attraction under Aversive Conditions: Misattributions or Fear-Reduction?
ERIC Educational Resources Information Center
Miller, Rowland S.
Interpersonal attraction appears to increase under aversive conditions. Two distinct theories suggest that attraction results from either misattribution or fear reduction. To investigate the effects of misattribution and fear reduction on attraction, 36 male college students were ostensibly exposed to an electromagnetic field while an attractive…
Is Beauty Talent? Sex Interaction in the Attractiveness Halo Effect.
ERIC Educational Resources Information Center
Kaplan, Robert M.
Male and female subjects judged an essay purportedly written by an attractive or an unattractive female author. The attractive author was rated as significantly more talented by male judges. Female judges rated the attractive author less talented although this difference was not statistically significant. A second experiment concerned ratings by…
Long-range attraction in aqueous colloidal suspensions
NASA Astrophysics Data System (ADS)
Zhao, Qing; Coult, Jason; Pollack, Gerald H.
2010-11-01
Long-range attractions in aqueous suspensions were observed between polymeric microspheres and also between microspheres and a gel bead. Attractive displacements were consistently seen even between like-charged entities, and they were observed over spans as large as 2 mm. Such behaviors are unexpected, and may reside in a long-range attraction mechanism.
Self-Esteem and Facial Attractiveness in Learning Disabled Children.
ERIC Educational Resources Information Center
Cooper, Patricia S.
1993-01-01
A total of 55 learning-disabled children ages 8 to 13 years completed a self-esteem measure, and photographs of their faces were rated for attractiveness by adults and peers. Found relationships between children's facial attractiveness and self-esteem and between adult and peer ratings of facial attractiveness. Found no gender differences in…
Somatic Attractiveness: As in Other Things, Moderation is Best.
ERIC Educational Resources Information Center
Freeman, Harvey R.
1985-01-01
Investigated whether a physical attractiveness stereotype exists when "attractive" is defined in terms of physique and "positive" is defined in terms of sex role characteristics and future life happiness. Sex role and life happiness were rated highest for those of intermediate attractiveness. Results for somatic beauty are discussed. (Author/BL)
Colouration in crab spiders: substrate choice and prey attraction.
Heiling, Astrid M; Chittka, Lars; Cheng, Ken; Herberstein, Marie E
2005-05-01
Australian crab spiders Thomisus spectabilis ambush pollinating insects, such as honeybees (Apis mellifera) on flowers, and can change their body colour between yellow and white. It is traditionally assumed that the spiders change their colour to match the flower colour, thus rendering them cryptic to insect prey. Here, we test this assumption combining state-of-the-art knowledge of bee vision and behavioural experiments. In the field, yellow spiders are only found on yellow daisies (Chrysanthemum frutescens), whereas white spiders are found on yellow and white daisies. These field patterns were confirmed in the laboratory. When given the choice between white and yellow daisies, yellow spiders preferred yellow daisies, whereas white spiders showed only a slight but non-significant preference for white flowers. Thus, T. spectabilis select background colours according to their own body colour. When viewed from a distance, bees use an achromatic signal produced by their green receptors for target detection. Through this visual channel, white spiders on white flowers, and yellow spiders on yellow flowers are virtually undetectable. From a closer distance of a few centimetres, when bees evaluate colour contrast, the combination of spider colour against different flower backgrounds affected the response of honeybees, but not in ways predicted by a classical crypsis/conspicuousness interpretation. Yellow spiders on yellow flowers are not perfectly matched when interpreted through the colour vision of a honeybee. Nevertheless, honeybees showed indifference to the presence of a spider, equally landing on vacant or spider-occupied flowers. Likewise, white spiders are poorly hidden on white flowers, as white spiders reflect ultraviolet light strongly, while white flowers do not. Surprisingly, bees are attracted to this contrast, and significantly more honeybees preferred white flowers occupied by white spiders. White spiders on yellow flowers produce the highest colour
Surprise! 20-month-old infants understand the emotional consequences of false beliefs.
Scott, Rose M
2017-02-01
Recent studies suggest that by the second year of life, infants can attribute false beliefs to agents. However, prior studies have largely focused on infants' ability to predict a mistaken agent's physical actions on objects. The present research investigated whether 20-month-old infants could also reason about belief-based emotional displays. In Experiments 1 and 2, infants viewed an agent who shook two objects: one rattled and the other was silent. Infants expected the agent to express surprise at the silent object if she had a false belief that both objects rattled, but not if she was merely ignorant about the objects' properties. Experiment 3 replicated and extended these findings: if an agent falsely believed that two containers held toy bears (when only one did so), infants expected the agent to express surprise at the empty, but not the full, container. Together, these results provide the first evidence that infants in the second year of life understand the causal relationship between beliefs and emotional displays. These findings thus provide new evidence for false-belief understanding in infancy and suggest that infants, like older children, possess a robust understanding of belief that applies to a broad range of belief-based responses.
Expectation and surprise determine neural population responses in the ventral visual stream.
Egner, Tobias; Monti, Jim M; Summerfield, Christopher
2010-12-08
Visual cortex is traditionally viewed as a hierarchy of neural feature detectors, with neural population responses being driven by bottom-up stimulus features. Conversely, "predictive coding" models propose that each stage of the visual hierarchy harbors two computationally distinct classes of processing unit: representational units that encode the conditional probability of a stimulus and provide predictions to the next lower level; and error units that encode the mismatch between predictions and bottom-up evidence, and forward prediction error to the next higher level. Predictive coding therefore suggests that neural population responses in category-selective visual regions, like the fusiform face area (FFA), reflect a summation of activity related to prediction ("face expectation") and prediction error ("face surprise"), rather than a homogenous feature detection response. We tested the rival hypotheses of the feature detection and predictive coding models by collecting functional magnetic resonance imaging data from the FFA while independently varying both stimulus features (faces vs houses) and subjects' perceptual expectations regarding those features (low vs medium vs high face expectation). The effects of stimulus and expectation factors interacted, whereby FFA activity elicited by face and house stimuli was indistinguishable under high face expectation and maximally differentiated under low face expectation. Using computational modeling, we show that these data can be explained by predictive coding but not by feature detection models, even when the latter are augmented with attentional mechanisms. Thus, population responses in the ventral visual stream appear to be determined by feature expectation and surprise rather than by stimulus features per se.
Fuzzy Naive Bayesian for constructing regulated network with weights.
Zhou, Xi Y; Tian, Xue W; Lim, Joon S
2015-01-01
In the data mining field, classification is a very crucial technology, and the Bayesian classifier has been one of the hotspots in classification research area. However, assumptions of Naive Bayesian and Tree Augmented Naive Bayesian (TAN) are unfair to attribute relations. Therefore, this paper proposes a new algorithm named Fuzzy Naive Bayesian (FNB) using neural network with weighted membership function (NEWFM) to extract regulated relations and weights. Then, we can use regulated relations and weights to construct a regulated network. Finally, we will classify the heart and Haberman datasets by the FNB network to compare with experiments of Naive Bayesian and TAN. The experiment results show that the FNB has a higher classification rate than Naive Bayesian and TAN.
An introduction to using Bayesian linear regression with clinical data.
Baldwin, Scott A; Larson, Michael J
2016-12-31
Statistical training psychology focuses on frequentist methods. Bayesian methods are an alternative to standard frequentist methods. This article provides researchers with an introduction to fundamental ideas in Bayesian modeling. We use data from an electroencephalogram (EEG) and anxiety study to illustrate Bayesian models. Specifically, the models examine the relationship between error-related negativity (ERN), a particular event-related potential, and trait anxiety. Methodological topics covered include: how to set up a regression model in a Bayesian framework, specifying priors, examining convergence of the model, visualizing and interpreting posterior distributions, interval estimates, expected and predicted values, and model comparison tools. We also discuss situations where Bayesian methods can outperform frequentist methods as well has how to specify more complicated regression models. Finally, we conclude with recommendations about reporting guidelines for those using Bayesian methods in their own research. We provide data and R code for replicating our analyses.
Fatal attraction: rare species in the spotlight
Angulo, Elena; Deves, Anne-Laure; Saint Jalmes, Michel; Courchamp, Franck
2009-01-01
The exploitation of rare and endangered species can end in the species's extinction because the increased value people associate with rarity increases the economic incentive to exploit the last individuals, creating a positive feedback loop. This recently proposed concept, called the anthropogenic Allee effect (AAE), relies on the assumption that people do value rarity, but this remains to be established. Moreover, it also remains to be determined whether attraction to rarity is a trait confined to a minority of hobbyists (e.g. wildlife collectors, exotic pet owners) or characteristic of the general public. We estimated how much the general public valued rare species compared with common ones, using five different metrics related to personal investment: time spent, physical effort, unpleasantness, economic investment and risk. We surveyed the visitors of a zoo. To see the rare species, the visitors to the zoo invested more time in searching and contemplation, they were ready to expend more physical effort, they tolerated more unpleasant conditions, they were willing to pay more and, finally, they risked more to obtain (steal) a rare species. Our results provide substantial evidence of how the general public places more value on rare species, compared with common species. This confirms the AAE as an actual process, which in addition concerns a large part of the population. This has important consequences for the conservation of species that are rare now, or that could become so in the future. PMID:19141425
How to attract pupils for soil education
NASA Astrophysics Data System (ADS)
Houskova, Beata
2013-04-01
At present time is the protection of the environment more and more important. Soil as integral part of the environment has to be protected and exploited according to the principles of sustainability. Soil is considered as non renewable resource because of very long time (more than the human life) of its creation. Also degradation processes of soil need very long time for removal of their effect and the result is not always the same soil as it was before degradation - quality of many soil properties is lost and the recovery process is time and many consuming. People simply need healthy soil for their existence of the Earth. Because of these facts the soil protection and sustainable use is crucial. Thus crucial is also education of young generation to be able to understand the value of soil for human beings.Soil is very multifunctional subject, thus also education of its protection can be variable. One way which we used was to attract children via painting competition with the topic: Soil importance and protection. Children had to create pictures by use colours made directly from different soils. The response was very positive. Children understand very well the importance of soil protection. What they do not understand, but what they recognized is that sometimes adults use soil in such a way which leads to soil degradation.
Sex differences in science museum exhibit attraction
NASA Astrophysics Data System (ADS)
Arámbula Greenfield, Teresa
This study examines the relative attraction of hands-on, interactive science museum exhibits for females and males. Studies have demonstrated that such exhibits can be effective learning experiences for children, with both academic and affective benefits. Other studies have shown that girls and boys do not always experience the same science-related educational opportunities and that, even when they do, they do not necessarily receive the same benefits from them. These early differences can lead to more serious educational and professional disparities later in life. As interactive museum exhibits represent a science experience that is-readily available to both girls and boys, the question arose as to whether they were being used similarly by the two groups as well as by adult women and men. It was found that both girls and boys used all types of exhibits, but that girls were more likely than boys to use puzzles and exhibits focusing on the human body; boys were more likely than girls to use computers and exhibits illustrating physical science principles. However, this was less true of children accompanied by adults (parents) than it was of unaccompanied children on school field trips who roamed the museum more freely.Received: 16 February 1994; Revised: 3 February 1995;
Caulier, Guillaume; Flammang, Patrick; Gerbaux, Pascal; Eeckhaut, Igor
2013-01-01
Marine organisms have developed a high diversity of chemical defences in order to avoid predators and parasites. In sea cucumbers, saponins function as repellents and many species produce these cytotoxic secondary metabolites. Nonetheless, they are colonized by numerous symbiotic organisms amongst which the Harlequin crab, Lissocarcinus orbicularis, is one of the most familiar in the Indo-Pacific Ocean. We here identify for the first time the nature of the molecules secreted by sea cucumbers and attracting the symbionts: saponins are the kairomones recognized by the crabs and insuring the symbiosis. The success of this symbiosis would be due to the ability that crabs showed during evolution to bypass the sea cucumber chemical defences, their repellents becoming powerful attractants. This study therefore highlights the complexity of chemical communication in the marine environment.
ERIC Educational Resources Information Center
Rappleye, Jeremy
2007-01-01
This book attempts to theorize cross-national attraction by comparing American and Chinese attraction to Japanese education. The study takes a long historical view--spanning roughly from the Meiji Restoration (1868) to today--to determine when and why Japanese education has become attractive to these two countries. It uses a combination of…
Bayesian Logical Data Analysis for the Physical Sciences
NASA Astrophysics Data System (ADS)
Gregory, Phil
2010-05-01
Preface; Acknowledgements; 1. Role of probability theory in science; 2. Probability theory as extended logic; 3. The how-to of Bayesian inference; 4. Assigning probabilities; 5. Frequentist statistical inference; 6. What is a statistic?; 7. Frequentist hypothesis testing; 8. Maximum entropy probabilities; 9. Bayesian inference (Gaussian errors); 10. Linear model fitting (Gaussian errors); 11. Nonlinear model fitting; 12. Markov Chain Monte Carlo; 13. Bayesian spectral analysis; 14. Bayesian inference (Poisson sampling); Appendix A. Singular value decomposition; Appendix B. Discrete Fourier transforms; Appendix C. Difference in two samples; Appendix D. Poisson ON/OFF details; Appendix E. Multivariate Gaussian from maximum entropy; References; Index.
Bayesian statistics in medical devices: innovation sparked by the FDA.
Campbell, Gregory
2011-09-01
Bayesian statistical methodology has been used for more than 10 years in medical device premarket submissions to the U.S. Food and Drug Administration (FDA). A complete list of the publicly available information associated with these FDA applications is presented. In addition to the increasing number of Bayesian methodological papers in the statistical journals, a number of successful Bayesian clinical trials in the biomedical journals have been recently reported. Some challenges that require more methodological development are discussed. The promise of using Bayesian methods for incorporation of prior information as well as for conducting adaptive trials is great.
Bayesian just-so stories in psychology and neuroscience.
Bowers, Jeffrey S; Davis, Colin J
2012-05-01
According to Bayesian theories in psychology and neuroscience, minds and brains are (near) optimal in solving a wide range of tasks. We challenge this view and argue that more traditional, non-Bayesian approaches are more promising. We make 3 main arguments. First, we show that the empirical evidence for Bayesian theories in psychology is weak. This weakness relates to the many arbitrary ways that priors, likelihoods, and utility functions can be altered in order to account for the data that are obtained, making the models unfalsifiable. It further relates to the fact that Bayesian theories are rarely better at predicting data compared with alternative (and simpler) non-Bayesian theories. Second, we show that the empirical evidence for Bayesian theories in neuroscience is weaker still. There are impressive mathematical analyses showing how populations of neurons could compute in a Bayesian manner but little or no evidence that they do. Third, we challenge the general scientific approach that characterizes Bayesian theorizing in cognitive science. A common premise is that theories in psychology should largely be constrained by a rational analysis of what the mind ought to do. We question this claim and argue that many of the important constraints come from biological, evolutionary, and processing (algorithmic) considerations that have no adaptive relevance to the problem per se. In our view, these factors have contributed to the development of many Bayesian "just so" stories in psychology and neuroscience; that is, mathematical analyses of cognition that can be used to explain almost any behavior as optimal.
Dimensionality and Transcultural Specificity of the Sexual Attraction Questionnaire (SAQ).
Fernández, Juan; Quiroga, María Angeles; Icaza, Vanessa J; Escorial, Sergio
2012-03-01
Sexual attraction was considered a component of sexual orientation from the beginning of the second half of the 20th century to present times. However, some recent researchers have studied sexual attraction as an independent field measuring it by the Sexual Attraction Questionnaire (SAQ). This study analyzes sexual attraction through the SAQ in 400 university students from a Peruvian catholic university. These participants -191 women and 209 men- show a very diverse curricular background. The following hypotheses were tested: a) the structure of the SAQ, pointing out two concepts: attraction to men and attraction to women; b) the high inverse correlation between these two concepts or factors; c) the specific impact of this context in sexual attraction: higher percentage of attracted by none of the sexes and lower percentage of attracted to the opposite sex, in comparison with other contexts; and d) the Lippa prediction (2006, 2007), regarding a higher polarization of sexual attraction for men than for women. Results support the first three hypotheses. Clarifications are laid down with regard to the fourth one. Discussion focuses on theoretical and applied advantages of using the SAQ as opposed to the frequent use of a single item of sexual attraction for each sex.
Effects of partner beauty on opposite-sex attractiveness judgments.
Little, Anthony C; Caldwell, Christine A; Jones, Benedict C; DeBruine, Lisa M
2011-12-01
Many studies show mate choice copying effects on mate preferences in non-human species in which individuals follow or copy the mate choices of same-sex conspecifics. Recent studies suggest that social learning also influences mate preferences in humans. Studies on heterosexual humans have focused on rating the attractiveness of potential mates (targets) presented alongside individuals of the opposite sex to the target (models). Here, we examined several different types of pairing to examine how specific social learning is to mate preferences. In Study 1, we replicated a previous effect whereby target faces of the opposite sex to the subject were rated as more attractive when paired with attractive than unattractive partner models of the same sex as the subject. Using the same paired stimuli, Study 2 demonstrated no effect of a paired model if subjects were asked to rate targets who were the same sex as themselves. In Study 3, we used pairs of the same sex, stating the pair were friends, and subjects rated targets of the opposite sex to themselves. Attractive models decreased targets' attractiveness, opposite to the effect in Study 1. Finally, Study 4 examined if attractive versus unattractive non-face stimuli might influence attraction. Unlike in Study 1, pairing with attractive stimuli either had no effect or decreased the attractiveness of paired target face images. These data suggest that social transmission of preferences via pairing with attractive/unattractive images is relatively specific to learning about mate preferences but does not influence attractiveness judgments more generally.
Turner, Wendy C.; Kausrud, Kyrre L.; Krishnappa, Yathin S.; Cromsigt, Joris P. G. M.; Ganz, Holly H.; Mapaure, Isaac; Cloete, Claudine C.; Havarua, Zepee; Küsters, Martina; Getz, Wayne M.; Stenseth, Nils Chr.
2014-01-01
Parasites can shape the foraging behaviour of their hosts through cues indicating risk of infection. When cues for risk co-occur with desired traits such as forage quality, individuals face a trade-off between nutrient acquisition and parasite exposure. We evaluated how this trade-off may influence disease transmission in a 3-year experimental study of anthrax in a guild of mammalian herbivores in Etosha National Park, Namibia. At plains zebra (Equus quagga) carcass sites we assessed (i) carcass nutrient effects on soils and grasses, (ii) concentrations of Bacillus anthracis (BA) on grasses and in soils, and (iii) herbivore grazing behaviour, compared with control sites, using motion-sensing camera traps. We found that carcass-mediated nutrient pulses improved soil and vegetation, and that BA is found on grasses up to 2 years after death. Host foraging responses to carcass sites shifted from avoidance to attraction, and ultimately to no preference, with the strength and duration of these behavioural responses varying among herbivore species. Our results demonstrate that animal carcasses alter the environment and attract grazing hosts to parasite aggregations. This attraction may enhance transmission rates, suggesting that hosts are limited in their ability to trade off nutrient intake with parasite avoidance when relying on indirect cues. PMID:25274365
Potentials-Attract or Likes-Attract in Human Mate Choice in China
He, Qiao-Qiao; Zhang, Zhen; Zhang, Jian-Xin; Wang, Zhi-Guo; Tu, Ying; Ji, Ting; Tao, Yi
2013-01-01
To explain how individuals’ self-perceived long-term mate value influences their mate preference and mate choice, two hypotheses have been presented, which are “potentials-attract” and “likes-attract”, respectively. The potentials-attract means that people choose mates matched with their sex-specific traits indicating reproductive potentials; and the likes-attract means that people choose mates matched with their own conditions. However, the debate about these two hypotheses still remains unsolved. In this paper, we tested these two hypotheses using a human’s actual mate choice data from a Chinese online dating system (called the Baihe website), where 27,183 users of Baihe website are included, in which there are 590 paired couples (1180 individuals) who met each other via the website. Our main results show that not only the relationship between individuals’ own attributes and their self-stated mate preference but also that between individuals’ own attributes and their actual mate choice are more consistent with the likes-attract hypothesis, i.e., people tend to choose mates who are similar to themselves in a variety of attributes. PMID:23565153
Gelation transitions of colloidal systems with bridging attractions
NASA Astrophysics Data System (ADS)
Yuan, Guangcui; Luo, Junhua; Han, Charles C.; Liu, Yun
2016-10-01
Gelation transitions in a colloidal system, where there is a strong reversible attraction between small, soft microgels and large, hard spheres, are systematically investigated. Different from widely studied depletion attraction systems that are also two-component systems, the strong attraction between small solvent and large solute particles introduces bridging attractions between large solute particles. We conclusively demonstrate that the formation of physical gels at the intermediate volume fraction of our bridging attraction system follows more closely with the percolation line that is in stark contrast to what is observed in depletion attraction systems, where the gelation transition is related with the frustrated spinodal separation, not a purely kinetic phenomenon. Our results introduce a different way to control gelation transitions in spherical colloidal systems, and imply that people need to be prudent when generalizing the physical picture of the gelation transitions obtained from systems with different origins of effective attraction as the solvent molecule may play important roles.
Gelation transitions of colloidal systems with bridging attractions.
Yuan, Guangcui; Luo, Junhua; Han, Charles C; Liu, Yun
2016-10-01
Gelation transitions in a colloidal system, where there is a strong reversible attraction between small, soft microgels and large, hard spheres, are systematically investigated. Different from widely studied depletion attraction systems that are also two-component systems, the strong attraction between small solvent and large solute particles introduces bridging attractions between large solute particles. We conclusively demonstrate that the formation of physical gels at the intermediate volume fraction of our bridging attraction system follows more closely with the percolation line that is in stark contrast to what is observed in depletion attraction systems, where the gelation transition is related with the frustrated spinodal separation, not a purely kinetic phenomenon. Our results introduce a different way to control gelation transitions in spherical colloidal systems, and imply that people need to be prudent when generalizing the physical picture of the gelation transitions obtained from systems with different origins of effective attraction as the solvent molecule may play important roles.
The influence of position and context on facial attractiveness.
Rodway, Paul; Schepman, Astrid; Lambert, Jordana
2013-11-01
It has been shown that a person's position in a group influences how that person is evaluated, with people in the middle perceived as more important than people on the fringe of a group. Four experiments examined whether the position of a face, in a line of five faces, influenced facial attractiveness. The middle position influenced the perceived attractiveness of the target face but the direction of this effect depended on the attractiveness of the target and the surrounding faces. Attractive faces were perceived as less attractive when in the middle of unattractive faces, or faces of average attractiveness. Conversely, unattractive faces were perceived as more attractive when in the middle of other unattractive faces. These results have wide implications, suggesting that the more central a stimulus is in a context then the greater the influence of the context on the judgment of that stimulus.
The dynamical crossover in attractive colloidal systems
Mallamace, Francesco; Corsaro, Carmelo; Stanley, H. Eugene; Mallamace, Domenico; Chen, Sow-Hsin
2013-12-07
We study the dynamical arrest in an adhesive hard-sphere colloidal system. We examine a micellar suspension of the Pluronic-L64 surfactant in the temperature (T) and volume fraction (ϕ) phase diagram. According to mode-coupling theory (MCT), this system is characterized by a cusp-like singularity and two glassy phases: an attractive glass (AG) phase and a repulsive glass (RG) phase. The T − ϕ phase diagram of this system as confirmed by a previous series of scattering data also exhibits a Percolation Threshold (PT) line, a reentrant behavior (AG-liquid-RG), and a glass-to-glass transition. The AG phase can be generated out of the liquid phase by using T and ϕ as control parameters. We utilize viscosity and nuclear magnetic resonance (NMR) techniques. NMR data confirm all the characteristic properties of the colloidal system phase diagram and give evidence of the onset of a fractal-like percolating structure at a precise threshold. The MCT scaling laws used to study the shear viscosity as a function of ϕ and T show in both cases a fragile-to-strong liquid glass-forming dynamic crossover (FSC) located near the percolation threshold where the clustering process is fully developed. These results suggest a larger thermodynamic generality for this phenomenon, which is usually studied only as a function of the temperature. We also find that the critical values of the control parameters, coincident with the PT line, define the locus of the FSC. In the region between the FSC and the glass transition lines the system dynamics are dominated by clustering effects. We thus demonstrate that it is possible, using the conceptual framework provided by extended mode-coupling theory, to describe the way a system approaches dynamic arrest, taking into account both cage and hopping effects.
Watkins, Christopher D; Nicholls, Mike J; Batres, Carlota; Xiao, Dengke; Talamas, Sean; Perrett, David I
2017-06-01
Although recent work suggests that opposite-sex facial attractiveness is less salient in memory when individuals are in a committed romantic relationship, romantic relationship quality can vary over time. In light of this, we tested whether activating concerns about romantic relationship quality strengthens memory for attractive faces. Partnered women were exposed briefly to faces manipulated in shape cues to attractiveness before either being asked to think about a moment of emotional closeness or distance in their current relationship. We measured sensitivity in memory for faces as the extent to which they recognized correct versions of studied faces over versions of the same person altered to look either more or less-attractive than their original (i.e., studied) version. Contrary to predictions, high relationship quality strengthened hit rate for faces regardless of the sex or attractiveness of the face. In general, women's memories were more sensitive to attractiveness in women, but were biased toward attractiveness in male faces, both when responding to unfamiliar faces and versions of familiar faces that were more attractive than the original male identity from the learning phase. However, findings varied according to self-rated attractiveness and a psychometric measure of the quality of their current relationship. Attractive women were more sensitive to attractiveness in men, while their less-attractive peers had a stronger bias to remember women as more-attractive and men as less-attractive than their original image respectively. Women in better-quality romantic relationships had stronger positive biases toward, and false memories for, attractive men. Our findings suggest a sophisticated pattern of sensitivity and bias in women's memory for facial cues to quality that varies systematically according to factors that may alter the costs of female mating competition ('market demand') and relationship maintenance.
Bergemann, Kevin J; Amonoo, Jojo A; Song, Byeongseop; Green, Peter F; Forrest, Stephen R
2015-06-10
We find that mixtures of C60 with the wide energy gap, small molecular weight semiconductor bathophenanthroline (BPhen) exhibit a combination of surprisingly high electron conductivity and efficient exciton blocking when employed as buffer layers in organic photovoltaic cells. Photoluminescence quenching measurements show that a 1:1 BPhen/C60 mixed layer has an exciton blocking efficiency of 84 ± 5% compared to that of 100% for a neat BPhen layer. This high blocking efficiency is accompanied by a 100-fold increase in electron conductivity compared with neat BPhen. Transient photocurrent measurements show that charge transport through a neat BPhen buffer is dispersive, in contrast to nondispersive transport in the compound buffer. Interestingly, although the conductivity is high, there is no clearly defined insulating-to-conducting phase transition with increased insulating BPhen fraction. Thus, we infer that C60 undergoes nanoscale (<10 nm domain size) phase segregation even at very high (>80%) BPhen fractions.
Maheshwari, Pankaj N.; Abiola, Olajide O.; Wagaskar, Vinayak G.; Oswal, Ajay T.
2017-01-01
Hydrocele is a very common condition that is simple to evaluate and treat. Management of hydrocele is usually delegated to the junior members of the surgical team. Sometimes this simple condition can spring huge surprises. A 20-year-old man presented with acute onset large, painless fluctuant left hemi-scrotal swelling. Scrotal ultrasonography showed thickened tunica vaginalis. A diagnosis of left hydrocele was made and repair by excision of sac was planned. During the procedure, the sac was found studded with red nodular growths; histopathology reported malignant mesothelioma of tunica vaginalis. Metastatic evaluation showed extensive retroperitoneal lymph nodal involvement. Despite receiving adjuvant chemotherapy with radiotherapy patient died due to extensive metastasis within 16 months. This case is presented for rarity of diagnosis, young age of presentation, absence of etiological factor and rapidly progressive clinical course. PMID:28216946
Vascular legacy: HOPE ADVANCEs to EMPA-REG and LEADER: A Surprising similarity
Kalra, Sanjay; Sahay, Rakesh
2017-01-01
Recently reported cardiovascular outcome studies on empagliflozin (EMPA-REG) and liraglutide (LEADER) have spurred interest in this field of diabetology. This commentary compares and contrasts these studies with two equally important outcome trials conducted using blood pressure lowering agents. A comparison with MICROHOPE (using ramipril) and ADVANCE (using perindopril + indapamide) blood pressure arms throws up interesting facts. The degree of blood pressure lowering, dissociation between cardiovascular and cerebrovascular benefits, and discordance between renal and retinal outcomes are surprisingly similar in these trials, conducted using disparate molecules. The time taken to achieve such benefits is similar for all drugs except empagliflozin. Such discussion helps inform rational and evidence-based choice of therapy and forms the framework for future research. PMID:28217527
Cordes, Thekla; Michelucci, Alessandro; Hiller, Karsten
2015-01-01
Itaconic acid is well known as a precursor for polymer synthesis and has been involved in industrial processes for decades. In a recent surprising discovery, itaconic acid was found to play a role as an immune-supportive metabolite in mammalian immune cells, where it is synthesized as an antimicrobial compound from the citric acid cycle intermediate cis-aconitic acid. Although the immune-responsive gene 1 protein (IRG1) has been associated to immune response without a mechanistic function, the critical link to itaconic acid production through an enzymatic function of this protein was only recently revealed. In this review, we highlight the history of itaconic acid as an industrial and antimicrobial compound, starting with its biotechnological synthesis and ending with its antimicrobial function in mammalian immune cells.
Surprising Alteration of Antibacterial Activity of 5″-Modified Neomycin against Resistant Bacteria
Zhang, Jianjun; Chiang, Fang-I; Wu, Long; Czyryca, Przemyslaw Greg; Li, Ding; Chang, Cheng-Wei Tom
2009-01-01
A facile synthetic protocol for the production of neomycin B derivatives with various modifications at the 5″ position has been developed. Structural activity relationship (SAR) against aminoglycoside resistant bacteria equipped with various aminoglycoside-modifying enzymes (AME's) was investigated. Enzymatic and molecular modeling studies reveal that the superb substrate promiscuity of AME's allows the resistant bacteria to cope with diverse structural modifications despite the observation that several derivatives show enhanced antibacterial activity than the parent neomycin. Surprisingly, when testing synthetic neomycin derivatives against other human pathogens, two leads exhibit prominent activity against both Methicillin-resistant Staphylococcus aureus (MRSA) and vancomycin-resistant enterococci (VRE) that are known to exert high level of resistance against clinically used aminoglycosides. These findings can be extremely useful in developing new aminoglycoside antibiotics against resistant bacteria. Our result also suggests that new biological and antimicrobial activities can be obtained by chemical modifications of old drugs. PMID:19012394
Srokosz, M A; Bryden, H L
2015-06-19
The importance of the Atlantic Meridional Overturning Circulation (AMOC) heat transport for climate is well acknowledged. Climate models predict that the AMOC will slow down under global warming, with substantial impacts, but measurements of ocean circulation have been inadequate to evaluate these predictions. Observations over the past decade have changed that situation, providing a detailed picture of variations in the AMOC. These observations reveal a surprising degree of AMOC variability in terms of the intraannual range, the amplitude and phase of the seasonal cycle, the interannual changes in strength affecting the ocean heat content, and the decline of the AMOC over the decade, both of the latter two exceeding the variations seen in climate models.
El Chichón's "surprise" eruption in 1982: lessons for reducing volcano risk
Tilling, R.I.
2009-01-01
Unfortunately, the eruptions came as an almost total surprise for scientists and government authorities, effectively precluding opportunities to implement timely mitigative countermeasures. During the months before eruption onset, fumarolic activity increased and inhabitants living close to the volcano felt occasional earthquakes, prompting the Chiapas government to request help from the Federal government. Both the Chiapas and Federal governmental actions were slow, and the requested assistance came after the volcano erupted. Perhaps the most important lesson learned from the disastrous outcome at El Chichón is that its decreased activity (29 March–2 April) should not have been assumed by the senior scientist on site—and the military authorities acting on his advice—to signal the end of eruption. While the 1982 eruptions caused a national tragedy, they also fostered multidisciplinary studies of eruptive phenomena, not only at El Chichón but also other explosive volcanoes in the world.
Zhang, Chendong; Chen, Yuxuan; Johnson, Amber; Li, Ming-Yang; Li, Lain-Jong; Mende, Patrick C; Feenstra, Randall M; Shih, Chih-Kang
2015-10-14
By using a comprehensive form of scanning tunneling spectroscopy, we have revealed detailed quasi-particle electronic structures in transition metal dichalcogenides, including the quasi-particle gaps, critical point energy locations, and their origins in the Brillouin zones. We show that single layer WSe2 surprisingly has an indirect quasi-particle gap with the conduction band minimum located at the Q-point (instead of K), albeit the two states are nearly degenerate. We have further observed rich quasi-particle electronic structures of transition metal dichalcogenides as a function of atomic structures and spin-orbit couplings. Such a local probe for detailed electronic structures in conduction and valence bands will be ideal to investigate how electronic structures of transition metal dichalcogenides are influenced by variations of local environment.
Measuring the operational efficiency of individual theme park attractions.
Kim, Changhee; Kim, Soowook
2016-01-01
This study assesses the operation efficiency of theme park attractions using the data envelopment analysis, utilizing actual data on 15 attractions at Samsung Everland located in Yongin-si, Republic of Korea. In particular, this study identifies crowding and waiting time as one of the main causes of visitor's satisfaction, and analyzes the efficiency of individual attractions in terms of waiting time. The installation area, installation cost, and annual repair cost are set as input factors and the number of annual users and customer satisfaction as output factors. The results show that the roller coaster-type attractions were less efficient than other types of attractions while rotating-type attractions were relatively more efficient. However, an importance performance analysis on individual attraction's efficiency and satisfaction showed that operational efficiency should not be the sole consideration in attraction installation. In addition, the projection points for input factors for efficient use of attractions and the appropriate reference set for benchmarking are provided as guideline for attraction efficiency management.
Is homophobia associated with an implicit same-sex attraction?
Macinnis, Cara C; Hodson, Gordon
2013-01-01
Some theorists propose that homophobia stems from underlying same-sex attraction. A few studies have tested this hypothesis, yet without a clear measure of implicit sexual attraction, producing mixed results. For the first time, we test this attraction-based account of homophobia among both men and women using an implicit measure of sexual attraction. No evidence of an attraction-based account of homophobia emerged. Instead, implicit same-sex attraction was related to positive evaluations of gay men and lesbians among female participants. Even in targeted analyses examining the relation between implicit same-sex attraction and homosexual evaluations among only those theoretically most likely to demonstrate an attraction-based homophobic effect, implicit same-sex attraction was not associated with evaluations of homosexuals or was associated with more positive evaluations of homosexuals. In addition, explicit same-sex attraction was related to positive evaluations of gay men and lesbians for male participants. These results are more in keeping with the attitude-similarity effect (i.e., people like, rather than dislike, similar others).
Accurate Biomass Estimation via Bayesian Adaptive Sampling
NASA Astrophysics Data System (ADS)
Wheeler, K.; Knuth, K.; Castle, P.
2005-12-01
Typical estimates of standing wood derived from remote sensing sources take advantage of aggregate measurements of canopy heights (e.g. LIDAR) and canopy diameters (segmentation of IKONOS imagery) to obtain a wood volume estimate by assuming homogeneous species and a fixed function that returns volume. The validation of such techniques use manually measured diameter at breast height records (DBH). Our goal is to improve the accuracy and applicability of biomass estimation methods to heterogeneous forests and transitional areas. We are developing estimates with quantifiable uncertainty using a new form of estimation function, active sampling, and volumetric reconstruction image rendering for species specific mass truth. Initially we are developing a Bayesian adaptive sampling method for BRDF associated with the MISR Rahman model with respect to categorical biomes. This involves characterizing the probability distributions of the 3 free parameters of the Rahman model for the 6 categories of biomes used by MISR. Subsequently, these distributions can be used to determine the optimal sampling methodology to distinguish biomes during acquisition. We have a remotely controlled semi-autonomous helicopter that has stereo imaging, lidar, differential GPS, and spectrometers covering wavelengths from visible to NIR. We intend to automatically vary the way points of the flight path via the Bayesian adaptive sampling method. The second critical part of this work is in automating the validation of biomass estimates via using machine vision techniques. This involves taking 2-D pictures of trees of known species, and then via Bayesian techniques, reconstructing 3-D models of the trees to estimate the distribution moments associated with wood volume. Similar techniques have been developed by the medical imaging community. This then provides probability distributions conditional upon species. The final part of this work is in relating the BRDF actively sampled measurements to species