Of Bits and Wows: A Bayesian Theory of Surprise with Applications to Attention
Baldi, Pierre; Itti, Laurent
2010-01-01
The amount of information contained in a piece of data can be measured by the effect this data has on its observer. Fundamentally, this effect is to transform the observer's prior beliefs into posterior beliefs, according to Bayes theorem. Thus the amount of information can be measured in a natural way by the distance (relative entropy) between the prior and posterior distributions of the observer over the available space of hypotheses. This facet of information, termed “surprise”, is important in dynamic situations where beliefs change, in particular during learning and adaptation. Surprise can often be computed analytically, for instance in the case of distributions from the exponential family, or it can be numerically approximated. During sequential Bayesian learning, surprise decreases like the inverse of the number of training examples. Theoretical properties of surprise are discussed, in particular how it differs and complements Shannon's definition of information. A computer vision neural network architecture is then presented capable of computing surprise over images and video stimuli. Hypothesizing that surprising data ought to attract natural or artificial attention systems, the output of this architecture is used in a psychophysical experiment to analyze human eye movements in the presence of natural video stimuli. Surprise is found to yield robust performance at predicting human gaze (ROC-like ordinal dominance score ∼ 0.7 compared to ∼ 0.8 for human inter-observer repeatability, ∼ 0.6 for simpler intensity contrast-based predictor, and 0.5 for chance). The resulting theory of surprise is applicable across different spatio-temporal scales, modalities, and levels of abstraction. PMID:20080025
ERIC Educational Resources Information Center
Adler, Jonathan E.
2008-01-01
Surprise is of great value for learning, especially in cases where deep-seated preconceptions and assumptions are upset by vivid demonstrations. In this essay, Jonathan Adler explores the ways in which surprise positively affects us and serves as a valuable tool for motivating learning. Adler considers how students' attention is aroused and…
Surprise Calculator: Estimating relative entropy and Surprise between samples
NASA Astrophysics Data System (ADS)
Seehars, Sebastian
2016-05-01
The Surprise is a measure for consistency between posterior distributions and operates in parameter space. It can be used to analyze either the compatibility of separately analyzed posteriors from two datasets, or the posteriors from a Bayesian update. The Surprise Calculator estimates relative entropy and Surprise between two samples, assuming they are Gaussian. The software requires the R package CompQuadForm to estimate the significance of the Surprise, and rpy2 to interface R with Python.
Surprise beyond prediction error
Chumbley, Justin R; Burke, Christopher J; Stephan, Klaas E; Friston, Karl J; Tobler, Philippe N; Fehr, Ernst
2014-01-01
Surprise drives learning. Various neural “prediction error” signals are believed to underpin surprise-based reinforcement learning. Here, we report a surprise signal that reflects reinforcement learning but is neither un/signed reward prediction error (RPE) nor un/signed state prediction error (SPE). To exclude these alternatives, we measured surprise responses in the absence of RPE and accounted for a host of potential SPE confounds. This new surprise signal was evident in ventral striatum, primary sensory cortex, frontal poles, and amygdala. We interpret these findings via a normative model of surprise. PMID:24700400
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
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.
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. PMID:27116247
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.
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…
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.
Thornhill; Gangestad
1999-12-01
Humans in societies around the world discriminate between potential mates on the basis of attractiveness in ways that can dramatically affect their lives. From an evolutionary perspective, a reasonable working hypothesis is that the psychological mechanisms underlying attractiveness judgments are adaptations that have evolved in the service of choosing a mate so as to increase gene propagation throughout evolutionary history. The main hypothesis that has directed evolutionary psychology research into facial attractiveness is that these judgments reflect information about what can be broadly defined as an individual's health. This has been investigated by examining whether attractiveness judgments show special design for detecting cues that allow us to make assessments of overall phenotypic condition. This review examines the three major lines of research that have been pursued in order to answer the question of whether attractiveness reflects non-obvious indicators of phenotypic condition. These are studies that have examined facial symmetry, averageness, and secondary sex characteristics as hormone markers. PMID:10562724
ERIC Educational Resources Information Center
Meyer, Donald L.
Bayesian statistical methodology and its possible uses in the behavioral sciences are discussed in relation to the solution of problems in both the use and teaching of fundamental statistical methods, including confidence intervals, significance tests, and sampling. The Bayesian model explains these statistical methods and offers a consistent…
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…
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.
NASA Astrophysics Data System (ADS)
Oviatt, Eric; Patsiaouris, Konstantinos; Denardo, Bruce
2009-11-01
A sound source of finite size produces a diverging traveling wave in an unbounded fluid. A rigid body that is small compared to the wavelength experiences an attractive radiation force (toward the source). An attractive force is also exerted on the fluid itself. The effect can be demonstrated with a styrofoam ball suspended near a loudspeaker that is producing sound of high amplitude and low frequency (for example, 100 Hz). The behavior can be understood and roughly calculated as a time-averaged Bernoulli effect. A rigorous scattering calculation yields a radiation force that is within a factor of two of the Bernoulli result. For a spherical wave, the force decreases as the inverse fifth power of the distance from the source. Applications of the phenomenon include ultrasonic filtration of liquids and the growth of supermassive black holes that emit sound waves in a surrounding plasma. An experiment is being conducted in an anechoic chamber with a 1-inch diameter aluminum ball that is suspended from an analytical balance. Directly below the ball is a baffled loudspeaker that exerts an attractive force that is measured by the balance.
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. PMID:15559576
Thomas, J.H.
2003-05-22
The data from RHIC have produced many unanticipated results. I will describe a few of the surprises that occur in the soft spectra while my colleagues at this conference will summarize the hard spectra. One particularly important discovery is that properties of the initial state have an impact on the final state in relativistic heavy ion collisions. Another important discovery is that the collision zone is opaque to the passage of hadrons and perhaps even partons. And finally, the data tell us very precisely where the colliding systems hadronize on the phase diagram for nuclear matter.
Burr, M.T.
1995-10-01
Brazil faces a need to expand electric generation capacity by 25 gigawatts (GW) through the year 2004. This means that about 10,350 MW plants need to be installed during each of the next eight years. The situation is particularly serious in the populous, industrialized south and southeastern regions. As a result, the new government is taking measures to attract private power developers and accelerate privatization. This progress is encouraging, but a number of fundamental issues must be addressed before IPPs can begin meeting the power demands. Stumbling blocks remain: regulatory hurdles, market imbalances, credit worthiness concerns and a history of political and economic volatility.
Small is beautiful: Surprising nanoparticles.
Duchêne, Dominique; Gref, Ruxandra
2016-04-11
In the preparation of nanoparticles for drug delivery, it is well known that their size as well as their surface decorations can play a major role in interaction with living media. It is less known that their shape and internal structure can interplay with cellular and in vivo fate. The scientific literature is full of a large variety of surprising terms referring to their shape and structure. The aim of this review is to present some examples of the most often encountered surprising nanoparticles prepared and usable in the pharmaceutical technology domain. They are presented in two main groups related to their physical aspects: 1) smooth surface particles, such as Janus particles, "snowmen", "dumbbells", "rattles", and "onions" and 2) branched particles, such as "flowers", "stars" and "urchins". The mode of preparation and potential applications are briefly presented. The topic has a serious, wider importance, namely in opportunity these structures have to allow exploration of the role of shape and structure on the utility (and perhaps toxicity) of these nanostructures. PMID:26902723
Researchers Uncover Surprises about Celiac Disease
... news/fullstory_159122.html Researchers Uncover Surprises About Celiac Disease Immune condition most common among people descended ... has revealed some surprising findings about who develops celiac disease in the United States. The study found ...
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…
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.
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
Neural dynamics of prediction and surprise in infants
Kouider, Sid; Long, Bria; Le Stanc, Lorna; Charron, Sylvain; Fievet, Anne-Caroline; Barbosa, Leonardo S.; Gelskov, Sofie V.
2015-01-01
Prior expectations shape neural responses in sensory regions of the brain, consistent with a Bayesian predictive coding account of perception. Yet, it remains unclear whether such a mechanism is already functional during early stages of development. To address this issue, we study how the infant brain responds to prediction violations using a cross-modal cueing paradigm. We record electroencephalographic responses to expected and unexpected visual events preceded by auditory cues in 12-month-old infants. We find an increased response for unexpected events. However, this effect of prediction error is only observed during late processing stages associated with conscious access mechanisms. In contrast, early perceptual components reveal an amplification of neural responses for predicted relative to surprising events, suggesting that selective attention enhances perceptual processing for expected events. Taken together, these results demonstrate that cross-modal statistical regularities are used to generate predictions that differentially influence early and late neural responses in infants. PMID:26460901
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 diagnostic theory using a programmable pocket calculator.
Edwards, F H; Graeber, G M
1987-01-01
A programmable pocket calculator program has been written to serve as an aid in diagnosis. The program uses a Bayesian statistical algorithm to calculate the relative probability of two diagnostic alternatives. The ability to carry out Bayesian statistical calculations at the bedside should make the use of such techniques more attractive to clinical practitioners. PMID:3319380
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…
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. PMID:27375438
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.
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.
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.
Bayesianism Versus Confirmation
NASA Astrophysics Data System (ADS)
Strevens, Michael
2014-03-01
The usual Bayesian approach to understanding the confirmation of scientific theories is inadequate. The problem lies not with Bayesian epistemology, but with a simplistic equation of the subjective, individualistic evidential relevance relation that Bayesianism attempts to capture and the more objective relevance relation of confirmation.
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.
An Ordinary but Surprisingly Powerful Theorem
ERIC Educational Resources Information Center
Sultan, Alan
2009-01-01
Being a mathematician, the author started to wonder if there are any theorems in mathematics that seem very ordinary on the outside, but when applied, have surprisingly far reaching consequences. The author thought about this and came up with the following unlikely candidate which follows immediately from the definition of the area of a rectangle…
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…
Attractiveness and School Achievement
ERIC Educational Resources Information Center
Salvia, John; And Others
1977-01-01
The purpose of this study was to ascertain the relationship between rated attractiveness and two measures of school performance. Attractive children received significantly higher report cards and, to some degree, higher achievement test scores than their unattractive peers. (Author)
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.
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.
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.
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. PMID:25754528
The alkali metals: 200 years of surprises.
Dye, James L
2015-03-13
Alkali metal compounds have been known since antiquity. In 1807, Sir Humphry Davy surprised everyone by electrolytically preparing (and naming) potassium and sodium metals. In 1808, he noted their interaction with ammonia, which, 100 years later, was attributed to solvated electrons. After 1960, pulse radiolysis of nearly any solvent produced solvated electrons, which became one of the most studied species in chemistry. In 1968, alkali metal solutions in amines and ethers were shown to contain alkali metal anions in addition to solvated electrons. The advent of crown ethers and cryptands as complexants for alkali cations greatly enhanced alkali metal solubilities. This permitted us to prepare a crystalline salt of Na(-) in 1974, followed by 30 other alkalides with Na(-), K(-), Rb(-) and Cs(-) anions. This firmly established the -1 oxidation state of alkali metals. The synthesis of alkalides led to the crystallization of electrides, with trapped electrons as the anions. Electrides have a variety of electronic and magnetic properties, depending on the geometries and connectivities of the trapping sites. In 2009, the final surprise was the experimental demonstration that alkali metals under high pressure lose their metallic character as the electrons are localized in voids between the alkali cations to become high-pressure electrides! PMID:25666067
Assertiveness and Physical Attractiveness.
ERIC Educational Resources Information Center
Kleim, David M.; And Others
Earlier research investigating the relationship between physical attractiveness and assertiveness found that physically attractive females were more assertive than other females. To investigate this relationship further and to broaden the scope of the study, 69 students were videotaped in groups of five to ten while responding to open-ended…
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…
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…
Mallick, Himel; Yi, Nengjun
2016-01-01
Park and Casella (2008) provided the Bayesian lasso for linear models by assigning scale mixture of normal (SMN) priors on the parameters and independent exponential priors on their variances. In this paper, we propose an alternative Bayesian analysis of the lasso problem. A different hierarchical formulation of Bayesian lasso is introduced by utilizing the scale mixture of uniform (SMU) representation of the Laplace density. We consider a fully Bayesian treatment that leads to a new Gibbs sampler with tractable full conditional posterior distributions. Empirical results and real data analyses show that the new algorithm has good mixing property and performs comparably to the existing Bayesian method in terms of both prediction accuracy and variable selection. An ECM algorithm is provided to compute the MAP estimates of the parameters. Easy extension to general models is also briefly discussed.
Stroke Recovery: Surprising Influences and Residual Consequences
Hillis, Argye E.; Tippett, Donna C.
2014-01-01
There is startling individual variability in the degree to which people recover from stroke and the duration of time over which recovery of some symptoms occurs. There are a variety of mechanisms of recovery from stroke which take place at distinct time points after stroke and are influenced by different variables. We review recent studies from our laboratory that unveil some surprising findings, such as the role of education in chronic recovery. We also report data showing that the consequences that most plague survivors of stroke and their caregivers are loss of high level cortical functions, such as empathy or written language. These results have implications for rehabilitation and management of stroke. PMID:25844378
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.
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. PMID:26776199
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...
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. PMID:9831888
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. PMID:26966228
Physical Attractiveness and Courtship
ERIC Educational Resources Information Center
Silverman, Irwin
1971-01-01
This study shows a high and disquieting degree of similarity in physical attractiveness between dating partners, and suggests also that more similar partners tend to form stronger romantic attachments. (Author)
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
Surprises in low-dimensional correlated systems
NASA Astrophysics Data System (ADS)
Lin, Hsiu-Hau
In this thesis, correlation effects in low-dimensional systems were studied. In particular, we focus on two systems: a point-contact in the quantum-Hall regime under the influence of ac drive and quasi-one-dimensional ladder materials with generic interactions in weak coupling. Powerful techniques, including renormalization group, quantum field theory, operator product expansions, bosonization,...etc., were employed to extract surprising physics out of these strongly fluctuating systems. We first study the effect of an ac drive on the current-voltage (I-V) characteristics of a tunnel junction between two fractional Quantum Hall fluids at filling nu-1 an odd integer. In a semi-classical limit, the tunneling current exhibits mode-locking, which corresponds to plateaus in the I-V curve at integer multiples of I = ef , with f the ac drive frequency. However, the full quantum model exhibits rounded plateaus centered around the quantized current values due to quantum fluctuations. The locations of these plateaus can serve as an indirect hint of fractional charges. Switching attentions to quasi-one-dimensional coupled-chain systems, we present a systematic weak-coupling renormalization group (RG) technique and find that generally broad regions of the phase space of the ladder materials are unstable to pairing, usually with approximate d-wave symmetry. The dimensional crossovers from 1D to 2D were also discussed. Carbon nanotubes as possible candidates that display such unconventional pairing and interesting physics in weak coupling were discussed. Quite surprisingly, a hidden symmetry was found in the weakly-coupled two-leg ladder. A perturbative renormalization group analysis reveals that at half-filling the model scales onto an exactly soluble SO(8) symmetric Gross-Neveu model. Integrability of the Gross-Neveu model is employed to extract the exact energies, degeneracies and quantum numbers of all the low energy excited states, which fall into degenerate SO(8
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.
Long-term evolution is surprisingly predictable in lattice proteins
Palmer, Michael E.; Moudgil, Arnav; Feldman, Marcus W.
2013-01-01
It has long been debated whether natural selection acts primarily upon individual organisms, or whether it also commonly acts upon higher-level entities such as lineages. Two arguments against the effectiveness of long-term selection on lineages have been (i) that long-term evolutionary outcomes will not be sufficiently predictable to support a meaningful long-term fitness and (ii) that short-term selection on organisms will almost always overpower long-term selection. Here, we use a computational model of protein folding and binding called ‘lattice proteins’. We quantify the long-term evolutionary success of lineages with two metrics called the k-fitness and k-survivability. We show that long-term outcomes are surprisingly predictable in this model: only a small fraction of the possible outcomes are ever realized in multiple replicates. Furthermore, the long-term fitness of a lineage depends only partly on its short-term fitness; other factors are also important, including the ‘evolvability’ of a lineage—its capacity to produce adaptive variation. In a system with a distinct short-term and long-term fitness, evolution need not be ‘short-sighted’: lineages may be selected for their long-term properties, sometimes in opposition to short-term selection. Similar evolutionary basins of attraction have been observed in vivo, suggesting that natural biological lineages will also have a predictive long-term fitness. PMID:23466559
NASA Astrophysics Data System (ADS)
Granade, Christopher; Combes, Joshua; Cory, D. G.
2016-03-01
In recent years, Bayesian methods have been proposed as a solution to a wide range of issues in quantum state and process tomography. State-of-the-art Bayesian tomography solutions suffer from three problems: numerical intractability, a lack of informative prior distributions, and an inability to track time-dependent processes. Here, we address all three problems. First, we use modern statistical methods, as pioneered by Huszár and Houlsby (2012 Phys. Rev. A 85 052120) and by Ferrie (2014 New J. Phys. 16 093035), to make Bayesian tomography numerically tractable. Our approach allows for practical computation of Bayesian point and region estimators for quantum states and channels. Second, we propose the first priors on quantum states and channels that allow for including useful experimental insight. Finally, we develop a method that allows tracking of time-dependent states and estimates the drift and diffusion processes affecting a state. We provide source code and animated visual examples for our methods.
Setting Up Surprises: Should We or Shouldn't We?
ERIC Educational Resources Information Center
Back, Jenni
2007-01-01
In this article, the author discusses the advantages and the disadvantages of using surprise elements in teaching mathematics. According to the author, there are three key ideas concerning the element of surprise: (1) The ethical aspects of teachers' manipulation of their students in order to construct surprise; (2) Every mathematical task…
NASA Astrophysics Data System (ADS)
von Toussaint, Udo
2011-07-01
Bayesian inference provides a consistent method for the extraction of information from physics experiments even in ill-conditioned circumstances. The approach provides a unified rationale for data analysis, which both justifies many of the commonly used analysis procedures and reveals some of the implicit underlying assumptions. This review summarizes the general ideas of the Bayesian probability theory with emphasis on the application to the evaluation of experimental data. As case studies for Bayesian parameter estimation techniques examples ranging from extra-solar planet detection to the deconvolution of the apparatus functions for improving the energy resolution and change point estimation in time series are discussed. Special attention is paid to the numerical techniques suited for Bayesian analysis, with a focus on recent developments of Markov chain Monte Carlo algorithms for high-dimensional integration problems. Bayesian model comparison, the quantitative ranking of models for the explanation of a given data set, is illustrated with examples collected from cosmology, mass spectroscopy, and surface physics, covering problems such as background subtraction and automated outlier detection. Additionally the Bayesian inference techniques for the design and optimization of future experiments are introduced. Experiments, instead of being merely passive recording devices, can now be designed to adapt to measured data and to change the measurement strategy on the fly to maximize the information of an experiment. The applied key concepts and necessary numerical tools which provide the means of designing such inference chains and the crucial aspects of data fusion are summarized and some of the expected implications are highlighted.
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.
Surprising decline in Iran's growth rates.
Roudi, F
1997-11-01
According to Iran's 1996 census, the country's population was 60 million, about 6-7 million people fewer than estimates used by the UN and other international organizations. These findings surprised Iranian demographers and have been examined with skepticism outside of the country. However, if Iran's 1986 and 1996 censuses are comparable and children were not undercounted, these results indicate a remarkable decline in fertility. The proportion of Iran's population under age 5 years fell from 18% in 1986 to 10% in 1996. An Institut National d'Etudes Demographiques, Paris, study published in 1996 estimated that Iran's total fertility rate (TFR) fell from an average of 6.2 children/woman in 1986 to 3.5 in 1993. However, based upon analyses of sample surveys, the Iranian government's health ministry reported that the TFR dropped from 5.0 in 1991 to 3.3 in 1995. Irrespective of questions over the magnitude of Iran's fertility decline, it is clear that the Iranian government is committed to limiting population growth. The UN Population Fund considers Iran's family planning program to be one of the world's best-functioning, with the Ministry of Health Care and Medical Education providing free contraceptives. A bill was passed in 1993 which penalizes couples who have more than 3 children and posters around the country encourage the one- or two-child family. Iran's family planning program is integrated into the national primary health care system and provides a broad range of reproductive health services to women. The program is also the only one in the region which promotes both male and female sterilization. PMID:12321257
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.
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.
Correlates of Interpersonal Attraction.
ERIC Educational Resources Information Center
Prisbell, Marshall
A study assessed the relationship of the independent variables of interpersonal attraction to the dependent variables of feeling good, relational safety, and uncertainty level. Subjects were 75 elementary and secondary school teachers, 61 communication students, 18 child development professionals, and 8 service club members. Each subject completed…
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…
Attractive characteristics of mirrors
NASA Astrophysics Data System (ADS)
Post, R. F.; Ryutov, D. D.
1994-12-01
A summary of the attractive characteristics of mirror devices is presented. Recent progress in development of axisymmetric mirror devices is described. Potentialities of mirrors as a basis for D(3)He fusion power generators and high-flux neutron sources for fusion material tests are discussed.
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 adolescents.…
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.
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…
Interocular conflict attracts attention.
Paffen, Chris L E; Hessels, Roy S; Van der Stigchel, Stefan
2012-02-01
During binocular rivalry, perception alternates.between dissimilar images presented dichoptically. Since.its discovery, researchers have debated whether the phenomenon is subject to attentional control. While it is now clear that attentional control over binocular rivalry is possible, the opposite is less evident: Is interocular conflict (i.e., the situation leading to binocular rivalry) able to attract attention?In order to answer this question, we used a change blindness paradigm in which observers looked for salient changes in two alternating frames depicting natural scenes. Each frame contained two images: one for the left and one for the right eye. Changes occurring in a single image (monocular) were detected faster than those occurring in both images (binocular). In addition,monocular change detection was also faster than detection in fused versions of the changed and unchanged regions. These results show that interocular conflict is capable of attracting attention, since it guides visual attention toward salient changes that otherwise would remain unnoticed for longer. The results of a second experiment indicated that interocular conflict attracts attention during the first phase of presentation, a phase during which the stimulus is abnormally fused [added]. PMID:22167536
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.
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.
Old Star's "Rebirth" Gives Astronomers Surprises
NASA Astrophysics Data System (ADS)
2005-04-01
Astronomers using the National Science Foundation's Very Large Array (VLA) radio telescope are taking advantage of a once-in-a-lifetime opportunity to watch an old star suddenly stir back into new activity after coming to the end of its normal life. Their surprising results have forced them to change their ideas of how such an old, white dwarf star can re-ignite its nuclear furnace for one final blast of energy. Sakurai's Object Radio/Optical Images of Sakurai's Object: Color image shows nebula ejected thousands of years ago. Contours indicate radio emission. Inset is Hubble Space Telescope image, with contours indicating radio emission; this inset shows just the central part of the region. CREDIT: Hajduk et al., NRAO/AUI/NSF, ESO, StSci, NASA Computer simulations had predicted a series of events that would follow such a re-ignition of fusion reactions, but the star didn't follow the script -- events moved 100 times more quickly than the simulations predicted. "We've now produced a new theoretical model of how this process works, and the VLA observations have provided the first evidence supporting our new model," said Albert Zijlstra, of the University of Manchester in the United Kingdom. Zijlstra and his colleagues presented their findings in the April 8 issue of the journal Science. The astronomers studied a star known as V4334 Sgr, in the constellation Sagittarius. It is better known as "Sakurai's Object," after Japanese amateur astronomer Yukio Sakurai, who discovered it on February 20, 1996, when it suddenly burst into new brightness. At first, astronomers thought the outburst was a common nova explosion, but further study showed that Sakurai's Object was anything but common. The star is an old white dwarf that had run out of hydrogen fuel for nuclear fusion reactions in its core. Astronomers believe that some such stars can undergo a final burst of fusion in a shell of helium that surrounds a core of heavier nuclei such as carbon and oxygen. However, the
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
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
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
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
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
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.
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
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
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…
NASA Astrophysics Data System (ADS)
Loredo, Thomas J.
2004-04-01
I describe a framework for adaptive scientific exploration based on iterating an Observation-Inference-Design cycle that allows adjustment of hypotheses and observing protocols in response to the results of observation on-the-fly, as data are gathered. The framework uses a unified Bayesian methodology for the inference and design stages: Bayesian inference to quantify what we have learned from the available data and predict future data, and Bayesian decision theory to identify which new observations would teach us the most. When the goal of the experiment is simply to make inferences, the framework identifies a computationally efficient iterative ``maximum entropy sampling'' strategy as the optimal strategy in settings where the noise statistics are independent of signal properties. Results of applying the method to two ``toy'' problems with simulated data-measuring the orbit of an extrasolar planet, and locating a hidden one-dimensional object-show the approach can significantly improve observational efficiency in settings that have well-defined nonlinear models. I conclude with a list of open issues that must be addressed to make Bayesian adaptive exploration a practical and reliable tool for optimizing scientific exploration.
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.
Zhao, Tianshan; Zhou, Jian; Wang, Qian; Jena, Puru
2016-07-21
Using multiscale first-principles calculations, we show that two interacting negatively charged B12I9(-) monoanions not only attract, in defiance of the Coulomb's law, but also the energy barrier at 400 K is small enough that these two moieties combine to form a stable B24I18(2-) moiety. Ab initio molecular dynamics simulations further confirm its stability up to 1500 K. Studies of other B12X9(-) (X = Br, Cl, F, H, Au, CN) show that while all of these B24X18(2-) moieties are stable against dissociation, the energy barrier, with the exception of B24Au18(2-), is large so as to hinder their experimental observation. Our results explain the recent experimental observation of the "spontaneous" formation of B24I18(2-) in an ion trap. A simple model based upon electrostatics shows that this unusual behavior is due to competition between the attractive dipole-dipole interaction caused by the aspherical shape of the particle and the repulsive interaction between the like charges. PMID:27351125
Surprise and Sense Making: Undergraduate Placement Experiences in SMEs
ERIC Educational Resources Information Center
Walmsley, Andreas; Thomas, Rhodri; Jameson, Stephanie
2006-01-01
Purpose: This paper seeks to explore undergraduate placement experiences in tourism and hospitality SMEs, focusing on the notions of surprise and sense making. It aims to argue that surprises and sense making are important elements not only of the adjustment process when entering new work environments, but also of the learning experience that…
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…
Understanding and predicting ecological dynamics: are major surprises inevitable?
Doak, Daniel F; Estes, James A; Halpern, Benjamin S; Jacob, Ute; Lindberg, David R; Lovvorn, James; Monson, Daniel H; Tinker, M Timothy; Williams, Terrie M; Wootton, J Timothy; Carroll, Ian; Emmerson, Mark; Micheli, Fiorenza; Novak, Mark
2008-04-01
Ecological surprises, substantial and unanticipated changes in the abundance of one or more species that result from previously unsuspected processes, are a common outcome of both experiments and observations in community and population ecology. Here, we give examples of such surprises along with the results of a survey of well-established field ecologists, most of whom have encountered one or more surprises over the course of their careers. Truly surprising results are common enough to require their consideration in any reasonable effort to characterize nature and manage natural resources. We classify surprises as dynamic-, pattern-, or intervention-based, and we speculate on the common processes that cause ecological systems to so often surprise us. A long-standing and still growing concern in the ecological literature is how best to make predictions of future population and community dynamics. Although most work on this subject involves statistical aspects of data analysis and modeling, the frequency and nature of ecological surprises imply that uncertainty cannot be easily tamed through improved analytical procedures, and that prudent management of both exploited and conserved communities will require precautionary and adaptive management approaches. PMID:18481520
Neural mechanism of unconscious perception of surprised facial expression.
Duan, Xujun; Dai, Qian; Gong, Qiyong; Chen, Huafu
2010-08-01
Previous functional neuroimaging studies have uncovered partly separable neural substrates for perceiving different facial expressions presented below the level of conscious awareness. However, as one of the six basic emotions, the neural mechanism of unconsciously perceiving surprised faces has not yet been investigated. Using a backward masking procedure, we studied the neural activities in response to surprised faces presented below the threshold of conscious visual perception by means of functional magnetic resonance imaging (fMRI). Eighteen healthy adults were scanned while viewing surprised faces, which presented for 33 ms and immediately "masked" by a neutral face for 467 ms. As a control, they viewed masked happy or neutral faces as well. In comparison to both control conditions, masked surprised faces yielded significantly greater activation in the parahippocampal gyrus and fusiform gyrus, which associated previously with novelty detection. In the present study, automatic activation of these areas to masked surprised faces was investigated as a function of individual differences in the ability of identifying and differentiating one's emotions, as assessed by the 20-item Toronto Alexithymia Scale (TAS-20). The correlation results showed that, the subscale, Difficulty Identifying Feelings, was negatively correlated with the neural response of these areas to masked surprised faces, which suggest that decreased activation magnitude in specific brain regions may reflect increased difficulties in recognizing one's emotions in everyday life. Additionally, we confirmed activation of the right amygdala and right thalamus to the masked surprised faces, which was previously proved to be involved in the unconscious emotional perception system. PMID:20398771
Physical attractiveness and personality development.
Shea, J; Crossman, S M; Adams, G R
1978-05-01
A test of the relationship between physical attractiveness and ego development was completed through an interview study of 294 men and women college students. Ss responded to personality measures assessing identity formation, locus of control, and ego functioning and were rated on facial attractiveness and body form scales. Contrary to the physical attractiveness stereotype, attractive and unattractive Ss did not differ in their personality styles. PMID:650605
Bayesian Magic in Asteroseismology
NASA Astrophysics Data System (ADS)
Kallinger, T.
2015-09-01
Only a few years ago asteroseismic observations were so rare that scientists had plenty of time to work on individual data sets. They could tune their algorithms in any possible way to squeeze out the last bit of information. Nowadays this is impossible. With missions like MOST, CoRoT, and Kepler we basically drown in new data every day. To handle this in a sufficient way statistical methods become more and more important. This is why Bayesian techniques started their triumph march across asteroseismology. I will go with you on a journey through Bayesian Magic Land, that brings us to the sea of granulation background, the forest of peakbagging, and the stony alley of model comparison.
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,"…
Efficient Bayesian Phase Estimation
NASA Astrophysics Data System (ADS)
Wiebe, Nathan; Granade, Chris
2016-07-01
We introduce a new method called rejection filtering that we use to perform adaptive Bayesian phase estimation. Our approach has several advantages: it is classically efficient, easy to implement, achieves Heisenberg limited scaling, resists depolarizing noise, tracks time-dependent eigenstates, recovers from failures, and can be run on a field programmable gate array. It also outperforms existing iterative phase estimation algorithms such as Kitaev's method.
Efficient Bayesian Phase Estimation.
Wiebe, Nathan; Granade, Chris
2016-07-01
We introduce a new method called rejection filtering that we use to perform adaptive Bayesian phase estimation. Our approach has several advantages: it is classically efficient, easy to implement, achieves Heisenberg limited scaling, resists depolarizing noise, tracks time-dependent eigenstates, recovers from failures, and can be run on a field programmable gate array. It also outperforms existing iterative phase estimation algorithms such as Kitaev's method. PMID:27419551
NASA Astrophysics Data System (ADS)
Wiegerinck, Wim; Schoenaker, Christiaan; Duane, Gregory
2016-04-01
Recently, methods for model fusion by dynamically combining model components in an interactive ensemble have been proposed. In these proposals, fusion parameters have to be learned from data. One can view these systems as parametrized dynamical systems. We address the question of learnability of dynamical systems with respect to both short term (vector field) and long term (attractor) behavior. In particular we are interested in learning in the imperfect model class setting, in which the ground truth has a higher complexity than the models, e.g. due to unresolved scales. We take a Bayesian point of view and we define a joint log-likelihood that consists of two terms, one is the vector field error and the other is the attractor error, for which we take the L1 distance between the stationary distributions of the model and the assumed ground truth. In the context of linear models (like so-called weighted supermodels), and assuming a Gaussian error model in the vector fields, vector field learning leads to a tractable Gaussian solution. This solution can then be used as a prior for the next step, Bayesian attractor learning, in which the attractor error is used as a log-likelihood term. Bayesian attractor learning is implemented by elliptical slice sampling, a sampling method for systems with a Gaussian prior and a non Gaussian likelihood. Simulations with a partially observed driven Lorenz 63 system illustrate the approach.
Bayesian ARTMAP for regression.
Sasu, L M; Andonie, R
2013-10-01
Bayesian ARTMAP (BA) is a recently introduced neural architecture which uses a combination of Fuzzy ARTMAP competitive learning and Bayesian learning. Training is generally performed online, in a single-epoch. During training, BA creates input data clusters as Gaussian categories, and also infers the conditional probabilities between input patterns and categories, and between categories and classes. During prediction, BA uses Bayesian posterior probability estimation. So far, BA was used only for classification. The goal of this paper is to analyze the efficiency of BA for regression problems. Our contributions are: (i) we generalize the BA algorithm using the clustering functionality of both ART modules, and name it BA for Regression (BAR); (ii) we prove that BAR is a universal approximator with the best approximation property. In other words, BAR approximates arbitrarily well any continuous function (universal approximation) and, for every given continuous function, there is one in the set of BAR approximators situated at minimum distance (best approximation); (iii) we experimentally compare the online trained BAR with several neural models, on the following standard regression benchmarks: CPU Computer Hardware, Boston Housing, Wisconsin Breast Cancer, and Communities and Crime. Our results show that BAR is an appropriate tool for regression tasks, both for theoretical and practical reasons. PMID:23665468
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.
Bayesian Inference of Tumor Hypoxia
NASA Astrophysics Data System (ADS)
Gunawan, R.; Tenti, G.; Sivaloganathan, S.
2009-12-01
Tumor hypoxia is a state of oxygen deprivation in tumors. It has been associated with aggressive tumor phenotypes and with increased resistance to conventional cancer therapies. In this study, we report on the application of Bayesian sequential analysis in estimating the most probable value of tumor hypoxia quantification based on immunohistochemical assays of a biomarker. The `gold standard' of tumor hypoxia assessment is a direct measurement of pO2 in vivo by the Eppendorf polarographic electrode, which is an invasive technique restricted to accessible sites and living tissues. An attractive alternative is immunohistochemical staining to detect proteins expressed by cells during hypoxia. Carbonic anhydrase IX (CAIX) is an enzyme expressed on the cell membrane during hypoxia to balance the immediate extracellular microenvironment. CAIX is widely regarded as a surrogate marker of chronic hypoxia in various cancers. The study was conducted with two different experimental procedures. The first data set was a group of three patients with invasive cervical carcinomas, from which five biopsies were obtained. Each of the biopsies was fully sectioned and from each section, the proportion of CAIX-positive cells was estimated. Measurements were made by image analysis of multiple deep sections cut through these biopsies, labeled for CAIX using both immunofluorescence and immunohistochemical techniques [1]. The second data set was a group of 24 patients, also with invasive cervical carcinomas, from which two biopsies were obtained. Bayesian parameter estimation was applied to obtain a reliable inference about the proportion of CAIX-positive cells within the carcinomas, based on the available biopsies. From the first data set, two to three biopsies were found to be sufficient to infer the overall CAIX percentage in the simple form: best estimate±uncertainty. The second data-set led to a similar result in 70% of the cases. In the remaining cases Bayes' theorem warned us
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. PMID:12317726
Information geometry of Bayesian statistics
NASA Astrophysics Data System (ADS)
Matsuzoe, Hiroshi
2015-01-01
A survey of geometry of Bayesian statistics is given. From the viewpoint of differential geometry, a prior distribution in Bayesian statistics is regarded as a volume element on a statistical model. In this paper, properties of Bayesian estimators are studied by applying equiaffine structures of statistical manifolds. In addition, geometry of anomalous statistics is also studied. Deformed expectations and deformed independeces are important in anomalous statistics. After summarizing geometry of such deformed structues, a generalization of maximum likelihood method is given. A suitable weight on a parameter space is important in Bayesian statistics, whereas a suitable weight on a sample space is important in anomalous statistics.
Beyond initial attraction: physical attractiveness in newlywed marriage.
McNulty, James K; Neff, Lisa A; Karney, Benjamin R
2008-02-01
Physical appearance plays a crucial role in shaping new relationships, but does it continue to affect established relationships, such as marriage? In the current study, the authors examined how observer ratings of each spouse's facial attractiveness and the difference between those ratings were associated with (a) observations of social support behavior and (b) reports of marital satisfaction. In contrast to the robust and almost universally positive effects of levels of attractiveness on new relationships, the only association between levels of attractiveness and the outcomes of these marriages was that attractive husbands were less satisfied. Further, in contrast to the importance of matched attractiveness to new relationships, similarity in attractiveness was unrelated to spouses' satisfaction and behavior. Instead, the relative difference between partners' levels of attractiveness appeared to be most important in predicting marital behavior, such that both spouses behaved more positively in relationships in which wives were more attractive than their husbands, but they behaved more negatively in relationships in which husbands were more attractive than their wives. These results highlight the importance of dyadic examinations of the effects of spouses' qualities on their marriages. PMID:18266540
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. PMID:27028721
Computationally efficient Bayesian tracking
NASA Astrophysics Data System (ADS)
Aughenbaugh, Jason; La Cour, Brian
2012-06-01
In this paper, we describe the progress we have achieved in developing a computationally efficient, grid-based Bayesian fusion tracking system. In our approach, the probability surface is represented by a collection of multidimensional polynomials, each computed adaptively on a grid of cells representing state space. Time evolution is performed using a hybrid particle/grid approach and knowledge of the grid structure, while sensor updates use a measurement-based sampling method with a Delaunay triangulation. We present an application of this system to the problem of tracking a submarine target using a field of active and passive sonar buoys.
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.
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…
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
Physical Attractiveness Stereotypes about Marriage: Attractiveness Matching Is Good.
ERIC Educational Resources Information Center
Sussman, Steve; And Others
Previous research on physical attractiveness stereotypes about marriage have used stimulus individuals in isolation. To examine these attractiveness stereotypes using couples as targets, 72 college students (36 females, 36 males) rated eight photographs of four male-female couple types. Members of each couple were either matched (attractive…
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
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.
Surprise maximization reveals the community structure of complex networks
NASA Astrophysics Data System (ADS)
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.
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
On the temporal interpretation of certain surprise questions.
Giorgi, Alessandra
2016-01-01
This article considers a special kind of surprise questions, i.e. those introduced by the adversative particle ma (but), and compares it with surprise exclamations. The main issue addressed here concerns the obligatory presence in the questions of the imperfect verbal form, versus the obligatory presence in exclamations of a non-imperfect indicative. It will be shown that the special semantics associated with these structures determines the presence of a certain verbal form. Some syntactic issues will be addressed in the final section, having to do with the representation in the syntax of properties connected to the context. PMID:27610309
Physical Attractiveness and Courtship Progress.
ERIC Educational Resources Information Center
White, Gregory L.
1980-01-01
Among college students who were casual or serious daters, greater relative attractiveness was positively correlated with greater relative availability of opposite-sexed friends and negatively correlated with worrying about partner's potential involvement with others. A 9-month follow-up revealed that similarity of attractiveness was predictive of…
Physical Attractiveness and Interpersonal Influence
ERIC Educational Resources Information Center
Dion, Karen K.; Stein, Steven
1978-01-01
Examines the hypothesis that attractive individuals should be more successful with opposite-sex peers but less successful with same-sex peers than unattractive individuals. Also investigates the influence strategies employed by persons differing in attractiveness since nothing is currently known about the actual behavior exhibited by attractive…
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…
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 stereotype and memory.
Rohner, Jean-Christophe; Rasmussen, Anders
2011-08-01
Three experiments examined explicit and implicit memory for information that is congruent with the physical attractiveness stereotype (i.e. attractive-positive and unattractive-negative) and information that is incongruent with the physical attractiveness stereotype (i.e. attractive-negative and unattractive-positive). Measures of explicit recognition sensitivity and implicit discriminability revealed a memorial advantage for congruent compared to incongruent information, as evident from hit and false alarm rates and reaction times, respectively. Measures of explicit memory showed a recognition bias toward congruent compared to incongruent information, where participants tended to call congruent information old, independently of whether the information had been shown previously or not. This recognition bias was unrelated to reports of subjective confidence in retrieval. The present findings shed light on the cognitive mechanisms that might mediate discriminatory behavior towards physically attractive and physically unattractive individuals. PMID:21255024
Evidence for surprise minimization over value maximization in choice behavior
Schwartenbeck, Philipp; FitzGerald, Thomas H. B.; Mathys, Christoph; Dolan, Ray; Kronbichler, Martin; Friston, Karl
2015-01-01
Classical economic models are predicated on the idea that the ultimate aim of choice is to maximize utility or reward. In contrast, an alternative perspective highlights the fact that adaptive behavior requires agents’ to model their environment and minimize surprise about the states they frequent. We propose that choice behavior can be more accurately accounted for by surprise minimization compared to reward or utility maximization alone. Minimizing surprise makes a prediction at variance with expected utility models; namely, that in addition to attaining valuable states, agents attempt to maximize the entropy over outcomes and thus ‘keep their options open’. We tested this prediction using a simple binary choice paradigm and show that human decision-making is better explained by surprise minimization compared to utility maximization. Furthermore, we replicated this entropy-seeking behavior in a control task with no explicit utilities. These findings highlight a limitation of purely economic motivations in explaining choice behavior and instead emphasize the importance of belief-based motivations. PMID:26564686
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...
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...
How Surprising Is a Simple Pattern? Quantifying ''Eureka!''
ERIC Educational Resources Information Center
Feldman, Jacob
2004-01-01
Simple patterns are compelling. When all the observed facts fit into a simple theory or ''story,'' we are intuitively convinced that the pattern must be "real" rather than random. But how surprising is a simple pattern, really? That is, given a pattern of featural data, such as the properties of a set of objects, how unlikely would the pattern be…
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.
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 sperm competition estimates.
Jones, Beatrix; Clark, Andrew G
2003-01-01
We introduce a Bayesian method for estimating parameters for a model of multiple mating and sperm displacement from genotype counts of brood-structured data. The model is initially targeted for Drosophila melanogaster, but is easily adapted to other organisms. The method is appropriate for use with field studies where the number of mates and the genotypes of the mates cannot be controlled, but where unlinked markers have been collected for a set of females and a sample of their offspring. Advantages over previous approaches include full use of multilocus information and the ability to cope appropriately with missing data and ambiguities about which alleles are maternally vs. paternally inherited. The advantages of including X-linked markers are also demonstrated. PMID:12663555
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
Depression, Schizophrenia, and Social Attraction.
ERIC Educational Resources Information Center
Boswell, Philip C.; Murray, Edward J.
1981-01-01
Compared the dysphoric mood induction and attraction that subjects reported after a vicarious experience with a depressed patient and a comparable experience with a schizophrenic patient. Results showed similar arousal of dysphoric mood and rejection for both patients. (RC)
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.
UNIFORMLY MOST POWERFUL BAYESIAN TESTS
Johnson, Valen E.
2014-01-01
Uniformly most powerful tests are statistical hypothesis tests that provide the greatest power against a fixed null hypothesis among all tests of a given size. In this article, the notion of uniformly most powerful tests is extended to the Bayesian setting by defining uniformly most powerful Bayesian tests to be tests that maximize the probability that the Bayes factor, in favor of the alternative hypothesis, exceeds a specified threshold. Like their classical counterpart, uniformly most powerful Bayesian tests are most easily defined in one-parameter exponential family models, although extensions outside of this class are possible. The connection between uniformly most powerful tests and uniformly most powerful Bayesian tests can be used to provide an approximate calibration between p-values and Bayes factors. Finally, issues regarding the strong dependence of resulting Bayes factors and p-values on sample size are discussed. PMID:24659829
Dietary Effects on Cuticular Hydrocarbons and Sexual Attractiveness in Drosophila
Fedina, Tatyana Y.; Kuo, Tsung-Han; Dreisewerd, Klaus; Dierick, Herman A.; Yew, Joanne Y.; Pletcher, Scott D.
2012-01-01
Dietary composition is known to have profound effects on many aspects of animal physiology, including lifespan, general health, and reproductive potential. We have previously shown that aging and insulin signaling significantly influence the composition and sexual attractiveness of Drosophila melanogaster female cuticular hydrocarbons (CHCs), some of which are known to be sex pheromones. Because diet is intimately linked to aging and to the activity of nutrient-sensing pathways, we asked how diet affects female CHCs and attractiveness. Here we report consistent and significant effects of diet composition on female CHC profiles across ages, with dietary yeast and sugar driving CHC changes in opposite directions. Surprisingly, however, we found no evidence that these changes affect female attractiveness. Multivariate comparisons among responses of CHC profiles to diet, aging, and insulin signaling suggest that diet may alter the levels of some CHCs in a way that results in profiles that are more attractive while simultaneously altering other CHCs in a way that makes them less attractive. For example, changes in short-chain CHCs induced by a high-yeast diet phenocopy changes caused by aging and by decreased insulin signaling, both of which result in less attractive females. On the other hand, changes in long-chain CHCs in response to the same diet result in levels that are comparable to those observed in attractive young females and females with increased insulin signaling. The effects of a high-sugar diet tend in the opposite direction, as levels of short-chain CHCs resemble those in attractive females with increased insulin signaling and changes in long-chain CHCs are similar to those caused by decreased insulin signaling. Together, these data suggest that diet-dependent changes in female CHCs may be sending conflicting messages to males. PMID:23227150
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.
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.
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.
[Pulmonary embolism in athletes--a surprising diagnosis].
Rieck, Jonathan; Elkayam, Amitai; Varon, David
2015-04-01
Pulmonary embolus is considered a rare and surprising event in the athletic population. Failure to diagnose this condition may lead to serious morbidity and even death. We report a case series of athletes diagnosed at the Acute Diagnostic Unit over the last two years, and discuss the special diagnostic, mechanistic and treatment principles in this population. We hope that this article will increase awareness of this condition amongst the medical teams dealing with this super fit population. PMID:26065218
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. PMID:23262769
'The thieving magpie'? No evidence for attraction to shiny objects.
Shephard, T V; Lea, S E G; Hempel de Ibarra, N
2015-01-01
It is widely accepted in European culture that magpies (Pica pica) are unconditionally attracted to shiny objects and routinely steal small trinkets such as jewellery, almost as a compulsion. Despite the long history of this folklore, published accounts of magpies collecting shiny objects are rare and empirical evidence for the behaviour is lacking. The latter is surprising considering that an attraction to bright objects is well documented in some bird species. The present study aims to clarify whether magpies show greater attraction to shiny objects than non-shiny objects when presented at the same time. We did not find evidence of an unconditional attraction to shiny objects in either captive or free-living birds. Instead, all objects elicited responses indicating neophobia in free-living birds. We suggest that humans notice when magpies occasionally pick up shiny objects because they believe the birds find them attractive, while it goes unnoticed when magpies interact with less eye-catching items. The folklore may therefore result from observation bias and cultural inflation of orally transmitted episodic events. PMID:25123853
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.
Approximate Bayesian multibody tracking.
Lanz, Oswald
2006-09-01
Visual tracking of multiple targets is a challenging problem, especially when efficiency is an issue. Occlusions, if not properly handled, are a major source of failure. Solutions supporting principled occlusion reasoning have been proposed but are yet unpractical for online applications. This paper presents a new solution which effectively manages the trade-off between reliable modeling and computational efficiency. The Hybrid Joint-Separable (HJS) filter is derived from a joint Bayesian formulation of the problem, and shown to be efficient while optimal in terms of compact belief representation. Computational efficiency is achieved by employing a Markov random field approximation to joint dynamics and an incremental algorithm for posterior update with an appearance likelihood that implements a physically-based model of the occlusion process. A particle filter implementation is proposed which achieves accurate tracking during partial occlusions, while in cases of complete occlusion, tracking hypotheses are bound to estimated occlusion volumes. Experiments show that the proposed algorithm is efficient, robust, and able to resolve long-term occlusions between targets with identical appearance. PMID:16929730
Bayesian Spatial Quantile Regression
Reich, Brian J.; Fuentes, Montserrat; Dunson, David B.
2013-01-01
Tropospheric ozone is one of the six criteria pollutants regulated by the United States Environmental Protection Agency under the Clean Air Act and has been linked with several adverse health effects, including mortality. Due to the strong dependence on weather conditions, ozone may be sensitive to climate change and there is great interest in studying the potential effect of climate change on ozone, and how this change may affect public health. In this paper we develop a Bayesian spatial model to predict ozone under different meteorological conditions, and use this model to study spatial and temporal trends and to forecast ozone concentrations under different climate scenarios. We develop a spatial quantile regression model that does not assume normality and allows the covariates to affect the entire conditional distribution, rather than just the mean. The conditional distribution is allowed to vary from site-to-site and is smoothed with a spatial prior. For extremely large datasets our model is computationally infeasible, and we develop an approximate method. We apply the approximate version of our model to summer ozone from 1997–2005 in the Eastern U.S., and use deterministic climate models to project ozone under future climate conditions. Our analysis suggests that holding all other factors fixed, an increase in daily average temperature will lead to the largest increase in ozone in the Industrial Midwest and Northeast. PMID:23459794
Bayesian Spatial Quantile Regression.
Reich, Brian J; Fuentes, Montserrat; Dunson, David B
2011-03-01
Tropospheric ozone is one of the six criteria pollutants regulated by the United States Environmental Protection Agency under the Clean Air Act and has been linked with several adverse health effects, including mortality. Due to the strong dependence on weather conditions, ozone may be sensitive to climate change and there is great interest in studying the potential effect of climate change on ozone, and how this change may affect public health. In this paper we develop a Bayesian spatial model to predict ozone under different meteorological conditions, and use this model to study spatial and temporal trends and to forecast ozone concentrations under different climate scenarios. We develop a spatial quantile regression model that does not assume normality and allows the covariates to affect the entire conditional distribution, rather than just the mean. The conditional distribution is allowed to vary from site-to-site and is smoothed with a spatial prior. For extremely large datasets our model is computationally infeasible, and we develop an approximate method. We apply the approximate version of our model to summer ozone from 1997-2005 in the Eastern U.S., and use deterministic climate models to project ozone under future climate conditions. Our analysis suggests that holding all other factors fixed, an increase in daily average temperature will lead to the largest increase in ozone in the Industrial Midwest and Northeast. PMID:23459794
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
Vocal attractiveness increases by averaging.
Bruckert, Laetitia; Bestelmeyer, Patricia; Latinus, Marianne; Rouger, Julien; Charest, Ian; Rousselet, Guillaume A; Kawahara, Hideki; Belin, Pascal
2010-01-26
Vocal attractiveness has a profound influence on listeners-a bias known as the "what sounds beautiful is good" vocal attractiveness stereotype [1]-with tangible impact on a voice owner's success at mating, job applications, and/or elections. The prevailing view holds that attractive voices are those that signal desirable attributes in a potential mate [2-4]-e.g., lower pitch in male voices. However, this account does not explain our preferences in more general social contexts in which voices of both genders are evaluated. Here we show that averaging voices via auditory morphing [5] results in more attractive voices, irrespective of the speaker's or listener's gender. Moreover, we show that this phenomenon is largely explained by two independent by-products of averaging: a smoother voice texture (reduced aperiodicities) and a greater similarity in pitch and timbre with the average of all voices (reduced "distance to mean"). These results provide the first evidence for a phenomenon of vocal attractiveness increases by averaging, analogous to a well-established effect of facial averaging [6, 7]. They highlight prototype-based coding [8] as a central feature of voice perception, emphasizing the similarity in the mechanisms of face and voice perception. PMID:20129047
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
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
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. PMID:26062324
Herschel and Planck: surprises in the sub-mm band
NASA Astrophysics Data System (ADS)
González-Nuevo González, J.
2015-05-01
This paper focused on three of the most spectacular and almost unexpected results obtained from the observations in the sub-mm band coming from the ESA's Herschel and Planck missions: the detection of hundred of strongly lensed galaxies, the identification of high-z proto-clusters, and the study of the weak lensing signal through the cross-correlation analysis. Although, there were theoretical works that anticipate them, none of these interesting results appeared in the original scientific programs of both mission. For this reason we have called them ``surprises''.
The doctor was surprised; or, how to diagnose a miracle.
Duffin, Jacalyn
2007-01-01
A survey of more than six hundred miracle records in the canonization files of the Vatican Secret Archives from the seventeenth century to the twentieth century reveals that more than 95 percent are healings from illness. The history of the canonization process is summarized to explain the sources. The diagnoses amenable to miracle cure change through time to reflect current medical preoccupations and methods. Physician testimony has always been crucial to the investigation of miracles for declaring the hopeless prognosis and the surprise at recovery. From this analysis, medicine and religion emerge as parallel semiotic endeavors, using their canons of wisdom and careful observation to derive meaning in suffering. PMID:18084104
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)
Attractiveness and Influence in Counseling
ERIC Educational Resources Information Center
Schmidt, Lyle D.; Strong, Stanley R.
1971-01-01
The results showed that in spite of violently different feelings about (or descriptions of) the roles, the subjects were equally influenced by them. This suggests that social attractiveness may not be important when the client's problems require expert opinion and knowledge. (Author/CG(
Functional Similarity and Interpersonal Attraction.
ERIC Educational Resources Information Center
Neimeyer, Greg J.; Neimeyer, Robert A.
1981-01-01
Students participated in dyadic disclosure exercises over a five-week period. Results indicated members of high functional similarity dyads evidenced greater attraction to one another than did members of low functional similarity dyads. "Friendship" pairs of male undergraduates displayed greater functional similarity than did "nominal" pairs from…
Fatal attraction: sexually cannibalistic invaders attract naive native mantids
Fea, Murray P.; Stanley, Margaret C.; Holwell, Gregory I.
2013-01-01
Overlap in the form of sexual signals such as pheromones raises the possibility of reproductive interference by invasive species on similar, yet naive native species. Here, we test the potential for reproductive interference through heterospecific mate attraction and subsequent predation of males by females of a sexually cannibalistic invasive praying mantis. Miomantis caffra is invasive in New Zealand, where it is widely considered to be displacing the only native mantis species, Orthodera novaezealandiae, and yet mechanisms behind this displacement are unknown. We demonstrate that native males are more attracted to the chemical cues of introduced females than those of conspecific females. Heterospecific pairings also resulted in a high degree of mortality for native males. This provides evidence for a mechanism behind displacement that has until now been undetected and highlights the potential for reproductive interference to greatly influence the impact of an invasive species. PMID:24284560
Fatal attraction: sexually cannibalistic invaders attract naive native mantids.
Fea, Murray P; Stanley, Margaret C; Holwell, Gregory I
2013-01-01
Overlap in the form of sexual signals such as pheromones raises the possibility of reproductive interference by invasive species on similar, yet naive native species. Here, we test the potential for reproductive interference through heterospecific mate attraction and subsequent predation of males by females of a sexually cannibalistic invasive praying mantis. Miomantis caffra is invasive in New Zealand, where it is widely considered to be displacing the only native mantis species, Orthodera novaezealandiae, and yet mechanisms behind this displacement are unknown. We demonstrate that native males are more attracted to the chemical cues of introduced females than those of conspecific females. Heterospecific pairings also resulted in a high degree of mortality for native males. This provides evidence for a mechanism behind displacement that has until now been undetected and highlights the potential for reproductive interference to greatly influence the impact of an invasive species. PMID:24284560
Variational Bayesian method for Retinex.
Wang, Liqian; Xiao, Liang; Liu, Hongyi; Wei, Zhihui
2014-08-01
In this paper, we propose a variational Bayesian method for Retinex to simulate and interpret how the human visual system perceives color. To construct a hierarchical Bayesian model, we use the Gibbs distributions as prior distributions for the reflectance and the illumination, and the gamma distributions for the model parameters. By assuming that the reflection function is piecewise continuous and illumination function is spatially smooth, we define the energy functions in the Gibbs distributions as a total variation function and a smooth function for the reflectance and the illumination, respectively. We then apply the variational Bayes approximation to obtain the approximation of the posterior distribution of unknowns so that the unknown images and hyperparameters are estimated simultaneously. Experimental results demonstrate the efficiency of the proposed method for providing competitive performance without additional information about the unknown parameters, and when prior information is added the proposed method outperforms the non-Bayesian-based Retinex methods we compared. PMID:24846606
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.
Bayesian image reconstruction in astronomy
NASA Astrophysics Data System (ADS)
Nunez, Jorge; Llacer, Jorge
1990-09-01
This paper presents the development and testing of a new iterative reconstruction algorithm for astronomy. A maximum a posteriori method of image reconstruction in the Bayesian statistical framework is proposed for the Poisson-noise case. The method uses the entropy with an adjustable 'sharpness parameter' to define the prior probability and the likelihood with 'data increment' parameters to define the conditional probability. The method makes it possible to obtain reconstructions with neither the problem of the 'grey' reconstructions associated with the pure Bayesian reconstructions nor the problem of image deterioration, typical of the maximum-likelihood method. The present iterative algorithm is fast and stable, maintains positivity, and converges to feasible images.
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…
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...
Taspase 1: A protease with many biological surprises
Niizuma, Hidetaka; Cheng, Emily H; Hsieh, James J
2015-01-01
Taspase 1 (TASP1) cleaves the mixed-lineage leukemia (MLL) and transcription factor (TF) IIA families of nuclear proteins to orchestrate various biological processes. TASP1 is not a classical oncogene, but assists in cell proliferation and permits oncogenic initiation through cleavage of MLL and TFIIA. TASP1 is thus better classified as a “non-oncogene addiction” protease, and targeting TASP1 offers a novel and attractive anticancer therapeutic strategy. PMID:27308523
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
Fingertip aura and interpersonal attraction.
Murstein, B I; Hadjolian, S E
1977-06-01
Concluding from our survey of the literature that fingertip auras (Kirlian effect) might be associated with interpersonal attraction, four hypotheses were advanced to test this assertion. It was hypothesized that individuals would respond with bigger auras to (1) opposite-sex photographers as compared to same-sex photographers, (2) to seductive opposite-sex photographers as opposed to normally behaving opposite-sex photographers, (3) to opposite-sex unknown peers as opposed to same-sex unknown peers, and (4) to liked as opposed to disliked same-sex persons. All hypotheses except (2) were supported. The second hypothesis was significant in a direction contrary to hypothesis. Fingertip auras are seen as a promising measurement device in the study of interpersonal attraction. PMID:16367230
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
2011-06-12
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
Facial Attractiveness Ratings from Video-Clips and Static Images Tell the Same Story
Rhodes, Gillian; Lie, Hanne C.; Thevaraja, Nishta; Taylor, Libby; Iredell, Natasha; Curran, Christine; Tan, Shi Qin Claire; Carnemolla, Pia; Simmons, Leigh W.
2011-01-01
Most of what we know about what makes a face attractive and why we have the preferences we do is based on attractiveness ratings of static images of faces, usually photographs. However, several reports that such ratings fail to correlate significantly with ratings made to dynamic video clips, which provide richer samples of appearance, challenge the validity of this literature. Here, we tested the validity of attractiveness ratings made to static images, using a substantial sample of male faces. We found that these ratings agreed very strongly with ratings made to videos of these men, despite the presence of much more information in the videos (multiple views, neutral and smiling expressions and speech-related movements). Not surprisingly, given this high agreement, the components of video-attractiveness were also very similar to those reported previously for static-attractiveness. Specifically, averageness, symmetry and masculinity were all significant components of attractiveness rated from videos. Finally, regression analyses yielded very similar effects of attractiveness on success in obtaining sexual partners, whether attractiveness was rated from videos or static images. These results validate the widespread use of attractiveness ratings made to static images in evolutionary and social psychological research. We speculate that this validity may stem from our tendency to make rapid and robust judgements of attractiveness. PMID:22096491
Jokela, Markus
2010-01-01
Physical attractiveness has been associated with mating behavior, but its role in reproductive success of contemporary humans has received surprisingly little attention. In the Wisconsin Longitudinal Study (1244 women, 997 men born between 1937 and 1940) we examined whether attractiveness assessed from photographs taken at age ~18 predicted the number of biological children at age 53–56. In women, attractiveness predicted higher reproductive success in a nonlinear fashion, so that attractive (second highest quartile) women had 16% and very attractive (highest quartile) women 6% more children than their less attractive counterparts. In men, there was a threshold effect so that men in the lowest attractiveness quartile had 13% fewer children than others who did not differ from each other in the average number of children. These associations were partly but not completely accounted for by attractive participants’ increased marriage probability. A linear regression analysis indicated relatively weak directional selection gradient for attractiveness (β=0.06 in women, β=0.07 in men). These findings indicate that physical attractiveness may be associated with reproductive success in humans living in industrialized settings. PMID:21151758
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…
Collective motion from local attraction.
Strömbom, Daniel
2011-08-21
Many animal groups, for example schools of fish or flocks of birds, exhibit complex dynamic patterns while moving cohesively in the same direction. These flocking patterns have been studied using self-propelled particle models, most of which assume that collective motion arises from individuals aligning with their neighbours. Here, we propose a self-propelled particle model in which the only social force between individuals is attraction. We show that this model generates three different phases: swarms, undirected mills and moving aligned groups. By studying our model in the zero noise limit, we show how these phases depend on the relative strength of attraction and individual inertia. Moreover, by restricting the field of vision of the individuals and increasing the degree of noise in the system, we find that the groups generate both directed mills and three dynamically moving, 'rotating chain' structures. A rich diversity of patterns is generated by social attraction alone, which may provide insight into the dynamics of natural flocks. PMID:21620861
Pyrazines Attract Catocheilus Thynnine Wasps.
Bohman, Bjorn; Peakall, Rod
2014-01-01
Five previously identified semiochemicals from the sexually deceptive Western Australian hammer orchid Drakaea livida, all showing electrophysiological activity in gas chromatography-electroantennogram detection (EAD) studies, were tested in field bioassays as attractants for a Catocheilus thynnine wasp. Two of these compounds, (3,5,6-trimethylpyrazin-2-yl)methyl 3-methylbutanoate and 2-(3-methylbutyl)-3,5,6-trimethylpyrazine, were attractive to male wasps. Additionally, the semiochemical 3-(3-methylbutyl)-2,5-dimethylpyrazine, a close analogue to 2-(3-methylbutyl)-3,5,6-trimethylpyrazine, identified in five other species of thynnine wasps, was equally active. The three remaining compounds from D. livida, which were EAD-active against Catocheilus, did not attract the insects in field trials. It is interesting that two structurally similar compounds induce similar behaviours in field experiments, yet only one of these compounds is present in the orchid flower. Our findings suggest the possibility that despite the high specificity normally characterising sex pheromone systems, the evolution of sexual deception may not be entirely constrained by the need to precisely match the sex pheromone constituents and blends. Such evolutionary flexibility may be particularly important during the early stages of speciation. PMID:26462695
Pyrazines Attract Catocheilus Thynnine Wasps
Bohman, Bjorn; Peakall, Rod
2014-01-01
Five previously identified semiochemicals from the sexually deceptive Western Australian hammer orchid Drakaea livida, all showing electrophysiological activity in gas chromatography–electroantennogram detection (EAD) studies, were tested in field bioassays as attractants for a Catocheilus thynnine wasp. Two of these compounds, (3,5,6-trimethylpyrazin-2-yl)methyl 3-methylbutanoate and 2-(3-methylbutyl)-3,5,6-trimethylpyrazine, were attractive to male wasps. Additionally, the semiochemical 3-(3-methylbutyl)-2,5-dimethylpyrazine, a close analogue to 2-(3-methylbutyl)-3,5,6-trimethylpyrazine, identified in five other species of thynnine wasps, was equally active. The three remaining compounds from D. livida, which were EAD-active against Catocheilus, did not attract the insects in field trials. It is interesting that two structurally similar compounds induce similar behaviours in field experiments, yet only one of these compounds is present in the orchid flower. Our findings suggest the possibility that despite the high specificity normally characterising sex pheromone systems, the evolution of sexual deception may not be entirely constrained by the need to precisely match the sex pheromone constituents and blends. Such evolutionary flexibility may be particularly important during the early stages of speciation. PMID:26462695
Attracted diffusion-limited aggregation.
Rahbari, S H Ebrahimnazhad; Saberi, A A
2012-07-01
In this paper we present results of extensive Monte Carlo simulations of diffusion-limited aggregation (DLA) with a seed placed on an attractive plane as a simple model in connection with the electrical double layers. We compute the fractal dimension of the aggregated patterns as a function of the attraction strength α. For the patterns grown in both two and three dimensions, the fractal dimension shows a significant dependence on the attraction strength for small values of α and approaches that of the ordinary two-dimensional (2D) DLA in the limit of large α. For the nonattracting case with α = 1, our results in three dimensions reproduce the patterns of 3D ordinary DLA, while in two dimensions our model leads to the formation of a compact cluster with dimension 2. For intermediate α, the 3D clusters have a quasi-2D structure with a fractal dimension very close to that of the ordinary 2D DLA. This allows one to control the morphology of a growing cluster by tuning a single external parameter α. PMID:23005417
Attracted diffusion-limited aggregation
NASA Astrophysics Data System (ADS)
Rahbari, S. H. Ebrahimnazhad; Saberi, A. A.
2012-07-01
In this paper we present results of extensive Monte Carlo simulations of diffusion-limited aggregation (DLA) with a seed placed on an attractive plane as a simple model in connection with the electrical double layers. We compute the fractal dimension of the aggregated patterns as a function of the attraction strength α. For the patterns grown in both two and three dimensions, the fractal dimension shows a significant dependence on the attraction strength for small values of α and approaches that of the ordinary two-dimensional (2D) DLA in the limit of large α. For the nonattracting case with α=1, our results in three dimensions reproduce the patterns of 3D ordinary DLA, while in two dimensions our model leads to the formation of a compact cluster with dimension 2. For intermediate α, the 3D clusters have a quasi-2D structure with a fractal dimension very close to that of the ordinary 2D DLA. This allows one to control the morphology of a growing cluster by tuning a single external parameter α.
The Influence of Physical Attractiveness and Gender on Ultimatum Game Decisions.
Solnick; Schweitzer
1999-09-01
Physical appearance influences behavior in a number of environments, yet surprisingly little is known about the influence of physical attractiveness on the bargaining process. We conducted an ultimatum game experiment to investigate the influence of physical attractiveness and gender on ultimatum game decisions. Results from this study revealed no significant differences in the offers or demands attractive and unattractive people made. However, attractive people and men were treated differently by others. Consistent with the notion of a "beauty premium," attractive people were offered more, but more was demanded of them. Men were also offered more, and less was demanded of them. We discuss implications of these results with respect to bargaining and the labor market. Copyright 1999 Academic Press. PMID:10471361
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
Destabilization of flapping sheets: The surprising analogue of soap films
NASA Astrophysics Data System (ADS)
Lhuissier, H.; Villermaux, E.
2009-06-01
When punctured, a uniform liquid sheet is known, since Taylor and Culick, to recess at a constant speed, balancing surface tension and inertia. For planar soap films, this steady solution holds until the initially smooth receding rim is violently destabilized, exhibiting deep indentations from which droplets are ejected. A surprising new three-dimensional mechanism explaining this destabilization and resulting wavelength has been demonstrated: because of the shear between the still outer medium and the receding liquid, the film flaps through a Kelvin-Helmholtz instability, itself inducing an acceleration perpendicular to the film, which intensifies with the flapping amplitude. To this acceleration is associated a classical Rayleigh-Taylor mechanism, promoting the rim indentations. To cite this article: H. Lhuissier, E. Villermaux, C. R. Mecanique 337 (2009).
Stability of the Taylor--Culick receding rim: surprising observations
NASA Astrophysics Data System (ADS)
Lhuissier, Henri; Villermaux, Emmanuel
2008-11-01
When punctured, a uniform liquid sheet is known, since Taylor and Culick, to recess at a constant speed balancing surface tension and inertia. For planar soap films, this steady solution holds until the initially smooth receding rim is violently destabilized, exhibiting deep indentations from which droplets are ejected. A surprising new three dimensional mechanism explaining this destabilization and resulting wavelength has been evidenced : because of the shear between the still outer medium and the receding liquid, the film flaps through a Kelvin--Helmholtz instability, itself inducing an acceleration perpendicular to the film, which intensifies with the flapping amplitude. To this acceleration is associated a classical Rayleigh--Taylor mechanism, promoting the rim indentations. The same mechanism holds for a punctured round bubble, for which the relevant acceleration is the Culick velocity squared divided by the bubble radius. The bearing of this phenomenon on aerosols formation in Nature will be underlined.
A closer look at eta Carinae's surprising nitrogen chemistry
NASA Astrophysics Data System (ADS)
Cordiner, Martin; Jones, Paul; Millar, Tom; Charnley, Steven; Mcelroy, Daniel; Milam, Stefanie
2013-04-01
The ejecta of the luminous blue variable (LBV) star eta Carinae has recently been found to be surprisingly rich in simple nitrogen-bearing molecules, and theory predicts that more complex species such as HC3N and CH3CN are abundant in the warm inner regions of the Homunculus. We therefore propose to search for emission from HC3N, CH3CN and other nitrogen-bearing molecules in eta Carinae. We will also map HCN and HNC with unprecedented spatial detail to determine the origin and spatial extent of these species. The proposed observations will be crucial for developing chemical models of this source, which we will use to (1) promote understanding of the chemistry of this star and its mysterious ejecta and (2) provide information on molecule formation around massive stars that are about to undergo Type II supernova explosions.
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.
Tree Leaf Shadows to the Sun's Density: A Surprising Route
NASA Astrophysics Data System (ADS)
Mallmann, A. James
2013-01-01
Rays of sunlight that strike raindrops produce rainbows that provide information about the spectrum of sunlight. Rays of sunlight that strike airborne ice crystals produce halos, sun pillars, and many other patterns of light and color in the sky. Analysis of those patterns makes it possible to determine the types and orientations of the ice crystals. Rays of sunlight that strike opaque objects produce shadow patterns that can be seen on any clear day. I was surprised to discover that the shadow patterns produced when sunlight strikes tree leaves provide all the information needed to determine the average density of the Sun. It seems unlikely that the Sun's density could be determined without knowing its mass or its volume. And, although it may seem even more unlikely, the density of the Sun can be determined using only information available in the shadows of tree leaves.
Subjective and Objective Facial Attractiveness
Stillman, Mark A.; Frisina, Andrew C.
2010-01-01
Background: Studies have not adequately compared subjective/objective ratings of female dermatology patients including patients presenting for cosmetic procedures. Objective: To examine objective versus subjective facial attractiveness ratings, demographic variables, and how men versus women judge female facial attractiveness. Methods: Sixty-five women (mean 42 years) presenting to a dermatology office. Subjects filled out a demographic and attractiveness questionnaire and were photographed. Four judges (2 male and 2 female) rated the photographs on a predefined 1 to 7 scale. Results: Mean subjective rating (subjects rating themselves) was 4.85 versus 3.61 for objective rating (judges rating subjects) (p<0.001). The mean age of subjects self-rating (subjective rating) who rated themselves in the 5 to 7 range was 39 years; the mean age of subjects self-rating (subjective rating) who rated themselves in the 3 to 4 range was 45 years (p=0.053). The mean age of subjects objectively rated by judges in the 5 to 7 range was 33 years; the mean age of subjects objectively rated by judges in the 3 to 4 range was 43 years (p<0.001); and the mean age of subjects objectively rated by judges in the 1 to 2 range was 50 years (p<0.001). The mean subjective rating (subjects rating themselves) for married women was 4.55 versus 5.27 for unmarried women (p=0.007); the mean objective rating (judges rating subjects) was 3.22 versus 4.15 (p<0.001). The mean objective rating by male judges was 3.09 versus 4.12 for female judges (p<0.001) Conclusion: Female patients presenting to a dermatology office rated themselves more attractive than did judges who viewed photographs of the subjects. Age and marital status were significant factors, and male judges rated attractiveness lower than female judges. Limitations of the study, implications, and suggestions for future research directions are discussed. PMID:21203353
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.
Bayesian Integration of Spatial Information
ERIC Educational Resources Information Center
Cheng, Ken; Shettleworth, Sara J.; Huttenlocher, Janellen; Rieser, John J.
2007-01-01
Spatial judgments and actions are often based on multiple cues. The authors review a multitude of phenomena on the integration of spatial cues in diverse species to consider how nearly optimally animals combine the cues. Under the banner of Bayesian perception, cues are sometimes combined and weighted in a near optimal fashion. In other instances…
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 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...
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
Bayesian versus 'plain-vanilla Bayesian' multitarget statistics
NASA Astrophysics Data System (ADS)
Mahler, Ronald P. S.
2004-08-01
Finite-set statistics (FISST) is a direct generalization of single-sensor, single-target Bayes statistics to the multisensor-multitarget realm, based on random set theory. Various aspects of FISST are being investigated by several research teams around the world. In recent years, however, a few partisans have claimed that a "plain-vanilla Bayesian approach" suffices as down-to-earth, "straightforward," and general "first principles" for multitarget problems. Therefore, FISST is mere mathematical "obfuscation." In this and a companion paper I demonstrate the speciousness of these claims. In this paper I summarize general Bayes statistics, what is required to use it in multisensor-multitarget problems, and why FISST is necessary to make it practical. Then I demonstrate that the "plain-vanilla Bayesian approach" is so heedlessly formulated that it is erroneous, not even Bayesian denigrates FISST concepts while unwittingly assuming them, and has resulted in a succession of algorithms afflicted by inherent -- but less than candidly acknowledged -- computational "logjams."
Small particles dominate Saturn's Phoebe ring to surprisingly large distances.
Hamilton, Douglas P; Skrutskie, Michael F; Verbiscer, Anne J; Masci, Frank J
2015-06-11
Saturn's faint outermost ring, discovered in 2009 (ref. 1), is probably formed by particles ejected from the distant moon Phoebe. The ring was detected between distances of 128 and 207 Saturn radii (RS = 60,330 kilometres) from the planet, with a full vertical extent of 40RS, making it well over ten times larger than Saturn's hitherto largest known ring, the E ring. The total radial extent of the Phoebe ring could not, however, be determined at that time, nor could particle sizes be significantly constrained. Here we report infrared imaging of the entire ring, which extends from 100RS out to a surprisingly distant 270RS. We model the orbital dynamics of ring particles launched from Phoebe, and construct theoretical power-law profiles of the particle size distribution. We find that very steep profiles fit the data best, and that elevated grain temperatures, arising because of the radiative inefficiency of the smallest grains, probably contribute to the steepness. By converting our constraint on particle sizes into a form that is independent of the uncertain size distribution, we determine that particles with radii greater than ten centimetres, whose orbits do not decay appreciably inward over 4.5 billion years, contribute at most about ten per cent to the cross-sectional area of the ring's dusty component. PMID:26062508
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.
Small particles dominate Saturn's Phoebe ring to surprisingly large distances
NASA Astrophysics Data System (ADS)
Hamilton, Douglas P.; Skrutskie, Michael F.; Verbiscer, Anne J.; Masci, Frank J.
2015-06-01
Saturn's faint outermost ring, discovered in 2009 (ref. 1), is probably formed by particles ejected from the distant moon Phoebe. The ring was detected between distances of 128 and 207 Saturn radii (RS = 60,330 kilometres) from the planet, with a full vertical extent of 40RS, making it well over ten times larger than Saturn's hitherto largest known ring, the E ring. The total radial extent of the Phoebe ring could not, however, be determined at that time, nor could particle sizes be significantly constrained. Here we report infrared imaging of the entire ring, which extends from 100RS out to a surprisingly distant 270RS. We model the orbital dynamics of ring particles launched from Phoebe, and construct theoretical power-law profiles of the particle size distribution. We find that very steep profiles fit the data best, and that elevated grain temperatures, arising because of the radiative inefficiency of the smallest grains, probably contribute to the steepness. By converting our constraint on particle sizes into a form that is independent of the uncertain size distribution, we determine that particles with radii greater than ten centimetres, whose orbits do not decay appreciably inward over 4.5 billion years, contribute at most about ten per cent to the cross-sectional area of the ring's dusty component.
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
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
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.
A surprising dipolar cycloaddition provides ready access to aminoglycosides.
Dahl, Russell S; Finney, Nathaniel S
2004-07-14
This contribution describes the results of a new research effort in our laboratory aimed at the synthesis of novel aminoglycosides and amino-C-glycosides. Despite the importance of such compounds, and the previous development of some methodological solutions, this remains an important area of research. Notable features of our approach, which is distinct from and complementary to previous efforts, are the following: (1) Reliance on a surprising and unprecedented formation of glycal triazolines via an inverse electron demand dipolar cycloaddition of glucal. We believe this desirable transformation has not previously been discovered because of the unusual selection of substrates and solvent required. (2) Very mild reaction conditions. An initial thermal cycloaddition is carried out in an inert solvent, the triazoline generated is photochemically converted to a reactive aziridine, and the crude aziridine undergoes ring opening at room temperature in the presence of a nucleophile and a mild Lewis acid catalyst. (3) Formation of products lacking an N-acyl group, allowing ready synthesis of novel glucosamine derivatives. PMID:15237974
Nematode Sodium Calcium Exchangers: A Surprising Lack of Transport
Sharma, Vishal; O’Halloran, Damien M.
2016-01-01
Na+/Ca2+ exchangers are low-affinity, high-capacity transporters that rapidly transport calcium against a gradient of Na+ ions. Na+/Ca2+ exchangers are divided into three groups based upon substrate specificity: Na+/Ca2+ exchangers (NCX), Na+/Ca2+/K+ exchangers (NCKX), and Ca2+/cation exchangers (NCLX). In mammals, there are three NCX genes, five NCKX genes, and a single NCLX gene. The genome of the nematode Caenorhabditis elegans contains 10 Na+/Ca2+ exchanger genes: three NCX, five NCLX, and two NCKX genes. In a previous study, we characterized the structural and taxonomic specializations within the family of Na+/Ca2+ exchangers across the phylum Nematoda and observed a complex picture of Na+/Ca2+ exchanger evolution across diverse nematode species. We noted multiple cases of putative gene gain and loss and, most surprisingly, did not detect members of the NCLX type of exchangers within subsets of nematode species. In this commentary, we discuss these findings and speculate on the functional outcomes and physiology of these observations. Our data highlight the importance of studying diverse systems in order to get a deeper understanding of the evolution and regulation of Ca2+ signaling critical for animal function. PMID:26848260
Endosymbiont evolution: predictions from theory and surprises from genomes.
Wernegreen, Jennifer J
2015-12-01
Genome data have created new opportunities to untangle evolutionary processes shaping microbial variation. Among bacteria, long-term mutualists of insects represent the smallest and (typically) most AT-rich genomes. Evolutionary theory provides a context to predict how an endosymbiotic lifestyle may alter fundamental evolutionary processes--mutation, selection, genetic drift, and recombination--and thus contribute to extreme genomic outcomes. These predictions can then be explored by comparing evolutionary rates, genome size and stability, and base compositional biases across endosymbiotic and free-living bacteria. Recent surprises from such comparisons include genome reduction among uncultured, free-living species. Some studies suggest that selection generally drives this streamlining, while drift drives genome reduction in endosymbionts; however, this remains an hypothesis requiring additional data. Unexpected evidence of selection acting on endosymbiont GC content hints that even weak selection may be effective in some long-term mutualists. Moving forward, intraspecific analysis offers a promising approach to distinguish underlying mechanisms, by testing the null hypothesis of neutrality and by quantifying mutational spectra. Such analyses may clarify whether endosymbionts and free-living bacteria occupy distinct evolutionary trajectories or, alternatively, represent varied outcomes of similar underlying forces. PMID:25866055
How microorganisms avoid phagocyte attraction.
Bestebroer, Jovanka; De Haas, Carla J C; Van Strijp, Jos A G
2010-05-01
Microorganisms have developed several mechanisms to modulate the host immune system to increase their survival and propagation in the host. Their presence in the host is not only revealed by self-produced peptides but also through host-derived chemokines and active complement fragments. These so-called chemoattractants are recognized by G protein-coupled receptors (GPCRs) expressed on leukocyte cell membranes. Activation of GPCRs triggers leukocyte activation and guides their recruitment to the site of infection. Therefore, GPCRs play a central role in leukocyte trafficking leading to microbial clearance. It is therefore not surprising that microorganisms are able to sabotage this arm of the immune response. Different microorganisms have evolved a variety of tactics to modulate GPCR activation. Here, we review the mechanisms and proteins used by major human pathogens and less virulent microorganisms that affect GPCR signaling. While viruses generally produce receptor and chemoattractant mimics, parasites and bacteria such as Staphylococcus aureus, Streptococcus pyogenes, Porphyromonas gingivalis, and Bordetella pertussis secrete proteins that affect receptor signaling, directly antagonize receptors, cleave stimuli, and even prevent stimulus generation. As the large arsenal of GPCR modulators aids prolonged microbial persistence in the host, their study provides us a better understanding of microbial pathogenesis. PMID:20059549
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 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.
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
Hierarchical Bayesian inverse reinforcement learning.
Choi, Jaedeug; Kim, Kee-Eung
2015-04-01
Inverse reinforcement learning (IRL) is the problem of inferring the underlying reward function from the expert's behavior data. The difficulty in IRL mainly arises in choosing the best reward function since there are typically an infinite number of reward functions that yield the given behavior data as optimal. Another difficulty comes from the noisy behavior data due to sub-optimal experts. We propose a hierarchical Bayesian framework, which subsumes most of the previous IRL algorithms as well as models the sub-optimality of the expert's behavior. Using a number of experiments on a synthetic problem, we demonstrate the effectiveness of our approach including the robustness of our hierarchical Bayesian framework to the sub-optimal expert behavior data. Using a real dataset from taxi GPS traces, we additionally show that our approach predicts the driving behavior with a high accuracy. PMID:25291805
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. PMID:23599051
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
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.
Exponential tilting in Bayesian asymptotics
Kharroubi, S. A.; Sweeting, T. J.
2016-01-01
We use exponential tilting to obtain versions of asymptotic formulae for Bayesian computation that do not involve conditional maxima of the likelihood function, yielding a more stable computational procedure and significantly reducing computational time. In particular we present an alternative version of the Laplace approximation for a marginal posterior density. Implementation of the asymptotic formulae and a modified signed root based importance sampler are illustrated with an example. PMID:27279661
Bayesian segmentation of hyperspectral images
NASA Astrophysics Data System (ADS)
Mohammadpour, Adel; Féron, Olivier; Mohammad-Djafari, Ali
2004-11-01
In this paper we consider the problem of joint segmentation of hyperspectral images in the Bayesian framework. The proposed approach is based on a Hidden Markov Modeling (HMM) of the images with common segmentation, or equivalently with common hidden classification label variables which is modeled by a Potts Markov Random Field. We introduce an appropriate Markov Chain Monte Carlo (MCMC) algorithm to implement the method and show some simulation results.
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
Frequentist tests for Bayesian models
NASA Astrophysics Data System (ADS)
Lucy, L. B.
2016-04-01
Analogues of the frequentist chi-square and F tests are proposed for testing goodness-of-fit and consistency for Bayesian models. Simple examples exhibit these tests' detection of inconsistency between consecutive experiments with identical parameters, when the first experiment provides the prior for the second. In a related analysis, a quantitative measure is derived for judging the degree of tension between two different experiments with partially overlapping parameter vectors.
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.
Bayesian kinematic earthquake source models
NASA Astrophysics Data System (ADS)
Minson, S. E.; Simons, M.; Beck, J. L.; Genrich, J. F.; Galetzka, J. E.; Chowdhury, F.; Owen, S. E.; Webb, F.; Comte, D.; Glass, B.; Leiva, C.; Ortega, F. H.
2009-12-01
Most coseismic, postseismic, and interseismic slip models are based on highly regularized optimizations which yield one solution which satisfies the data given a particular set of regularizing constraints. This regularization hampers our ability to answer basic questions such as whether seismic and aseismic slip overlap or instead rupture separate portions of the fault zone. We present a Bayesian methodology for generating kinematic earthquake source models with a focus on large subduction zone earthquakes. Unlike classical optimization approaches, Bayesian techniques sample the ensemble of all acceptable models presented as an a posteriori probability density function (PDF), and thus we can explore the entire solution space to determine, for example, which model parameters are well determined and which are not, or what is the likelihood that two slip distributions overlap in space. Bayesian sampling also has the advantage that all a priori knowledge of the source process can be used to mold the a posteriori ensemble of models. Although very powerful, Bayesian methods have up to now been of limited use in geophysical modeling because they are only computationally feasible for problems with a small number of free parameters due to what is called the "curse of dimensionality." However, our methodology can successfully sample solution spaces of many hundreds of parameters, which is sufficient to produce finite fault kinematic earthquake models. Our algorithm is a modification of the tempered Markov chain Monte Carlo (tempered MCMC or TMCMC) method. In our algorithm, we sample a "tempered" a posteriori PDF using many MCMC simulations running in parallel and evolutionary computation in which models which fit the data poorly are preferentially eliminated in favor of models which better predict the data. We present results for both synthetic test problems as well as for the 2007 Mw 7.8 Tocopilla, Chile earthquake, the latter of which is constrained by InSAR, local high
Human amygdala response to dynamic facial expressions of positive and negative surprise.
Vrticka, Pascal; Lordier, Lara; Bediou, Benoît; Sander, David
2014-02-01
Although brain imaging evidence accumulates to suggest that the amygdala plays a key role in the processing of novel stimuli, only little is known about its role in processing expressed novelty conveyed by surprised faces, and even less about possible interactive encoding of novelty and valence. Those investigations that have already probed human amygdala involvement in the processing of surprised facial expressions either used static pictures displaying negative surprise (as contained in fear) or "neutral" surprise, and manipulated valence by contextually priming or subjectively associating static surprise with either negative or positive information. Therefore, it still remains unresolved how the human amygdala differentially processes dynamic surprised facial expressions displaying either positive or negative surprise. Here, we created new artificial dynamic 3-dimensional facial expressions conveying surprise with an intrinsic positive (wonderment) or negative (fear) connotation, but also intrinsic positive (joy) or negative (anxiety) emotions not containing any surprise, in addition to neutral facial displays either containing ("typical surprise" expression) or not containing ("neutral") surprise. Results showed heightened amygdala activity to faces containing positive (vs. negative) surprise, which may either correspond to a specific wonderment effect as such, or to the computation of a negative expected value prediction error. Findings are discussed in the light of data obtained from a closely matched nonsocial lottery task, which revealed overlapping activity within the left amygdala to unexpected positive outcomes. PMID:24219397
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 second law of thermodynamics.
Bartolotta, Anthony; Carroll, Sean M; Leichenauer, Stefan; Pollack, Jason
2016-08-01
We derive a generalization of the second law of thermodynamics that uses Bayesian updates to explicitly incorporate the effects of a measurement of a system at some point in its evolution. By allowing an experimenter's knowledge to be updated by the measurement process, this formulation resolves a tension between the fact that the entropy of a statistical system can sometimes fluctuate downward and the information-theoretic idea that knowledge of a stochastically evolving system degrades over time. The Bayesian second law can be written as ΔH(ρ_{m},ρ)+〈Q〉_{F|m}≥0, where ΔH(ρ_{m},ρ) is the change in the cross entropy between the original phase-space probability distribution ρ and the measurement-updated distribution ρ_{m} and 〈Q〉_{F|m} is the expectation value of a generalized heat flow out of the system. We also derive refined versions of the second law that bound the entropy increase from below by a non-negative number, as well as Bayesian versions of integral fluctuation theorems. We demonstrate the formalism using simple analytical and numerical examples. PMID:27627241
Bayesian second law of thermodynamics
NASA Astrophysics Data System (ADS)
Bartolotta, Anthony; Carroll, Sean M.; Leichenauer, Stefan; Pollack, Jason
2016-08-01
We derive a generalization of the second law of thermodynamics that uses Bayesian updates to explicitly incorporate the effects of a measurement of a system at some point in its evolution. By allowing an experimenter's knowledge to be updated by the measurement process, this formulation resolves a tension between the fact that the entropy of a statistical system can sometimes fluctuate downward and the information-theoretic idea that knowledge of a stochastically evolving system degrades over time. The Bayesian second law can be written as Δ H (ρm,ρ ) + F |m≥0 , where Δ H (ρm,ρ ) is the change in the cross entropy between the original phase-space probability distribution ρ and the measurement-updated distribution ρm and
F |m is the expectation value of a generalized heat flow out of the system. We also derive refined versions of the second law that bound the entropy increase from below by a non-negative number, as well as Bayesian versions of integral fluctuation theorems. We demonstrate the formalism using simple analytical and numerical examples.
Bayesian Phylogeography Finds Its Roots
Lemey, Philippe; Rambaut, Andrew; Drummond, Alexei J.; Suchard, Marc A.
2009-01-01
As a key factor in endemic and epidemic dynamics, the geographical distribution of viruses has been frequently interpreted in the light of their genetic histories. Unfortunately, inference of historical dispersal or migration patterns of viruses has mainly been restricted to model-free heuristic approaches that provide little insight into the temporal setting of the spatial dynamics. The introduction of probabilistic models of evolution, however, offers unique opportunities to engage in this statistical endeavor. Here we introduce a Bayesian framework for inference, visualization and hypothesis testing of phylogeographic history. By implementing character mapping in a Bayesian software that samples time-scaled phylogenies, we enable the reconstruction of timed viral dispersal patterns while accommodating phylogenetic uncertainty. Standard Markov model inference is extended with a stochastic search variable selection procedure that identifies the parsimonious descriptions of the diffusion process. In addition, we propose priors that can incorporate geographical sampling distributions or characterize alternative hypotheses about the spatial dynamics. To visualize the spatial and temporal information, we summarize inferences using virtual globe software. We describe how Bayesian phylogeography compares with previous parsimony analysis in the investigation of the influenza A H5N1 origin and H5N1 epidemiological linkage among sampling localities. Analysis of rabies in West African dog populations reveals how virus diffusion may enable endemic maintenance through continuous epidemic cycles. From these analyses, we conclude that our phylogeographic framework will make an important asset in molecular epidemiology that can be easily generalized to infer biogeogeography from genetic data for many organisms. PMID:19779555
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.
Interpersonal Congruency, Attitude Similarity, and Interpersonal Attraction
ERIC Educational Resources Information Center
Touhey, John C.
1975-01-01
As no experimental study has examined the effects of congruency on attraction, the present investigation orthogonally varied attitude similarity and interpersonal congruency in order to compare the two independent variables as determinants of interpersonal attraction. (Author/RK)
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. PMID:21775236
Optimizing Inequality Constrained Priors in Bayesian Networks
NASA Astrophysics Data System (ADS)
Holmes, Dawn E.
2005-11-01
Intelligent systems based on Bayesian networks have been successful in medical diagnosis, finance and many other areas. Updating probabilities in Bayesian networks relies on algorithms that require complete causal information. Sensitivity analysis now strongly indicates that probabilities in Bayesian networks are not robust and this reinforces the view that a sound theoretical model for finding a minimally prejudiced estimate of the prior distribution is desirable. In this paper we are concerned with how to find the optimum prior distribution, given all and only the knowledge available. In particular, we show how to integrate prior knowledge expressed in terms of inequality constraints, into a Bayesian network based intelligent system.
Variational bayesian method of estimating variance components.
Arakawa, Aisaku; Taniguchi, Masaaki; Hayashi, Takeshi; Mikawa, Satoshi
2016-07-01
We developed a Bayesian analysis approach by using a variational inference method, a so-called variational Bayesian method, to determine the posterior distributions of variance components. This variational Bayesian method and an alternative Bayesian method using Gibbs sampling were compared in estimating genetic and residual variance components from both simulated data and publically available real pig data. In the simulated data set, we observed strong bias toward overestimation of genetic variance for the variational Bayesian method in the case of low heritability and low population size, and less bias was detected with larger population sizes in both methods examined. The differences in the estimates of variance components between the variational Bayesian and the Gibbs sampling were not found in the real pig data. However, the posterior distributions of the variance components obtained with the variational Bayesian method had shorter tails than those obtained with the Gibbs sampling. Consequently, the posterior standard deviations of the genetic and residual variances of the variational Bayesian method were lower than those of the method using Gibbs sampling. The computing time required was much shorter with the variational Bayesian method than with the method using Gibbs sampling. PMID:26877207
Attribution, the Attractiveness Stereotype, and the Elderly.
ERIC Educational Resources Information Center
Johnson, Douglas F.; Pittenger, John B.
1984-01-01
Tests the applicability of the physical attractiveness stereotype to perceptions of the elderly. In the first study, college-age and elderly observers rated the attractiveness of faces of elderly people. In the second study, subjects rated faces at three levels of attractiveness on personality, success in life experiences, and occupational…
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. PMID:25733515
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
Volcanic Plumes on Io: Old Friends and Recent Surprises
NASA Astrophysics Data System (ADS)
McEwen, A. S.
2002-05-01
One of the most spectacular phenomena on Io are the active volcanic plumes. Nine plumes were observed during the Voyager 1 encounter in 1979: Pele (300 km high), Loki (150 km; 2 plumes), and 6 smaller "Prometheus-type" plumes. When Voyager 2 imaged Io 4 months later, all of the these plumes were detected except Pele, and there were two new large red plume deposits (Surt and Aten) similar to the deposits of Pele. These 2 new plume vents were at relatively high latitudes (45N and 48S) whereas the others were more equatorial. Galileo observed a total of 10 plumes prior to 2000, 4 of which were erupting from the same volcanic complexes as in 1979, so there was a total of 15 volcanic centers with observed plumes, all equatorial except Masubi at 44S. We found that Prometheus-type plumes wander, apparently erupting from rootless vents where silicate lava flows over volatile-rich ground. Red deposits, on the other hand, seem to mark the deep vents for silicate lava. Galileo and HST also showed that Pele is normally detectable only at UV wavelengths or at very high phase angles, and was in an anomalous state during the Voyager 1 encounter. The only good candidate for a "stealth" SO2 gas plume visible only in eclipse was seen over Acala, although some Prometheus-type plumes appeared much larger in eclipse. The existence of many much smaller plumes was predicted from Voyager observations of bright streaks radial to Pele, but Galileo has not confirmed this hypothesis. From the joint Galileo-Cassini observations within a few days of Jan 1, 2001 we were surprised to see a giant new plume (400 km high) over Tvashtar Catena (63 N) with UV color properties and a 1200-km diameter red plume deposit, both very similar to Pele. In the I31 flyby (August 2001) Galileo flew through the region occupied by the Tvashtar plume 7 months earlier. The images did not detect a plume, but SO2 may have been detected by the plasma science experiment. However, the images did reveal a giant (500 km
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. PMID:25408499
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.
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
Effects of Instructor Attractiveness on Learning.
Westfall, Richard; Millar, Murray; Walsh, Mandy
2016-01-01
Although a considerable body of research has examined the impact of student attractiveness on instructors, little attention has been given to the influence of instructor attractiveness on students. This study tested the hypothesis that persons would perform significantly better on a learning task when they perceived their instructor to be high in physical attractiveness. To test the hypothesis, participants listened to an audio lecture while viewing a photograph of instructor. The photograph depicted either a physically attractive instructor or a less attractive instructor. Following the lecture, participants completed a forced choice recognition task covering material from the lecture. Consistent with the predictions; attractive instructors were associated with more learning. Finally, we replicated previous findings demonstrating the role attractiveness plays in person perception. PMID:27410051
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.
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.
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
Eruption Forecasting: Success and Surprise at Kasatochi and Okmok Volcanoes
NASA Astrophysics Data System (ADS)
Prejean, S.; Power, J.; Brodsky, E.
2008-12-01
seismic network on Kasatochi Island. Unlike Kasatochi, Okmok volcano, also located in the central Aleutian Islands, hosts 13 telemetered seismic stations and several telemetered GPS stations. The volcano has received considerable study by AVO, and the record of historical eruptions is well known. Despite regular scrutiny of Okmok data, the 2008 eruption was a surprise as there were fewer than 3 hours of clear pre-eruptive seismicity. The color code/alert level at Okmok went directly from Green/Normal to Red/Warning on July 12 after eruptive activity began. Interpretation of co-eruptive seismicity remained a challenge through the course of the eruption as bursts of volcanic tremor often did not correlate immediately with ash output at the vent as observed in satellite data.
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
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…
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…
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…
Accurate Biomass Estimation via Bayesian Adaptive Sampling
NASA Technical Reports Server (NTRS)
Wheeler, Kevin R.; Knuth, Kevin H.; Castle, Joseph P.; Lvov, Nikolay
2005-01-01
The following concepts were introduced: a) Bayesian adaptive sampling for solving biomass estimation; b) Characterization of MISR Rahman model parameters conditioned upon MODIS landcover. c) Rigorous non-parametric Bayesian approach to analytic mixture model determination. d) Unique U.S. asset for science product validation and verification.
Bayesian Statistics for Biological Data: Pedigree Analysis
ERIC Educational Resources Information Center
Stanfield, William D.; Carlton, Matthew A.
2004-01-01
The use of Bayes' formula is applied to the biological problem of pedigree analysis to show that the Bayes' formula and non-Bayesian or "classical" methods of probability calculation give different answers. First year college students of biology can be introduced to the Bayesian statistics.
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…
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. PMID:24670156
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
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
Flexible Bayesian Human Fecundity Models
Kim, Sungduk; Sundaram, Rajeshwari; Buck Louis, Germaine M.; Pyper, Cecilia
2016-01-01
Human fecundity is an issue of considerable interest for both epidemiological and clinical audiences, and is dependent upon a couple’s biologic capacity for reproduction coupled with behaviors that place a couple at risk for pregnancy. Bayesian hierarchical models have been proposed to better model the conception probabilities by accounting for the acts of intercourse around the day of ovulation, i.e., during the fertile window. These models can be viewed in the framework of a generalized nonlinear model with an exponential link. However, a fixed choice of link function may not always provide the best fit, leading to potentially biased estimates for probability of conception. Motivated by this, we propose a general class of models for fecundity by relaxing the choice of the link function under the generalized nonlinear model framework. We use a sample from the Oxford Conception Study (OCS) to illustrate the utility and fit of this general class of models for estimating human conception. Our findings reinforce the need for attention to be paid to the choice of link function in modeling conception, as it may bias the estimation of conception probabilities. Various properties of the proposed models are examined and a Markov chain Monte Carlo sampling algorithm was developed for implementing the Bayesian computations. The deviance information criterion measure and logarithm of pseudo marginal likelihood are used for guiding the choice of links. The supplemental material section contains technical details of the proof of the theorem stated in the paper, and contains further simulation results and analysis.
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
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
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
Encoding expert knowledge: A Bayesian diagnostic system for diesel generators
Bley, D.C.
1991-01-01
Developing computer systems to capture the knowledge of human experts offers new opportunities to electric utilities. Such systems become particularly attractive when technical expertise resides within a single individual, possibly nearing retirement, who has not otherwise passed along his important knowledge and though processes. An expert system model called the Bayesian diagnostic module (BMD) has been developed to aid plant personnel in diagnosing the causes of equipment failure. The BDM deals with uncertainty in a mathematically logical and rigorous way. If sufficient observables are provided as input, it can identify a single cause of failure with very high confidence. Given less complete information, the method degrades gracefully by advising operators about alternative causes of failure, including as estimate of the likelihood that each cause is the correct one. The complete theoretical foundation of the BDM is briefly summarized in this paper.
First names and perceptions of physical attractiveness.
Erwin, P G
1993-11-01
I examined the impact of first names on ratings of physical attractiveness as judged by British undergraduate subjects using male and female full-face pictures presented on photographic slides. The photographs were identified with attractive names, unattractive names, or without any name indicated. Subjects rated the stimulus figures for physical attractiveness. Names accounted for approximately 6% of the variance in subjects' ratings of physical attractiveness. This effect was highly significant for pictures of women (p < .001), but nonsignificant for pictures of men (p > .05). PMID:8301616
Bayesian Approach to Network Modularity
Hofman, Jake M.; Wiggins, Chris H.
2009-01-01
We present an efficient, principled, and interpretable technique for inferring module assignments and for identifying the optimal number of modules in a given network. We show how several existing methods for finding modules can be described as variant, special, or limiting cases of our work, and how the method overcomes the resolution limit problem, accurately recovering the true number of modules. Our approach is based on Bayesian methods for model selection which have been used with success for almost a century, implemented using a variational technique developed only in the past decade. We apply the technique to synthetic and real networks and outline how the method naturally allows selection among competing models. PMID:18643711
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 Kernel Mixtures for Counts
Canale, Antonio; Dunson, David B.
2011-01-01
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. PMID:22523437
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. PMID:22523437
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. PMID:27443742
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…
Interpersonal Attraction in the Counseling Relationship.
ERIC Educational Resources Information Center
Wachowiak, Dale; Diaz, Sandra
Murstein's Stimulus-Value-Role theory of dyadic relationships, in which attraction depends on the exchange value of the assets and liabilities each person brings to the situation, is employed as a foundation for this review of the literature on interpersonal attraction in the counseling relationship. A three-stage model, accounting for both…
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...
An Attributional Approach to Counselor Attractiveness.
ERIC Educational Resources Information Center
Hackman, Hollis W.; Claiborn, Charles D.
1982-01-01
Examined two components of counselor attractiveness--perceived similarity and liking--in a comparison of two theoretical approaches to attractiveness and influence in counseling--the referent power hypothesis and an attributional approach. Results generally support the attributional approach over the reference power hypothesis. (Author)
Correlates of Attraction Among Preschool Children.
ERIC Educational Resources Information Center
Ross, Michael B.
The generalizability of several variables which have been related to attraction among adults to preschool children was investigated. It was found that perceived physical attractiveness, perceived proximity, and familiarity are all significantly positively correlated with how popular a child is in his nursery school class. (Author)
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…
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.
Attitude Similarity, Topic Importance, and Psychotherapeutic Attraction
ERIC Educational Resources Information Center
Cheney, Thomas
1975-01-01
The effect of attitude similarity and topic importance on attraction was studied by exposing 75 prison inmates, incarcerated for public intoxication, to varying attitudes of a psychotherapist. Subjects were more attracted to the therapist after receiving alcohol items regardless of degree of similarity expressed. (Author)
Attraction, Discrepancy and Responses to Psychological Treatment.
ERIC Educational Resources Information Center
Patton, Michael J.
The responses of a laboratory subject (S) to a counselor-accomplice and to the psychological treatment situation are examined by manipulating experimentally interpersonal attraction and communication discrepancy. Four treatment conditions were set up: (1) topic similarity and positive attraction for counselor, (2) topic discrepancy and positive…
Surprise disrupts cognition via a fronto-basal ganglia suppressive mechanism.
Wessel, Jan R; Jenkinson, Ned; Brittain, John-Stuart; Voets, Sarah H E M; Aziz, Tipu Z; Aron, Adam R
2016-01-01
Surprising events markedly affect behaviour and cognition, yet the underlying mechanism is unclear. Surprise recruits a brain mechanism that globally suppresses motor activity, ostensibly via the subthalamic nucleus (STN) of the basal ganglia. Here, we tested whether this suppressive mechanism extends beyond skeletomotor suppression and also affects cognition (here, verbal working memory, WM). We recorded scalp-EEG (electrophysiology) in healthy participants and STN local field potentials in Parkinson's patients during a task in which surprise disrupted WM. For scalp-EEG, surprising events engage the same independent neural signal component that indexes action stopping in a stop-signal task. Importantly, the degree of this recruitment mediates surprise-related WM decrements. Intracranially, STN activity is also increased post surprise, especially when WM is interrupted. These results suggest that surprise interrupts cognition via the same fronto-basal ganglia mechanism that interrupts action. This motivates a new neural theory of how cognition is interrupted, and how distraction arises after surprising events. PMID:27088156
Surprise disrupts cognition via a fronto-basal ganglia suppressive mechanism
Wessel, Jan R.; Jenkinson, Ned; Brittain, John-Stuart; Voets, Sarah H. E. M.; Aziz, Tipu Z.; Aron, Adam R.
2016-01-01
Surprising events markedly affect behaviour and cognition, yet the underlying mechanism is unclear. Surprise recruits a brain mechanism that globally suppresses motor activity, ostensibly via the subthalamic nucleus (STN) of the basal ganglia. Here, we tested whether this suppressive mechanism extends beyond skeletomotor suppression and also affects cognition (here, verbal working memory, WM). We recorded scalp-EEG (electrophysiology) in healthy participants and STN local field potentials in Parkinson's patients during a task in which surprise disrupted WM. For scalp-EEG, surprising events engage the same independent neural signal component that indexes action stopping in a stop-signal task. Importantly, the degree of this recruitment mediates surprise-related WM decrements. Intracranially, STN activity is also increased post surprise, especially when WM is interrupted. These results suggest that surprise interrupts cognition via the same fronto-basal ganglia mechanism that interrupts action. This motivates a new neural theory of how cognition is interrupted, and how distraction arises after surprising events. PMID:27088156
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,…
Attracting Lagrangian coherent structures on Riemannian manifolds.
Karrasch, Daniel
2015-08-01
It is a wide-spread convention to identify repelling Lagrangian Coherent Structures (LCSs) with ridges of the forward finite-time Lyapunov exponent (FTLE) field and to identify attracting LCSs with ridges of the backward FTLE. However, we show that, in two-dimensional incompressible flows, also attracting LCSs appear as ridges of the forward FTLE field. This raises the issue of the characterization of attracting LCSs using a forward finite-time Lyapunov analysis. To this end, we extend recent results regarding the relationship between forward and backward maximal and minimal FTLEs, to both the whole finite-time Lyapunov spectrum and to stretch directions. This is accomplished by considering the singular value decomposition (SVD) of the linearized flow map. By virtue of geometrical insights from the SVD, we provide characterizations of attracting LCSs in forward time for two geometric approaches to hyperbolic LCSs. We apply these results to the attracting FTLE ridge of the incompressible saddle flow. PMID:26328582
Attracting Lagrangian coherent structures on Riemannian manifolds
NASA Astrophysics Data System (ADS)
Karrasch, Daniel
2015-08-01
It is a wide-spread convention to identify repelling Lagrangian Coherent Structures (LCSs) with ridges of the forward finite-time Lyapunov exponent (FTLE) field and to identify attracting LCSs with ridges of the backward FTLE. However, we show that, in two-dimensional incompressible flows, also attracting LCSs appear as ridges of the forward FTLE field. This raises the issue of the characterization of attracting LCSs using a forward finite-time Lyapunov analysis. To this end, we extend recent results regarding the relationship between forward and backward maximal and minimal FTLEs, to both the whole finite-time Lyapunov spectrum and to stretch directions. This is accomplished by considering the singular value decomposition (SVD) of the linearized flow map. By virtue of geometrical insights from the SVD, we provide characterizations of attracting LCSs in forward time for two geometric approaches to hyperbolic LCSs. We apply these results to the attracting FTLE ridge of the incompressible saddle flow.
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. PMID:27347672
Aphid Sex Pheromone Compounds Interfere with Attraction of Common Green Lacewings to Floral Bait.
Koczor, Sándor; Szentkirályi, Ferenc; Pickett, John A; Birkett, Michael A; Tóth, Miklós
2015-06-01
Common green lacewings (Chrysoperla carnea complex) form a group of generalist predators important for biological control. Several reports show attraction of these insects to plant volatiles, and a highly attractive ternary compound floral bait has been developed. With aphids being a preferred prey of larvae, one might expect these lacewings to be attracted to aphid semiochemicals, for instance, to aphid sex pheromones, as found for several other green lacewing species. However, in a previous study, we found that traps containing aphid sex pheromone compounds (1R,4aS,7S,7aR)-nepetalactol (NEPOH), (4aS,7S,7aR)-nepetalactone (NEPONE), and a ternary floral bait attracted fewer individuals than those containing the ternary floral bait alone. In the present study, possible causes for this effect of NEPOH and NEPONE on trap capture were studied. We established that C. carnea complex catches in traps with a ternary floral lure were not influenced by the presence of Chrysopa formosa individuals in traps (attracted by NEPOH and NEPONE) or by synthetic skatole (a characteristic component of Chrysopa defense secretion). A direct negative effect of NEPOH and NEPONE on attraction of C. carnea complex was found, suggesting active avoidance of these aphid sex pheromone components. This finding is surprising as the larvae of these lacewings prey preferentially on aphids. Possible mechanisms underlying this phenomenon are discussed. PMID:25956798
An Intuitive Dashboard for Bayesian Network Inference
NASA Astrophysics Data System (ADS)
Reddy, Vikas; Charisse Farr, Anna; Wu, Paul; Mengersen, Kerrie; Yarlagadda, Prasad K. D. V.
2014-03-01
Current Bayesian network software packages provide good graphical interface for users who design and develop Bayesian networks for various applications. However, the intended end-users of these networks may not necessarily find such an interface appealing and at times it could be overwhelming, particularly when the number of nodes in the network is large. To circumvent this problem, this paper presents an intuitive dashboard, which provides an additional layer of abstraction, enabling the end-users to easily perform inferences over the Bayesian networks. Unlike most software packages, which display the nodes and arcs of the network, the developed tool organises the nodes based on the cause-and-effect relationship, making the user-interaction more intuitive and friendly. In addition to performing various types of inferences, the users can conveniently use the tool to verify the behaviour of the developed Bayesian network. The tool has been developed using QT and SMILE libraries in C++.
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
NASA Astrophysics Data System (ADS)
Qian, Song S.; Richardson, Curtis J.
Using wetlands as a sink of nutrients, phosphorus in particular, is becoming an increasingly attractive alternative to conventional wastewater treatment technology. In this paper, we briefly review the mechanism of phosphorus retention in wetlands, as well as previous modeling efforts. A Bayesian method is then proposed for estimating the long-term phosphorus accretion rate in wetlands through a piecewise linear model of outflow phosphorus concentration and phosphorus mass loading rate. The Bayesian approach was used for its simplicity in computation and its ability to accurately represent uncertainty. Applied to an Everglades wetland, the Bayesian method not only produced the probability distribution of the long-term phosphorus accretion rate but also generated a relationship of acceptable level of ``risk'' and optimal phosphorus mass loading rate for the proposed constructed wetlands in south Florida. The latter is a useful representation of uncertainty which is of interest to decision makers.
Attraction by Repulsion: Pairing Electrons using Electrons
NASA Astrophysics Data System (ADS)
Ilani, Shahal
One of the fundamental properties of electrons is their mutual Columbic repulsion. If electrons are placed in a solid, however, this basic property may change. A famous example is that of superconductors, where coupling to lattice vibrations makes electrons attractive and leads to the formation of bound pairs. But what if all the degrees of freedom in the solid are electronic? Is it possible to make electrons attract each other only by their repulsion to other electrons? Such an `excitonic' mechanism for attraction was proposed fifty years ago by W. A. Little, with the hope that it could lead to better and more exotic superconductivity. Yet, despite many efforts to synthesize materials that possess this unique property, to date there is still no evidence for electronic-based attraction. In this talk I will present our recent experiments that observe this unusual electronic attraction using a different, bottom-up approach. Our experiments are based on a new generation of quantum devices made from pristine carbon nanotubes, combined with precision cryogenic manipulation. Using this setup we can now assemble the fundamental building block of the excitonic attraction and demonstrate that two electrons that naturally repel each other can be made attractive using an independent electronic system as the binding glue. I will discuss the lessons learned from these experiments on what is achievable with plain electrostatics, and on the possibility to use the observed mechanism for creating exotic states of matter.
The Putative Son's Attractiveness Alters the Perceived Attractiveness of the Putative Father.
Prokop, Pavol
2015-08-01
A body of literature has investigated female mate choice in the pre-mating context (pre-mating sexual selection). Humans, however, are long-living mammals forming pair-bonds which sequentially produce offspring. Post-mating evaluations of a partner's attractiveness may thus significantly influence the reproductive success of men and women. I tested herein the theory that the attractiveness of putative sons provides extra information about the genetic quality of fathers, thereby influencing fathers' attractiveness across three studies. As predicted, facially attractive boys were more frequently attributed to attractive putative fathers and vice versa (Study 1). Furthermore, priming with an attractive putative son increased the attractiveness of the putative father with the reverse being true for unattractive putative sons. When putative fathers were presented as stepfathers, the effect of the boy's attractiveness on the stepfather's attractiveness was lower and less consistent (Study 2). This suggests that the presence of an attractive boy has the strongest effect on the perceived attractiveness of putative fathers rather than on non-fathers. The generalized effect of priming with beautiful non-human objects also exists, but its effect is much weaker compared with the effects of putative biological sons (Study 3). Overall, this study highlighted the importance of post-mating sexual selection in humans and suggests that the heritable attractive traits of men are also evaluated by females after mating and/or may be used by females in mate poaching. PMID:25731909
Singh, R; Ho, S Y
2000-06-01
Dissimilarity and similarity between attitudes of the participants and a stranger were manipulated across two sets of issues to test the attraction, repulsion and similarity-dissimilarity asymmetry hypotheses. Participants (N = 192) judged social (liking, enjoyment of company) and intellectual (intelligence, general knowledge) attractiveness of the stranger. The similarity in the first set of attitudes x similarity in the second set of attitudes effect emerged in social attraction, but not in intellectual attraction. Stated simply, dissimilarity had a greater weight than similarity in social attraction, but equal weight in intellectual attraction. These results support the similarity-dissimilarity asymmetry hypothesis that predicts dissimilarity-repulsion to be stronger than similarity-attraction. However, they reject (1) the attraction hypothesis that dissimilarity and similarity produce equal and opposite effects on social attraction; and (2) the repulsion hypothesis that only dissimilar attitudes affect social attraction by leading to repulsion. An equal weighting of dissimilarity and similarity in intellectual attraction further suggested that the similarity-dissimilarity asymmetry on social attraction is reflective of a stronger avoidance response in the Darwinian sense. PMID:10907095
BNFinder2: Faster Bayesian network learning and Bayesian classification
Dojer, Norbert; Bednarz, Paweł; Podsiadło, Agnieszka; Wilczyński, Bartek
2013-01-01
Summary: Bayesian Networks (BNs) are versatile probabilistic models applicable to many different biological phenomena. In biological applications the structure of the network is usually unknown and needs to be inferred from experimental data. BNFinder is a fast software implementation of an exact algorithm for finding the optimal structure of the network given a number of experimental observations. Its second version, presented in this article, represents a major improvement over the previous version. The improvements include (i) a parallelized learning algorithm leading to an order of magnitude speed-ups in BN structure learning time; (ii) inclusion of an additional scoring function based on mutual information criteria; (iii) possibility of choosing the resulting network specificity based on statistical criteria and (iv) a new module for classification by BNs, including cross-validation scheme and classifier quality measurements with receiver operator characteristic scores. Availability and implementation: BNFinder2 is implemented in python and freely available under the GNU general public license at the project Web site https://launchpad.net/bnfinder, together with a user’s manual, introductory tutorial and supplementary methods. Contact: dojer@mimuw.edu.pl or bartek@mimuw.edu.pl Supplementary information: Supplementary data are available at Bioinformatics online. PMID:23818512
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
Charge-induced patchy attractions between proteins.
Li, Weimin; Persson, Björn A; Morin, Maxim; Behrens, Manja A; Lund, Mikael; Zackrisson Oskolkova, Malin
2015-01-15
Static light scattering (SLS) combined with structure-based Monte Carlo (MC) simulations provide new insights into mechanisms behind anisotropic, attractive protein interactions. A nonmonotonic behavior of the osmotic second virial coefficient as a function of ionic strength is here shown to originate from a few charged amino acids forming an electrostatic attractive patch, highly directional and complementary. Together with Coulombic repulsion, this attractive patch results in two counteracting electrostatic contributions to the interaction free energy which, by operating over different length scales, is manifested in a subtle, salt-induced minimum in the second virial coefficient as observed in both experiment and simulations. PMID:25494398
A letter from the United States: the fox in our backyard--science, serendipity and surprise.
Lee, Richard V
2009-11-01
The story of how Charles Darwin composed The Origin of Species, published in November of 1859, has been told many times during the bicentennial of Darwin s birth and the sesquicentennial of the publication of the book. It is a history well known to biologists and historians of science. The heated debate that accompanied the demonstration of natural selection as a mechanism of speciation and continues to the present is surprising. Human beings do not welcome surprise: "the emotion aroused by something unexpected." The history of science and human intellect, however, illustrate the creative stimulus of surprise and serendipity in the development of human knowledge and the evolution of culture. The lives of Homo sapiens would not change if our intellect was unable or unwilling to respond to the unexpected and to make connections between surprising and commonplace events. The rich diversity of South American life was surprising to the European travelers of the 18th and 19th centuries: surprising by its beauty and profusion, but also by its similarities to the creatures of Europe and Africa. Darwin s curiosity sought and welcomed surprise). PMID:20098812
Nessler, Bernhard; Pfeiffer, Michael; Buesing, Lars; Maass, Wolfgang
2013-04-01
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
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
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
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
Physical Distance and Attraction: An Intensification Effect
ERIC Educational Resources Information Center
Schiffenbauer, Allen; Schiavo, R. Steven
1976-01-01
This study was designed to test the effects of both interaction distance and the quality of the interaction upon attraction. The implications of this research for studies concerning crowding is discussed, as are possible explanatory mechanisms. (Editor/RK)
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. PMID:23499392
Integrating body movement into attractiveness research
Fink, Bernhard; Weege, Bettina; Neave, Nick; Pham, Michael N.; Shackelford, Todd K.
2015-01-01
People judge attractiveness and make trait inferences from the physical appearance of others, and research reveals high agreement among observers making such judgments. Evolutionary psychologists have argued that interest in physical appearance and beauty reflects adaptations that motivate the search for desirable qualities in a potential partner. Although men more than women value the physical appearance of a partner, appearance universally affects social perception in both sexes. Most studies of attractiveness perceptions have focused on third party assessments of static representations of the face and body. Corroborating evidence suggests that body movement, such as dance, also conveys information about mate quality. Here we review evidence that dynamic cues (e.g., gait, dance) also influence perceptions of mate quality, including personality traits, strength, and overall attractiveness. We recommend that attractiveness research considers the informational value of body movement in addition to static cues, to present an integrated perspective on human social perception. PMID:25784887
Locus of Control and Interpersonal Attraction.
ERIC Educational Resources Information Center
Fagan, M. Michael
1980-01-01
The role of locus of control in interpersonal attraction was examined by administering 1) the Nowicki-Strickland Locus of Control Scale and 2) a sociometric test of friendship to 200 eighth graders. (CM)
Integrating body movement into attractiveness research.
Fink, Bernhard; Weege, Bettina; Neave, Nick; Pham, Michael N; Shackelford, Todd K
2015-01-01
People judge attractiveness and make trait inferences from the physical appearance of others, and research reveals high agreement among observers making such judgments. Evolutionary psychologists have argued that interest in physical appearance and beauty reflects adaptations that motivate the search for desirable qualities in a potential partner. Although men more than women value the physical appearance of a partner, appearance universally affects social perception in both sexes. Most studies of attractiveness perceptions have focused on third party assessments of static representations of the face and body. Corroborating evidence suggests that body movement, such as dance, also conveys information about mate quality. Here we review evidence that dynamic cues (e.g., gait, dance) also influence perceptions of mate quality, including personality traits, strength, and overall attractiveness. We recommend that attractiveness research considers the informational value of body movement in addition to static cues, to present an integrated perspective on human social perception. PMID:25784887
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. PMID:27627373
Spatiotemporal Bayesian Networks for Malaria Prediction: Case Study of Northern Thailand.
Haddawy, Peter; Kasantikul, Rangwan; Hasan, A H M Imrul; Rattanabumrung, Chunyanuch; Rungrun, Pichamon; Suksopee, Natwipa; Tantiwaranpant, Saran; Niruntasuk, Natcha
2016-01-01
While a diversity of modeling technique have been used to create predictive models of malaria, no work has made use of Bayesian networks. Bayes nets are attractive due to their ability to represent uncertainty, model time lagged and nonlinear relations, and provide explanations of inferences. This paper explores the use of Bayesian networks to model malaria, demonstrating the approach by creating a village level model with weekly temporal resolution for Tha Song Yang district in northern Thailand. The network is learned using data on cases and environmental covariates. The network models incidence over time as well as evolution of the environmental variables, and captures time lagged and nonlinear effects. Out of sample evaluation shows the model to have high accuracy for one and two week predictions. PMID:27577491
Deductive updating is not Bayesian.
Markovits, Henry; Brisson, Janie; de Chantal, Pier-Luc
2015-07-01
One of the major debates concerning the nature of inferential reasoning is between counterexample-based theories such as mental model theory and probabilistic theories. This study looks at conclusion updating after the addition of statistical information to examine the hypothesis that deductive reasoning cannot be explained by probabilistic inferences. In Study 1, participants were given an initial "If P then Q rule" for a phenomenon on a recently discovered planet, told that "Q was true," and asked to make a judgment of either deductive validity or probabilistic likelihood of the putative conclusion that "P is true." They were then told the results of 1,000 observations. In the low-probability problem, 950 times P was false and Q was true, whereas 50 times P was true and Q was true. In the high-probability problem, these proportions were inverted. On the low-probability problem, probabilistic ratings and judgments of logical validity decreased. However, on the high-probability problem, probabilistic ratings remained high whereas judgments of logical validity significantly decreased. Confidence ratings were consistent with this different pattern for probabilistic and for deductive inferences. Study 2 replicated this result with another form of inference, "If P then Q. P is false." These results show that deductive updating is not explicable by Bayesian updating. PMID:25603167
Bayesian Analysis of Underground Flooding
NASA Astrophysics Data System (ADS)
Bogardi, Istvan; Duckstein, Lucien; Szidarovszky, Ferenc
1982-08-01
An event-based stochastic model is used to describe the spatial phenomenon of water inrush into underground works located under a karstic aquifer, and a Bayesian analysis is performed because of high parameter uncertainty. The random variables of the model are inrush yield per event, distance between events, number of events per unit underground space, maximum yield, and total yield over mine lifetime. Physically based hypotheses on the types of distributions are made and reinforced by observations. High parameter uncertainty stems from the random characteristics of karstic limestone and the limited amount of observation data. Thus, during the design stage, only indirect data such as regional information and geological analogies are available; updating of this information should then be done as the construction progresses and inrush events are observed and recorded. A Bayes simulation algorithm is developed and applied to estimate the probability distributions of inrush event characteristics used in the design of water control facilities in underground mining. A real-life example in the Transdanubian region of Hungary is used to illustrate the methodology.
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.
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 analysis of volcanic eruptions
NASA Astrophysics Data System (ADS)
Ho, Chih-Hsiang
1990-10-01
The simple Poisson model generally gives a good fit to many volcanoes for volcanic eruption forecasting. Nonetheless, empirical evidence suggests that volcanic activity in successive equal time-periods tends to be more variable than a simple Poisson with constant eruptive rate. An alternative model is therefore examined in which eruptive rate(λ) for a given volcano or cluster(s) of volcanoes is described by a gamma distribution (prior) rather than treated as a constant value as in the assumptions of a simple Poisson model. Bayesian analysis is performed to link two distributions together to give the aggregate behavior of the volcanic activity. When the Poisson process is expanded to accomodate a gamma mixing distribution on λ, a consequence of this mixed (or compound) Poisson model is that the frequency distribution of eruptions in any given time-period of equal length follows the negative binomial distribution (NBD). Applications of the proposed model and comparisons between the generalized model and simple Poisson model are discussed based on the historical eruptive count data of volcanoes Mauna Loa (Hawaii) and Etna (Italy). Several relevant facts lead to the conclusion that the generalized model is preferable for practical use both in space and time.
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
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
Sparse Bayesian infinite factor models
Bhattacharya, A.; Dunson, D. B.
2011-01-01
We focus on sparse modelling of high-dimensional covariance matrices using Bayesian latent factor models. We propose a multiplicative gamma process shrinkage prior on the factor loadings which allows introduction of infinitely many factors, with the loadings increasingly shrunk towards zero as the column index increases. We use our prior on a parameter-expanded loading matrix to avoid the order dependence typical in factor analysis models and develop an efficient Gibbs sampler that scales well as data dimensionality increases. The gain in efficiency is achieved by the joint conjugacy property of the proposed prior, which allows block updating of the loadings matrix. We propose an adaptive Gibbs sampler for automatically truncating the infinite loading matrix through selection of the number of important factors. Theoretical results are provided on the support of the prior and truncation approximation bounds. A fast algorithm is proposed to produce approximate Bayes estimates. Latent factor regression methods are developed for prediction and variable selection in applications with high-dimensional correlated predictors. Operating characteristics are assessed through simulation studies, and the approach is applied to predict survival times from gene expression data. PMID:23049129
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
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
Sequential effects in face-attractiveness judgment.
Kondo, Aki; Takahashi, Kohske; Watanabe, Katsumi
2012-01-01
A number of studies have shown that current-trial responses are biased toward the response of the preceding trial in perceptual decisionmaking tasks (the sequential effect-Holland and Lockhead, 1968 Perception & Psychophysics 3 409-414). The sequential effect has been widely observed in evaluation of the physical properties of stimuli as well as more complex properties. However, it is unclear whether subjective decisions (e.g., attractiveness judgments) are also susceptible to the sequential effect. Here, we examined whether the sequential effect would occur in face-attractiveness judgments. Forty-eight pictures of male and female faces were presented successively. Participants rated the attractiveness of each face on a 7-point scale. The results showed that the attractiveness rating of a given face assimilated toward the rating of the preceding trial. In a separate experiment, we provided the average attractiveness rating by others for each trial as feedback. The feedback weakened the sequential effect. These findings suggest that attractiveness judgment is also biased toward the preceding judgment, and hence the sequential effect can be extended into the domain of subjective decisionmaking. PMID:22611662
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…
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.
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…
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
Surprise! Infants consider possible bases of generalization for a single input example
Gerken, LouAnn; Dawson, Colin; Chatila, Razanne; Tenenbaum, Josh
2014-01-01
Infants have been shown to generalize from a small number of input examples. However, existing studies allow two possible means of generalization. One is via a process of noting similarities shared by several examples. Alternatively, generalization may reflect an implicit desire to explain the input. The latter view suggests that generalization might occur when even a single input example is surprising, given the learner’s current model of the domain. To test the possibility that infants are able to generalize based on a single example, we familiarized 9-month-olds with a single three-syllable input example that contained either one surprising feature (syllable repetition, Exp. 1) or two features (repetition and a rare syllable, Exp. 2). In both experiments, infants generalized only to new strings that maintained all of the surprising features from familiarization. This research suggests that surprise can promote very rapid generalization. PMID:24703007
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.
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
Computational surprisal analysis speeds-up genomic characterization of cancer processes.
Kravchenko-Balasha, Nataly; Simon, Simcha; Levine, R D; Remacle, F; Exman, Iaakov
2014-01-01
Surprisal analysis is increasingly being applied for the examination of transcription levels in cellular processes, towards revealing inner network structures and predicting response. But to achieve its full potential, surprisal analysis should be integrated into a wider range computational tool. The purposes of this paper are to combine surprisal analysis with other important computation procedures, such as easy manipulation of the analysis results--e.g. to choose desirable result sub-sets for further inspection--, retrieval and comparison with relevant datasets from public databases, and flexible graphical displays for heuristic thinking. The whole set of computation procedures integrated into a single practical tool is what we call Computational Surprisal Analysis. This combined kind of analysis should facilitate significantly quantitative understanding of different cellular processes for researchers, including applications in proteomics and metabolomics. Beyond that, our vision is that Computational Surprisal Analysis has the potential to reach the status of a routine method of analysis for practitioners. The resolving power of Computational Surprisal Analysis is here demonstrated by its application to a variety of cellular cancer process transcription datasets, ours and from the literature. The results provide a compact biological picture of the thermodynamic significance of the leading gene expression phenotypes in every stage of the disease. For each transcript we characterize both its inherent steady state weight, its correlation with the other transcripts and its variation due to the disease. We present a dedicated website to facilitate the analysis for researchers and practitioners. PMID:25405334
Kawaguchi, Norihiko; Sakamoto, Kazuhiro; Saito, Naohiro; Furusawa, Yoshito; Tanji, Jun; Aoki, Masashi; Mushiake, Hajime
2015-02-01
Visual search is coordinated adaptively by monitoring and predicting the environment. The supplementary eye field (SEF) plays a role in oculomotor control and outcome evaluation. However, it is not clear whether the SEF is involved in adjusting behavioral modes based on preceding feedback. We hypothesized that the SEF drives exploration-exploitation transitions by generating "surprise signals" or rectified prediction errors, which reflect differences between predicted and actual outcomes. To test this hypothesis, we introduced an oculomotor two-target search task in which monkeys were required to find two valid targets among four identical stimuli. After they detected the valid targets, they exploited their knowledge of target locations to obtain a reward by choosing the two valid targets alternately. Behavioral analysis revealed two distinct types of oculomotor search patterns: exploration and exploitation. We found that two types of SEF neurons represented the surprise signals. The error-surprise neurons showed enhanced activity when the monkey received the first error feedback after the target pair change, and this activity was followed by an exploratory oculomotor search pattern. The correct-surprise neurons showed enhanced activity when the monkey received the first correct feedback after an error trial, and this increased activity was followed by an exploitative, fixed-type search pattern. Our findings suggest that error-surprise neurons are involved in the transition from exploitation to exploration and that correct-surprise neurons are involved in the transition from exploration to exploitation. PMID:25411455
Computational Surprisal Analysis Speeds-Up Genomic Characterization of Cancer Processes
Kravchenko-Balasha, Nataly; Simon, Simcha; Levine, R. D.; Remacle, F.; Exman, Iaakov
2014-01-01
Surprisal analysis is increasingly being applied for the examination of transcription levels in cellular processes, towards revealing inner network structures and predicting response. But to achieve its full potential, surprisal analysis should be integrated into a wider range computational tool. The purposes of this paper are to combine surprisal analysis with other important computation procedures, such as easy manipulation of the analysis results – e.g. to choose desirable result sub-sets for further inspection –, retrieval and comparison with relevant datasets from public databases, and flexible graphical displays for heuristic thinking. The whole set of computation procedures integrated into a single practical tool is what we call Computational Surprisal Analysis. This combined kind of analysis should facilitate significantly quantitative understanding of different cellular processes for researchers, including applications in proteomics and metabolomics. Beyond that, our vision is that Computational Surprisal Analysis has the potential to reach the status of a routine method of analysis for practitioners. The resolving power of Computational Surprisal Analysis is here demonstrated by its application to a variety of cellular cancer process transcription datasets, ours and from the literature. The results provide a compact biological picture of the thermodynamic significance of the leading gene expression phenotypes in every stage of the disease. For each transcript we characterize both its inherent steady state weight, its correlation with the other transcripts and its variation due to the disease. We present a dedicated website to facilitate the analysis for researchers and practitioners. PMID:25405334
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. PMID:27114864
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
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.
Tactile length contraction as Bayesian inference.
Tong, Jonathan; Ngo, Vy; Goldreich, Daniel
2016-08-01
To perceive, the brain must interpret stimulus-evoked neural activity. This is challenging: The stochastic nature of the neural response renders its interpretation inherently uncertain. Perception would be optimized if the brain used Bayesian inference to interpret inputs in light of expectations derived from experience. Bayesian inference would improve perception on average but cause illusions when stimuli violate expectation. Intriguingly, tactile, auditory, and visual perception are all prone to length contraction illusions, characterized by the dramatic underestimation of the distance between punctate stimuli delivered in rapid succession; the origin of these illusions has been mysterious. We previously proposed that length contraction illusions occur because the brain interprets punctate stimulus sequences using Bayesian inference with a low-velocity expectation. A novel prediction of our Bayesian observer model is that length contraction should intensify if stimuli are made more difficult to localize. Here we report a tactile psychophysical study that tested this prediction. Twenty humans compared two distances on the forearm: a fixed reference distance defined by two taps with 1-s temporal separation and an adjustable comparison distance defined by two taps with temporal separation t ≤ 1 s. We observed significant length contraction: As t was decreased, participants perceived the two distances as equal only when the comparison distance was made progressively greater than the reference distance. Furthermore, the use of weaker taps significantly enhanced participants' length contraction. These findings confirm the model's predictions, supporting the view that the spatiotemporal percept is a best estimate resulting from a Bayesian inference process. PMID:27121574
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.
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. PMID:20076767
Bayesian Calibration of Microsimulation Models
Rutter, Carolyn M.; Miglioretti, Diana L.; Savarino, James E.
2009-01-01
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. PMID:20076767
Bayesian tomographic reconstruction of microsystems
NASA Astrophysics Data System (ADS)
Salem, Sofia Fekih; Vabre, Alexandre; Mohammad-Djafari, Ali
2007-11-01
The microtomography by X ray transmission plays an increasingly dominating role in the study and the understanding of microsystems. Within this framework, an experimental setup of high resolution X ray microtomography was developed at CEA-List to quantify the physical parameters related to the fluids flow in microsystems. Several difficulties rise from the nature of experimental data collected on this setup: enhanced error measurements due to various physical phenomena occurring during the image formation (diffusion, beam hardening), and specificities of the setup (limited angle, partial view of the object, weak contrast). To reconstruct the object we must solve an inverse problem. This inverse problem is known to be ill-posed. It therefore needs to be regularized by introducing prior information. The main prior information we account for is that the object is composed of a finite known number of different materials distributed in compact regions. This a priori information is introduced via a Gauss-Markov field for the contrast distributions with a hidden Potts-Markov field for the class materials in the Bayesian estimation framework. The computations are done by using an appropriate Markov Chain Monte Carlo (MCMC) technique. In this paper, we present first the basic steps of the proposed algorithms. Then we focus on one of the main steps in any iterative reconstruction method which is the computation of forward and adjoint operators (projection and backprojection). A fast implementation of these two operators is crucial for the real application of the method. We give some details on the fast computation of these steps and show some preliminary results of simulations.
Bayesian analogy with relational transformations.
Lu, Hongjing; Chen, Dawn; Holyoak, Keith J
2012-07-01
How can humans acquire relational representations that enable analogical inference and other forms of high-level reasoning? Using comparative relations as a model domain, we explore the possibility that bottom-up learning mechanisms applied to objects coded as feature vectors can yield representations of relations sufficient to solve analogy problems. We introduce Bayesian analogy with relational transformations (BART) and apply the model to the task of learning first-order comparative relations (e.g., larger, smaller, fiercer, meeker) from a set of animal pairs. Inputs are coded by vectors of continuous-valued features, based either on human magnitude ratings, normed feature ratings (De Deyne et al., 2008), or outputs of the topics model (Griffiths, Steyvers, & Tenenbaum, 2007). Bootstrapping from empirical priors, the model is able to induce first-order relations represented as probabilistic weight distributions, even when given positive examples only. These learned representations allow classification of novel instantiations of the relations and yield a symbolic distance effect of the sort obtained with both humans and other primates. BART then transforms its learned weight distributions by importance-guided mapping, thereby placing distinct dimensions into correspondence. These transformed representations allow BART to reliably solve 4-term analogies (e.g., larger:smaller::fiercer:meeker), a type of reasoning that is arguably specific to humans. Our results provide a proof-of-concept that structured analogies can be solved with representations induced from unstructured feature vectors by mechanisms that operate in a largely bottom-up fashion. We discuss potential implications for algorithmic and neural models of relational thinking, as well as for the evolution of abstract thought. PMID:22775500
Predation-Related Costs and Benefits of Conspecific Attraction in Songbirds—An Agent-Based Approach
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
NASA Astrophysics Data System (ADS)
Kuhlicke, C.
2009-04-01
By definition natural disasters always contain a moment of surprise. Their occurrence is mostly unforeseen and unexpected. They hit people unprepared, overwhelm them and expose their helplessness. Yet, there is surprisingly little known on the reasons for their being surprised. Aren't natural disasters expectable and foreseeable after all? Aren't the return rates of most hazards well known and shouldn't people be better prepared? The central question of this presentation is hence: Why do natural disasters so often radically surprise people at all (and how can we explain this being surprised)? In the first part of the presentation, it is argued that most approaches to vulnerability are not able to grasp this moment of surprise. On the contrary, they have their strength in unravelling the expectable: A person who is marginalized or even oppressed in everyday life is also vulnerable during times of crisis and stress, at least this is the central assumption of most vulnerability studies. In the second part, an understanding of vulnerability is developed, which allows taking into account such radical surprises. First, two forms of the unknown are differentiated: An area of the unknown an actor is more or less aware of (ignorance), and an area, which is not even known to be not known (nescience). The discovery of the latter is mostly associated with a "radical surprise", since it is per definition impossible to prepare for it. Second, a definition of vulnerability is proposed, which allows capturing the dynamics of surprises: People are vulnerable when they discover their nescience exceeding by definition previously established routines, stocks of knowledge and resources—in a general sense their capacities—to deal with their physical and/or social environment. This definition explicitly takes the view of different actors serious and departs from their being surprised. In the third part findings of a case study are presented, the 2002 flood in Germany. It is shown
A Bayesian Approach for Multigroup Nonlinear Factor Analysis.
ERIC Educational Resources Information Center
Song, Xin-Yuan; Lee, Sik-Yum
2002-01-01
Developed a Bayesian approach for a general multigroup nonlinear factor analysis model that simultaneously obtains joint Bayesian estimates of the factor scores and the structural parameters subjected to some constraints across different groups. (SLD)
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.
Evolution of 'pollinator'- attracting signals in fungi.
Schiestl, Florian P; Steinebrunner, Fabrizio; Schulz, Claudia; von Reuss, Stephan; Francke, Wittko; Weymuth, Christophe; Leuchtmann, Adrian
2006-09-22
Fungi produce a plethora of secondary metabolites yet their biological significance is often little understood. Some compounds show well-known antibiotic properties, others may serve as volatile signals for the attraction of insects that act as vectors of spores or gametes. Our investigations in an outcrossing, self-incompatible fungus show that a fungus-produced volatile compound with fungitoxic activities is also responsible for the attraction of specific insects that transfer gametes. We argue that insect attraction using this compound is likely to have evolved from its primary function of defence--as has been suggested for floral scent in the angiosperms. We, thus, propose that similar yet convergent evolutionary pathways have lead to interspecific communication signals in both fungi and plants. PMID:17148414
Recognition bias and the physical attractiveness stereotype.
Rohner, Jean-Christophe; Rasmussen, Anders
2012-06-01
Previous studies have found a recognition bias for information consistent with the physical attractiveness stereotype (PAS), in which participants believe that they remember that attractive individuals have positive qualities and that unattractive individuals have negative qualities, regardless of what information actually occurred. The purpose of this research was to examine whether recognition bias for PAS congruent information is replicable and invariant across a variety of conditions (i.e. generalizable). The effects of nine different moderator variables were examined in two experiments. With a few exceptions, the effect of PAS congruence on recognition bias was independent of the moderator variables. The results suggest that the tendency to believe that one remembers information consistent with the physical attractiveness stereotype is a robust phenomenon. PMID:22416805
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. PMID:27300913
Motivated behavioral outcomes affect ratings of attractiveness.
Bernard, Larry C; Hardy, David J
2014-12-01
A relatively new theory of motivation posits that purposeful human behavior may be partly explained by multidimensional individual differences "traits of action" (motives). Its 15 motives can be characterized according to their purpose: individual integrity, competitiveness, and cooperativeness. Existing evidence supports the model on which the motives are based and the reliability and validity of strategies to assess them. This experiment tested whether the hypothetical results of consistent, motivated cooperative and competitive behavior could affect ratings of attractiveness. Male and female participants (N = 98; M age = 18.8, SD = 1.4) were shown 24 opposite-sex facial photos ranging in attractiveness. The photos were paired with one of three conditions representing theoretical outcomes that would result from low, control, and high levels of cooperative and competitive motives. As predicted, outcome descriptions representing high motive strength of six motives statistically significantly affected ratings of attractiveness. This result was independent of sex of participant and consistent with the theory. PMID:25457092
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
Schmidt, D.M.; George, J.S.; Wood, C.C.
1999-04-01
The authors developed a method for analyzing neural electromagnetic data that allows probabilistic inferences to be drawn about regions of activation. The method involves the generation of a large number of possible solutions which both fir the data and prior expectations about the nature of probable solutions made explicit by a Bayesian formalism. In addition, they have introduced a model for the current distributions that produce MEG and (EEG) data that allows extended regions of activity, and can easily incorporate prior information such as anatomical constraints from MRI. To evaluate the feasibility and utility of the Bayesian approach with actual data, they analyzed MEG data from a visual evoked response experiment. They compared Bayesian analyses of MEG responses to visual stimuli in the left and right visual fields, in order to examine the sensitivity of the method to detect known features of human visual cortex organization. They also examined the changing pattern of cortical activation as a function of time.
Bayesian network structure learning using quantum annealing
NASA Astrophysics Data System (ADS)
O'Gorman, B.; Babbush, R.; Perdomo-Ortiz, A.; Aspuru-Guzik, A.; Smelyanskiy, V.
2015-02-01
We introduce a method for the problem of learning the structure of a Bayesian network using the quantum adiabatic algorithm. We do so by introducing an efficient reformulation of a standard posterior-probability scoring function on graphs as a pseudo-Boolean function, which is equivalent to a system of 2-body Ising spins, as well as suitable penalty terms for enforcing the constraints necessary for the reformulation; our proposed method requires 𝓞(n2) qubits for n Bayesian network variables. Furthermore, we prove lower bounds on the necessary weighting of these penalty terms. The logical structure resulting from the mapping has the appealing property that it is instance-independent for a given number of Bayesian network variables, as well as being independent of the number of data cases.
Tobia, Michael J; Gläscher, Jan; Sommer, Tobias
2016-06-15
This experiment investigated whether behavioral surprise, an information-theoretic measure of the amount of memory and information integration associated with a response, is correlated with neural activity during decision making. A total of 30 participants (age 18-30) were scanned with functional MRI while completing 240 trials of a sequential decision-making task in which they selected an amount to wager from four possible values on each trial. Behavioral surprise was computed trial by trial using both context-free and context-specific formulations, and was used as a parametric modulator in functional MRI analyses. Whereas context-free surprise was not significantly correlated, two sets of clusters (P<0.005; cluster size>156 voxels) were differentially modulated by context-specific behavioral surprise. An anterior system comprised of the inferior frontal gyrus and anterior cingulate (each bilaterally), and left caudate, was positively modulated. A posterior system comprised of the posterior cingulate, parahippocampal gyrus and posterior hippocampus (each bilaterally), and left angular gyrus, was negatively modulated. These anticorrelated systems indicate that more surprising (resource demanding) actions recruit greater activity from the anterior system and less activity from the posterior system and less surprising actions (memory-guided) recruit greater activity from the posterior system and less activity from the anterior system. These results show that context-specific behavioral surprise is a unique neural signal and may be related to mechanisms for both cognitive control and memory-guided behavior, and support contemporary theories that the brain is a statistical observer of external and internal events. PMID:27110868
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
Malaria Parasites Produce Volatile Mosquito Attractants
Kelly, Megan; Su, Chih-Ying; Schaber, Chad; Crowley, Jan R.; Hsu, Fong-Fu; Carlson, John R.
2015-01-01
ABSTRACT The malaria parasite Plasmodium falciparum contains a nonphotosynthetic plastid organelle that possesses plant-like metabolic pathways. Plants use the plastidial isoprenoid biosynthesis pathway to produce volatile odorants, known as terpenes. In this work, we describe the volatile chemical profile of cultured malaria parasites. Among the identified compounds are several plant-like terpenes and terpene derivatives, including known mosquito attractants. We establish the molecular identity of the odorant receptors of the malaria mosquito vector Anopheles gambiae, which responds to these compounds. The malaria parasite produces volatile signals that are recognized by mosquitoes and may thereby mediate host attraction and facilitate transmission. PMID:25805727
Floral Nectar: Pollinator Attraction or Manipulation?
Pyke, Graham H
2016-05-01
The literature suggests that floral nectar acts principally to attract pollinator visitation (and/or revisitation), thereby enhancing plant reproductive success. However, floral nectar also manipulates pollinator behaviour during and immediately following plant visits, affecting pollen transfer, and plant reproduction. I argue that floral nectar should really be viewed as a pollinator manipulant rather than attractant, thus potentially explaining why its concentration is not generally high and why it decreases with increasing pollinator body size. Otherwise, such patterns may remain mysterious and unexplained. PMID:26987770
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.
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.
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.
Bayesian parameter estimation for effective field theories
NASA Astrophysics Data System (ADS)
Wesolowski, Sarah; Klco, Natalie; Furnstahl, Richard; Phillips, Daniel; Thapilaya, Arbin
2015-10-01
We present a procedure based on Bayesian statistics for effective field theory (EFT) parameter estimation from experimental or lattice data. The extraction of low-energy constants (LECs) is guided by physical principles such as naturalness in a quantifiable way and various sources of uncertainty are included by the specification of Bayesian priors. Special issues for EFT parameter estimation are demonstrated using representative model problems, and a set of diagnostics is developed to isolate and resolve these issues. We apply the framework to the extraction of the LECs of the nucleon mass expansion in SU(2) chiral perturbation theory from synthetic lattice data.
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
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
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…
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.…
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
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
ERIC Educational Resources Information Center
Cavior, Norman; And Others
1975-01-01
Tenth and twelfth grade males and females who knew each other judged, within grade levels, their classmates on physical attractiveness (PA), perceived attitude similarity (PAS), and interpersonal attraction (IA). Regression analyses supported the hypotheses that PA and PAS are positively correlated. (Author)
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…
Sex Attraction in Bactericera cockerelli (Hemiptera: Triozidae)
Technology Transfer Automated Retrieval System (TEKTRAN)
The potato psyllid, Bactericera (= Paratrioza) cockerelli (Šulc) (Hemiptera: Triozidae), is a major pest of potato. We examined the role of chemical signals in sex attraction, assessing male and female response to male- and female-produced volatile chemicals. In laboratory olfactometer assays, pot...
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
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...
The Pioneer Anomaly as a Coulomb Attraction
NASA Astrophysics Data System (ADS)
Morris, Steven
2016-06-01
The anomalous acceleration of the Pioneer 10 and Pioneer 11 spacecraft can be explained as a Coulomb attraction between the positively-charged Solar System (due to cosmic rays) and the negatively-charged spacecraft (due to alpha-particle emission from the radioisotope thermoelectric generators).
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,…
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)
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…
Olfaction: attracting both sperm and the nose.
Vosshall, Leslie B
2004-11-01
Odorant receptor genes are expressed not only in the nose but also in testes, where they have been hypothesized to play a role in sperm chemotaxis. New data demonstrate that human odorant receptor hOR 17-4 may play similar roles in both tissues, lending support to the idea that chemical attraction is important for reproduction. PMID:15530382
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. PMID:25813741
Gelation and phase separation of attractive colloids
NASA Astrophysics Data System (ADS)
Lu, Peter James
2008-07-01
I present several scientific and technical contributions in this thesis. I demonstrate that the gelation of spherical particles with isotropic, short-range attractive interactions is initiated by spinodal decomposition, a thermodynamic instability that triggers the formation of clusters that span and dynamically arrest to create a gel. This simple, universal gelation picture does not depend on microscopic system-specific details---thus broadly describing any particle system with short-range attractions---and suggests that gelation, often considered a purely kinetic phenomenon, is in fact a direct consequence of equilibrium liquid-gas phase separation. I also demonstrate that spherical particles with isotropic attractive interactions exhibit a stable phase---a fluid of particle clusters---that persists on experimental timescales even in the absence of any long-range Coulombic charge repulsion; this contrasts some expectations based on simulation and theory. I describe a new capability I created by integrating accelerated image processing software that I wrote into a high-speed confocal microscope system that I developed: active target-locking, the ability to follow freely-moving complex objects within a microscope sample, even as they change size, shape, and orientation---in real time. Finally, I report continuous, month-long observations of near-critical spinodal decomposition of colloids with isotropic attractions, aboard the International Space Station. I also include detailed descriptions, with examples and illustrations, of the tools and techniques that I have developed to produce these results.
Are high-quality mates always attractive?
Holveck, Marie-Jeanne; Verhulst, Simon; Fawcett, Tim W
2010-01-01
Sexual selection theory posits that females should choose mates in a way that maximizes their reproductive success. But what exactly is the optimal choice? Most empirical research is based on the assumption that females seek a male of the highest possible quality (in terms of the genes or resources he can provide), and hence show directional preferences for indicators of male quality. This implies that attractiveness and quality should be highly correlated. However, females frequently differ in what they find attractive. New theoretical and empirical insights provide mounting evidence that a female’s own quality biases her judgement of male attractiveness, such that male quality and attractiveness do not always coincide. A recent experiment in songbirds demonstrated for the first time that manipulation of female condition can lead to divergent female preferences, with low-quality females actively preferring low-quality males over high-quality males. This result is in line with theory on state-dependent mate choice and is reminiscent of assortative mating preferences in humans. Here we discuss the implications of this work for the study of mate preferences. PMID:20714411
Physical Attractiveness and Judged Suitability for Leadership.
ERIC Educational Resources Information Center
Cherulnik, Paul D.
This study examined the influence of appearance on leadership processes by examining the effect of attractiveness on the actual performance of a leadership task. College students (N=62) performed a simulation task in which they played the role of a candidate for student government president. All the students were videotaped, giving a prepared…
Attracting Clients to Service-Oriented Programs.
ERIC Educational Resources Information Center
Disney, Diane M.
One of a series of manuals developed by the Home and Community-Based Career Education Project, the outreach component publication describes how the project went about attracting clients for its adult vocational counseling services. Sections include: creating a publicity campaign, using an advertising agency, creating products for the mass media,…
Attracting Reentry Women to Engineering and Technology.
ERIC Educational Resources Information Center
American Society for Engineering Education, Washington, DC.
Three papers on attracting reentry women to engineering and technology are presented. The first paper, "Encouraging Older Women as Engineering Students," discusses the opportunities, the problems, and suggested actions for women pursuing engineering careers. The second paper, "Industrial Programs for Reentry Opportunities for Women as Engineers,"…
Body Type Attractiveness Preferences of the Aged.
ERIC Educational Resources Information Center
Portnoy, Enid J.
A study explored the relationship between body types and four attraction dimensions (physical, social, task, and communication) as perceived by older adults (mean age 68). Subjects, 35 males and 73 females in private residences and senior citizen centers, were shown three same-sex body silhouettes representing the older ectomorph, mesomorph, and…
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…
Attracting New Learners: International Evidence and Practice.
ERIC Educational Resources Information Center
Taylor, Sue, Ed.; Cameron, Helen, Ed.
This document explores the question of how the United Kingdom can attract more people into education and training. The introduction discusses the international seminar on which the document is based. "What Triggers Participation?" offers a conceptual framework for the seminar's findings. "A Comparative Perspective" examines participation and…
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…
Fish Aversion and Attraction to Selected Agrichemicals.
da Rosa, João Gabriel Santos; de Abreu, Murilo Sander; Giacomini, Ana Cristina Varrone; Koakoski, Gessi; Kalichak, Fabiana; Oliveira, Thiago Acosta; de Alcântara Barcellos, Heloísa Helena; Barreto, Rodrigo Egydio; Barcellos, Leonardo José Gil
2016-10-01
In agriculture intensive areas, fishponds and natural water bodies located in close proximity to these fields receive water with variable amounts of agrichemicals. Consequently, toxic compounds reach nontarget organisms. For instance, aquatic organisms can be exposed to tebuconazole-based fungicides (TBF), glyphosate-based herbicides (GBH), and atrazine-based herbicides (ABH) that are potentially dangerous, which motivates the following question: Are these agrichemicals attractant or aversive to fish? To answer this question, adult zebrafish were tested in a chamber that allows fish to escape from or seek a lane of contaminated water. This attraction and aversion paradigm was evaluated with zebrafish in the presence of an acute contamination with these compounds. We showed that only GBH was aversive to fish, whereas ABH and TBF caused neither attraction nor aversion for zebrafish. Thus, these chemicals do not impose an extra toxic risk by being an attractant for fish, although TBF and ABH can be more deleterious, because they induce no aversive response. Because the uptake and bioaccumulation of chemicals in fish seems to be time- and dose-dependent, a fish that remains longer in the presence of these substances tends to absorb higher concentrations than one that escapes from contaminated sites. PMID:27423874
Facial Attractiveness Assessment using Illustrated Questionnairers
MESAROS, ANCA; CORNEA, DANIELA; CIOARA, LIVIU; DUDEA, DIANA; MESAROS, MICHAELA; BADEA, MINDRA
2015-01-01
Introduction. An attractive facial appearance is considered nowadays to be a decisive factor in establishing successful interactions between humans. In relation to this topic, scientific literature states that some of the facial features have more impact then others, and important authors revealed that certain proportions between different anthropometrical landmarks are mandatory for an attractive facial appearance. Aim. Our study aims to assess if certain facial features count differently in people’s opinion while assessing facial attractiveness in correlation with factors such as age, gender, specific training and culture. Material and methods. A 5-item multiple choice illustrated questionnaire was presented to 236 dental students. The Photoshop CS3 software was used in order to obtain the sets of images for the illustrated questions. The original image was handpicked from the internet by a panel of young dentists from a series of 15 pictures of people considered to have attractive faces. For each of the questions, the images presented were simulating deviations from the ideally symmetric and proportionate face. The sets of images consisted in multiple variations of deviations mixed with the original photo. Junior and sophomore year students from our dental medical school, having different nationalities were required to participate in our questionnaire. Simple descriptive statistics were used to interpret the data. Results. Assessing the results obtained from the questionnaire it was observed that a majority of students considered as unattractive the overdevelopment of the lower third, while the initial image with perfect symmetry and proportion was considered as the most attractive by only 38.9% of the subjects. Likewise, regarding the symmetry 36.86% considered unattractive the canting of the inter-commissural line. The interviewed subjects considered that for a face to be attractive it needs to have harmonious proportions between the different facial
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
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
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
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
The contribution of surprise to the prediction based modulation of fMRI responses.
Amado, Catarina; Hermann, Petra; Kovács, Petra; Grotheer, Mareike; Vidnyánszky, Zoltán; Kovács, Gyula
2016-04-01
In recent years, several functional magnetic resonance imaging (fMRI) studies showed that correct stimulus predictions reduce the neural responses when compared to surprising events (Egner et al., 2010). Further, it has been shown that such fulfilled expectations enhance the magnitude of repetition suppression (RS, i.e. a decreased neuronal response after the repetition of a given stimulus) in face selective visual cortex as well (Summerfield et al., 2008). Current MEG and neuroimaging studies suggest that the underlying mechanisms of expectation effects are independent from these of RS (Grotheer and Kovács, 2015; Todorovic and Lange, 2012). However, it is not clear as of today how perceptual expectations modulate the neural responses: is the difference between correctly predicted and surprising stimuli due to a genuine response reduction for correctly predicted stimuli or is it due to an increased response for surprising stimuli? Therefore, here we used a modified version of the paradigm of Grotheer and Kovács (2015) to induce predictions independently from repetition probability by presenting pairs of faces (female, male or infant) that were either repeated or alternating. Orthogonally to this, predictions were manipulated by the gender of the first face within each pair so that it signaled high, low or equal probability of repetitions. An unpredicted, neutral condition with equal probabilities for alternating and repeated trials was used to identify the role of surprising and enhancing modulations. Similarly, to Grotheer and Kovács (2015), we found significant RS and significant expectation effect in the FFA. Importantly, we observed larger response for surprising events in comparison to the neutral and correctly predicted conditions for alternating trials. Altogether, these results emphasize the role of surprise in prediction effects. PMID:26873275
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
Heterogeneous Factor Analysis Models: A Bayesian Approach.
ERIC Educational Resources Information Center
Ansari, Asim; Jedidi, Kamel; Dube, Laurette
2002-01-01
Developed Markov Chain Monte Carlo procedures to perform Bayesian inference, model checking, and model comparison in heterogeneous factor analysis. Tested the approach with synthetic data and data from a consumption emotion study involving 54 consumers. Results show that traditional psychometric methods cannot fully capture the heterogeneity in…
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 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
BART: Bayesian Atmospheric Radiative Transfer fitting code
NASA Astrophysics Data System (ADS)
Cubillos, Patricio; Blecic, Jasmina; Harrington, Joseph; Rojo, Patricio; Lust, Nate; Bowman, Oliver; Stemm, Madison; Foster, Andrew; Loredo, Thomas J.; Fortney, Jonathan; Madhusudhan, Nikku
2016-08-01
BART implements a Bayesian, Monte Carlo-driven, radiative-transfer scheme for extracting parameters from spectra of planetary atmospheres. BART combines a thermochemical-equilibrium code, a one-dimensional line-by-line radiative-transfer code, and the Multi-core Markov-chain Monte Carlo statistical module to constrain the atmospheric temperature and chemical-abundance profiles of exoplanets.
Von Neumann was not a Quantum Bayesian.
Stacey, Blake C
2016-05-28
Wikipedia has claimed for over 3 years now that John von Neumann was the 'first quantum Bayesian'. In context, this reads as stating that von Neumann inaugurated QBism, the approach to quantum theory promoted by Fuchs, Mermin and Schack. This essay explores how such a claim is, historically speaking, unsupported. PMID:27091166
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…
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…
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.
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
Explanation mode for Bayesian automatic object recognition
NASA Astrophysics Data System (ADS)
Hazlett, Thomas L.; Cofer, Rufus H.; Brown, Harold K.
1992-09-01
One of the more useful techniques to emerge from AI is the provision of an explanation modality used by the researcher to understand and subsequently tune the reasoning of an expert system. Such a capability, missing in the arena of statistical object recognition, is not that difficult to provide. Long standing results show that the paradigm of Bayesian object recognition is truly optimal in a minimum probability of error sense. To a large degree, the Bayesian paradigm achieves optimality through adroit fusion of a wide range of lower informational data sources to give a higher quality decision--a very 'expert system' like capability. When various sources of incoming data are represented by C++ classes, it becomes possible to automatically backtrack the Bayesian data fusion process, assigning relative weights to the more significant datums and their combinations. A C++ object oriented engine is then able to synthesize 'English' like textural description of the Bayesian reasoning suitable for generalized presentation. Key concepts and examples are provided based on an actual object recognition problem.
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. PMID:25645903
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…
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…
Evaluating Individualized Reading Programs: A Bayesian Model.
ERIC Educational Resources Information Center
Maxwell, Martha
Simple Bayesian approaches can be applied to answer specific questions in evaluating an individualized reading program. A small reading and study skills program located in the counseling center of a major research university collected and compiled data on student characteristics such as class, number of sessions attended, grade point average, and…
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.
A Bayesian Approach to Interactive Retrieval
ERIC Educational Resources Information Center
Tague, Jean M.
1973-01-01
A probabilistic model for interactive retrieval is presented. Bayesian statistical decision theory principles are applied: use of prior and sample information about the relationship of document descriptions to query relevance; maximization of expected value of a utility function, to the problem of optimally restructuring search strategies in an…
QUEST - A Bayesian adaptive psychometric method
NASA Technical Reports Server (NTRS)
Watson, A. B.; Pelli, D. G.
1983-01-01
An adaptive psychometric procedure that places each trial at the current most probable Bayesian estimate of threshold is described. The procedure takes advantage of the common finding that the human psychometric function is invariant in form when expressed as a function of log intensity. The procedure is simple, fast, and efficient, and may be easily implemented on any computer.
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.
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.
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. PMID:26442771
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. PMID:27265828
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)
Model attraction in medical image object recognition
NASA Astrophysics Data System (ADS)
Tascini, Guido; Zingaretti, Primo
1995-04-01
This paper presents as new approach to image recognition based on a general attraction principle. A cognitive recognition is governed by a 'focus on attention' process that concentrates on the visual data subset of task- relevant type only. Our model-based approach combines it with another process, focus on attraction, which concentrates on the transformations of visual data having relevance for the matching. The recognition process is characterized by an intentional evolution of the visual data. This chain of image transformations is viewed as driven by an attraction field that attempts to reduce the distance between the image-point and the model-point in the feature space. The field sources are determined during a learning phase, by supplying the system with a training set. The paper describes a medical interpretation case in the feature space, concerning human skin lesions. The samples of the training set, supplied by the dermatologists, allow the system to learn models of lesions in terms of features such as hue factor, asymmetry factor, and asperity factor. The comparison of the visual data with the model derives the trend of image transformations, allowing a better definition of the given image and its classification. The algorithms are implemented in C language on a PC equipped with Matrox Image Series IM-1280 acquisition and processing boards. The work is now in progress.
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
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. PMID:27475077
A Public Education Primer: Basic (and Sometimes Surprising) Facts about the U.S. Education System
ERIC Educational Resources Information Center
Kober, Nancy; Rentner, Diane Stark; Jennings, Jack
2006-01-01
Public education matters, whether one is a student, parent, teacher, volunteer, employer, employee, or taxpayer. Although an individual undoubtedly knows something about public education, he may be unaware of important facts about the U.S. education system or may be surprised to learn how things have changed in recent years. In this primer on…
Connotations of Surprise in the Conditionals 'To' and 'Tara' in Japanese: A Review and Synthesis.
ERIC Educational Resources Information Center
Compernolle, Tim Van
1993-01-01
The two conditionals 'to' and '-tara' in Japanese do not carry neutral connotations. This paper offers evidence to support the claim that '-tara' can carry, among other things, a connotation of surprise in reference to specific past events. However, evidence is also offered to show that the conditional 'to,' contrary to what is stated in most…
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.
Surprising Incentive: An Instrument for Promoting Safety Performance of Construction Employees
Ghasemi, Fakhradin; Mohammadfam, Iraj; Soltanian, Ali Reza; Mahmoudi, Shahram; Zarei, Esmaeil
2015-01-01
Background In comparison with other industries, the construction industry still has a higher rate of fatal injuries, and thus, there is a need to apply new and innovative approaches for preventing accidents and promoting safe conditions at construction sites. Methods In this study, the effectiveness of a new incentive system—the surprising incentive system—was assessed. One year after the implementation of this new incentive system, behavioral changes of employees with respect to seven types of activities were observed. Results The results of this study showed that there is a significant relationship between the new incentive system and the safety performance of frontline employees. The new incentive system had a greater positive impact in the first 6 months since its implementation. In the long term, however, safety performance experienced a gradual reduction. Based on previous studies, all activities selected in this study are important indicators of the safety conditions at workplaces. However, there is a need for a comprehensive and simple-to-apply tool for assessing frontline employees' safety performance. Shortening the intervals between incentives is more effective in promoting safety performance. Conclusion The results of this study proved that the surprising incentive would improve the employees' safety performance just in the short term because the surprising value of the incentives dwindle over time. For this reason and to maintain the surprising value of the incentive system, the amount and types of incentives need to be evaluated and modified annually or biannually. PMID:26929832
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…
ERIC Educational Resources Information Center
Schein, Jeffrey; Caplan, Eric
2014-01-01
The thoughts of Mordecai Kaplan and Michael Rosenak present surprising commonalities as well as illuminating differences. Similarities include the perception that Judaism and Jewish education are in crisis, the belief that Jewish peoplehood must include commitment to meaningful content, the need for teachers to teach from a position of…
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. PMID:21829657
Dynamic Bayesian filtering for real-time seismic analyses
Blough, D.K.; Rohay, A.C.; Anderson, K.K.; Nicholson, W.L.
1994-04-01
State space modeling, which includes techniques such as the Kalman filter, has been used to analyze many non-stationary time series. The ability of these dynamic models to adapt and track changes in the underlying process makes them attractive for application to the real-time analysis of three-component seismic waveforms. The authors are investigating the application of state space models formulated as Bayesian time series models to phase detection, polarization, and spectrogram estimation of seismograms. This approach removes the need to specify data windows in the time series for time averaging estimation (e.g., spectrum estimation). They are using this model to isolate particular seismic phases based on polarization parameters that are determined at a spectrum of frequencies. They plan to use polarization parameters, frequency spectra, and magnitudes to discriminate between different types of seismic sources. They present the application of this technique to artificial time series and to several real seismic events including the Non-Proliferation Experiment (NPE) two nuclear tests and three earthquakes from the Nevada Test site, as recorded on several regional broadband seismic stations. A preliminary result of this analysis indicates that earthquakes and explosions can potentially be discriminated on the bass of the polarization characteristics of scattered seismic phases. However, the chemical (NPE) and nuclear explosions appear to have very similar polarization characteristics.
Wilkins, Clara L; Chan, Joy F; Kaiser, Cheryl R
2011-10-01
What does it take to find a member of a different race attractive? In this research, we suggest that for Whites, attraction to Asians may be based, in part, on stereotypes and variations in Asians' racial appearance. Study 1 reveals that Asians are stereotyped as being more feminine and less masculine than other racial groups-characteristics considered appealing for women but not for men to possess. Study 2 examines how variation in racial appearance, phenotypic prototypicality (PP), shapes the degree to which Asians are gender stereotyped and how PP relates to perceptions of attractiveness. Higher PP Asian men are perceived as being less masculine and less physically attractive than lower PP Asian men. These findings inform theory on how within-group variation in racial appearance affects stereotyping and other social outcomes. PMID:21988581
Tran, Van Hai; Pham, Kim Son; Inomata, Shin-ichi; Ando, Tetsu
2002-07-01
Screening tests of synthetic lepidopteran sex pheromones were carried out at orchards in the Mekong Delta over an approximately two-year period starting from December 1998. Monoenyl acetates with a C10-C14 chain attracted six species distributed mainly in Southeast Asia: Adoxophyes privatana, Archips atrolucens, and Meridemisfurtiva in the Tortricidae family, and Argyrogramma signata. Spodoptera pectinicornis, and Zonoplusia ochreata in the Noctuidae family. These were in addition to three other noctuid species that had been attracted during previous field examinations within a temperate zone. Furthermore, male moths of three species belonging to the Cosmopterigidae, Gelechiidae, or Batrachedridae family were also caught by traps baited with acetates. Trienes with a C18-C21 chain and their monoepoxides. which are stereotypes of pheromones secreted by females in the Geometridae family, failed to attract any geometrid male, but attracted three Noctuidae species and four Arctiidae species. PMID:12199508
Klohnen, Eva C; Luo, Shanhong
2003-10-01
Little is known about whether personality characteristics influence initial attraction. Because adult attachment differences influence a broad range of relationship processes, the authors examined their role in 3 experimental attraction studies. The authors tested four major attraction hypotheses--self similarity, ideal-self similarity, complementarity, and attachment security--and examined both actual and perceptual factors. Replicated analyses across samples, designs, and manipulations showed that actual security and self similarity predicted attraction. With regard to perceptual factors, ideal similarity, self similarity, and security all were significant predictors. Whereas perceptual ideal and self similarity had incremental predictive power, perceptual security's effects were subsumed by perceptual ideal similarity. Perceptual self similarity fully mediated actual attachment similarity effects, whereas ideal similarity was only a partial mediator. PMID:14561124
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
Attractive versus Unattractive Clients: Mediating Influences on Counselors' Perceptions.
ERIC Educational Resources Information Center
Lewis, Kathleen N; And Others
1981-01-01
Investigated the effects of clients' age, physical attractiveness, and behavior on subjects' attraction to the clients. Results indicated that "counselor" subjects were significantly more attracted to child than to adult clients and to clients demonstrating good in-session behaviors. Physically attractive clients were not rated significantly more…
Viewing Attractiveness Socialization from a Social Network Perspective.
ERIC Educational Resources Information Center
Downs, A. Chris
Providing a framework for a symposium exploring the influence of physical attractiveness on the socialization process, this paper (1) offers a working definition of physical attractiveness, (2) reviews stereotypes associated with attractiveness, and (3) discusses a social network perspective on the influence of attractiveness. Physical…
Impressions of Counselors as a Function of Counselor Physical Attractiveness
ERIC Educational Resources Information Center
Carter, Jean A.
1978-01-01
Research assessed the effects of counselor physical attractiveness and inter-actions between attractiveness and counselor subject sex. It is suggested that sex of counselor and client may play a more important role independently and in conjunction with attractiveness than does attractiveness alone in influencing impressions and expectations.…
The Size-Weight Illusion is not anti-Bayesian after all: a unifying Bayesian account.
Peters, Megan A K; Ma, Wei Ji; Shams, Ladan
2016-01-01
When we lift two differently-sized but equally-weighted objects, we expect the larger to be heavier, but the smaller feels heavier. However, traditional Bayesian approaches with "larger is heavier" priors predict the smaller object should feel lighter; this Size-Weight Illusion (SWI) has thus been labeled "anti-Bayesian" and has stymied psychologists for generations. We propose that previous Bayesian approaches neglect the brain's inference process about density. In our Bayesian model, objects' perceived heaviness relationship is based on both their size and inferred density relationship: observers evaluate competing, categorical hypotheses about objects' relative densities, the inference about which is then used to produce the final estimate of weight. The model can qualitatively and quantitatively reproduce the SWI and explain other researchers' findings, and also makes a novel prediction, which we confirmed. This same computational mechanism accounts for other multisensory phenomena and illusions; that the SWI follows the same process suggests that competitive-prior Bayesian inference can explain human perception across many domains. PMID:27350899
Yu, Jihnhee; Hutson, Alan D; Siddiqui, Adnan H; Kedron, Mary A
2016-02-01
In some small clinical trials, toxicity is not a primary endpoint; however, it often has dire effects on patients' quality of life and is even life-threatening. For such clinical trials, rigorous control of the overall incidence of adverse events is desirable, while simultaneously collecting safety information. In this article, we propose group sequential toxicity monitoring strategies to control overall toxicity incidents below a certain level as opposed to performing hypothesis testing, which can be incorporated into an existing study design based on the primary endpoint. We consider two sequential methods: a non-Bayesian approach in which stopping rules are obtained based on the 'future' probability of an excessive toxicity rate; and a Bayesian adaptation modifying the proposed non-Bayesian approach, which can use the information obtained at interim analyses. Through an extensive Monte Carlo study, we show that the Bayesian approach often provides better control of the overall toxicity rate than the non-Bayesian approach. We also investigate adequate toxicity estimation after the studies. We demonstrate the applicability of our proposed methods in controlling the symptomatic intracranial hemorrhage rate for treating acute ischemic stroke patients. PMID:22407172
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).
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.
Bayesian Population Projections for the United Nations
Raftery, Adrian E.; Alkema, Leontine; Gerland, Patrick
2014-01-01
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. PMID:25324591
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.
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.
Bayesian image reconstruction: Application to emission tomography
Nunez, J.; Llacer, J.
1989-02-01
In this paper we propose a Maximum a Posteriori (MAP) method of image reconstruction in the Bayesian framework for the Poisson noise case. We use entropy to define the prior probability and likelihood to define the conditional probability. The method uses sharpness parameters which can be theoretically computed or adjusted, allowing us to obtain MAP reconstructions without the problem of the grey'' reconstructions associated with the pre Bayesian reconstructions. We have developed several ways to solve the reconstruction problem and propose a new iterative algorithm which is stable, maintains positivity and converges to feasible images faster than the Maximum Likelihood Estimate method. We have successfully applied the new method to the case of Emission Tomography, both with simulated and real data. 41 refs., 4 figs., 1 tab.
A Bayesian Model of Sensory Adaptation
Sato, Yoshiyuki; Aihara, Kazuyuki
2011-01-01
Recent studies reported two opposite types of adaptation in temporal perception. Here, we propose a Bayesian model of sensory adaptation that exhibits both types of adaptation. We regard adaptation as the adaptive updating of estimations of time-evolving variables, which determine the mean value of the likelihood function and that of the prior distribution in a Bayesian model of temporal perception. On the basis of certain assumptions, we can analytically determine the mean behavior in our model and identify the parameters that determine the type of adaptation that actually occurs. The results of our model suggest that we can control the type of adaptation by controlling the statistical properties of the stimuli presented. PMID:21541346
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.
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.
A note on variational Bayesian factor analysis.
Zhao, Jian-hua; Yu, Philip L H
2009-09-01
Existing works on variational bayesian (VB) treatment for factor analysis (FA) model such as [Ghahramani, Z., & Beal, M. (2000). Variational inference for Bayesian mixture of factor analysers. In Advances in neural information proceeding systems. Cambridge, MA: MIT Press; Nielsen, F. B. (2004). Variational approach to factor analysis and related models. Master's thesis, The Institute of Informatics and Mathematical Modelling, Technical University of Denmark.] are found theoretically and empirically to suffer two problems: (1) penalize the model more heavily than BIC and (2) perform unsatisfactorily in low noise cases as redundant factors can not be effectively suppressed. A novel VB treatment is proposed in this paper to resolve the two problems and a simulation study is conducted to testify its improved performance over existing treatments. PMID:19135337
Applications of Bayesian spectrum representation in acoustics
NASA Astrophysics Data System (ADS)
Botts, Jonathan M.
This dissertation utilizes a Bayesian inference framework to enhance the solution of inverse problems where the forward model maps to acoustic spectra. A Bayesian solution to filter design inverts a acoustic spectra to pole-zero locations of a discrete-time filter model. Spatial sound field analysis with a spherical microphone array is a data analysis problem that requires inversion of spatio-temporal spectra to directions of arrival. As with many inverse problems, a probabilistic analysis results in richer solutions than can be achieved with ad-hoc methods. In the filter design problem, the Bayesian inversion results in globally optimal coefficient estimates as well as an estimate the most concise filter capable of representing the given spectrum, within a single framework. This approach is demonstrated on synthetic spectra, head-related transfer function spectra, and measured acoustic reflection spectra. The Bayesian model-based analysis of spatial room impulse responses is presented as an analogous problem with equally rich solution. The model selection mechanism provides an estimate of the number of arrivals, which is necessary to properly infer the directions of simultaneous arrivals. Although, spectrum inversion problems are fairly ubiquitous, the scope of this dissertation has been limited to these two and derivative problems. The Bayesian approach to filter design is demonstrated on an artificial spectrum to illustrate the model comparison mechanism and then on measured head-related transfer functions to show the potential range of application. Coupled with sampling methods, the Bayesian approach is shown to outperform least-squares filter design methods commonly used in commercial software, confirming the need for a global search of the parameter space. The resulting designs are shown to be comparable to those that result from global optimization methods, but the Bayesian approach has the added advantage of a filter length estimate within the same unified
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.
Structure Learning in Bayesian Sensorimotor Integration
Genewein, Tim; Hez, Eduard; Razzaghpanah, Zeynab; Braun, Daniel A.
2015-01-01
Previous studies have shown that sensorimotor processing can often be described by Bayesian learning, in particular the integration of prior and feedback information depending on its degree of reliability. Here we test the hypothesis that the integration process itself can be tuned to the statistical structure of the environment. We exposed human participants to a reaching task in a three-dimensional virtual reality environment where we could displace the visual feedback of their hand position in a two dimensional plane. When introducing statistical structure between the two dimensions of the displacement, we found that over the course of several days participants adapted their feedback integration process in order to exploit this structure for performance improvement. In control experiments we found that this adaptation process critically depended on performance feedback and could not be induced by verbal instructions. Our results suggest that structural learning is an important meta-learning component of Bayesian sensorimotor integration. PMID:26305797
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.
The NIFTy way of Bayesian signal inference
NASA Astrophysics Data System (ADS)
Selig, Marco
2014-12-01
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 D3PO algorithm targeting the non-trivial task of denoising, deconvolving, and decomposing photon observations in high energy astronomy.
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.
Basins of attraction for chimera states
NASA Astrophysics Data System (ADS)
Martens, Erik A.; Panaggio, Mark J.; Abrams, Daniel M.
2016-02-01
Chimera states—curious symmetry-broken states in systems of identical coupled oscillators—typically occur only for certain initial conditions. Here we analyze their basins of attraction in a simple system comprised of two populations. Using perturbative analysis and numerical simulation we evaluate asymptotic states and associated destination maps, and demonstrate that basins form a complex twisting structure in phase space. Understanding the basins’ precise nature may help in the development of control methods to switch between chimera patterns, with possible technological and neural system applications.
Repulsive and attractive Casimir interactions in liquids
Phan, Anh D.; Viet, N. A.
2011-12-15
The Casimir interactions in solid-liquid-solid systems as a function of separation distance have been studied by the Lifshitz theory. The dielectric permittivity functions for a wide range of materials are described by Drude, Drude-Lorentz, and oscillator models. We find that the Casimir forces between gold and silica or MgO materials are both repulsive and attractive. We also find the stable forms for the systems. Our studies would provide good guidance for future experimental studies on dispersion interactions.
Classical scattering in strongly attractive potentials
NASA Astrophysics Data System (ADS)
Khrapak, S. A.
2014-03-01
Scattering in central attractive potentials is investigated systematically, in the limit of strong interaction, when large-angle scattering dominates. In particular, three important model interactions (Lennard-Jones, Yukawa, and exponential), which are qualitatively different from each other, are studied in detail. It is shown that for each of these interactions the dependence of the scattering angle on the properly normalized impact parameter exhibits a quasiuniversal behavior. This implies simple scaling of the transport cross sections with energy in the considered limit. Accurate fits for the momentum transfer cross section are suggested. Applications of the obtained results are discussed.
Classical scattering in strongly attractive potentials.
Khrapak, S A
2014-03-01
Scattering in central attractive potentials is investigated systematically, in the limit of strong interaction, when large-angle scattering dominates. In particular, three important model interactions (Lennard-Jones, Yukawa, and exponential), which are qualitatively different from each other, are studied in detail. It is shown that for each of these interactions the dependence of the scattering angle on the properly normalized impact parameter exhibits a quasiuniversal behavior. This implies simple scaling of the transport cross sections with energy in the considered limit. Accurate fits for the momentum transfer cross section are suggested. Applications of the obtained results are discussed. PMID:24730827
Hamano, Jun; Morita, Tatsuya; Inoue, Satoshi; Ikenaga, Masayuki; Matsumoto, Yoshihisa; Sekine, Ryuichi; Yamaguchi, Takashi; Hirohashi, Takeshi; Tajima, Tsukasa; Tatara, Ryohei; Watanabe, Hiroaki; Otani, Hiroyuki; Takigawa, Chizuko; Matsuda, Yoshinobu; Nagaoka, Hiroka; Mori, Masanori; Yamamoto, Naoki; Shimizu, Mie; Sasara, Takeshi
2015-01-01
Background. Predicting the short-term survival in cancer patients is an important issue for patients, family, and oncologists. Although the prognostic accuracy of the surprise question has value in 1-year mortality for cancer patients, the prognostic value for short-term survival has not been formally assessed. The primary aim of the present study was to assess the prognostic value of the surprise question for 7-day and 30-day survival in patients with advanced cancer. Patients and Methods. The present multicenter prospective cohort study was conducted in Japan from September 2012 through April 2014, involving 16 palliative care units, 19 hospital-based palliative care teams, and 23 home-based palliative care services. Results. We recruited 2,425 patients and included 2,361 for analysis: 912 from hospital-based palliative care teams, 895 from hospital palliative care units, and 554 from home-based palliative care services. The sensitivity, specificity, positive predictive value, and negative predictive value of the 7-day survival surprise question were 84.7% (95% confidence interval [CI], 80.7%–88.0%), 68.0% (95% CI, 67.3%–68.5%), 30.3% (95% CI, 28.9%–31.5%), and 96.4% (95% CI, 95.5%–97.2%), respectively. The sensitivity, specificity, positive predictive value, and negative predictive value for the 30-day surprise question were 95.6% (95% CI, 94.4%–96.6%), 37.0% (95% CI, 35.9%–37.9%), 57.6% (95% CI, 56.8%–58.2%), and 90.4% (95% CI, 87.7%–92.6%), respectively. Conclusion. Surprise questions are useful for screening patients for short survival. However, the high false-positive rates do not allow clinicians to provide definitive prognosis prediction. Implications for Practice: The findings of this study indicate that clinicians can screen patients for 7- or 30-day survival using surprise questions with 90% or more sensitivity. Clinicians cannot provide accurate prognosis estimation, and all patients will not always die within the defined periods. The
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.
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
Efficient Bayesian-based multiview deconvolution.
Preibisch, Stephan; Amat, Fernando; Stamataki, Evangelia; Sarov, Mihail; Singer, Robert H; Myers, Eugene; Tomancak, Pavel
2014-06-01
Light-sheet fluorescence microscopy is able to image large specimens with high resolution by capturing the samples from multiple angles. Multiview deconvolution can substantially improve the resolution and contrast of the images, but its application has been limited owing to the large size of the data sets. Here we present a Bayesian-based derivation of multiview deconvolution that drastically improves the convergence time, and we provide a fast implementation using graphics hardware. PMID:24747812
Efficient Bayesian-based multiview deconvolution
Preibisch, Stephan; Amat, Fernando; Stamataki, Evangelia; Sarov, Mihail; Singer, Robert H; Myers, Eugene; Tomancak, Pavel
2014-01-01
Light-sheet fluorescence microscopy is able to image large specimens with high resolution by capturing the samples from multiple angles. Multiview deconvolution can substantially improve the resolution and contrast of the images, but its application has been limited owing to the large size of the data sets. Here we present a Bayesian-based derivation of multiview deconvolution that drastically improves the convergence time, and we provide a fast implementation using graphics hardware. PMID:24747812
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
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.
On Bayesian estimation of marginal structural models.
Saarela, Olli; Stephens, David A; Moodie, Erica E M; Klein, Marina B
2015-06-01
The purpose of inverse probability of treatment (IPT) weighting in estimation of marginal treatment effects is to construct a pseudo-population without imbalances in measured covariates, thus removing the effects of confounding and informative censoring when performing inference. In this article, we formalize the notion of such a pseudo-population as a data generating mechanism with particular characteristics, and show that this leads to a natural Bayesian interpretation of IPT weighted estimation. Using this interpretation, we are able to propose the first fully Bayesian procedure for estimating parameters of marginal structural models using an IPT weighting. Our approach suggests that the weights should be derived from the posterior predictive treatment assignment and censoring probabilities, answering the question of whether and how the uncertainty in the estimation of the weights should be incorporated in Bayesian inference of marginal treatment effects. The proposed approach is compared to existing methods in simulated data, and applied to an analysis of the Canadian Co-infection Cohort. PMID:25677103
Bayesian outcome-based strategy classification.
Lee, Michael D
2016-03-01
Hilbig and Moshagen (Psychonomic Bulletin & Review, 21, 1431-1443, 2014) recently developed a method for making inferences about the decision processes people use in multi-attribute forced choice tasks. Their paper makes a number of worthwhile theoretical and methodological contributions. Theoretically, they provide an insightful psychological motivation for a probabilistic extension of the widely-used "weighted additive" (WADD) model, and show how this model, as well as other important models like "take-the-best" (TTB), can and should be expressed in terms of meaningful priors. Methodologically, they develop an inference approach based on the Minimum Description Length (MDL) principles that balances both the goodness-of-fit and complexity of the decision models they consider. This paper aims to preserve these useful contributions, but provide a complementary Bayesian approach with some theoretical and methodological advantages. We develop a simple graphical model, implemented in JAGS, that allows for fully Bayesian inferences about which models people use to make decisions. To demonstrate the Bayesian approach, we apply it to the models and data considered by Hilbig and Moshagen (Psychonomic Bulletin & Review, 21, 1431-1443, 2014), showing how a prior predictive analysis of the models, and posterior inferences about which models people use and the parameter settings at which they use them, can contribute to our understanding of human decision making. PMID:25697091
Bayesian approach to global discrete optimization
Mockus, J.; Mockus, A.; Mockus, L.
1994-12-31
We discuss advantages and disadvantages of the Bayesian approach (average case analysis). We present the portable interactive version of software for continuous global optimization. We consider practical multidimensional problems of continuous global optimization, such as optimization of VLSI yield, optimization of composite laminates, estimation of unknown parameters of bilinear time series. We extend Bayesian approach to discrete optimization. We regard the discrete optimization as a multi-stage decision problem. We assume that there exists some simple heuristic function which roughly predicts the consequences of the decisions. We suppose randomized decisions. We define the probability of the decision by the randomized decision function depending on heuristics. We fix this function with exception of some parameters. We repeat the randomized decision several times at the fixed values of those parameters and accept the best decision as the result. We optimize the parameters of the randomized decision function to make the search more efficient. Thus we reduce the discrete optimization problem to the continuous problem of global stochastic optimization. We solve this problem by the Bayesian methods of continuous global optimization. We describe the applications to some well known An problems of discrete programming, such as knapsack, traveling salesman, and scheduling.
Posterior Predictive Bayesian Phylogenetic Model Selection
Lewis, Paul O.; Xie, Wangang; Chen, Ming-Hui; Fan, Yu; Kuo, Lynn
2014-01-01
We present two distinctly different posterior predictive approaches to Bayesian phylogenetic model selection and illustrate these methods using examples from green algal protein-coding cpDNA sequences and flowering plant rDNA sequences. The Gelfand–Ghosh (GG) approach allows dissection of an overall measure of model fit into components due to posterior predictive variance (GGp) and goodness-of-fit (GGg), which distinguishes this method from the posterior predictive P-value approach. The conditional predictive ordinate (CPO) method provides a site-specific measure of model fit useful for exploratory analyses and can be combined over sites yielding the log pseudomarginal likelihood (LPML) which is useful as an overall measure of model fit. CPO provides a useful cross-validation approach that is computationally efficient, requiring only a sample from the posterior distribution (no additional simulation is required). Both GG and CPO add new perspectives to Bayesian phylogenetic model selection based on the predictive abilities of models and complement the perspective provided by the marginal likelihood (including Bayes Factor comparisons) based solely on the fit of competing models to observed data. [Bayesian; conditional predictive ordinate; CPO; L-measure; LPML; model selection; phylogenetics; posterior predictive.] PMID:24193892
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
Risk-Sensitivity in Bayesian Sensorimotor Integration
Grau-Moya, Jordi; Ortega, Pedro A.; Braun, Daniel A.
2012-01-01
Information processing in the nervous system during sensorimotor tasks with inherent uncertainty has been shown to be consistent with Bayesian integration. Bayes optimal decision-makers are, however, risk-neutral in the sense that they weigh all possibilities based on prior expectation and sensory evidence when they choose the action with highest expected value. In contrast, risk-sensitive decision-makers are sensitive to model uncertainty and bias their decision-making processes when they do inference over unobserved variables. In particular, they allow deviations from their probabilistic model in cases where this model makes imprecise predictions. Here we test for risk-sensitivity in a sensorimotor integration task where subjects exhibit Bayesian information integration when they infer the position of a target from noisy sensory feedback. When introducing a cost associated with subjects' response, we found that subjects exhibited a characteristic bias towards low cost responses when their uncertainty was high. This result is in accordance with risk-sensitive decision-making processes that allow for deviations from Bayes optimal decision-making in the face of uncertainty. Our results suggest that both Bayesian integration and risk-sensitivity are important factors to understand sensorimotor integration in a quantitative fashion. PMID:23028294
Bayesian analysis of the modified Omori law
NASA Astrophysics Data System (ADS)
Holschneider, M.; Narteau, C.; Shebalin, P.; Peng, Z.; Schorlemmer, D.
2012-06-01
In order to examine variations in aftershock decay rate, we propose a Bayesian framework to estimate the {K, c, p}-values of the modified Omori law (MOL), λ(t) = K(c + t)-p. The Bayesian setting allows not only to produce a point estimator of these three parameters but also to assess their uncertainties and posterior dependencies with respect to the observed aftershock sequences. Using a new parametrization of the MOL, we identify the trade-off between the c and p-value estimates and discuss its dependence on the number of aftershocks. Then, we analyze the influence of the catalog completeness interval [tstart, tstop] on the various estimates. To test this Bayesian approach on natural aftershock sequences, we use two independent and non-overlapping aftershock catalogs of the same earthquakes in Japan. Taking into account the posterior uncertainties, we show that both the handpicked (short times) and the instrumental (long times) catalogs predict the same ranges of parameter values. We therefore conclude that the same MOL may be valid over short and long times.
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
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.
Learning Bayesian Networks from Correlated Data
Bae, Harold; Monti, Stefano; Montano, Monty; Steinberg, Martin H.; Perls, Thomas T.; Sebastiani, Paola
2016-01-01
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. PMID:27146517
Learning Bayesian Networks from Correlated Data.
Bae, Harold; Monti, Stefano; Montano, Monty; Steinberg, Martin H; Perls, Thomas T; Sebastiani, Paola
2016-01-01
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. PMID:27146517
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.
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
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
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. PMID:26405944
Nonperturbative approach to the attractive Hubbard model
Allen, S.; Tremblay, A.-M. S.
2001-08-15
A nonperturbative approach to the single-band attractive Hubbard model is presented in the general context of functional-derivative approaches to many-body theories. As in previous work on the repulsive model, the first step is based on a local-field-type ansatz, on enforcement of the Pauli principle and a number of crucial sumrules. The Mermin-Wagner theorem in two dimensions is automatically satisfied. At this level, two-particle self-consistency has been achieved. In the second step of the approximation, an improved expression for the self-energy is obtained by using the results of the first step in an exact expression for the self-energy, where the high- and low-frequency behaviors appear separately. The result is a cooperon-like formula. The required vertex corrections are included in this self-energy expression, as required by the absence of a Migdal theorem for this problem. Other approaches to the attractive Hubbard model are critically compared. Physical consequences of the present approach and agreement with Monte Carlo simulations are demonstrated in the accompanying paper (following this one).
Hospitals can attract women through education.
Rynne, S J
1987-09-01
Hospitals are responding to women's demands for information about healthcare by instituting educational programs specifically for women. To plan such programs, the first step is to establish the major goal--whether to attract new market segments or to better serve existing users of services. It is possible to accomplish both, but they may require different approaches in terms of the program's location, time, presenters, topics, and promotion. In addition to attracting an audience, these programs also can build an image and promote utilization of services. Women who hear or read of the programs will get the impression the hospital cares and is enlightened about women. Targeted segments can be established by factors such as age, geography, and employment status, and programs can be set up to meet the specific needs of each segment. The program planners must resist the urge to tell women what the planners want them to know; instead, planners should learn what the women want to know. The programs also should rely on research that deals specifically with women, instead of information applicable to all people, since that information is usually based on the study of men only. Once the program has been presented, its effectiveness can be measured through random telephone or mail surveys to determine whether the target market has been reached. PMID:10283485
Tuning short-range attractions in protein solutions: from attractive glasses to equilibrium clusters
NASA Astrophysics Data System (ADS)
Stradner, Anna; Thurston, George M.; Schurtenberger, Peter
2005-08-01
We report small-angle scattering experiments with two different types of model proteins, lysozyme and the eye lens protein γB-crystallin. We discuss the results in the context of recent suggestions that globular proteins possess a short-ranged attractive potential, and that simple models from colloid science could help to rationalize the best route for obtaining protein crystals and to interpret their complex phase diagrams. The short-range attraction leads to an extremely interesting phase behaviour with a liquid-gas coexistence curve that is metastable with respect to the liquid-solid (crystal) boundary and the occurrence of an attractive glass. We demonstrate that for γB-crystallin, the scattering data are indeed in good agreement with predictions for an interaction potential consisting of short-ranged attraction and hard sphere repulsion, and we also provide evidence of a dynamically arrested glass or gel phase at high concentrations. We also report on a systematic study of the effect of a weak screened Coulomb repulsion in highly concentrated lysozyme solutions. We demonstrate that combining short-range attraction and long-range repulsion results in the formation of small equilibrium clusters, and we discuss the concentration and temperature dependence of the cluster size in view of its analogy to micelle formation.
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
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.
Investigating locality effects and surprisal in written English syntactic choice phenomena.
Rajkumar, Rajakrishnan; van Schijndel, Marten; White, Michael; Schuler, William
2016-10-01
We investigate the extent to which syntactic choice in written English is influenced by processing considerations as predicted by Gibson's (2000) Dependency Locality Theory (DLT) and Surprisal Theory (Hale, 2001; Levy, 2008). A long line of previous work attests that languages display a tendency for shorter dependencies, and in a previous corpus study, Temperley (2007) provided evidence that this tendency exerts a strong influence on constituent ordering choices. However, Temperley's study included no frequency-based controls, and subsequent work on sentence comprehension with broad-coverage eye-tracking corpora found weak or negative effects of DLT-based measures when frequency effects were statistically controlled for (Demberg & Keller, 2008; van Schijndel, Nguyen, & Schuler 2013; van Schijndel & Schuler, 2013), calling into question the actual impact of dependency locality on syntactic choice phenomena. Going beyond Temperley's work, we show that DLT integration costs are indeed a significant predictor of syntactic choice in written English even in the presence of competing frequency-based and cognitively motivated control factors, including n-gram probability and PCFG surprisal as well as embedding depth (Wu, Bachrach, Cardenas, & Schuler, 2010; Yngve, 1960). Our study also shows that the predictions of dependency length and surprisal are only moderately correlated, a finding which mirrors Dember & Keller's (2008) results for sentence comprehension. Further, we demonstrate that the efficacy of dependency length in predicting the corpus choice increases with increasing head-dependent distances. At the same time, we find that the tendency towards dependency locality is not always observed, and with pre-verbal adjuncts in particular, non-locality cases are found more often than not. In contrast, surprisal is effective in these cases, and the embedding depth measures further increase prediction accuracy. We discuss the implications of our findings for theories of
Asem, Judith S A; Schiffino, Felipe L; Holland, Peter C
2015-09-01
The dorsolateral striatum (DLS) is frequently implicated in sensory-motor integration, including the performance of sensory orienting responses (ORs) and learned stimulus-response habits. Our laboratory previously identified a role for the DLS in rats' performance of conditioned ORs to Pavlovian cues for food delivery. Here, we considered whether DLS is also critical to another aspect of attention in associative learning, the surprise-induced enhancement of cue associability. A large behavioral literature shows that a cue present when an expected event is omitted enters into new associations more rapidly when that cue is subsequently paired with food. Research from our laboratory has shown that both cue associability enhancements and conditioned ORs depend on the function of a circuit that includes the amygdala central nucleus and the substantia nigra pars compacta. In three experiments, we explored the involvement of DLS in surprise-induced associability enhancements, using a three-stage serial prediction task that permitted separation of DLS function in registering surprise (prediction error) and enhancing cue associability, and in using that increased associability to learn more rapidly about that cue later. The results showed that DLS is critical to the expression, but not the establishment, of the enhanced cue associability normally produced by surprise in this task. They extend the role of DLS and the amygdalo-nigro-striatal circuit underlying learned orienting to more subtle aspects of attention in associative learning, but are consistent with the general notion that DLS is more important in the expression of previously acquired tendencies than in their acquisition. PMID:26108257
Each individual is a surprise: a conversation with Marianne Horney Eckardt.
Rubin, Jeffrey B
2014-06-01
"Each Individual is a Surprise" is a brief account of a dialogue between Marianne Horney Eckardt and myself about the state of psychoanalysis and the psychoanalytic process, the danger of idolatry, the damaging impact of psychoanalytic schools when they create a standardized and pathologizing approach to people, the value of curiosity and humility and retaining one's clinical creativity. The role of Rank, Horney, Sullivan, and Fromm in Dr. Eckardt's long life and rich work is touched upon. PMID:24882069
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.
The Bayesian bridge between simple and universal kriging
Omre, H.; Halvorsen, K.B. )
1989-10-01
Kriging techniques are suited well for evaluation of continuous, spatial phenomena. Bayesian statistics are characterized by using prior qualified guesses on the model parameters. By merging kriging techniques and Bayesian theory, prior guesses may be used in a spatial setting. Partial knowledge of model parameters defines a continuum of models between what is named simple and universal kriging in geostatistical terminology. The Bayesian approach to kriging is developed and discussed, and a case study concerning depth conversion of seismic reflection times is presented.
Modular structure of brain functional networks: breaking the resolution limit by Surprise
NASA Astrophysics Data System (ADS)
Nicolini, Carlo; Bifone, Angelo
2016-01-01
The modular organization of brain networks has been widely investigated using graph theoretical approaches. Recently, it has been demonstrated that graph partitioning methods based on the maximization of global fitness functions, like Newman’s Modularity, suffer from a resolution limit, as they fail to detect modules that are smaller than a scale determined by the size of the entire network. Here we explore the effects of this limitation on the study of brain connectivity networks. We demonstrate that the resolution limit prevents detection of important details of the brain modular structure, thus hampering the ability to appreciate differences between networks and to assess the topological roles of nodes. We show that Surprise, a recently proposed fitness function based on probability theory, does not suffer from these limitations. Surprise maximization in brain co-activation and functional connectivity resting state networks reveals the presence of a rich structure of heterogeneously distributed modules, and differences in networks’ partitions that are undetectable by resolution-limited methods. Moreover, Surprise leads to a more accurate identification of the network’s connector hubs, the elements that integrate the brain modules into a cohesive structure.
Modular structure of brain functional networks: breaking the resolution limit by Surprise
Nicolini, Carlo; Bifone, Angelo
2016-01-01
The modular organization of brain networks has been widely investigated using graph theoretical approaches. Recently, it has been demonstrated that graph partitioning methods based on the maximization of global fitness functions, like Newman’s Modularity, suffer from a resolution limit, as they fail to detect modules that are smaller than a scale determined by the size of the entire network. Here we explore the effects of this limitation on the study of brain connectivity networks. We demonstrate that the resolution limit prevents detection of important details of the brain modular structure, thus hampering the ability to appreciate differences between networks and to assess the topological roles of nodes. We show that Surprise, a recently proposed fitness function based on probability theory, does not suffer from these limitations. Surprise maximization in brain co-activation and functional connectivity resting state networks reveals the presence of a rich structure of heterogeneously distributed modules, and differences in networks’ partitions that are undetectable by resolution-limited methods. Moreover, Surprise leads to a more accurate identification of the network’s connector hubs, the elements that integrate the brain modules into a cohesive structure. PMID:26763931
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.
Tweedy, Luke; Knecht, David A.; Mackay, Gillian M.; Insall, Robert H.
2016-01-01
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. PMID:26981861
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. PMID:26981861
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
The mating game: do opposites really attract?
Gow, Jennifer L
2008-03-01
When selecting a mate, females of many species face a complicated decision: choosing a very closely related mate will lead to inbreeding, while choosing a mate who is too genetically dissimilar risks breaking up beneficial gene complexes or local genetic adaptations. To ensure the best genetic quality of their offspring, the perfect compromise lies somewhere in between: an optimally genetically dissimilar partner. Empirical evidence demonstrating female preference for genetically dissimilar mates is proof of the adage 'opposites attract'. In stark contrast, Chandler & Zamudio (2008) show in this issue of Molecular Ecology that female spotted salamanders often choose males that are genetically more similar to themselves (although not if the males are small). Along with other recent work, these field studies highlight the broad spectrum of options available to females with respect to relatedness in their choice of mate that belies this rule of thumb. PMID:18266628
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.
Physician equity alliances: attractive alternatives to PHOs.
Goldstein, D
1997-04-01
Physician equity alliances are becoming attractive alternatives to PHOs as integrative models for partnering with physicians, securing managed care contracts and increasing revenue. Unlike many PHOs, these alliances provide mechanisms for asset integration and long-term relationships along with utilization management, sophisticated information systems, access to capital and opportunities for physicians to integrate clinically. There are six major types of physician equity alliances: majority physician-owned, clinic without walls, health system joint venture, publicly held physician practice management company, specialty network, and venture capital. The type of alliance that a physician group practice ultimately develops depends on vision, values, method of capitalization, initial organizer of the alliance, level of involvement of physicians in business issues, corporate structure desired, and characteristics of the managed care market in which the alliance will operate. PMID:10166285
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.
Mosquito repellent attracts Culicoides imicola (Diptera: Ceratopogonidae).
Braverman, Y; Chizov-Ginzburg, A; Mullens, B A
1999-01-01
A plant-derived mosquito repellent, based on the oil of Eucalyptus maculata var. citriodora Hook, was evaluated against the biting midge Culicoides imicola Kieffer. Suction black light-traps covered with repellent-impregnated polyester mesh and deployed near horses attracted large numbers of C. imicola, which were seen near the treated net within a few minutes of the start of the experiment. Initial collections in the traps were approximately 3 times as large as those in control traps with untreated mesh. Numbers collected in treated traps were similar to untreated control traps after 4 h. Traps with mesh treated with DEET or another plant-derived (Meliaceae) proprietary product, AG1000, acted as repellents relative to the control. The differential activity of repellents against blood-feeding Diptera is discussed. PMID:10071502
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
2015-05-26
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 (fru(M))-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
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
The Size-Weight Illusion is not anti-Bayesian after all: a unifying Bayesian account
Ma, Wei Ji; Shams, Ladan
2016-01-01
When we lift two differently-sized but equally-weighted objects, we expect the larger to be heavier, but the smaller feels heavier. However, traditional Bayesian approaches with “larger is heavier” priors predict the smaller object should feel lighter; this Size-Weight Illusion (SWI) has thus been labeled “anti-Bayesian” and has stymied psychologists for generations. We propose that previous Bayesian approaches neglect the brain’s inference process about density. In our Bayesian model, objects’ perceived heaviness relationship is based on both their size and inferred density relationship: observers evaluate competing, categorical hypotheses about objects’ relative densities, the inference about which is then used to produce the final estimate of weight. The model can qualitatively and quantitatively reproduce the SWI and explain other researchers’ findings, and also makes a novel prediction, which we confirmed. This same computational mechanism accounts for other multisensory phenomena and illusions; that the SWI follows the same process suggests that competitive-prior Bayesian inference can explain human perception across many domains. PMID:27350899
Role of Physical Attractiveness in Peer Attribution of Psychological Disturbance
ERIC Educational Resources Information Center
Cash, Thomas F.; And Others
1977-01-01
The physical attractiveness stereotype was examined as it pertains to the attribution of psychological disturbance among peers. Consistent with the stereotype, attractive interviewees were judged as less disturbed with better prognosis than unattractive interviewees. (Author)
Bayesian Methodology for the Space Interferometry Mission
NASA Astrophysics Data System (ADS)
Loredo, T. J.; Chernoff, D. F.
2000-05-01
We will describe work in progress on the development of Bayesian methodology for the analysis of data from the Space Interferometry Mission (SIM). There are two main thrusts to this work: development of new methods for the detection and analysis of Keplerian reflex motion in astrometric data; and adaptive experimental design for on-the-fly refinement of the SIM grid. For detection and measurement of reflex motions (e.g., from planetary companions), we use the algorithm developed by Bretthorst for the Bayesian analysis of superposed nonlinear models to develop an alternative to the commonly used Lomb-Scargle (LS) periodogram that we call the Kepler periodogram. The LS periodogram emerges as a special case of the Kepler periodogram when the data are 1-dimensional (e.g., radial velocity (RV) measurements) and the bodies in question are in a circular orbit. But the Kepler periodogram generalizes the LS periodogram to account for orbital eccentricity, higher dimensional data (e.g., astrometric data, or a combination of astrometric and RV data), and sources of systematic error such as uncertainty in inertial motion. We use the Bayesian theory of experimental design to develop adaptive strategies for SIM observing. This includes identifying the best sampling scheme for detecting and monitoring Keplerian reflex motions in science targets, and (perhaps more crucially) the adaptive refinement of the SIM astrometric grid from observations of candidate grid stars throughout the SIM mission. Included in this latter task are classification of candidate grid objects as inertial or noninertial and scheduling of observations to best update our knowledge of grid star motions.
Bayesian inference tools for inverse problems
NASA Astrophysics Data System (ADS)
Mohammad-Djafari, Ali
2013-08-01
In this paper, first the basics of Bayesian inference with a parametric model of the data is presented. Then, the needed extensions are given when dealing with inverse problems and in particular the linear models such as Deconvolution or image reconstruction in Computed Tomography (CT). The main point to discuss then is the prior modeling of signals and images. A classification of these priors is presented, first in separable and Markovien models and then in simple or hierarchical with hidden variables. For practical applications, we need also to consider the estimation of the hyper parameters. Finally, we see that we have to infer simultaneously on the unknowns, the hidden variables and the hyper parameters. Very often, the expression of this joint posterior law is too complex to be handled directly. Indeed, rarely we can obtain analytical solutions to any point estimators such the Maximum A posteriori (MAP) or Posterior Mean (PM). Three main tools are then can be used: Laplace approximation (LAP), Markov Chain Monte Carlo (MCMC) and Bayesian Variational Approximations (BVA). To illustrate all these aspects, we will consider a deconvolution problem where we know that the input signal is sparse and propose to use a Student-t prior for that. Then, to handle the Bayesian computations with this model, we use the property of Student-t which is modelling it via an infinite mixture of Gaussians, introducing thus hidden variables which are the variances. Then, the expression of the joint posterior of the input signal samples, the hidden variables (which are here the inverse variances of those samples) and the hyper-parameters of the problem (for example the variance of the noise) is given. From this point, we will present the joint maximization by alternate optimization and the three possible approximation methods. Finally, the proposed methodology is applied in different applications such as mass spectrometry, spectrum estimation of quasi periodic biological signals and
Bayesian Decision Support for Adaptive Lung Treatments
NASA Astrophysics Data System (ADS)
McShan, Daniel; Luo, Yi; Schipper, Matt; TenHaken, Randall
2014-03-01
Purpose: A Bayesian Decision Network will be demonstrated to provide clinical decision support for adaptive lung response-driven treatment management based on evidence that physiologic metrics may correlate better with individual patient response than traditional (population-based) dose and volume-based metrics. Further, there is evidence that information obtained during the course of radiation therapy may further improve response predictions. Methods: Clinical factors were gathered for 58 patients including planned mean lung dose, and the bio-markers IL-8 and TGF-β1 obtained prior to treatment and two weeks into treatment along with complication outcomes for these patients. A Bayesian Decision Network was constructed using Netica 5.0.2 from Norsys linking these clinical factors to obtain a prediction of radiation induced lung disese (RILD) complication. A decision node was added to the network to provide a plan adaption recommendation based on the trade-off between the RILD prediction and complexity of replanning. A utility node provides the weighting cost between the competing factors. Results: The decision node predictions were optimized against the data for the 58 cases. With this decision network solution, one can consider the decision result for a new patient with specific findings to obtain a recommendation to adaptively modify the originally planned treatment course. Conclusions: A Bayesian approach allows handling and propagating probabilistic data in a logical and principled manner. Decision networks provide the further ability to provide utility-based trade-offs, reflecting non-medical but practical cost/benefit analysis. The network demonstrated illustrates the basic concept, but many other factors may affect these decisions and work on building better models are being designed and tested. Acknowledgement: Supported by NIH-P01-CA59827
Bayesian population modeling of drug dosing adherence.
Fellows, Kelly; Stoneking, Colin J; Ramanathan, Murali
2015-10-01
Adherence is a frequent contributing factor to variations in drug concentrations and efficacy. The purpose of this work was to develop an integrated population model to describe variation in adherence, dose-timing deviations, overdosing and persistence to dosing regimens. The hybrid Markov chain-von Mises method for modeling adherence in individual subjects was extended to the population setting using a Bayesian approach. Four integrated population models for overall adherence, the two-state Markov chain transition parameters, dose-timing deviations, overdosing and persistence were formulated and critically compared. The Markov chain-Monte Carlo algorithm was used for identifying distribution parameters and for simulations. The model was challenged with medication event monitoring system data for 207 hypertension patients. The four Bayesian models demonstrated good mixing and convergence characteristics. The distributions of adherence, dose-timing deviations, overdosing and persistence were markedly non-normal and diverse. The models varied in complexity and the method used to incorporate inter-dependence with the preceding dose in the two-state Markov chain. The model that incorporated a cooperativity term for inter-dependence and a hyperbolic parameterization of the transition matrix probabilities was identified as the preferred model over the alternatives. The simulated probability densities from the model satisfactorily fit the observed probability distributions of adherence, dose-timing deviations, overdosing and persistence parameters in the sample patients. The model also adequately described the median and observed quartiles for these parameters. The Bayesian model for adherence provides a parsimonious, yet integrated, description of adherence in populations. It may find potential applications in clinical trial simulations and pharmacokinetic-pharmacodynamic modeling. PMID:26319548
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
Radioactive Contraband Detection: A Bayesian Approach
Candy, J; Breitfeller, E; Guidry, B; Manatt, D; Sale, K; Chambers, D; Axelrod, M; Meyer, A
2009-03-16
Radionuclide emissions from nuclear contraband challenge both detection and measurement technologies to capture and record each event. The development of a sequential Bayesian processor incorporating both the physics of gamma-ray emissions and the measurement of photon energies offers a physics-based approach to attack this challenging problem. It is shown that a 'physics-based' structure can be used to develop an effective detection technique, but also motivates the implementation of this approach using or particle filters to enhance and extract the required information.
Bayesian Automatic Classification Of HMI Images
NASA Astrophysics Data System (ADS)
Ulrich, R. K.; Beck, John G.
2011-05-01
The Bayesian automatic classification system known as "AutoClass" finds a set of class definitions based on a set of observed data and assigns data to classes without human supervision. It has been applied to Mt Wilson data to improve modeling of total solar irradiance variations (Ulrich, et al, 2010). We apply AutoClass to HMI observables to automatically identify regions of the solar surface. To prevent small instrument artifacts from interfering with class identification, we apply a flat-field correction and a rotationally shifted temporal average to the HMI images prior to processing with AutoClass. Additionally, the sensitivity of AutoClass to instrumental artifacts is investigated.
Bayesian Model Selection for Group Studies
Stephan, Klaas Enno; Penny, Will D.; Daunizeau, Jean; Moran, Rosalyn J.; Friston, Karl J.
2009-01-01
Bayesian model selection (BMS) is a powerful method for determining the most likely among a set of competing hypotheses about the mechanisms that generated observed data. BMS has recently found widespread application in neuroimaging, particularly in the context of dynamic causal modelling (DCM). However, so far, combining BMS results from several subjects has relied on simple (fixed effects) metrics, e.g. the group Bayes factor (GBF), that do not account for group heterogeneity or outliers. In this paper, we compare the GBF with two random effects methods for BMS at the between-subject or group level. These methods provide inference on model-space using a classical and Bayesian perspective respectively. First, a classical (frequentist) approach uses the log model evidence as a subject-specific summary statistic. This enables one to use analysis of variance to test for differences in log-evidences over models, relative to inter-subject differences. We then consider the same problem in Bayesian terms and describe a novel hierarchical model, which is optimised to furnish a probability density on the models themselves. This new variational Bayes method rests on treating the model as a random variable and estimating the parameters of a Dirichlet distribution which describes the probabilities for all models considered. These probabilities then define a multinomial distribution over model space, allowing one to compute how likely it is that a specific model generated the data of a randomly chosen subject as well as the exceedance probability of one model being more likely than any other model. Using empirical and synthetic data, we show that optimising a conditional density of the model probabilities, given the log-evidences for each model over subjects, is more informative and appropriate than both the GBF and frequentist tests of the log-evidences. In particular, we found that the hierarchical Bayesian approach is considerably more robust than either of the other
Bayesian estimation of self-similarity exponent
NASA Astrophysics Data System (ADS)
Makarava, Natallia; Benmehdi, Sabah; Holschneider, Matthias
2011-08-01
In this study we propose a Bayesian approach to the estimation of the Hurst exponent in terms of linear mixed models. Even for unevenly sampled signals and signals with gaps, our method is applicable. We test our method by using artificial fractional Brownian motion of different length and compare it with the detrended fluctuation analysis technique. The estimation of the Hurst exponent of a Rosenblatt process is shown as an example of an H-self-similar process with non-Gaussian dimensional distribution. Additionally, we perform an analysis with real data, the Dow-Jones Industrial Average closing values, and analyze its temporal variation of the Hurst exponent.