Bayesian Belief Networks for predicting drinking water distribution system pipe breaks

International Nuclear Information System (INIS)

Francis, Royce A.; Guikema, Seth D.; Henneman, Lucas

2014-01-01

In this paper, we use Bayesian Belief Networks (BBNs) to construct a knowledge model for pipe breaks in a water zone. To the authors’ knowledge, this is the first attempt to model drinking water distribution system pipe breaks using BBNs. Development of expert systems such as BBNs for analyzing drinking water distribution system data is not only important for pipe break prediction, but is also a first step in preventing water loss and water quality deterioration through the application of machine learning techniques to facilitate data-based distribution system monitoring and asset management. Due to the difficulties in collecting, preparing, and managing drinking water distribution system data, most pipe break models can be classified as “statistical–physical” or “hypothesis-generating.” We develop the BBN with the hope of contributing to the “hypothesis-generating” class of models, while demonstrating the possibility that BBNs might also be used as “statistical–physical” models. Our model is learned from pipe breaks and covariate data from a mid-Atlantic United States (U.S.) drinking water distribution system network. BBN models are learned using a constraint-based method, a score-based method, and a hybrid method. Model evaluation is based on log-likelihood scoring. Sensitivity analysis using mutual information criterion is also reported. While our results indicate general agreement with prior results reported in pipe break modeling studies, they also suggest that it may be difficult to select among model alternatives. This model uncertainty may mean that more research is needed for understanding whether additional pipe break risk factors beyond age, break history, pipe material, and pipe diameter might be important for asset management planning. - Highlights: • We show Bayesian Networks for predictive and diagnostic management of water distribution systems. • Our model may enable system operators and managers to prioritize system

Estimation of Remained defects in a Safety-Critical Software using Bayesian Belief Network of Software Development Life Cycle

International Nuclear Information System (INIS)

Lee, Seung Jun; Jung, Wondea Jung

2015-01-01

Some researchers recognized Bayesian belief network (BBN) method to be a promising method of quantifying software reliability. Brookhaven National Laboratory (BNL) comprehensively reviewed various quantitative software reliability methods to identify the most promising methods for use in probabilistic safety assessments (PSAs) of digital systems of NPPs against a set of the most desirable characteristics developed therein. BBNs are recognized as a promising way of quantifying software reliability and are useful for integrating many aspects of software engineering and quality assurance. The method explicitly incorporates important factors relevant to reliability, such as the quality of the developer, the development process, problem complexity, testing effort, and the operation environment. In this work, a BBN model was developed to estimate the number of remained defects in a safety-critical software based on the quality evaluation of software development life cycle (SDLC). Even though a number of software reliability evaluation methods exist, none of them can be applicable to the safety-critical software in an NPP because software quality in terms of PDF is required for the PSA

Can Bayesian Belief Networks help tackling conceptual model uncertainties in contaminated site risk assessment?

DEFF Research Database (Denmark)

Troldborg, Mads; Thomsen, Nanna Isbak; McKnight, Ursula S.

different conceptual models may describe the same contaminated site equally well. In many cases, conceptual model uncertainty has been shown to be one of the dominant sources for uncertainty and is therefore essential to account for when quantifying uncertainties in risk assessments. We present here......A key component in risk assessment of contaminated sites is the formulation of a conceptual site model. The conceptual model is a simplified representation of reality and forms the basis for the mathematical modelling of contaminant fate and transport at the site. A conceptual model should...... a Bayesian Belief Network (BBN) approach for evaluating the uncertainty in risk assessment of groundwater contamination from contaminated sites. The approach accounts for conceptual model uncertainty by considering multiple conceptual models, each of which represents an alternative interpretation of the site...

BBN predictions for 4He

International Nuclear Information System (INIS)

Walker, T.P.

1993-01-01

The standard model of the hot big bang assumes a homogeneous and isotropic Universe with gravity described by General Relativity and strong and electroweak interactions described by the Standard Model of particle physics. The hot big bang model makes the unavoidable prediction that the production of primordial elements occurred about one minute after the big band (referred to as big bang or primordial nucleosynthesis BBN). This review concerns the range of the primordial abundance of 4 He as predicted by standard BBN (i.e., primordial nucleosynthesis assuming a homogeneous distribution of baryons). In it the author discusses: (1) Uncertainties in the calculation of Y p (the mass fraction of primordial 4 He), (2) The expected range of Y p , (3) How the predictions stack up against the latest observations, and (4) The latest BBN bounds on Ω B h 2 and N ν . 13 refs., 2 figs

BBN-Based Portfolio Risk Assessment for NASA Technology R&D Outcome

Science.gov (United States)

Geuther, Steven C.; Shih, Ann T.

2016-01-01

The NASA Aeronautics Research Mission Directorate (ARMD) vision falls into six strategic thrusts that are aimed to support the challenges of the Next Generation Air Transportation System (NextGen). In order to achieve the goals of the ARMD vision, the Airspace Operations and Safety Program (AOSP) is committed to developing and delivering new technologies. To meet the dual challenges of constrained resources and timely technology delivery, program portfolio risk assessment is critical for communication and decision-making. This paper describes how Bayesian Belief Network (BBN) is applied to assess the probability of a technology meeting the expected outcome. The network takes into account the different risk factors of technology development and implementation phases. The use of BBNs allows for all technologies of projects in a program portfolio to be separately examined and compared. In addition, the technology interaction effects are modeled through the application of object-oriented BBNs. The paper discusses the development of simplified project risk BBNs and presents various risk results. The results presented include the probability of project risks not meeting success criteria, the risk drivers under uncertainty via sensitivity analysis, and what-if analysis. Finally, the paper shows how program portfolio risk can be assessed using risk results from BBNs of projects in the portfolio.

Development and Execution of the RUNSAFE Runway Safety Bayesian Belief Network Model

Science.gov (United States)

Green, Lawrence L.

2015-01-01

One focus area of the National Aeronautics and Space Administration (NASA) is to improve aviation safety. Runway safety is one such thrust of investigation and research. The two primary components of this runway safety research are in runway incursion (RI) and runway excursion (RE) events. These are adverse ground-based aviation incidents that endanger crew, passengers, aircraft and perhaps other nearby people or property. A runway incursion is the incorrect presence of an aircraft, vehicle or person on the protected area of a surface designated for the landing and take-off of aircraft; one class of RI events simultaneously involves two aircraft, such as one aircraft incorrectly landing on a runway while another aircraft is taking off from the same runway. A runway excursion is an incident involving only a single aircraft defined as a veer-off or overrun off the runway surface. Within the scope of this effort at NASA Langley Research Center (LaRC), generic RI, RE and combined (RI plus RE, or RUNSAFE) event models have each been developed and implemented as a Bayesian Belief Network (BBN). Descriptions of runway safety issues from the literature searches have been used to develop the BBN models. Numerous considerations surrounding the process of developing the event models have been documented in this report. The event models were then thoroughly reviewed by a Subject Matter Expert (SME) panel through multiple knowledge elicitation sessions. Numerous improvements to the model structure (definitions, node names, node states and the connecting link topology) were made by the SME panel. Sample executions of the final RUNSAFE model have been presented herein for baseline and worst-case scenarios. Finally, a parameter sensitivity analysis for a given scenario was performed to show the risk drivers. The NASA and LaRC research in runway safety event modeling through the use of BBN technology is important for several reasons. These include: 1) providing a means to clearly

Coastal vulnerability assessment using Fuzzy Logic and Bayesian Belief Network approaches

Science.gov (United States)

Valentini, Emiliana; Nguyen Xuan, Alessandra; Filipponi, Federico; Taramelli, Andrea

2017-04-01

Natural hazards such as sea surge are threatening low-lying coastal plains. In order to deal with disturbances a deeper understanding of benefits deriving from ecosystem services assessment, management and planning can contribute to enhance the resilience of coastal systems. In this frame assessing current and future vulnerability is a key concern of many Systems Of Systems SOS (social, ecological, institutional) that deals with several challenges like the definition of Essential Variables (EVs) able to synthesize the required information, the assignment of different weight to be attributed to each considered variable, the selection of method for combining the relevant variables. It is widely recognized that ecosystems contribute to human wellbeing and then their conservation increases the resilience capacities and could play a key role in reducing climate related risk and thus physical and economic losses. A way to fully exploit ecosystems potential, i.e. their so called ecopotential (see H2020 EU funded project "ECOPOTENTIAL"), is the Ecosystem based Adaptation (EbA): the use of ecosystem services as part of an adaptation strategy. In order to provide insight in understanding regulating ecosystem services to surge and which variables influence them and to make the best use of available data and information (EO products, in situ data and modelling), we propose a multi-component surge vulnerability assessment, focusing on coastal sandy dunes as natural barriers. The aim is to combine together eco-geomorphological and socio-economic variables with the hazard component on the base of different approaches: 1) Fuzzy Logic; 2) Bayesian Belief Networks (BBN). The Fuzzy Logic approach is very useful to get a spatialized information and it can easily combine variables coming from different sources. It provides information on vulnerability moving along-shore and across-shore (beach-dune transect), highlighting the variability of vulnerability conditions in the spatial

Preparation and preliminary evaluation of 99Tcm-HYNIC-β-Ala-BBN(7-14)NH2

International Nuclear Information System (INIS)

Quan Xin; Zhang Yan; Jia Bing; Shi Jiyun; Wang Fan; Zhao Huiyun; Yu Zilin

2007-01-01

99 Tc m -HYNIC-β-Ala-BBN(7-14)NH 2 is prepared by choosing Tricine and EDDA as coligands, and the in vitro stability and biodistribution are compared for the two compounds. The results of ITLC and HPLC analyses show that the labeling yield of both compounds is >95%, and the radiochemical purity (RCP) after purification of Sep-Pak C-18 cartridge is >99%. Both of the compounds show pretty good stability in saline and fetal bovine serum, but cysteine challenge assay shows that the stability of 99 Tc m -HYNIC(EDDA)- β-Ala-BBN (7-14) NH 2 is much better than 99 Tc m -HYNIC (Tricine)-β-Ala-BBN (7-14) NH 2 , with the RCP is >95% and 99 Tc m HYNIC (EDDA)-βAla-BBN (7-14)NH 2 and 99 Tc m -HYNIC (Tricine)-β-Ala-BBN(7-14)NH 2 is defined as two-compartment model, with T 1/2α calculated to be 0.27 min and 1.55 min, and T 1/2β calculated to be 18.1 min and 29.7 min, respectively. Biodistribution reveals that the radio uptake of 99 Tc m -HYNIC(Tricine)-β-Ala-BBN(7-14)NH 2 is higher than that of 99 Tc m -HYNIC(EDDA)-β-Ala-BBN(7-14)NH 2 for all of tis- sues at all time points of the experiment. The uptake in kidneys for both compounds is relatively high, as the uptake in livers and intestines for 99 Tc m -HYNIC(Tricine)-β-Ala-BBN(7- 14)NH 2 is significantly higher than that for 99 Tc m -HYNIC(EDDA)-β-Ala-BBN(7-14)NH 2 , which means that 99 Tc m -HYNIC(EDDA)-β-Ala-BBN(7-14)NH 2 is mainly excreted through kidneys, while 99 Tc m -HYNIC(Tricine)-β-Ala-BBN(7-14)NH 2 is excreted through both kidneys and hepatobiliary system. The above data demonstrate that 99 Tc m -HYNIC(EDDA)-β- Ala-BBN(7-14)NH 2 possesses better chemical and biological properties. (authors)

A Bayesian Belief Network Approach to Predict Damages Caused by Disturbance Agents

Directory of Open Access Journals (Sweden)

Alfred Radl

2017-12-01

Full Text Available In mountain forests of Central Europe, storm and snow breakage as well as bark beetles are the prevailing major disturbances. The complex interrelatedness between climate, disturbance agents, and forest management increases the need for an integrative approach explicitly addressing the multiple interactions between environmental changes, forest management, and disturbance agents to support forest resource managers in adaptive management. Empirical data with a comprehensive coverage for modelling the susceptibility of forests and the impact of disturbance agents are rare, thus making probabilistic models, based on expert knowledge, one of the few modelling approaches that are able to handle uncertainties due to the available information. Bayesian belief networks (BBNs are a kind of probabilistic graphical model that has become very popular to practitioners and scientists mainly due to considerations of risk and uncertainties. In this contribution, we present a development methodology to define and parameterize BBNs based on expert elicitation and approximation. We modelled storm and bark beetle disturbances agents, analyzed effects of the development methodology on model structure, and evaluated behavior with stand data from Norway spruce (Picea abies (L. Karst. forests in southern Austria. The high vulnerability of the case study area according to different disturbance agents makes it particularly suitable for testing the BBN model.

Constraining f(T) teleparallel gravity by big bang nucleosynthesis. f(T) cosmology and BBN

Energy Technology Data Exchange (ETDEWEB)

Capozziello, S. [Universita di Napoli ' ' Federico II' ' , Complesso Universitario di Monte Sant' Angelo, Dipartimento di Fisica ' ' E. Pancini' ' , Napoli (Italy); Istituto Nazionale di Fisica Nucleare (INFN), Sezione di Napoli (Italy); Gran Sasso Science Institute, L' Aquila (Italy); Lambiase, G. [University of Salerno, Dipartimento di Fisica E.R. Cainaiello, Fisciano (Italy); INFN, Gruppo Collegato di Salerno, Sezione di Napoli, Fisciano (Italy); Saridakis, E.N. [National Technical University of Athens, Department of Physics, Athens (Greece); Baylor University, CASPER, Physics Department, Waco, TX (United States)

2017-09-15

We use Big Bang Nucleosynthesis (BBN) observational data on the primordial abundance of light elements to constrain f(T) gravity. The three most studied viable f(T) models, namely the power law, the exponential and the square-root exponential are considered, and the BBN bounds are adopted in order to extract constraints on their free parameters. For the power-law model, we find that the constraints are in agreement with those obtained using late-time cosmological data. For the exponential and the square-root exponential models, we show that for reliable regions of parameters space they always satisfy the BBN bounds. We conclude that viable f(T) models can successfully satisfy the BBN constraints. (orig.)

Constraining f(T) teleparallel gravity by big bang nucleosynthesis: f(T) cosmology and BBN.

Science.gov (United States)

Capozziello, S; Lambiase, G; Saridakis, E N

2017-01-01

We use Big Bang Nucleosynthesis (BBN) observational data on the primordial abundance of light elements to constrain f ( T ) gravity. The three most studied viable f ( T ) models, namely the power law, the exponential and the square-root exponential are considered, and the BBN bounds are adopted in order to extract constraints on their free parameters. For the power-law model, we find that the constraints are in agreement with those obtained using late-time cosmological data. For the exponential and the square-root exponential models, we show that for reliable regions of parameters space they always satisfy the BBN bounds. We conclude that viable f ( T ) models can successfully satisfy the BBN constraints.

Constraining f( T) teleparallel gravity by big bang nucleosynthesis. f(T) cosmology and BBN

Science.gov (United States)

Capozziello, S.; Lambiase, G.; Saridakis, E. N.

2017-09-01

We use Big Bang Nucleosynthesis (BBN) observational data on the primordial abundance of light elements to constrain f( T) gravity. The three most studied viable f( T) models, namely the power law, the exponential and the square-root exponential are considered, and the BBN bounds are adopted in order to extract constraints on their free parameters. For the power-law model, we find that the constraints are in agreement with those obtained using late-time cosmological data. For the exponential and the square-root exponential models, we show that for reliable regions of parameters space they always satisfy the BBN bounds. We conclude that viable f( T) models can successfully satisfy the BBN constraints.

Constraining f(T) teleparallel gravity by big bang nucleosynthesis. f(T) cosmology and BBN

International Nuclear Information System (INIS)

Capozziello, S.; Lambiase, G.; Saridakis, E.N.

2017-01-01

We use Big Bang Nucleosynthesis (BBN) observational data on the primordial abundance of light elements to constrain f(T) gravity. The three most studied viable f(T) models, namely the power law, the exponential and the square-root exponential are considered, and the BBN bounds are adopted in order to extract constraints on their free parameters. For the power-law model, we find that the constraints are in agreement with those obtained using late-time cosmological data. For the exponential and the square-root exponential models, we show that for reliable regions of parameters space they always satisfy the BBN bounds. We conclude that viable f(T) models can successfully satisfy the BBN constraints. (orig.)

Characterizing Species at Risk II: Using Bayesian Belief Networks as Decision Support Tools to Determine Species Conservation Categories Under the Northwest Forest Plan

Directory of Open Access Journals (Sweden)

Bruce G. Marcot

2006-12-01

Full Text Available We developed a set of decision-aiding models as Bayesian belief networks (BBNs that represented a complex set of evaluation guidelines used to determine the appropriate conservation of hundreds of potentially rare species on federally-administered lands in the Pacific Northwest United States. The models were used in a structured assessment and paneling procedure as part of an adaptive management process that evaluated new scientific information under the Northwest Forest Plan. The models were not prescriptive but helped resource managers and specialists to evaluate complicated and at times conflicting conservation guidelines and to reduce bias and uncertainty in evaluating the scientific data. We concluded that applying the BBN modeling framework to complex and equivocal evaluation guidelines provided a set of clear, intuitive decision-aiding tools that greatly aided the species evaluation and conservation process.

Using Bayesian belief networks in adaptive management.

Science.gov (United States)

J.B. Nyberg; B.G. Marcot; R. Sulyma

2006-01-01

Bayesian belief and decision networks are relatively new modeling methods that are especially well suited to adaptive-management applications, but they appear not to have been widely used in adaptive management to date. Bayesian belief networks (BBNs) can serve many purposes for practioners of adaptive management, from illustrating system relations conceptually to...

Estimating dependability of programmable systems using bayesian belief nets

International Nuclear Information System (INIS)

Gran, Bjoern Axel; Dahll, Gustav

2000-05-01

The research programme at the Halden Project on software safety assessment is augmented through a joint project with Kongsberg Defence and Aerospace AS and Det Norske Veritas. The objective of this project is to investigate the possibility to combine the Bayesian Belief Net (BBN) methodology with a software safety standard. The report discusses software safety standards in general, with respect to how they can be used to measure software safety. The possibility to transfer the requirements of a software safety standard into a BBN is also investigated. The aim is to utilise the BBN methodology and associated tools, by transferring the software safety measurement into a probabilistic quantity. In this way software can be included in a total probabilistic safety analysis. This project was performed by applying the method for an evaluation of a real, safety related programmable system which was developed according to the avionic standard DO-178B. The test case, the standard, and the BBN methodology are shortly described. This is followed by a description of the construction of the BBN used in this project. This includes the topology of the BBN, the elicitation of probabilities and the making of observations. Based on this a variety of computations are made using the SERENE methodology and the HUGIN tool. Observations and conclusions are made on the basis of the findings from this process. This report should be considered as a progress report in a more long-term activity on the use of BBNs as support for safety assessment of programmable systems. (Author). 23 refs., 9 figs., tabs

Continuous/discrete non parametric Bayesian belief nets with UNICORN and UNINET

NARCIS (Netherlands)

Cooke, R.M.; Kurowicka, D.; Hanea, A.M.; Morales Napoles, O.; Ababei, D.A.; Ale, B.J.M.; Roelen, A.

2007-01-01

Hanea et al. (2006) presented a method for quantifying and computing continuous/discrete non parametric Bayesian Belief Nets (BBN). Influences are represented as conditional rank correlations, and the joint normal copula enables rapid sampling and conditionalization. Further mathematical background

Facial expression recognition based on improved deep belief networks

Science.gov (United States)

Wu, Yao; Qiu, Weigen

2017-08-01

In order to improve the robustness of facial expression recognition, a method of face expression recognition based on Local Binary Pattern (LBP) combined with improved deep belief networks (DBNs) is proposed. This method uses LBP to extract the feature, and then uses the improved deep belief networks as the detector and classifier to extract the LBP feature. The combination of LBP and improved deep belief networks is realized in facial expression recognition. In the JAFFE (Japanese Female Facial Expression) database on the recognition rate has improved significantly.

Probabilistic Volcanic Multi-Hazard Assessment at Somma-Vesuvius (Italy): coupling Bayesian Belief Networks with a physical model for lahar propagation

Science.gov (United States)

Tierz, Pablo; Woodhouse, Mark; Phillips, Jeremy; Sandri, Laura; Selva, Jacopo; Marzocchi, Warner; Odbert, Henry

2017-04-01

Volcanoes are extremely complex physico-chemical systems where magma formed at depth breaks into the planet's surface resulting in major hazards from local to global scales. Volcano physics are dominated by non-linearities, and complicated spatio-temporal interrelationships which make volcanic hazards stochastic (i.e. not deterministic) by nature. In this context, probabilistic assessments are required to quantify the large uncertainties related to volcanic hazards. Moreover, volcanoes are typically multi-hazard environments where different hazardous processes can occur whether simultaneously or in succession. In particular, explosive volcanoes are able to accumulate, through tephra fallout and Pyroclastic Density Currents (PDCs), large amounts of pyroclastic material into the drainage basins surrounding the volcano. This addition of fresh particulate material alters the local/regional hydrogeological equilibrium and increases the frequency and magnitude of sediment-rich aqueous flows, commonly known as lahars. The initiation and volume of rain-triggered lahars may depend on: rainfall intensity and duration; antecedent rainfall; terrain slope; thickness, permeability and hydraulic diffusivity of the tephra deposit; etc. Quantifying these complex interrelationships (and their uncertainties), in a tractable manner, requires a structured but flexible probabilistic approach. A Bayesian Belief Network (BBN) is a directed acyclic graph that allows the representation of the joint probability distribution for a set of uncertain variables in a compact and efficient way, by exploiting unconditional and conditional independences between these variables. Once constructed and parametrized, the BBN uses Bayesian inference to perform causal (e.g. forecast) and/or evidential reasoning (e.g. explanation) about query variables, given some evidence. In this work, we illustrate how BBNs can be used to model the influence of several variables on the generation of rain-triggered lahars

Comparing the treatment of uncertainty in Bayesian networks and fuzzy expert systems used for a human reliability analysis application

International Nuclear Information System (INIS)

Baraldi, Piero; Podofillini, Luca; Mkrtchyan, Lusine; Zio, Enrico; Dang, Vinh N.

2015-01-01

The use of expert systems can be helpful to improve the transparency and repeatability of assessments in areas of risk analysis with limited data available. In this field, human reliability analysis (HRA) is no exception, and, in particular, dependence analysis is an HRA task strongly based on analyst judgement. The analysis of dependence among Human Failure Events refers to the assessment of the effect of an earlier human failure on the probability of the subsequent ones. This paper analyses and compares two expert systems, based on Bayesian Belief Networks and Fuzzy Logic (a Fuzzy Expert System, FES), respectively. The comparison shows that a BBN approach should be preferred in all the cases characterized by quantifiable uncertainty in the input (i.e. when probability distributions can be assigned to describe the input parameters uncertainty), since it provides a satisfactory representation of the uncertainty and its output is directly interpretable for use within PSA. On the other hand, in cases characterized by very limited knowledge, an analyst may feel constrained by the probabilistic framework, which requires assigning probability distributions for describing uncertainty. In these cases, the FES seems to lead to a more transparent representation of the input and output uncertainty. - Highlights: • We analyse treatment of uncertainty in two expert systems. • We compare a Bayesian Belief Network (BBN) and a Fuzzy Expert System (FES). • We focus on the input assessment, inference engines and output assessment. • We focus on an application problem of interest for human reliability analysis. • We emphasize the application rather than math to reach non-BBN or FES specialists

Understanding Migration as an Adaptation in Deltas Using a Bayesian Network Model

Science.gov (United States)

Lázár, A. N.; Adams, H.; de Campos, R. S.; Mortreux, C. C.; Clarke, D.; Nicholls, R. J.; Amisigo, B. A.

2016-12-01

Deltas are hotspots of high population density, fertile lands and dramatic environmental and anthropogenic pressures and changes. Amongst other environmental factors, sea level rise, soil salinization, water shortages and erosion threaten people's livelihoods and wellbeing. As a result, there is a growing concern that significant environmental change induced migration might occur from these areas. Migration, however, is already happening for economic, education and other reasons (e.g. livelihood change, marriage, planned relocation, etc.). Migration hence has multiple, interlinked drivers and depending on the perspective, can be considered as a positive or negative phenomenon. The DECCMA project (Deltas, Vulnerability & Climate Change: Migration & Adaptation) studies migration as part of a suite of adaptation options available to the coastal populations in the Ganges delta in Bangladesh, the Mahanadi delta in India and the Volta delta in Ghana. It aims to develop a holistic framework of analysis that assesses the impact of climate and environmental change on the migration patterns of these areas. This assessment framework will couple environmental, socio-economics and governance dimensions in an attempt to synthesise drivers and barriers and allow testing of plausible future scenarios. One of the integrative methods of DECCMA is a Bayesian Belief Network (BBN) model describing the decision-making of a coastal household. BBN models are built on qualitative and quantitative observations/expert knowledge and describe the probability of different events/responses etc. BBN models are especially useful to capture uncertainties of large systems and engaging with stakeholders. The DECCMA BBN model is based on household survey results from delta migrant sending areas. This presentation will describe model elements (livelihood sensitivity to climate change, local and national adaptation options, household characteristics/attitude, social networks, household decision) and

Application of Bayesian Belief networks to the human reliability analysis of an oil tanker operation focusing on collision accidents

International Nuclear Information System (INIS)

Martins, Marcelo Ramos; Maturana, Marcos Coelho

2013-01-01

During the last three decades, several techniques have been developed for the quantitative study of human reliability. In the 1980s, techniques were developed to model systems by means of binary trees, which did not allow for the representation of the context in which human actions occur. Thus, these techniques cannot model the representation of individuals, their interrelationships, and the dynamics of a system. These issues make the improvement of methods for Human Reliability Analysis (HRA) a pressing need. To eliminate or at least attenuate these limitations, some authors have proposed modeling systems using Bayesian Belief Networks (BBNs). The application of these tools is expected to address many of the deficiencies in current approaches to modeling human actions with binary trees. This paper presents a methodology based on BBN for analyzing human reliability and applies this method to the operation of an oil tanker, focusing on the risk of collision accidents. The obtained model was used to determine the most likely sequence of hazardous events and thus isolate critical activities in the operation of the ship to study Internal Factors (IFs), Skills, and Management and Organizational Factors (MOFs) that should receive more attention for risk reduction.

Some nuclear physics aspects of BBN

Science.gov (United States)

Coc, Alain

2017-09-01

Primordial or big bang nucleosynthesis (BBN) is now a parameter free theory whose predictions are in good overall agreement with observations. However, the 7 Li calculated abundance is significantly higher than the one deduced from spectroscopic observations. Nuclear physics solutions to this lithium problem have been investigated by experimental means. Other solutions which were considered involve exotic sources of extra neutrons which inevitably leads to an increase of the deuterium abundance, but this seems now excluded by recent deuterium observations.

Implementing particle-in-cell plasma simulation code on the BBN TC2000

International Nuclear Information System (INIS)

Sturtevant, J.E.; Maccabe, A.B.

1990-01-01

The BBN TC2000 is a multiple instruction, multiple data (MIMD) machine that combines a physically distributed memory with a logically shared memory programming environment using the unique Butterfly switch. Particle-In-Cell (PIC) plasma simulations model the interaction of charged particles with electric and magnetic fields. This paper describes the implementation of both a 1-D electrostatic and a 2 1/2-D electromagnetic PIC (particle-in-cell) plasma simulation code on a BBN TC2000. Performance is compared to implementations of the same code on the shared memory Sequent Balance and distributed memory Intel iPSC hypercube

BBN: Description of the PLUM System as Used for MUC-4

National Research Council Canada - National Science Library

Ayuso, Damaris; Boisen, Sean; Fox, Heidi; Gish, Herb; Ingria, Robert; Weischedel, Ralph

1992-01-01

.... In contrast, BBN's PLUM system (Probabilistic Language Understanding Model) was developed as part of a DARPA-funded research effort on integrating probabilistic language models with more traditional linguistic techniques...

The BBN (Bolt Beranek and Newman) Knowledge Acquisition Project. Phase 1. Functional Description; Test Plan.

Science.gov (United States)

1987-05-01

Computers . " Symbolics. Inc. 8. Carnegie Group. Inc KnoiledgeCraft Carnegie Group, Inc.. 1985. .- 9. Moser, Margaret, An Overviev of NIKL. Section of BBN...ORGANIZATION NAME AND ADDRESS I0. PROGRAM ELEMENT. PROJECT. TASK BBN Laboratories Inc. AREAAWoRIUNTNUMER_ 10 Moulton St. Cambridge, MA 02238 It...knowledge representation, expert systems; strategic computing , . A 20 ABSTRACT (Contnue an r rerse ide If neceaesary and Identify by block number) This

Gender differences in collaborative learning over online social networks: Epistemological beliefs and behaviors

Directory of Open Access Journals (Sweden)

Rosanna Y.-Y. Chan

2013-09-01

Full Text Available Online social networks are popular venues for computer-supported collaborative work and computer-supported collaborative learning. Professionals within the same discipline, such as software developers, often interact over various social network sites for knowledge updates and collective understandings. The current study aims at gathering empirical evidences concerning gender differences in online social network beliefs and behaviors. A total of 53 engineering postgraduate students were engaged in a blogging community for collaborative learning. Participants’ beliefs about collaboration and nature of knowledge and knowing (i.e. epistemological beliefs are investigated. More specifically, social network analysis metrics including in-degree, out-degree, closeness centrality, and betweenness centrality are obtained from an 8-interval longitudinal SNA. Methodologically speaking, the current work puts forward mixed methods of longitudinal SNA and quantitative beliefs survey to explore online social network participants’ beliefs and behaviors. The study’s findings demonstrate significant gender differences in collaborative learning through online social networks, including (1 female engineering postgraduate students engage significantly more actively in online communications, (2 male engineering postgraduate students are more likely to be the potential controllers of information flows, and (3 gender differences exist in belief gains related to social aspects, but not individual's epistemic aspects. Overall, participants in both genders demonstrated enhanced beliefs in collaboration as well as the nature of knowledge and knowing.

Deep Belief Networks for dimensionality reduction

NARCIS (Netherlands)

Noulas, A.K.; Kröse, B.J.A.

2008-01-01

Deep Belief Networks are probabilistic generative models which are composed by multiple layers of latent stochastic variables. The top two layers have symmetric undirected connections, while the lower layers receive directed top-down connections from the layer above. The current state-of-the-art

Fuzzy knowledge base construction through belief networks based on Lukasiewicz logic

Science.gov (United States)

Lara-Rosano, Felipe

1992-01-01

In this paper, a procedure is proposed to build a fuzzy knowledge base founded on fuzzy belief networks and Lukasiewicz logic. Fuzzy procedures are developed to do the following: to assess the belief values of a consequent, in terms of the belief values of its logical antecedents and the belief value of the corresponding logical function; and to update belief values when new evidence is available.

Experimental challenge to the big-bang nucleosynthesis - Cosmological 7Li problem in BBN

Science.gov (United States)

Kubono, S.; Kawabata, T.; Hou, S. Q.; He, J. J.

2018-04-01

The primordial nucleosynthesis(BBN) right after the big bang (BB) is one of the key elements that basically support the BB model. The BBN is well known that it produced primarily light elements, and explains reasonably most of the elemental abundances. However, there remains an interesting and serious question. That is so called the cosmological 7Li problem in BBN. The BBN simulations using nuclear data together with the recent detailed micro-wave background measurements explain most of the light elements including D, 4He, etc, but the 7Li abundance is over predicted roughly by a factor of three. Although this problem should be investigated in all the fields relevant including physics and astronomical observations, I will concentrate my discussion on the nuclear physics side, especially the recent progress for studying the last possible major destruction process of 7Be, the 7Be(n,α)4He reaction, which would reduce the overproduction if the cross section is large. There are several efforts recently made for the 7Be(n,α)4He reaction in the world. A new theoretical estimate was made compiling all available data of the mirror reaction 7Li(p,α)4He, suggesting about one order smaller reaction rate than the ones currently being used (Wagoner rate). The n-TOF group measured some part of the s-wave components of the reaction, suggesting that the s-wave contributions are much smaller than the Wagoner rate. The p-wave component was measured clearly at RCNP, Osaka using the time-reverse reaction 4He(α,n)7Be, indicating that the p-wave contribution dominates at the effective temperature region for the BBN. However, the sum of the s-wave and p-wave contributions is about one order of magnitude smaller than the Wagoner rate. It should be of great interest to confirm by the indirect method, Trojan-Horse method to deduce cross sections at the effective temperature region, and also see the cross sections for a wider energy range systematically, which is under way by the BELICOS

Generating prior probabilities for classifiers of brain tumours using belief networks

Directory of Open Access Journals (Sweden)

Arvanitis Theodoros N

2007-09-01

Full Text Available Abstract Background Numerous methods for classifying brain tumours based on magnetic resonance spectra and imaging have been presented in the last 15 years. Generally, these methods use supervised machine learning to develop a classifier from a database of cases for which the diagnosis is already known. However, little has been published on developing classifiers based on mixed modalities, e.g. combining imaging information with spectroscopy. In this work a method of generating probabilities of tumour class from anatomical location is presented. Methods The method of "belief networks" is introduced as a means of generating probabilities that a tumour is any given type. The belief networks are constructed using a database of paediatric tumour cases consisting of data collected over five decades; the problems associated with using this data are discussed. To verify the usefulness of the networks, an application of the method is presented in which prior probabilities were generated and combined with a classification of tumours based solely on MRS data. Results Belief networks were constructed from a database of over 1300 cases. These can be used to generate a probability that a tumour is any given type. Networks are presented for astrocytoma grades I and II, astrocytoma grades III and IV, ependymoma, pineoblastoma, primitive neuroectodermal tumour (PNET, germinoma, medulloblastoma, craniopharyngioma and a group representing rare tumours, "other". Using the network to generate prior probabilities for classification improves the accuracy when compared with generating prior probabilities based on class prevalence. Conclusion Bayesian belief networks are a simple way of using discrete clinical information to generate probabilities usable in classification. The belief network method can be robust to incomplete datasets. Inclusion of a priori knowledge is an effective way of improving classification of brain tumours by non-invasive methods.

The DARPA quantum network

International Nuclear Information System (INIS)

Elliot, B.

2005-01-01

Full text: The DARPA quantum network is now in initial operational, with six nodes performing quantum cryptography 24x7 across the Boston metro area between our campuses at Harvard University, Boston University, and BBN Technologies. In this talk, we present our recent activities, including the deployment of this network, building our Mark 1 Entangled QKD system, porting BBN QKD protocol software to NIST and Qinetiq freespace systems, performing initial design of a superconducting single photon detector with U. Rochester and NIST Boulder, and implementing a novel Low-Density Parity Check (LDPC) protocol for QKD. (author)

Bayesian Belief Networks Approach for Modeling Irrigation Behavior

Science.gov (United States)

Andriyas, S.; McKee, M.

2012-12-01

Canal operators need information to manage water deliveries to irrigators. Short-term irrigation demand forecasts can potentially valuable information for a canal operator who must manage an on-demand system. Such forecasts could be generated by using information about the decision-making processes of irrigators. Bayesian models of irrigation behavior can provide insight into the likely criteria which farmers use to make irrigation decisions. This paper develops a Bayesian belief network (BBN) to learn irrigation decision-making behavior of farmers and utilizes the resulting model to make forecasts of future irrigation decisions based on factor interaction and posterior probabilities. Models for studying irrigation behavior have been rarely explored in the past. The model discussed here was built from a combination of data about biotic, climatic, and edaphic conditions under which observed irrigation decisions were made. The paper includes a case study using data collected from the Canal B region of the Sevier River, near Delta, Utah. Alfalfa, barley and corn are the main crops of the location. The model has been tested with a portion of the data to affirm the model predictive capabilities. Irrigation rules were deduced in the process of learning and verified in the testing phase. It was found that most of the farmers used consistent rules throughout all years and across different types of crops. Soil moisture stress, which indicates the level of water available to the plant in the soil profile, was found to be one of the most significant likely driving forces for irrigation. Irrigations appeared to be triggered by a farmer's perception of soil stress, or by a perception of combined factors such as information about a neighbor irrigating or an apparent preference to irrigate on a weekend. Soil stress resulted in irrigation probabilities of 94.4% for alfalfa. With additional factors like weekend and irrigating when a neighbor irrigates, alfalfa irrigation

Peer beliefs and smoking in adolescence: a longitudinal social network analysis.

Science.gov (United States)

Ragan, Daniel T

2016-03-01

Peer smoking is one of the strongest predictors of adolescent cigarette use, but less is known about whether other peer characteristics also contribute to this behavior. This study examined the links between adolescent cigarette use and peer beliefs about smoking. It tested whether peer beliefs about smoking are associated with changes in cigarette use, whether this association is a result of changes in individual beliefs about smoking, and how beliefs inform friendship choices. Analyses drew on data collected from 29 school-based networks, each measured at five occasions as students moved from 6th through 9th grade, as part of the study of the PROSPER partnership model. Longitudinal social network models provided estimates of friendship selection and behavior for an average of 6,200 students at each measurement point and more than 9,000 students overall. Peer beliefs about smoking influenced cigarette use both directly and through their impact on individual beliefs. Respondents tended to name friends whose beliefs about smoking were similar to their own, and the likelihood of being named as a friend was higher for those who reported more positive beliefs about smoking. The results from this study suggest that peer beliefs about smoking, in addition to peer cigarette use itself, are associated with adolescent smoking through several mechanisms. Because beliefs favorable to cigarette use are present before adolescents actually smoke, these results underscore the importance of implementing smoking prevention programs in early adolescence.

Using Bayesian Belief Networks and event trees for volcanic hazard assessment and decision support : reconstruction of past eruptions of La Soufrière volcano, Guadeloupe and retrospective analysis of 1975-77 unrest.

Science.gov (United States)

Komorowski, Jean-Christophe; Hincks, Thea; Sparks, Steve; Aspinall, Willy; Legendre, Yoann; Boudon, Georges

2013-04-01

Since 1992, mild but persistent seismic and fumarolic unrest at La Soufrière de Guadeloupe volcano has prompted renewed concern about hazards and risks, crisis response planning, and has rejuvenated interest in geological studies. Scientists monitoring active volcanoes frequently have to provide science-based decision support to civil authorities during such periods of unrest. In these circumstances, the Bayesian Belief Network (BBN) offers a formalized evidence analysis tool for making inferences about the state of the volcano from different strands of data, allowing associated uncertainties to be treated in a rational and auditable manner, to the extent warranted by the strength of the evidence. To illustrate the principles of the BBN approach, a retrospective analysis is undertaken of the 1975-77 crisis, providing an inferential assessment of the evolving state of the magmatic system and the probability of subsequent eruption. Conditional dependencies and parameters in the BBN are characterized quantitatively by structured expert elicitation. Revisiting data available in 1976 suggests the probability of magmatic intrusion would have been evaluated high at the time, according with subsequent thinking about the volcanological nature of the episode. The corresponding probability of a magmatic eruption therefore would have been elevated in July and August 1976; however, collective uncertainty about the future course of the crisis was great at the time, even if some individual opinions were certain. From this BBN analysis, while the more likely appraised outcome - based on observational trends at 31 August 1976 - might have been 'no eruption' (mean probability 0.5; 5-95 percentile range 0.8), an imminent magmatic eruption (or blast) could have had a probability of about 0.4, almost as substantial. Thus, there was no real scientific basis to assert one scenario was more likely than the other. This retrospective evaluation adds objective probabilistic expression to

Decision scenario analysis for addressing sediment accumulation in Lago Lucchetti, Puerto Rico

Science.gov (United States)

A Bayesian belief network (BBN) was used to characterize the effects of sediment accumulation on water storage capacity of a reservoir (Lago Lucchetti) in southwest Puerto Rico and the potential of different management options to increase reservoir life expectancy. Water and sedi...

The cosmic 6Li and 7Li problems and BBN with long-lived charged massive particles

International Nuclear Information System (INIS)

Karsten, Jedamzik

2007-01-01

Charged massive particles (CHAMPs), when present during the Big Bang nucleosynthesis (BBN) era, may significantly alter the synthesis of light elements when compared to a standard BBN scenario. This is due to the formation of bound states with nuclei. This paper presents a detailed numerical and analytical analysis of such CHAMP BBN. All reactions important for predicting light-element yields are calculated within the Born approximation. Three prior neglected effects are treated in detail: (a) photo destruction of bound states due to electromagnetic cascades induced by the CHAMP decay, (b) late-time efficient destruction/production of H 2 , Li 6 , and Li 7 due to reactions on charge Z = 1 nuclei bound to CHAMPs, and (c) CHAMP exchange between nuclei. Each of these effects may induce orders-of-magnitude changes in the final abundance yields. The study focusses on the impact of CHAMPs on a possible simultaneous solution of the Li 6 and Li 7 problems. It is shown that a prior suggested simultaneous solution of the Li 6 and Li 7 problems for a relic decaying at τ x ∼ 1000 s is only very weakly dependent on the relic being neutral or charged, unless its hadronic branching ratio is B h -4 very small. By use of a Monte-Carlo analysis it is shown that within CHAMP BBN the existence of further parameter space for a simultaneous solution of the Li 6 and Li 7 problem for long decay times τ x ≥ 10 6 s seems possible but fairly unlikely. (author)

A method for risk-informed safety significance categorization using the analytic hierarchy process and bayesian belief networks

International Nuclear Information System (INIS)

Ha, Jun Su; Seong, Poong Hyun

2004-01-01

A risk-informed safety significance categorization (RISSC) is to categorize structures, systems, or components (SSCs) of a nuclear power plant (NPP) into two or more groups, according to their safety significance using both probabilistic and deterministic insights. In the conventional methods for the RISSC, the SSCs are quantitatively categorized according to their importance measures for the initial categorization. The final decisions (categorizations) of SSCs, however, are qualitatively made by an expert panel through discussions and adjustments of opinions by using the probabilistic insights compiled in the initial categorization process and combining the probabilistic insights with the deterministic insights. Therefore, owing to the qualitative and linear decision-making process, the conventional methods have the demerits as follows: (1) they are very costly in terms of time and labor, (2) it is not easy to reach the final decision, when the opinions of the experts are in conflict and (3) they have an overlapping process due to the linear paradigm (the categorization is performed twice - first, by the engineers who propose the method, and second, by the expert panel). In this work, a method for RISSC using the analytic hierarchy process (AHP) and bayesian belief networks (BBN) is proposed to overcome the demerits of the conventional methods and to effectively arrive at a final decision (or categorization). By using the AHP and BBN, the expert panel takes part in the early stage of the categorization (that is, the quantification process) and the safety significance based on both probabilistic and deterministic insights is quantified. According to that safety significance, SSCs are quantitatively categorized into three categories such as high safety significant category (Hi), potentially safety significant category (Po), or low safety significant category (Lo). The proposed method was applied to the components such as CC-V073, CV-V530, and SI-V644 in Ulchin Unit

Hypothesis Management Framework: a exible design pattern for belief networks in decision support systems

NARCIS (Netherlands)

Gosliga, S.P. van; Voorde, I. van de

2008-01-01

This article discusses a design pattern for building belief networks for application domains in which causal models are hard to construct. In this approach we pursue a modular belief network structure that is easily extended by the users themselves, while remaining reliable for decision support. The

Development of a Bayesian model to estimate health care outcomes in the severely wounded

Directory of Open Access Journals (Sweden)

Alexander Stojadinovic

2010-08-01

Full Text Available Alexander Stojadinovic1, John Eberhardt2, Trevor S Brown3, Jason S Hawksworth4, Frederick Gage3, Douglas K Tadaki3, Jonathan A Forsberg5, Thomas A Davis3, Benjamin K Potter5, James R Dunne6, E A Elster31Combat Wound Initiative Program, 4Department of Surgery, Walter Reed Army Medical Center, Washington, DC, USA; 2DecisionQ Corporation, Washington, DC, USA; 3Regenerative Medicine Department, Combat Casualty Care, Naval Medical Research Center, Silver Spring, MD, USA; 5Integrated Department of Orthopaedics and Rehabilitation, 6Department of Surgery, National Naval Medical Center, Bethesda, MD, USABackground: Graphical probabilistic models have the ability to provide insights as to how clinical factors are conditionally related. These models can be used to help us understand factors influencing health care outcomes and resource utilization, and to estimate morbidity and clinical outcomes in trauma patient populations.Study design: Thirty-two combat casualties with severe extremity injuries enrolled in a prospective observational study were analyzed using step-wise machine-learned Bayesian belief network (BBN and step-wise logistic regression (LR. Models were evaluated using 10-fold cross-validation to calculate area-under-the-curve (AUC from receiver operating characteristics (ROC curves.Results: Our BBN showed important associations between various factors in our data set that could not be developed using standard regression methods. Cross-validated ROC curve analysis showed that our BBN model was a robust representation of our data domain and that LR models trained on these findings were also robust: hospital-acquired infection (AUC: LR, 0.81; BBN, 0.79, intensive care unit length of stay (AUC: LR, 0.97; BBN, 0.81, and wound healing (AUC: LR, 0.91; BBN, 0.72 showed strong AUC.Conclusions: A BBN model can effectively represent clinical outcomes and biomarkers in patients hospitalized after severe wounding, and is confirmed by 10-fold �

Up-conversion emission of Er{sup 3+}/Yb{sup 3+}co-doped BaBi{sub 2}Nb{sub 2}O{sub 9} (BBN) phosphors

Energy Technology Data Exchange (ETDEWEB)

Façanha, M.X., E-mail: marcello.facanha@uece.br [Departamento de Química, Centro de Ciências, Universidade Federal do Ceará (UFC), Fortaleza, Ceará (Brazil); Faculdade de Educação de Crateús (FAEC), Universidade Estadual do Ceará (UECE), Fortaleza, Ceará (Brazil); Laboratório de Telecomunicações e Ciências e Engenharia de Materiais (LOCEM), Universidade Federal do Ceará (UFC), Fortaleza, Ceará (Brazil); Nascimento, J.P.C. do [Departamento de Química, Centro de Ciências, Universidade Federal do Ceará (UFC), Fortaleza, Ceará (Brazil); Laboratório de Telecomunicações e Ciências e Engenharia de Materiais (LOCEM), Universidade Federal do Ceará (UFC), Fortaleza, Ceará (Brazil); Silva, M.A.S., E-mail: marceloassilva@yahoo.com.br [Laboratório de Telecomunicações e Ciências e Engenharia de Materiais (LOCEM), Universidade Federal do Ceará (UFC), Fortaleza, Ceará (Brazil); and others

2017-03-15

On this paper, polycrystalline samples of the tetragonal systems BaBi{sub 2}Nb{sub 2}O{sub 9} (BBN) and BBN co-doped with Er{sup 3+}/Yb{sup 3+} (BBN: 0.04Er{sup 3+}yYb{sup 3+}, where y=0.02, 0.04, 0.06 and 0.08 mol%) were synthesized by the solid state method. The crystalline structure and photoluminescent properties of the ceramic phosphors were investigated by powder X-ray diffraction (PXRD), Raman spectroscopy and spectral analysis of up-conversion (UC) emission. The results reveal that all compositions crystallize in the I4/mmm space group at room temperature, and show UC green emissions (centered at 525 nm and 550 nm) and red (around 660 nm) coming from ({sup 2}H{sub 11/2}, {sup 4}S{sub 3/2}→{sup 4}I{sub 15/2}) and ({sup 4}F{sub 9/2}→{sup 4}I{sub 15/2}) transitions, respectively, under excitation at 980 nm. Increasing variations of the Yb{sup 3+} sensitizer concentration in the host BBN, lead to a significant intensity increase in both UC emissions due to the efficiency of the energy-transfer process. The BBN: 0.04 mol%Er{sup 3+}0.08 mol%Yb{sup 3+} composition showed the higher intensity bands, thus establishing the BBN as an alternative host material for luminescent centers.

Sentimen Analisis Tweet Berbahasa Indonesia Dengan Deep Belief Network

Directory of Open Access Journals (Sweden)

Ira zulfa

2017-07-01

Full Text Available Sentiment analysis is a computational research of opinion sentiment and emotion which is expressed in textual mode. Twitter becomes the most popular communication device among internet users. Deep Learning is a new area of machine learning research. It aims to move machine learning closer to its main goal, artificial intelligence. The purpose of deep learning is to change the manual of engineering with learning. At its growth, deep learning has algorithms arrangement that focus on non-linear data representation. One of the machine learning methods is Deep Belief Network (DBN. Deep Belief Network (DBN, which is included in Deep Learning method, is a stack of several algorithms with some extraction features that optimally utilize all resources. This study has two points. First, it aims to classify positive, negative, and neutral sentiments towards the test data. Second, it determines the classification model accuracy by using Deep Belief Network method so it would be able to be applied into the tweet classification, to highlight the sentiment class of training data tweet in Bahasa Indonesia. Based on the experimental result, it can be concluded that the best method in managing tweet data is the DBN method with an accuracy of 93.31%, compared with  Naive Bayes method which has an accuracy of 79.10%, and SVM (Support Vector Machine method with an accuracy of 92.18%.

A Belief-Space Approach to Integrated Intelligence - Research Area 10.3: Intelligent Networks

Science.gov (United States)

2017-12-05

A Belief-Space Approach to Integrated Intelligence- Research Area 10.3: Intelligent Networks The views, opinions and/or findings contained in this...Technology (MIT) Title: A Belief-Space Approach to Integrated Intelligence- Research Area 10.3: Intelligent Networks Report Term: 0-Other Email: tlp...students presented progress and received feedback from the research group . o wrote papers on their research and submitted them to leading conferences

Maritime Transportation Risk Assessment of Tianjin Port with Bayesian Belief Networks.

Science.gov (United States)

Zhang, Jinfen; Teixeira, Ângelo P; Guedes Soares, C; Yan, Xinping; Liu, Kezhong

2016-06-01

This article develops a Bayesian belief network model for the prediction of accident consequences in the Tianjin port. The study starts with a statistical analysis of historical accident data of six years from 2008 to 2013. Then a Bayesian belief network is constructed to express the dependencies between the indicator variables and accident consequences. The statistics and expert knowledge are synthesized in the Bayesian belief network model to obtain the probability distribution of the consequences. By a sensitivity analysis, several indicator variables that have influence on the consequences are identified, including navigational area, ship type and time of the day. The results indicate that the consequences are most sensitive to the position where the accidents occurred, followed by time of day and ship length. The results also reflect that the navigational risk of the Tianjin port is at the acceptable level, despite that there is more room of improvement. These results can be used by the Maritime Safety Administration to take effective measures to enhance maritime safety in the Tianjin port. © 2016 Society for Risk Analysis.

Dynamical 3-Space Predicts Hotter Early Universe: Resolves CMB-BBN 7-Li and 4-He Abundance Anomalies

Directory of Open Access Journals (Sweden)

Cahill R. T.

2010-01-01

Full Text Available The observed abundances of 7-Li and 4-He are significantly inconsistent with the predictions from Big Bang Nucleosynthesis (BBN when using the $Lambda$CDM cosmological model together with the value for $Omega_B h^2 = 0.0224pm0.0009$ from WMAP CMB fluctuations, with the value from BBN required to fit observed abundances being $0.009 < Omega_B h^2 < 0.013$. The dynamical 3-space theory is shown to predict a 20% hotter universe in the radiation-dominated epoch, which then results in a remarkable parameter-free agreement between the BBN and the WMAP value for $Omega_B h^2$. The dynamical 3-space also gives a parameter-free fit to the supernova redshift data, and predicts that the flawed $Lambda$CDM model would require $Omega_Lambda = 0.73$ and $Omega_M = 0.27$ to fit the 3-space dynamics Hubble expansion, and independently of the supernova data. These results amount to the discovery of new physics for the early universe that is matched by numerous other successful observational and experimental tests.

Dynamical 3-Space Predicts Hotter Early Universe: Resolves CMB-BBN 7-Li and 4-He Abundance Anomalies

Directory of Open Access Journals (Sweden)

Cahill R. T.

2010-01-01

Full Text Available The observed abundances of 7 Li and 4 He are significantly inconsistent with the pre- dictions from Big Bang Nucleosynthesis (BBN when using the CDM cosmolog- ical model together with the value for B h 2 = 0 : 0224 0 : 0009 from WMAP CMB fluctuations, with the value from BBN required to fit observed abundances being 0 : 009 < B h 2 < 0 : 013. The dynamical 3-space theory is shown to predict a 20% hot- ter universe in the radiation-dominated epoch, which then results in a remarkable parameter-free agreement between the BBN and the WMAP value for B h 2 . The dy- namical 3-space also gives a parameter-free fit to the supernova redshift data, and pre- dicts that the flawed CDM model would require = 0 : 73 and M = 0 : 27 to fit the 3-space dynamics Hubble expansion, and independently of the supernova data. These results amount to the discovery of new physics for the early universe that is matched by numerous other successful observational and experimental tests.

Single and combined fault diagnosis of reciprocating compressor valves using a hybrid deep belief network

NARCIS (Netherlands)

Tran, Van Tung; Thobiani, Faisal Al; Tinga, Tiedo; Ball, Andrew David; Niu, Gang

2017-01-01

In this paper, a hybrid deep belief network is proposed to diagnose single and combined faults of suction and discharge valves in a reciprocating compressor. This hybrid integrates the deep belief network structured by multiple stacked restricted Boltzmann machines for pre-training and simplified

A Bayesian belief nets based quantitative software reliability assessment for PSA: COTS case study

International Nuclear Information System (INIS)

Eom, H. S.; Sung, T. Y.; Jeong, H. S.; Park, J. H.; Kang, H. G.; Lee, K. Y.; Park, J. K

2002-03-01

Current reliability assessments of safety critical software embedded in the digital systems in nuclear power plants are based on the rule-based qualitative assessment methods. Then recently practical needs require the quantitative features of software reliability for Probabilistic Safety Assessment (PSA) that is one of important methods being used in assessing the whole safety of nuclear power plant. But conventional quantitative software reliability assessment methods are not enough to get the necessary results in assessing the safety critical software used in nuclear power plants. Thus, current reliability assessment methods for these digital systems exclude the software part or use arbitrary values for the software reliability in the assessment. This reports discusses a Bayesian Belief Nets (BBN) based quantification method that models current qualitative software assessment in formal way and produces quantitative results required for PSA. Commercial Off-The-Shelf (COTS) software dedication process that KAERI developed was applied to the discussed BBN based method for evaluating the plausibility of the proposed method in PSA

Strategic Belief Management

DEFF Research Database (Denmark)

Foss, Nicolai Juul

While (managerial) beliefs are central to many aspects of strategic organization, interactive beliefs are almost entirely neglected, save for some game theory treatments. In an increasingly connected and networked economy, firms confront coordination problems that arise because of network effects....... The capability to manage beliefs will increasingly be a strategic one, a key source of wealth creation, and a key research area for strategic organization scholars.......While (managerial) beliefs are central to many aspects of strategic organization, interactive beliefs are almost entirely neglected, save for some game theory treatments. In an increasingly connected and networked economy, firms confront coordination problems that arise because of network effects...

Visible technologies, invisible organisations: An empirical study of public beliefs about electricity supply networks

International Nuclear Information System (INIS)

Devine-Wright, Patrick; Devine-Wright, Hannah; Sherry-Brennan, Fionnguala

2010-01-01

Reducing carbon emissions in the energy system poses significant challenges to electricity transmission and distribution networks. Whilst these challenges are as much social as economic or technical, to date few research studies have investigated public beliefs about electricity supply networks. This research aimed to address this gap by means of a nationally representative study of UK adults (n=1041), probing beliefs about how electricity reaches the home, responsibility for electricity supply, associations with the words 'National Grid', as well as beliefs about the planning of new infrastructure. Findings suggest that electricity networks are represented predominantly in terms of technologies rather than organisations, specifically in terms of familiar, visible components such as cables or wires, rather than more systemic concepts such as networks. Transmission and distribution network operators were largely invisible to members of the public. In terms of planning new lines, most respondents assumed that government ministers were involved in decision-making, while local residents were widely perceived to have little influence; moreover, there was strong public support for placing new power lines underground, regardless of the cost. In conclusion, organisational invisibility, coupled with low expectations of participatory involvement, could provoke public opposition and delay siting new network infrastructure.

Dual integrin and gastrin-releasing peptide receptor targeted tumor imaging using 18F-labeled PEGylated RGD-bombesin heterodimer 18F-FB-PEG3-Glu-RGD-BBN.

Science.gov (United States)

Liu, Zhaofei; Yan, Yongjun; Chin, Frederic T; Wang, Fan; Chen, Xiaoyuan

2009-01-22

Radiolabeled RGD and bombesin peptides have been extensively investigated for tumor integrin alpha(v)beta(3) and GRPR imaging, respectively. Due to the fact that many tumors are both integrin and GRPR positive, we designed and synthesized a heterodimeric peptide Glu-RGD-BBN, which is expected to be advantageous over the monomeric peptides for dual-receptor targeting. A PEG(3) spacer was attached to the glutamate alpha-amino group of Glu-RGD-BBN to enhance the (18)F labeling yield and to improve the in vivo kinetics. PEG(3)-Glu-RGD-BBN possesses the comparable GRPR and integrin alpha(v)beta(3) receptor-binding affinities as the corresponding monomers, respectively. The dual-receptor targeting properties of (18)F-FB-PEG(3)-Glu-RGD-BBN were observed in PC-3 tumor model. (18)F-FB-PEG(3)-Glu-RGD-BBN with high tumor contrast and favorable pharmacokinetics is a promising PET tracer for dual integrin and GRPR positive tumor imaging. This heterodimer strategy may also be an applicable method to develop other molecules with improved in vitro and in vivo characterizations for tumor diagnosis and therapy.

Deep Belief Networks for Electroencephalography: A Review of Recent Contributions and Future Outlooks.

Science.gov (United States)

Movahedi, Faezeh; Coyle, James L; Sejdic, Ervin

2018-05-01

Deep learning, a relatively new branch of machine learning, has been investigated for use in a variety of biomedical applications. Deep learning algorithms have been used to analyze different physiological signals and gain a better understanding of human physiology for automated diagnosis of abnormal conditions. In this paper, we provide an overview of deep learning approaches with a focus on deep belief networks in electroencephalography applications. We investigate the state-of-the-art algorithms for deep belief networks and then cover the application of these algorithms and their performances in electroencephalographic applications. We covered various applications of electroencephalography in medicine, including emotion recognition, sleep stage classification, and seizure detection, in order to understand how deep learning algorithms could be modified to better suit the tasks desired. This review is intended to provide researchers with a broad overview of the currently existing deep belief network methodology for electroencephalography signals, as well as to highlight potential challenges for future research.

COmmunications and Networking with QUantum Operationally-Secure Technology for Maritime Deployment (CONQUEST)

Science.gov (United States)

2017-03-06

15 minutes 48 Efficient post -processing for CV QKD Saikat Guha BBN Review Meeting Feb 17, 2017 Communications and Networking with Quantum Operationally...Raytheon BBN Technologies; Dr. Saikat Guha Contractor Address: 10 Moulton Street, Cambridge, MA 02138 Title of the Project: COmmunications and...Equipment Purchased No equipment has been purchased or constructed at this time. Section D. Key Personnel There have been no changes in

Stakeholder perceptions of soil managements in the Canyoles watershed. A Bayesian Belief Network approach

Science.gov (United States)

Burguet Marimón, Maria; Quinn, Claire; Stringer, Lindsay; Cerdà, Artemi

2017-04-01

The fate of the management and use of land is the result of economic, social and political factors (Tengberg et al., 2016). Stakeholder perceptions are relevant in understanding land management (Marques et al., 2015; Teshome et al., 2016) as perceptions can shape behaviours and actions. In the Canyoles River watershed (Eastern Spain), rainfed agriculture has been replaced by traditional irrigation systems at its valley bottom, and by drip irrigation on its slopes. The new irrigation systems in hilly citrus orchards, along with intensive farming, use of herbicides and high fertilization, are causing high erosion and land degradation rates due to the lack of vegetation cover, soil compaction and the loss of organic matter. Bayesian Belief Networks (BBN) are defined as a 'graphical tool for building decision support systems to help make decisions under uncertain conditions' (Cain, 2001). In this work, BBNs were used to incorporate the issues and objectives identified by stakeholders during interviews about their perceptions of different soil management practices in the Canyoles watershed. BBNs are appropriate for the modeling of geospatial data which can contain different kinds of uncertainties due to positional error, feature classification error, resolution, attribute error, data completeness, currency, and logical consistency, and can integrate qualitative and quantitative data. Our stakeholders were farmers, politicians (especially the mayors of the nearby towns), managers, farm employees and technicians. The questions asked to the stakeholders were related to their concern in keeping the farm active and profitable, the changes in the price of the farm products, the price of the fertilizers and tractors and if soil erosion is a key issue in their farms Preliminary results from the interviews performed with the stakeholders suggest that there is still a strong refusal to the use of different cover crops, as well as to the change in the tillage systems. Farmers do

The cosmic {sup 6}Li and {sup 7}Li problems and BBN with long-lived charged massive particles

Energy Technology Data Exchange (ETDEWEB)

Karsten, Jedamzik [Montpellier-2 Univ., Lab. de Physique Mathemathique et Theorique, C.N.R.S., 34 - Montpellier (France)

2007-07-01

Charged massive particles (CHAMPs), when present during the Big Bang nucleosynthesis (BBN) era, may significantly alter the synthesis of light elements when compared to a standard BBN scenario. This is due to the formation of bound states with nuclei. This paper presents a detailed numerical and analytical analysis of such CHAMP BBN. All reactions important for predicting light-element yields are calculated within the Born approximation. Three prior neglected effects are treated in detail: (a) photo destruction of bound states due to electromagnetic cascades induced by the CHAMP decay, (b) late-time efficient destruction/production of H{sup 2}, Li{sup 6}, and Li{sup 7} due to reactions on charge Z = 1 nuclei bound to CHAMPs, and (c) CHAMP exchange between nuclei. Each of these effects may induce orders-of-magnitude changes in the final abundance yields. The study focusses on the impact of CHAMPs on a possible simultaneous solution of the Li{sup 6} and Li{sup 7} problems. It is shown that a prior suggested simultaneous solution of the Li{sup 6} and Li{sup 7} problems for a relic decaying at {tau}{sub x} {approx} 1000 s is only very weakly dependent on the relic being neutral or charged, unless its hadronic branching ratio is B{sub h} << 10{sup -4} very small. By use of a Monte-Carlo analysis it is shown that within CHAMP BBN the existence of further parameter space for a simultaneous solution of the Li{sup 6} and Li{sup 7} problem for long decay times {tau}{sub x} {>=} 10{sup 6} s seems possible but fairly unlikely. (author)

Updated BBN bounds on the cosmological lepton asymmetry for non-zero θ13

International Nuclear Information System (INIS)

Mangano, Gianpiero; Miele, Gennaro; Pastor, Sergio; Pisanti, Ofelia; Sarikas, Srdjan

2012-01-01

We discuss the bounds on the cosmological lepton number from Big Bang Nucleosynthesis (BBN), in light of recent evidences for a large value of the neutrino mixing angle θ 13 , sin 2 θ 13 ≥0.01 at 2σ. The largest asymmetries for electron and μ, τ neutrinos compatible with 4 He and 2 H primordial yields are computed versus the neutrino mass hierarchy and mixing angles. The flavour oscillation dynamics is traced till the beginning of BBN and neutrino distributions after decoupling are numerically computed. The latter contains in general, non-thermal distortion due to the onset of flavour oscillations driven by solar squared mass difference in the temperature range where neutrino scatterings become inefficient to enforce thermodynamical equilibrium. Depending on the value of θ 13 , this translates into a larger value for the effective number of neutrinos, N eff . Upper bounds on this parameter are discussed for both neutrino mass hierarchies. Values for N eff which are large enough to be detectable by the Planck experiment are found only for the (presently disfavoured) range sin 2 θ 13 ≤0.01.

Random Deep Belief Networks for Recognizing Emotions from Speech Signals.

Science.gov (United States)

Wen, Guihua; Li, Huihui; Huang, Jubing; Li, Danyang; Xun, Eryang

2017-01-01

Now the human emotions can be recognized from speech signals using machine learning methods; however, they are challenged by the lower recognition accuracies in real applications due to lack of the rich representation ability. Deep belief networks (DBN) can automatically discover the multiple levels of representations in speech signals. To make full of its advantages, this paper presents an ensemble of random deep belief networks (RDBN) method for speech emotion recognition. It firstly extracts the low level features of the input speech signal and then applies them to construct lots of random subspaces. Each random subspace is then provided for DBN to yield the higher level features as the input of the classifier to output an emotion label. All outputted emotion labels are then fused through the majority voting to decide the final emotion label for the input speech signal. The conducted experimental results on benchmark speech emotion databases show that RDBN has better accuracy than the compared methods for speech emotion recognition.

Random Deep Belief Networks for Recognizing Emotions from Speech Signals

Directory of Open Access Journals (Sweden)

Guihua Wen

2017-01-01

Full Text Available Now the human emotions can be recognized from speech signals using machine learning methods; however, they are challenged by the lower recognition accuracies in real applications due to lack of the rich representation ability. Deep belief networks (DBN can automatically discover the multiple levels of representations in speech signals. To make full of its advantages, this paper presents an ensemble of random deep belief networks (RDBN method for speech emotion recognition. It firstly extracts the low level features of the input speech signal and then applies them to construct lots of random subspaces. Each random subspace is then provided for DBN to yield the higher level features as the input of the classifier to output an emotion label. All outputted emotion labels are then fused through the majority voting to decide the final emotion label for the input speech signal. The conducted experimental results on benchmark speech emotion databases show that RDBN has better accuracy than the compared methods for speech emotion recognition.

Evidence of social network influence on multiple HIV risk behaviors and normative beliefs among young Tanzanian men.

Science.gov (United States)

Mulawa, Marta; Yamanis, Thespina J; Hill, Lauren M; Balvanz, Peter; Kajula, Lusajo J; Maman, Suzanne

2016-03-01

Research on network-level influences on HIV risk behaviors among young men in sub-Saharan Africa is severely lacking. One significant gap in the literature that may provide direction for future research with this population is understanding the degree to which various HIV risk behaviors and normative beliefs cluster within men's social networks. Such research may help us understand which HIV-related norms and behaviors have the greatest potential to be changed through social influence. Additionally, few network-based studies have described the structure of social networks of young men in sub-Saharan Africa. Understanding the structure of men's peer networks may motivate future research examining the ways in which network structures shape the spread of information, adoption of norms, and diffusion of behaviors. We contribute to filling these gaps by using social network analysis and multilevel modeling to describe a unique dataset of mostly young men (n = 1249 men and 242 women) nested within 59 urban social networks in Dar es Salaam, Tanzania. We examine the means, ranges, and clustering of men's HIV-related normative beliefs and behaviors. Networks in this urban setting varied substantially in both composition and structure and a large proportion of men engaged in risky behaviors including inconsistent condom use, sexual partner concurrency, and intimate partner violence perpetration. We found significant clustering of normative beliefs and risk behaviors within these men's social networks. Specifically, network membership explained between 5.78 and 7.17% of variance in men's normative beliefs and between 1.93 and 15.79% of variance in risk behaviors. Our results suggest that social networks are important socialization sites for young men and may influence the adoption of norms and behaviors. We conclude by calling for more research on men's social networks in Sub-Saharan Africa and map out several areas of future inquiry. Copyright © 2016 Elsevier Ltd. All

SELENE - Self-Forming Extensible Lunar EVA Network, Phase I

Data.gov (United States)

National Aeronautics and Space Administration — The overall objective of this research effort (Phase I and Phase II) by Scientific Systems Company, Inc. and BBN Technologies is to develop the SELENE network --...

A belief network approach for development of a nuclear power plant diagnosis system

Energy Technology Data Exchange (ETDEWEB)

Hwang, I K; Kim, J T; Lee, D Y; Jung, C H; Kim, J Y; Lee, J S; Ham, C S [Korea Atomic Energy Research Institute, Taejon (Korea, Republic of)

1999-12-31

Belief network (or Bayesian network) based on Bayes` rule in probabilistic theory can be applied to the reasoning of diagnostic system. This paper describes the basic theory of concept and feasibility of using the network for diagnosis of nuclear power plants. An example shows that the probabilities of root causes of a failure are calculated from the measured or believed evidences. 6 refs., 3 figs. (Author)

A belief network approach for development of a nuclear power plant diagnosis system

Energy Technology Data Exchange (ETDEWEB)

Hwang, I. K.; Kim, J. T.; Lee, D. Y.; Jung, C. H.; Kim, J. Y.; Lee, J. S.; Ham, C. S. [Korea Atomic Energy Research Institute, Taejon (Korea, Republic of)

1998-12-31

Belief network (or Bayesian network) based on Bayes` rule in probabilistic theory can be applied to the reasoning of diagnostic system. This paper describes the basic theory of concept and feasibility of using the network for diagnosis of nuclear power plants. An example shows that the probabilities of root causes of a failure are calculated from the measured or believed evidences. 6 refs., 3 figs. (Author)

Rational Irrationality: Modeling Climate Change Belief Polarization Using Bayesian Networks.

Science.gov (United States)

Cook, John; Lewandowsky, Stephan

2016-01-01

Belief polarization is said to occur when two people respond to the same evidence by updating their beliefs in opposite directions. This response is considered to be "irrational" because it involves contrary updating, a form of belief updating that appears to violate normatively optimal responding, as for example dictated by Bayes' theorem. In light of much evidence that people are capable of normatively optimal behavior, belief polarization presents a puzzling exception. We show that Bayesian networks, or Bayes nets, can simulate rational belief updating. When fit to experimental data, Bayes nets can help identify the factors that contribute to polarization. We present a study into belief updating concerning the reality of climate change in response to information about the scientific consensus on anthropogenic global warming (AGW). The study used representative samples of Australian and U.S. Among Australians, consensus information partially neutralized the influence of worldview, with free-market supporters showing a greater increase in acceptance of human-caused global warming relative to free-market opponents. In contrast, while consensus information overall had a positive effect on perceived consensus among U.S. participants, there was a reduction in perceived consensus and acceptance of human-caused global warming for strong supporters of unregulated free markets. Fitting a Bayes net model to the data indicated that under a Bayesian framework, free-market support is a significant driver of beliefs about climate change and trust in climate scientists. Further, active distrust of climate scientists among a small number of U.S. conservatives drives contrary updating in response to consensus information among this particular group. Copyright © 2016 Cognitive Science Society, Inc.

Approximation Methods for Inference and Learning in Belief Networks: Progress and Future Directions

National Research Council Canada - National Science Library

Pazzan, Michael

1997-01-01

.... In this research project, we have investigated methods and implemented algorithms for efficiently making certain classes of inference in belief networks, and for automatically learning certain...

An exploratory study on 99mTc-RGD-BBN peptide scintimammography in the assessment of breast malignant lesions compared to 99mTc-3P4-RGD2.

Directory of Open Access Journals (Sweden)

Qianqian Chen

Full Text Available This study aimed to explore the diagnostic performance of single photon emission computed tomography / computerized tomography (SPECT/CT using a new radiotracer 99mTc-RGD-BBN for breast malignant tumor compared with 99mTc-3P4-RGD2.6 female patients with breast malignant tumors diagnosed by fine needle aspiration cytology biopsy (FNAB who were scheduled to undergo surgery were included in the study. 99mTc-3P4-RGD2 and 99mTc-RGD-BBN were performed with single photon emission computed tomography (SPECT at 1 hour after intravenous injection of 299 ± 30 MBq and 293 ± 32 MBq of radiotracers respectively at separate day. The results were evaluated by the Tumor to non-Tumor ratios (T/NT. 99mTc-RGD-BBN and 99mTc-3P4-RGD2 SPECT/CT images were interpreted independently by 3 experienced nuclear medicine physicians using a 3-point scale system. All of the samples were analyzed immunohistochemically to evaluate the integrin αvβ3 and gastrin-releasing peptide receptor (GRPR expression. The safety, biodistribution and radiation dosimetry of 99mTc-RGD-BBN were also evaluated in the healthy volunteers.No serious adverse events were reported in any of the patients during the study. The effective radiation dose entirely conformed to the relevant standards. A total of 6 palpable malignant lesions were detected using 99mTc-RGD-BBN SPECT/CT with clear uptake. All malignant lesions were also detected using 99mTc-3P4-RGD2 SPECT/CT. The results showed that five malignant lesions were with clear uptake and the other one with barely an uptake. 4 malignant cases were found with both αvβ3 and GRPR expression, 1 case with only GRPR positive expression (integrin αvβ3 negative and 1 case with only integrin αvβ3 positive expression (GRPR negative.99mTc-RGD-BBN is a safe agent for detecting breast cancer. 99mTc-RGD-BBN may have the potential to make up for the deficiency of 99mTc-3P4-RGD2 in the detection of breast cancer with only GRPR positive expression (integrin �

A guide on the elicitation of expert knowledge in constructing BBN for quantitative reliability assessment of safety critical software

International Nuclear Information System (INIS)

Eom, H. S.; Kang, H. G.; Chang, S. C.; Ha, J. J.

2003-08-01

This report describes the methodology which could elicit probabilistic representation from the experts' knowledge or qualitative data. It is necessary to elicit expert's knowledge while we quantitatively assess the reliability of safety critical software using Bayesian Belief Nets(BBNs). Especially in composing the node probability table and in making out the input data for BBN model, experts' qualitative judgment or qualitative data should be converted into probabilistic representation. This conversion process is vulnerable to bias or error. The purpose of the report is to provide the guideline to avoid the occurrence of this kinds of bias/error or to eliminate them which is included in the existing data prepared by experts. The contents of the report are: o The types and the explanation of bias and error The types of bias and error which might be occur in the process of eliciting the expert's knowledge. o The procedure of expert's judgment elicitation. The process and techniques to avoid bias and error in eliciting the expert's judgments. o The examples of expert's knowledge appeared in the BBNs The examples of expert's knowledge (probability values) appeared in the BBNs for assessing the safety of digital system

A study on the quantitative evaluation of the reliability for safety critical software using Bayesian belief nets

International Nuclear Information System (INIS)

Eom, H. S.; Jang, S. C.; Ha, J. J.

2003-01-01

Despite the efforts to avoid undesirable risks, or at least to bring them under control in the world, new risks that are highly difficult to manage continue to emerge from the use of new technologies, such as the use of digital instrumentation and control (I and C) components in nuclear power plant. Whenever new risk issues came out by now, we have endeavored to find the most effective ways to reduce risks, or to allocate limited resources to do this. One of the major challenges is the reliability analysis of safety-critical software associated with digital safety systems. Though many activities such as testing, verification and validation (V and V) techniques have been carried out in the design stage of software, however, the process of quantitatively evaluating the reliability of safety-critical software has not yet been developed because of the irrelevance of the conventional software reliability techniques to apply for the digital safety systems. This paper focuses on the applicability of Bayesian Belief Net (BBN) techniques to quantitatively estimate the reliability of safety-critical software adopted in digital safety system. In this paper, a typical BBN model was constructed using the dedication process of the Commercial-Off-The-Shelf (COTS) installed by KAERI. In conclusion, the adoption of BBN technique can facilitate the process of evaluating the safety-critical software reliability in nuclear power plant, as well as provide very useful information (e.g., 'what if' analysis) associated with software reliability in the viewpoint of practicality

Network Traffic Prediction Based on Deep Belief Network and Spatiotemporal Compressive Sensing in Wireless Mesh Backbone Networks

Directory of Open Access Journals (Sweden)

Laisen Nie

2018-01-01

Full Text Available Wireless mesh network is prevalent for providing a decentralized access for users and other intelligent devices. Meanwhile, it can be employed as the infrastructure of the last few miles connectivity for various network applications, for example, Internet of Things (IoT and mobile networks. For a wireless mesh backbone network, it has obtained extensive attention because of its large capacity and low cost. Network traffic prediction is important for network planning and routing configurations that are implemented to improve the quality of service for users. This paper proposes a network traffic prediction method based on a deep learning architecture and the Spatiotemporal Compressive Sensing method. The proposed method first adopts discrete wavelet transform to extract the low-pass component of network traffic that describes the long-range dependence of itself. Then, a prediction model is built by learning a deep architecture based on the deep belief network from the extracted low-pass component. Otherwise, for the remaining high-pass component that expresses the gusty and irregular fluctuations of network traffic, the Spatiotemporal Compressive Sensing method is adopted to predict it. Based on the predictors of two components, we can obtain a predictor of network traffic. From the simulation, the proposed prediction method outperforms three existing methods.

Chemoprevention with green propolis green propolis extracted in L-lysine versus carcinogenesis promotion with L-lysine in N-Butyl-N-[4-hydroxybutyl] nitrosamine (BBN induced rat bladder cancer Quimioprevenção com própolis verde extraído em L-Lisina versus promoção da carcinogênese como L-Lisina em ratos induzidos ao câncer de bexiga pelo N-Butyl-N-[4-hydroxybutyl] nitrosamine (BBN

Directory of Open Access Journals (Sweden)

Conceição Aparecida Dornelas

2012-02-01

Full Text Available PURPOSE: To determine the effects of green propolis extracted in L-lysine (WSDP and of L- lysine for 40 weeks on induced rat bladder carcinogenesis. METHODS: The animals (groups I, II, III, IV, V and VI received BBN during 14 weeks. Group I was treated with propolis 30 days prior received BBN, and then these animals were treated daily with propolis; Groups II and III was treated with subcutaneous and oral propolis (respectively concurrently with BBN. The animals of Group IV were treated L-lysine; Group V received water subcutaneous; and Group VI received only to BBN. Among the animals not submitted to carcinogenesis induction, Group VII received propolis, Group VIII received L-lysine and Group IX received water. RESULTS: The carcinoma incidence in Group I was lower than that of control (Group VI. The carcinoma multiplicity in Group IV was greater than in Group VI. All animals treated with L-lysine developed carcinomas, and they were also more invasive in Group IV than in controls. On the other hand, Group VIII showed no bladder lesions. CONCLUSION: The WSDP is chemopreventive against rat bladder carcinogenesis, if administered 30 days prior to BBN , and that L-lysine causes promotion of bladder carcinogenesis.OBJETIVO: Determinar os efeitos da própolis verde extraída em L - Lisina (WSDP e da L-Lisina por 40 semanas em ratos induzidos a carcinogênese de bexiga. MÉTODOS: Os animais (grupos I, II, III, IV, V e VI receberam BBN por 14 semanas. O grupo I foi tratado com própolis 30 dias antes de receber BBN e em seguida estes animais foram tratados diariamente com própolis; Os grupos II e III foram tratados com própolis subcutânea e oral (respectivamente e concorretemente com BBN. Os animais do grupo IV foram tratados com L- Lisina; o grupo V recebeu água subcutânea; o grupo VI recebeu apenas BBN. Entre os animais não submetidos a indução de carcinogênese, Grupo VII, receberam própolis, Grupo VIII, receberam L-Lisina e Grupo IX

Intelligent Condition Diagnosis Method Based on Adaptive Statistic Test Filter and Diagnostic Bayesian Network.

Science.gov (United States)

Li, Ke; Zhang, Qiuju; Wang, Kun; Chen, Peng; Wang, Huaqing

2016-01-08

A new fault diagnosis method for rotating machinery based on adaptive statistic test filter (ASTF) and Diagnostic Bayesian Network (DBN) is presented in this paper. ASTF is proposed to obtain weak fault features under background noise, ASTF is based on statistic hypothesis testing in the frequency domain to evaluate similarity between reference signal (noise signal) and original signal, and remove the component of high similarity. The optimal level of significance α is obtained using particle swarm optimization (PSO). To evaluate the performance of the ASTF, evaluation factor Ipq is also defined. In addition, a simulation experiment is designed to verify the effectiveness and robustness of ASTF. A sensitive evaluation method using principal component analysis (PCA) is proposed to evaluate the sensitiveness of symptom parameters (SPs) for condition diagnosis. By this way, the good SPs that have high sensitiveness for condition diagnosis can be selected. A three-layer DBN is developed to identify condition of rotation machinery based on the Bayesian Belief Network (BBN) theory. Condition diagnosis experiment for rolling element bearings demonstrates the effectiveness of the proposed method.

Intelligent Condition Diagnosis Method Based on Adaptive Statistic Test Filter and Diagnostic Bayesian Network

Directory of Open Access Journals (Sweden)

Ke Li

2016-01-01

Full Text Available A new fault diagnosis method for rotating machinery based on adaptive statistic test filter (ASTF and Diagnostic Bayesian Network (DBN is presented in this paper. ASTF is proposed to obtain weak fault features under background noise, ASTF is based on statistic hypothesis testing in the frequency domain to evaluate similarity between reference signal (noise signal and original signal, and remove the component of high similarity. The optimal level of significance α is obtained using particle swarm optimization (PSO. To evaluate the performance of the ASTF, evaluation factor Ipq is also defined. In addition, a simulation experiment is designed to verify the effectiveness and robustness of ASTF. A sensitive evaluation method using principal component analysis (PCA is proposed to evaluate the sensitiveness of symptom parameters (SPs for condition diagnosis. By this way, the good SPs that have high sensitiveness for condition diagnosis can be selected. A three-layer DBN is developed to identify condition of rotation machinery based on the Bayesian Belief Network (BBN theory. Condition diagnosis experiment for rolling element bearings demonstrates the effectiveness of the proposed method.

Intelligent Condition Diagnosis Method Based on Adaptive Statistic Test Filter and Diagnostic Bayesian Network

Science.gov (United States)

Li, Ke; Zhang, Qiuju; Wang, Kun; Chen, Peng; Wang, Huaqing

2016-01-01

A new fault diagnosis method for rotating machinery based on adaptive statistic test filter (ASTF) and Diagnostic Bayesian Network (DBN) is presented in this paper. ASTF is proposed to obtain weak fault features under background noise, ASTF is based on statistic hypothesis testing in the frequency domain to evaluate similarity between reference signal (noise signal) and original signal, and remove the component of high similarity. The optimal level of significance α is obtained using particle swarm optimization (PSO). To evaluate the performance of the ASTF, evaluation factor Ipq is also defined. In addition, a simulation experiment is designed to verify the effectiveness and robustness of ASTF. A sensitive evaluation method using principal component analysis (PCA) is proposed to evaluate the sensitiveness of symptom parameters (SPs) for condition diagnosis. By this way, the good SPs that have high sensitiveness for condition diagnosis can be selected. A three-layer DBN is developed to identify condition of rotation machinery based on the Bayesian Belief Network (BBN) theory. Condition diagnosis experiment for rolling element bearings demonstrates the effectiveness of the proposed method. PMID:26761006

A Bayesian approach for predicting risk of autonomous underwater vehicle loss during their missions

International Nuclear Information System (INIS)

Brito, Mario; Griffiths, Gwyn

2016-01-01

Autonomous Underwater Vehicles (AUVs) are effective platforms for science research and monitoring, and for military and commercial data-gathering purposes. However, there is an inevitable risk of loss during any mission. Quantifying the risk of loss is complex, due to the combination of vehicle reliability and environmental factors, and cannot be determined through analytical means alone. An alternative approach – formal expert judgment – is a time-consuming process; consequently a method is needed to broaden the applicability of judgments beyond the narrow confines of an elicitation for a defined environment. We propose and explore a solution founded on a Bayesian Belief Network (BBN), where the results of the expert judgment elicitation are taken as the initial prior probability of loss due to failure. The network topology captures the causal effects of the environment separately on the vehicle and on the support platform, and combines these to produce an updated probability of loss due to failure. An extended version of the Kaplan–Meier estimator is then used to update the mission risk profile with travelled distance. Sensitivity analysis of the BBN is presented and a case study of Autosub3 AUV deployment in the Amundsen Sea is discussed in detail. - Highlights: • Novel method to estimate risk of autonomous vehicle loss in uncertain environments. • A framework to integrate frequentist and subjective probability modelling. • A Bayesian belief updating method for capturing variation in operating environment. • Graphical approach for sensitivity analysis, applicable to any BBN model validation. • Pragmatic case studies showing the application of the proposed framework.

A Belief Network Decision Support Method Applied to Aerospace Surveillance and Battle Management Projects

National Research Council Canada - National Science Library

Staker, R

2003-01-01

This report demonstrates the application of a Bayesian Belief Network decision support method for Force Level Systems Engineering to a collection of projects related to Aerospace Surveillance and Battle Management...

BELIEF dashboard - a web-based curation interface to support generation of BEL networks

OpenAIRE

Madan, Sumit; Hodapp, Sven; Fluck, Juliane

2015-01-01

The relevance of network-based approaches in systems biology to achieve a better understanding of biological mechanisms has increased enormously. The Biological Expression Language (BEL) is well designed to collate findings from scientific literature into biological network models. To facilitate encoding and biocuration of such findings in BEL, a free and user-friendly web-based curation interface called BELIEF Dashboard has been developed. The interface incorporates an information extraction...

Cambodian Parental Involvement: The Role of Parental Beliefs, Social Networks, and Trust

Science.gov (United States)

Eng, Sothy; Szmodis, Whitney; Mulsow, Miriam

2014-01-01

The role of social capital (parental beliefs, social networks, and trust) as a predictor of parental involvement in Cambodian children's education was examined, controlling for human capital (family socioeconomic status). Parents of elementary students (n = 273) were interviewed face to face in Cambodia. Teacher contact scored highest, followed by…

A preliminary approach to quantifying the overall environmental risks posed by development projects during environmental impact assessment.

Science.gov (United States)

Nicol, Sam; Chadès, Iadine

2017-01-01

Environmental impact assessment (EIA) is used globally to manage the impacts of development projects on the environment, so there is an imperative to demonstrate that it can effectively identify risky projects. However, despite the widespread use of quantitative predictive risk models in areas such as toxicology, ecosystem modelling and water quality, the use of predictive risk tools to assess the overall expected environmental impacts of major construction and development proposals is comparatively rare. A risk-based approach has many potential advantages, including improved prediction and attribution of cause and effect; sensitivity analysis; continual learning; and optimal resource allocation. In this paper we investigate the feasibility of using a Bayesian belief network (BBN) to quantify the likelihood and consequence of non-compliance of new projects based on the occurrence probabilities of a set of expert-defined features. The BBN incorporates expert knowledge and continually improves its predictions based on new data as it is collected. We use simulation to explore the trade-off between the number of data points and the prediction accuracy of the BBN, and find that the BBN could predict risk with 90% accuracy using approximately 1000 data points. Although a further pilot test with real project data is required, our results suggest that a BBN is a promising method to monitor overall risks posed by development within an existing EIA process given a modest investment in data collection.

DeepQA: improving the estimation of single protein model quality with deep belief networks.

Science.gov (United States)

Cao, Renzhi; Bhattacharya, Debswapna; Hou, Jie; Cheng, Jianlin

2016-12-05

Protein quality assessment (QA) useful for ranking and selecting protein models has long been viewed as one of the major challenges for protein tertiary structure prediction. Especially, estimating the quality of a single protein model, which is important for selecting a few good models out of a large model pool consisting of mostly low-quality models, is still a largely unsolved problem. We introduce a novel single-model quality assessment method DeepQA based on deep belief network that utilizes a number of selected features describing the quality of a model from different perspectives, such as energy, physio-chemical characteristics, and structural information. The deep belief network is trained on several large datasets consisting of models from the Critical Assessment of Protein Structure Prediction (CASP) experiments, several publicly available datasets, and models generated by our in-house ab initio method. Our experiments demonstrate that deep belief network has better performance compared to Support Vector Machines and Neural Networks on the protein model quality assessment problem, and our method DeepQA achieves the state-of-the-art performance on CASP11 dataset. It also outperformed two well-established methods in selecting good outlier models from a large set of models of mostly low quality generated by ab initio modeling methods. DeepQA is a useful deep learning tool for protein single model quality assessment and protein structure prediction. The source code, executable, document and training/test datasets of DeepQA for Linux is freely available to non-commercial users at http://cactus.rnet.missouri.edu/DeepQA/ .

Study of the 2H(p,γ)3He reaction in the BBN energy range at LUNA

Science.gov (United States)

Trezzi, Davide; LUNA Collaboration

2018-01-01

Using Big Bang Nucleosynthesis with the recent cosmological parameters obtained by the Planck collaboration, a primordial deuterium abundance value D/H = (2.65 ± 0.07) × 10-5 is obtained. This one is a little bit in tension with astronomical observations on metal- poor damped Lyman alpha systems where D/H = (2.53 ± 0.04) × 105. In order to reduce the BBN calculation uncertainty, a measurement of the 2H(p,γ)3He cross section in the energy range 10-300 keV with a 3% accuracy is thus desirable. Thanks to the low background of the underground Gran Sasso Laboratories, and to the experience accumulated in more than twenty years of scientific activity, LUNA (Laboratory for Underground Nuclear Astrophysics) planned to measure the 2H(p,γ)3He fusion cross section at the BBN energy range in 2015-2016. A feasibility test of the measurement has been recently performed at LUNA. In this paper, the results obtained will be shown. Possible cosmological outcomes from the future LUNA data will be also discussed.

Optimization, biological evaluation and microPET imaging of copper-64-labeled bombesin agonists, [64Cu-NO2A-(X)-BBN(7-14)NH2], in a prostate tumor xenografted mouse model

International Nuclear Information System (INIS)

Lane, Stephanie R.; Nanda, Prasanta; Rold, Tammy L.; Sieckman, Gary L.; Figueroa, Said D.; Hoffman, Timothy J.; Jurisson, Silvia S.; Smith, Charles J.

2010-01-01

Gastrin-releasing peptide receptors (GRPr) are a member of the bombesin (BBN) receptor family. GRPr are expressed in high numbers on specific human cancers, including human prostate cancer. Therefore, copper-64 ( 64 Cu) radiolabeled BBN(7-14)NH 2 conjugates could have potential for diagnosis of human prostate cancer via positron-emission tomography (PET). The aim of this study was to produce [ 64 Cu-NO2A-(X)-BBN(7-14)NH 2 ] conjugates for prostate cancer imaging, where X=pharmacokinetic modifier (beta-alanine, 5-aminovaleric acid, 6-aminohexanoic acid, 8-aminooctanoic acid, 9-aminonanoic acid or para-aminobenzoic acid) and NO2A=1,4,7-triazacyclononane-1,4-diacetic acid [a derivative of NOTA (1,4,7-triazacyclononane-1,4,7-triacetic acid)]. Methods: [(X)-BBN(7-14)NH 2 ] Conjugates were synthesized by solid-phase peptide synthesis (SPPS), after which NOTA was added via manual conjugation. The new peptide conjugates were radiolabeled with 64 Cu radionuclide. The receptor-binding affinity was determined in human prostate PC-3 cells, and tumor-targeting efficacy was determined in PC-3 tumor-bearing severely combined immunodeficient (SCID) mice. Whole-body maximum intensity microPET/CT images of PC-3 tumor-bearing SCID mice were obtained 18 h postinjection (pi). Results: Competitive binding assays in PC-3 cells indicated high receptor-binding affinity for the [NO2A-(X)-BBN(7-14)NH 2 ] and [ nat Cu-NO2A-(X)-BBN(7-14)NH 2 ] conjugates. In vivo biodistribution studies of the [ 64 Cu-NO2A-(X)-BBN(7-14)NH 2 ] conjugates at 1, 4 and 24 h pi showed very high uptake of the tracer in GRPr-positive tissue with little accumulation and retention in nontarget tissues. High-quality, high-contrast microPET images were obtained, with xenografted tumors being clearly visible at 18 h pi. Conclusions: NO2A chelator sufficiently stabilizes copper(II) radiometal under in vivo conditions, producing conjugates with very high uptake and retention in targeted GRPr. Preclinical evaluation of these

Predicting Software Suitability Using a Bayesian Belief Network

Science.gov (United States)

Beaver, Justin M.; Schiavone, Guy A.; Berrios, Joseph S.

2005-01-01

The ability to reliably predict the end quality of software under development presents a significant advantage for a development team. It provides an opportunity to address high risk components earlier in the development life cycle, when their impact is minimized. This research proposes a model that captures the evolution of the quality of a software product, and provides reliable forecasts of the end quality of the software being developed in terms of product suitability. Development team skill, software process maturity, and software problem complexity are hypothesized as driving factors of software product quality. The cause-effect relationships between these factors and the elements of software suitability are modeled using Bayesian Belief Networks, a machine learning method. This research presents a Bayesian Network for software quality, and the techniques used to quantify the factors that influence and represent software quality. The developed model is found to be effective in predicting the end product quality of small-scale software development efforts.

BBN technical memorandum W1310 hydroacoustic network capability studies

Energy Technology Data Exchange (ETDEWEB)

Angell, J., LLNL

1997-12-01

This report summarizes work performed under contract to Lawrence Livermore National Laboratory during the period 1 August to 30 November 1997. Four separate tasks were undertaken during this period which investigated various aspects of hydroacoustic network performance using the Hydroacoustic Coverage Assessment Model (HydroCAM). The purpose of this report is to document each of these tasks.

Research on Improved Depth Belief Network-Based Prediction of Cardiovascular Diseases

Directory of Open Access Journals (Sweden)

Peng Lu

2018-01-01

Full Text Available Quantitative analysis and prediction can help to reduce the risk of cardiovascular disease. Quantitative prediction based on traditional model has low accuracy. The variance of model prediction based on shallow neural network is larger. In this paper, cardiovascular disease prediction model based on improved deep belief network (DBN is proposed. Using the reconstruction error, the network depth is determined independently, and unsupervised training and supervised optimization are combined. It ensures the accuracy of model prediction while guaranteeing stability. Thirty experiments were performed independently on the Statlog (Heart and Heart Disease Database data sets in the UCI database. Experimental results showed that the mean of prediction accuracy was 91.26% and 89.78%, respectively. The variance of prediction accuracy was 5.78 and 4.46, respectively.

Low-energy cross sections of the BBN reaction d({alpha},{gamma}){sup 6}Li by Coulomb dissociation of {sup 6}Li

Energy Technology Data Exchange (ETDEWEB)

Heil, Michael; Suemmerer, Klaus [GSI Darmstadt (Germany); Hammache, Fairouz [IPN Orsay (France); Galaviz, Daniel [TU Darmstadt (Germany); Typel, Stefan [GANIL Caen (France)

2008-07-01

The primordial abundances of D, ({sup 3}He), {sup 4}He, and {sup 7}Li can be used to infer the baryon density of the Universe based on the framework of Big-Bang Nucleosynthesis (BBN). By precision measurements of the cosmic microwave background (CMB) an independent method became available recently. This lead to a renewed interest for BBN. Together with the recent observation of {sup 6}Li in old stars and the problems to reconcile calculated primordial {sup 7}Li abundances with those predicted on the basis of CMB results, the production of both, {sup 6}Li and {sup 7}Li in BBN has been reinvestigated. One important ingredient is the low-energy S-factor of the d-alpha radiative-capture reaction. Up to now, the only available experimental result by Kiener et al. (1991) introduced an uncertainty of about a factor of 20 in the {sup 6}Li yield. We have therefore reinvestigated the d-alpha reaction with the help of Coulomb dissociation (CD) of {sup 6}Li at 150 MeV/nucleon at GSI. CD is the only practical way to study the low-energy S-factor (which involves l=2 multipolarity) due to the large number of E2 photons contained in the equivalent-photon flux. Preliminary results indicate a drop of the S-factor as predicted by theory, contrary to the constant low-energy S-factor resulting from the previous study.

[Terahertz Spectroscopic Identification with Deep Belief Network].

Science.gov (United States)

Ma, Shuai; Shen, Tao; Wang, Rui-qi; Lai, Hua; Yu, Zheng-tao

2015-12-01

Feature extraction and classification are the key issues of terahertz spectroscopy identification. Because many materials have no apparent absorption peaks in the terahertz band, it is difficult to extract theirs terahertz spectroscopy feature and identify. To this end, a novel of identify terahertz spectroscopy approach with Deep Belief Network (DBN) was studied in this paper, which combines the advantages of DBN and K-Nearest Neighbors (KNN) classifier. Firstly, cubic spline interpolation and S-G filter were used to normalize the eight kinds of substances (ATP, Acetylcholine Bromide, Bifenthrin, Buprofezin, Carbazole, Bleomycin, Buckminster and Cylotriphosphazene) terahertz transmission spectra in the range of 0.9-6 THz. Secondly, the DBN model was built by two restricted Boltzmann machine (RBM) and then trained layer by layer using unsupervised approach. Instead of using handmade features, the DBN was employed to learn suitable features automatically with raw input data. Finally, a KNN classifier was applied to identify the terahertz spectrum. Experimental results show that using the feature learned by DBN can identify the terahertz spectrum of different substances with the recognition rate of over 90%, which demonstrates that the proposed method can automatically extract the effective features of terahertz spectrum. Furthermore, this KNN classifier was compared with others (BP neural network, SOM neural network and RBF neural network). Comparisons showed that the recognition rate of KNN classifier is better than the other three classifiers. Using the approach that automatic extract terahertz spectrum features by DBN can greatly reduce the workload of feature extraction. This proposed method shows a promising future in the application of identifying the mass terahertz spectroscopy.

A preliminary approach to quantifying the overall environmental risks posed by development projects during environmental impact assessment.

Directory of Open Access Journals (Sweden)

Sam Nicol

Full Text Available Environmental impact assessment (EIA is used globally to manage the impacts of development projects on the environment, so there is an imperative to demonstrate that it can effectively identify risky projects. However, despite the widespread use of quantitative predictive risk models in areas such as toxicology, ecosystem modelling and water quality, the use of predictive risk tools to assess the overall expected environmental impacts of major construction and development proposals is comparatively rare. A risk-based approach has many potential advantages, including improved prediction and attribution of cause and effect; sensitivity analysis; continual learning; and optimal resource allocation. In this paper we investigate the feasibility of using a Bayesian belief network (BBN to quantify the likelihood and consequence of non-compliance of new projects based on the occurrence probabilities of a set of expert-defined features. The BBN incorporates expert knowledge and continually improves its predictions based on new data as it is collected. We use simulation to explore the trade-off between the number of data points and the prediction accuracy of the BBN, and find that the BBN could predict risk with 90% accuracy using approximately 1000 data points. Although a further pilot test with real project data is required, our results suggest that a BBN is a promising method to monitor overall risks posed by development within an existing EIA process given a modest investment in data collection.

arXiv AlterBBN v2: A public code for calculating Big-Bang nucleosynthesis constraints in alternative cosmologies

CERN Document Server

Arbey, A.; Hickerson, K.P.; Jenssen, E.S.

We present the version 2 of AlterBBN, an open public code for the calculation of the abundance of the elements from Big-Bang nucleosynthesis. It does not rely on any closed external library or program, aims at being user-friendly and allowing easy modifications, and provides a fast and reliable calculation of the Big-Bang nucleosynthesis constraints in the standard and alternative cosmologies.

Geometry on the parameter space of the belief propagation algorithm on Bayesian networks

Energy Technology Data Exchange (ETDEWEB)

Watanabe, Yodai [National Institute of Informatics, Research Organization of Information and Systems, 2-1-2 Hitotsubashi, Chiyoda-ku, Tokyo 101-8430 (Japan); Laboratory for Mathematical Neuroscience, RIKEN Brain Science Institute, 2-1 Hirosawa, Wako-shi, Saitama 351-0198 (Japan)

2006-01-30

This Letter considers a geometrical structure on the parameter space of the belief propagation algorithm on Bayesian networks. The statistical manifold of posterior distributions is introduced, and the expression for the information metric on the manifold is derived. The expression is used to construct a cost function which can be regarded as a measure of the distance in the parameter space.

Cognitive Network Modeling as a Basis for Characterizing Human Communication Dynamics and Belief Contagion in Technology Adoption

Science.gov (United States)

Hutto, Clayton; Briscoe, Erica; Trewhitt, Ethan

2012-01-01

Societal level macro models of social behavior do not sufficiently capture nuances needed to adequately represent the dynamics of person-to-person interactions. Likewise, individual agent level micro models have limited scalability - even minute parameter changes can drastically affect a model's response characteristics. This work presents an approach that uses agent-based modeling to represent detailed intra- and inter-personal interactions, as well as a system dynamics model to integrate societal-level influences via reciprocating functions. A Cognitive Network Model (CNM) is proposed as a method of quantitatively characterizing cognitive mechanisms at the intra-individual level. To capture the rich dynamics of interpersonal communication for the propagation of beliefs and attitudes, a Socio-Cognitive Network Model (SCNM) is presented. The SCNM uses socio-cognitive tie strength to regulate how agents influence--and are influenced by--one another's beliefs during social interactions. We then present experimental results which support the use of this network analytical approach, and we discuss its applicability towards characterizing and understanding human information processing.

Quantum Graphical Models and Belief Propagation

International Nuclear Information System (INIS)

Leifer, M.S.; Poulin, D.

2008-01-01

Belief Propagation algorithms acting on Graphical Models of classical probability distributions, such as Markov Networks, Factor Graphs and Bayesian Networks, are amongst the most powerful known methods for deriving probabilistic inferences amongst large numbers of random variables. This paper presents a generalization of these concepts and methods to the quantum case, based on the idea that quantum theory can be thought of as a noncommutative, operator-valued, generalization of classical probability theory. Some novel characterizations of quantum conditional independence are derived, and definitions of Quantum n-Bifactor Networks, Markov Networks, Factor Graphs and Bayesian Networks are proposed. The structure of Quantum Markov Networks is investigated and some partial characterization results are obtained, along the lines of the Hammersley-Clifford theorem. A Quantum Belief Propagation algorithm is presented and is shown to converge on 1-Bifactor Networks and Markov Networks when the underlying graph is a tree. The use of Quantum Belief Propagation as a heuristic algorithm in cases where it is not known to converge is discussed. Applications to decoding quantum error correcting codes and to the simulation of many-body quantum systems are described

Classification of ECG beats using deep belief network and active learning.

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G, Sayantan; T, Kien P; V, Kadambari K

2018-04-12

A new semi-supervised approach based on deep learning and active learning for classification of electrocardiogram signals (ECG) is proposed. The objective of the proposed work is to model a scientific method for classification of cardiac irregularities using electrocardiogram beats. The model follows the Association for the Advancement of medical instrumentation (AAMI) standards and consists of three phases. In phase I, feature representation of ECG is learnt using Gaussian-Bernoulli deep belief network followed by a linear support vector machine (SVM) training in the consecutive phase. It yields three deep models which are based on AAMI-defined classes, namely N, V, S, and F. In the last phase, a query generator is introduced to interact with the expert to label few beats to improve accuracy and sensitivity. The proposed approach depicts significant improvement in accuracy with minimal queries posed to the expert and fast online training as tested on the MIT-BIH Arrhythmia Database and the MIT-BIH Supra-ventricular Arrhythmia Database (SVDB). With 100 queries labeled by the expert in phase III, the method achieves an accuracy of 99.5% in "S" versus all classifications (SVEB) and 99.4% accuracy in "V " versus all classifications (VEB) on MIT-BIH Arrhythmia Database. In a similar manner, it is attributed that an accuracy of 97.5% for SVEB and 98.6% for VEB on SVDB database is achieved respectively. Graphical Abstract Reply- Deep belief network augmented by active learning for efficient prediction of arrhythmia.

Multiple roles for executive control in belief-desire reasoning: distinct neural networks are recruited for self perspective inhibition and complexity of reasoning.

Science.gov (United States)

Hartwright, Charlotte E; Apperly, Ian A; Hansen, Peter C

2012-07-16

Belief-desire reasoning is a core component of 'Theory of Mind' (ToM), which can be used to explain and predict the behaviour of agents. Neuroimaging studies reliably identify a network of brain regions comprising a 'standard' network for ToM, including temporoparietal junction and medial prefrontal cortex. Whilst considerable experimental evidence suggests that executive control (EC) may support a functioning ToM, co-ordination of neural systems for ToM and EC is poorly understood. We report here use of a novel task in which psychologically relevant ToM parameters (true versus false belief; approach versus avoidance desire) were manipulated orthogonally. The valence of these parameters not only modulated brain activity in the 'standard' ToM network but also in EC regions. Varying the valence of both beliefs and desires recruits anterior cingulate cortex, suggesting a shared inhibitory component associated with negatively valenced mental state concepts. Varying the valence of beliefs additionally draws on ventrolateral prefrontal cortex, reflecting the need to inhibit self perspective. These data provide the first evidence that separate functional and neural systems for EC may be recruited in the service of different aspects of ToM. Copyright © 2012 Elsevier Inc. All rights reserved.

Causal inference in biology networks with integrated belief propagation.

Science.gov (United States)

Chang, Rui; Karr, Jonathan R; Schadt, Eric E

2015-01-01

Inferring causal relationships among molecular and higher order phenotypes is a critical step in elucidating the complexity of living systems. Here we propose a novel method for inferring causality that is no longer constrained by the conditional dependency arguments that limit the ability of statistical causal inference methods to resolve causal relationships within sets of graphical models that are Markov equivalent. Our method utilizes Bayesian belief propagation to infer the responses of perturbation events on molecular traits given a hypothesized graph structure. A distance measure between the inferred response distribution and the observed data is defined to assess the 'fitness' of the hypothesized causal relationships. To test our algorithm, we infer causal relationships within equivalence classes of gene networks in which the form of the functional interactions that are possible are assumed to be nonlinear, given synthetic microarray and RNA sequencing data. We also apply our method to infer causality in real metabolic network with v-structure and feedback loop. We show that our method can recapitulate the causal structure and recover the feedback loop only from steady-state data which conventional method cannot.

IgG Responses to Tissue-Associated Antigens as Biomarkers of Immunological Treatment Efficacy

Directory of Open Access Journals (Sweden)

Heath A. Smith

2011-01-01

Full Text Available We previously demonstrated that IgG responses to a panel of 126 prostate tissue-associated antigens are common in patients with prostate cancer. In the current report we questioned whether changes in IgG responses to this panel might be used as a measure of immune response, and potentially antigen spread, following prostate cancer-directed immune-active therapies. Sera were obtained from prostate cancer patients prior to and three months following treatment with androgen deprivation therapy (=34, a poxviral vaccine (=31, and a DNA vaccine (=21. Changes in IgG responses to individual antigens were identified by phage immunoblot. Patterns of IgG recognition following three months of treatment were evaluated using a machine-learned Bayesian Belief Network (ML-BBN. We found that different antigens were recognized following androgen deprivation compared with vaccine therapies. While the number of clinical responders was low in the vaccine-treated populations, we demonstrate that ML-BBN can be used to develop potentially predictive models.

Deep Learning and Developmental Learning: Emergence of Fine-to-Coarse Conceptual Categories at Layers of Deep Belief Network.

Science.gov (United States)

Sadeghi, Zahra

2016-09-01

In this paper, I investigate conceptual categories derived from developmental processing in a deep neural network. The similarity matrices of deep representation at each layer of neural network are computed and compared with their raw representation. While the clusters generated by raw representation stand at the basic level of abstraction, conceptual categories obtained from deep representation shows a bottom-up transition procedure. Results demonstrate a developmental course of learning from specific to general level of abstraction through learned layers of representations in a deep belief network. © The Author(s) 2016.

Synthesis and biological evaluation of copper-64 radiolabeled [DUPA-6-Ahx-(NODAGA)-5-Ava-BBN(7-14)NH2], a novel bivalent targeting vector having affinity for two distinct biomarkers (GRPr/PSMA) of prostate cancer

International Nuclear Information System (INIS)

Bandari, Rajendra Prasad; Jiang, Zongrun; Reynolds, Tamila Stott; Bernskoetter, Nicole E.; Szczodroski, Ashley F.; Bassuner, Kurt J.; Kirkpatrick, Daniel L.; Rold, Tammy L.; Sieckman, Gary L.; Hoffman, Timothy J.; Connors, James P.; Smith, Charles J.

2014-01-01

Gastrin-releasing peptide receptors (GRPr) and prostate-specific membrane antigen (PSMA) are two identifying biomarkers expressed in very high numbers on prostate cancer cells and could serve as a useful tool for molecular targeting and diagnosis of disease via positron-emission tomography (PET). The aim of this study was to produce the multipurpose, bivalent [DUPA-6-Ahx-( 64 Cu-NODAGA)-5-Ava-BBN(7-14)NH 2 ] radioligand for prostate cancer imaging, where DUPA = (2-[3-(1,3-dicarboxypropyl)-ureido]pentanedioic acid), a small-molecule, PSMA-targeting probe, 6Ahx = 6-aminohexanoic acid, 5-Ava = 5-aminovaleric acid, NODAGA = [2-(4,7-biscarboxymethyl)-1,4,7-(triazonan-1-yl)pentanedioic acid] (a derivative of NOTA (1,4,7-triazacyclononane-1,4,7-triacetic acid)), and BBN(7-14)NH 2 = bombesin, a GRPr-specific peptide targeting probe. Methods: The PSMA/GRPr dual targeting ligand precursor [DUPA-6-Ahx-K-5-Ava-BBN(7-14)NH 2 ], was synthesized by solid-phase and manual peptide synthesis, after which NODAGA was added via manual conjugation to the ε-amine of lysine (K). The new bivalent GRPr/PSMA targeting vector was purified by reversed-phase high performance liquid chromatography (RP-HPLC), characterized by electrospray-ionization mass spectrometry (ESI-MS), and metallated with 64 CuCl 2 and nat CuCl 2 . The receptor binding affinity was evaluated in human, prostate, PC-3 (GRPr-positive) and LNCaP (PSMA-positive) cells and the tumor-targeting efficacy determined in severe combined immunodeficient (SCID) and athymic nude mice bearing PC-3 and LNCaP tumors. Whole-body maximum intensity microPET/CT images of PC-3/LNCaP tumor-bearing mice were obtained 18 h post-injection (p.i.). Results: Competitive binding assays in PC-3 and LNCaP cells indicated high receptor binding affinity for the [DUPA-6-Ahx-( nat Cu-NODAGA)-5-Ava-BBN(7-14)NH 2 ] conjugate. MicroPET scintigraphy in PC-3/LNCaP tumor-bearing mice indicated that xenografted tumors were visible at 18 h p.i. with collateral

Synthesis and biological evaluation of copper-64 radiolabeled [DUPA-6-Ahx-(NODAGA)-5-Ava-BBN(7-14)NH2], a novel bivalent targeting vector having affinity for two distinct biomarkers (GRPr/PSMA) of prostate cancer.

Science.gov (United States)

Bandari, Rajendra Prasad; Jiang, Zongrun; Reynolds, Tamila Stott; Bernskoetter, Nicole E; Szczodroski, Ashley F; Bassuner, Kurt J; Kirkpatrick, Daniel L; Rold, Tammy L; Sieckman, Gary L; Hoffman, Timothy J; Connors, James P; Smith, Charles J

2014-04-01

Gastrin-releasing peptide receptors (GRPr) and prostate-specific membrane antigen (PSMA) are two identifying biomarkers expressed in very high numbers on prostate cancer cells and could serve as a useful tool for molecular targeting and diagnosis of disease via positron-emission tomography (PET). The aim of this study was to produce the multipurpose, bivalent [DUPA-6-Ahx-((64)Cu-NODAGA)-5-Ava-BBN(7-14)NH2] radioligand for prostate cancer imaging, where DUPA = (2-[3-(1,3-dicarboxypropyl)-ureido]pentanedioic acid), a small-molecule, PSMA-targeting probe, 6Ahx = 6-aminohexanoic acid, 5-Ava = 5-aminovaleric acid, NODAGA = [2-(4,7-biscarboxymethyl)-1,4,7-(triazonan-1-yl)pentanedioic acid] (a derivative of NOTA (1,4,7-triazacyclononane-1,4,7-triacetic acid)), and BBN(7-14)NH2 = bombesin, a GRPr-specific peptide targeting probe. The PSMA/GRPr dual targeting ligand precursor [DUPA-6-Ahx-K-5-Ava-BBN(7-14)NH2], was synthesized by solid-phase and manual peptide synthesis, after which NODAGA was added via manual conjugation to the ε-amine of lysine (K). The new bivalent GRPr/PSMA targeting vector was purified by reversed-phase high performance liquid chromatography (RP-HPLC), characterized by electrospray-ionization mass spectrometry (ESI-MS), and metallated with (64)CuCl2 and (nat)CuCl2. The receptor binding affinity was evaluated in human, prostate, PC-3 (GRPr-positive) and LNCaP (PSMA-positive) cells and the tumor-targeting efficacy determined in severe combined immunodeficient (SCID) and athymic nude mice bearing PC-3 and LNCaP tumors. Whole-body maximum intensity microPET/CT images of PC-3/LNCaP tumor-bearing mice were obtained 18 h post-injection (p.i.). Competitive binding assays in PC-3 and LNCaP cells indicated high receptor binding affinity for the [DUPA-6-Ahx-((nat)Cu-NODAGA)-5-Ava-BBN(7-14)NH2] conjugate. MicroPET scintigraphy in PC-3/LNCaP tumor-bearing mice indicated that xenografted tumors were visible at 18h p.i. with collateral, background radiation also

Convolutional Deep Belief Networks for Single-Cell/Object Tracking in Computational Biology and Computer Vision

OpenAIRE

Zhong, Bineng; Pan, Shengnan; Zhang, Hongbo; Wang, Tian; Du, Jixiang; Chen, Duansheng; Cao, Liujuan

2016-01-01

In this paper, we propose deep architecture to dynamically learn the most discriminative features from data for both single-cell and object tracking in computational biology and computer vision. Firstly, the discriminative features are automatically learned via a convolutional deep belief network (CDBN). Secondly, we design a simple yet effective method to transfer features learned from CDBNs on the source tasks for generic purpose to the object tracking tasks using only limited amount of tra...

Influences of variables on ship collision probability in a Bayesian belief network model

International Nuclear Information System (INIS)

Hänninen, Maria; Kujala, Pentti

2012-01-01

The influences of the variables in a Bayesian belief network model for estimating the role of human factors on ship collision probability in the Gulf of Finland are studied for discovering the variables with the largest influences and for examining the validity of the network. The change in the so-called causation probability is examined while observing each state of the network variables and by utilizing sensitivity and mutual information analyses. Changing course in an encounter situation is the most influential variable in the model, followed by variables such as the Officer of the Watch's action, situation assessment, danger detection, personal condition and incapacitation. The least influential variables are the other distractions on bridge, the bridge view, maintenance routines and the officer's fatigue. In general, the methods are found to agree on the order of the model variables although some disagreements arise due to slightly dissimilar approaches to the concept of variable influence. The relative values and the ranking of variables based on the values are discovered to be more valuable than the actual numerical values themselves. Although the most influential variables seem to be plausible, there are some discrepancies between the indicated influences in the model and literature. Thus, improvements are suggested to the network.

Isolated guitar transcription using a deep belief network

Directory of Open Access Journals (Sweden)

Gregory Burlet

2017-03-01

Full Text Available Music transcription involves the transformation of an audio recording to common music notation, colloquially referred to as sheet music. Manually transcribing audio recordings is a difficult and time-consuming process, even for experienced musicians. In response, several algorithms have been proposed to automatically analyze and transcribe the notes sounding in an audio recording; however, these algorithms are often general-purpose, attempting to process any number of instruments producing any number of notes sounding simultaneously. This paper presents a polyphonic transcription algorithm that is constrained to processing the audio output of a single instrument, specifically an acoustic guitar. The transcription system consists of a novel note pitch estimation algorithm that uses a deep belief network and multi-label learning techniques to generate multiple pitch estimates for each analysis frame of the input audio signal. Using a compiled dataset of synthesized guitar recordings for evaluation, the algorithm described in this work results in an 11% increase in the f-measure of note transcriptions relative to Zhou et al.’s (2009 transcription algorithm in the literature. This paper demonstrates the effectiveness of deep, multi-label learning for the task of polyphonic transcription.

Active semi-supervised learning method with hybrid deep belief networks.

Science.gov (United States)

Zhou, Shusen; Chen, Qingcai; Wang, Xiaolong

2014-01-01

In this paper, we develop a novel semi-supervised learning algorithm called active hybrid deep belief networks (AHD), to address the semi-supervised sentiment classification problem with deep learning. First, we construct the previous several hidden layers using restricted Boltzmann machines (RBM), which can reduce the dimension and abstract the information of the reviews quickly. Second, we construct the following hidden layers using convolutional restricted Boltzmann machines (CRBM), which can abstract the information of reviews effectively. Third, the constructed deep architecture is fine-tuned by gradient-descent based supervised learning with an exponential loss function. Finally, active learning method is combined based on the proposed deep architecture. We did several experiments on five sentiment classification datasets, and show that AHD is competitive with previous semi-supervised learning algorithm. Experiments are also conducted to verify the effectiveness of our proposed method with different number of labeled reviews and unlabeled reviews respectively.

A deep belief network approach using VDRAS data for nowcasting

Science.gov (United States)

Han, Lei; Dai, Jie; Zhang, Wei; Zhang, Changjiang; Feng, Hanlei

2018-04-01

Nowcasting or very short-term forecasting convective storms is still a challenging problem due to the high nonlinearity and insufficient observation of convective weather. As the understanding of the physical mechanism of convective weather is also insufficient, the numerical weather model cannot predict convective storms well. Machine learning approaches provide a potential way to nowcast convective storms using various meteorological data. In this study, a deep belief network (DBN) is proposed to nowcast convective storms using the real-time re-analysis meteorological data. The nowcasting problem is formulated as a classification problem. The 3D meteorological variables are fed directly to the DBN with dimension of input layer 6*6*80. Three hidden layers are used in the DBN and the dimension of output layer is two. A box-moving method is presented to provide the input features containing the temporal and spatial information. The results show that the DNB can generate reasonable prediction results of the movement and growth of convective storms.

The BEL information extraction workflow (BELIEF): evaluation in the BioCreative V BEL and IAT track

OpenAIRE

Madan, Sumit; Hodapp, Sven; Senger, Philipp; Ansari, Sam; Szostak, Justyna; Hoeng, Julia; Peitsch, Manuel; Fluck, Juliane

2016-01-01

Network-based approaches have become extremely important in systems biology to achieve a better understanding of biological mechanisms. For network representation, the Biological Expression Language (BEL) is well designed to collate findings from the scientific literature into biological network models. To facilitate encoding and biocuration of such findings in BEL, a BEL Information Extraction Workflow (BELIEF) was developed. BELIEF provides a web-based curation interface, the BELIEF Dashboa...

The BEL information extraction workflow (BELIEF): evaluation in the BioCreative V BEL and IAT track.

Science.gov (United States)

Madan, Sumit; Hodapp, Sven; Senger, Philipp; Ansari, Sam; Szostak, Justyna; Hoeng, Julia; Peitsch, Manuel; Fluck, Juliane

2016-01-01

Network-based approaches have become extremely important in systems biology to achieve a better understanding of biological mechanisms. For network representation, the Biological Expression Language (BEL) is well designed to collate findings from the scientific literature into biological network models. To facilitate encoding and biocuration of such findings in BEL, a BEL Information Extraction Workflow (BELIEF) was developed. BELIEF provides a web-based curation interface, the BELIEF Dashboard, that incorporates text mining techniques to support the biocurator in the generation of BEL networks. The underlying UIMA-based text mining pipeline (BELIEF Pipeline) uses several named entity recognition processes and relationship extraction methods to detect concepts and BEL relationships in literature. The BELIEF Dashboard allows easy curation of the automatically generated BEL statements and their context annotations. Resulting BEL statements and their context annotations can be syntactically and semantically verified to ensure consistency in the BEL network. In summary, the workflow supports experts in different stages of systems biology network building. Based on the BioCreative V BEL track evaluation, we show that the BELIEF Pipeline automatically extracts relationships with an F-score of 36.4% and fully correct statements can be obtained with an F-score of 30.8%. Participation in the BioCreative V Interactive task (IAT) track with BELIEF revealed a systems usability scale (SUS) of 67. Considering the complexity of the task for new users-learning BEL, working with a completely new interface, and performing complex curation-a score so close to the overall SUS average highlights the usability of BELIEF.Database URL: BELIEF is available at http://www.scaiview.com/belief/. © The Author(s) 2016. Published by Oxford University Press. All rights reserved. For permissions, please e-mail: journals.permissions@oup.com.

Comparative Study on Cyber Securities between Power Reactor and Research Reactor with Bayesian Update

International Nuclear Information System (INIS)

Shin, Jinsoo; Heo, Gyunyoung; Son, Han Seong

2016-01-01

The Stuxnet has shown that nuclear facilities are no more safe from cyber-attack. Due to practical experiences and concerns on increasing of digital system application, cyber security has become the important issue in nuclear industry. Korea Institute of Nuclear Nonproliferation and control (KINAC) published a regulatory standard (KINAC/RS-015) to establish cyber security framework for nuclear facilities. However, it is difficult to research about cyber security. It is hard to quantify cyber-attack which has malicious activity which is different from existing design basis accidents (DBAs). We previously proposed a methodology on development of a cyber security risk model with BBN. However, the methodology had a limitation in which the input data as prior information was solely on expert opinions. In this study, we propose a cyber security risk model for instrumentation and control (I and C) system of nuclear facilities with some equation for quantification by using Bayesian Belief Network (BBN) in order to overcome the limitation of previous research. The proposed model has been used for comparative study on cyber securities between large-sized nuclear power plants (NPPs) and small-sized Research Reactors (RR). In this study, we proposed the cyber security risk evaluation model with BBN. It includes I and C architecture, which is a target system of cyber-attack, malicious activity, which causes cyber-attack from attacker, and mitigation measure, which mitigates the cyber-attack risk. Likelihood and consequence as prior information are evaluated by considering characteristics of I and C architecture and malicious activity. The BBN model provides posterior information with Bayesian update by adding any of assumed cyber-attack scenarios as evidence. Cyber security risk for nuclear facilities is analyzed by comparing between prior information and posterior information of each node. In this study, we conducted comparative study on cyber securities between power reactor

Comparative Study on Cyber Securities between Power Reactor and Research Reactor with Bayesian Update

Energy Technology Data Exchange (ETDEWEB)

Shin, Jinsoo; Heo, Gyunyoung [Kyung Hee University, Yongin (Korea, Republic of); Son, Han Seong [Joongbu Univiersity, Geumsan (Korea, Republic of)

2016-10-15

The Stuxnet has shown that nuclear facilities are no more safe from cyber-attack. Due to practical experiences and concerns on increasing of digital system application, cyber security has become the important issue in nuclear industry. Korea Institute of Nuclear Nonproliferation and control (KINAC) published a regulatory standard (KINAC/RS-015) to establish cyber security framework for nuclear facilities. However, it is difficult to research about cyber security. It is hard to quantify cyber-attack which has malicious activity which is different from existing design basis accidents (DBAs). We previously proposed a methodology on development of a cyber security risk model with BBN. However, the methodology had a limitation in which the input data as prior information was solely on expert opinions. In this study, we propose a cyber security risk model for instrumentation and control (I and C) system of nuclear facilities with some equation for quantification by using Bayesian Belief Network (BBN) in order to overcome the limitation of previous research. The proposed model has been used for comparative study on cyber securities between large-sized nuclear power plants (NPPs) and small-sized Research Reactors (RR). In this study, we proposed the cyber security risk evaluation model with BBN. It includes I and C architecture, which is a target system of cyber-attack, malicious activity, which causes cyber-attack from attacker, and mitigation measure, which mitigates the cyber-attack risk. Likelihood and consequence as prior information are evaluated by considering characteristics of I and C architecture and malicious activity. The BBN model provides posterior information with Bayesian update by adding any of assumed cyber-attack scenarios as evidence. Cyber security risk for nuclear facilities is analyzed by comparing between prior information and posterior information of each node. In this study, we conducted comparative study on cyber securities between power reactor

Prediction of new bioactive molecules using a Bayesian belief network.

Science.gov (United States)

Abdo, Ammar; Leclère, Valérie; Jacques, Philippe; Salim, Naomie; Pupin, Maude

2014-01-27

Natural products and synthetic compounds are a valuable source of new small molecules leading to novel drugs to cure diseases. However identifying new biologically active small molecules is still a challenge. In this paper, we introduce a new activity prediction approach using Bayesian belief network for classification (BBNC). The roots of the network are the fragments composing a compound. The leaves are, on one side, the activities to predict and, on another side, the unknown compound. The activities are represented by sets of known compounds, and sets of inactive compounds are also used. We calculated a similarity between an unknown compound and each activity class. The more similar activity is assigned to the unknown compound. We applied this new approach on eight well-known data sets extracted from the literature and compared its performance to three classical machine learning algorithms. Experiments showed that BBNC provides interesting prediction rates (from 79% accuracy for high diverse data sets to 99% for low diverse ones) with a short time calculation. Experiments also showed that BBNC is particularly effective for homogeneous data sets but has been found to perform less well with structurally heterogeneous sets. However, it is important to stress that we believe that using several approaches whenever possible for activity prediction can often give a broader understanding of the data than using only one approach alone. Thus, BBNC is a useful addition to the computational chemist's toolbox.

Research on Factors Influencing Municipal Household Solid Waste Separate Collection: Bayesian Belief Networks

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Zhujie Chu

2016-02-01

Full Text Available Municipal household solid waste (MHSW has become a serious problem in China over the course of the last two decades, resulting in significant side effects to the environment. Therefore, effective management of MHSW has attracted wide attention from both researchers and practitioners. Separate collection, the first and crucial step to solve the MHSW problem, however, has not been thoroughly studied to date. An empirical survey has been conducted among 387 households in Harbin, China in this study. We use Bayesian Belief Networks model to determine the influencing factors on separate collection. Four types of factors are identified, including political, economic, social cultural and technological based on the PEST (political, economic, social and technological analytical method. In addition, we further analyze the influential power of different factors, based on the network structure and probability changes obtained by Netica software. Results indicate that technological dimension has the greatest impact on MHSW separate collection, followed by the political dimension and economic dimension; social cultural dimension impacts MHSW the least.

Collective Dynamics of Belief Evolution under Cognitive Coherence and Social Conformity.

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Rodriguez, Nathaniel; Bollen, Johan; Ahn, Yong-Yeol

2016-01-01

Human history has been marked by social instability and conflict, often driven by the irreconcilability of opposing sets of beliefs, ideologies, and religious dogmas. The dynamics of belief systems has been studied mainly from two distinct perspectives, namely how cognitive biases lead to individual belief rigidity and how social influence leads to social conformity. Here we propose a unifying framework that connects cognitive and social forces together in order to study the dynamics of societal belief evolution. Each individual is endowed with a network of interacting beliefs that evolves through interaction with other individuals in a social network. The adoption of beliefs is affected by both internal coherence and social conformity. Our framework may offer explanations for how social transitions can arise in otherwise homogeneous populations, how small numbers of zealots with highly coherent beliefs can overturn societal consensus, and how belief rigidity protects fringe groups and cults against invasion from mainstream beliefs, allowing them to persist and even thrive in larger societies. Our results suggest that strong consensus may be insufficient to guarantee social stability, that the cognitive coherence of belief-systems is vital in determining their ability to spread, and that coherent belief-systems may pose a serious problem for resolving social polarization, due to their ability to prevent consensus even under high levels of social exposure. We argue that the inclusion of cognitive factors into a social model could provide a more complete picture of collective human dynamics.

MODELING INFORMATION SYSTEM AVAILABILITY BY USING BAYESIAN BELIEF NETWORK APPROACH

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Semir Ibrahimović

2016-03-01

Full Text Available Modern information systems are expected to be always-on by providing services to end-users, regardless of time and location. This is particularly important for organizations and industries where information systems support real-time operations and mission-critical applications that need to be available on 24  7  365 basis. Examples of such entities include process industries, telecommunications, healthcare, energy, banking, electronic commerce and a variety of cloud services. This article presents a modified Bayesian Belief Network model for predicting information system availability, introduced initially by Franke, U. and Johnson, P. (in article “Availability of enterprise IT systems – an expert based Bayesian model”. Software Quality Journal 20(2, 369-394, 2012 based on a thorough review of several dimensions of the information system availability, we proposed a modified set of determinants. The model is parameterized by using probability elicitation process with the participation of experts from the financial sector of Bosnia and Herzegovina. The model validation was performed using Monte Carlo simulation.

Hydroacoustic Studies Using HydroCAM - Station-centric Integration of Models and Observations. Quarterly Report No. 5 October - December 2003

International Nuclear Information System (INIS)

Upton, Zachary M.; Pulli, Jay J.

2004-01-01

OAK-B135 Quarterly Technical Report summarizing BBN's support of the DOE/NNSA GNEM program. This report details BBN's efforts to improve the modeling of explosions and other events underwater and their propagation to hydroacoustic sensor networks. OK to release, no restriction on copyright

Peer Smoking and Smoking-related Beliefs Among College Students in Bangladesh.

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Kamimura, Akiko; Ahmmad, Zobayer; Pye, Mu; Gull, Bethany

2018-01-01

Smoking is a significant public health issue in Bangladesh. The purpose of this study was to examine peer smoking and smoking-related beliefs among college students in Bangladesh. College students at two universities in Dhaka, Bangladesh participated in a self-administered survey in May and June 2017. First, being a current or former smoker is associated with lower levels of beliefs among respondents that they would not smoke even with smoker friends or nervousness, and lower levels of intentions that they would not smoke, while current smokers and former smokers have different smoking-related beliefs. Second, having smoker friends is associated with lower levels of intentions that they would not smoke. Third, higher levels of normative beliefs that it is important not to smoke are associated with higher levels of beliefs that they would not smoke even with smoker friends or nervousness, higher levels of intentions that they would not smoke, and higher levels of avoidance of smoking. Smoking-related beliefs and perceived norms in individuals' social networks are important components in promoting tobacco cessation in Bangladesh. But it is challenging to prevent or intervene in smoking because of the high rates of smoking in this country and the high prevalence of smokers in individuals' social networks. Future studies should examine the most effective interventions to combat smoking in high-smoking social networks, such as using mobile apps or social media, and evaluate the effectiveness of such interventions.

Peer Smoking and Smoking-related Beliefs Among College Students in Bangladesh

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Akiko Kamimura

2018-01-01

Full Text Available Objectives Smoking is a significant public health issue in Bangladesh. The purpose of this study was to examine peer smoking and smoking-related beliefs among college students in Bangladesh. Methods College students at two universities in Dhaka, Bangladesh participated in a self-administered survey in May and June 2017. Results First, being a current or former smoker is associated with lower levels of beliefs among respondents that they would not smoke even with smoker friends or nervousness, and lower levels of intentions that they would not smoke, while current smokers and former smokers have different smoking-related beliefs. Second, having smoker friends is associated with lower levels of intentions that they would not smoke. Third, higher levels of normative beliefs that it is important not to smoke are associated with higher levels of beliefs that they would not smoke even with smoker friends or nervousness, higher levels of intentions that they would not smoke, and higher levels of avoidance of smoking. Conclusions Smoking-related beliefs and perceived norms in individuals’ social networks are important components in promoting tobacco cessation in Bangladesh. But it is challenging to prevent or intervene in smoking because of the high rates of smoking in this country and the high prevalence of smokers in individuals’ social networks. Future studies should examine the most effective interventions to combat smoking in high-smoking social networks, such as using mobile apps or social media, and evaluate the effectiveness of such interventions.

Research and Development in Natural Language Understanding as Part of the Strategic Computing Program.

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1987-04-01

facilities. BBN is developing a series of increasingly sophisticated natural language understanding systems which will serve as an integrated interface...Haas, A.R. A Syntactic Theory of Belief and Action. Artificial Intelligence. 1986. Forthcoming. [6] Hinrichs, E. Temporale Anaphora im Englischen

Real-time classification and sensor fusion with a spiking deep belief network.

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O'Connor, Peter; Neil, Daniel; Liu, Shih-Chii; Delbruck, Tobi; Pfeiffer, Michael

2013-01-01

Deep Belief Networks (DBNs) have recently shown impressive performance on a broad range of classification problems. Their generative properties allow better understanding of the performance, and provide a simpler solution for sensor fusion tasks. However, because of their inherent need for feedback and parallel update of large numbers of units, DBNs are expensive to implement on serial computers. This paper proposes a method based on the Siegert approximation for Integrate-and-Fire neurons to map an offline-trained DBN onto an efficient event-driven spiking neural network suitable for hardware implementation. The method is demonstrated in simulation and by a real-time implementation of a 3-layer network with 2694 neurons used for visual classification of MNIST handwritten digits with input from a 128 × 128 Dynamic Vision Sensor (DVS) silicon retina, and sensory-fusion using additional input from a 64-channel AER-EAR silicon cochlea. The system is implemented through the open-source software in the jAER project and runs in real-time on a laptop computer. It is demonstrated that the system can recognize digits in the presence of distractions, noise, scaling, translation and rotation, and that the degradation of recognition performance by using an event-based approach is less than 1%. Recognition is achieved in an average of 5.8 ms after the onset of the presentation of a digit. By cue integration from both silicon retina and cochlea outputs we show that the system can be biased to select the correct digit from otherwise ambiguous input.

Academic Activities Transaction Extraction Based on Deep Belief Network

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Xiangqian Wang

2017-01-01

Full Text Available Extracting information about academic activity transactions from unstructured documents is a key problem in the analysis of academic behaviors of researchers. The academic activities transaction includes five elements: person, activities, objects, attributes, and time phrases. The traditional method of information extraction is to extract shallow text features and then to recognize advanced features from text with supervision. Since the information processing of different levels is completed in steps, the error generated from various steps will be accumulated and affect the accuracy of final results. However, because Deep Belief Network (DBN model has the ability to automatically unsupervise learning of the advanced features from shallow text features, the model is employed to extract the academic activities transaction. In addition, we use character-based feature to describe the raw features of named entities of academic activity, so as to improve the accuracy of named entity recognition. In this paper, the accuracy of the academic activities extraction is compared by using character-based feature vector and word-based feature vector to express the text features, respectively, and with the traditional text information extraction based on Conditional Random Fields. The results show that DBN model is more effective for the extraction of academic activities transaction information.

Deep Belief Network Based Hybrid Model for Building Energy Consumption Prediction

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Chengdong Li

2018-01-01

Full Text Available To enhance the prediction performance for building energy consumption, this paper presents a modified deep belief network (DBN based hybrid model. The proposed hybrid model combines the outputs from the DBN model with the energy-consuming pattern to yield the final prediction results. The energy-consuming pattern in this study represents the periodicity property of building energy consumption and can be extracted from the observed historical energy consumption data. The residual data generated by removing the energy-consuming pattern from the original data are utilized to train the modified DBN model. The training of the modified DBN includes two steps, the first one of which adopts the contrastive divergence (CD algorithm to optimize the hidden parameters in a pre-train way, while the second one determines the output weighting vector by the least squares method. The proposed hybrid model is applied to two kinds of building energy consumption data sets that have different energy-consuming patterns (daily-periodicity and weekly-periodicity. In order to examine the advantages of the proposed model, four popular artificial intelligence methods—the backward propagation neural network (BPNN, the generalized radial basis function neural network (GRBFNN, the extreme learning machine (ELM, and the support vector regressor (SVR are chosen as the comparative approaches. Experimental results demonstrate that the proposed DBN based hybrid model has the best performance compared with the comparative techniques. Another thing to be mentioned is that all the predictors constructed by utilizing the energy-consuming patterns perform better than those designed only by the original data. This verifies the usefulness of the incorporation of the energy-consuming patterns. The proposed approach can also be extended and applied to some other similar prediction problems that have periodicity patterns, e.g., the traffic flow forecasting and the electricity consumption

Convolutional Deep Belief Networks for Single-Cell/Object Tracking in Computational Biology and Computer Vision.

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Zhong, Bineng; Pan, Shengnan; Zhang, Hongbo; Wang, Tian; Du, Jixiang; Chen, Duansheng; Cao, Liujuan

2016-01-01

In this paper, we propose deep architecture to dynamically learn the most discriminative features from data for both single-cell and object tracking in computational biology and computer vision. Firstly, the discriminative features are automatically learned via a convolutional deep belief network (CDBN). Secondly, we design a simple yet effective method to transfer features learned from CDBNs on the source tasks for generic purpose to the object tracking tasks using only limited amount of training data. Finally, to alleviate the tracker drifting problem caused by model updating, we jointly consider three different types of positive samples. Extensive experiments validate the robustness and effectiveness of the proposed method.

Development of the predictive maintenance system prototype for the rod control system

International Nuclear Information System (INIS)

Lim, H. S.; Hong, H. P.; Koo, J. M.; Kim, Y. B.; Han, H. W.

2003-01-01

The demand for safety and reliability of Nuclear Power Plants (NPPs) has been constantly increasing and economical operation is also an important issue. Developing and adopting predictive maintenance technology for the major systems or equipment is considered as a way to achieve these goals. This paper describes the development of a predictive maintenance system prototype for the Rod Control System, which adopts an advanced methodology. Bayesian Belief Networks (BBN) has been adopted for the real time fault diagnosis and prediction of the system. Through a simulation test, it was confirmed that the prototype monitors and secures sound operability of rod drive mechanism and its control system, and also provides the predictive maintenance information

Unsupervised Fault Diagnosis of a Gear Transmission Chain Using a Deep Belief Network

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Jun He

2017-07-01

Full Text Available Artificial intelligence (AI techniques, which can effectively analyze massive amounts of fault data and automatically provide accurate diagnosis results, have been widely applied to fault diagnosis of rotating machinery. Conventional AI methods are applied using features selected by a human operator, which are manually extracted based on diagnostic techniques and field expertise. However, developing robust features for each diagnostic purpose is often labour-intensive and time-consuming, and the features extracted for one specific task may be unsuitable for others. In this paper, a novel AI method based on a deep belief network (DBN is proposed for the unsupervised fault diagnosis of a gear transmission chain, and the genetic algorithm is used to optimize the structural parameters of the network. Compared to the conventional AI methods, the proposed method can adaptively exploit robust features related to the faults by unsupervised feature learning, thus requires less prior knowledge about signal processing techniques and diagnostic expertise. Besides, it is more powerful at modelling complex structured data. The effectiveness of the proposed method is validated using datasets from rolling bearings and gearbox. To show the superiority of the proposed method, its performance is compared with two well-known classifiers, i.e., back propagation neural network (BPNN and support vector machine (SVM. The fault classification accuracies are 99.26% for rolling bearings and 100% for gearbox when using the proposed method, which are much higher than that of the other two methods.

Unsupervised Fault Diagnosis of a Gear Transmission Chain Using a Deep Belief Network.

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He, Jun; Yang, Shixi; Gan, Chunbiao

2017-07-04

Artificial intelligence (AI) techniques, which can effectively analyze massive amounts of fault data and automatically provide accurate diagnosis results, have been widely applied to fault diagnosis of rotating machinery. Conventional AI methods are applied using features selected by a human operator, which are manually extracted based on diagnostic techniques and field expertise. However, developing robust features for each diagnostic purpose is often labour-intensive and time-consuming, and the features extracted for one specific task may be unsuitable for others. In this paper, a novel AI method based on a deep belief network (DBN) is proposed for the unsupervised fault diagnosis of a gear transmission chain, and the genetic algorithm is used to optimize the structural parameters of the network. Compared to the conventional AI methods, the proposed method can adaptively exploit robust features related to the faults by unsupervised feature learning, thus requires less prior knowledge about signal processing techniques and diagnostic expertise. Besides, it is more powerful at modelling complex structured data. The effectiveness of the proposed method is validated using datasets from rolling bearings and gearbox. To show the superiority of the proposed method, its performance is compared with two well-known classifiers, i.e., back propagation neural network (BPNN) and support vector machine (SVM). The fault classification accuracies are 99.26% for rolling bearings and 100% for gearbox when using the proposed method, which are much higher than that of the other two methods.

The neural basis of testable and non-testable beliefs.

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Jonathon R Howlett

Full Text Available Beliefs about the state of the world are an important influence on both normal behavior and psychopathology. However, understanding of the neural basis of belief processing remains incomplete, and several aspects of belief processing have only recently been explored. Specifically, different types of beliefs may involve fundamentally different inferential processes and thus recruit distinct brain regions. Additionally, neural processing of truth and falsity may differ from processing of certainty and uncertainty. The purpose of this study was to investigate the neural underpinnings of assessment of testable and non-testable propositions in terms of truth or falsity and the level of certainty in a belief. Functional magnetic resonance imaging (fMRI was used to study 14 adults while they rated propositions as true or false and also rated the level of certainty in their judgments. Each proposition was classified as testable or non-testable. Testable propositions activated the DLPFC and posterior cingulate cortex, while non-testable statements activated areas including inferior frontal gyrus, superior temporal gyrus, and an anterior region of the superior frontal gyrus. No areas were more active when a proposition was accepted, while the dorsal anterior cingulate was activated when a proposition was rejected. Regardless of whether a proposition was testable or not, certainty that the proposition was true or false activated a common network of regions including the medial prefrontal cortex, caudate, posterior cingulate, and a region of middle temporal gyrus near the temporo-parietal junction. Certainty in the truth or falsity of a non-testable proposition (a strong belief without empirical evidence activated the insula. The results suggest that different brain regions contribute to the assessment of propositions based on the type of content, while a common network may mediate the influence of beliefs on motivation and behavior based on the level of

A Bayesian Belief Network approach to assess the potential of non wood forest products for small scale forest owners

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Vacik, Harald; Huber, Patrick; Hujala, Teppo; Kurtilla, Mikko; Wolfslehner, Bernhard

2015-04-01

It is an integral element of the European understanding of sustainable forest management to foster the design and marketing of forest products, non-wood forest products (NWFPs) and services that go beyond the production of timber. Despite the relevance of NWFPs in Europe, forest management and planning methods have been traditionally tailored towards wood and wood products, because most forest management models and silviculture techniques were developed to ensure a sustained production of timber. Although several approaches exist which explicitly consider NWFPs as management objectives in forest planning, specific models are needed for the assessment of their production potential in different environmental contexts and for different management regimes. Empirical data supporting a comprehensive assessment of the potential of NWFPs are rare, thus making development of statistical models particularly problematic. However, the complex causal relationships between the sustained production of NWFPs, the available ecological resources, as well as the organizational and the market potential of forest management regimes are well suited for knowledge-based expert models. Bayesian belief networks (BBNs) are a kind of probabilistic graphical model that have become very popular to practitioners and scientists mainly due to the powerful probability theory involved, which makes BBNs suitable to deal with a wide range of environmental problems. In this contribution we present the development of a Bayesian belief network to assess the potential of NWFPs for small scale forest owners. A three stage iterative process with stakeholder and expert participation was used to develop the Bayesian Network within the frame of the StarTree Project. The group of participants varied in the stages of the modelling process. A core team, consisting of one technical expert and two domain experts was responsible for the entire modelling process as well as for the first prototype of the network

Association of health professional leadership behaviors on health promotion practice beliefs.

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Stone, Jacqueline D; Belcher, Harolyn M E; Attoh, Prince; D'Abundo, Michelle; Gong, Tao

2017-04-01

Leadership is a process by which an individual influences a group or individual to achieve a common goal, in this case health promotion for individuals with disabilities. (1) To examine the association between the transformational leadership behaviors of the Association of University Centers on Disabilities (AUCD) network professionals and their practice beliefs about health promotion activities, specifically cardiovascular fitness and healthy weight, for people with disabilities. (2) To determine if discipline and/or years of practice moderate the association between transformational leadership behaviors and practice beliefs regarding health promotion. There is a positive association between transformational leadership behaviors and health professionals practice beliefs regarding health promotion activities for persons with disabilities. A quantitative cross-sectional web-based survey design was used to determine the association between leadership behaviors and practices beliefs regarding health promotion for people with disabilities. The Multifactor Leadership Questionnaire and an adapted version of the Role of Health Promotion in Physical Therapy Survey were used to measure leadership and practice beliefs, respectively. Multiple regression analysis was applied to determine the association of leadership behaviors with health promotion practice beliefs variables. Transformational leadership behaviors of the AUCD network professionals were positively associated with health promotion practice beliefs about cardiovascular fitness for people with disabilities. Years post licensure and discipline did not moderate the association between transformational leadership and practice beliefs regarding health promotion. Transformational leadership may facilitate health professionals' health promotion practices for people with disabilities. Further research and training in leadership is needed. Copyright © 2017 Elsevier Inc. All rights reserved.

Robustness of spiking Deep Belief Networks to noise and reduced bit precision of neuro-inspired hardware platforms.

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Stromatias, Evangelos; Neil, Daniel; Pfeiffer, Michael; Galluppi, Francesco; Furber, Steve B; Liu, Shih-Chii

2015-01-01

Increasingly large deep learning architectures, such as Deep Belief Networks (DBNs) are the focus of current machine learning research and achieve state-of-the-art results in different domains. However, both training and execution of large-scale Deep Networks require vast computing resources, leading to high power requirements and communication overheads. The on-going work on design and construction of spike-based hardware platforms offers an alternative for running deep neural networks with significantly lower power consumption, but has to overcome hardware limitations in terms of noise and limited weight precision, as well as noise inherent in the sensor signal. This article investigates how such hardware constraints impact the performance of spiking neural network implementations of DBNs. In particular, the influence of limited bit precision during execution and training, and the impact of silicon mismatch in the synaptic weight parameters of custom hybrid VLSI implementations is studied. Furthermore, the network performance of spiking DBNs is characterized with regard to noise in the spiking input signal. Our results demonstrate that spiking DBNs can tolerate very low levels of hardware bit precision down to almost two bits, and show that their performance can be improved by at least 30% through an adapted training mechanism that takes the bit precision of the target platform into account. Spiking DBNs thus present an important use-case for large-scale hybrid analog-digital or digital neuromorphic platforms such as SpiNNaker, which can execute large but precision-constrained deep networks in real time.

Further development of a method to calculate frequencies of loss of control including their uncertainty

NARCIS (Netherlands)

Ale, B.J.M.; Van Gulijk, C.; Hanea, D.M.; Hudson, P.; Lin, P.H.; Sillem, S.; Steenhoek, M.; Ababei, D.

2013-01-01

An integrated model for risk in a real-time environment for the hydrocarbon industry based on the CATS model for commercial aviation safety has been further developed. The approach described in earlier papers required Bayesian Belief Nets (BBN) to be developed for each process unit separately. A

Top-down feedback in an HMAX-like cortical model of object perception based on hierarchical Bayesian networks and belief propagation.

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Salvador Dura-Bernal

Full Text Available Hierarchical generative models, such as Bayesian networks, and belief propagation have been shown to provide a theoretical framework that can account for perceptual processes, including feedforward recognition and feedback modulation. The framework explains both psychophysical and physiological experimental data and maps well onto the hierarchical distributed cortical anatomy. However, the complexity required to model cortical processes makes inference, even using approximate methods, very computationally expensive. Thus, existing object perception models based on this approach are typically limited to tree-structured networks with no loops, use small toy examples or fail to account for certain perceptual aspects such as invariance to transformations or feedback reconstruction. In this study we develop a Bayesian network with an architecture similar to that of HMAX, a biologically-inspired hierarchical model of object recognition, and use loopy belief propagation to approximate the model operations (selectivity and invariance. Crucially, the resulting Bayesian network extends the functionality of HMAX by including top-down recursive feedback. Thus, the proposed model not only achieves successful feedforward recognition invariant to noise, occlusions, and changes in position and size, but is also able to reproduce modulatory effects such as illusory contour completion and attention. Our novel and rigorous methodology covers key aspects such as learning using a layerwise greedy algorithm, combining feedback information from multiple parents and reducing the number of operations required. Overall, this work extends an established model of object recognition to include high-level feedback modulation, based on state-of-the-art probabilistic approaches. The methodology employed, consistent with evidence from the visual cortex, can be potentially generalized to build models of hierarchical perceptual organization that include top-down and bottom

Implicit false-belief processing in the human brain.

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Schneider, Dana; Slaughter, Virginia P; Becker, Stefanie I; Dux, Paul E

2014-11-01

Eye-movement patterns in 'Sally-Anne' tasks reflect humans' ability to implicitly process the mental states of others, particularly false-beliefs - a key theory of mind (ToM) operation. It has recently been proposed that an efficient ToM system, which operates in the absence of awareness (implicit ToM, iToM), subserves the analysis of belief-like states. This contrasts to consciously available belief processing, performed by the explicit ToM system (eToM). The frontal, temporal and parietal cortices are engaged when humans explicitly 'mentalize' about others' beliefs. However, the neural underpinnings of implicit false-belief processing and the extent to which they draw on networks involved in explicit general-belief processing are unknown. Here, participants watched 'Sally-Anne' movies while fMRI and eye-tracking measures were acquired simultaneously. Participants displayed eye-movements consistent with implicit false-belief processing. After independently localizing the brain areas involved in explicit general-belief processing, only the left anterior superior temporal sulcus and precuneus revealed greater blood-oxygen-level-dependent activity for false- relative to true-belief trials in our iToM paradigm. No such difference was found for the right temporal-parietal junction despite significant activity in this area. These findings fractionate brain regions that are associated with explicit general ToM reasoning and false-belief processing in the absence of awareness. Copyright © 2014 Elsevier Inc. All rights reserved.

A Framework for Assessment of Aviation Safety Technology Portfolios

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Jones, Sharon M.; Reveley, Mary S.

2014-01-01

The programs within NASA's Aeronautics Research Mission Directorate (ARMD) conduct research and development to improve the national air transportation system so that Americans can travel as safely as possible. NASA aviation safety systems analysis personnel support various levels of ARMD management in their fulfillment of system analysis and technology prioritization as defined in the agency's program and project requirements. This paper provides a framework for the assessment of aviation safety research and technology portfolios that includes metrics such as projected impact on current and future safety, technical development risk and implementation risk. The paper also contains methods for presenting portfolio analysis and aviation safety Bayesian Belief Network (BBN) output results to management using bubble charts and quantitative decision analysis techniques.

Robustness of spiking Deep Belief Networks to noise and reduced bit precision of neuro-inspired hardware platforms

Directory of Open Access Journals (Sweden)

Evangelos eStromatias

2015-07-01

Full Text Available Increasingly large deep learning architectures, such as Deep Belief Networks (DBNs are the focus of current machine learning research and achieve state-of-the-art results in different domains. However, both training and execution of large-scale Deep Networks requires vast computing resources, leading to high power requirements and communication overheads. The on-going work on design and construction of spike-based hardware platforms offers an alternative for running deep neural networks with significantly lower power consumption, but has to overcome hardware limitations in terms of noise and limited weight precision, as well as noise inherent in the sensor signal. This article investigates how such hardware constraints impact the performance of spiking neural network implementations of DBNs. In particular, the influence of limited bit precision during execution and training, and the impact of silicon mismatch in the synaptic weight parameters of custom hybrid VLSI implementations is studied. Furthermore, the network performance of spiking DBNs is characterized with regard to noise in the spiking input signal. Our results demonstrate that spiking DBNs can tolerate very low levels of hardware bit precision down to almost 2 bits, and shows that their performance can be improved by at least 30% through an adapted training mechanism that takes the bit precision of the target platform into account. Spiking DBNs thus present an important use-case for large-scale hybrid analog-digital or digital neuromorphic platforms such as SpiNNaker, which can execute large but precision-constrained deep networks in real time.

Rolling bearing fault feature learning using improved convolutional deep belief network with compressed sensing

Science.gov (United States)

Shao, Haidong; Jiang, Hongkai; Zhang, Haizhou; Duan, Wenjing; Liang, Tianchen; Wu, Shuaipeng

2018-02-01

The vibration signals collected from rolling bearing are usually complex and non-stationary with heavy background noise. Therefore, it is a great challenge to efficiently learn the representative fault features of the collected vibration signals. In this paper, a novel method called improved convolutional deep belief network (CDBN) with compressed sensing (CS) is developed for feature learning and fault diagnosis of rolling bearing. Firstly, CS is adopted for reducing the vibration data amount to improve analysis efficiency. Secondly, a new CDBN model is constructed with Gaussian visible units to enhance the feature learning ability for the compressed data. Finally, exponential moving average (EMA) technique is employed to improve the generalization performance of the constructed deep model. The developed method is applied to analyze the experimental rolling bearing vibration signals. The results confirm that the developed method is more effective than the traditional methods.

An ecosystem service approach to support integrated pond management: a case study using Bayesian belief networks--highlighting opportunities and risks.

Science.gov (United States)

Landuyt, Dries; Lemmens, Pieter; D'hondt, Rob; Broekx, Steven; Liekens, Inge; De Bie, Tom; Declerck, Steven A J; De Meester, Luc; Goethals, Peter L M

2014-12-01

Freshwater ponds deliver a broad range of ecosystem services (ESS). Taking into account this broad range of services to attain cost-effective ESS delivery is an important challenge facing integrated pond management. To assess the strengths and weaknesses of an ESS approach to support decisions in integrated pond management, we applied it on a small case study in Flanders, Belgium. A Bayesian belief network model was developed to assess ESS delivery under three alternative pond management scenarios: intensive fish farming (IFF), extensive fish farming (EFF) and nature conservation management (NCM). A probabilistic cost-benefit analysis was performed that includes both costs associated with pond management practices and benefits associated with ESS delivery. Whether or not a particular ESS is included in the analysis affects the identification of the most preferable management scenario by the model. Assessing the delivery of a more complete set of ecosystem services tends to shift the results away from intensive management to more biodiversity-oriented management scenarios. The proposed methodology illustrates the potential of Bayesian belief networks. BBNs facilitate knowledge integration and their modular nature encourages future model expansion to more encompassing sets of services. Yet, we also illustrate the key weaknesses of such exercises, being that the choice whether or not to include a particular ecosystem service may determine the suggested optimal management practice. Copyright © 2014 Elsevier Ltd. All rights reserved.

Rolling bearing fault diagnosis using adaptive deep belief network with dual-tree complex wavelet packet.

Science.gov (United States)

Shao, Haidong; Jiang, Hongkai; Wang, Fuan; Wang, Yanan

2017-07-01

Automatic and accurate identification of rolling bearing fault categories, especially for the fault severities and compound faults, is a challenge in rotating machinery fault diagnosis. For this purpose, a novel method called adaptive deep belief network (DBN) with dual-tree complex wavelet packet (DTCWPT) is developed in this paper. DTCWPT is used to preprocess the vibration signals to refine the fault characteristics information, and an original feature set is designed from each frequency-band signal of DTCWPT. An adaptive DBN is constructed to improve the convergence rate and identification accuracy with multiple stacked adaptive restricted Boltzmann machines (RBMs). The proposed method is applied to the fault diagnosis of rolling bearings. The results confirm that the proposed method is more effective than the existing methods. Copyright © 2017 ISA. Published by Elsevier Ltd. All rights reserved.

A deep belief network with PLSR for nonlinear system modeling.

Science.gov (United States)

Qiao, Junfei; Wang, Gongming; Li, Wenjing; Li, Xiaoli

2017-10-31

Nonlinear system modeling plays an important role in practical engineering, and deep learning-based deep belief network (DBN) is now popular in nonlinear system modeling and identification because of the strong learning ability. However, the existing weights optimization for DBN is based on gradient, which always leads to a local optimum and a poor training result. In this paper, a DBN with partial least square regression (PLSR-DBN) is proposed for nonlinear system modeling, which focuses on the problem of weights optimization for DBN using PLSR. Firstly, unsupervised contrastive divergence (CD) algorithm is used in weights initialization. Secondly, initial weights derived from CD algorithm are optimized through layer-by-layer PLSR modeling from top layer to bottom layer. Instead of gradient method, PLSR-DBN can determine the optimal weights using several PLSR models, so that a better performance of PLSR-DBN is achieved. Then, the analysis of convergence is theoretically given to guarantee the effectiveness of the proposed PLSR-DBN model. Finally, the proposed PLSR-DBN is tested on two benchmark nonlinear systems and an actual wastewater treatment system as well as a handwritten digit recognition (nonlinear mapping and modeling) with high-dimension input data. The experiment results show that the proposed PLSR-DBN has better performances of time and accuracy on nonlinear system modeling than that of other methods. Copyright © 2017 Elsevier Ltd. All rights reserved.

A Mixed Methods Approach to Code Stakeholder Beliefs in Urban Water Governance

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Bell, E. V.; Henry, A.; Pivo, G.

2017-12-01

What is a reliable way to code policies to represent belief systems? The Advocacy Coalition Framework posits that public policy may be viewed as manifestations of belief systems. Belief systems include both ontological beliefs about cause-and-effect relationships and policy effectiveness, as well as normative beliefs about appropriate policy instruments and the relative value of different outcomes. The idea that belief systems are embodied in public policy is important for urban water governance because it trains our focus on belief conflict; this can help us understand why many water-scarce cities do not adopt innovative technology despite available scientific information. To date, there has been very little research on systematic, rigorous methods to measure the belief system content of public policies. We address this by testing the relationship between beliefs and policy participation to develop an innovative coding framework. With a focus on urban water governance in Tucson, Arizona, we analyze grey literature on local water management. Mentioned policies are coded into a typology of common approaches identified in urban water governance literature, which include regulation, education, price and non-price incentives, green infrastructure and other types of technology. We then survey local water stakeholders about their perceptions of these policies. Urban water governance requires coordination of organizations from multiple sectors, and we cannot assume that belief development and policy participation occur in a vacuum. Thus, we use a generalized exponential random graph model to test the relationship between perceptions and policy participation in the Tucson water governance network. We measure policy perceptions for organizations by averaging across their respective, affiliated respondents and generating a belief distance matrix of coordinating network participants. Similarly, we generate a distance matrix of these actors based on the frequency of their

Survey of bayesian belif nets for quantitative reliability assessment of safety critical software used in nuclear power plants

Energy Technology Data Exchange (ETDEWEB)

Eom, H.S.; Sung, T.Y.; Jeong, H.S.; Park, J.H.; Kang, H.G.; Lee, K

2001-03-01

As part of the Probabilistic Safety Assessment of safety grade digital systems used in Nuclear Power plants research, measures and methodologies applicable to quantitative reliability assessment of safety critical software were surveyed. Among the techniques proposed in the literature we selected those which are in use widely and investigated their limitations in quantitative software reliability assessment. One promising methodology from the survey is Bayesian Belief Nets (BBN) which has a formalism and can combine various disparate evidences relevant to reliability into final decision under uncertainty. Thus we analyzed BBN and its application cases in digital systems assessment area and finally studied the possibility of its application to the quantitative reliability assessment of safety critical software.

Survey of bayesian belif nets for quantitative reliability assessment of safety critical software used in nuclear power plants

International Nuclear Information System (INIS)

Eom, H. S.; Sung, T. Y.; Jeong, H. S.; Park, J. H.; Kang, H. G.; Lee, K.

2001-03-01

As part of the Probabilistic Safety Assessment of safety grade digital systems used in Nuclear Power plants research, measures and methodologies applicable to quantitative reliability assessment of safety critical software were surveyed. Among the techniques proposed in the literature we selected those which are in use widely and investigated their limitations in quantitative software reliability assessment. One promising methodology from the survey is Bayesian Belief Nets (BBN) which has a formalism and can combine various disparate evidences relevant to reliability into final decision under uncertainty. Thus we analyzed BBN and its application cases in digital systems assessment area and finally studied the possibility of its application to the quantitative reliability assessment of safety critical software

Sociospatial Knowledge Networks: Appraising Community as Place.

Science.gov (United States)

Skelly, Anne H.; Arcury, Thomas A.; Gesler, Wilbert M.; Cravey, Altha J.; Dougherty, Molly C.; Washburn, Sarah A.; Nash, Sally

2002-01-01

A new theory of geographical analysis--sociospatial knowledge networks--provides a framework for understanding the social and spatial locations of a community's health knowledge and beliefs. This theory is guiding an ethnographic study of health beliefs, knowledge, and knowledge networks in a diverse rural community at high risk for type-2…

Promoting Enjoyment in Girls' Physical Education: The Impact of Goals, Beliefs, and Self-Determination

Science.gov (United States)

Wang, C. K. John; Liu, W. C.

2007-01-01

This study examined the network of relationships between sport ability beliefs, achievement goals, self-determination and female students' enjoyment in school physical education (PE). Female secondary students (n = 343) from a single-sex secondary school in Singapore participated in the survey. They were assessed on sport ability beliefs, goal…

Cognitive biases explain religious belief, paranormal belief, and belief in life's purpose.

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Willard, Aiyana K; Norenzayan, Ara

2013-11-01

Cognitive theories of religion have postulated several cognitive biases that predispose human minds towards religious belief. However, to date, these hypotheses have not been tested simultaneously and in relation to each other, using an individual difference approach. We used a path model to assess the extent to which several interacting cognitive tendencies, namely mentalizing, mind body dualism, teleological thinking, and anthropomorphism, as well as cultural exposure to religion, predict belief in God, paranormal beliefs and belief in life's purpose. Our model, based on two independent samples (N=492 and N=920) found that the previously known relationship between mentalizing and belief is mediated by individual differences in dualism, and to a lesser extent by teleological thinking. Anthropomorphism was unrelated to religious belief, but was related to paranormal belief. Cultural exposure to religion (mostly Christianity) was negatively related to anthropomorphism, and was unrelated to any of the other cognitive tendencies. These patterns were robust for both men and women, and across at least two ethnic identifications. The data were most consistent with a path model suggesting that mentalizing comes first, which leads to dualism and teleology, which in turn lead to religious, paranormal, and life's-purpose beliefs. Alternative theoretical models were tested but did not find empirical support. Copyright © 2013 Elsevier B.V. All rights reserved.

You Are What You Read: The Belief Systems of Cyber-Bystanders on Social Networking Sites.

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Leung, Angel N M; Wong, Natalie; Farver, JoAnn M

2018-01-01

The present study tested how exposure to two types of responses to a hypothetical simulated Facebook setting influenced cyber-bystanders' perceived control and normative beliefs using a 4 cyberbully-victim group (pure cyberbullies, non-involved, pure cyberbullied victims, and cyberbullied-victims) × 2 condition (offend vs. defend) experimental design. 203 Hong Kong Chinese secondary school and university students (132 females, 71 males; 12 to 28; M = 16.70; SD = 3.03 years old) were randomly assigned into one of two conditions. Results showed that participants' involvement in cyberbullying significantly related to their control beliefs about bully and victim assisting behaviors, while exposure to the two different conditions (offend vs. defend comments) was related to both their control and normative beliefs. In general, the defend condition promoted higher control beliefs to help the victims and promoted higher normative beliefs to help the victims. Regardless of their past involvement in cyberbullying and exposure to offend vs. defend conditions, both cyber-bullies and cyber-victims were more inclined to demonstrate normative beliefs to help victims than to assist bullies. These results have implications for examining environmental influences in predicting bystander behaviors in cyberbullying contexts, and for creating a positive environment to motivate adolescents to become "upstanders" in educational programs to combat cyberbullying.

You Are What You Read: The Belief Systems of Cyber-Bystanders on Social Networking Sites

Directory of Open Access Journals (Sweden)

Angel N. M. Leung

2018-04-01

Full Text Available The present study tested how exposure to two types of responses to a hypothetical simulated Facebook setting influenced cyber-bystanders’ perceived control and normative beliefs using a 4 cyberbully-victim group (pure cyberbullies, non-involved, pure cyberbullied victims, and cyberbullied-victims × 2 condition (offend vs. defend experimental design. 203 Hong Kong Chinese secondary school and university students (132 females, 71 males; 12 to 28; M = 16.70; SD = 3.03 years old were randomly assigned into one of two conditions. Results showed that participants’ involvement in cyberbullying significantly related to their control beliefs about bully and victim assisting behaviors, while exposure to the two different conditions (offend vs. defend comments was related to both their control and normative beliefs. In general, the defend condition promoted higher control beliefs to help the victims and promoted higher normative beliefs to help the victims. Regardless of their past involvement in cyberbullying and exposure to offend vs. defend conditions, both cyber-bullies and cyber-victims were more inclined to demonstrate normative beliefs to help victims than to assist bullies. These results have implications for examining environmental influences in predicting bystander behaviors in cyberbullying contexts, and for creating a positive environment to motivate adolescents to become “upstanders” in educational programs to combat cyberbullying.

You Are What You Read: The Belief Systems of Cyber-Bystanders on Social Networking Sites

Science.gov (United States)

Leung, Angel N. M.; Wong, Natalie; Farver, JoAnn M.

2018-01-01

The present study tested how exposure to two types of responses to a hypothetical simulated Facebook setting influenced cyber-bystanders’ perceived control and normative beliefs using a 4 cyberbully-victim group (pure cyberbullies, non-involved, pure cyberbullied victims, and cyberbullied-victims) × 2 condition (offend vs. defend) experimental design. 203 Hong Kong Chinese secondary school and university students (132 females, 71 males; 12 to 28; M = 16.70; SD = 3.03 years old) were randomly assigned into one of two conditions. Results showed that participants’ involvement in cyberbullying significantly related to their control beliefs about bully and victim assisting behaviors, while exposure to the two different conditions (offend vs. defend comments) was related to both their control and normative beliefs. In general, the defend condition promoted higher control beliefs to help the victims and promoted higher normative beliefs to help the victims. Regardless of their past involvement in cyberbullying and exposure to offend vs. defend conditions, both cyber-bullies and cyber-victims were more inclined to demonstrate normative beliefs to help victims than to assist bullies. These results have implications for examining environmental influences in predicting bystander behaviors in cyberbullying contexts, and for creating a positive environment to motivate adolescents to become “upstanders” in educational programs to combat cyberbullying. PMID:29740362

Bayesian Belief Networks (BBN) and Expert Systems for supporting model based sensor fault detection analysis of smart building systems

NARCIS (Netherlands)

Schagen, J.D.; Taal, A.; Itard, L.C.M.; Heiselberg, Per Kvols

2016-01-01

The Hague University in Delft uses an advanced climate control system. All sensors and actuators are monitored and deviations from the sensor data are reported daily. The building manager will have to combine the information from the sensor data in order to draw the right conclusions. In this paper,

Illness beliefs and the sociocultural context of diabetes self-management in British South Asians: a mixed methods study.

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Patel, Neesha R; Chew-Graham, Carolyn; Bundy, Christine; Kennedy, Anne; Blickem, Christian; Reeves, David

2015-05-10

British South Asians have a higher incidence of diabetes and poorer health outcomes compared to the general UK population. Beliefs about diabetes are known to play an important role in self-management, yet little is known about the sociocultural context in shaping beliefs. This study aimed to explore the influence of sociocultural context on illness beliefs and diabetes self-management in British South Asians. A mixed methods approach was used. 67 participants recruited using random and purposive sampling, completed a questionnaire measuring illness beliefs, fatalism, health outcomes and demographics; 37 participants completed a social network survey interview and semi-structured interviews. Results were analysed using SPSS and thematic analysis. Quantitative data found certain social network characteristics (emotional and illness work) were related to perceived concern, emotional distress and health outcomes (p work remained a significant predictor of perceived concern and emotional distress related to diabetes (p culturally appropriate interventions to modify beliefs and support self-management in this population.

Deep Belief Networks Based Toponym Recognition for Chinese Text

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Shu Wang

2018-06-01

Full Text Available In Geographical Information Systems, geo-coding is used for the task of mapping from implicitly geo-referenced data to explicitly geo-referenced coordinates. At present, an enormous amount of implicitly geo-referenced information is hidden in unstructured text, e.g., Wikipedia, social data and news. Toponym recognition is the foundation of mining this useful geo-referenced information by identifying words as toponyms in text. In this paper, we propose an adapted toponym recognition approach based on deep belief network (DBN by exploring two key issues: word representation and model interpretation. A Skip-Gram model is used in the word representation process to represent words with contextual information that are ignored by current word representation models. We then determine the core hyper-parameters of the DBN model by illustrating the relationship between the performance and the hyper-parameters, e.g., vector dimensionality, DBN structures and probability thresholds. The experiments evaluate the performance of the Skip-Gram model implemented by the Word2Vec open-source tool, determine stable hyper-parameters and compare our approach with a conditional random field (CRF based approach. The experimental results show that the DBN model outperforms the CRF model with smaller corpus. When the corpus size is large enough, their statistical metrics become approaching. However, their recognition results express differences and complementarity on different kinds of toponyms. More importantly, combining their results can directly improve the performance of toponym recognition relative to their individual performances. It seems that the scale of the corpus has an obvious effect on the performance of toponym recognition. Generally, there is no adequate tagged corpus on specific toponym recognition tasks, especially in the era of Big Data. In conclusion, we believe that the DBN-based approach is a promising and powerful method to extract geo

An fMRI study on the comparison of different types of false belief reasoning: False belief-based emotion and behavior attribution.

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Döhnel, Katrin; Schuwerk, Tobias; Sodian, Beate; Hajak, Göran; Rupprecht, Rainer; Sommer, Monika

2017-12-01

False belief (FB) reasoning is a key Theory of Mind (ToM) competence. By 4 years of age, children understand that a person's behavior can be based on a FB about reality. Children cannot understand that a person's emotion can also be based on a FB before the age of six. In order to generate hypothesis on basic processes distinguishing these two types of belief reasoning, the present functional magnetic resonance imaging study in adults directly compares functional activity associated with these two FB tasks. Both tasks were associated with activity in the ToM network including the medial prefrontal cortex and the left temporo-parietal junction. Differential activity was observed in the anterior dorsolateral prefrontal cortex for FB-based emotion relative to behavior attribution. Contrary to FB behavior attribution, FB-based emotion attribution requires the processing of two different mental states: a belief and an emotion and their relation to each other. The activity pattern may reflect the differential demands on cognitive processes associated with the two different belief-based attribution processes. These results shed new light on the still ongoing debate about the nature of the developmental lag between the two FB tasks.

Global Diversity and Local Consensus in Status Beliefs : The Role of Network Clustering and Resistance to Belief Change

NARCIS (Netherlands)

Grow, André; Flache, Andreas; Wittek, Rafael

2017-01-01

Formal models of status construction theory suggest that beliefs about the relative social worth and competence of members of different social groups can emerge from face-to-face interactions in task-focused groups and eventually become consensual in large populations. We propose two extensions of

Generalized belief propagation on tree robust structured region graphs

NARCIS (Netherlands)

Gelfand, A.E.; Welling, M.; Murphy, K.; de Freitas, N.

2012-01-01

This paper provides some new guidance in the construction of region graphs for Generalized Belief Propagation (GBP). We connect the problem of choosing the outer regions of a LoopStructured Region Graph (SRG) to that of finding a fundamental cycle basis of the corresponding Markov network. We also

[French validation of the Revised Paranormal Belief Scale].

Science.gov (United States)

Bouvet, R; Djeriouat, H; Goutaudier, N; Py, J; Chabrol, H

2014-09-01

For the last decades, many researchers have focused on paranormal beliefs. Beliefs in the existence of paranormal phenomena would be common and studies conducted in westernized countries have highlighted a high prevalence of individuals believing in the existence of such phenomena. Tobacyk and Milford (1984) developed the Revised Paranormal Belief Scale (RPBS) for assessing beliefs in paranormal phenomena. This 26-item self-reported questionnaire, measuring beliefs in phenomena such as witchcraft or superstition, is one of the most widely used questionnaires to assess such beliefs. While studies focusing on paranormal beliefs tend to develop, there is no French self-report instrument to assess this construct. Researchers have tried to identify specific variables that might be linked to such beliefs, and some have focused on personalities of individuals who believe in the paranormal. Schizotypy has been reported to be significantly and positively correlated with paranormal beliefs. The aim of this study was a) to validate the French version of the RPBS and b) to explore the relationship between Schizotypal Personality Disorder traits and paranormal beliefs. After being recruited using the Internet and social networks (e.g. facebook), a sample of 313 participants (mean [SD] age=31.12 [11.62]; range 18-58years) completed the Schizotypal Personality Questionnaire (SPQ-B), assessing Schizotypal Personality Disorder traits and the Revised Paranormal Belief Scale assessing paranormal beliefs. Confirmatory factor analysis (CFA) was conducted to test the proposed 7-factor structure of the RPB developed by Tobacyk. Several adjustment indices were used to evaluate the model. As the first model did not fit the original one, others models were tested. Our findings indicated that a seven-factor solution, excluding 2 items, best described the item structure: (1) spiritualism, (2) superstition, (3) witchcraft, (4) precognition, (5) traditional religious belief, (6) psi, (7) and

The Main Path to C, N, O Elements in Big Bang Nucleosynthesis

International Nuclear Information System (INIS)

Su-Qing, Hou; Kai-Su, Wu; Yong-Shou, Chen; Neng-Chuan, Shu; Zhi-Hong, Li

2010-01-01

The production of C, N, O elements in a standard big bang nucleosynthesis scenario is investigated. Using the up-to-date data of nuclear reactions in BBN, in particular the 8 Li (n,γ) 9 Li which has been measured in China Institute of Atomic Energy, a full nucleosynthesis network calculation of BBN is carried out. Our calculation results show that the abundance of 12 C is increased for an order of magnitude after addition of the reaction chain 8 Li(n,γ) 9 Li(α,n) 12 B(β) 12 C, which was neglected in previous studies. We find that this sequence provides the main channel to convert the light elements into C, N, O in standard BBN. (nuclear physics)

Ontological confusions but not mentalizing abilities predict religious belief, paranormal belief, and belief in supernatural purpose.

Science.gov (United States)

Lindeman, Marjaana; Svedholm-Häkkinen, Annika M; Lipsanen, Jari

2015-01-01

The current research tested the hypothesis that the abilities for understanding other people's minds give rise to the cognitive biases that underlie supernatural beliefs. We used structural equation modeling (N=2789) to determine the roles of various mentalizing tendencies, namely self-reported affective and cognitive empathy (i.e., mind reading), actual cognitive and affective empathic abilities, hyper-empathizing, and two cognitive biases (core ontological confusions and promiscuous teleology) in giving rise to supernatural beliefs. Support for a path from mentalizing abilities through cognitive biases to supernatural beliefs was weak. The relationships of mentalizing abilities with supernatural beliefs were also weak, and these relationships were not substantially mediated by cognitive biases. Core ontological confusions emerged as the best predictor, while promiscuous teleology predicted only a small proportion of variance. The results were similar for religious beliefs, paranormal beliefs, and for belief in supernatural purpose. Copyright © 2014 Elsevier B.V. All rights reserved.

Lateralized direct and indirect semantic priming effects in subjects with paranormal experiences and beliefs.

Science.gov (United States)

Pizzagalli, D; Lehmann, D; Brugger, P

2001-01-01

The present investigation tested the hypothesis that, as an aspect of schizotypal thinking, the formation of paranormal beliefs was related to spreading activation characteristics within semantic networks. From a larger student population (n = 117) prescreened for paranormal belief, 12 strong believers and 12 strong disbelievers (all women) were invited for a lateralized semantic priming task with directly and indirectly related prime-target pairs. Believers showed stronger indirect (but not direct) semantic priming effects than disbelievers after left (but not right) visual field stimulation, indicating faster appreciation of distant semantic relations specifically by the right hemisphere, reportedly specialized in coarse rather than focused semantic processing. These results are discussed in the light of recent findings in schizophrenic patients with thought disorders. They suggest that a disinhibition with semantic networks may underlie the formation of paranormal belief. The potential usefulness of work with healthy subjects for neuropsychiatric research is stressed. Copyright 2001 S. Karger AG, Basel

The Relationship among Pre-Service EFL Teachers' Beliefs about Language Learning, Pedagogical Beliefs, and Beliefs about ICT Integration

Science.gov (United States)

Inayati, Dian; Emaliana, Ive

2017-01-01

This paper elucidates the relationship among pre-service teachers' beliefs about language learning, pedagogical beliefs, and beliefs about ICT Integration through survey methodology. This study employed a quantitative approach, particularly a correlational relationship to investigate the relationships among beliefs about language learning,…

A Bayesian Framework for False Belief Reasoning in Children: A Rational Integration of Theory-Theory and Simulation Theory.

Science.gov (United States)

Asakura, Nobuhiko; Inui, Toshio

2016-01-01

Two apparently contrasting theories have been proposed to account for the development of children's theory of mind (ToM): theory-theory and simulation theory. We present a Bayesian framework that rationally integrates both theories for false belief reasoning. This framework exploits two internal models for predicting the belief states of others: one of self and one of others. These internal models are responsible for simulation-based and theory-based reasoning, respectively. The framework further takes into account empirical studies of a developmental ToM scale (e.g., Wellman and Liu, 2004): developmental progressions of various mental state understandings leading up to false belief understanding. By representing the internal models and their interactions as a causal Bayesian network, we formalize the model of children's false belief reasoning as probabilistic computations on the Bayesian network. This model probabilistically weighs and combines the two internal models and predicts children's false belief ability as a multiplicative effect of their early-developed abilities to understand the mental concepts of diverse beliefs and knowledge access. Specifically, the model predicts that children's proportion of correct responses on a false belief task can be closely approximated as the product of their proportions correct on the diverse belief and knowledge access tasks. To validate this prediction, we illustrate that our model provides good fits to a variety of ToM scale data for preschool children. We discuss the implications and extensions of our model for a deeper understanding of developmental progressions of children's ToM abilities.

Suppressed Belief

Directory of Open Access Journals (Sweden)

Komarine Romdenh-Romluc

2009-12-01

Full Text Available Moran’s revised conception of conscious belief requires us to reconceptualise suppressed belief. The work of Merleau-Ponty offers a way to do this. His account of motor-skills allows us to understand suppressed beliefs as pre-reflective ways of dealing with the world.

Can Cultural Worldviews Influence Network Composition?

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Vaisey, Stephen; Lizardo, Omar

2010-01-01

Most sociological research assumes that social network composition shapes individual beliefs. Network theory and research has not adequately considered that internalized cultural worldviews might affect network composition. Drawing on a synthetic, dual-process theory of culture and two waves of nationally-representative panel data, this article…

Prediction Markets and Beliefs about Climate: Results from Agent-Based Simulations

Science.gov (United States)

Gilligan, J. M.; John, N. J.; van der Linden, M.

2015-12-01

Climate scientists have long been frustrated by persistent doubts a large portion of the public expresses toward the scientific consensus about anthropogenic global warming. The political and ideological polarization of this doubt led Vandenbergh, Raimi, and Gilligan [1] to propose that prediction markets for climate change might influence the opinions of those who mistrust the scientific community but do trust the power of markets.We have developed an agent-based simulation of a climate prediction market in which traders buy and sell future contracts that will pay off at some future year with a value that depends on the global average temperature at that time. The traders form a heterogeneous population with different ideological positions, different beliefs about anthropogenic global warming, and different degrees of risk aversion. We also vary characteristics of the market, including the topology of social networks among the traders, the number of traders, and the completeness of the market. Traders adjust their beliefs about climate according to the gains and losses they and other traders in their social network experience. This model predicts that if global temperature is predominantly driven by greenhouse gas concentrations, prediction markets will cause traders' beliefs to converge toward correctly accepting anthropogenic warming as real. This convergence is largely independent of the structure of the market and the characteristics of the population of traders. However, it may take considerable time for beliefs to converge. Conversely, if temperature does not depend on greenhouse gases, the model predicts that traders' beliefs will not converge. We will discuss the policy-relevance of these results and more generally, the use of agent-based market simulations for policy analysis regarding climate change, seasonal agricultural weather forecasts, and other applications.[1] MP Vandenbergh, KT Raimi, & JM Gilligan. UCLA Law Rev. 61, 1962 (2014).

Classification of Exacerbation Frequency in the COPDGene Cohort Using Deep Learning with Deep Belief Networks.

Science.gov (United States)

Ying, Jun; Dutta, Joyita; Guo, Ning; Hu, Chenhui; Zhou, Dan; Sitek, Arkadiusz; Li, Quanzheng

2016-12-21

This study aims to develop an automatic classifier based on deep learning for exacerbation frequency in patients with chronic obstructive pulmonary disease (COPD). A threelayer deep belief network (DBN) with two hidden layers and one visible layer was employed to develop classification models and the models' robustness to exacerbation was analyzed. Subjects from the COPDGene cohort were labeled with exacerbation frequency, defined as the number of exacerbation events per year. 10,300 subjects with 361 features each were included in the analysis. After feature selection and parameter optimization, the proposed classification method achieved an accuracy of 91.99%, using a 10-fold cross validation experiment. The analysis of DBN weights showed that there was a good visual spatial relationship between the underlying critical features of different layers. Our findings show that the most sensitive features obtained from the DBN weights are consistent with the consensus showed by clinical rules and standards for COPD diagnostics. We thus demonstrate that DBN is a competitive tool for exacerbation risk assessment for patients suffering from COPD.

Deep learning architecture for iris recognition based on optimal Gabor filters and deep belief network

Science.gov (United States)

He, Fei; Han, Ye; Wang, Han; Ji, Jinchao; Liu, Yuanning; Ma, Zhiqiang

2017-03-01

Gabor filters are widely utilized to detect iris texture information in several state-of-the-art iris recognition systems. However, the proper Gabor kernels and the generative pattern of iris Gabor features need to be predetermined in application. The traditional empirical Gabor filters and shallow iris encoding ways are incapable of dealing with such complex variations in iris imaging including illumination, aging, deformation, and device variations. Thereby, an adaptive Gabor filter selection strategy and deep learning architecture are presented. We first employ particle swarm optimization approach and its binary version to define a set of data-driven Gabor kernels for fitting the most informative filtering bands, and then capture complex pattern from the optimal Gabor filtered coefficients by a trained deep belief network. A succession of comparative experiments validate that our optimal Gabor filters may produce more distinctive Gabor coefficients and our iris deep representations be more robust and stable than traditional iris Gabor codes. Furthermore, the depth and scales of the deep learning architecture are also discussed.

Prediction of maize phenotype based on whole-genome single nucleotide polymorphisms using deep belief networks

Science.gov (United States)

Rachmatia, H.; Kusuma, W. A.; Hasibuan, L. S.

2017-05-01

Selection in plant breeding could be more effective and more efficient if it is based on genomic data. Genomic selection (GS) is a new approach for plant-breeding selection that exploits genomic data through a mechanism called genomic prediction (GP). Most of GP models used linear methods that ignore effects of interaction among genes and effects of higher order nonlinearities. Deep belief network (DBN), one of the architectural in deep learning methods, is able to model data in high level of abstraction that involves nonlinearities effects of the data. This study implemented DBN for developing a GP model utilizing whole-genome Single Nucleotide Polymorphisms (SNPs) as data for training and testing. The case study was a set of traits in maize. The maize dataset was acquisitioned from CIMMYT’s (International Maize and Wheat Improvement Center) Global Maize program. Based on Pearson correlation, DBN is outperformed than other methods, kernel Hilbert space (RKHS) regression, Bayesian LASSO (BL), best linear unbiased predictor (BLUP), in case allegedly non-additive traits. DBN achieves correlation of 0.579 within -1 to 1 range.

The Origins of Belief Representation: Monkeys Fail to Automatically Represent Others’ Beliefs

Science.gov (United States)

Martin, Alia; Santos, Laurie R.

2014-01-01

Young infants’ successful performance on false belief tasks has led several researchers to argue that there may be a core knowledge system for representing the beliefs of other agents, emerging early in human development and constraining automatic belief processing into adulthood. One way to investigate this purported core belief representation system is to examine whether non-human primates share such a system. Although non-human primates have historically performed poorly on false belief tasks that require executive function capacities, little work has explored how primates perform on more automatic measures of belief processing. To get at this issue, we modified Kovács et al. (2010)’s test of automatic belief representation to examine whether one non-human primate species—the rhesus macaque (Macaca mulatta)—is automatically influenced by another agent’s beliefs when tracking an object’s location. Monkeys saw an event in which a human agent watched an apple move back and forth between two boxes and an outcome in which one box was revealed to be empty. By occluding segments of the apple’s movement from either the monkey or the agent, we manipulated both the monkeys’ belief (true or false) and agent’s belief (true or false) about the final location of the apple. We found that monkeys looked longer at events that violated their own beliefs than at events that were consistent with their beliefs. In contrast to human infants, however, monkeys’ expectations were not influenced by another agent’s beliefs, suggesting that belief representation may be an aspect of core knowledge unique to humans. PMID:24374209

Conscious Belief

Directory of Open Access Journals (Sweden)

David Pitt

2016-04-01

Full Text Available Tim Crane maintains that beliefs cannot be conscious because they persist in the absence of consciousness. Conscious judgments can share their contents with beliefs, and their occurrence can be evidence for what one believes; but they cannot be beliefs, because they don’t persist. I challenge Crane’s premise that belief attributions to the temporarily unconscious are literally true. To say of an unconscious agent that she believes that p is like saying that she sings well. To say she sings well is to say that when she sings, her singing is good. To say that she believes that p is (roughly to say that when she consciously considers the content that p she consciously affirms (believes it. I also argue that the phenomenal view of intentional content Crane appears to endorse prima facie commits him to the view, at least controversial, perhaps incoherent, that there is unconscious phenomenology (the intentional contents of unconscious beliefs.

Modeling the Evolution of Beliefs Using an Attentional Focus Mechanism.

Directory of Open Access Journals (Sweden)

Dimitrije Marković

2015-10-01

Full Text Available For making decisions in everyday life we often have first to infer the set of environmental features that are relevant for the current task. Here we investigated the computational mechanisms underlying the evolution of beliefs about the relevance of environmental features in a dynamical and noisy environment. For this purpose we designed a probabilistic Wisconsin card sorting task (WCST with belief solicitation, in which subjects were presented with stimuli composed of multiple visual features. At each moment in time a particular feature was relevant for obtaining reward, and participants had to infer which feature was relevant and report their beliefs accordingly. To test the hypothesis that attentional focus modulates the belief update process, we derived and fitted several probabilistic and non-probabilistic behavioral models, which either incorporate a dynamical model of attentional focus, in the form of a hierarchical winner-take-all neuronal network, or a diffusive model, without attention-like features. We used Bayesian model selection to identify the most likely generative model of subjects' behavior and found that attention-like features in the behavioral model are essential for explaining subjects' responses. Furthermore, we demonstrate a method for integrating both connectionist and Bayesian models of decision making within a single framework that allowed us to infer hidden belief processes of human subjects.

A Cognitive Perspective on Policy Implementation : Reform Beliefs, Sensemaking, and Social Networks

NARCIS (Netherlands)

Siciliano, Michael D.; Moolenaar, Nienke M.; Daly, Alan J.; Liou, Yi Hwa

2017-01-01

Utilizing a cognitive perspective, this article examines the social processes through which teachers come to understand the Common Core State Standards. The authors begin by identifying three beliefs that have important implications for policy implementation: self-efficacy, resource adequacy, and

Convolutional deep belief network with feature encoding for classification of neuroblastoma histological images

Directory of Open Access Journals (Sweden)

Soheila Gheisari

2018-01-01

Full Text Available Background: Neuroblastoma is the most common extracranial solid tumor in children younger than 5 years old. Optimal management of neuroblastic tumors depends on many factors including histopathological classification. The gold standard for classification of neuroblastoma histological images is visual microscopic assessment. In this study, we propose and evaluate a deep learning approach to classify high-resolution digital images of neuroblastoma histology into five different classes determined by the Shimada classification. Subjects and Methods: We apply a combination of convolutional deep belief network (CDBN with feature encoding algorithm that automatically classifies digital images of neuroblastoma histology into five different classes. We design a three-layer CDBN to extract high-level features from neuroblastoma histological images and combine with a feature encoding model to extract features that are highly discriminative in the classification task. The extracted features are classified into five different classes using a support vector machine classifier. Data: We constructed a dataset of 1043 neuroblastoma histological images derived from Aperio scanner from 125 patients representing different classes of neuroblastoma tumors. Results: The weighted average F-measure of 86.01% was obtained from the selected high-level features, outperforming state-of-the-art methods. Conclusion: The proposed computer-aided classification system, which uses the combination of deep architecture and feature encoding to learn high-level features, is highly effective in the classification of neuroblastoma histological images.

Integration of biological, economic and sociological knowledge by Bayesian belief networks: the interdisciplinary evaluation of potential management plans for Baltic salmon

DEFF Research Database (Denmark)

Levontin, Polina; Kulmala, Soile; Haapasaari, Päivi Elisabet

2011-01-01

There is a growing need to evaluate fisheries management plans in a comprehensive interdisciplinary context involving stakeholders. The use of a probabilistic management model to evaluate potential management plans for Baltic salmon fisheries is demonstrated. The analysis draws on several scientific...... studies: a biological stock assessment with integrated economic analysis of the commercial fisheries, an evaluation of recreational fisheries, and a sociological study aimed at understanding stakeholder perspectives and potential commitment to alternative management plans. A Bayesian belief network is used...... is highlighted by modelling the link between commitment and implementation success. Such analyses, relying on prior knowledge, can forewarn of the consequences of management choices before they are implemented...

Introducing the modified paranormal belief scale: distinguishing between classic paranormal beliefs, religious paranormal beliefs and conventional religiosity among undergraduates in Northern Ireland and Wales

OpenAIRE

Williams, Emyr; Francis, Leslie J.; Lewis, Christopher Alan

2009-01-01

Previous empirical studies concerned with the association between paranormal beliefs and conventional religiosity have produced conflicting evidence. Drawing on Rice's (2003) distinction between classic paranormal beliefs and religious paranormal beliefs, the present study proposed a modified form of the Tobacyk Revised Paranormal Belief Scale to produce separate scores for these two forms of paranormal belief, styled 'religious paranormal beliefs' and 'classic paranormal beliefs'. Data provi...

The Relationships among Chinese Practicing Teachers' Epistemic Beliefs, Pedagogical Beliefs and Their Beliefs about the Use of ICT

Science.gov (United States)

Deng, Feng; Chai, Ching Sing; Tsai, Chin-Chung; Lee, Min-Hsien

2014-01-01

This study aimed to investigate the relationships among practicing teachers' epistemic beliefs, pedagogical beliefs and their beliefs about the use of ICT through survey methodology. Participants were 396 high school practicing teachers from mainland China. The path analysis results analyzed via structural equation modelling technique indicated…

Recursive belief manipulation and second-order false-beliefs

DEFF Research Database (Denmark)

Braüner, Torben; Blackburn, Patrick Rowan; Polyanskaya, Irina

2016-01-01

it indicate that a more fundamental *conceptual change* has taken place? In this paper we extend Braüner's hybrid-logical analysis of first-order false-belief tasks to the second-order case, and argue that our analysis supports a version of the conceptual change position.......The literature on first-order false-belief is extensive, but less is known about the second-order case. The ability to handle second-order false-beliefs correctly seems to mark a cognitively significant step, but what is its status? Is it an example of *complexity only* development, or does...

Tunable Sparse Network Coding for Multicast Networks

DEFF Research Database (Denmark)

Feizi, Soheil; Roetter, Daniel Enrique Lucani; Sørensen, Chres Wiant

2014-01-01

This paper shows the potential and key enabling mechanisms for tunable sparse network coding, a scheme in which the density of network coded packets varies during a transmission session. At the beginning of a transmission session, sparsely coded packets are transmitted, which benefits decoding...... complexity. At the end of a transmission, when receivers have accumulated degrees of freedom, coding density is increased. We propose a family of tunable sparse network codes (TSNCs) for multicast erasure networks with a controllable trade-off between completion time performance to decoding complexity...... a mechanism to perform efficient Gaussian elimination over sparse matrices going beyond belief propagation but maintaining low decoding complexity. Supporting simulation results are provided showing the trade-off between decoding complexity and completion time....

Combining Volcano Monitoring Timeseries Analyses with Bayesian Belief Networks to Update Hazard Forecast Estimates

Science.gov (United States)

Odbert, Henry; Hincks, Thea; Aspinall, Willy

2015-04-01

Volcanic hazard assessments must combine information about the physical processes of hazardous phenomena with observations that indicate the current state of a volcano. Incorporating both these lines of evidence can inform our belief about the likelihood (probability) and consequences (impact) of possible hazardous scenarios, forming a basis for formal quantitative hazard assessment. However, such evidence is often uncertain, indirect or incomplete. Approaches to volcano monitoring have advanced substantially in recent decades, increasing the variety and resolution of multi-parameter timeseries data recorded at volcanoes. Interpreting these multiple strands of parallel, partial evidence thus becomes increasingly complex. In practice, interpreting many timeseries requires an individual to be familiar with the idiosyncrasies of the volcano, monitoring techniques, configuration of recording instruments, observations from other datasets, and so on. In making such interpretations, an individual must consider how different volcanic processes may manifest as measureable observations, and then infer from the available data what can or cannot be deduced about those processes. We examine how parts of this process may be synthesised algorithmically using Bayesian inference. Bayesian Belief Networks (BBNs) use probability theory to treat and evaluate uncertainties in a rational and auditable scientific manner, but only to the extent warranted by the strength of the available evidence. The concept is a suitable framework for marshalling multiple strands of evidence (e.g. observations, model results and interpretations) and their associated uncertainties in a methodical manner. BBNs are usually implemented in graphical form and could be developed as a tool for near real-time, ongoing use in a volcano observatory, for example. We explore the application of BBNs in analysing volcanic data from the long-lived eruption at Soufriere Hills Volcano, Montserrat. We show how our method

Religious beliefs are factual beliefs: Content does not correlate with context sensitivity.

Science.gov (United States)

Levy, Neil

2017-04-01

Neil Van Leeuwen argues that religious beliefs are not factual beliefs: typically, at least, they are attitudes of a different type. He argues that they exhibit much more sensitivity to context than factual beliefs: outside of contexts in which they are salient, they do not govern behaviour or inference, or provide background assumptions for cognition. This article surveys a large range of data to show that the kind of context sensitivity that Van Leeuwen thinks is the province of religious beliefs does not correlate with belief content. Beliefs about matters of fact beyond the theological realm exhibit this kind of sensitivity too. Conversely, theological and supernatural beliefs often guide behaviour across contexts. It is the intuitiveness of representations across contexts that predicts context (in)sensitivity, and intuitiveness is powerfully influenced by processing fluency. Fluency, in turn, is sensitive to cues that vary across contexts. Copyright © 2017 Elsevier B.V. All rights reserved.

Evolution of Religious Beliefs

CERN Multimedia

CERN. Geneva

2009-01-01

Humans may be distinguished from all other animals in having beliefs about the causal interaction of physical objects. Causal beliefs are a developmental primitive in human children; animals, by contrast, have very few causal beliefs. The origin of human causal beliefs comes from the evolutionary advantage it gave in relation to complex tool making and use. Causal beliefs gave rise religion and mystical thinking as our ancestors wanted to know the causes of events that affected their lives.

Social Networks and Parent Motivational Beliefs: Evidence from an Urban School District

Science.gov (United States)

Curry, Katherine A.; Jean-Marie, Gaëtane; Adams, Curt M.

2016-01-01

Background: Despite devotion of substantial resources and effort to increase parent/school partnerships, gaps remain between policy rhetoric and practice, especially in high-poverty communities. Current research focuses on parent involvement or effects of parent motivational beliefs on parent choice for behavior; however, it does not address the…

Revisiting “What They Think”: Adolescent Drinking and the Importance of Peer Beliefs

Science.gov (United States)

Ragan, Daniel T.

2014-01-01

The association between delinquent peers and delinquent behavior is among the most consistent findings in the criminological literature, and a number of recent studies have raised the standards for determining the nature and extent of peer influence. Despite these advances, however, key questions about how deviant behavior is socially transmitted remain unresolved. In particular, much of the research examining peer influence is limited to peer behavior, despite a rich literature supporting the salience of beliefs, such as expectations and moral approval, in shaping behaviors. The current study takes advantage of advances in the modeling of peer influence and selection processes to re-examine the contributions of peer beliefs and behaviors to adolescent drinking. I employ longitudinal social network analysis to examine how peers contribute to the complex interplay between deviant beliefs and behaviors. I find evidence that beliefs related to peer drinking have both a direct and indirect impact on behavior and also play an important role in the friendship selection process. These results highlight the importance of understanding how peers influence deviant behavior and suggest that peer beliefs are an important part of this relationship. PMID:25382862

The moderating role of rational beliefs in the relationship between irrational beliefs and posttraumatic stress symptomology.

Science.gov (United States)

Hyland, Philip; Shevlin, Mark; Adamson, Gary; Boduszek, Daniel

2014-05-01

Rational Emotive Behaviour Therapy (REBT) assumes that rational beliefs act as cognitive protective factors against the development of psychopathology; however little empirical evidence exists regarding the nature of the possible protective effects that they offer. The current study investigates whether rational beliefs moderate the impact of irrational beliefs on posttraumatic stress symptomology (PTS). Three hundred and thirteen active law enforcement, military, and related emergency service personnel took part in the current study. Sequential moderated multiple regression analysis was employed to investigate: (i) the direct impact of irrational beliefs on PTS; (ii) the direct impact of rational beliefs on PTS; (iii) the moderating effects of rational beliefs in the relationship between irrational beliefs and PTS. The irrational beliefs predicted by REBT theory emerged as critical predictors of PTS symptomology, in particular Depreciation beliefs. Rational beliefs (Preferences, and Acceptance beliefs) had a direct, negative impact on levels of PTS, and Acceptance beliefs moderated the impact of Catastrophizing beliefs on PTS. Irrational beliefs are important cognitive vulnerability factors in symptoms of PTS, while rational beliefs (Acceptance) appear to have a protective role in the emergence of PTS symptoms, both directly and by moderating the impact of Catastrophizing beliefs.

Behaviour in O of the Neural Networks Training Cost

DEFF Research Database (Denmark)

Goutte, Cyril

1998-01-01

We study the behaviour in zero of the derivatives of the cost function used when training non-linear neural networks. It is shown that a fair number offirst, second and higher order derivatives vanish in zero, validating the belief that 0 is a peculiar and potentially harmful location. These calc......We study the behaviour in zero of the derivatives of the cost function used when training non-linear neural networks. It is shown that a fair number offirst, second and higher order derivatives vanish in zero, validating the belief that 0 is a peculiar and potentially harmful location....... These calculations arerelated to practical and theoretical aspects of neural networks training....

Belief in complementary and alternative medicine is related to age and paranormal beliefs in adults.

Science.gov (United States)

Van den Bulck, Jan; Custers, Kathleen

2010-04-01

The use of complementary and alternative medicine (CAM) is widespread, even among people who use conventional medicine. Positive beliefs about CAM are common among physicians and medical students. Little is known about the beliefs regarding CAM among the general public. Among science students, belief in CAM was predicted by belief in the paranormal. In a cross-sectional study, 712 randomly selected adults (>18 years old) responded to the CAM Health Belief Questionnaire (CHBQ) and a paranormal beliefs scale. CAM beliefs were very prevalent in this sample of adult Flemish men and women. Zero-order correlations indicated that belief in CAM was associated with age (r = 0.173 P paranormal belief (r = 0.365 P paranormal. Paranormal beliefs accounted for 14% of the variance of the CAM beliefs (regression coefficient: 0.376; 95%: CI 0.30-0.44). The level of education (regression coefficient: 0.06; 95% CI: -0.014-0.129) and social desirability (regression coefficient: -0.023; 95% CI: -0.048-0.026) did not make a significant contribution to the explained variance (paranormal beliefs.

Processing of false belief passages during natural story comprehension: An fMRI study.

Science.gov (United States)

Kandylaki, Katerina D; Nagels, Arne; Tune, Sarah; Wiese, Richard; Bornkessel-Schlesewsky, Ina; Kircher, Tilo

2015-11-01

The neural correlates of theory of mind (ToM) are typically studied using paradigms which require participants to draw explicit, task-related inferences (e.g., in the false belief task). In a natural setup, such as listening to stories, false belief mentalizing occurs incidentally as part of narrative processing. In our experiment, participants listened to auditorily presented stories with false belief passages (implicit false belief processing) and immediately after each story answered comprehension questions (explicit false belief processing), while neural responses were measured with functional magnetic resonance imaging (fMRI). All stories included (among other situations) one false belief condition and one closely matched control condition. For the implicit ToM processing, we modeled the hemodynamic response during the false belief passages in the story and compared it to the hemodynamic response during the closely matched control passages. For implicit mentalizing, we found activation in typical ToM processing regions, that is the angular gyrus (AG), superior medial frontal gyrus (SmFG), precuneus (PCUN), middle temporal gyrus (MTG) as well as in the inferior frontal gyrus (IFG) billaterally. For explicit ToM, we only found AG activation. The conjunction analysis highlighted the left AG and MTG as well as the bilateral IFG as overlapping ToM processing regions for both implicit and explicit modes. Implicit ToM processing during listening to false belief passages, recruits the left SmFG and billateral PCUN in addition to the "mentalizing network" known form explicit processing tasks. © 2015 Wiley Periodicals, Inc.

Belief Elicitation in Experiments

DEFF Research Database (Denmark)

Blanco, Mariana; Engelmann, Dirk; Koch, Alexander

Belief elicitation in economics experiments usually relies on paying subjects according to the accuracy of stated beliefs in addition to payments for other decisions. Such incentives, however, allow risk-averse subjects to hedge with their stated beliefs against adverse outcomes of other decisions......-belief elicitation treatment using a financial investment frame, where hedging arguably would be most natural....

The neural correlates of religious and nonreligious belief.

Directory of Open Access Journals (Sweden)

Sam Harris

2009-10-01

Full Text Available While religious faith remains one of the most significant features of human life, little is known about its relationship to ordinary belief at the level of the brain. Nor is it known whether religious believers and nonbelievers differ in how they evaluate statements of fact. Our lab previously has used functional neuroimaging to study belief as a general mode of cognition [1], and others have looked specifically at religious belief [2]. However, no research has compared these two states of mind directly.We used functional magnetic resonance imaging (fMRI to measure signal changes in the brains of thirty subjects-fifteen committed Christians and fifteen nonbelievers-as they evaluated the truth and falsity of religious and nonreligious propositions. For both groups, and in both categories of stimuli, belief (judgments of "true" vs judgments of "false" was associated with greater signal in the ventromedial prefrontal cortex, an area important for self-representation [3], [4], [5], [6], emotional associations [7], reward [8], [9], [10], and goal-driven behavior [11]. This region showed greater signal whether subjects believed statements about God, the Virgin Birth, etc. or statements about ordinary facts. A comparison of both stimulus categories suggests that religious thinking is more associated with brain regions that govern emotion, self-representation, and cognitive conflict, while thinking about ordinary facts is more reliant upon memory retrieval networks.While religious and nonreligious thinking differentially engage broad regions of the frontal, parietal, and medial temporal lobes, the difference between belief and disbelief appears to be content-independent. Our study compares religious thinking with ordinary cognition and, as such, constitutes a step toward developing a neuropsychology of religion. However, these findings may also further our understanding of how the brain accepts statements of all kinds to be valid descriptions of the

Vehicle detection from very-high-resolution (VHR) aerial imagery using attribute belief propagation (ABP)

Science.gov (United States)

Wang, Yanli; Li, Ying; Zhang, Li; Huang, Yuchun

2016-10-01

With the popularity of very-high-resolution (VHR) aerial imagery, the shape, color, and context attribute of vehicles are better characterized. Due to the various road surroundings and imaging conditions, vehicle attributes could be adversely affected so that vehicle is mistakenly detected or missed. This paper is motivated to robustly extract the rich attribute feature for detecting the vehicles of VHR imagery under different scenarios. Based on the hierarchical component tree of vehicle context, attribute belief propagation (ABP) is proposed to detect salient vehicles from the statistical perspective. With the Max-tree data structure, the multi-level component tree around the road network is efficiently created. The spatial relationship between vehicle and its belonging context is established with the belief definition of vehicle attribute. To effectively correct single-level belief error, the inter-level belief linkages enforce consistency of belief assignment between corresponding components at different levels. ABP starts from an initial set of vehicle belief calculated by vehicle attribute, and then iterates through each component by applying inter-level belief passing until convergence. The optimal value of vehicle belief of each component is obtained via minimizing its belief function iteratively. The proposed algorithm is tested on a diverse set of VHR imagery acquired in the city and inter-city areas of the West and South China. Experimental results show that the proposed algorithm can detect vehicle efficiently and suppress the erroneous effectively. The proposed ABP framework is promising to robustly classify the vehicles from VHR Aerial imagery.

Designing neural networks that process mean values of random variables

International Nuclear Information System (INIS)

Barber, Michael J.; Clark, John W.

2014-01-01

We develop a class of neural networks derived from probabilistic models posed in the form of Bayesian networks. Making biologically and technically plausible assumptions about the nature of the probabilistic models to be represented in the networks, we derive neural networks exhibiting standard dynamics that require no training to determine the synaptic weights, that perform accurate calculation of the mean values of the relevant random variables, that can pool multiple sources of evidence, and that deal appropriately with ambivalent, inconsistent, or contradictory evidence. - Highlights: • High-level neural computations are specified by Bayesian belief networks of random variables. • Probability densities of random variables are encoded in activities of populations of neurons. • Top-down algorithm generates specific neural network implementation of given computation. • Resulting “neural belief networks” process mean values of random variables. • Such networks pool multiple sources of evidence and deal properly with inconsistent evidence

Designing neural networks that process mean values of random variables

Energy Technology Data Exchange (ETDEWEB)

Barber, Michael J. [AIT Austrian Institute of Technology, Innovation Systems Department, 1220 Vienna (Austria); Clark, John W. [Department of Physics and McDonnell Center for the Space Sciences, Washington University, St. Louis, MO 63130 (United States); Centro de Ciências Matemáticas, Universidade de Madeira, 9000-390 Funchal (Portugal)

2014-06-13

We develop a class of neural networks derived from probabilistic models posed in the form of Bayesian networks. Making biologically and technically plausible assumptions about the nature of the probabilistic models to be represented in the networks, we derive neural networks exhibiting standard dynamics that require no training to determine the synaptic weights, that perform accurate calculation of the mean values of the relevant random variables, that can pool multiple sources of evidence, and that deal appropriately with ambivalent, inconsistent, or contradictory evidence. - Highlights: • High-level neural computations are specified by Bayesian belief networks of random variables. • Probability densities of random variables are encoded in activities of populations of neurons. • Top-down algorithm generates specific neural network implementation of given computation. • Resulting “neural belief networks” process mean values of random variables. • Such networks pool multiple sources of evidence and deal properly with inconsistent evidence.

Indoor Positioning Using Nonparametric Belief Propagation Based on Spanning Trees

Directory of Open Access Journals (Sweden)

Savic Vladimir

2010-01-01

Full Text Available Nonparametric belief propagation (NBP is one of the best-known methods for cooperative localization in sensor networks. It is capable of providing information about location estimation with appropriate uncertainty and to accommodate non-Gaussian distance measurement errors. However, the accuracy of NBP is questionable in loopy networks. Therefore, in this paper, we propose a novel approach, NBP based on spanning trees (NBP-ST created by breadth first search (BFS method. In addition, we propose a reliable indoor model based on obtained measurements in our lab. According to our simulation results, NBP-ST performs better than NBP in terms of accuracy and communication cost in the networks with high connectivity (i.e., highly loopy networks. Furthermore, the computational and communication costs are nearly constant with respect to the transmission radius. However, the drawbacks of proposed method are a little bit higher computational cost and poor performance in low-connected networks.

Network dynamics of social influence in the wisdom of crowds.

Science.gov (United States)

Becker, Joshua; Brackbill, Devon; Centola, Damon

2017-06-27

A longstanding problem in the social, biological, and computational sciences is to determine how groups of distributed individuals can form intelligent collective judgments. Since Galton's discovery of the "wisdom of crowds" [Galton F (1907) Nature 75:450-451], theories of collective intelligence have suggested that the accuracy of group judgments requires individuals to be either independent, with uncorrelated beliefs, or diverse, with negatively correlated beliefs [Page S (2008) The Difference: How the Power of Diversity Creates Better Groups, Firms, Schools, and Societies ]. Previous experimental studies have supported this view by arguing that social influence undermines the wisdom of crowds. These results showed that individuals' estimates became more similar when subjects observed each other's beliefs, thereby reducing diversity without a corresponding increase in group accuracy [Lorenz J, Rauhut H, Schweitzer F, Helbing D (2011) Proc Natl Acad Sci USA 108:9020-9025]. By contrast, we show general network conditions under which social influence improves the accuracy of group estimates, even as individual beliefs become more similar. We present theoretical predictions and experimental results showing that, in decentralized communication networks, group estimates become reliably more accurate as a result of information exchange. We further show that the dynamics of group accuracy change with network structure. In centralized networks, where the influence of central individuals dominates the collective estimation process, group estimates become more likely to increase in error.

A study on quantitative V and V of safety-critical software

International Nuclear Information System (INIS)

Eom, H. S.; Kang, H. G.; Chang, S. C.; Ha, J. J.; Son, H. S.

2004-03-01

Recently practical needs have required quantitative features for the software reliability for Probabilistic Safety Assessment which is one of the important methods being used in assessing the overall safety of nuclear power plant. But the conventional assessment methods of software reliability could not provide enough information for PSA of NPP, therefore current assessments of a digital system which includes safety-critical software usually exclude the software part or use arbitrary values. This paper describes a Bayesian Belief Networks based method that models the rule-based qualitative software assessment method for a practical use and can produce quantitative results for PSA. The framework was constructed by utilizing BBN that can combine the qualitative and quantitative evidence relevant to the reliability of safety-critical software and can infer a conclusion in a formal and a quantitative way. The case study was performed by applying the method for assessing the quality of software requirement specification of safety-critical software that will be embedded in reactor protection system

Extreme Overvalued Beliefs: How Violent Extremist Beliefs Become "Normalized".

Science.gov (United States)

Rahman, Tahir

2018-01-12

Extreme overvalued beliefs (EOB) are rigidly held, non-deusional beliefs that are the motive behind most acts of terrorism and mass shootings. EOBs are differentiated from delusions and obsessions. The concept of an overvalued idea was first described by Wernicke and later applied to terrorism by McHugh. Our group of forensic psychiatrists (Rahman, Resnick, Harry) refined the definition as an aid in the differential diagnosis seen in acts of violence. The form and content of EOBs is discussed as well as group effects, conformity, and obedience to authority. Religious cults such as The People's Temple, Heaven's Gate, Aum Shinrikyo, and Islamic State (ISIS) and conspiracy beliefs such as assassinations, moon-hoax, and vaccine-induced autism beliefs are discussed using this construct. Finally, some concluding thoughts on countering violent extremism, including its online presence is discussed utilizing information learned from online eating disorders and consumer experience.

EMD-Based Predictive Deep Belief Network for Time Series Prediction: An Application to Drought Forecasting

Directory of Open Access Journals (Sweden)

Norbert A. Agana

2018-02-01

Full Text Available Drought is a stochastic natural feature that arises due to intense and persistent shortage of precipitation. Its impact is mostly manifested as agricultural and hydrological droughts following an initial meteorological phenomenon. Drought prediction is essential because it can aid in the preparedness and impact-related management of its effects. This study considers the drought forecasting problem by developing a hybrid predictive model using a denoised empirical mode decomposition (EMD and a deep belief network (DBN. The proposed method first decomposes the data into several intrinsic mode functions (IMFs using EMD, and a reconstruction of the original data is obtained by considering only relevant IMFs. Detrended fluctuation analysis (DFA was applied to each IMF to determine the threshold for robust denoising performance. Based on their scaling exponents, irrelevant intrinsic mode functions are identified and suppressed. The proposed method was applied to predict different time scale drought indices across the Colorado River basin using a standardized streamflow index (SSI as the drought index. The results obtained using the proposed method was compared with standard methods such as multilayer perceptron (MLP and support vector regression (SVR. The proposed hybrid model showed improvement in prediction accuracy, especially for multi-step ahead predictions.

Posttraumatic Maladaptive Beliefs Scale: Evolution of the Personal Beliefs and Reactions Scale

Science.gov (United States)

Vogt, Dawne S.; Shipherd, Jillian C.; Resick, Patricia A.

2012-01-01

The Posttraumatic Maladaptive Beliefs Scale (PMBS) was developed to measure maladaptive beliefs about current life circumstances that may occur following trauma exposure. This scale assesses maladaptive beliefs within three domains: (a) Threat of Harm, (b) Self-Worth and Judgment, and (c) Reliability and Trustworthiness of Others. Items for the…

The Role of Irrational Beliefs, Self Efficacy and Social Support in Relapse of Abuse Disorder

Directory of Open Access Journals (Sweden)

Toraj Hashemi

2010-05-01

Full Text Available Aim: This study aimed to determine the role of irrational beliefs system, self efficacy and social support network in predicting of relapse/non-relapse of drug misusing, and comparison of mentioned variables between these two groups. Method: For this purpose 100 persons who had repeated relapse and 100 persons who did not have relapse were selected by available sampling of Rehabilitation Organization of Tabriz city. Albert Alic’s irrational beliefs, Sherer’s self efficacy and Wax’s social support questionnaires administered among selected samples. Results: The results showed that, there were significant differences between two relapse and non-relapse groups on irrational beliefs, self-efficacy and social support. Conclusion: The results have applied implications in addiction treatment clinics.

Conditional Belief Types

Science.gov (United States)

2016-04-19

Rationality of a player is determined by comparing her actual expected payoff to her expected payoff when her strategy is changed , while her beliefs —and...reduced strategies, and it is possible that under such conditions, beliefs about other players’ reduced strategies change as well. Thus, independence...assumptions, whether they concern observability of moves or subjective beliefs of any other kind, can be all accommodated by changing the informational

On the application of Hidden Markov Model and Bayesian Belief Network to seismic noise at Las Canadas Caldera, Tenerife, Spain

International Nuclear Information System (INIS)

Quintero Oliveros, Anggi; Carniel, Roberto; Tarraga, Marta; Aspinall, Willy

2008-01-01

The Teide-Pico Viejo volcanic complex situated in Tenerife Island (Canary Islands, Spain) has recently shown signs of unrest, long after its last eruptive episode at Chinyero in 1909, and the last explosive episode which happened at Montana Blanca, 2000 years ago. In this paper we study the seismicity of the Teide-Pico Viejo complex recorded between May and December 2004, in order to show the applicability of tools such as Hidden Markov Models and Bayesian Belief Networks which can be used to build a structure for evaluating the probability of given eruptive or volcano-related scenarios. The results support the existence of a bidirectional relationship between volcano-tectonic events and the background seismic noise - in particular its frequency content. This in turn suggests that the two phenomena can be related to one unique process influencing their generation

On the application of Hidden Markov Model and Bayesian Belief Network to seismic noise at Las Canadas Caldera, Tenerife, Spain

Energy Technology Data Exchange (ETDEWEB)

Quintero Oliveros, Anggi [Dipartimento di Georisorse e Territorio, Universita di Udine (Italy); Departamento de Ciencias de La Tierra, Universidad Simon Bolivar, Caracas (Venezuela); Carniel, Roberto [Dipartimento di Georisorse e Territorio, Universita di Udine (Italy)], E-mail: roberto.carniel@uniud.it; Tarraga, Marta [Departamento de Volcanologia, Museo Nacional de Ciencias Naturales, CSIC, Madrid (Spain); Aspinall, Willy [Aspinall and Associates, 5 Woodside Close, Beaconsfield, Bucks (United Kingdom)

2008-08-15

The Teide-Pico Viejo volcanic complex situated in Tenerife Island (Canary Islands, Spain) has recently shown signs of unrest, long after its last eruptive episode at Chinyero in 1909, and the last explosive episode which happened at Montana Blanca, 2000 years ago. In this paper we study the seismicity of the Teide-Pico Viejo complex recorded between May and December 2004, in order to show the applicability of tools such as Hidden Markov Models and Bayesian Belief Networks which can be used to build a structure for evaluating the probability of given eruptive or volcano-related scenarios. The results support the existence of a bidirectional relationship between volcano-tectonic events and the background seismic noise - in particular its frequency content. This in turn suggests that the two phenomena can be related to one unique process influencing their generation.

Public beliefs about and attitudes towards bipolar disorder: testing theory based models of stigma.

Science.gov (United States)

Ellison, Nell; Mason, Oliver; Scior, Katrina

2015-04-01

Given the vast literature into public beliefs and attitudes towards schizophrenia and depression, there is paucity of research on attitudes towards bipolar disorder despite its similar prevalence to schizophrenia. This study explored public beliefs and attitudes towards bipolar disorder and examined the relationship between these different components of stigma. Using an online questionnaire distributed via email, social networking sites and public institutions, 753 members of the UK population were presented with a vignette depicting someone who met DSM-IV criteria for bipolar disorder. Causal beliefs, beliefs about prognosis, emotional reactions, stereotypes, and social distance were assessed in response to the vignette. Preacher and Hayes procedure for estimating direct and indirect effects of multiple mediators was used to examine the relationship between these components of stigma. Bipolar disorder was primarily associated with positive beliefs and attitudes and elicited a relatively low desire for social distance. Fear partially mediated the relationship between stereotypes and social distance. Biomedical causal beliefs reduced desire for social distance by increasing compassion, whereas fate causal beliefs increased it through eliciting fear. Psychosocial causal beliefs had mixed effects. The measurement of stigma using vignettes and self-report questionnaires has implications for ecological validity and participants may have been reluctant to reveal the true extent of their negative attitudes. Dissemination of these findings to people with bipolar disorder has implications for the reduction of internalised stigma in this population. Anti-stigma campaigns should attend to causal beliefs, stereotypes and emotional reactions as these all play a vital role in discriminatory behaviour towards people with bipolar disorder. Copyright © 2015 Elsevier B.V. All rights reserved.

Effects of a Cancer Prevention Advertisement on Beliefs and Knowledge about Cancer Prevention.

Science.gov (United States)

Kye, Su Yeon; Yoo, Jisu; Lee, Min Hee; Jun, Jae Kwan

2015-01-01

Outcome-expectation beliefs and knowledge may ultimately influence behavior for cancer prevention. The aims of this study were to measure changes in knowledge and beliefs about cancer prevention before and after viewing a television advertisement and identify the factors affecting receptivity to its messages. A one-group pretest-posttest design was used in this study of 1,000 individuals aged 20 to 65 years who were recruited online in November 2014. The outcome variables included cancer prevention beliefs based on the Health Belief Model (five items) and knowledge about risk factors for cancer (seven items). Perceived susceptibility, perceived benefits, and self-efficacy increased significantly and their perceived severity and perceived barriers decreased significantly, after participants viewed the television advertisement. Correct responses to questions about risk factors also increased significantly, except for smoking. The main factors affecting changes in the outcome variables were age, interest in cancer prevention, social network, satisfaction with the ad, and pretest scores. Television advertisements with positive frameworks can be an efficient channel of improving beliefs and knowledge about cancer prevention in a short period. The continuous development of intervention materials that consider the demographics, needs, and satisfaction of the target group will be necessary for future studies.

Application of a Bayesian belief network for assessing the vulnerability of permafrost to thaw and implications for greenhouse gas production and climate feedback

International Nuclear Information System (INIS)

Webster, K.L.; McLaughlin, J.W.

2014-01-01

Highlights: • Permafrost areas are subject to accelerated rates of climate change leading to thaw. • Thaw will increase decomposition rates, exacerbating climate feedback. • We present a Bayesian belief network as a tool to examine interacting factors. • Organic soil (Hudson Plain region) and mineral soil (Arctic region) are contrasted. • Hudson Plain has contributed more to climate feedback than Arctic, but gap closing. - Abstract: Permafrost affected soils are an important component of the Boreal, Subarctic, and Arctic ecosystems of Canada. These areas are undergoing accelerated rates of climate change and have been identified as being at high risk for thaw. Thaw will expose soil to warmer conditions that support increased decomposition rates, which in turn will affect short- and long-term carbon storage capacity and result in feedback to global climate. We present a tool in the form of a Bayesian belief network influence diagram that will allow policymakers and managers to understand how interacting factors contribute to permafrost thaw and resulting effects on greenhouse gas (GHG) production and climate feedback. A theoretical example of expected responses from an organic soil typical of the Hudson Plain region and a mineral soil typical in the Arctic region demonstrate variability in responses across different combinations of climate and soil conditions within Canada. Based on the network results, the Arctic has historically had higher probability of thaw, but the Hudson Plain has had higher probability of producing carbon dioxide (CO 2 ) and methane (CH 4 ). Under past and current climate conditions, the Hudson Plain has, on a per unit area basis, contributed more to climate feedback than the Arctic. However, the gap in contribution between the two regions is likely to decrease as thaw progresses more rapidly in the Arctic than Hudson Plain region, resulting in strong positive feedback to climate warming from both regions. The flexible framework

Task-specific feature extraction and classification of fMRI volumes using a deep neural network initialized with a deep belief network: Evaluation using sensorimotor tasks.

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Jang, Hojin; Plis, Sergey M; Calhoun, Vince D; Lee, Jong-Hwan

2017-01-15

Feedforward deep neural networks (DNNs), artificial neural networks with multiple hidden layers, have recently demonstrated a record-breaking performance in multiple areas of applications in computer vision and speech processing. Following the success, DNNs have been applied to neuroimaging modalities including functional/structural magnetic resonance imaging (MRI) and positron-emission tomography data. However, no study has explicitly applied DNNs to 3D whole-brain fMRI volumes and thereby extracted hidden volumetric representations of fMRI that are discriminative for a task performed as the fMRI volume was acquired. Our study applied fully connected feedforward DNN to fMRI volumes collected in four sensorimotor tasks (i.e., left-hand clenching, right-hand clenching, auditory attention, and visual stimulus) undertaken by 12 healthy participants. Using a leave-one-subject-out cross-validation scheme, a restricted Boltzmann machine-based deep belief network was pretrained and used to initialize weights of the DNN. The pretrained DNN was fine-tuned while systematically controlling weight-sparsity levels across hidden layers. Optimal weight-sparsity levels were determined from a minimum validation error rate of fMRI volume classification. Minimum error rates (mean±standard deviation; %) of 6.9 (±3.8) were obtained from the three-layer DNN with the sparsest condition of weights across the three hidden layers. These error rates were even lower than the error rates from the single-layer network (9.4±4.6) and the two-layer network (7.4±4.1). The estimated DNN weights showed spatial patterns that are remarkably task-specific, particularly in the higher layers. The output values of the third hidden layer represented distinct patterns/codes of the 3D whole-brain fMRI volume and encoded the information of the tasks as evaluated from representational similarity analysis. Our reported findings show the ability of the DNN to classify a single fMRI volume based on the

Belief Change in Reasoning Agents

OpenAIRE

Jin, Yi

2007-01-01

The capability of changing beliefs upon new information in a rational and efficient way is crucial for an intelligent agent. Belief change therefore is one of the central research fields in Artificial Intelligence (AI) for over two decades. In the AI literature, two different kinds of belief change operations have been intensively investigated: belief update, which deal with situations where the new information describes changes of the world; and belief revision, which assumes the world is st...

Illness causal beliefs in Turkish immigrants

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Klimidis Steven

2007-07-01

Full Text Available Abstract Background People hold a wide variety of beliefs concerning the causes of illness. Such beliefs vary across cultures and, among immigrants, may be influenced by many factors, including level of acculturation, gender, level of education, and experience of illness and treatment. This study examines illness causal beliefs in Turkish-immigrants in Australia. Methods Causal beliefs about somatic and mental illness were examined in a sample of 444 members of the Turkish population of Melbourne. The socio-demographic characteristics of the sample were broadly similar to those of the Melbourne Turkish community. Five issues were examined: the structure of causal beliefs; the relative frequency of natural, supernatural and metaphysical beliefs; ascription of somatic, mental, or both somatic and mental conditions to the various causes; the correlations of belief types with socio-demographic, modernizing and acculturation variables; and the relationship between causal beliefs and current illness. Results Principal components analysis revealed two broad factors, accounting for 58 percent of the variation in scores on illness belief scales, distinctly interpretable as natural and supernatural beliefs. Second, beliefs in natural causes were more frequent than beliefs in supernatural causes. Third, some causal beliefs were commonly linked to both somatic and mental conditions while others were regarded as more specific to either somatic or mental disorders. Last, there was a range of correlations between endorsement of belief types and factors defining heterogeneity within the community, including with demographic factors, indicators of modernizing and acculturative processes, and the current presence of illness. Conclusion Results supported the classification of causal beliefs proposed by Murdock, Wilson & Frederick, with a division into natural and supernatural causes. While belief in natural causes is more common, belief in supernatural causes

Illness causal beliefs in Turkish immigrants.

Science.gov (United States)

Minas, Harry; Klimidis, Steven; Tuncer, Can

2007-07-24

People hold a wide variety of beliefs concerning the causes of illness. Such beliefs vary across cultures and, among immigrants, may be influenced by many factors, including level of acculturation, gender, level of education, and experience of illness and treatment. This study examines illness causal beliefs in Turkish-immigrants in Australia. Causal beliefs about somatic and mental illness were examined in a sample of 444 members of the Turkish population of Melbourne. The socio-demographic characteristics of the sample were broadly similar to those of the Melbourne Turkish community. Five issues were examined: the structure of causal beliefs; the relative frequency of natural, supernatural and metaphysical beliefs; ascription of somatic, mental, or both somatic and mental conditions to the various causes; the correlations of belief types with socio-demographic, modernizing and acculturation variables; and the relationship between causal beliefs and current illness. Principal components analysis revealed two broad factors, accounting for 58 percent of the variation in scores on illness belief scales, distinctly interpretable as natural and supernatural beliefs. Second, beliefs in natural causes were more frequent than beliefs in supernatural causes. Third, some causal beliefs were commonly linked to both somatic and mental conditions while others were regarded as more specific to either somatic or mental disorders. Last, there was a range of correlations between endorsement of belief types and factors defining heterogeneity within the community, including with demographic factors, indicators of modernizing and acculturative processes, and the current presence of illness. Results supported the classification of causal beliefs proposed by Murdock, Wilson & Frederick, with a division into natural and supernatural causes. While belief in natural causes is more common, belief in supernatural causes persists despite modernizing and acculturative influences. Different

Cyber Panel Experimentation Program

National Research Council Canada - National Science Library

Haines, Joshua

2003-01-01

.... A variety of multi-step cyber attacks were perpetrated against the target network each of which typifies a current-day real-world attack. The preliminary results presented here represent those available at conclusion of the experiment process by BBN.

What Happens When a Teacher's Science Belief Structure Is in Disequilibrium? Entangled Nature of Beliefs and Practice

Science.gov (United States)

Martin, Anita; Park, Soonhye; Hand, Brian

2017-08-01

This qualitative case study examined the process of change in an experienced elementary teacher's belief structure during implementation of an inquiry-based science program. Difficulties generally associated with ascertaining beliefs were minimized by using Leatham's (Journal of Mathematics Teacher Education, 9, 91-102 (2006) Sensible System Framework, enabling researchers to obtain rich descriptions of the teacher's belief structure by focusing on words (professed beliefs), intentions (intended beliefs), and actions (enacted beliefs). Models were constructed of the teacher's belief structure before and after implementation of the Science Writing Heuristic (SWH) approach (Hand et al. International Journal of Science Education, 26(2), 131-149, 2004), an inquiry-based approach to teaching science. Key beliefs for this teacher were related to how students learn, goals for teaching science, focus of instruction, and roles of teacher and student. Ultimately, the teacher shifted her professed, intended, and enacted beliefs resulting in a shift from a teacher-centered to a student-centered classroom. Findings support Thagard's Coherence Theory of Justification (2002), positing that change in one belief creates a state of disequilibrium that must be alleviated by changing/realigning other beliefs in order to re-establish coherence in the overall belief structure. This research focus is distinct from the general trend in teacher beliefs research in important ways. Most significant is that this study was not focused on the traditional two lists—those beliefs that were consistent with practice and those that were inconsistent with practice—but instead focused on the entwined nature of beliefs and practice and have shown that a teacher's practice can be viewed as their enacted beliefs, an integral part of the teacher's overall belief structure.

Do Humans Have Two Systems to Track Beliefs and Belief-Like States?

Science.gov (United States)

Apperly, Ian A.; Butterfill, Stephen A.

2009-01-01

The lack of consensus on how to characterize humans' capacity for belief reasoning has been brought into sharp focus by recent research. Children fail critical tests of belief reasoning before 3 to 4 years of age (H. Wellman, D. Cross, & J. Watson, 2001; H. Wimmer & J. Perner, 1983), yet infants apparently pass false-belief tasks at 13 or 15…

Extreme Overvalued Beliefs: How Violent Extremist Beliefs Become “Normalized”

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Tahir Rahman

2018-01-01

Full Text Available Extreme overvalued beliefs (EOB are rigidly held, non-deusional beliefs that are the motive behind most acts of terrorism and mass shootings. EOBs are differentiated from delusions and obsessions. The concept of an overvalued idea was first described by Wernicke and later applied to terrorism by McHugh. Our group of forensic psychiatrists (Rahman, Resnick, Harry refined the definition as an aid in the differential diagnosis seen in acts of violence. The form and content of EOBs is discussed as well as group effects, conformity, and obedience to authority. Religious cults such as The People’s Temple, Heaven’s Gate, Aum Shinrikyo, and Islamic State (ISIS and conspiracy beliefs such as assassinations, moon-hoax, and vaccine-induced autism beliefs are discussed using this construct. Finally, some concluding thoughts on countering violent extremism, including its online presence is discussed utilizing information learned from online eating disorders and consumer experience.

Extreme Overvalued Beliefs: How Violent Extremist Beliefs Become “Normalized”

Science.gov (United States)

Rahman, Tahir

2018-01-01

Extreme overvalued beliefs (EOB) are rigidly held, non-deusional beliefs that are the motive behind most acts of terrorism and mass shootings. EOBs are differentiated from delusions and obsessions. The concept of an overvalued idea was first described by Wernicke and later applied to terrorism by McHugh. Our group of forensic psychiatrists (Rahman, Resnick, Harry) refined the definition as an aid in the differential diagnosis seen in acts of violence. The form and content of EOBs is discussed as well as group effects, conformity, and obedience to authority. Religious cults such as The People’s Temple, Heaven’s Gate, Aum Shinrikyo, and Islamic State (ISIS) and conspiracy beliefs such as assassinations, moon-hoax, and vaccine-induced autism beliefs are discussed using this construct. Finally, some concluding thoughts on countering violent extremism, including its online presence is discussed utilizing information learned from online eating disorders and consumer experience. PMID:29329259

BELIEF Project: the Portal and the Digital Library

International Nuclear Information System (INIS)

Zoppi, F.; Calabro, G.

2007-01-01

BELIEF (Bringing Europes eLectronic Infrastructures to Expanding Frontiers) Project aim to create a platform where eInfrastructures providers and users can collaborate and exchange knowledge, which will help ensure that eInfrastructures are developed and used effectively worldwide, filling the gap separating the Research Infrastructure providers from the users, and thus contribute to the emergence of a competitive knowledge-based economy. To create this synergy of multi-disciplinary Research Infrastructure communities, BELIEF created a one-stop-shop for eInfrastructures communities providing online a Digital Library (DL) and a Portal with a search and contact facility, case studies, a discussion forum, eInfrastructures publications. Offline, it has organised events including brainstorming, networking workshops and international conferences and publications, since BELIEFs values are firmly rooted in international cooperation to the emerging economies, particularly of Latin America and India. The Portal and the DL are key parts of this project. There was an opportunity to provide a ready and common source of information on eInfrastructures, both for the users wanting to find out the supply, and for the providers wanting to extend user base and develop their systems. The Portal and the DL respond to this demand by supplying to researchers documentation that matches their search criteria precisely, according to their interest and professional profile. (Author)

[Research of electroencephalography representational emotion recognition based on deep belief networks].

Science.gov (United States)

Yang, Hao; Zhang, Junran; Jiang, Xiaomei; Liu, Fei

2018-04-01

In recent years, with the rapid development of machine learning techniques,the deep learning algorithm has been widely used in one-dimensional physiological signal processing. In this paper we used electroencephalography (EEG) signals based on deep belief network (DBN) model in open source frameworks of deep learning to identify emotional state (positive, negative and neutrals), then the results of DBN were compared with support vector machine (SVM). The EEG signals were collected from the subjects who were under different emotional stimuli, and DBN and SVM were adopted to identify the EEG signals with changes of different characteristics and different frequency bands. We found that the average accuracy of differential entropy (DE) feature by DBN is 89.12%±6.54%, which has a better performance than previous research based on the same data set. At the same time, the classification effects of DBN are better than the results from traditional SVM (the average classification accuracy of 84.2%±9.24%) and its accuracy and stability have a better trend. In three experiments with different time points, single subject can achieve the consistent results of classification by using DBN (the mean standard deviation is1.44%), and the experimental results show that the system has steady performance and good repeatability. According to our research, the characteristic of DE has a better classification result than other characteristics. Furthermore, the Beta band and the Gamma band in the emotional recognition model have higher classification accuracy. To sum up, the performances of classifiers have a promotion by using the deep learning algorithm, which has a reference for establishing a more accurate system of emotional recognition. Meanwhile, we can trace through the results of recognition to find out the brain regions and frequency band that are related to the emotions, which can help us to understand the emotional mechanism better. This study has a high academic value and

Free will and paranormal beliefs.

Science.gov (United States)

Mogi, Ken

2014-01-01

Free will is one of the fundamental aspects of human cognition. In the context of cognitive neuroscience, various experiments on time perception, sensorimotor coordination, and agency suggest the possibility that it is a robust illusion (a feeling independent of actual causal relationship with actions) constructed by neural mechanisms. Humans are known to suffer from various cognitive biases and failures, and the sense of free will might be one of them. Here I report a positive correlation between the belief in free will and paranormal beliefs (UFO, reincarnation, astrology, and psi). Web questionnaires involving 2076 subjects (978 males, 1087 females, and 11 other genders) were conducted, which revealed significant positive correlations between belief in free will (theory and practice) and paranormal beliefs. There was no significant correlation between belief in free will and knowledge in paranormal phenomena. Paranormal belief scores for females were significantly higher than those for males, with corresponding significant (albeit weaker) difference in belief in free will. These results are consistent with the view that free will is an illusion which shares common cognitive elements with paranormal beliefs.

Free will and paranormal beliefs

Directory of Open Access Journals (Sweden)

Ken eMogi

2014-04-01

Full Text Available Free will is one of the fundamental aspects of human cognition. In the context of cognitive neuroscience, various experiments on time perception, sensorimotor coordination, and agency suggest the possibility that it is a robust illusion (a feeling independent of actual causal relationship with actions constructed by neural mechanisms. Humans are known to suffer from various cognitive biases and failures, and the sense of free will might be one of them. Here I report a positive correlation between the belief in free will and paranormal beliefs (UFO, reincarnation, astrology, and psi. Web questionnaires involving 2076 subjects (978 males, 1087 females, and 11 other genders were conducted, which revealed significant positive correlations between belief in free will (theory and practice and paranormal beliefs. There was no significant correlation between belief in free will and knowledge in paranormal phenomena. Paranormal belief scores for females were significantly higher than those for males, with corresponding significant (albeit weaker difference in belief in free will. These results are consistent with the view that free will is an illusion which shares common cognitive elements with paranormal beliefs.

Free will and paranormal beliefs

Science.gov (United States)

Mogi, Ken

2014-01-01

Free will is one of the fundamental aspects of human cognition. In the context of cognitive neuroscience, various experiments on time perception, sensorimotor coordination, and agency suggest the possibility that it is a robust illusion (a feeling independent of actual causal relationship with actions) constructed by neural mechanisms. Humans are known to suffer from various cognitive biases and failures, and the sense of free will might be one of them. Here I report a positive correlation between the belief in free will and paranormal beliefs (UFO, reincarnation, astrology, and psi). Web questionnaires involving 2076 subjects (978 males, 1087 females, and 11 other genders) were conducted, which revealed significant positive correlations between belief in free will (theory and practice) and paranormal beliefs. There was no significant correlation between belief in free will and knowledge in paranormal phenomena. Paranormal belief scores for females were significantly higher than those for males, with corresponding significant (albeit weaker) difference in belief in free will. These results are consistent with the view that free will is an illusion which shares common cognitive elements with paranormal beliefs. PMID:24765084

Negatively-biased credulity and the cultural evolution of beliefs.

Science.gov (United States)

Fessler, Daniel M T; Pisor, Anne C; Navarrete, Carlos David

2014-01-01

The functions of cultural beliefs are often opaque to those who hold them. Accordingly, to benefit from cultural evolution's ability to solve complex adaptive problems, learners must be credulous. However, credulity entails costs, including susceptibility to exploitation, and effort wasted due to false beliefs. One determinant of the optimal level of credulity is the ratio between the costs of two types of errors: erroneous incredulity (failing to believe information that is true) and erroneous credulity (believing information that is false). This ratio can be expected to be asymmetric when information concerns hazards, as the costs of erroneous incredulity will, on average, exceed the costs of erroneous credulity; no equivalent asymmetry characterizes information concerning benefits. Natural selection can therefore be expected to have crafted learners' minds so as to be more credulous toward information concerning hazards. This negatively-biased credulity extends general negativity bias, the adaptive tendency for negative events to be more salient than positive events. Together, these biases constitute attractors that should shape cultural evolution via the aggregated effects of learners' differential retention and transmission of information. In two studies in the U.S., we demonstrate the existence of negatively-biased credulity, and show that it is most pronounced in those who believe the world to be dangerous, individuals who may constitute important nodes in cultural transmission networks. We then document the predicted imbalance in cultural content using a sample of urban legends collected from the Internet and a sample of supernatural beliefs obtained from ethnographies of a representative collection of the world's cultures, showing that beliefs about hazards predominate in both.

Gravitational-Wave Stochastic Background from Cosmic Strings

International Nuclear Information System (INIS)

Siemens, Xavier; Creighton, Jolien; Mandic, Vuk

2007-01-01

We consider the stochastic background of gravitational waves produced by a network of cosmic strings and assess their accessibility to current and planned gravitational wave detectors, as well as to big bang nucleosynthesis (BBN), cosmic microwave background (CMB), and pulsar timing constraints. We find that current data from interferometric gravitational wave detectors, such as Laser Interferometer Gravitational Wave Observatory (LIGO), are sensitive to areas of parameter space of cosmic string models complementary to those accessible to pulsar, BBN, and CMB bounds. Future more sensitive LIGO runs and interferometers such as Advanced LIGO and Laser Interferometer Space Antenna (LISA) will be able to explore substantial parts of the parameter space

Estimation of total Effort and Effort Elapsed in Each Step of Software Development Using Optimal Bayesian Belief Network

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Fatemeh Zare Baghiabad

2017-09-01

Full Text Available Accuracy in estimating the needed effort for software development caused software effort estimation to be a challenging issue. Beside estimation of total effort, determining the effort elapsed in each software development step is very important because any mistakes in enterprise resource planning can lead to project failure. In this paper, a Bayesian belief network was proposed based on effective components and software development process. In this model, the feedback loops are considered between development steps provided that the return rates are different for each project. Different return rates help us determine the percentages of the elapsed effort in each software development step, distinctively. Moreover, the error measurement resulted from optimized effort estimation and the optimal coefficients to modify the model are sought. The results of the comparison between the proposed model and other models showed that the model has the capability to highly accurately estimate the total effort (with the marginal error of about 0.114 and to estimate the effort elapsed in each software development step.

Toward a formalized account of attitudes: The Causal Attitude Network (CAN) model.

Science.gov (United States)

Dalege, Jonas; Borsboom, Denny; van Harreveld, Frenk; van den Berg, Helma; Conner, Mark; van der Maas, Han L J

2016-01-01

This article introduces the Causal Attitude Network (CAN) model, which conceptualizes attitudes as networks consisting of evaluative reactions and interactions between these reactions. Relevant evaluative reactions include beliefs, feelings, and behaviors toward the attitude object. Interactions between these reactions arise through direct causal influences (e.g., the belief that snakes are dangerous causes fear of snakes) and mechanisms that support evaluative consistency between related contents of evaluative reactions (e.g., people tend to align their belief that snakes are useful with their belief that snakes help maintain ecological balance). In the CAN model, the structure of attitude networks conforms to a small-world structure: evaluative reactions that are similar to each other form tight clusters, which are connected by a sparser set of "shortcuts" between them. We argue that the CAN model provides a realistic formalized measurement model of attitudes and therefore fills a crucial gap in the attitude literature. Furthermore, the CAN model provides testable predictions for the structure of attitudes and how they develop, remain stable, and change over time. Attitude strength is conceptualized in terms of the connectivity of attitude networks and we show that this provides a parsimonious account of the differences between strong and weak attitudes. We discuss the CAN model in relation to possible extensions, implication for the assessment of attitudes, and possibilities for further study. (c) 2015 APA, all rights reserved).

Paranormal beliefs and religiosity: Chinese version of the Revised Paranormal Belief Scale.

Science.gov (United States)

Shiah, Yung-Jong; Tam, Wai-Cheong Carl; Wu, Ming-Hsun; Chang, Frances

2010-10-01

This paper reports an initial study investigating the relations of paranormal beliefs with religiosity in a Chinese sample, as well as the development of a Chinese version of the Revised Paranormal Belief Scale and a test of its psychometric properties with 310 college students (5.5% Christians, 21.3% Buddhists, 61% believers in traditional Chinese religions, and 12% atheists). The reliability and validity of the Chinese version were satisfactory. In general, traditional Chinese religious believers had higher scores on paranormal belief than did Christians and atheists, and the mean total score of the Chinese participants was higher than previously reported in a Western sample. It was concluded that the greater involvement of practitioners of traditional Chinese religions in activities emphasizing paranormal experiences might contribute to their greater paranormal belief, especially as compared to the minority Christian group. The results are consistent with the idea that Christianity may offer the least support for paranormal belief.

Scandinavian belief in fate

Directory of Open Access Journals (Sweden)

Åke Ström

1967-02-01

Full Text Available In point of principle, Christianity does not give room for any belief in fate. Astrology, horoscopes, divination, etc., are strictly rejected. Belief in fate never disappeared in Christian countries, nor did it in Scandinavia in Christian times. Especially in folklore we can find it at any period: People believed in an implacable fate. All folklore is filled up with this belief in destiny. Nobody can escape his fate. The future lies in the hands of fate, and the time to come takes its form according to inscrutable laws. The pre-Christian period in Scandinavia, dominated by pagan Norse religion, and the secularized epoch of the 20th century, however, show more distinctive and more widespread beliefs in fate than does the Christian period. The present paper makes a comparison between these forms of belief.

Moral Beliefs and Cognitive Homogeneity

Directory of Open Access Journals (Sweden)

Nevia Dolcini

2018-04-01

Full Text Available The Emotional Perception Model of moral judgment intends to account for experientialism about morality and moral reasoning. In explaining how moral beliefs are formed and applied in practical reasoning, the model attempts to overcome the mismatch between reason and action/desire: morality isn’t about reason for actions, yet moral beliefs, if caused by desires, may play a motivational role in (moral agency. The account allows for two kinds of moral beliefs: genuine moral beliefs, which enjoy a relation to desire, and motivationally inert moral beliefs acquired in ways other than experience. Such etiology-based dichotomy of concepts, I will argue, leads to the undesirable view of cognition as a non-homogeneous phenomenon. Moreover, the distinction between moral beliefs and moral beliefs would entail a further dichotomy encompassing the domain of moral agency: one and the same action might possibly be either genuine moral, or not moral, if acted by individuals lacking the capacity for moral feelings, such as psychopaths.

Belief attribution despite verbal interference.

Science.gov (United States)

Forgeot d'Arc, Baudouin; Ramus, Franck

2011-05-01

False-belief (FB) tasks have been widely used to study the ability of individuals to represent the content of their conspecifics' mental states (theory of mind). However, the cognitive processes involved are still poorly understood, and it remains particularly debated whether language and inner speech are necessary for the attribution of beliefs to other agents. We present a completely nonverbal paradigm consisting of silent animated cartoons in five closely related conditions, systematically teasing apart different aspects of scene analysis and allowing the assessment of the attribution of beliefs, goals, and physical causation. In order to test the role of language in belief attribution, we used verbal shadowing as a dual task to inhibit inner speech. Data on 58 healthy adults indicate that verbal interference decreases overall performance, but has no specific effect on belief attribution. Participants remained able to attribute beliefs despite heavy concurrent demands on their verbal abilities. Our results are most consistent with the hypothesis that belief attribution is independent from inner speech.

When fast logic meets slow belief: Evidence for a parallel-processing model of belief bias.

Science.gov (United States)

Trippas, Dries; Thompson, Valerie A; Handley, Simon J

2017-05-01

Two experiments pitted the default-interventionist account of belief bias against a parallel-processing model. According to the former, belief bias occurs because a fast, belief-based evaluation of the conclusion pre-empts a working-memory demanding logical analysis. In contrast, according to the latter both belief-based and logic-based responding occur in parallel. Participants were given deductive reasoning problems of variable complexity and instructed to decide whether the conclusion was valid on half the trials or to decide whether the conclusion was believable on the other half. When belief and logic conflict, the default-interventionist view predicts that it should take less time to respond on the basis of belief than logic, and that the believability of a conclusion should interfere with judgments of validity, but not the reverse. The parallel-processing view predicts that beliefs should interfere with logic judgments only if the processing required to evaluate the logical structure exceeds that required to evaluate the knowledge necessary to make a belief-based judgment, and vice versa otherwise. Consistent with this latter view, for the simplest reasoning problems (modus ponens), judgments of belief resulted in lower accuracy than judgments of validity, and believability interfered more with judgments of validity than the converse. For problems of moderate complexity (modus tollens and single-model syllogisms), the interference was symmetrical, in that validity interfered with belief judgments to the same degree that believability interfered with validity judgments. For the most complex (three-term multiple-model syllogisms), conclusion believability interfered more with judgments of validity than vice versa, in spite of the significant interference from conclusion validity on judgments of belief.

STATED VS. ENACTED BELIEFS: LOOKING AT PRE-SERVICE TEACHERS' PEDAGOGICAL BELIEFS THROUGH CLASSROOM INTERACTION

Directory of Open Access Journals (Sweden)

Alberto Fajardo

2013-08-01

Full Text Available This article explores the relationship between pedagogical beliefs and classroom practice. Two Colombian pre-service primary school language teachers in the final stage of their five-year training programme were the research participants. Interview and classroom observation were the methods used, and content analysis was the analytical approach. It is argued in this study that by comparing the stated beliefs (as articulated in interviews and enacted beliefs (as manifested in classroom interaction, it is possible to gain a fine-grained understanding of the relationship between beliefs and teaching practice. The findings suggested that while there were significant cases of coherence between beliefs and classroom action, there was also evidence of some incongruent relationships.

The birth beliefs scale - a new measure to assess basic beliefs about birth.

Science.gov (United States)

Preis, Heidi; Benyamini, Yael

2017-03-01

Basic beliefs about birth as a natural and safe or a medical and risky process are central in the decisions on where and how to birth. Despite their importance, they have not been studied separately from other childbirth-related constructs. Our aim was to develop a measure to assess these beliefs. Pregnant Israeli women (N = 850, gestational week ≥14) were recruited in women's health centers, in online natural birth forums, and through home midwives. Participants filled in questionnaires including sociodemographic and obstetric background, the Birth Beliefs Scale (BBS), dispositional desire for control (DC) and planned mode of delivery. Factor analyses revealed that the BBS is composed of two factors: beliefs about birth as a natural process and beliefs about birth as a medical process. Both subscales showed good internal and test-retest reliability. They had good construct validity, predicted birth choices, and were weakly correlated with DC. Women's medical obstetric history was associated with the BBS, further supporting the validity of the scale. Beliefs about birth may be the building blocks that make up perceptions of birth and drive women's preferences. The new scale provides an easy way to distinctly assess them so they can be used to further understand planned birth behaviors. Additional studies are needed to comprehend how these beliefs form in different cultural contexts and how they evolve over time.

Beliefs about chelation among thalassemia patients

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Trachtenberg Felicia L

2012-12-01

Full Text Available Abstract Background Understanding patients’ views about medication is crucial to maximize adherence. Thalassemia is a congenital blood disorder requiring chronic blood transfusions and daily iron chelation therapy. Methods The Beliefs in Medicine Questionnaire (BMQ was used to assess beliefs in chelation in thalassemia patients from North America and London in the Thalassemia Longitudinal Cohort (TLC of the Thalassemia Clinical Research Network (TCRN. Chelation adherence was based on patient report of doses administered out of those prescribed in the last four weeks. Results Of 371 patients (ages 5-58y, mean 24y, 93% were transfused and 92% receiving chelation (26% deferoxamine (DFO; a slow subcutaneous infusion via portable pump, 63% oral, 11% combination. Patients expressed high “necessity” for transfusion (96%, DFO chelation (92% and oral chelation (89%, with lower “concern” about treatment (48%, 39%, 19% respectively. Concern about oral chelation was significantly lower than that of DFO (p Conclusions Despite their requirement for multimodal therapy, thalassemia patients have positive views about medicine, more so than in other disease populations. Patients may benefit from education about the tolerability of chelation and strategies to effectively cope with side effects, both of which might be beneficial in lowering body iron burden. Clinicaltrials.gov identifier NCT00661804

Lucky Belief in Science Education - Gettier Cases and the Value of Reliable Belief-Forming Processes

Science.gov (United States)

Brock, Richard

2018-05-01

The conceptualisation of knowledge as justified true belief has been shown to be, at the very least, an incomplete account. One challenge to the justified true belief model arises from the proposition of situations in which a person possesses a belief that is both justified and true which some philosophers intuit should not be classified as knowledge. Though situations of this type have been imagined by a number of writers, they have come to be labelled Gettier cases. Gettier cases arise when a fallible justification happens to lead to a true belief in one context, a case of `lucky belief'. In this article, it is argued that students studying science may make claims that resemble Gettier cases. In some contexts, a student may make a claim that is both justified and true but which arises from an alternative conception of a scientific concept. A number of instances of lucky belief in topics in science education are considered leading to an examination of the criteria teachers use to assess students' claims in different contexts. The possibility of lucky belief leads to the proposal that, in addition to the acquisition of justified true beliefs, the development of reliable belief-forming processes is a significant goal of science education. The pedagogic value of various kinds of claims is considered and, it is argued, the criteria used to judge claims may be adjusted to suit the context of assessment. It is suggested that teachers should be alert to instances of lucky belief that mask alternative conceptions.

Updating Parameters for Volcanic Hazard Assessment Using Multi-parameter Monitoring Data Streams And Bayesian Belief Networks

Science.gov (United States)

Odbert, Henry; Aspinall, Willy

2014-05-01

Evidence-based hazard assessment at volcanoes assimilates knowledge about the physical processes of hazardous phenomena and observations that indicate the current state of a volcano. Incorporating both these lines of evidence can inform our belief about the likelihood (probability) and consequences (impact) of possible hazardous scenarios, forming a basis for formal quantitative hazard assessment. However, such evidence is often uncertain, indirect or incomplete. Approaches to volcano monitoring have advanced substantially in recent decades, increasing the variety and resolution of multi-parameter timeseries data recorded at volcanoes. Interpreting these multiple strands of parallel, partial evidence thus becomes increasingly complex. In practice, interpreting many timeseries requires an individual to be familiar with the idiosyncrasies of the volcano, monitoring techniques, configuration of recording instruments, observations from other datasets, and so on. In making such interpretations, an individual must consider how different volcanic processes may manifest as measureable observations, and then infer from the available data what can or cannot be deduced about those processes. We examine how parts of this process may be synthesised algorithmically using Bayesian inference. Bayesian Belief Networks (BBNs) use probability theory to treat and evaluate uncertainties in a rational and auditable scientific manner, but only to the extent warranted by the strength of the available evidence. The concept is a suitable framework for marshalling multiple strands of evidence (e.g. observations, model results and interpretations) and their associated uncertainties in a methodical manner. BBNs are usually implemented in graphical form and could be developed as a tool for near real-time, ongoing use in a volcano observatory, for example. We explore the application of BBNs in analysing volcanic data from the long-lived eruption at Soufriere Hills Volcano, Montserrat. We discuss

Delusions and the Right Hemisphere: A Review of the Case for the Right Hemisphere as a Mediator of Reality-Based Belief.

Science.gov (United States)

Gurin, Lindsey; Blum, Sonja

2017-01-01

Delusions are beliefs that remain fixed despite evidence that they are incorrect. Although the precise neural mechanism of delusional belief remains to be elucidated, there is a predominance of right-hemisphere lesions among patients with delusional syndromes accompanied by structural pathology, suggesting that right-hemisphere lesions, or networks with key nodes in the right hemisphere, may be playing a role. The authors discuss the potential theoretical basis and empiric support for a specific right-hemisphere role in delusion production, drawing on its roles in pragmatic communication; perceptual integration; attentional surveillance and anomaly/novelty detection; and belief updating.

Intention and Normative Belief

OpenAIRE

Chislenko, Eugene

2016-01-01

I defend the view that we act “under the guise of the good.” More specifically, I argue that an intention to do something is a belief that one ought to do it. I show how conflicts in intention and belief, as well as more complex impairments in these states, account for the central problem cases: akrasia in belief and intention, apparently unintelligible choices, and lack of motivation or accidie.

Exploring the beliefs of Australian prefabricated house builders

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Dale A Steinhardt

2016-06-01

Full Text Available The housing sector accounts for a majority of newly constructed buildings. Prefabrication, defined as the factory construction of houses or significant components, is widely promoted as a means to improve efficiency. This paper focuses on the research questions: RQ1. What are the attitudes of builders towards prefabrication adoption? RQ2. What types of stakeholders do builders believe influence their adoption decisions? RQ3. What types of contextual influences do builders believe impact their adoption decisions? Current prefabrication research has focused on the advantages and disadvantages of prefabrication, without further unpacking the beliefs of stakeholders that underpin them. This paper addresses this gap and increases the understanding of beliefs that can frame interventions to increase the market penetration of prefabrication. Fourteen interviews with Australian prefabricators were undertaken as a Belief Elicitation Study. This qualitative methodology is framed by the Theory of Planned Behaviour (TPB and the Technology Acceptance Model (TAM. Results show that modern high-quality prefabricated housing has struggled to overcome historical stigma; improved construction speed has not and is not likely to translate to reduced totals costs for a majority of firms; and prefabrication adoption has been hindered by an almost completely unsupportive industry infrastructure. Recommendations are made to frame arguments in improving short-term outcomes for an industry driven by practical considerations. Future discourse must focus on cost impacts, financial security and risk reduction. Establishing networks of prefabricators that can build a strong, unified voice for the industry should be prioritised.

Negatively-Biased Credulity and the Cultural Evolution of Beliefs

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Fessler, Daniel M. T.; Pisor, Anne C.; Navarrete, Carlos David

2014-01-01

The functions of cultural beliefs are often opaque to those who hold them. Accordingly, to benefit from cultural evolution’s ability to solve complex adaptive problems, learners must be credulous. However, credulity entails costs, including susceptibility to exploitation, and effort wasted due to false beliefs. One determinant of the optimal level of credulity is the ratio between the costs of two types of errors: erroneous incredulity (failing to believe information that is true) and erroneous credulity (believing information that is false). This ratio can be expected to be asymmetric when information concerns hazards, as the costs of erroneous incredulity will, on average, exceed the costs of erroneous credulity; no equivalent asymmetry characterizes information concerning benefits. Natural selection can therefore be expected to have crafted learners’ minds so as to be more credulous toward information concerning hazards. This negatively-biased credulity extends general negativity bias, the adaptive tendency for negative events to be more salient than positive events. Together, these biases constitute attractors that should shape cultural evolution via the aggregated effects of learners’ differential retention and transmission of information. In two studies in the U.S., we demonstrate the existence of negatively-biased credulity, and show that it is most pronounced in those who believe the world to be dangerous, individuals who may constitute important nodes in cultural transmission networks. We then document the predicted imbalance in cultural content using a sample of urban legends collected from the Internet and a sample of supernatural beliefs obtained from ethnographies of a representative collection of the world’s cultures, showing that beliefs about hazards predominate in both. PMID:24736596

Negatively-biased credulity and the cultural evolution of beliefs.

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Daniel M T Fessler

Full Text Available The functions of cultural beliefs are often opaque to those who hold them. Accordingly, to benefit from cultural evolution's ability to solve complex adaptive problems, learners must be credulous. However, credulity entails costs, including susceptibility to exploitation, and effort wasted due to false beliefs. One determinant of the optimal level of credulity is the ratio between the costs of two types of errors: erroneous incredulity (failing to believe information that is true and erroneous credulity (believing information that is false. This ratio can be expected to be asymmetric when information concerns hazards, as the costs of erroneous incredulity will, on average, exceed the costs of erroneous credulity; no equivalent asymmetry characterizes information concerning benefits. Natural selection can therefore be expected to have crafted learners' minds so as to be more credulous toward information concerning hazards. This negatively-biased credulity extends general negativity bias, the adaptive tendency for negative events to be more salient than positive events. Together, these biases constitute attractors that should shape cultural evolution via the aggregated effects of learners' differential retention and transmission of information. In two studies in the U.S., we demonstrate the existence of negatively-biased credulity, and show that it is most pronounced in those who believe the world to be dangerous, individuals who may constitute important nodes in cultural transmission networks. We then document the predicted imbalance in cultural content using a sample of urban legends collected from the Internet and a sample of supernatural beliefs obtained from ethnographies of a representative collection of the world's cultures, showing that beliefs about hazards predominate in both.

When fast logic meets slow belief: Evidence for a parallel-processing model of belief bias

OpenAIRE

Trippas, Dries; Thompson, Valerie A.; Handley, Simon J.

2016-01-01

Two experiments pitted the default-interventionist account of belief bias against a parallel-processing model. According to the former, belief bias occurs because a fast, belief-based evaluation of the conclusion pre-empts a working-memory demanding logical analysis. In contrast, according to the latter both belief-based and logic-based responding occur in parallel. Participants were given deductive reasoning problems of variable complexity and instructed to decide whether the conclusion was ...

Integrated wetland management for waterfowl and shorebirds at Mattamuskeet National Wildlife Refuge, North Carolina

Science.gov (United States)

Tavernia, Brian G.; Stanton, John D.; Lyons, James E.

2017-11-22

Mattamuskeet National Wildlife Refuge (MNWR) offers a mix of open water, marsh, forest, and cropland habitats on 20,307 hectares in coastal North Carolina. In 1934, Federal legislation (Executive Order 6924) established MNWR to benefit wintering waterfowl and other migratory bird species. On an annual basis, the refuge staff decide how to manage 14 impoundments to benefit not only waterfowl during the nonbreeding season, but also shorebirds during fall and spring migration. In making these decisions, the challenge is to select a portfolio, or collection, of management actions for the impoundments that optimizes use by the three groups of birds while respecting budget constraints. In this study, a decision support tool was developed for these annual management decisions.Within the decision framework, there are three different management objectives: shorebird-use days during fall and spring migrations, and waterfowl-use days during the nonbreeding season. Sixteen potential management actions were identified for impoundments; each action represents a combination of hydroperiod and vegetation manipulation. Example hydroperiods include semi-permanent and seasonal drawdowns, and vegetation manipulations include mechanical-chemical treatment, burning, disking, and no action. Expert elicitation was used to build a Bayesian Belief Network (BBN) model that predicts shorebird- and waterfowl-use days for each potential management action. The BBN was parameterized for a representative impoundment, MI-9, and predictions were re-scaled for this impoundment to predict outcomes at other impoundments on the basis of size. Parameter estimates in the BBN model can be updated using observations from ongoing monitoring that is part of the Integrated Waterbird Management and Monitoring (IWMM) program.The optimal portfolio of management actions depends on the importance, that is, weights, assigned to the three objectives, as well as the budget. Five scenarios with a variety of objective

Against Motivational Efficacy of Beliefs

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Seungbae Park

2015-07-01

Full Text Available Danielle Bromwich (2010 argues that a belief is motivationally efficacious in that, other things being equal, it disposes an agent to answer a question in accordance with that belief. I reply that what we are disposed to do is largely determined by our genes, whereas what we believe is largely determined by stimuli from the environment. We have a standing and default disposition to answer questions honestly, ceteris paribus, even before we are exposed to environmental stimuli. Since this standing and default disposition is innate, and our beliefs have their source in environmental stimuli, our beliefs cannot be the source of the disposition. Moreover, a recent finding in neuroscience suggests that motivation is extrinsic to belief.

Underestimating belief in climate change

Science.gov (United States)

Jost, John T.

2018-03-01

People are influenced by second-order beliefs — beliefs about the beliefs of others. New research finds that citizens in the US and China systematically underestimate popular support for taking action to curb climate change. Fortunately, they seem willing and able to correct their misperceptions.

Narcissism and belief in the paranormal.

Science.gov (United States)

Roe, Chris A; Morgan, Claire L

2002-04-01

The present study was designed to assess whether the relationship between narcissistic personality and paranormal belief identified by Tobacyk and Mitchell earlier could be replicated with a general population and to see whether the effect could be found with a narrower definition of paranormal beliefs that focuses only on belief in psychic phenomena. 75 participants completed the Narcissistic Personality Inventory and two measures of paranormal belief, the Paranormal Belief Scale and the Australian Sheep-Goat Scale. There was no correlation between narcissism and Paranormal Belief Scale scores, but narcissism and Australian Sheep-Goat Scale scores were significantly positively correlated. Of the three subscales to the Australian Sheep-Goat measure, scores for narcissism correlated with belief in ESP and PK but not in Life after death. These relationships were interpreted in terms of need for control.

Attitudes and beliefs as verbal behavior

OpenAIRE

Guerin, Bernard

1994-01-01

Attitudes and beliefs are analyzed as verbal behavior. It is argued that shaping by a verbal community is an essential part of the formation and maintenance of both attitudes and beliefs, and it is suggested that verbal communities mediate the important shift in control from events in the environment (attitudes and beliefs as tacts) to control by other words (attitudes and beliefs as intraverbals). It appears that both attitudes and beliefs are constantly being socially negotiated through aut...

First-in-human study of PET and optical dual-modality image-guided surgery in glioblastoma using 68Ga-IRDye800CW-BBN.

Science.gov (United States)

Li, Deling; Zhang, Jingjing; Chi, Chongwei; Xiao, Xiong; Wang, Junmei; Lang, Lixin; Ali, Iqbal; Niu, Gang; Zhang, Liwei; Tian, Jie; Ji, Nan; Zhu, Zhaohui; Chen, Xiaoyuan

2018-01-01

Purpose : Despite the use of fluorescence-guided surgery (FGS), maximum safe resection of glioblastoma multiforme (GBM) remains a major challenge. It has restricted surgeons between preoperative diagnosis and intraoperative treatment. Currently, an integrated approach combining preoperative assessment with intraoperative guidance would be a significant step in this direction. Experimental design : We developed a novel 68 Ga-IRDye800CW-BBN PET/near-infrared fluorescence (NIRF) dual-modality imaging probe targeting gastrin-releasing peptide receptor (GRPR) in GBM. The preclinical in vivo tumor imaging and FGS were first evaluated using an orthotopic U87MG glioma xenograft model. Subsequently, the first-in-human prospective cohort study (NCT 02910804) of GBM patients were conducted with preoperative PET assessment and intraoperative FGS. Results : The orthotopic tumors in mice could be precisely resected using the near-infrared intraoperative system. Translational cohort research in 14 GBM patients demonstrated an excellent correlation between preoperative positive PET uptake and intraoperative NIRF signal. The tumor fluorescence signals were significantly higher than those from adjacent brain tissue in vivo and ex vivo (p dual-modality imaging technique is feasible for integrated pre- and intraoperative targeted imaging via the same molecular receptor and improved intraoperative GBM visualization and maximum safe resection.

Perceived parental beliefs about the causes of success in sport: relationship to athletes' achievement goals and personal beliefs.

Science.gov (United States)

White, Sally A; Kavussanu, Maria; Tank, Kari M; Wingate, Jason M

2004-02-01

This study examined the relationship between perceived parental beliefs and young athletes' achievement goal orientations and personal beliefs about the causes of success in sport. Participants were 183 male and female athletes, 11-18 years old, involved in team sports. Athletes completed the Task and Ego Orientation in Sport Questionnaire, the Beliefs about the Causes of Sport Success Questionnaire, and two modified versions of the latter inventory to assess their perceptions of their parents' beliefs. Canonical correlation analysis revealed that perceived parental beliefs were related to goal orientations and personal beliefs in a conceptually coherent fashion. Thus, the perceived parental belief that effort leads to success in sport was related to athletes' task orientation and personal belief that effort causes sport success. In contrast, the perceived parental beliefs that superior ability, external factors, and using deceptive tactics are precursors to success in sport corresponded to athletes' ego orientation and the same personal beliefs. The findings are discussed in terms of their implications for understanding the socialization experiences of young athletes.

Mentalizing regions represent distributed, continuous, and abstract dimensions of others' beliefs.

Science.gov (United States)

Koster-Hale, Jorie; Richardson, Hilary; Velez, Natalia; Asaba, Mika; Young, Liane; Saxe, Rebecca

2017-11-01

The human capacity to reason about others' minds includes making causal inferences about intentions, beliefs, values, and goals. Previous fMRI research has suggested that a network of brain regions, including bilateral temporo-parietal junction (TPJ), superior temporal sulcus (STS), and medial prefrontal-cortex (MPFC), are reliably recruited for mental state reasoning. Here, in two fMRI experiments, we investigate the representational content of these regions. Building on existing computational and neural evidence, we hypothesized that social brain regions contain at least two functionally and spatially distinct components: one that represents information related to others' motivations and values, and another that represents information about others' beliefs and knowledge. Using multi-voxel pattern analysis, we find evidence that motivational versus epistemic features are independently represented by theory of mind (ToM) regions: RTPJ contains information about the justification of the belief, bilateral TPJ represents the modality of the source of knowledge, and VMPFC represents the valence of the resulting emotion. These representations are found only in regions implicated in social cognition and predict behavioral responses at the level of single items. We argue that cortical regions implicated in mental state inference contain complementary, but distinct, representations of epistemic and motivational features of others' beliefs, and that, mirroring the processes observed in sensory systems, social stimuli are represented in distinct and distributed formats across the human brain. Copyright © 2017 The Authors. Published by Elsevier Inc. All rights reserved.

Measurement of the Constructs of Health Belief Model related to Self-care during Pregnancy in Women Referred to South Tehran Health Network

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Yalda Soleiman Ekhtiari

2016-03-01

Full Text Available Background and Objective: Self-care activities during pregnancy can be effective in reducing adverse pregnancy outcomes. Health Belief Model (HBM is one of the most applicable models in educational need assessment for planning and implementation of educational interventions. The purpose of this study was to measurement of the constructs of HBM related to self-care during pregnancy in women referred to South Tehran health network.Materials and Methods: In this cross-sectional study 270 pregnant women who referred to health centers of South Tehran Health Networks participated. Demographic, knowledge and attitude questionnaires based on constructs of HBM was used to measure the status of knowledge and attitude of women. Data were analyzed using statistical software SPSS18.Results: Results showed that 92.2% of women had the knowledge scores in good level. The scores of perceived severity, perceived self-efficacy and cues to action were in good level in almost of women but almost of women obtained weak point in perceived susceptibility, perceived benefits and barriersConclusion: HBM can be used as an appropriate tool for assessment the status of pregnant women in the field of self-care behaviors during pregnancy and planning and implementation of educational interventions.

The Making of Paranormal Belief: History, Discourse Analysis and the Object of Belief

OpenAIRE

White, Lewis

2013-01-01

The present study comprises a discursive analysis of a cognitive phenomenon, paranormal beliefs. A discursive psychological approach to belief highlights that an important component of the cognitivist work has been how the object of paranormal belief has been defined in formal study. Using discourse analysis, as developed as a method in the history of psychology, this problem is explored through analysis of published scales. The findings highlight three rhetorical themes that are deployed in ...

Intrusion Detection System Using Deep Neural Network for In-Vehicle Network Security.

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Min-Joo Kang

Full Text Available A novel intrusion detection system (IDS using a deep neural network (DNN is proposed to enhance the security of in-vehicular network. The parameters building the DNN structure are trained with probability-based feature vectors that are extracted from the in-vehicular network packets. For a given packet, the DNN provides the probability of each class discriminating normal and attack packets, and, thus the sensor can identify any malicious attack to the vehicle. As compared to the traditional artificial neural network applied to the IDS, the proposed technique adopts recent advances in deep learning studies such as initializing the parameters through the unsupervised pre-training of deep belief networks (DBN, therefore improving the detection accuracy. It is demonstrated with experimental results that the proposed technique can provide a real-time response to the attack with a significantly improved detection ratio in controller area network (CAN bus.

Intrusion Detection System Using Deep Neural Network for In-Vehicle Network Security.

Science.gov (United States)

Kang, Min-Joo; Kang, Je-Won

2016-01-01

A novel intrusion detection system (IDS) using a deep neural network (DNN) is proposed to enhance the security of in-vehicular network. The parameters building the DNN structure are trained with probability-based feature vectors that are extracted from the in-vehicular network packets. For a given packet, the DNN provides the probability of each class discriminating normal and attack packets, and, thus the sensor can identify any malicious attack to the vehicle. As compared to the traditional artificial neural network applied to the IDS, the proposed technique adopts recent advances in deep learning studies such as initializing the parameters through the unsupervised pre-training of deep belief networks (DBN), therefore improving the detection accuracy. It is demonstrated with experimental results that the proposed technique can provide a real-time response to the attack with a significantly improved detection ratio in controller area network (CAN) bus.

Erosion of belief and disbelief: effects of religiosity and negative affect on beliefs in the paranormal and supernatural.

Science.gov (United States)

Beck, R; Miller, J P

2001-04-01

The authors investigated the effects of religiosity and negative affect on beliefs in the paranormal and supernatural among 94 undergraduate students enrolled in psychology classes at a small, private U.S. university. They hypothesized that religiosity would predict differential beliefs in the supernatural versus the paranormal but that negative affect would attenuate these beliefs. In addition, the authors predicted that belief in the supernatural and negative affect would interact to predict belief in the paranormal. Overall, the results were consistent with predictions. The religious participants were skeptical of paranormal phenomena but were accepting of supernatural phenomena. In addition, increased reports of negative affect over the preceding year appeared to attenuate belief in the supernatural for the religious participants. By contrast, for the nonreligious participants, increased belief in both the supernatural and paranormal was predicted when reports of negative affect were high. Finally, the interaction of supernatural belief and negative affect significantly predicted belief in the paranormal.

Improved Deep Belief Networks (IDBN Dynamic Model-Based Detection and Mitigation for Targeted Attacks on Heavy-Duty Robots

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Lianpeng Li

2018-04-01

Full Text Available In recent years, the robots, especially heavy-duty robots, have become the hardest-hit areas for targeted attacks. These attacks come from both the cyber-domain and the physical-domain. In order to improve the security of heavy-duty robots, this paper proposes a detection and mitigation mechanism which based on improved deep belief networks (IDBN and dynamic model. The detection mechanism consists of two parts: (1 IDBN security checks, which can detect targeted attacks from the cyber-domain; (2 Dynamic model and security detection, used to detect the targeted attacks which can possibly lead to a physical-domain damage. The mitigation mechanism was established on the base of the detection mechanism and could mitigate transient and discontinuous attacks. Moreover, a test platform was established to carry out the performance evaluation test for the proposed mechanism. The results show that, the detection accuracy for the attack of the cyber-domain of IDBN reaches 96.2%, and the detection accuracy for the attack of physical-domain control commands reaches 94%. The performance evaluation test has verified the reliability and high efficiency of the proposed detection and mitigation mechanism for heavy-duty robots.

Extensible Adaptive System for STEM Learning

Science.gov (United States)

2013-07-16

Copyright 2013 Raytheon BBN Technologies Corp. All Rights Reserved ONR STEM Grand Challenge Extensible Adaptive System for STEM Learning ...Contract # N00014-12-C-0535 Raytheon BBN Technologies Corp. (BBN) Reference # 14217 In partial fulfillment of contract deliverable item # A001...Quarterly Progress Report #2 April 7, 2013 –July 6, 2013 Submitted July 16, 2013 BBN Technical POC: John Makhoul Raytheon BBN Technologies

Homo economicus belief inhibits trust.

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Ziqiang Xin

Full Text Available As a foundational concept in economics, the homo economicus assumption regards humans as rational and self-interested actors. In contrast, trust requires individuals to believe partners' benevolence and unselfishness. Thus, the homo economicus belief may inhibit trust. The present three experiments demonstrated that the direct exposure to homo economicus belief can weaken trust. And economic situations like profit calculation can also activate individuals' homo economicus belief and inhibit their trust. It seems that people's increasing homo economicus belief may serve as one cause of the worldwide decline of trust.

Homo Economicus Belief Inhibits Trust

Science.gov (United States)

Xin, Ziqiang; Liu, Guofang

2013-01-01

As a foundational concept in economics, the homo economicus assumption regards humans as rational and self-interested actors. In contrast, trust requires individuals to believe partners’ benevolence and unselfishness. Thus, the homo economicus belief may inhibit trust. The present three experiments demonstrated that the direct exposure to homo economicus belief can weaken trust. And economic situations like profit calculation can also activate individuals’ homo economicus belief and inhibit their trust. It seems that people’s increasing homo economicus belief may serve as one cause of the worldwide decline of trust. PMID:24146907

Paranormal beliefs of Latvian college students: a Latvian version of the revised paranormal belief scale.

Science.gov (United States)

Utinans, A; Ancane, G; Tobacyk, J J; Boyraz, G; Livingston, M M; Tobacyk, J S

2015-02-01

A Latvian version of the Revised Paranormal Belief Scale (RPBS) was completed by 229 Latvian university students. Exploratory and confirmatory factor analyses revealed six relatively independent factors labeled Magical Abilities, Psychokinesis, Traditional Religious Belief, Superstition, Spirit Travel, and Extraordinary Life Forms. Based on the motivational-control model, it was hypothesized that the societal stressors affecting Latvian society during the last 50 yr. have led to a reduced sense of personal control which, in turn, has resulted in increased endorsement of paranormal beliefs to re-establish a sense of control. The motivational-control hypothesis was not supported. Results indicated that (except for Traditional Religious Belief in women), the majority of these students were disbelievers in paranormal phenomena. As hypothesized, Latvian women reported significantly greater paranormal belief than men.

Teacher Beliefs and Technology Integration

Science.gov (United States)

Kim, ChanMin; Kim, Min Kyu; Lee, Chiajung; Spector, J. Michael; DeMeester, Karen

2013-01-01

The purpose of this exploratory mixed methods study was to investigate how teacher beliefs were related to technology integration practices. We were interested in how and to what extent teachers' (a) beliefs about the nature of knowledge and learning, (b) beliefs about effective ways of teaching, and (c) technology integration practices were…

Frameless ALOHA Protocol for Wireless Networks

DEFF Research Database (Denmark)

Stefanovic, Cedomir; Popovski, Petar; Vukobratovic, Dejan

2012-01-01

We propose a novel distributed random access scheme for wireless networks based on slotted ALOHA, motivated by the analogies between successive interference cancellation and iterative belief-propagation decoding on erasure channels. The proposed scheme assumes that each user independently accesse...

Are essentialist beliefs associated with prejudice?

Science.gov (United States)

Haslam, Nick; Rothschild, Louis; Ernst, Donald

2002-03-01

Gordon Allport (1954) proposed that belief in group essences is one aspect of the prejudiced personality, alongside a rigid, dichotomous and ambiguity-intolerant cognitive style. We examined whether essentialist beliefs-beliefs that a social category has a fixed, inherent, identity-defining nature-are indeed associated in this fashion with prejudice towards black people, women and gay men. Allport's claim, which is mirrored by many contemporary social theorists, received partial support but had to be qualified in important respects. Essence-related beliefs were associated strongly with anti-gay attitudes but only weakly with sexism and racism, and they did not reflect a cognitive style that was consistent across stigmatized categories. When associations with prejudice were obtained, only a few specific beliefs were involved, and some anti-essentialist beliefs were associated with anti-gay attitudes. Nevertheless, the powerful association that essence-related beliefs had with anti-gay attitudes was independent of established prejudice-related traits, indicating that they have a significant role to play in the psychology of prejudice.

How psychotic-like are paranormal beliefs?

Science.gov (United States)

Cella, Matteo; Vellante, Marcello; Preti, Antonio

2012-09-01

Paranormal beliefs and Psychotic-like Experiences (PLE) are phenotypically similar and can occur in individuals with psychosis but also in the general population; however the relationship of these experiences for psychosis risk is largely unclear. This study investigates the association of PLE and paranormal beliefs with psychological distress. Five hundred and three young adults completed measures of paranormal beliefs (Beliefs in the Paranormal Scale), psychological distress (General Health Questionnaire), delusion (Peters et al. Delusions Inventory), and hallucination (Launay-Slade Hallucination Scale) proneness. The frequency and intensity of PLE was higher in believers in the paranormal compared to non-believers, however psychological distress levels were comparable. Regression findings confirmed that paranormal beliefs were predicted by delusion and hallucination-proneness but not psychological distress. The use of a cross-sectional design in a specific young adult population makes the findings exploratory and in need of replication with longitudinal studies. The predictive value of paranormal beliefs and experiences for psychosis may be limited; appraisal or the belief emotional salience rather than the belief per se may be more relevant risk factors to predict psychotic risk. Copyright © 2012 Elsevier Ltd. All rights reserved.

Agency Beliefs Over Time and Across Cultures: Free Will Beliefs Predict Higher Job Satisfaction

Science.gov (United States)

Feldman, Gilad; Farh, Jiing-Lih; Wong, Kin Fai Ellick

2017-01-01

In three studies, we examined the relationship between free will beliefs and job satisfaction over time and across cultures. Study 1 examined 252 Taiwanese real-estate agents over a 3-months period. Study 2 examined job satisfaction for 137 American workers on an online labor market over a 6-months period. Study 3 extended to a large sample of 14,062 employees from 16 countries and examined country-level moderators. We found a consistent positive relationship between the belief in free will and job satisfaction. The relationship was above and beyond other agency constructs (Study 2), mediated by perceived autonomy (Studies 2-3), and stronger in countries with a higher national endorsement of the belief in free will (Study 3). We conclude that free-will beliefs predict outcomes over time and across cultures beyond other agency constructs. We call for more cross-cultural and longitudinal studies examining free-will beliefs as predictors of real-life outcomes. PMID:29191084

Belief, hope and faith.

Science.gov (United States)

Figueiredo, Luis Claudio

2004-12-01

A case of hysteria is presented in order to create a frame of reference for the author's approach to the concepts of hope, belief and faith. A difference between hope as a 'sad passion' (which is here called regressive hope) and hope as a principle of mental functioning is established. The concept of hope will at first always be based on beliefs--either beliefs organised in the paranoid-schizoid position (called here fragmented and delusional beliefs)--or those organised from the depressive position (complex systems of beliefs, which end up being dogmatic); the latter typically occur in neurotics. It is suggested here that there is another possibility for hope, which is based on faith. The meaning of faith is considered here externally to the religious sense. The solid establishment of hope as a principle--based on faith--can be viewed as responsible for the opening up of creative potentials and as one of the main aims of analysis. Such an aim, however requires the establishment of a deep relationship, both in theory and in clinical practice, between the Kleinian question of the depressive position and the Freudian question of the Oedipus complex.

Effects of Epistemological Beliefs and Topic-Specific Beliefs on Undergraduates' Cognitive and Strategic Processing of Dual-Positional Text.

Science.gov (United States)

Kardash, CarolAnne M.; Howell, Karen L.

2000-01-01

Investigates effects of epistemological beliefs and topic-specific beliefs on undergraduates' (N=40) cognitive and strategic processing of a dual-positional text. Findings reveal that epistemological beliefs about the speed of learning affected the overall number of cognitive processes exhibited, whereas topic-specific beliefs interacted with the…

Conceptions about the mind-body problem and their relations to afterlife beliefs, paranormal beliefs, religiosity, and ontological confusions.

Science.gov (United States)

Riekki, Tapani; Lindeman, Marjaana; Lipsanen, Jari

2013-01-01

We examined lay people's conceptions about the relationship between mind and body and their correlates. In Study 1, a web survey (N = 850) of reflective dualistic, emergentistic, and monistic perceptions of the mind-body relationship, afterlife beliefs (i.e., common sense dualism), religiosity, paranormal beliefs, and ontological confusions about physical, biological, and psychological phenomena was conducted. In Study 2 (N = 73), we examined implicit ontological confusions and their relations to afterlife beliefs, paranormal beliefs, and religiosity. Correlation and regression analyses showed that reflective dualism, afterlife beliefs, paranormal beliefs, and religiosity were strongly and positively related and that reflective dualism and afterlife beliefs mediated the relationship between ontological confusions and religious and paranormal beliefs. The results elucidate the contention that dualism is a manifestation of universal cognitive processes related to intuitions about physical, biological, and psychological phenomena by showing that especially individuals who confuse the distinctive attributes of these phenomena tend to set the mind apart from the body.

Conceptions about the mind-body problem and their relations to afterlife beliefs, paranormal beliefs, religiosity, and ontological confusions

Science.gov (United States)

Riekki, Tapani; Lindeman, Marjaana; Lipsanen, Jari

2013-01-01

We examined lay people’s conceptions about the relationship between mind and body and their correlates. In Study 1, a web survey (N = 850) of reflective dualistic, emergentistic, and monistic perceptions of the mind-body relationship, afterlife beliefs (i.e., common sense dualism), religiosity, paranormal beliefs, and ontological confusions about physical, biological, and psychological phenomena was conducted. In Study 2 (N = 73), we examined implicit ontological confusions and their relations to afterlife beliefs, paranormal beliefs, and religiosity. Correlation and regression analyses showed that reflective dualism, afterlife beliefs, paranormal beliefs, and religiosity were strongly and positively related and that reflective dualism and afterlife beliefs mediated the relationship between ontological confusions and religious and paranormal beliefs. The results elucidate the contention that dualism is a manifestation of universal cognitive processes related to intuitions about physical, biological, and psychological phenomena by showing that especially individuals who confuse the distinctive attributes of these phenomena tend to set the mind apart from the body. PMID:25247011

Reliability analysis of reactor inspection robot(RIROB)

International Nuclear Information System (INIS)

Eom, H. S.; Kim, J. H.; Lee, J. C.; Choi, Y. R.; Moon, S. S.

2002-05-01

This report describes the method and the result of the reliability analysis of RIROB developed in Korea Atomic Energy Research Institute. There are many classic techniques and models for the reliability analysis. These techniques and models have been used widely and approved in other industries such as aviation and nuclear industry. Though these techniques and models have been approved in real fields they are still insufficient for the complicated systems such RIROB which are composed of computer, networks, electronic parts, mechanical parts, and software. Particularly the application of these analysis techniques to digital and software parts of complicated systems is immature at this time thus expert judgement plays important role in evaluating the reliability of the systems at these days. In this report we proposed a method which combines diverse evidences relevant to the reliability to evaluate the reliability of complicated systems such as RIROB. The proposed method combines diverse evidences and performs inference in formal and in quantitative way by using the benefits of Bayesian Belief Nets (BBN)

Changing Conspiracy Beliefs through Rationality and Ridiculing.

Science.gov (United States)

Orosz, Gábor; Krekó, Péter; Paskuj, Benedek; Tóth-Király, István; Bőthe, Beáta; Roland-Lévy, Christine

2016-01-01

Conspiracy theory (CT) beliefs can be harmful. How is it possible to reduce them effectively? Three reduction strategies were tested in an online experiment using general and well-known CT beliefs on a comprehensive randomly assigned Hungarian sample ( N = 813): exposing rational counter CT arguments, ridiculing those who hold CT beliefs, and empathizing with the targets of CT beliefs. Several relevant individual differences were measured. Rational and ridiculing arguments were effective in reducing CT, whereas empathizing with the targets of CTs had no effect. Individual differences played no role in CT reduction, but the perceived intelligence and competence of the individual who conveyed the CT belief-reduction information contributed to the success of the CT belief reduction. Rational arguments targeting the link between the object of belief and its characteristics appear to be an effective tool in fighting conspiracy theory beliefs.

Importance of Beliefs, Attitudes and Values in the Frame of Human Resource Motivation

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Claudia MOISE

2014-06-01

Full Text Available The article deals with a complex and original field of analyse – the role that concepts such as beliefs, attitudes and values can entail in the modern human resources management techniques that are dealing with employee’s motivation. Nowadays employees have a complex approach regarding motivation. Especially when we speak about big organisations such as multinational companies, we will find complex jobs having many tasks and a complicated network of inter-relations within the organisation. In such cases, as we speak about middle and top management positions, employee’s motivation is relying on different types of motivation: intrinsic and extrinsic altogether. The substantiation of an efficient motivational strategy can be based on the link between beliefs, attitudes and values of the employees and their motivation development process.

Psychics, aliens, or experience? Using the Anomalistic Belief Scale to examine the relationship between type of belief and probabilistic reasoning.

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Prike, Toby; Arnold, Michelle M; Williamson, Paul

2017-08-01

A growing body of research has shown people who hold anomalistic (e.g., paranormal) beliefs may differ from nonbelievers in their propensity to make probabilistic reasoning errors. The current study explored the relationship between these beliefs and performance through the development of a new measure of anomalistic belief, called the Anomalistic Belief Scale (ABS). One key feature of the ABS is that it includes a balance of both experiential and theoretical belief items. Another aim of the study was to use the ABS to investigate the relationship between belief and probabilistic reasoning errors on conjunction fallacy tasks. As expected, results showed there was a relationship between anomalistic belief and propensity to commit the conjunction fallacy. Importantly, regression analyses on the factors that make up the ABS showed that the relationship between anomalistic belief and probabilistic reasoning occurred only for beliefs about having experienced anomalistic phenomena, and not for theoretical anomalistic beliefs. Copyright © 2017 Elsevier Inc. All rights reserved.

Belief Functions: Theory and Applications - Proceedings of the 2nd International Conference on Belief Functions

CERN Document Server

Masson, Marie-Hélène

2012-01-01

The theory of belief functions, also known as evidence theory or Dempster-Shafer theory, was first introduced by Arthur P. Dempster in the context of statistical inference, and was later developed by Glenn Shafer as a general framework for modeling epistemic uncertainty. These early contributions have been the starting points of many important developments, including the Transferable Belief Model and the Theory of Hints. The theory of belief functions is now well established as a general framework for reasoning with uncertainty, and has well understood connections to other frameworks such as probability, possibility and imprecise probability theories.   This volume contains the proceedings of the 2nd International Conference on Belief Functions that was held in Compiègne, France on 9-11 May 2012. It gathers 51 contributions describing recent developments both on theoretical issues (including approximation methods, combination rules, continuous belief functions, graphical models and independence concepts) an...

On the Relevance of Using Bayesian Belief Networks in Wireless Sensor Networks Situation Recognition

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Marco Zennaro

2010-12-01

Full Text Available Achieving situation recognition in ubiquitous sensor networks (USNs is an important issue that has been poorly addressed by both the research and practitioner communities. This paper describes some steps taken to address this issue by effecting USN middleware intelligence using an emerging situation awareness (ESA technology. We propose a situation recognition framework where temporal probabilistic reasoning is used to derive and emerge situation awareness in ubiquitous sensor networks. Using data collected from an outdoor environment monitoring in the city of Cape Town, we illustrate the use of the ESA technology in terms of sensor system operating conditions and environmental situation recognition.

Development and Validation of the Family Beliefs Inventory: A Measure of Unrealistic Beliefs among Parents and Adolescents.

Science.gov (United States)

Roehling, Patricia Vincent; Robin, Arthur L.

1986-01-01

Evaluated the criterion-related validity of the Family Beliefs Inventory, a new self-report measure of unreasonable beliefs regarding parent-adolescent relationships. Distressed fathers displayed more unreasonable beliefs concerning ruination, obedience, perfectionism, and malicious intent than nondistressed fathers. Distressed adolescents…

Constructivism, Factoring, and Beliefs.

Science.gov (United States)

Rauff, James V.

1994-01-01

Discusses errors made by remedial intermediate algebra students in factoring polynomials in light of student definitions of factoring. Found certain beliefs about factoring to logically imply many of the errors made. Suggests that belief-based teaching can be successful in teaching factoring. (16 references) (Author/MKR)

Concern beliefs in medications: changes over time and medication use factors related to a change in beliefs.

Science.gov (United States)

Shiyanbola, Olayinka O; Farris, Karen B; Chrischilles, Elizabeth

2013-01-01

Concern belief in medication is a construct that may characterize patients' attitude toward managing medicines, and this could change with time. Understanding the factors that would impact a change in concern beliefs would be helpful in interventions that could reframe patients' perceptions about their medicines. To examine if patient concern beliefs in medications change over time, assess the characteristics of individuals whose beliefs change, and determine what factors might impact a change in patient beliefs. Secondary data analysis using 2 longitudinal studies. The first study was an Internet-based survey of Medicare enrollees pre-post Medicare Part D. The second study was a randomized controlled trial evaluating a medication management intervention among adults with physical limitations. Respondents were classified as those whose beliefs remained stable and those whose beliefs increased and decreased over 2 separate periods. Chi-square analysis examined significant differences across the groups. Multiple linear regressions examined factors that influence changes in patient beliefs. Among older adults, there were differences in perceived health status (χ(2)=26.05, P=.001), number of pharmacies used (χ(2)=17.41, P=.008), and number of medicines used after the start of Medicare Part D. There were no significant differences among adults with physical limitations. Among older adults, having an increased number of medicines over time and reporting a self-reported adverse effect to a physician were positively associated with an increase in concern beliefs in medication. Having an increase in adherence was associated with a decrease in concern beliefs over time. Concern beliefs in medications may contribute independent information about individuals' response to drug programs and policies. Outcomes of medication use may influence patient anxieties about medicines. The instability of patient concerns in medications that occurs with prescription drug coverage changes

Well-Founded Belief and Perceptual Justification

DEFF Research Database (Denmark)

Broncano-Berrocal, Fernando

2016-01-01

According to Alan Millar, justified beliefs are well-founded beliefs. Millar cashes out the notion of well-foundedness in terms of having an adequate reason to believe something and believing it for that reason. To make his account of justified belief compatible with perceptual justification he...

Scaling Irrational Beliefs in the General Attitude and Belief Scale

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Lindsay R. Owings

2013-04-01

Full Text Available Accurate measurement of key constructs is essential to the continued development of Rational-Emotive Behavior Therapy (REBT. The General Attitude and Belief Scale (GABS, a contemporary inventory of rational and irrational beliefs based on current REBT theory, is one of the most valid and widely used instruments available, and recent research has continued to improve its psychometric standing. In this study of 544 students, item response theory (IRT methods were used (a to identify the most informative item in each irrational subscale of the GABS, (b to determine the level of irrationality represented by each of those items, and (c to suggest a condensed form of the GABS for further study with clinical populations. Administering only the most psychometrically informative items to clients could result in economies of time and effort. Further research based on the scaling of items could clarify the specific patterns of irrational beliefs associated with particular clinical syndromes.

Knowledge and Beliefs About E-Cigarettes in Straight-to-Work Young Adults.

Science.gov (United States)

Gowin, Mary; Cheney, Marshall K; Wann, Taylor F

2017-02-01

Young adults are a growing segment of electronic cigarette (e-cigarette) users. Young adults who go straight to work (STW) from high school make up a large portion of the young adult population, yet research to date has focused on college-educated young adults. This study explored STW young adult beliefs and knowledge about e-cigarettes. Semistructured individual interviews were used to elicit in-depth information from STW young adults ages 19-31 from a state in the southwest United States. Thirty interviews were conducted focusing on beliefs about e-cigarettes, current knowledge, and information-seeking practices. Interviews were recorded, transcribed, and analyzed using NVivo. Nine themes were identified falling into three categories: (1) beliefs about e-cigarettes, (2) knowledge about e-cigarettes, and (3) personal rules about e-cigarettes. STW young adults held positive beliefs about the health and safety of e-cigarettes for themselves, others, and the environment. They reported their social networks and the Internet as reliable sources of information about e-cigarettes, but they reported parents as the best source for advice. Participants had rules about e-cigarettes that contradicted some of their beliefs such as using e-cigarettes around children indicating that their beliefs were not as strongly held as they initially reported. Industry marketing and contradictory information may contribute to STW young adult knowledge and beliefs about e-cigarettes. Lack of credible public health information may also contribute to this issue. Ensuring that what is known about the benefits and harms of e-cigarettes is conveyed through multichannel communication and continued monitoring of marketing practices of the e-cigarette industry in light of the soon to be implemented regulations should be top priorities for public health. Beliefs and knowledge of STW young adults have not been explored even though they are heavily targeted by the e-cigarette industry. This group

Beliefs About Sexual Intimate Partner Violence Perpetration Among Adolescents in South Africa.

Science.gov (United States)

Pöllänen, Katri; de Vries, Hein; Mathews, Catherine; Schneider, Francine; de Vries, Petrus J

2018-02-01

Sexual intimate partner violence (IPV) is a public health problem worldwide. Research regarding beliefs about perpetrating sexual IPV is, however, limited. This study investigated attitudes, social influence, and self-efficacy beliefs and intentions toward perpetrating sexual IPV among Grade 8 adolescents ( M age = 13.73, SD = 1.04) in the Western Cape Province of South Africa. The study sample was taken from the baseline data of the Promoting sexual and reproductive health among adolescents in Southern and Eastern Africa (PREPARE) study, a cluster-randomized controlled trial. Young adolescents ( N = 2,199), from 42 randomly selected high schools, participated in the study and answered a paper-and-pencil questionnaire. Multivariate ANOVA were conducted to assess differences in beliefs and intention toward perpetrating sexual IPV between boys and girls, and between perpetrators and nonperpetrators. Results showed that boys were more frequently perpetrators (11.3% vs. 3.2%) and victims (13.6% vs. 6.4%) of sexual IPV than girls. Boys' attitudes toward perpetrating sexual IPV were more supportive than girls'. Boys perceived their social network to be more likely to think that putting pressure on a boyfriend or girlfriend to have sex is okay, and boys had a lower self-efficacy to refrain from pressuring a boyfriend or girlfriend to have sex compared with girls. Both boys and girls, who have perpetrated sexual IPV, had more tolerant attitude, social influence, and self-efficacy beliefs toward sexual IPV perpetration, compared with nonperpetrators. Intention not to perpetrate sexual IPV did not differ between boys and girls, or between perpetrators and nonperpetrators. Our findings suggest that interventions should address attitude and social influence beliefs regarding sexual IPV perpetration. More attention should be given to sexual IPV perpetration among boys. Given that sexual IPV victimization and perpetration are significantly linked, prevention of sexual IPV

Pre-service teachers’ perceived value of general pedagogical knowledge for practice: Relations with epistemic beliefs and source beliefs

Science.gov (United States)

Rosman, Tom; Rueß, Julia; Syring, Marcus; Schneider, Jürgen

2017-01-01

Pre-service teachers tend to devalue general pedagogical knowledge (GPK) as a valid source for deriving successful teaching practices. The present study investigated beliefs about knowledge sources and epistemic beliefs as predictors for students’ perceived value of GPK. Three pre-registered hypotheses were tested. We expected beliefs that GPK originates from scientific sources to entail a devaluation of GPK (Hypothesis 1). Concerning epistemic beliefs, we expected absolute beliefs to positively, and multiplistic beliefs to negatively predict pre-service teachers’ perceived practical value of GPK (Hypothesis 2). Finally, we expected relationships between epistemic beliefs and pre-service teachers’ perceived practical value of GPK to be confounded by epistemic trustworthiness, perceived topic-specific consistency and topic-specific familiarity (Hypothesis 3). In a study using a split plot design, 365 pre-service teachers were presented with four texts on different educational research topics. For each topic, three text versions were constructed. Even though they were invariant in content, these versions varied in a way that the results were allegedly generated by a practitioner, an expert or by means of a scientific study. Unexpectedly, results showed that research findings allegedly generated by means of a scientific study were associated with a higher perceived value of (topic-specific) GPK for practice (Hypothesis 1). As expected, the perceived value of GPK for practice was predicted by topic-specific multiplism and domain-specific absolutism (Hypothesis 2). These predictive effects were confounded by expertise evaluations of the source and the consistency of prior beliefs with the presented research results (Hypothesis 3). In summary, our results suggest that source beliefs might not be responsible for the devaluation of GPK, but that beliefs on the nature and structure of GPK (i.e., epistemic beliefs) might play an even more important role in this respect

Pre-service teachers' perceived value of general pedagogical knowledge for practice: Relations with epistemic beliefs and source beliefs.

Science.gov (United States)

Merk, Samuel; Rosman, Tom; Rueß, Julia; Syring, Marcus; Schneider, Jürgen

2017-01-01

Pre-service teachers tend to devalue general pedagogical knowledge (GPK) as a valid source for deriving successful teaching practices. The present study investigated beliefs about knowledge sources and epistemic beliefs as predictors for students' perceived value of GPK. Three pre-registered hypotheses were tested. We expected beliefs that GPK originates from scientific sources to entail a devaluation of GPK (Hypothesis 1). Concerning epistemic beliefs, we expected absolute beliefs to positively, and multiplistic beliefs to negatively predict pre-service teachers' perceived practical value of GPK (Hypothesis 2). Finally, we expected relationships between epistemic beliefs and pre-service teachers' perceived practical value of GPK to be confounded by epistemic trustworthiness, perceived topic-specific consistency and topic-specific familiarity (Hypothesis 3). In a study using a split plot design, 365 pre-service teachers were presented with four texts on different educational research topics. For each topic, three text versions were constructed. Even though they were invariant in content, these versions varied in a way that the results were allegedly generated by a practitioner, an expert or by means of a scientific study. Unexpectedly, results showed that research findings allegedly generated by means of a scientific study were associated with a higher perceived value of (topic-specific) GPK for practice (Hypothesis 1). As expected, the perceived value of GPK for practice was predicted by topic-specific multiplism and domain-specific absolutism (Hypothesis 2). These predictive effects were confounded by expertise evaluations of the source and the consistency of prior beliefs with the presented research results (Hypothesis 3). In summary, our results suggest that source beliefs might not be responsible for the devaluation of GPK, but that beliefs on the nature and structure of GPK (i.e., epistemic beliefs) might play an even more important role in this respect

Pre-service teachers' perceived value of general pedagogical knowledge for practice: Relations with epistemic beliefs and source beliefs.

Directory of Open Access Journals (Sweden)

Samuel Merk

Full Text Available Pre-service teachers tend to devalue general pedagogical knowledge (GPK as a valid source for deriving successful teaching practices. The present study investigated beliefs about knowledge sources and epistemic beliefs as predictors for students' perceived value of GPK. Three pre-registered hypotheses were tested. We expected beliefs that GPK originates from scientific sources to entail a devaluation of GPK (Hypothesis 1. Concerning epistemic beliefs, we expected absolute beliefs to positively, and multiplistic beliefs to negatively predict pre-service teachers' perceived practical value of GPK (Hypothesis 2. Finally, we expected relationships between epistemic beliefs and pre-service teachers' perceived practical value of GPK to be confounded by epistemic trustworthiness, perceived topic-specific consistency and topic-specific familiarity (Hypothesis 3. In a study using a split plot design, 365 pre-service teachers were presented with four texts on different educational research topics. For each topic, three text versions were constructed. Even though they were invariant in content, these versions varied in a way that the results were allegedly generated by a practitioner, an expert or by means of a scientific study. Unexpectedly, results showed that research findings allegedly generated by means of a scientific study were associated with a higher perceived value of (topic-specific GPK for practice (Hypothesis 1. As expected, the perceived value of GPK for practice was predicted by topic-specific multiplism and domain-specific absolutism (Hypothesis 2. These predictive effects were confounded by expertise evaluations of the source and the consistency of prior beliefs with the presented research results (Hypothesis 3. In summary, our results suggest that source beliefs might not be responsible for the devaluation of GPK, but that beliefs on the nature and structure of GPK (i.e., epistemic beliefs might play an even more important role in this

Forward induction reasoning and correct beliefs

NARCIS (Netherlands)

Perea y Monsuwé, Andrés

2017-01-01

All equilibrium concepts implicitly make a correct beliefs assumption, stating that a player believes that his opponents are correct about his first-order beliefs. In this paper we show that in many dynamic games of interest, this correct beliefs assumption may be incompatible with a very basic form

Comparisons of Belief-Based Personality Constructs in Polish and American University Students: Paranormal Beliefs, Locus of Control, Irrational Beliefs, and Social Interest.

Science.gov (United States)

Tobacyk, Jerome J.; Tobacyk, Zofia Socha

1992-01-01

Uses Social Learning Theory to compare 149 university students from Poland with 136 university students from the southern United States for belief-based personality constructs and personality correlates of paranormal beliefs. As hypothesized, Poles reported a more external locus of control and significantly greater endorsement of irrational…

Safety culture and networks of influence

International Nuclear Information System (INIS)

Pereira, Carlos Henrique V.; Barroso, Antonio C.O.; Vieira Neto, Antonio S.

2011-01-01

This paper analyzes the social networks that influence the formation and maintenance of the safety culture within the Institute of Energy and Nuclear Research (IPEN-CNEN/SP). From the mapping and analysis of social networks, actors with a significant degree of influence were identified. Later using a questionnaire, the beliefs of the population sample were mapped. Thus, the importance of key actors in the network analysis could be confirmed statistically. Therefore, based on the mentioned methods we could demonstrate our hypothesis, that there are some social networks that are important in the formation of safety culture, as well as the fact that the influence of some distinguished actors plays an essential role in this amalgam. (author)

Safety culture and networks of influence

Energy Technology Data Exchange (ETDEWEB)

Pereira, Carlos Henrique V.; Barroso, Antonio C.O.; Vieira Neto, Antonio S., E-mail: carloshvp@usp.br, E-mail: barroso@ipen.br, E-mail: asvneto@ipen.br [Instituto de Pesquisas Energeticas e Nucleares (IPEN/CNEN-SP), Sao Paulo, SP (Brazil)

2011-07-01

This paper analyzes the social networks that influence the formation and maintenance of the safety culture within the Institute of Energy and Nuclear Research (IPEN-CNEN/SP). From the mapping and analysis of social networks, actors with a significant degree of influence were identified. Later using a questionnaire, the beliefs of the population sample were mapped. Thus, the importance of key actors in the network analysis could be confirmed statistically. Therefore, based on the mentioned methods we could demonstrate our hypothesis, that there are some social networks that are important in the formation of safety culture, as well as the fact that the influence of some distinguished actors plays an essential role in this amalgam. (author)

Social Networks: Rational Learning and Information Aggregation

Science.gov (United States)

2009-09-01

predecessor, Gale and Kariv (2003) who generalize the payoff equalization result of Bala and Goyal (1998) in connected social networks (discussed below...requires more notation. Using Bayes’ Rule and the assumption of equal priors on the state θ, we have that the social belief given by observing... Social Networks: Rational Learning and Information Aggregation by Ilan Lobel B.Sc., Pontif́ıcia Universidade Católica do Rio de Janeiro (2004

Economic Beliefs and Party Preference

OpenAIRE

Michael W.M. Roos; Andreas Orland

2014-01-01

This paper reports the results of a questionnaire study used to explore the economic understanding, normative positions along the egalitarian-libertarian spectrum, and the party preferences of a large student sample. The aim of the study is both to find socio-economic determinants of normative and positive beliefs and to explore how beliefs about the economy influence party support. We find that positive beliefs of lay people differ systematically from those of economic experts. Positive beli...

Examining the incremental contribution of metacognitive beliefs beyond content-specific beliefs in relation to posttraumatic stress in a community sample.

Science.gov (United States)

Fergus, Thomas A; Bardeen, Joseph R

2017-11-01

Cognitive-behavioral models of posttraumatic stress disorder (PTSD) propose that the content of one's thoughts, including negative beliefs about the self, others, and world, play a fundamental role in our understanding and treatment of PTSD. Metacognitive theory suggests that metacognitive beliefs (i.e., beliefs about thinking), rather than content-specific beliefs, underlie PTSD. The present study provided the first known examination of the incremental contribution of metacognitive beliefs and trauma-related cognitions in relation to posttraumatic stress. Community adults recruited through an online crowdsourcing website who reported experiencing a criterion A traumatic event (N = 299) completed self-report measures of the study variables. Results from multiple linear regression analyses indicated that metacognitive beliefs of the uncontrollability and danger of thinking shared associations with each posttraumatic stress symptom cluster after accounting for the effects of content-specific beliefs and other covariates. The individual content-specific beliefs did not consistently share associations with posttraumatic stress symptoms in the regression analyses. The contribution of the individual content-specific beliefs to posttraumatic stress symptoms was consistently attenuated or rendered nonsignificant after accounting for metacognitive beliefs. These results are consistent with metacognitive theory in suggesting that metacognitive beliefs may be more important than trauma-related thought content in relation to posttraumatic stress. (PsycINFO Database Record (c) 2017 APA, all rights reserved).

False Belief Reasoning in Adults with and without Autistic Spectrum Disorder: Similarities and Differences

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Monika Sommer

2018-02-01

Full Text Available A central diagnostic criteria for autism spectrum disorder (ASD is the qualitative impairment in reciprocal social interaction and a prominent hypotheses that tried to explain this impairment is the Theory of Mind (ToM deficit hypotheses. On a behavioral level the critical test for having a ToM, the understanding of false beliefs (FB, is often used for testing ToM abilities in individuals with ASD. Investigating the neural underpinnings several neuroimaging studies revealed a network of areas involved in FB reasoning in neurotypical individuals. For ASD individuals the neural correlates of false belief processing are largely unknown. Using functional magnetic resonance imaging and an adapted unexpected transfer task, that makes it possible to distinguish between the computation of diverging beliefs and the selection of a belief-associated response, we investigated a group of adult high-functioning individuals with ASD (N = 15 and an age and IQ matched group of neurotypical adults (NT; N = 15. On the behavioral level we found no group differences. On the neural level, results were two-fold: In the story phase, in which participants had to compute whether the character's belief is congruent or incongruent to their own belief, there were no differences between neurotypical participants and those diagnosed with ASD. But, in the subsequent question phase, participants with ASD showed increased activity in the bilateral anterior prefrontal cortex, the left posterior frontal cortex, the left superior temporal gyrus, and the left temporoparietal area. These results suggest that during the story phase in which the participants processed observable actions the neural correlates do not differ between adult individuals with ASD and NT individuals. But in the question phase in which participants had to infer an unobservable mental state results revealed neural differences between the two groups. Possibly, these subtle neural processing differences may

The influence of relationship beliefs on gift giving

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Rai Dipankar

2017-12-01

Full Text Available People have fundamental beliefs about what constitutes a good relationship, known as implicit theories of relationship, where some people have destiny beliefs whereas others have growth beliefs. People with destiny beliefs believe that potential partners are meant either for each other or not, whereas people with growth beliefs believe that successful relationships are cultivated and developed. This research shows that different implicit theories of relationship influence consumers’ gift choice to their significant others. We demonstrate, through two studies, that consumers with destiny beliefs prefer giving gifts that are more feasible in nature, whereas consumers with growth beliefs prefer giving gifts that are more desirable in nature. We show that this effect is mediated by desirability-feasibility considerations. Specifically, consumers with destiny beliefs focus on feasibility considerations, which leads them to choose a highly feasible gift. Conversely, consumers with growth beliefs focus on desirability considerations, which leads them to choose a highly desirable gift. We also discuss the theoretical and managerial implications of our research.

Belief in reciprocity in a Chinese sample.

Science.gov (United States)

Zhang, Zhen; Zhang, Jianxin

2012-08-01

Belief in reciprocity refers to a personally internalized faith in the reciprocity norm: that people will return positive and negative interactions or favors in kind. The current study aims to examine the relationship between belief in reciprocity and altruism among a Chinese sample. The Personal Norm of Reciprocity Scale, Trait Forgiveness Scale, Prosocial Tendency Measure, and Altruism Scale were used to assess extent of belief in reciprocity, forgiveness, and prosocial motivation, respectively, among 204 Chinese undergraduates. The results indicated that belief in reciprocity was a partially negative, but not neutral, reciprocity norm for Chinese people. Specifically, belief in reciprocity was positively related to negative reciprocity, but not significantly related to positive reciprocity. Moreover, belief in reciprocity was negatively related to both prosocial tendency and altruistic motivation. The results also indicated that forgiveness largely mediated the effect of belief in reciprocity on altruism. Finally, the implications and limitations of the current study were discussed.

Betting and Belief: Modeling the Impact of Prediction Markets on Public Attribution of Climate Change

Science.gov (United States)

Gilligan, J. M.; Nay, J. J.; van der Linden, M.

2016-12-01

Despite overwhelming scientific evidence and an almost complete consensus among scientists, a large fraction of the American public is not convinced that global warming is anthropogenic. This doubt correlates strongly with political, ideological, and cultural orientation. [1] It has been proposed that people who do not trust climate scientists tend to trust markets, so prediction markets might be able to influence their beliefs about the causes of climate change. [2] We present results from an agent-based simulation of a prediction market in which traders invest based on their beliefs about what drives global temperature change (here, either CO2 concentration or total solar irradiance (TSI), which is a popular hypothesis among many who doubt the dominant role of CO2). At each time step, traders use historical and observed temperatures and projected future forcings (CO2 or TSI) to update Bayesian posterior probability distributions for future temperatures, conditional on their belief about what drives climate change. Traders then bet on future temperatures by trading in climate futures. Trading proceeds by a continuous double auction. Traders are randomly assigned initial beliefs about climate change, and they have some probability of changing their beliefs to match those of the most successful traders in their social network. We simulate two alternate realities in which the global temperature is controlled either by CO2 or by TSI, with stochastic noise. In both cases traders' beliefs converge, with a large majority reaching agreement on the actual cause of climate change. This convergence is robust, but the speed with which consensus emerges depends on characteristics of the traders' psychology and the structure of the market. Our model can serve as a test-bed for studying how beliefs might evolve under different market structures and different modes of decision-making and belief-change. We will report progress on studying alternate models of belief-change. This

Explaining body size beliefs in anorexia.

Science.gov (United States)

Gadsby, Stephen

2017-11-01

Cognitive neuropsychiatry has had much success in providing theoretical models for the causal origins of many delusional beliefs. Recently, it has been suggested that some anorexia nervosa patients' beliefs about their own body size should be considered delusions. As such, it seems high time the methods of cognitive neuropsychiatry were turned to modelling the false body size beliefs of anorexics. In this paper, I adopt an empiricist approach to modelling the causal origins of false body size beliefs in anorexia. Within the background of cognitive neuropsychiatry, empiricist models claim that abnormal beliefs are grounded by abnormal experiences bearing similar content. I discuss the kinds of abnormal experiences of body size anorexics suffer from which could ground their false beliefs about body size. These oversized experiences come in three varieties: false self-other body comparisons, spontaneous mental imagery of a fat body and distorted perception of affordances. Further theoretical and empirical research into the oversized experiences which anorexics suffer from presents a promising avenue for understanding and treating the disorder.

Probabilistic reasoning in intelligent systems networks of plausible inference

CERN Document Server

Pearl, Judea

1988-01-01

Probabilistic Reasoning in Intelligent Systems is a complete and accessible account of the theoretical foundations and computational methods that underlie plausible reasoning under uncertainty. The author provides a coherent explication of probability as a language for reasoning with partial belief and offers a unifying perspective on other AI approaches to uncertainty, such as the Dempster-Shafer formalism, truth maintenance systems, and nonmonotonic logic. The author distinguishes syntactic and semantic approaches to uncertainty--and offers techniques, based on belief networks, that provid

Gravity, God and Ghosts? Parents' Beliefs in Science, Religion, and the Paranormal and the Encouragement of Beliefs in Their Children

Science.gov (United States)

Braswell, Gregory S.; Rosengren, Karl S.; Berenbaum, Howard

2012-01-01

Using a questionnaire, the present study examined parents' beliefs regarding the development of children's beliefs about science, religion, and the paranormal. The study also investigated parental encouragement of children's beliefs, as well as parents' own beliefs within these domains. Results revealed that parents make distinctions between…

Decision Analysis Tools for Volcano Observatories

Science.gov (United States)

Hincks, T. H.; Aspinall, W.; Woo, G.

2005-12-01

Staff at volcano observatories are predominantly engaged in scientific activities related to volcano monitoring and instrumentation, data acquisition and analysis. Accordingly, the academic education and professional training of observatory staff tend to focus on these scientific functions. From time to time, however, staff may be called upon to provide decision support to government officials responsible for civil protection. Recognizing that Earth scientists may have limited technical familiarity with formal decision analysis methods, specialist software tools that assist decision support in a crisis should be welcome. A review is given of two software tools that have been under development recently. The first is for probabilistic risk assessment of human and economic loss from volcanic eruptions, and is of practical use in short and medium-term risk-informed planning of exclusion zones, post-disaster response, etc. A multiple branch event-tree architecture for the software, together with a formalism for ascribing probabilities to branches, have been developed within the context of the European Community EXPLORIS project. The second software tool utilizes the principles of the Bayesian Belief Network (BBN) for evidence-based assessment of volcanic state and probabilistic threat evaluation. This is of practical application in short-term volcano hazard forecasting and real-time crisis management, including the difficult challenge of deciding when an eruption is over. An open-source BBN library is the software foundation for this tool, which is capable of combining synoptically different strands of observational data from diverse monitoring sources. A conceptual vision is presented of the practical deployment of these decision analysis tools in a future volcano observatory environment. Summary retrospective analyses are given of previous volcanic crises to illustrate the hazard and risk insights gained from use of these tools.

Impacts of land-use change on the water cycle of urban areas within the Upper Great Lakes drainage basin

Science.gov (United States)

Bowling, L. C.; Cherkauer, K. A.; Pijanowski, B. C.; Niyogi, D.

2006-12-01

Urbanization is altering the global landscape at an unprecedented rate. This form of land cover/land-use change (LCLUC) can significantly reduce infiltration and runoff response times, and alter heat and water vapor fluxes, which can further alter surface-forced regional circulation patterns and modulate precipitation volume and intensity. Spatial patterns of future LCLUC are projected using the Land Transformation Model (LTM), enhanced to incorporate dynamic landcover, economics and policy using Bayesian Belief Networks (LTM- BBN). Different land use scenarios predicted by the LTM-BBN as well as a pre-development scenario are represented through the Unified Noah Land Surface Model (LSM) with an enhanced urban canopy model, embedded in the Weather Research and Forecasting (WRF) model. The coupled WRF-Noah LSM model will be used to investigate the connections between land-use, hydrometeorology and the atmosphere, through analysis of water and energy balances over several urbanized watersheds within the Upper Great Lakes region. Preliminary results focus on a single watershed, the White River in Indiana, which includes the city of Indianapolis. Coupled WRF-Noah simulations made using pre and post-development land use maps provide a 7 year climatology of convective storm morphology around the urban center. Precipitation and other meteorological variables from the WRF-Noah simulations are used to drive simulations of the White River watershed using the Variable Infiltration Capacity (VIC) macroscale hydrologic model. The VIC model has been modified to represent urban areas and has been calibrated for modern flow regimes in the White River watershed. Pre- and post-development VIC simulations are used to assess the impact of Indianapolis area infiltration changes. Finally, VIC model simulations utilizing projected land use change from 2005 through 2040 for the Indianapolis metropolitan area explore the magnitude of future hydrologic change, especially peak flow response

Turkish Prospective Middle School Mathematics Teachers' Beliefs and Perceived Self-Efficacy Beliefs Regarding the Use of Origami in Mathematics Education

Science.gov (United States)

Arslan, Okan; Isiksal-Bostan, Mine

2016-01-01

The purpose of this study was to investigate beliefs and perceived self-efficacy beliefs of Turkish prospective elementary mathematics teachers in using origami in mathematics education. Furthermore, gender differences in their beliefs and perceived self-efficacy beliefs were investigated. Data for the current study was collected via Origami in…

Plan-Belief Revision in Jason

DEFF Research Database (Denmark)

Jensen, Andreas Schmidt; Villadsen, Jørgen

2015-01-01

When information is shared between agents of unknown reliability, it is possible that their belief bases become inconsistent. In such cases, the belief base must be revised to restore consistency, so that the agent is able to reason. In some cases the inconsistent information may be due to use of...... of incorrect plans. We extend work by Alechina et al. to revise belief bases in which plans can be dynamically added and removed. We present an implementation of the algorithm in the AgentSpeak implementation Jason....

Anders Breivik: Extreme Beliefs Mistaken for Psychosis.

Science.gov (United States)

Rahman, Tahir; Resnick, Phillip J; Harry, Bruce

2016-03-01

The case of Anders Breivik, who committed mass murder in Norway in 2011, stirred controversy among forensic mental health experts. His bizarrely composed compendium and references to himself as the "Knights Templar" raised concerns that he had a psychotic mental illness. Beliefs such as Mr. Breivik's that precede odd, unusual, or extremely violent behavior present a unique challenge to the forensic evaluator, who sometimes struggles to understand those beliefs. Psychotic disorder frequently is invoked to characterize odd, unusual, or extreme beliefs, with a classification that has evolved over time. However, the important concept of overvalued idea, largely ignored in American psychiatry, may better characterize these beliefs in some cases. We discuss the definitions of delusion and overvalued ideas in the context of Anders Breivik's rigidly held extreme beliefs. We also review the British definition of overvalued idea and discuss McHugh's construct, to introduce the term "extreme overvalued belief" as an aid in sharpening the forensic evaluator's conceptualization of these and similar beliefs. © 2016 American Academy of Psychiatry and the Law.

Changing Conspiracy Beliefs through Rationality and Ridiculing

OpenAIRE

Orosz, Gábor; Krekó, Péter; Paskuj, Benedek; Tóth-Király, István; Bőthe, Beáta; Roland-Lévy, Christine

2016-01-01

Conspiracy theory (CT) beliefs can be harmful. How is it possible to reduce them effectively? Three reduction strategies were tested in an online experiment using general and well-known CT beliefs on a comprehensive randomly assigned Hungarian sample (N = 813): exposing rational counter CT arguments, ridiculing those who hold CT beliefs, and empathizing with the targets of CT beliefs. Several relevant individual differences were measured. Rational and ridiculing arguments were effective in re...

Politics of climate change belief

Science.gov (United States)

2017-01-01

Donald Trump's actions during the election and his first weeks as US president-elect send a strong message about his belief in climate change, or lack thereof. However, these actions may reflect polarization of climate change beliefs, not climate mitigation behaviour.

A belief-based evolutionarily stable strategy.

Science.gov (United States)

Deng, Xinyang; Wang, Zhen; Liu, Qi; Deng, Yong; Mahadevan, Sankaran

2014-11-21

As an equilibrium refinement of the Nash equilibrium, evolutionarily stable strategy (ESS) is a key concept in evolutionary game theory and has attracted growing interest. An ESS can be either a pure strategy or a mixed strategy. Even though the randomness is allowed in mixed strategy, the selection probability of pure strategy in a mixed strategy may fluctuate due to the impact of many factors. The fluctuation can lead to more uncertainty. In this paper, such uncertainty involved in mixed strategy has been further taken into consideration: a belief strategy is proposed in terms of Dempster-Shafer evidence theory. Furthermore, based on the proposed belief strategy, a belief-based ESS has been developed. The belief strategy and belief-based ESS can reduce to the mixed strategy and mixed ESS, which provide more realistic and powerful tools to describe interactions among agents. Copyright © 2014 Elsevier Ltd. All rights reserved.

Sufism Scholars Network in the Middle East, India, and Indonesia

Directory of Open Access Journals (Sweden)

Dwi Afrianti

2016-03-01

Full Text Available The history of Islam in Indonesia cannot be separated from the affected of local culture, religion, belief earlier, and culture of the spreader of Islam which are also influenced by religion and beliefs held previously, as well as the entry period into certain areas of different life times, willingness to form the teachings of the scholars/king. All of this shows the complexity of the uniqueness of Islam in Indonesian as the majority religion among diverse religions in Indonesia. Sufism are directly involved in the spread of Islam in Indonesia with a unique teaching that facilitate the engaging of non-Muslim communities into Islam, compromise or blends Islam with religious and beliefs practices rather than local beliefs change from an international network to the local level. The terms and the elements of the pre-Islamic culture are used to explain Islam itself. Islamic history of Sundanese, there is a link in teachings of Wihdat al-Wujud of Ibn al-‘Arabi who Sufism Scholar that connected between the international Islamic networks scholars and Sundanese in Indonesia. It is more popular, especially in the congregation of Thariqat Syattariyah originated from India, and it is widespread in Indonesia such as Aceh, Minangkabau and also Pamijahan-Tasikmalaya that brought by Abdul Muhyi since 17th century ago.

Comparative in vitro and in vivo evaluation of two 64Cu-labeled bombesin analogs in a mouse model of human prostate adenocarcinoma

International Nuclear Information System (INIS)

Yang, Y.-S.; Zhang Xianzhong; Xiong Zhengming; Chen Xiaoyuan

2006-01-01

Bombesin (BBN), an analog of human gastrin-releasing peptide (GRP), binds to the GRP receptor (GRPR) with high affinity and specificity. Overexpression of GRPR has been discovered in mostly androgen-independent human prostate tissues and, thus, provides a potential target for prostate cancer diagnosis and therapy. We have previously demonstrated the feasibility of the positron emission tomography (PET) imaging using 64 Cu-1,4,7,10-tetraazadodecane-N,N',N'',N'''-tetraacetic acid (DOTA)-[Lys 3 ]BBN to detect GRPR-positive prostate cancer. In this study, we compared the receptor affinity, metabolic stability, tumor-targeting efficacy, and pharmacokinetics of a truncated BBN analog 64 Cu-DOTA-Aca-BBN(7-14) with 64 Cu-DOTA-[Lys 3 ]BBN. Binding of each DOTA conjugate to GRPR on PC-3 and 22Rv1 prostate cancer cells was evaluated with competitive binding assay using 125 I-[Tyr 4 ]BBN as radioligand. In vivo pharmacokinetics was determined on male nude mice subcutaneously implanted with PC-3 cells. Dynamic microPET imaging was performed to evaluate the systemic distribution of the tracers. Metabolic stability of the tracers in blood, urine, tumor, liver and kidney was studied using high-performance liquid chromatography. The results showed that 125 I-[Tyr 4 ]BBN has a K d of 14.8±0.4 nM against PC-3 cells, and the receptor concentration on PC-3 cell surface is approximately 2.7±0.1x10 6 receptors per cell. The 50% inhibitory concentration value for DOTA-Aca-BBN(7-14) is 18.4±0.2 nM, and that for DOTA-[Lys 3 ]BBN is 2.2±0.5 nM. DOTA-[Lys 3 ]BBN shows a better tumor contrast and absolute tumor activity accumulation compared to DOTA-Aca-BBN(7-14). Studies on metabolic stability for both tracers on organ homogenates showed that 64 Cu-DOTA-[Lys 3 ]BBN is relatively stable. This study demonstrated that both tracers are suitable for targeted PET imaging to detect the expression of GRPR in prostate cancer, while 64 Cu-DOTA-[Lys 3 ]BBN may have a better potential for clinical

Predictors of anonymous cyber aggression: the role of adolescents' beliefs about anonymity, aggression, and the permanency of digital content.

Science.gov (United States)

Wright, Michelle F

2014-07-01

Little attention has been given to whether adolescents' beliefs about anonymity and their normative beliefs about cyber aggression jointly increase their perpetration of cyber aggression. To this end, the present longitudinal study examined the moderating influence of these variables on the relationships among adolescents' attitudes toward the permanency of digital content, confidence with not getting caught, and anonymous cyber aggression (ACA) assessed 1 year later (Time 2). These associations were examined among 274 7th and 8th graders and through five technologies, including social networking sites (SNS), e-mail, instant messenger (IM), mobile phones, and chatrooms. Findings indicated that increases in Time 2 ACA and attitudes toward the permanency of digital content were more strongly related when adolescents reported greater confidence with not getting caught and higher normative beliefs concerning cyber aggression through SNS and mobile phones. In addition, higher levels of attitudes toward the permanency of digital content, confidence with not getting caught, beliefs about anonymity, and normative beliefs regarding cyber aggression were related to greater Time 2 ACA through e-mail, IM, and chatrooms. All findings are discussed in the context of adolescents' positive attitudes toward ACA, and an appeal for additional research is made to understand more about anonymity in cyberspace.

Losing Belief, While Keeping Up the Attitudes

DEFF Research Database (Denmark)

Klausen, Søren Harnow

2013-01-01

While arguing that many cognitive states do indeed have a characteristic phenomenology, I find reasons for exempting beliefs from the program of cognitive phenomenology. Examining the complex relationship between beliefs and various kinds of conscious experience shows that belief is a messy conce...

Equilibria in social belief removal

CSIR Research Space (South Africa)

Booth, R

2008-09-01

Full Text Available In studies of multi-agent interaction, especially in game theory, the notion of equilibrium often plays a prominent role. A typical scenario for the belief merging problem is one in which several agents pool their beliefs together to form a...

Order effects in research on paranormal belief.

Science.gov (United States)

Dudley, R Thomas

2002-04-01

Measures of paranormal belief and emotional intelligence were given a group of 72 college students using Tobacyk's Revised Paranormal Belief Scale and Schutte, Malouff, Hall, Haggerty, Cooper, Golden, and Dornheim's Emotional Intelligence Scale. Order effects indicated that participants who took the Paranormal Belief Scale first had lower emotional intelligence scores than those who took the Emotional Intelligence Scale first. The study demonstrates the importance of taking order effects into account when conducting research on paranormal belief.

The self-attribution bias and paranormal beliefs.

Science.gov (United States)

van Elk, Michiel

2017-03-01

The present study investigated the relation between paranormal beliefs, illusory control and the self-attribution bias, i.e., the motivated tendency to attribute positive outcomes to oneself while negative outcomes are externalized. Visitors of a psychic fair played a card guessing game and indicated their perceived control over randomly selected cards as a function of the congruency and valence of the card. A stronger self-attribution bias was observed for paranormal believers compared to skeptics and this bias was specifically related to traditional religious beliefs and belief in superstition. No relation between paranormal beliefs and illusory control was found. Self-report measures indicated that paranormal beliefs were associated to being raised in a spiritual family and to anomalous experiences during childhood. Thereby this study suggests that paranormal beliefs are related to specific cognitive biases that in turn are shaped by socio-cultural factors. Copyright © 2017 Elsevier Inc. All rights reserved.

Race Research and the Ethics of Belief.

Science.gov (United States)

Anomaly, Jonathan

2017-06-01

On most accounts, beliefs are supposed to fit the world rather than change it. But believing can have social consequences, since the beliefs we form underwrite our actions and impact our character. Because our beliefs affect how we live our lives and how we treat other people, it is surprising how little attention is usually given to the moral status of believing apart from its epistemic justification. In what follows, I develop a version of the harm principle that applies to beliefs as well as actions. In doing so, I challenge the often exaggerated distinction between forming beliefs and acting on them. 1 After developing this view, I consider what it might imply about controversial research the goal of which is to yield true beliefs but the outcome of which might include negative social consequences. In particular, I focus on the implications of research into biological differences between racial groups.

Proposing an Operational Definition of Science Teacher Beliefs

Science.gov (United States)

Hutner, Todd L.; Markman, Arthur B.

2016-01-01

Much research has shown that a science teacher's beliefs are related to their teaching practice. This line of research has often defined "belief" epistemologically. That is, beliefs are often defined relative to other mental constructs, such as knowledge, dispositions, or attitudes. Left unspecified is the role beliefs play in cognition…

Regular Topologies for Gigabit Wide-Area Networks: Congestion Avoidance Testbed Experiments. Volume 3

Science.gov (United States)

Denny, Barbara A.; McKenney, Paul E., Sr.; Lee, Danny

1994-01-01

This document is Volume 3 of the final technical report on the work performed by SRI International (SRI) on SRI Project 8600. The document includes source listings for all software developed by SRI under this effort. Since some of our work involved the use of ST-II and the Sun Microsystems, Inc. (Sun) High-Speed Serial Interface (HSI/S) driver, we have included some of the source developed by LBL and BBN as well. In most cases, our decision to include source developed by other contractors depended on whether it was necessary to modify the original code. If we have modified the software in any way, it is included in this document. In the case of the Traffic Generator (TG), however, we have included all the ST-II software, even though BBN performed the integration, because the ST-II software is part of the standard TG release. It is important to note that all the code developed by other contractors is in the public domain, so that all software developed under this effort can be re-created from the source included here.

The Relative Ineffectiveness of Criminal Network Disruption

Science.gov (United States)

Duijn, Paul A. C.; Kashirin, Victor; Sloot, Peter M. A.

2014-01-01

Researchers, policymakers and law enforcement agencies across the globe struggle to find effective strategies to control criminal networks. The effectiveness of disruption strategies is known to depend on both network topology and network resilience. However, as these criminal networks operate in secrecy, data-driven knowledge concerning the effectiveness of different criminal network disruption strategies is very limited. By combining computational modeling and social network analysis with unique criminal network intelligence data from the Dutch Police, we discovered, in contrast to common belief, that criminal networks might even become ‘stronger’, after targeted attacks. On the other hand increased efficiency within criminal networks decreases its internal security, thus offering opportunities for law enforcement agencies to target these networks more deliberately. Our results emphasize the importance of criminal network interventions at an early stage, before the network gets a chance to (re-)organize to maximum resilience. In the end disruption strategies force criminal networks to become more exposed, which causes successful network disruption to become a long-term effort. PMID:24577374

Application of Bayesian belief net in modelling the origin and effects of terrigenous dissolved organic matter in a boreal aquatic ecosystem

Science.gov (United States)

Rahikainen, Mika; Hoikkala, Laura; Soinne, Helena

2013-04-01

Bayesian belief nets (BBN) are capable of developing holistic understanding of the origin, transportation, and effects of dissolved organic matter (DOM) in ecosystems. The role of riverine DOM, transporting carbon and macronutrients N and P into lakes and coastal areas, has been largely neglected in research about processes influencing aquatic ecosystem functions although dissolved organic matter provides a significant nutrient source for primary producers in aquatic environments. This neglect has also contributed to the environmental policies which are focused in the control of inorganic N and P load. It is of great social and economic interest to gain improved knowledge of whether the currently applied policy instruments act in synchrony in mitigating eutrophication caused by N and P versus DOM load. DOM is a complex mixture of compounds that are poorly characterized. DOM export is strongly regulated by land use (urban, forest, agricultural land, peat land), in addition to soil type and soil organic carbon concentration. Furthermore, the composition of DOM varies according to its origin. The fate and effects of DOM loads in the fresh water and coastal environments depend, for example, on their biodegradability. Degradation kinetics again depends on the interactions between composition of the DOM pool and the receiving environment. Impact studies of dissolved organic matter pose a complicated environmental impact assessment challenge for science. There exists strategic uncertainty in the science about the causal dependencies and about the quality of knowledge related to DOM. There is a clear need for systematization in the approach as uncertainty is typically high about many key processes. A cross-sectorial, integrative analysis will aid in focusing on the most relevant issues. A holistic and unambiguous analysis will provide support for policy-decisions and management by indicating which outcome is more probable than another. The task requires coupling complex

Korean Americans' Beliefs about Colorectal Cancer Screening

Directory of Open Access Journals (Sweden)

Shin-Young Lee, PhD, RN

2013-06-01

Conclusion: Results show the critical need for in-depth understanding of unique health and cultural beliefs about CRC screening in KAs. These beliefs could be useful for future intervention strategies to change health and cultural beliefs in order to increase CRC screening participation in KAs.

False belief understanding in Cantonese-speaking children.

Science.gov (United States)

Tardif, Twila; Wellman, Henry M; Cheung, Kar Man

2004-11-01

The present study investigates the performance of 96 Cantonese-speaking three- to five-year-old preschoolers on three false belief tasks - a deceptive object, a change of location, and an unexpected contents task encompassing a variety of task factors. Most importantly, the research examines the possibility that false belief performance depends on specific linguistic factors such as the type of verb used in the test question--an explicitly false vs. a neutral belief verb. Cantonese was chosen as particularly useful for examining this question because it explicitly codes belief status as either neutral (nam5) or false (ji5wai4), and because it offers additional linguistic and cultural contrasts to research conducted on false belief with children learning English and other Indo-European languages. As expected, a strong age effect was found, as well as a significant advantage for children who received the explicit false belief (ji5wai4) wording and for those who were asked to explain rather than predict the protagonist's actions. Interestingly, there was also a strong task difference with children performing better on the deceptive object task than on the other two false belief tasks. We argue that these results point both to universal trajectories in theory of mind development and to interesting, but localized, effects of language and culture on children's false belief understanding.

SPORT SCIENCE STUDENTS‟ BELIEFS ABOUT LANGUAGE LEARNING

Directory of Open Access Journals (Sweden)

Suvi Akhiriyah

2017-04-01

Full Text Available There are many reasons for students of Sport Science to use English. Yet, knowing the importance of learning English is sometimes not enough to encourage them to learn English well. Based on the experience in teaching them, erroneous belief seems to be held by many of them. It arouses curiosity about the beliefs which might be revealed to help the students to be successful in language learning. By investigating sport science students‘ beliefs about language learning, it is expected that types of the beliefs which they hold can be revealed. Understanding students‘ beliefs about language learning is essential because these beliefs can have possible consequences for second language learning and instruction. This study is expected to provide empirical evidence. The subjects of this study were 1st semester students majoring in Sport Science of Sport Science Faculty. There were 4 classes with 38 students in each class. There were approximately 152 students as the population of the study. The sample was taken by using random sampling. All members of the population received the questionnaire. The questionnaire which was later handed back to the researcher is considered as the sample. The instrument in this study is the newest version of Beliefs About Language Learning Inventory (BALLI, version 2.0, developed by Horwitz to asses the beliefs about learning a foreign language.

Developing resident learning profiles: Do scientific evidence epistemology beliefs, EBM self-efficacy beliefs and EBM skills matter?

Science.gov (United States)

Robert, Nancy J.

This study investigated resident scientific evidence epistemology beliefs, evidence based medicine (EBM) self-efficacy beliefs, and EBM skills. A convenience sample of fifty-one residents located in six U.S. based residency programs completed an online instrument. Hofer's epistemology survey questionnaire was modified to test responses based on four types of scientific evidence encountered in medical practice (Clinical Trial Phase 1, Clinical Trial Phase 3, Meta-analysis and Qualitative). It was hypothesized that epistemology beliefs would differ based on the type of scientific evidence considered. A principal components analysis produced a two factor solution that was significant across type of scientific evidence suggesting that when evaluating epistemology beliefs context does matter. Factor 1 is related to the certainty of research methods and the certainty of medical conclusions and factor 2 denotes medical justification. For each type of scientific evidence, both factors differed on questions comprising the factor structure with significant differences found for the factor 1 and 2 questions. A justification belief case problem using checklist format was triangulated with the survey results, and as predicted the survey and checklist justification z scores indicated no significant differences, and two new justification themes emerged. Modified versions of Finney and Schraw's statistical self-efficacy and skill instruments produced expected significant EBM score correlations with unexpected results indicating that the number of EBM and statistics courses are not significant for EBM self-efficacy and skill scores. The study results were applied to the construction of a learning profile that provided residents belief and skill feedback specific to individual learning needs. The learning profile design incorporated core values related to 'Believer' populations that focus on art, harmony, tact and diplomacy. Future research recommendations include testing context

False belief reasoning in the brain: An ERP study

Institute of Scientific and Technical Information of China (English)

2008-01-01

Understanding others mind and interpersonal interaction are the cognitive basis of successful social interactions. People’s mental states and behaviors rely on their holding beliefs for self and others. To investigate the neural substrates of false belief reasoning, the 32 channels event-related potentials (ERP) of 14 normal adults were measured while they understood false-belief and true belief used de-ceptive appearance task. After onset of the false-belief or true-belief questions, N100, P200 and late negative component (LNC) were elicited at centro-frontal sites. Compared with true belief, false belief reasoning elicited significant declined LNC in the time window from 400 to 800 ms. The source analysis of difference wave (False minus True) showed a dipole located in the middle cingulated cortex. These findings show that false belief reasoning probably included inhibitive process.

False belief reasoning in the brain: An ERP study

Institute of Scientific and Technical Information of China (English)

无

2008-01-01

Understanding others mind and interpersonal interaction are the cognitive basis of successful social interactions. People's mental states and behaviors rely on their holding beliefs for self and others. To investigate the neural substrates of false belief reasoning, the 32 channels event-related potentials (ERP) of 14 normal adults were measured while they understood false-belief and true belief used deceptive appearance task. After onset of the false-belief or true-belief questions, N100, P200 and late negative component (LNC) were elicited at centro-frontal sites. Compared with true belief, false belief reasoning elicited significant declined LNC in the time window from 400 to 800 ms. The source analysis of difference wave (False minus True) showed a dipole located in the middle cingulated cortex. These findings show that false belief reasoning probably included inhibitive process.

Folk beliefs of cultural changes in China

OpenAIRE

Xu, Yi; Hamamura, Takeshi

2014-01-01

For the last several decades, Chinese society has experienced transformative changes. How are these changes understood among Chinese people? To examine this question, Part 1 in this research solicited folk beliefs of cultural change from a group of Chinese participants in an open-ended format, and the generated folk beliefs were rated by another group of participants in Part 2 to gage each belief's level of agreement. Part 3 plotted the folk beliefs retained in Part 2 using the Google Ngram V...

Analytic cognitive style predicts religious and paranormal belief.

Science.gov (United States)

Pennycook, Gordon; Cheyne, James Allan; Seli, Paul; Koehler, Derek J; Fugelsang, Jonathan A

2012-06-01

An analytic cognitive style denotes a propensity to set aside highly salient intuitions when engaging in problem solving. We assess the hypothesis that an analytic cognitive style is associated with a history of questioning, altering, and rejecting (i.e., unbelieving) supernatural claims, both religious and paranormal. In two studies, we examined associations of God beliefs, religious engagement (attendance at religious services, praying, etc.), conventional religious beliefs (heaven, miracles, etc.) and paranormal beliefs (extrasensory perception, levitation, etc.) with performance measures of cognitive ability and analytic cognitive style. An analytic cognitive style negatively predicted both religious and paranormal beliefs when controlling for cognitive ability as well as religious engagement, sex, age, political ideology, and education. Participants more willing to engage in analytic reasoning were less likely to endorse supernatural beliefs. Further, an association between analytic cognitive style and religious engagement was mediated by religious beliefs, suggesting that an analytic cognitive style negatively affects religious engagement via lower acceptance of conventional religious beliefs. Results for types of God belief indicate that the association between an analytic cognitive style and God beliefs is more nuanced than mere acceptance and rejection, but also includes adopting less conventional God beliefs, such as Pantheism or Deism. Our data are consistent with the idea that two people who share the same cognitive ability, education, political ideology, sex, age and level of religious engagement can acquire very different sets of beliefs about the world if they differ in their propensity to think analytically. Copyright © 2012 Elsevier B.V. All rights reserved.

Zero-Sum Matrix Game with Payoffs of Dempster-Shafer Belief Structures and Its Applications on Sensors

Science.gov (United States)

Deng, Xinyang; Jiang, Wen; Zhang, Jiandong

2017-01-01

The zero-sum matrix game is one of the most classic game models, and it is widely used in many scientific and engineering fields. In the real world, due to the complexity of the decision-making environment, sometimes the payoffs received by players may be inexact or uncertain, which requires that the model of matrix games has the ability to represent and deal with imprecise payoffs. To meet such a requirement, this paper develops a zero-sum matrix game model with Dempster–Shafer belief structure payoffs, which effectively represents the ambiguity involved in payoffs of a game. Then, a decomposition method is proposed to calculate the value of such a game, which is also expressed with belief structures. Moreover, for the possible computation-intensive issue in the proposed decomposition method, as an alternative solution, a Monte Carlo simulation approach is presented, as well. Finally, the proposed zero-sum matrix games with payoffs of Dempster–Shafer belief structures is illustratively applied to the sensor selection and intrusion detection of sensor networks, which shows its effectiveness and application process. PMID:28430156

Self-deception as pseudo-rational regulation of belief.

Science.gov (United States)

Michel, Christoph; Newen, Albert

2010-09-01

Self-deception is a special kind of motivational dominance in belief-formation. We develop criteria which set paradigmatic self-deception apart from related phenomena of auto-manipulation such as pretense and motivational bias. In self-deception rational subjects defend or develop beliefs of high subjective importance in response to strong counter-evidence. Self-deceivers make or keep these beliefs tenable by putting prima-facie rational defense-strategies to work against their established standards of rational evaluation. In paradigmatic self-deception, target-beliefs are made tenable via reorganizations of those belief-sets that relate relevant data to target-beliefs. This manipulation of the evidential value of relevant data goes beyond phenomena of motivated perception of data. In self-deception belief-defense is pseudo-rational. Self-deceivers will typically apply a dual standard of evaluation that remains intransparent to the subject. The developed model of self-deception as pseudo-rational belief-defense is empirically anchored. So, we hope to put forward a promising candidate. Copyright © 2010 Elsevier Inc. All rights reserved.

Beliefs and brownies: in search for a new identity for 'belief' research

DEFF Research Database (Denmark)

Skott, Jeppe

2014-01-01

Belief research (BR) has contributed with better understandings of teachers’ acts and meaning making, but is fraught with conceptual and methodological problems. Also, the premise that teachers’ beliefs impact practice is often not confirmed. I compare BR with a conceptual framework, Patterns...... of the rationale of BR, but involves a fundamental shift of identity for research on affect, which alleviates some of the problems of BR and is useful for understanding the dynamics of teachers’ contribution to classroom practice....

Belief update as social choice

NARCIS (Netherlands)

van Benthem, J.; Girard, P.; Roy, O.; Marion, M.

2011-01-01

Dynamic epistemic-doxastic logics describe the new knowledge or new beliefs indexBelief of agents after some informational event has happened. Technically, this requires an update rule that turns a doxastic-epistemic modelM(recording the current information state of the agents) and a dynamic ‘event

Are Teacher Beliefs Gender-Related?

NARCIS (Netherlands)

Kraker - de Pauw, Emmy; van Wesel, F.; Verwijmeren, Thijs; Denessen, Eddie; Krabbendam, Lydia

2016-01-01

Teacher beliefs influence student behaviour and learning outcomes. Little is known about the role of specific teacher characteristics (e.g., gender and teaching domain) in the formation of these beliefs. In the current study, three versions of the Implicit Association Test (IAT) were used to assess

Are teacher beliefs gender-related?

NARCIS (Netherlands)

Kraker-Pauw, E. de; Wesel, F. van; Verwijmeren, T.; Denessen, E.J.P.G.; Krabbendam, L.

2016-01-01

Teacher beliefs influence student behaviour and learning outcomes. Little is known about the role of specific teacher characteristics (e.g., gender and teaching domain) in the formation of these beliefs. In the current study, three versions of the Implicit Association Test (IAT) were used to assess

Changing Preservice Teachers' Beliefs about Motivating Students

Science.gov (United States)

Peterson, Sarah; Schreiber, Jim; Moss, Connie

2011-01-01

We examined the effects of an educational psychology course on students' beliefs about motivating students. After providing opportunities to engage in systematic intentional inquiry of their beliefs about teaching and learning, we expected that students' beliefs would become more soundly based in theory and research. Following several classes on…

Confirming the structure of negative beliefs about psychosis and bipolar disorder: A confirmatory factor analysis study of the Personal Beliefs about Experience Questionnaire and Personal Beliefs about Illness Questionnaire.

Science.gov (United States)

Taylor, Peter J; Pyle, Melissa; Schwannauer, Matthias; Hutton, Paul; Morrison, Anthony

2015-11-01

Negative beliefs about psychosis and other mental health difficulties may contribute to depression and distress in individuals with these experiences. The Personal Beliefs about Experience Questionnaire (PBEQ) and Personal Beliefs about Illness Questionnaire (PBIllQ) are two widely used measures of these beliefs. It is currently uncertain how the items on these measures map onto different underlying factors. This study therefore aimed to test the factor structure of these two measures. Confirmatory factor analysis (CFA) was used to test three alternative, pre-specified, factor structures for the PBIllQ and PBEQ in a sample of individuals diagnosed with bipolar disorder (n = 202) and a sample of individuals with experien-ces of psychosis (n = 362). Associations with depressive symptoms were also examined. A three-factor structure was supported for both measures, which included Negative Expectations/Appraisals (NEA), Internal Shame/Defectiveness (ISD) and External Shame (ES) factors. The NEA and ISD subscales also had consistent independent associations with depressive symptoms. The results suggest that the PBIllQ and PBEQ may capture three distinct sets of negative beliefs in individuals with psychosis or bipolar disorder and that these beliefs may have important consequences for subsequent difficulties in these populations such as depression. Both measures may be helpful in supporting assessment and formulation in clinical practice and in evaluating belief change in intervention trials. However, when used in these settings, the three subscales identified in this study may be the most valid way of calculating scores on these measures. Negative personal beliefs about the causes, meaning and consequences of psychosis and bipolar disorder are associated with greater distress and depression. Two related measures, the PBIllQ and PBEQ, have been developed to assess these beliefs. Our analyses suggest that scores on these questionnaires are best broken down into three

Normative beliefs and sexual risk in China.

Science.gov (United States)

Li, Li; Ding, Ying Ying; Wu, Zunyou; Rotheram-Borus, Mary Jane; Guo, Sam

2011-08-01

We examined normative beliefs about multiple sexual partners and social status in China and their association with risky sexual behaviors and sexually transmitted infections (STIs). Self-reported and biological markers of sexual risk were examined among 3,716 market vendors from a city in eastern China. Men who were older or with less education believed having multiple sexual partners was linked to higher social status. Adjusting for demographic characteristics, normative beliefs were significantly associated with having multiple sexual partners, while having multiple sexual partners was significantly associated with STIs. Normative beliefs regarding sexual behaviors may play an important role in individual risk behaviors. Future HIV/STI interventions must address community beliefs about the positive meaning of sexual risks, particularly among men with traditional beliefs about gender roles.

The relationship between clients' depression etiological beliefs and psychotherapy orientation preferences, expectations, and credibility beliefs.

Science.gov (United States)

Tompkins, Kelley A; Swift, Joshua K; Rousmaniere, Tony G; Whipple, Jason L

2017-06-01

The purpose of this study was to examine the relationship between clients' etiological beliefs for depression and treatment preferences, credibility beliefs, and outcome expectations for five different depression treatments-behavioral activation, cognitive therapy, interpersonal psychotherapy, pharmacotherapy, and psychodynamic psychotherapy. Adult psychotherapy clients (N = 98) were asked to complete an online survey that included the Reasons for Depression Questionnaire, a brief description of each of the five treatment options, and credibility, expectancy, and preference questions for each option. On average, the participating clients rated pharmacotherapy as significantly less credible, having a lower likelihood of success, and being less preferred than the four types of psychotherapy. In general, interpersonal psychotherapy was also rated more negatively than the other types of psychotherapy. However, these findings depended somewhat on whether the participating client was personally experiencing depression. Credibility beliefs, outcome expectations, and preferences for pharmacotherapy were positively associated with biological beliefs for depression; however, the other hypothesized relationships between etiological beliefs and treatment attitudes were not supported. Although the study is limited based on the specific sample and treatment descriptions that were used, the results may still have implications for psychotherapy research, training, and practice. (PsycINFO Database Record (c) 2017 APA, all rights reserved).

Executive functions in morality, religion, and paranormal beliefs.

Science.gov (United States)

Wain, Omar; Spinella, Marcello

2007-01-01

Moral, religious, and paranormal beliefs share some degree of overlap and play important roles in guiding peoples' behavior. Although partly cultural phenomena, they also have neurobiological components based on functional neuroimaging studies and research in clinical populations. Because all three show relationships to prefrontal system functioning, the current study examined whether they related to executive functions as measured by the Executive Function Inventory in a community sample. As in previous research, religious beliefs related positively to both moral attitudes and paranormal beliefs. Moral attitudes, however, did not relate to paranormal beliefs. Paranormal beliefs related inversely to impulse control and organization, whereas small positive correlations occurred between traditional religious beliefs, impulse control, and empathy. Moral attitudes, on the other hand, showed consistent positive correlations with all executive functions measured, independent of demographic influences. These findings concordantly support that prefrontal systems play a role in morality, religion, and paranormal beliefs.

Preventive but Not Curative Efficacy of Celecoxib on Bladder Carcinogenesis in a Rat Model

Directory of Open Access Journals (Sweden)

José Sereno

2010-01-01

Full Text Available To evaluate the effect of a cyclooxygenase 2 inhibitor, celecoxib (CEL, on bladder cancer inhibition in a rat model, when used as preventive versus as curative treatment. The study comprised 52 male Wistar rats, divided in 5 groups, during a 20-week protocol: control: vehicle, carcinogen: 0.05% of N-butyl-N-(4-hydroxybutyl nitrosamine (BBN, CEL: 10 mg/kg/day of the selective COX-2 inhibitor Celebrex, preventive CEL (CEL+BBN-P, and curative CEL (BBN+CEL-C groups. Although tumor growth was markedly inhibited by the preventive application of CEL, it was even aggravated by the curative treatment. The incidence of gross bladder carcinoma was: control 0/8(0%, BBN 13/20(65%, CEL 0/8(0%, CEL+BBN-P 1/8(12.5%, and BBN+CEL-C 6/8(75%. The number and volume of carcinomas were significantly lower in the CEL+BBN-P versus BBN, accompanied by an ample reduction in hyperplasia, dysplasia, and papillary tumors as well as COX-2 immunostaining. In spite of the reduction of tumor volumes in the curative BBN+CEL-C group, tumor malignancy was augmented. An anti-inflammatory and antioxidant profile was encountered only in the group under preventive treatment. In conclusion, preventive, but not curative, celecoxib treatment promoted a striking inhibitory effect on bladder cancer development, reinforcing the potential role of chemopreventive strategies based on cyclooxygenase 2 inhibition.

Apocalypse soon? Dire messages reduce belief in global warming by contradicting just-world beliefs.

Science.gov (United States)

Feinberg, Matthew; Willer, Robb

2011-01-01

Though scientific evidence for the existence of global warming continues to mount, in the United States and other countries belief in global warming has stagnated or even decreased in recent years. One possible explanation for this pattern is that information about the potentially dire consequences of global warming threatens deeply held beliefs that the world is just, orderly, and stable. Individuals overcome this threat by denying or discounting the existence of global warming, and this process ultimately results in decreased willingness to counteract climate change. Two experiments provide support for this explanation of the dynamics of belief in global warming, suggesting that less dire messaging could be more effective for promoting public understanding of climate-change research.

Beliefs About Child TV Viewing in Low-Income Mexican American Parents of Preschoolers: Development of the Beliefs About Child TV Viewing Scale (B-TV).

Science.gov (United States)

Thompson, Darcy A; Johnson, Susan L; Schmiege, Sarah J; Vandewater, Elizabeth A; Boles, Richard E; Lev, Jerusha; Tschann, Jeanne M

2018-06-01

Objectives Parental beliefs about child television viewing may affect the way parents regulate child television viewing. Despite this, little research has focused on the development of measures of parental beliefs about child television viewing, particularly among ethnic minority parents and parents of young children. This study's objective was to develop and test a culturally-based measure of parental beliefs about television viewing in low-income Mexican American mothers of preschoolers. Methods Using a cross-sectional study design, 22 items reflecting parental beliefs about influences of TV on children were developed and assessed for psychometric properties in a sample of 312 low-income Mexican American mothers of preschoolers. Results Using exploratory factor analysis, we identified four factors reflecting four domains of parental beliefs: positive general beliefs, positive sleep-related beliefs, positive functional beliefs, and negative general beliefs. Internal reliabilities were acceptable (Cronbach's alpha = 0.70-0.89) for all factors except negative general beliefs (Cronbach's alpha = 0.61). Positive sleep-related beliefs and Positive Functional Beliefs were correlated with children's average daily hours of TV (r = 0.16, p parental beliefs regarding child TV viewing, and has good initial reliability and validity for three factors. Future use will allow investigators to conduct more in-depth evaluations on the influence of parental beliefs on the way parents shape their child's use of the TV.

Playing with knowledge and belief

NARCIS (Netherlands)

Fiutek, V.

2013-01-01

This thesis contributes to the development of Soft Dynamic Epistemic Logic (Soft DEL). Soft DEL has been introduced to deal with a number of informational phenomena, including belief revision. The work in this thesis extends the scope of Soft DEL to belief contraction, providing as such a framework

Using Bayesian Belief Networks To Assess Volcano State from Multiple Monitoring Timeseries And Other Evidence

Science.gov (United States)

Odbert, Henry; Aspinall, Willy

2013-04-01

When volcanoes exhibit unrest or become eruptively active, science-based decision support invariably is sought by civil authorities. Evidence available to scientists about a volcano's internal state is usually indirect, secondary or very nebulous.Advancement of volcano monitoring technology in recent decades has increased the variety and resolution of multi-parameter timeseries data recorded at volcanoes. Monitoring timeseries may be interpreted in real time by observatory staff and are often later subjected to further analytic scrutiny by the research community at large. With increasing variety and resolution of data, interpreting these multiple strands of parallel, partial evidence has become increasingly complex. In practice, interpretation of many timeseries involves familiarity with the idiosyncracies of the volcano, the monitoring techniques, the configuration of the recording instrumentation, observations from other datasets, and so on. Assimilation of this knowledge is necessary in order to select and apply the appropriate statistical techniques required to extract the required information. Bayesian Belief Networks (BBNs) use probability theory to treat and evaluate uncertainties in a rational and auditable scientific manner, but only to the extent warranted by the strength of the available evidence. The concept is a suitable framework for marshalling multiple observations, model results and interpretations - and associated uncertainties - in a methodical manner. The formulation is usually implemented in graphical form and could be developed as a tool for near real-time, ongoing use in a volcano observatory, for example. We explore the application of BBNs in analysing volcanic timeseries, the certainty with which inferences may be drawn, and how they can be updated dynamically. Such approaches provide a route to developing analytical interface(s) between volcano monitoring analyses and probabilistic hazard analysis. We discuss the use of BBNs in hazard

Islamic Cultures: Health Care Beliefs and Practices.

Science.gov (United States)

Kemp, Charles

1996-01-01

Presents an overview of Islamic health care beliefs and practices, noting health-related social and spiritual issues, fundamental beliefs and themes in Islam, health care beliefs and practices common among Muslims, and health-affecting social roles among Muslims. Cultural, religious, and social barriers to health care and ways to reduce them are…

Mentalizing Deficits Constrain Belief in a Personal God

Science.gov (United States)

Norenzayan, Ara; Gervais, Will M.; Trzesniewski, Kali H.

2012-01-01

Religious believers intuitively conceptualize deities as intentional agents with mental states who anticipate and respond to human beliefs, desires and concerns. It follows that mentalizing deficits, associated with the autistic spectrum and also commonly found in men more than in women, may undermine this intuitive support and reduce belief in a personal God. Autistic adolescents expressed less belief in God than did matched neuro-typical controls (Study 1). In a Canadian student sample (Study 2), and two American national samples that controlled for demographic characteristics and other correlates of autism and religiosity (Study 3 and 4), the autism spectrum predicted reduced belief in God, and mentalizing mediated this relationship. Systemizing (Studies 2 and 3) and two personality dimensions related to religious belief, Conscientiousness and Agreeableness (Study 3), failed as mediators. Mentalizing also explained the robust and well-known, but theoretically debated, gender gap in religious belief wherein men show reduced religious belief (Studies 2–4). PMID:22666332

Assessment of dysfunctional beliefs in borderline personality disorder.

Science.gov (United States)

Butler, Andrew C; Brown, Gregory K; Beck, Aaron T; Grisham, Jessica R

2002-10-01

This study had two aims: to test the hypothesis that borderline personality disorder (BPD) patients hold numerous dysfunctional beliefs associated with a variety of Axis II disorders, and to construct a BPD belief scale which captures these beliefs. Beliefs were measured using the Personality Belief Questionnaire (PBQ) which is designed to assess beliefs associated with various personality disorders, although not specifically BPD. Eighty-four BPD patients and 204 patients with other personality disorders (OPD) were randomly split into two study samples. Fourteen PBQ items were found to discriminate BPD from OPD patients in both samples. These items came from the PBQ Dependent, Paranoid, Avoidant, and Histrionic scales and reflect themes of dependency, helplessness, distrust, fears of rejection/abandonment/losing emotional control, and extreme attention-seeking behavior. A BPD beliefs scale constructed from these items showed good internal consistency and diagnostic validity among the 288 study patients. The scale may be used to assist in diagnosis and cognitive therapy of BPD.

Addressing Value and Belief Systems on Climate Literacy in the Southeastern United States

Science.gov (United States)

McNeal, K. S.

2012-12-01

The southeast (SEUS; AL, AR, GA, FL, KY, LA, NC, SC, TN, E. TX) faces the greatest impacts as a result of climate change of any region in the U.S. which presents considerable and costly adaptation challenges. Paradoxically, people in the SEUS hold attitudes and perceptions that are more dismissive of climate change than those of any other region. An additional mismatch exists between the manner in which climate science is generally communicated and the underlying core values and beliefs held by a large segment of people in the SEUS. As a result, people frequently misinterpret and/or distrust information sources, inhibiting efforts to productively discuss and consider climate change and related impacts on human and environmental systems, and possible solutions and outcomes. The Climate Literacy Partnership in the Southeast (CLiPSE) project includes an extensive network of partners throughout the SEUS from faith, agriculture, culturally diverse, leisure, and K-20 educator communities that aim to address this educational need through a shared vision. CLiPSE has conducted a Climate Stewardship Survey (CSS) to determine the knowledge and perceptions of individuals in and beyond the CLiPSE network. The descriptive results of the CSS indicate that religion, predominantly Protestantism, plays a minor role in climate knowledge and perceptions. Likewise, political affiliation plays a minimal role in climate knowledge and perceptions between religions. However, when Protestants were broken out by political affiliation, statistically significant differences (t(30)=2.44, p=0.02) in knowledge related to the causes of climate change exist. Those Protestants affiliated with the Democratic Party (n=206) tended to maintain a statistically significant stronger knowledge of the causes of global climate change than their Republican counterparts. When SEUS educator (n=277) group was only considered, similar trends were evidenced, indicating that strongly held beliefs potentially

Paranormal belief, schizotypy, and Body Mass Index.

Science.gov (United States)

Hergovich, Andreas; Willinger, Ulrike; Arendasy, Martin

2005-06-01

There are indications that subjects with schizotypal personality have a lower Body Mass Index. Also schizotypal personality is linked to a higher incidence of paranormal belief. In this study we examined whether low Body Mass Index is also linked to paranormal belief. In a pilot study 48 students of psychology (85.4% women) between the ages of 20 and 27 years were administered a questionnaire assessing weight, height, and paranormal belief. Analysis suggested an association between belief in paranormal phenomena and low Body Mass Index. In a follow-up study with 300 subjects and equal sex distribution, the relationship was examined under control of schizotypy. The results for Body Mass Index could not be confirmed; however, paranormal belief was heavily associated with the cognitive-perceptual component of schizotypy.

Indonesian teachers' epistemological beliefs and inclusive education.

Science.gov (United States)

Sheehy, Kieron; Budiyanto; Kaye, Helen; Rofiah, Khofidotur

2017-01-01

A growing number of children with intellectual disabilities attend inclusive schools in Indonesia. Previous research has suggested that teachers' type of school and experience influences their beliefs about inclusive education. This research collected questionnaire data from 267 Indonesian teachers and compared the responses from those working in inclusive, special and regular schools regarding their epistemological and pedagogical beliefs. The results showed that teachers in inclusive schools expressed stronger social constructivist beliefs than those in other schools. However, it was teachers' epistemological beliefs, rather than their type of school or experience, which were the significant predictor of their beliefs about inclusive education. The findings suggest that international epistemological research needs to have a more nuanced view of constructivist models of learning to better understand and inform how inclusive pedagogy is being enacted in different contexts.

Beliefs about God and mental health among American adults.

Science.gov (United States)

Silton, Nava R; Flannelly, Kevin J; Galek, Kathleen; Ellison, Christopher G

2014-10-01

This study examines the association between beliefs about God and psychiatric symptoms in the context of Evolutionary Threat Assessment System Theory, using data from the 2010 Baylor Religion Survey of US Adults (N = 1,426). Three beliefs about God were tested separately in ordinary least squares regression models to predict five classes of psychiatric symptoms: general anxiety, social anxiety, paranoia, obsession, and compulsion. Belief in a punitive God was positively associated with four psychiatric symptoms, while belief in a benevolent God was negatively associated with four psychiatric symptoms, controlling for demographic characteristics, religiousness, and strength of belief in God. Belief in a deistic God and one's overall belief in God were not significantly related to any psychiatric symptoms.

Cultural expressions of social class and their implications for group-related beliefs and behaviors

OpenAIRE

Rheinschmidt-Same, Michelle; Becker, Julia; Kraus, Michael

2017-01-01

In the wake of the Great Recession, rising inequality has increased social class disparities between people in society. In this research, we examine how differences in social class shape unique patterns of cultural expression, and how these cultural expressions affirm ingroup beliefs. In Study 1 (N=113), we provide evidence that cultural expressions of social class on an online social network can signal the social class of targets: by simply viewing the cultural practices of individuals captu...

Assessment of Religious Beliefs Form.

Science.gov (United States)

Faiver, Christopher M.; O'Brien, Eugene M.

1993-01-01

Notes that religion may be source of spiritual strength or source of conflict and guilt. Outlines importance of assessing religious beliefs of clients for treatment purposes and provides format for counselor to use. Says that, because counselors may be unaware of clients' individual perspectives, it is important to evaluate client's belief system…

The association between reality-based beliefs and indirectly experienced traumatization.

Science.gov (United States)

Shiri, Shimon; Wexler, Isaiah D; Schwartz, Isabella; Kadari, Michal; Kreitler, Shulamith

2010-12-01

The purpose of the study was to examine the association between belief types and the magnitude of indirect traumatization. Specific types of beliefs were defined in terms of the cognitive orientation theory, which is a cognitive-motivational approach to the understanding, predicting, and changing of behaviors. Belief types that were analyzed included beliefs about self, general beliefs, beliefs about norms, and goal beliefs as they relate to personal growth. Study participants included 38 rescuers (body handlers), 37 nurses, and 31 rehabilitation workers who treated injured civilians that had been exposed to politically motivated violence. The Cognitive Orientation for Posttraumatic Growth Scale was used to assess beliefs about personal growth. The Revised Posttraumatic Stress Disorder Inventory was administered to evaluate indirect traumatization. The results indicate that three of the four belief types related to personal growth were associated with the level of indirect traumatization. Optimistic and positive beliefs about self and general beliefs were associated with a lower level of indirect traumatization symptomatology, suggesting that these types of beliefs may counteract indirect traumatization. On the other hand, stronger goal beliefs were associated with greater indirect traumatization. The negative association between positive goal beliefs and indirect trauma may be related to the gap the individual perceives between the hoped-for ideals and the trauma-stricken reality. These results indicate the importance of cognitive beliefs and their possible role in determining the response to indirect traumatization.

Hierarchies of belief and interim rationalizability

Directory of Open Access Journals (Sweden)

Jeffrey C. Ely

2006-03-01

Full Text Available In games with incomplete information, conventional hierarchies of belief are incomplete as descriptions of the players' information for the purposes of determining a player's behavior. We show by example that this is true for a variety of solution concepts. We then investigate what is essential about a player's information to identify behavior. We specialize to two player games and the solution concept of interim rationalizability. We construct the universal type space for rationalizability and characterize the types in terms of their beliefs. Infinite hierarchies of beliefs over conditional beliefs, which we call Delta-hierarchies, are what turn out to matter. We show that any two types in any two type spaces have the same rationalizable sets in all games if and only if they have the same Delta-hierarchies.

Comparing strengths of beliefs explicitly

NARCIS (Netherlands)

Ghosh, S.; de Jongh, D.

2013-01-01

Inspired by a similar use in provability logic, formulas p > B q and p ≥ B q are introduced in the existing logical framework for discussing beliefs to express that the strength of belief in p is greater than (or equal to) that in q. Besides its usefulness in studying the properties of the concept

Testing a biopsychosocial model of the basic birth beliefs.

Science.gov (United States)

Preis, Heidi; Chen, Rony; Eisner, Michal; Pardo, Joseph; Peled, Yoav; Wiznitzer, Arnon; Benyamini, Yael

2018-03-01

Women perceive what birth is even before they are pregnant for the first time. Part of this conceptualization is the basic belief about birth as a medical and natural process. These two separate beliefs are pivotal in the decision-making process about labor and birth. Adapting Engel's biopsychosocial framework, we explored the importance of a wide range of factors which may contribute to these beliefs among first-time mothers. This observational study included 413 primiparae ≥24 weeks' gestation, recruited in medical centers and in natural birth communities in Israel. The women completed a questionnaire which included the Birth Beliefs Scale and a variety of biopsychosocial characteristics such as obstetric history, birth environment, optimism, health-related anxiety, and maternal expectations. Psychological dispositions were more related to the birth beliefs than the social or biomedical factors. Sociodemographic characteristics and birth environment were only marginally related to the birth beliefs. The basic belief that birth is a natural process was positively related to optimism and to conceiving spontaneously. Beliefs that birth is a medical process were related to pessimism, health-related anxiety, and to expectations that an infant's behavior reflects mothering. Expectations about motherhood as being naturally fulfilling were positively related to both beliefs. Psychological factors seem to be most influential in the conceptualization of the beliefs. It is important to recognize how women interpret the messages they receive about birth which, together with their obstetric experience, shape their beliefs. Future studies are recommended to understand the evolution of these beliefs, especially within diverse cultures. © 2017 Wiley Periodicals, Inc.

Modeling of Communication in a Computational Situation Assessment Model

International Nuclear Information System (INIS)

Lee, Hyun Chul; Seong, Poong Hyun

2009-01-01

Operators in nuclear power plants have to acquire information from human system interfaces (HSIs) and the environment in order to create, update, and confirm their understanding of a plant state, or situation awareness, because failures of situation assessment may result in wrong decisions for process control and finally errors of commission in nuclear power plants. Quantitative or prescriptive models to predict operator's situation assessment in a situation, the results of situation assessment, provide many benefits such as HSI design solutions, human performance data, and human reliability. Unfortunately, a few computational situation assessment models for NPP operators have been proposed and those insufficiently embed human cognitive characteristics. Thus we proposed a new computational situation assessment model of nuclear power plant operators. The proposed model incorporating significant cognitive factors uses a Bayesian belief network (BBN) as model architecture. It is believed that communication between nuclear power plant operators affects operators' situation assessment and its result, situation awareness. We tried to verify that the proposed model represent the effects of communication on situation assessment. As the result, the proposed model succeeded in representing the operators' behavior and this paper shows the details

Incorporating organizational factors into Probabilistic Risk Assessment (PRA) of complex socio-technical systems: A hybrid technique formalization

International Nuclear Information System (INIS)

Mohaghegh, Zahra; Kazemi, Reza; Mosleh, Ali

2009-01-01

This paper is a result of a research with the primary purpose of extending Probabilistic Risk Assessment (PRA) modeling frameworks to include the effects of organizational factors as the deeper, more fundamental causes of accidents and incidents. There have been significant improvements in the sophistication of quantitative methods of safety and risk assessment, but the progress on techniques most suitable for organizational safety risk frameworks has been limited. The focus of this paper is on the choice of 'representational schemes' and 'techniques.' A methodology for selecting appropriate candidate techniques and their integration in the form of a 'hybrid' approach is proposed. Then an example is given through an integration of System Dynamics (SD), Bayesian Belief Network (BBN), Event Sequence Diagram (ESD), and Fault Tree (FT) in order to demonstrate the feasibility and value of hybrid techniques. The proposed hybrid approach integrates deterministic and probabilistic modeling perspectives, and provides a flexible risk management tool for complex socio-technical systems. An application of the hybrid technique is provided in the aviation safety domain, focusing on airline maintenance systems. The example demonstrates how the hybrid method can be used to analyze the dynamic effects of organizational factors on system risk

Skepticism: Genuine unbelief or implicit beliefs in the supernatural?

Science.gov (United States)

Lindeman, Marjaana; Svedholm-Häkkinen, Annika M; Riekki, Tapani

2016-05-01

We examined whether skeptics hold implicit supernatural beliefs or implicit cognitive underpinnings of the beliefs. In study 1 (N=57), participants read a biological or a religious story about death. The story content had no effect on skeptics' (or believers') afterlife beliefs. Study 2 examined the relationships between religious and non-religious paranormal beliefs and implicit views about whether supernatural and religious phenomena are imaginary or real (n1=33, n2=31). The less supernatural beliefs were endorsed the easier it was to connect "supernatural" with "imaginary". Study 3 (N=63) investigated whether participants' supernatural beliefs and ontological confusions differ between speeded and non-speeded response conditions. Only non-analytical skeptics' ontological confusions increased in speeded conditions. The results indicate that skeptics overall do not hold implicit supernatural beliefs, but that non-analytically thinking skeptics may, under supporting conditions, be prone to biases that predispose to supernatural beliefs. Copyright © 2016 Elsevier Inc. All rights reserved.

Doctors' stress responses and poor communication performance in simulated bad-news consultations.

Science.gov (United States)

Brown, Rhonda; Dunn, Stewart; Byrnes, Karen; Morris, Richard; Heinrich, Paul; Shaw, Joanne

2009-11-01

No studies have previously evaluated factors associated with high stress levels and poor communication performance in breaking bad news (BBN) consultations. This study determined factors that were most strongly related to doctors' stress responses and poor communication performance during a simulated BBN task. In 2007, the authors recruited 24 doctors comprising 12 novices (i.e., interns/residents with 1-3 years' experience) and 12 experts (i.e., registrars, medical/radiation oncologists, or cancer surgeons, with more than 4 years' experience). Doctors participated in simulated BBN consultations and a number of control tasks. Five-minute-epoch heart rate (HR), HR variability, and communication performance were assessed in all participants. Subjects also completed a short questionnaire asking about their prior experience BBN, perceived stress, psychological distress (i.e., anxiety, depression), fatigue, and burnout. High stress responses were related to inexperience with BBN, fatigue, and giving bad versus good news. Poor communication performance in the consultation was related to high burnout and fatigue scores. These results suggest that BBN was a stressful experience for doctors even in a simulated encounter, especially for those who were inexperienced and/or fatigued. Poor communication performance was related to burnout and fatigue, but not inexperience with BBN. These results likely indicate that burnout and fatigue contributed to stress and poor work performance in some doctors during the simulated BBN task.

Italian retail gasoline activities: inadequate distribution network

International Nuclear Information System (INIS)

Verde, Stefano

2005-01-01

It is common belief that competition in the Italian retail gasoline activities is hindered by oil companies' collusive behaviour. However, when developing a broader analysis of the sector, low efficiency and scarce competition could results as the consequences coming from an inadequate distribution network and from the recognition of international markets and focal point [it

Folk Beliefs of Cultural Changes in China

Directory of Open Access Journals (Sweden)

Yi eXu

2014-09-01

Full Text Available For the last several decades, Chinese society has experienced transformative changes. How are these changes understood among Chinese people? To examine this question, Part 1 in this research solicited folk beliefs of cultural change from a group of Chinese participants in an open-ended format, and the generated folk beliefs were rated by another group of participants in Part 2 to gauge each belief’s level of agreement. Part 3 plotted the folk beliefs retained in Part 2 using the Google Ngram Viewer in order to infer the amount of intellectual interests that each belief has received cross-temporarily. These analyses suggested a few themes in Chinese folk beliefs of cultural change (1 rising perceived importance of materialism and individualism in understanding contemporary Chinese culture and Chinese psychology relative to those of the past (2 rising perceived importance of freedom, democracy and human rights and (3 enduring perceived importance of family relations and friendship as well as patriotism. Interestingly, findings from Parts 2 and 3 diverged somewhat, illuminating possible divergence between folk beliefs and intellectual interests especially for issues related to heritage of Confucianism.

Equilibria in social belief removal [Journal article

CSIR Research Space (South Africa)

Booth, R

2010-08-01

Full Text Available removal function >i, which tells it how to remove any given sentence from its belief set. In this paper we view >i as a unary function on the set L of non- tautologous sentences, i.e., agents are never required to remove >. The result of removing 2 L... from i?s belief set is denoted by >i( ). We assume i?s initial belief set can always be recaptured from >i alone by just removing the (b) (1) (A) contradiction, i.e., i?s initial belief set is >i(?). We call any n-tuple (>i)i2A of removal functions a...

The Development of Reasoning about Beliefs: Fact, Preference, and Ideology.

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Heiphetz, Larisa; Spelke, Elizabeth S; Harris, Paul L; Banaji, Mahzarin R

2013-05-01

The beliefs people hold about the social and physical world are central to self-definition and social interaction. The current research analyzes reasoning about three kinds of beliefs: those that concern matters of fact (e.g., dinosaurs are extinct), preference (e.g., green is the prettiest color), and ideology (e.g., there is only one God). The domain of ideology is of unique interest because it is hypothesized to contain elements of both facts and preferences. If adults' distinct reasoning about ideological beliefs is the result of prolonged experience with the physical and social world, children and adults should reveal distinct patterns of differentiating kinds of beliefs, and this difference should be particularly pronounced with respect to ideological beliefs. On the other hand, if adults' reasoning about beliefs is a basic component of social cognition, children and adults should demonstrate similar belief representations and patterns of belief differentiation. Two experiments demonstrate that 5-10 year old children and adults similarly judged religious beliefs to be intermediate between factual beliefs (where two disagreeing people cannot both be right) and preferences (where they can). From the age of 5 years and continuing into adulthood, individuals distinguished ideological beliefs from other types of mental states and demonstrated limited tolerance for belief-based disagreements.

Should informed consent be based on rational beliefs?

OpenAIRE

Savulescu, J; Momeyer, R W

1997-01-01

Our aim is to expand the regulative ideal governing consent. We argue that consent should not only be informed but also based on rational beliefs. We argue that holding true beliefs promotes autonomy. Information is important insofar as it helps a person to hold the relevant true beliefs. But in order to hold the relevant true beliefs, competent people must also think rationally. Insofar as information is important, rational deliberation is important. Just as physicians should aim to provide ...

Childhood trauma and the development of paranormal beliefs.

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Berkowski, Monisha; MacDonald, Douglas A

2014-04-01

Belief in the paranormal is fairly prevalent in the general population. Previous research has shown a link between several personological characteristics and paranormal beliefs. The current study attempted to further investigate this link by replicating previous models that have shown a link between childhood trauma, fantasy proneness, and paranormal beliefs. In addition, the study attempted to expand on this model by including other variables such as stigma, resiliency, and coping style. The study used a sample of 198 undergraduate students. A significant correlation between trauma and paranormal beliefs was found. Partial correlations and path analyses revealed that fantasy proneness and avoidant coping style fully mediate the relationship between trauma and paranormal beliefs. The results imply that researchers need to take into account how a person responds to trauma via the development of coping strategies to accurately understand any observed relationship between trauma and paranormal beliefs.

Feeling Is Believing: Inspiration Encourages Belief in God.

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Critcher, Clayton R; Lee, Chan Jean

2018-05-01

Even without direct evidence of God's existence, about half of the world's population believes in God. Although previous research has found that people arrive at such beliefs intuitively instead of analytically, relatively little research has aimed to understand what experiences encourage or legitimate theistic belief systems. Using cross-cultural correlational and experimental methods, we investigated whether the experience of inspiration encourages a belief in God. Participants who dispositionally experience more inspiration, were randomly assigned to relive or have an inspirational experience, or reported such experiences to be more inspirational all showed stronger belief in God. These effects were specific to inspiration (instead of adjacent affective experiences) and a belief in God (instead of other empirically unverifiable claims). Being inspired by someone or something (but not inspired to do something) offers a spiritually transcendent experience that elevates belief in God, in part because it makes people feel connected to something beyond themselves.

Analytic thinking reduces belief in conspiracy theories.

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Swami, Viren; Voracek, Martin; Stieger, Stefan; Tran, Ulrich S; Furnham, Adrian

2014-12-01

Belief in conspiracy theories has been associated with a range of negative health, civic, and social outcomes, requiring reliable methods of reducing such belief. Thinking dispositions have been highlighted as one possible factor associated with belief in conspiracy theories, but actual relationships have only been infrequently studied. In Study 1, we examined associations between belief in conspiracy theories and a range of measures of thinking dispositions in a British sample (N=990). Results indicated that a stronger belief in conspiracy theories was significantly associated with lower analytic thinking and open-mindedness and greater intuitive thinking. In Studies 2-4, we examined the causational role played by analytic thinking in relation to conspiracist ideation. In Study 2 (N=112), we showed that a verbal fluency task that elicited analytic thinking reduced belief in conspiracy theories. In Study 3 (N=189), we found that an alternative method of eliciting analytic thinking, which related to cognitive disfluency, was effective at reducing conspiracist ideation in a student sample. In Study 4, we replicated the results of Study 3 among a general population sample (N=140) in relation to generic conspiracist ideation and belief in conspiracy theories about the July 7, 2005, bombings in London. Our results highlight the potential utility of supporting attempts to promote analytic thinking as a means of countering the widespread acceptance of conspiracy theories. Copyright © 2014 Elsevier B.V. All rights reserved.

The hot hand belief and framing effects.

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MacMahon, Clare; Köppen, Jörn; Raab, Markus

2014-09-01

Recent evidence of the hot hand in sport-where success breeds success in a positive recency of successful shots, for instance-indicates that this pattern does not actually exist. Yet the belief persists. We used 2 studies to explore the effects of framing on the hot hand belief in sport. We looked at the effect of sport experience and task on the perception of baseball pitch behavior as well as the hot hand belief and free-throw behavior in basketball. Study 1 asked participants to designate outcomes with different alternation rates as the result of baseball pitches or coin tosses. Study 2 examined basketball free-throw behavior and measured predicted success before each shot as well as general belief in the hot hand pattern. The results of Study 1 illustrate that experience and stimulus alternation rates influence the perception of chance in human performance tasks. Study 2 shows that physically performing an act and making judgments are related. Specifically, beliefs were related to overall performance, with more successful shooters showing greater belief in the hot hand and greater predicted success for upcoming shots. Both of these studies highlight that the hot hand belief is influenced by framing, which leads to instability and situational contingencies. We show the specific effects of framing using accumulated experience of the individual with the sport and knowledge of its structure and specific experience with sport actions (basketball shots) prior to judgments.

How do Epistemological Beliefs Affect Training Motivation?

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Ingrid Molan

2014-05-01

Full Text Available Studies show that human resources development through workplace training is one of the major investments in the workforce in today’s globalized and challenging market. As training motivation influences employees’ preparation for the workplace training, their respond to the programme, their learning outcome, their performance levels, and use of acquired knowledge and skills in their workplace it seems logical to investigate and determine antecedents of training motivation. The aim of this study was to examine the relationship between the concepts of epistemological beliefs, training motivation and the actual participation in the workplace training. We predicted that epistemological beliefs would have an effect on training motivation and actual participation on the workplace training and that there would be a positive relationship between the concepts, meaning that the more sophisticated epistemological beliefs would lead to higher motivation and participation. To test the epistemological beliefs, the Epistemic Belief Inventory (Schraw, Bendixen & Dunkle, 2002 was used and adjusted to the workplace setting. Then the results were compared to employees’ training motivation, which was measured with a questionnaire made by authors of the present study, and employees’ actual number of training hours annually. The results confirmed the relationship between the concepts as well as a significant predicting value of epistemological beliefs on motivation and actual participation. Epistemic Belief Inventory did not yield expected results reported by the authors of the instrument therefore the limitations, possible other interpretations and suggested further exploration are discussed.

Individualized measurement of irrational beliefs in remitted depressives.

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Solomon, Ari; Arnow, Bruce A; Gotlib, Ian H; Wind, Brian

2003-04-01

Recent reviews of cognitive theories of depression have noted that individualized assessment strategies might help to resolve mixed findings regarding the stability of depressotypic beliefs and attitudes. We describe encouraging results for an individualized measure of one such cognitive construct, irrational beliefs. Twenty depression-prone women (recurrent major depressives in full remission) and twenty closely matched never-depressed controls completed leading forced-choice measures of irrational beliefs (the Belief Scale; BS) and sociotropy-autonomy (The Revised Personal Style Inventory), as well as the Specific Demands on Self Scale (SDS). The BS requires participants to rate their agreement with twenty preselected statements of irrational beliefs, while the SDS focuses on whether participants harbor any strongly held irrational beliefs, even if uncommon or idiosyncratic. Consistent with previous research, there were no group differences on the traditional measure of irrational beliefs. In contrast, depression-prone participants strongly exceeded controls on the SDS, and this difference persisted after controlling for residual depression, anxiety symptoms, anxiety diagnoses, sociotropy, and autonomy. These findings provide some initial support for a key assumption of the rational-emotive model of depression, and, more broadly, suggest that individualized assessment strategies may help researchers capture the core negative beliefs of asymptomatic individuals, even in the absence of mood or cognitive priming. Copyright 2003 Wiley Periodicals, Inc. J Clin Psychol 59: 439-455, 2003.

Organizational Conspiracy Beliefs: Implications for Leadership Styles and Employee Outcomes.

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van Prooijen, Jan-Willem; de Vries, Reinout E

2016-01-01

Belief in conspiracy theories about societal events is widespread among citizens. The extent to which conspiracy beliefs about managers and supervisors matter in the micro-level setting of organizations has not yet been examined, however. We investigated if leadership styles predict conspiracy beliefs among employees in the context of organizations. Furthermore, we examined if such organizational conspiracy beliefs have implications for organizational commitment and turnover intentions. We conducted a survey among a random sample of the US working population ( N  = 193). Despotic, laissez-faire, and participative leadership styles predicted organizational conspiracy beliefs, and the relations of despotic and laissez-faire leadership with conspiracy beliefs were mediated by feelings of job insecurity. Furthermore, organizational conspiracy beliefs predicted, via decreased organizational commitment, increased turnover intentions. Organizational conspiracy beliefs matter for how employees perceive their leaders, how they feel about their organization, and whether or not they plan to quit their jobs. A practical implication, therefore, is that it would be a mistake for managers to dismiss organizational conspiracy beliefs as innocent rumors that are harmless to the organization. Three novel conclusions emerge from this study. First, organizational conspiracy beliefs occur frequently among employees. Second, participative leadership predicts decreased organizational conspiracy beliefs; despotic and laissez-faire leadership predict increased organizational conspiracy beliefs due to the contribution of these destructive leadership styles to an insecure work environment. Third, organizational conspiracy beliefs harm organizations by influencing employee commitment and, indirectly, turnover intentions.

Valence-Dependent Belief Updating: Computational Validation

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Bojana Kuzmanovic

2017-06-01

Full Text Available People tend to update beliefs about their future outcomes in a valence-dependent way: they are likely to incorporate good news and to neglect bad news. However, belief formation is a complex process which depends not only on motivational factors such as the desire for favorable conclusions, but also on multiple cognitive variables such as prior beliefs, knowledge about personal vulnerabilities and resources, and the size of the probabilities and estimation errors. Thus, we applied computational modeling in order to test for valence-induced biases in updating while formally controlling for relevant cognitive factors. We compared biased and unbiased Bayesian models of belief updating, and specified alternative models based on reinforcement learning. The experiment consisted of 80 trials with 80 different adverse future life events. In each trial, participants estimated the base rate of one of these events and estimated their own risk of experiencing the event before and after being confronted with the actual base rate. Belief updates corresponded to the difference between the two self-risk estimates. Valence-dependent updating was assessed by comparing trials with good news (better-than-expected base rates with trials with bad news (worse-than-expected base rates. After receiving bad relative to good news, participants' updates were smaller and deviated more strongly from rational Bayesian predictions, indicating a valence-induced bias. Model comparison revealed that the biased (i.e., optimistic Bayesian model of belief updating better accounted for data than the unbiased (i.e., rational Bayesian model, confirming that the valence of the new information influenced the amount of updating. Moreover, alternative computational modeling based on reinforcement learning demonstrated higher learning rates for good than for bad news, as well as a moderating role of personal knowledge. Finally, in this specific experimental context, the approach based on

Developing a dimensional model for successful cognitive and emotional aging.

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Vahia, Ipsit V; Thompson, Wesley K; Depp, Colin A; Allison, Matthew; Jeste, Dilip V

2012-04-01

There is currently a lack of consensus on the definition of successful aging (SA) and existing implementations have omitted constructs associated with SA. We used empirical methods to develop a dimensional model of SA that incorporates a wider range of associated variables, and we examined the relationship among these components using factor analysis and Bayesian Belief Nets. We administered a successful aging questionnaire comprising several standardized measures related to SA to a sample of 1948 older women enrolled in the San Diego site of the Women's Health Initiative study. The SA-related variables we included in the model were self-rated successful aging, depression severity, physical and emotional functioning, optimism, resilience, attitude towards own aging, self-efficacy, and cognitive ability. After adjusting for age, education and income, we fitted an exploratory factor analysis model to the SA-related variables and then, in order to address relationships among these factors, we computed a Bayesian Belief Net (BBN) using rotated factor scores. The SA-related variables loaded onto five factors. Based on the loading, we labeled the factors as follows: self-rated successful aging, cognition, psychosocial protective factors, physical functioning, and emotional functioning. In the BBN, self-rated successful aging emerged as the primary downstream factor and exhibited significant partial correlations with psychosocial protective factors, physical/general status and mental/emotional status but not with cognitive ability. Our study represents a step forward in developing a dimensional model of SA. Our findings also point to a potential role for psychiatry in improving successful aging by managing depressive symptoms and developing psychosocial interventions to improve self-efficacy, resilience, and optimism.

Estructura factorial del inventario Leisure Coping Belief Scale en una muestra mexicana (Structure Factor of the Leisure Coping Belief Scale Inventory in a Mexican Sample

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Minerva Vanegas-Farfano

2014-12-01

Full Text Available Resumen Los pasatiempos, vistos como actividades que fomentan el desarrollo de habilidades, aptitudes y redes sociales, fuera de la escuela o el trabajo, presentan opciones físicas, intelectuales y económicas, capaces de apoyar el desarrollo personal y el manejo del estrés en todo tipo de poblaciones. Por ello, este estudio analiza las propiedades psicométricas de cuatro subescalas del cuestionario Leisure Coping Belief Scale (LCBS en 132 adultos de población mexicana. El análisis factorial apoya su dimensionalidad y estructura factorial en cuatro factores, como en el modelo original. La consistencia interna del inventario refleja una adecuada confiabilidad. Se evidencia que la LCBS-M es una medida válida y fiable para continuar realizando estudios sobre las creencias en torno al uso de los pasatiempos como estrategias de afrontamiento en adultos mexicanos. Abstract Hobbies, seen as activities that promote the development of abilities, skills, and social networks, outside of school or work, present physical, intellectual and economic options, able to support the personal development and stress management in all types of populations. Therefore, this study analyzes the psychometric properties of four subscales of the questionnaire Leisure Coping Belief Scale (LCBS in 132 adults of Mexican population. The factorial analysis supports its dimensionality and factorial structure in four factors, such as in the original model. The internal consistency of the inventory reflects adequate reliability. It is evident that the LCBS-M is a valid and reliable measure to continue the studies on beliefs about the use of the hobbies as coping strategies in Mexican adults.

Psychosis or Faith? Clinicians' Assessment of Religious Beliefs

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O'Connor, Shawn; Vandenberg, Brian

2005-01-01

This study investigated mental health professionals' assessment of the pathognomonic significance of religious beliefs. A total of 110 participants reviewed 3 vignettes depicting individuals possessing the religious beliefs associated with Catholicism, Mormonism, and Nation of Islam. The religious beliefs of the individuals in the vignettes were…

An integrated model of communication influence on beliefs.

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Eveland, William P; Cooper, Kathryn E

2013-08-20

How do people develop and maintain their beliefs about science? Decades of social science research exist to help us answer this question. The Integrated Model of Communication Influence on Beliefs presented here combines multiple theories that have considered aspects of this process into a comprehensive model to explain how individuals arrive at their scientific beliefs. In this article, we (i) summarize what is known about how science is presented in various news and entertainment media forms; (ii) describe how individuals differ in their choices to be exposed to various forms and sources of communication; (iii) discuss the implications of how individuals mentally process information on the effects of communication; (iv) consider how communication effects can be altered depending on background characteristics and motivations of individuals; and (v) emphasize that the process of belief formation is not unidirectional but rather, feeds back on itself over time. We conclude by applying the Integrated Model of Communication Influence on Beliefs to the complex issue of beliefs about climate change.

Functional beliefs and risk minimizing beliefs among Thai healthcare workers in Maharaj Nakorn Chiang Mai hospital: its association with intention to quit tobacco and alcohol.

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Jiraniramai, Surin; Jiraporncharoen, Wichuda; Pinyopornpanish, Kanokporn; Jakkaew, Nalinee; Wongpakaran, Tinakon; Angkurawaranon, Chaisiri

2017-07-12

Individual health beliefs are likely to play a key role in how people respond to knowledge and information about the potential harm from smoking and alcohol abuse. The objectives of the study were to 1) explore whether functional beliefs and risk minimizing beliefs were associated with intention to quit smoking and confidence to quit smoking and 2) explore whether functional beliefs and risk minimizing beliefs were associated with intention to quit alcohol drinking and confidence to quit alcohol drinking. A cross-sectional survey was conducted in 2013 among health care workers working in Thailand. Using predicted factor scores from factor analysis, the relationship between factor scores for each of the two beliefs and intention to quit and confidence to quit were tested using ANOVA and further adjusted for age and sex using linear regression. Functional beliefs were inversely associated with the intention to quit and confidence to quit smoking. Both functional beliefs and risk minimizing beliefs were each inversely associated with the intention to quit and confidence to quit alcohol drinking. Our study enhances the understanding of the complexities of health beliefs regarding these two commonly abused substances. As functional beliefs were associated with smoking and alcohol use, interventions to counter the cultural values and individual beliefs about the benefits of smoking and alcohol use are needed. Tackling risk minimizing beliefs by providing individualized feedback regarding harm may also be useful in alcohol drinkers.

Mental Rotation in False Belief Understanding.

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Xie, Jiushu; Cheung, Him; Shen, Manqiong; Wang, Ruiming

2018-05-01

This study examines the spontaneous use of embodied egocentric transformation (EET) in understanding false beliefs in the minds of others. EET involves the participants mentally transforming or rotating themselves into the orientation of an agent when trying to adopt his or her visuospatial perspective. We argue that psychological perspective taking such as false belief reasoning may also involve EET because of what has been widely reported in the embodied cognition literature, showing that our processing of abstract, propositional information is often grounded in concrete bodily sensations which are not apparently linked to higher cognition. In Experiment 1, an agent placed a ball into one of two boxes and left. The ball then rolled out and moved either into the other box (new box) or back into the original one (old box). The participants were to decide from which box they themselves or the agent would try to recover the ball. Results showed that false belief performance was affected by increased orientation disparity between the participants and the agent, suggesting involvement of embodied transformation. In Experiment 2, false belief was similarly induced and the participants were to decide if the agent would try to recover the ball in one specific box. Orientation disparity was again found to affect false belief performance. The present results extend previous findings on EET in visuospatial perspective taking and suggest that false belief reasoning, which is a kind of psychological perspective taking, can also involve embodied rotation, consistent with the embodied cognition view. Copyright © 2018 Cognitive Science Society, Inc.

Examining Belief and Confidence in Schizophrenia

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Joyce, Dan W.; Averbeck, Bruno B.; Frith, Chris D.; Shergill, Sukhwinder S.

2018-01-01

Background People with psychoses often report fixed, delusional beliefs that are sustained even in the presence of unequivocal contrary evidence. Such delusional beliefs are the result of integrating new and old evidence inappropriately in forming a cognitive model. We propose and test a cognitive model of belief formation using experimental data from an interactive “Rock Paper Scissors” game. Methods Participants (33 controls and 27 people with schizophrenia) played a competitive, time-pressured interactive two-player game (Rock, Paper, Scissors). Participant’s behavior was modeled by a generative computational model using leaky-integrator and temporal difference methods. This model describes how new and old evidence is integrated to form both a playing strategy to beat the opponent and provide a mechanism for reporting confidence in one’s playing strategy to win against the opponent Results People with schizophrenia fail to appropriately model their opponent’s play despite consistent (rather than random) patterns that can be exploited in the simulated opponent’s play. This is manifest as a failure to weigh existing evidence appropriately against new evidence. Further, participants with schizophrenia show a ‘jumping to conclusions’ bias, reporting successful discovery of a winning strategy with insufficient evidence. Conclusions The model presented suggests two tentative mechanisms in delusional belief formation – i) one for modeling patterns in other’s behavior, where people with schizophrenia fail to use old evidence appropriately and ii) a meta-cognitive mechanism for ‘confidence’ in such beliefs where people with schizophrenia overweight recent reward history in deciding on the value of beliefs about the opponent. PMID:23521846

The role of beliefs in teacher agency

DEFF Research Database (Denmark)

Biesta, Gert; Priestley, Mark; Robinson, Sarah

2015-01-01

’s Curriculum for Excellence – in order to explore these questions. We focus on teachers’ beliefs in order to get a sense of the individual and collective discourses that inform teachers’ perceptions, judgements and decision-making and that motivate and drive teachers’ action. While the research suggests...... that beliefs play an important role in teachers’ work, an apparent mismatch between teachers’ individual beliefs and values and wider institutional discourses and cultures, and a relative lack of a clear and robust professional vision of the purposes of education indicate that the promotion of teacher agency...... does not just rely on the beliefs that individual teachers bring to their practice, but also requires collective development and consideration....

The effect of belief in free will on prejudice.

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Zhao, Xian; Liu, Li; Zhang, Xiao-xiao; Shi, Jia-xin; Huang, Zhen-wei

2014-01-01

The current research examined the role of the belief in free will on prejudice across Han Chinese and white samples. Belief in free will refers to the extent to which people believe human beings truly have free will. In Study 1, the beliefs of Han Chinese people in free will were measured, and their social distances from the Tibetan Chinese were used as an index of ethnic prejudice. The results showed that the more that Han Chinese endorsed the belief in free will, the less that they showed prejudice against the Tibetan Chinese. In Study 2, the belief of the Han Chinese in free will was manipulated, and their explicit feelings towards the Uyghur Chinese were used as an indicator of ethnic prejudice. The results showed that the participants in the condition of belief in free will reported less prejudice towards Uyghur Chinese compared to their counterparts in the condition of disbelief in free will. In Study 3, white peoples' belief in free will was manipulated, and their pro-black attitudes were measured as an indirect indicator of racial prejudice. The results showed that, compared to the condition of disbelief in free will, the participants who were primed by a belief in free will reported stronger pro-black attitudes. These three studies suggest that endorsement of the belief in free will can lead to decreased ethnic/racial prejudice compared to denial of the belief in free will. The theoretical and practical implications are discussed.

Belief change

CSIR Research Space (South Africa)

Booth, R

2012-07-01

Full Text Available In this paper the authors present a brief overview of belief change, a research area concerned with the question of how a rational agent ought to change its mind in the face of new, possibly conflicting, information. The authors limit themselves...

The ecology of religious beliefs

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Botero, Carlos A.; Gardner, Beth; Kirby, Kathryn R.; Bulbulia, Joseph; Gavin, Michael C.; Gray, Russell D.

2014-01-01

Although ecological forces are known to shape the expression of sociality across a broad range of biological taxa, their role in shaping human behavior is currently disputed. Both comparative and experimental evidence indicate that beliefs in moralizing high gods promote cooperation among humans, a behavioral attribute known to correlate with environmental harshness in nonhuman animals. Here we combine fine-grained bioclimatic data with the latest statistical tools from ecology and the social sciences to evaluate the potential effects of environmental forces, language history, and culture on the global distribution of belief in moralizing high gods (n = 583 societies). After simultaneously accounting for potential nonindependence among societies because of shared ancestry and cultural diffusion, we find that these beliefs are more prevalent among societies that inhabit poorer environments and are more prone to ecological duress. In addition, we find that these beliefs are more likely in politically complex societies that recognize rights to movable property. Overall, our multimodel inference approach predicts the global distribution of beliefs in moralizing high gods with an accuracy of 91%, and estimates the relative importance of different potential mechanisms by which this spatial pattern may have arisen. The emerging picture is neither one of pure cultural transmission nor of simple ecological determinism, but rather a complex mixture of social, cultural, and environmental influences. Our methods and findings provide a blueprint for how the increasing wealth of ecological, linguistic, and historical data can be leveraged to understand the forces that have shaped the behavior of our own species. PMID:25385605

Harm beliefs and coping expectancies in youth with specific phobias.

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Ollendick, Thomas H; Öst, Lars-Göran; Ryan, Sarah M; Capriola, Nicole N; Reuterskiöld, Lena

2017-04-01

Catastrophic beliefs and lowered coping expectancies are often present in individuals with specific phobias (SPs). The current study examined these beliefs and expectancies in 251 youth who received One Session Treatment for one of the three most common types of SP in youth (animals, natural environment, and situational). We compared the children's subjective beliefs to objective ratings of the likelihood of occurrence and the dangerousness of the feared events. Results revealed pre-treatment differences in the youths' beliefs across phobia types and age. Specifically, children with animal phobias rated their beliefs as more likely to occur than did children with environmental and situational phobias. In addition, older children rated their beliefs as more dangerous than younger children. However, regardless of phobia type or child age, the beliefs improved following treatment. Changes in catastrophic beliefs and coping expectancies were related to changes in clinical severity following treatment but not 6-months following treatment. Moreover, at pre-treatment, children viewed their beliefs as significantly more catastrophic and likely to occur than did independent coders of these beliefs; however, these differences were no longer evident following treatment. Clinical implications are discussed, highlighting how changes in beliefs and expectancies might be associated with treatment outcomes. Copyright © 2017 Elsevier Ltd. All rights reserved.

Analyzing Sexual Health-Related Beliefs Among Couples in Marriage Based on the Health Belief Model

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Majid Barati

2014-06-01

Full Text Available Introduction: Sexual health is the integrity between mind, emotions, and body, and any disorder leading to discoordination, can be associated with sexual dysfunction. The aim of this study was to investigate the beliefs of couples attending marriage counseling centers toward sexual health based on the health belief model. Materials and Methods: This cross sectional descriptive study was performed on 400 couples referring to marriage counseling centers of Hamadan recruited with a random sampling method. The participants completed a self-administered questionnaire including demographic characteristics, knowledge and health belief model constructs. Data analysis was performed using SPSS-16 software, by Pearson’s coefficient correlation, independent T-test, and one-way ANOVA. Results: Couples had a moderate knowledge of sexual health. In addition, perceived susceptibility and severity of the consequences of unsafe sexual behavior among couples were not satisfactory however, perceived benefits and barriers were reported in a relatively good level. Internet and friends were the most important sources for sexual health information. Conclusion: Promoting knowledge and beliefs toward sexual health by preparing training packages based on the needs of couples and removing obstacles to have normal sexual behavior are necessary.

Predicting dyadic adjustment from general and relationship-specific beliefs.

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DeBord, J; Romans, J S; Krieshok, T

1996-05-01

The cognitive mediation model of human psychological functioning has received increasing attention by researchers studying the role of cognitive variables in relationship distress. This study is an examination of the role of general irrational beliefs, as measured by the Irrational Beliefs Test (IBT; Jones, 1968), and relationship-specific irrational beliefs, as measured by the Relationship Belief Questionnaire (RBQ; Romans & DeBord, 1994), in predicting the perceived quality of relationships by married or cohabiting couples. Results indicated that respondents who reported higher levels of relationship-specific irrational beliefs also reported higher levels of dyadic adjustment; but contrary to expectation, higher levels of general irrational beliefs correlated with lower levels of dyadic adjustment. Implications of these findings are discussed in relation to the depressive realism hypothesis.

Omega-3 Fatty Acids Inhibit Tumor Growth in a Rat Model of Bladder Cancer

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Belmiro Parada

2013-01-01

Full Text Available Omega-3 (ω-3 fatty acids have been tested on prevention and treatment of several cancer types, but the efficacy on “in vivo” bladder cancer has not been analyzed yet. This study aimed at evaluating the chemopreventive efficacy of eicosapentaenoic acid (EPA and docosahexaenoic acid (DHA mixture in an animal model of bladder cancer. Forty-four male Wistar rats were divided into 4 groups during a 20-week protocol: control; carcinogen—N-butyl-N-(4-hydroxybutyl nitrosamine (BBN; ω-3 (DHA + EPA; and ω-3 + BBN. BBN and ω-3 were given during the initial 8 weeks. At week 20 blood and bladder were collected and checked for the presence of urothelium lesions and tumors, markers of inflammation, proliferation, and redox status. Incidence of bladder carcinoma was, control (0%, ω-3 (0%, BBN (65%, and ω-3 + BBN (62.5%. The ω-3 + BBN group had no infiltrative tumors or carcinoma in situ, and tumor volume was significantly reduced compared to the BBN (0.9 ± 0.1 mm3 versus 112.5 ± 6.4 mm3. Also, it showed a reduced MDA/TAS ratio and BBN-induced serum CRP, TGF-β1, and CD31 were prevented. In conclusion, omega-3 fatty acids inhibit the development of premalignant and malignant lesions in a rat model of bladder cancer, which might be due to anti-inflammatory, antioxidant, anti-proliferative, and anti-angiogenic properties.

Beyond "born this way?" reconsidering sexual orientation beliefs and attitudes.

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Grzanka, Patrick R; Zeiders, Katharine H; Miles, Joseph R

2016-01-01

Previous research on heterosexuals' beliefs about sexual orientation (SO) has been limited in that it has generally examined heterosexuals' beliefs from an essentialist perspective. The recently developed Sexual Orientation Beliefs Scale (SOBS; Arseneau, Grzanka, Miles, & Fassinger, 2013) assesses multifarious "lay beliefs" about SO from essentialist, social constructionist, and constructivist perspectives. This study used the SOBS to explore latent group-based patterns in endorsement of these beliefs in 2 samples of undergraduate students: a mixed-gender sample (n = 379) and an all-women sample (n = 266). While previous research has posited that essentialist beliefs about the innateness of SO predict positive attitudes toward sexual minorities, our research contributes to a growing body of scholarship that suggests that biological essentialism should be considered in the context of other beliefs. Using a person-centered analytic strategy, we found that that college students fell into distinct patterns of SO beliefs that are more different on beliefs about the homogeneity, discreteness, and informativeness of SO categories than on beliefs about the naturalness of SO. Individuals with higher levels of endorsement on all 4 SOBS subscales (a group we named multidimensional essentialism) and those who were highest in discreteness, homogeneity, and informativeness beliefs (i.e., high-DHI) reported higher levels of homonegativity when compared with those who were high only in naturalness beliefs. We discuss the implications of these findings for counseling and psychotherapy about SO, as well educational and social interventions. (PsycINFO Database Record (c) 2016 APA, all rights reserved).

Bayesian Belief Network to support conflict analysis for groundwater protection: the case of the Apulia region.

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Giordano, Raffaele; D'Agostino, Daniela; Apollonio, Ciro; Lamaddalena, Nicola; Vurro, Michele

2013-01-30

Water resource management is often characterized by conflicts, as a result of the heterogeneity of interests associated with a shared resource. Many water conflicts arise on a global scale and, in particular, an increasing level of conflicts can be observed in the Mediterranean basin, characterized by water scarcity. In the present work, in order to assist the conflict analysis process, and thus outline a proper groundwater management, stakeholders were involved in the process and suitable tools were used in a Mediterranean area (the Apulia region, in Italy). In particular, this paper seeks to elicit and structure farmers' mental models influencing their decision over the main water source for irrigation. The more crucial groundwater is for farmers' objectives, the more controversial is the groundwater protection strategy. Bayesian Belief Networks were developed to simulate farmers' behavior with regard to groundwater management and to assess the impacts of protection strategy. These results have been used to calculate the conflict degree in the study area, derived from the introduction of policies for the reduction of groundwater exploitation for irrigation purposes. The less acceptable the policy is, the more likely it is that conflict will develop between farmers and the Regional Authority. The results of conflict analysis were also used to contribute to the debate concerning potential conflict mitigation measures. The approach adopted in this work has been discussed with a number of experts in groundwater management policies and irrigation management, and its main strengths and weaknesses have been identified. Increasing awareness of the existence of potential conflicts and the need to deal with them can be seen as an interesting initial shift in the Apulia region's water management regime, which is still grounded in merely technical approaches. Copyright © 2012 Elsevier Ltd. All rights reserved.

Spanking infants and toddlers: maternal belief and practice.

Science.gov (United States)

Socolar, R R; Stein, R E

1995-01-01

To describe maternal beliefs and practices of spanking infants and toddlers and the relations between factors affecting these beliefs and practices. Cross-sectional survey. Site 1 was an inner-city teaching hospital pediatric clinic. Site 2 was a private pediatrician's office in a nearby suburban neighborhood. Mothers of children less than 4 years old in the waiting area. Site 1: n = 104; site 2: n = 100. Systematic sample of convenience. Mothers were interviewed using a 20-minute structured questionnaire. Measures were constructed to assess beliefs (Cronbach's alpha = .90) and practices about spanking and approach to discipline (alpha > .71). Belief in spanking correlated significantly (P children 1 to 3 years old. Forty-two percent reported that they had spanked their own child in the past week. Mothers believed more strongly in spanking for dangerous misbehaviors than for annoying ones (P disciplining very young children. The context of the spanking affects beliefs and practices. The finding that belief and practice of spanking are highly correlated suggests that belief rather than impulse largely explains spanking of children less than 4 years old. The high correlation between spanking and negative approach toward discipline raises questions about whether negative consequences of spanking are the result of spanking per se, the negative approach toward the child, or both.

Constraining axion dark matter with Big Bang Nucleosynthesis

International Nuclear Information System (INIS)

Blum, Kfir; D'Agnolo, Raffaele Tito; Lisanti, Mariangela; Safdi, Benjamin R.

2014-01-01

We show that Big Bang Nucleosynthesis (BBN) significantly constrains axion-like dark matter. The axion acts like an oscillating QCD θ angle that redshifts in the early Universe, increasing the neutron–proton mass difference at neutron freeze-out. An axion-like particle that couples too strongly to QCD results in the underproduction of 4 He during BBN and is thus excluded. The BBN bound overlaps with much of the parameter space that would be covered by proposed searches for a time-varying neutron EDM. The QCD axion does not couple strongly enough to affect BBN

Constraining axion dark matter with Big Bang Nucleosynthesis

Science.gov (United States)

Blum, Kfir; D'Agnolo, Raffaele Tito; Lisanti, Mariangela; Safdi, Benjamin R.

2014-10-01

We show that Big Bang Nucleosynthesis (BBN) significantly constrains axion-like dark matter. The axion acts like an oscillating QCD θ angle that redshifts in the early Universe, increasing the neutron-proton mass difference at neutron freeze-out. An axion-like particle that couples too strongly to QCD results in the underproduction of 4He during BBN and is thus excluded. The BBN bound overlaps with much of the parameter space that would be covered by proposed searches for a time-varying neutron EDM. The QCD axion does not couple strongly enough to affect BBN.

Positive and Negative Aspects of Using Social Networks in Higher Education: A Focus Group Study

Science.gov (United States)

Vural, Ömer Faruk

2015-01-01

Social Networking Sites (SNS) have become popular among students and faculties, especially for all young population. SNSs are a relatively new technology, and little research has been conducted on the beliefs of the teacher candidates about using Social Network as an instructional tool. The study was conducted to find out for what purposes…

A Bayesian network based framework for real-time crash prediction on the basic freeway segments of urban expressways.

Science.gov (United States)

Hossain, Moinul; Muromachi, Yasunori

2012-03-01

The concept of measuring the crash risk for a very short time window in near future is gaining more practicality due to the recent advancements in the fields of information systems and traffic sensor technology. Although some real-time crash prediction models have already been proposed, they are still primitive in nature and require substantial improvements to be implemented in real-life. This manuscript investigates the major shortcomings of the existing models and offers solutions to overcome them with an improved framework and modeling method. It employs random multinomial logit model to identify the most important predictors as well as the most suitable detector locations to acquire data to build such a model. Afterwards, it applies Bayesian belief net (BBN) to build the real-time crash prediction model. The model has been constructed using high resolution detector data collected from Shibuya 3 and Shinjuku 4 expressways under the jurisdiction of Tokyo Metropolitan Expressway Company Limited, Japan. It has been specifically built for the basic freeway segments and it predicts the chance of formation of a hazardous traffic condition within the next 4-9 min for a particular 250 meter long road section. The performance evaluation results reflect that at an average threshold value the model is able to successful classify 66% of the future crashes with a false alarm rate less than 20%. Copyright © 2011 Elsevier Ltd. All rights reserved.

Criminalising defamation of religion and belief

NARCIS (Netherlands)

van Noorloos, L.A.

2014-01-01

This article deals with the role of criminal law in dealing with defamatory expressions about religion or belief. Defamation of religion and belief is a form of indirect defamation ‘via identification’ which, as the discussion about the Dutch group defamation law shows, stretches up the notion of

Teachers' Beliefs about Neuroscience and Education

Science.gov (United States)

Zambo, Debby; Zambo, Ron

2011-01-01

Information from neuroscience is readily available to educators, yet instructors of educational psychology and related fields have not investigated teachers' beliefs regarding this information. The purpose of this survey study was to uncover the beliefs 62 teachers held about neuroscience and education. Results indicate there were three types of…

Cultural Beliefs about Autism in Indonesia

Science.gov (United States)

Riany, Yulina Eva; Cuskelly, Monica; Meredith, Pamela

2016-01-01

Cultural beliefs about parenting have an important influence on parenting behaviours, including considerations about appropriate ways to parent children with autism. Although Indonesia has one of the largest and most ethnically diverse populations in the world, little is known about cultural beliefs regarding children with autism within Indonesian…

Strong commitment to traditional Protestant religious beliefs is negatively related to beliefs in paranormal phenomena.

Science.gov (United States)

Hillstrom, E L; Strachan, M

2000-02-01

Numerous studies have yielded small, negative correlations between measures of paranormal and "traditional religious beliefs". This may partly reflect opinions of Christians in the samples who take biblical sanctions against many "paranormal" activities seriously. To test this, 391 college students (270 women and 121 men) rated their beliefs in various paranormal phenomena and were classified as Believers, Nominal Believers, and Nonbelievers on the strength of their self-rated commitment to key biblical (particularly Protestant) doctrines. As predicted, Believers were significantly less likely than Nominal Believers or Nonbelievers to endorse reincarnation, contact with the dead, UFOs, telepathy, prophecy, psychokinesis, or healing, while the beliefs of Nominal Believers were similar to those of Nonbelievers. Substantial percentages of Nominal and Nonbelievers (30-50%) indicated at least moderate acceptance of the paranormal phenomena surveyed.

Traditional Christian Belief and Belief in the Supernatural : Diverging Trends in the Netherlands Between 1979 and 2005?

NARCIS (Netherlands)

Graaf, Nan Dirk de; Grotenhuis, Manfred te

2008-01-01

Is there an ongoing decline in religious beliefs in the Netherlands? Using cross-sectional data from 1979 up to 2005, we focus on traditional Christian faith and belief in the supernatural; the literature suggests that they undergo diverging trends. We first describe these trends using the Social

Traditional Christian belief and belief in the supernatural: Diverging trends in the Netherlands between 1979 and 2005?

NARCIS (Netherlands)

Graaf, N.D. de; Grotenhuis, H.F. te

2008-01-01

Is there an ongoing decline in religious beliefs in the Netherlands? Using cross-sectional data from 1979 up to 2005, we focus on traditional Christian faith and belief in the supernatural; the literature suggests that they undergo diverging trends. We first describe these trends using the Social

See, reflect, learn more: qualitative analysis of breaking bad news reflective narratives.

Science.gov (United States)

Karnieli-Miller, Orit; Palombo, Michal; Meitar, Dafna

2018-05-01

Breaking bad news (BBN) is a challenge that requires multiple professional competencies. BBN teaching often includes didactic and group role-playing sessions. Both are useful and important, but exclude another critical component of students' learning: day-to-day role-model observation in the clinics. Given the importance of observation and the potential benefit of reflective writing in teaching, we have incorporated reflective writing into our BBN course. The aim of this study was to enhance our understanding of the learning potential in reflective writing about BBN encounters and the ability to identify components that inhibit this learning. This was a systematic qualitative immersion/crystallization analysis of 166 randomly selected BBN narratives written by 83 senior medical students. We analysed the narratives in an iterative consensus-building process to identify the issues discussed, the lessons learned and the enhanced understanding of BBN. Having previously been unaware of, not invited to or having avoided BBN encounters, the mandatory assignment led students to search for or ask their mentors to join them in BBN encounters. Observation and reflective writing enhanced students' awareness that 'bad news' is relative and subjective, while shedding light on patients', families', physicians' and their own experiences and needs, revealing the importance of the different components of the BBN protocol. We identified diversity among the narratives and the extent of students' learning. Narrative writing provided students with an opportunity for a deliberative learning process. This led to deeper understanding of BBN encounters, of how to apply the newly taught protocol, or of the need for it. This process connected the formal and informal or hidden curricula. To maximise learning through reflective writing, students should be encouraged to write in detail about a recent observed encounter, analyse it according to the protocol, address different participants

Construction and Validation of Afterlife Belief Scale for Muslims.

Science.gov (United States)

Ghayas, Saba; Batool, Syeda Shahida

2017-06-01

The purpose of this study was to develop a scale in Urdu language for measuring different dimensions of afterlife belief. The scale was subjected to exploratory and confirmatory factor analysis on a sample of 504 individuals (235 men and 269 women) recruited from different cities in the Punjab, Pakistan. After exploratory and confirmatory factor analysis, 16 items were retained with three well-defined factor structures of afterlife belief: positive, negative, and extinction. The alpha coefficients of the subscales ranged from .65 to .78. Convergent and discriminant validity of the subscales of Afterlife Belief Scale was determined by finding its relationship with the Pleasant Afterlife Belief Scale, the Unpleasant Afterlife Belief Scale, the Anxiety Subscale of DASS, and the Belief in Equitable World Scale. The results support that the newly developed scale has promising validity.

An integrated model of communication influence on beliefs

Science.gov (United States)

Eveland, William P.; Cooper, Kathryn E.

2013-01-01

How do people develop and maintain their beliefs about science? Decades of social science research exist to help us answer this question. The Integrated Model of Communication Influence on Beliefs presented here combines multiple theories that have considered aspects of this process into a comprehensive model to explain how individuals arrive at their scientific beliefs. In this article, we (i) summarize what is known about how science is presented in various news and entertainment media forms; (ii) describe how individuals differ in their choices to be exposed to various forms and sources of communication; (iii) discuss the implications of how individuals mentally process information on the effects of communication; (iv) consider how communication effects can be altered depending on background characteristics and motivations of individuals; and (v) emphasize that the process of belief formation is not unidirectional but rather, feeds back on itself over time. We conclude by applying the Integrated Model of Communication Influence on Beliefs to the complex issue of beliefs about climate change. PMID:23940328

Formal and Informal Normative Beliefs Regarding Purchasing and Using Condoms

OpenAIRE

樋口, 匡貴; 中村, 菜々子

2009-01-01

Properly using condoms is one of the most effective types of protection against HIV. To clarify the contents of normative beliefs regarding purchasing and using condoms, 390 undergraduate student volunteers were surveyed. The exploratory and confirmatory factor analyses revealed that both males and females held two types of normative beliefs, namely formal normative beliefs and informal normative beliefs, regarding purchasing and using condoms. Formal normative beliefs were concerned with the...

Linking unfounded beliefs to genetic dopamine availability

Science.gov (United States)

Schmack, Katharina; Rössler, Hannes; Sekutowicz, Maria; Brandl, Eva J.; Müller, Daniel J.; Petrovic, Predrag; Sterzer, Philipp

2015-01-01

Unfounded convictions involving beliefs in the paranormal, grandiosity ideas or suspicious thoughts are endorsed at varying degrees among the general population. Here, we investigated the neurobiopsychological basis of the observed inter-individual variability in the propensity toward unfounded beliefs. One hundred two healthy individuals were genotyped for four polymorphisms in the COMT gene (rs6269, rs4633, rs4818, and rs4680, also known as val158met) that define common functional haplotypes with substantial impact on synaptic dopamine degradation, completed a questionnaire measuring unfounded beliefs, and took part in a behavioral experiment assessing perceptual inference. We found that greater dopamine availability was associated with a stronger propensity toward unfounded beliefs, and that this effect was statistically mediated by an enhanced influence of expectations on perceptual inference. Our results indicate that genetic differences in dopaminergic neurotransmission account for inter-individual differences in perceptual inference linked to the formation and maintenance of unfounded beliefs. Thus, dopamine might be critically involved in the processes underlying one's interpretation of the relationship between the self and the world. PMID:26483654

Linking unfounded beliefs to genetic dopamine availability

Directory of Open Access Journals (Sweden)

Katharina eSchmack

2015-09-01

Full Text Available Unfounded convictions involving beliefs in the paranormal, grandiosity ideas or suspicious thoughts are endorsed at varying degrees among the general population. Here, we investigated the neurobiopsychological basis of the observed inter-individual variability in the propensity towards unfounded beliefs. 109 healthy individuals were genotyped for four polymorphisms in the COMT gene (rs6269, rs4633, rs4818 and rs4680, also known as val158met that define common functional haplotypes with substantial impact on synaptic dopamine degradation, completed a questionnaire measuring unfounded beliefs, and took part in a behavioural experiment assessing perceptual inference. We found that greater dopamine availability was associated with a stronger propensity towards unfounded beliefs, and that this effect was mediated by an enhanced influence of expectations on perceptual inference. Our results indicate that genetic differences in dopaminergic neurotransmission account for inter-individual differences in perceptual inference linked to the formation and maintenance of unfounded beliefs. Thus, dopamine might be critically involved in the processes underlying one's interpretation of the relationship between the self and the world.

Episode-Centered Guidelines for Teacher Belief Change toward Technology Integration

Science.gov (United States)

Er, Erkan; Kim, ChanMin

2017-01-01

Teachers' episodic memories influence their beliefs. The investigation of episodic memories can help identify the teacher beliefs that limit technology-integration. We propose the Episode-Centered Belief Change (ECBC) model that utilizes teachers' episodic memories for changing beliefs impeding effective technology integration. We also propose…

Smoking beliefs and behavior among youth in Malaysia and Thailand.

Science.gov (United States)

Parkinson, Carla M; Hammond, David; Fong, Geoffrey T; Borland, Ron; Omar, Maizurah; Sirirassamee, Buppha; Awang, Rahmat; Driezen, Pete; Thompson, Mary

2009-01-01

To characterize smoking beliefs among Thai and Malaysian youth and to examine associations with gender, antismoking media exposure, and smoking status. Nationally representative samples of youth completed self-administered questionnaires. A substantial proportion of youth reported positive beliefs about smoking. Those reporting positive beliefs were more likely to be susceptible to smoking. Youth who noticed antismoking media were less likely to report positive beliefs about smoking. As in Western countries, beliefs about smoking held by youth in Southeast Asia are associated with smoking status. Antismoking media may be an important means of targeting beliefs about smoking among youth.

Changing Professional Practice Requires Changing Beliefs

Science.gov (United States)

Guerra, Patricia L.; Nelson, Sarah W.

2009-01-01

Creating schools that are culturally responsive and successful with all students requires doing basic work with educators to uncover their beliefs about children. If school leaders believe, like many people do, that changed behavior will result in changed beliefs, they are mistaken. Leaders must be proactive in identifying what teachers believe…

Belief Inhibition in Children's Reasoning: Memory-Based Evidence

Science.gov (United States)

Steegen, Sara; Neys, Wim De

2012-01-01

Adult reasoning has been shown as mediated by the inhibition of intuitive beliefs that are in conflict with logic. The current study introduces a classic procedure from the memory field to investigate belief inhibition in 12- to 17-year-old reasoners. A lexical decision task was used to probe the memory accessibility of beliefs that were cued…

Mainstream Teachers' Implicit Beliefs about English Language Learners: An Implicit Association Test Study of Teacher Beliefs

Science.gov (United States)

Harrison, Jamie; Lakin, Joni

2018-01-01

Teacher attitudes toward inclusion of English Learners (ELs) in the mainstream classroom have primarily focused on explicit beliefs as accessed through observation, case studies, and self-report surveys. The authors explore implicit mainstream teacher beliefs about ELs using the newly created Implicit Association Test-EL, with correlations to…

Breaking bad news in clinical setting - health professionals' experience and perceived competence in Southwestern Nigeria: a cross sectional study.

Science.gov (United States)

Adebayo, Philip Babatunde; Abayomi, Olukayode; Johnson, Peter O; Oloyede, Taofeeq; Oyelekan, Abimbola A A

2013-01-01

Communication skills are vital in clinical settings because the manner in which bad news is delivered could be a huge determinant of responses to such news; as well as compliance with beneficial treatment option. Information on training, institutional guidelines and protocols for breaking bad news (BBN) is scarce in Nigeria. We assessed the training, experience and perceived competence of BBN among medical personnel in southwestern Nigeria. The study was a cross-sectional descriptive study conducted out among doctors and nurses in two healthcare institutions in southwestern Nigeria using an anonymous questionnaire (adapted from the survey by Horwitz et al.), which focused on the respondents training, awareness of protocols in BBN; and perceived competence (using a Five-Point Likert Scale) in five clinical scenarios. We equally asked the respondents about an instance of BBN they have recently witnessed. A total of 113 of 130 selected (response rate 86.9%) respondents were studied. Eight (7.1%) of the respondents knew of the guidelines on BBN in the hospital in which they work. Twenty-three (20.3%) respondents claimed knowledge of a protocol. The median perceived competence rating was 4 out of 5 in all the clinical scenarios. Twenty-five (22.1%) respondents have had a formal training in BBN and they generally had significant higher perceived competence rating (P = 0.003-0.021). There is poor support from fellow workers during instances of BBN. It appears that the large proportion of the respondents in this study were unconsciously incompetent in BBN in view of the low level of training and little or no knowledge of well known protocols for BBN even though self-rated competence is high. Continuous medical education in communication skills among health personnel in Nigeria is advocated.

When Do Types Induce the Same Belief Hierarchy?

Directory of Open Access Journals (Sweden)

Andrés Perea

2016-10-01

Full Text Available Type structures are a simple device to describe higher-order beliefs. However, how can we check whether two types generate the same belief hierarchy? This paper generalizes the concept of a type morphism and shows that one type structure is contained in another if and only if the former can be mapped into the other using a generalized type morphism. Hence, every generalized type morphism is a hierarchy morphism and vice versa. Importantly, generalized type morphisms do not make reference to belief hierarchies. We use our results to characterize the conditions under which types generate the same belief hierarchy.

The Belief in Magic in the Age of Science

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Eugene Subbotsky

2014-01-01

Full Text Available The widely spread view on magical beliefs in modern industrial cultures contends that magical beliefs are a bunch of curious phenomena that persist today as an unnecessary addition to a much more important set of rational beliefs. Contrary to this view, in this article, the view is presented, which suggests that the belief in magic is a fundamental property of the human mind. Individuals can consciously consider themselves to be completely rational people and deny that they believe in magic or God despite harboring a subconscious belief in the supernatural. Research also shows how engagement in magical thinking can enhance cognitive functioning, such as creative thinking, perception and memory. Moreover, this article suggests that certain forms of social compliance and obedience to authority historically evolved from magical practices of mind control and are still powered by the implicit belief in magic. Finally, the article outlines areas of life, such as education, religion, political influence, commerce, military and political terror, and entertainment, in which magical thinking and beliefs of modern people can find practical applications.

Children's beliefs about parental divorce

OpenAIRE

Dovydaitienė, Miglė

2001-01-01

This article investigates children's beliefs about parental divorce and attitudes toward environment and people. Children's believes about parental divorce is evaluated in a sample 8 through 10-year children whose parents had been separated for about 3 years. Attitudes toward environment and people between children of separated as well as intact families are compared. We also examined the relation of children's beliefs about parental divorce and attitudes toward environment and people. The me...

Path planning in GPS-denied environments via collective intelligence of distributed sensor networks

Science.gov (United States)

Jha, Devesh K.; Chattopadhyay, Pritthi; Sarkar, Soumik; Ray, Asok

2016-05-01

This paper proposes a framework for reactive goal-directed navigation without global positioning facilities in unknown dynamic environments. A mobile sensor network is used for localising regions of interest for path planning of an autonomous mobile robot. The underlying theory is an extension of a generalised gossip algorithm that has been recently developed in a language-measure-theoretic setting. The algorithm has been used to propagate local decisions of target detection over a mobile sensor network and thus, it generates a belief map for the detected target over the network. In this setting, an autonomous mobile robot may communicate only with a few mobile sensing nodes in its own neighbourhood and localise itself relative to the communicating nodes with bounded uncertainties. The robot makes use of the knowledge based on the belief of the mobile sensors to generate a sequence of way-points, leading to a possible goal. The estimated way-points are used by a sampling-based motion planning algorithm to generate feasible trajectories for the robot. The proposed concept has been validated by numerical simulation on a mobile sensor network test-bed and a Dubin's car-like robot.

Dangerous Beliefs: College Alcohol Beliefs Are Associated With Increased Risk of Regretted Sexual Encounters.

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Osberg, Timothy M; Boyer, Amber

2016-10-14

This study explored the relative impact of college alcohol beliefs (CABs; i.e., the extent to which the student views alcohol as part of the fabric of college life), descriptive norms, injunctive norms, positive alcohol expectancies, and sensation seeking on college students' (N = 415) risk for engaging in regretted sexual encounters (RSE). Overall, 12% of our sample reported having experienced RSE within the past 30 days. When pitted against the other traditional predictors of college student drinking and its consequences, such as positive alcohol expectancies, descriptive and injunctive norms, and sensation seeking, CABs emerged as the strongest correlate of RSE other than drinking itself, and explained significant additional variance in RSE beyond these other predictors. Mediation analyses revealed that CABs had a significant indirect effect on RSE through typical weekly drinking. This pattern of findings indicates that college alcohol beliefs are, from a public health perspective, dangerous beliefs, that warrant serious consideration in the development of new approaches to college student drinking and its consequences.

Agent Communication for Dynamic Belief Update

Science.gov (United States)

Kobayashi, Mikito; Tojo, Satoshi

Thus far, various formalizations of rational / logical agent model have been proposed. In this paper, we include the notion of communication channel and belief modality into update logic, and introduce Belief Update Logic (BUL). First, we discuss that how we can reformalize the inform action of FIPA-ACL into communication channel, which represents a connection between agents. Thus, our agents can send a message only when they believe, and also there actually is, a channel between him / her and a receiver. Then, we present a static belief logic (BL) and show its soundness and completeness. Next, we develop the logic to BUL, which can update Kripke model by the inform action; in which we show that in the updated model the belief operator also satisfies K45. Thereafter, we show that every sentence in BUL can be translated into BL; thus, we can contend that BUL is also sound and complete. Furthermore, we discuss the features of CUL, including the case of inconsistent information, as well as channel transmission. Finally, we summarize our contribution and discuss some future issues.

Changing public stigma with continuum beliefs.

Science.gov (United States)

Corrigan, Patrick W; Schmidt, Annie; Bink, Andrea B; Nieweglowski, Katherine; Al-Khouja, Maya A; Qin, Sang; Discont, Steve

2017-10-01

Given the egregious effect of public stigma on the lives of people with mental illness, researchers have sought to unpack and identify effective components of anti-stigma programs. We expect to show that continuum messages have more positive effect on stigma and affirming attitudes (beliefs that people with mental illness recover and should be personally empowered) than categorical perspectives. The effect of continuum beliefs will interact with contact strategies. A total of 598 research participants were randomly assigned to online presentations representing one of the six conditions: three messages (continuum, categorical, or neutral control) by two processes (education or contact). Participants completed measures of continuum beliefs (as a manipulation check), stigma and affirming attitudes after viewing the condition. Continuum messages had significantly better effect on views that people with mental illness are "different," a finding that interacted with contact. Continuum messages also had better effects on recovery beliefs, once again an effect that interacted significantly with contact. Implications of these findings for improving anti-stigma programs are discussed.

Functional beliefs and risk minimizing beliefs among Thai healthcare workers in Maharaj Nakorn Chiang Mai hospital: its association with intention to quit tobacco and alcohol

OpenAIRE

Jiraniramai, Surin; Jiraporncharoen, Wichuda; Pinyopornpanish, Kanokporn; Jakkaew, Nalinee; Wongpakaran, Tinakon; Angkurawaranon, Chaisiri

2017-01-01

Background Individual health beliefs are likely to play a key role in how people respond to knowledge and information about the potential harm from smoking and alcohol abuse. The objectives of the study were to 1) explore whether functional beliefs and risk minimizing beliefs were associated with intention to quit smoking and confidence to quit smoking and 2) explore whether functional beliefs and risk minimizing beliefs were associated with intention to quit alcohol drinking and confidence t...

Validation of the Paranormal Health Beliefs Scale for adults.

Science.gov (United States)

Donizzetti, Anna Rosa; Petrillo, Giovanna

2017-01-01

We present the validation study of the Paranormal Health Beliefs Scale adult version, aimed to measure illusory beliefs about health. The scale was administered to 643 participants (54.3% females), having an average age of 29.7 years (standard deviation = 18.31). The results of the analyses confirmed the dimensions of the Paranormal Health Beliefs Scale as developed in the previous adolescent study (Beliefs: Religious, Superstitious, in Extraordinary Events, Parapsychological, and Pseudo-scientific of a biomedical nature), as well as the convergent and discriminant validity through the correlation with other constructs (locus of control and self-efficacy). The results also showed significant differences between subgroups by gender and age. The Paranormal Health Beliefs Scale shows satisfactory psychometric properties and thus may be used effectively to identify the varied range of illusory beliefs related to health, even within the context of lifelong educational programs aimed at health promotion.

Validation of the Paranormal Health Beliefs Scale for adults

Directory of Open Access Journals (Sweden)

Anna Rosa Donizzetti

2017-12-01

Full Text Available We present the validation study of the Paranormal Health Beliefs Scale adult version, aimed to measure illusory beliefs about health. The scale was administered to 643 participants (54.3% females, having an average age of 29.7 years (standard deviation = 18.31. The results of the analyses confirmed the dimensions of the Paranormal Health Beliefs Scale as developed in the previous adolescent study (Beliefs: Religious, Superstitious, in Extraordinary Events, Parapsychological, and Pseudo-scientific of a biomedical nature, as well as the convergent and discriminant validity through the correlation with other constructs (locus of control and self-efficacy. The results also showed significant differences between subgroups by gender and age. The Paranormal Health Beliefs Scale shows satisfactory psychometric properties and thus may be used effectively to identify the varied range of illusory beliefs related to health, even within the context of lifelong educational programs aimed at health promotion.

The extended reciprocity: Strong belief outperforms persistence.

Science.gov (United States)

Kurokawa, Shun

2017-05-21

The existence of cooperation is a mysterious phenomenon and demands explanation, and direct reciprocity is one key potential explanation for the evolution of cooperation. Direct reciprocity allows cooperation to evolve for cooperators who switch their behavior on the basis of information about the opponent's behavior. Here, relevant to direct reciprocity is information deficiency. When the opponent's last move is unknown, how should players behave? One possibility is to choose cooperation with some default probability without using any further information. In fact, our previous paper (Kurokawa, 2016a) examined this strategy. However, there might be beneficial information other than the opponent's last move. A subsequent study of ours (Kurokawa, 2017) examined the strategy which uses the own last move when the opponent's last move is unknown, and revealed that referring to the own move and trying to imitate it when information is absent is beneficial. Is there any other beneficial information else? How about strong belief (i.e., have infinite memory and believe that the opponent's behavior is unchanged)? Here, we examine the evolution of strategies with strong belief. Analyzing the repeated prisoner's dilemma game and using evolutionarily stable strategy (ESS) analysis against an invasion by unconditional defectors, we find the strategy with strong belief is more likely to evolve than the strategy which does not use information other than the opponent player's last move and more likely to evolve than the strategy which uses not only the opponent player's last move but also the own last move. Strong belief produces the extended reciprocity and facilitates the evolution of cooperation. Additionally, we consider the two strategies game between strategies with strong belief and any strategy, and we consider the four strategies game in which unconditional cooperators, unconditional defectors, pessimistic reciprocators with strong belief, and optimistic reciprocators with

Constraining axion dark matter with Big Bang Nucleosynthesis

Energy Technology Data Exchange (ETDEWEB)

Blum, Kfir; D' Agnolo, Raffaele Tito [Institute for Advanced Study, Princeton, NJ 08540 (United States); Lisanti, Mariangela; Safdi, Benjamin R. [Department of Physics, Princeton University, Princeton, NJ 08544 (United States)

2014-10-07

We show that Big Bang Nucleosynthesis (BBN) significantly constrains axion-like dark matter. The axion acts like an oscillating QCD θ angle that redshifts in the early Universe, increasing the neutron–proton mass difference at neutron freeze-out. An axion-like particle that couples too strongly to QCD results in the underproduction of {sup 4}He during BBN and is thus excluded. The BBN bound overlaps with much of the parameter space that would be covered by proposed searches for a time-varying neutron EDM. The QCD axion does not couple strongly enough to affect BBN.

Constraining axion dark matter with Big Bang Nucleosynthesis

Directory of Open Access Journals (Sweden)

Kfir Blum

2014-10-01

Full Text Available We show that Big Bang Nucleosynthesis (BBN significantly constrains axion-like dark matter. The axion acts like an oscillating QCD θ angle that redshifts in the early Universe, increasing the neutron–proton mass difference at neutron freeze-out. An axion-like particle that couples too strongly to QCD results in the underproduction of He4 during BBN and is thus excluded. The BBN bound overlaps with much of the parameter space that would be covered by proposed searches for a time-varying neutron EDM. The QCD axion does not couple strongly enough to affect BBN.

Academic Optimism: An Individual Teacher Belief

Science.gov (United States)

Ngidi, David P.

2012-01-01

In this study, academic optimism as an individual teacher belief was investigated. Teachers' self-efficacy beliefs were measured using the short form of the Teacher Sense of Efficacy Scale. One subtest from the Omnibus T-Scale, the faculty trust in clients subtest, was used to measure teachers' trust in students and parents. One subtest from the…

Plural religious beliefs: A Comparison between the Dutch and white ...

African Journals Online (AJOL)

The concept of religious beliefs is distilled from the perspective of one's belief in God. With regard to this belief in God we propose to distinguish between two dimensions: The personal versus the a-personal character of God and his transcendent versus his immanent nature. This leaves us with a plurality of beliefs in God.

On revision of partially specified convex probabilistic belief bases

CSIR Research Space (South Africa)

Rens, G

2016-08-01

Full Text Available We propose a method for an agent to revise its incomplete probabilistic beliefs when a new piece of propositional information is observed. In this work, an agent’s beliefs are represented by a set of probabilistic formulae – a belief base...

Can Legal Interventions Change Beliefs? The Effect of Exposure to Sexual Harassment Policy on Men's Gender Beliefs

Science.gov (United States)

Tinkler, Justine Eatenson; Li, Yan E.; Mollborn, Stefanie

2007-01-01

In spite of the relative success of equal opportunity laws on women's status in the workplace, we know little about the influence of such legal interventions on people's attitudes and beliefs. This paper focuses, in particular, on how sexual harassment policy affects men's beliefs about the gender hierarchy. We employ an experimental design in…

Life satisfaction and beliefs about self and the world in patients with psoriasis: a brief assessment.

Science.gov (United States)

Solovan, Caius; Marcu, Mirona; Chiticariu, Elena

2014-01-01

Psoriasis is a chronic skin condition that can decrease the level of self-esteem, leading to self-devaluation, emotional distress, irrational beliefs and discomfort in everyday life. In this study, we aimed to provide a deeper understanding of lifestyle satisfaction and to identify the nature and magnitude of irrational beliefs in patients with psoriasis. A two-year case-control study was carried out between 2010 and 2012. The study enrolled 100 consecutive patients with psoriasis vulgaris, admitted to a dermatology clinic and 101 healthy volunteers with similar demographic characteristics, willing to subject themselves to the testing. A series of standardized questionnaires were used, including: The Anamnestic Questionnaire, The General Attitudes and Beliefs Scale - Short version, The Rosenberg Self-Esteem Scale, The Self-Efficacy Scale and The Unconditional Self-Acceptance Questionnaire. The tests revealed a strong correlation between the presence of the disease and the decrease of subject's satisfaction regarding: body satisfaction, sexual satisfaction, social satisfaction, family satisfaction, professional satisfaction and satisfaction concerning their own health condition; p 0.35). The focus on psychological impacts of the disease provides important data for a holistic approach to patients with psoriasis. Effective cooperation between all the parties involved (physicians, family and social network) is necessary to improve the patient's psychological status.

Eating disorder beliefs and behaviours across eating disorder diagnoses.

Science.gov (United States)

Allan, Steven; Goss, Ken

2014-01-01

To test for differences between diagnostic groups on the severity of eating disorder beliefs and behaviours, evaluate the clinical significance of such differences, and assess the extent to which these beliefs and behaviours may be present at clinically significant levels across eating disorder diagnoses. 136 adult women outpatients (aged 18-65, with a BMI over 15) were diagnosed with an eating disorder and completed the Stirling Eating Disorder Scale. The expected pattern of statistically significant differences was found between diagnostic groups on anorexic dietary beliefs and behaviours and bulimic dietary beliefs and behaviours. A high percentage of participants in each diagnostic group scored above the clinical cut-off on the eating disorder belief and behaviour measures and a very high percentage of participants in each group reported clinically significant levels of restricting beliefs. Transdiagnostic or functional analytic approaches to treatment planning may lead to more effective interventions than current, diagnostically-based, care pathways. The high prevalence of restricting beliefs reported suggested that this may need to be a key focus for intervention for the majority of individuals presenting with an eating disorder. © 2013.

The Role of Science Teachers' Beliefs in International Classrooms

DEFF Research Database (Denmark)

for educators. Within each of these areas there are specific explorations that examine important areas such as, the roles of beliefs in teaching and learning, the impact of beliefs on student achievement, and ways in which beliefs are connected to teacher actions in the classroom. Throughout all...... of these discussions, there is a focus on international perspectives. Those reading this book can use the research presented to consider how to confront, challenge, and cultivate beliefs during the teacher professional development process....

relationship between patients' beliefs about their antihypertensives ...

African Journals Online (AJOL)

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effects of their medication, suggesting a high counter-balancing effect of this belief on their ... patients have positive belief regarding the efficacy of their ... Divorced. Widow. 11. 100. 5. 11. 9. 79. 4. 8. Religion. Muslim. Christian. 108. 19. 85. 15.

Relationships between beliefs about medications and nonadherence to prescribed chronic medications.

Science.gov (United States)

Phatak, Hemant M; Thomas, Joseph

2006-10-01

Medication beliefs of patients with a specific medical condition have been associated with nonadherence to drugs used to treat that condition. However, associations between medication beliefs and nonadherence of individuals on chronic, multiple medications have not been studied. To investigate associations between patients' medication beliefs and nonadherence to chronic drug therapy. A cross-sectional, self-administered survey of patients waiting to see pharmacists at an outpatient pharmacy in a primary care clinic was conducted. Participants' medication beliefs were assessed using the Beliefs about Medicines Questionnaire, and nonadherence was assessed using the Morisky Medication Adherence Scale. Pearson correlation analysis was used to assess bivariate associations between medication beliefs and nonadherence. Regression was used to assess relative strength of associations between various medication beliefs and nonadherence and also to assess the significance of the interactions between those beliefs and nonadherence. There were positive bivariate associations between specific concerns about medications (p harmful effects of medications (p belief and nonadherence was assessed, while controlling for other medication beliefs, specific-necessity (p = 0.02) and specific-concerns (p = 0.01) exhibited significant negative and positive associations with nonadherence, respectively. All two-way interactions between variables in the model were insignificant. A model consisting of age, total number of drugs used, and medication beliefs, that is, specific-necessity, specific-concerns, general-overuse, and general-harm, accounted for 26.5% of variance. Medication beliefs alone explained 22.4% of variation in nonadherence to chronic drug therapy. Patients' medication beliefs explained a significant portion of variation in medication nonadherence.

Childhood physical abuse and differential development of paranormal belief systems.

Science.gov (United States)

Perkins, Stefanie L; Allen, Rhiannon

2006-05-01

This study compared paranormal belief systems in individuals with and without childhood physical abuse histories. The Revised Paranormal Belief Scale and the Assessing Environments III Questionnaire were completed by 107 University students. Psi, precognition, and spiritualism, which are thought to provide a sense of personal efficacy and control, were among the most strongly held beliefs in abused subjects, and were significantly higher in abused versus nonabused subjects. Superstition and extraordinary life forms, thought to have an inverse or no relation to felt control, were the least strongly held beliefs in abused subjects, and, along with religious beliefs, did not differ between the two abuse groups. Witchcraft was unexpectedly found to be the most strongly held belief among those with abuse histories. Results suggest that by providing a sense of control, certain paranormal beliefs may offer a powerful emotional refuge to individuals who endured the stress of physical abuse in childhood.

Probability misjudgment, cognitive ability, and belief in the paranormal.

Science.gov (United States)

Musch, Jochen; Ehrenberg, Katja

2002-05-01

According to the probability misjudgment account of paranormal belief (Blackmore & Troscianko, 1985), believers in the paranormal tend to wrongly attribute remarkable coincidences to paranormal causes rather than chance. Previous studies have shown that belief in the paranormal is indeed positively related to error rates in probabilistic reasoning. General cognitive ability could account for a relationship between these two variables without assuming a causal role of probabilistic reasoning in the forming of paranormal beliefs, however. To test this alternative explanation, a belief in the paranormal scale (BPS) and a battery of probabilistic reasoning tasks were administered to 123 university students. Confirming previous findings, a significant correlation between BPS scores and error rates in probabilistic reasoning was observed. This relationship disappeared, however, when cognitive ability as measured by final examination grades was controlled for. Lower cognitive ability correlated substantially with belief in the paranormal. This finding suggests that differences in general cognitive performance rather than specific probabilistic reasoning skills provide the basis for paranormal beliefs.

Early false-belief understanding in traditional non-Western societies.

Science.gov (United States)

Barrett, H Clark; Broesch, Tanya; Scott, Rose M; He, Zijing; Baillargeon, Renée; Wu, Di; Bolz, Matthias; Henrich, Joseph; Setoh, Peipei; Wang, Jianxin; Laurence, Stephen

2013-03-22

The psychological capacity to recognize that others may hold and act on false beliefs has been proposed to reflect an evolved, species-typical adaptation for social reasoning in humans; however, controversy surrounds the developmental timing and universality of this trait. Cross-cultural studies using elicited-response tasks indicate that the age at which children begin to understand false beliefs ranges from 4 to 7 years across societies, whereas studies using spontaneous-response tasks with Western children indicate that false-belief understanding emerges much earlier, consistent with the hypothesis that false-belief understanding is a psychological adaptation that is universally present in early childhood. To evaluate this hypothesis, we used three spontaneous-response tasks that have revealed early false-belief understanding in the West to test young children in three traditional, non-Western societies: Salar (China), Shuar/Colono (Ecuador) and Yasawan (Fiji). Results were comparable with those from the West, supporting the hypothesis that false-belief understanding reflects an adaptation that is universally present early in development.

The Mathematical Development Beliefs Survey: Validity and Reliability of a Measure of Preschool Teachers' Beliefs about the Learning and Teaching of Early Mathematics

Science.gov (United States)

Platas, Linda M.

2015-01-01

The Mathematical Development Beliefs Survey was developed to measure early childhood teachers' beliefs about mathematics teaching and learning in the preschool classroom. This instrument was designed to measure beliefs concerning (a) age-appropriateness of mathematics instruction, (b) classroom locus of generation of mathematical knowledge…

Belief Revision in the GOAL Agent Programming Language

DEFF Research Database (Denmark)

Spurkeland, Johannes Svante; Jensen, Andreas Schmidt; Villadsen, Jørgen

2013-01-01

Agents in a multiagent system may in many cases find themselves in situations where inconsistencies arise. In order to properly deal with these, a good belief revision procedure is required. This paper illustrates the usefulness of such a procedure: a certain belief revision algorithm is consider...... in order to deal with inconsistencies and, particularly, the issue of inconsistencies, and belief revision is examined in relation to the GOAL agent programming language....

Internal evaluation of the European network for health technology assessment project.

Science.gov (United States)

Håheim, Lise Lund; Imaz, Iñaki; Loud, Marlène Läubli; Gasparetto, Teresa; González-Enriquez, Jesús; Dahlgren, Helena; Trofimovs, Igor; Berti, Elena; Mørland, Berit

2009-12-01

The internal evaluation studied the development of the European network for Health Technology Assessment (EUnetHTA) Project in achieving the general objective of establishing an effective and a sustainable network of health technology assessment (HTA) in Europe. The Work Package 3 group was dedicated to this task and performed the work. Information on activities during the project was collected from three sources. First, three yearly cross-sectional studies surveyed the participants' opinions. Responses were by individuals or by institutions. The last round included surveys to the Steering Committee, the Stakeholder Forum, and the Secretariat. Second, the Work Package Lead Partners were interviewed bi-annually, five times in total, to update the information on the Project's progress. Third, additional information was sought in available documents. The organizational structure remained stable. The Project succeeded in developing tools aimed at providing common methodology with intent to establish a standard of conducting and reporting HTA and to facilitate greater collaboration among agencies. The participants/agencies expressed their belief in a network and in maintaining local/national autonomy. The Work Package Leaders expressed a strong belief in the solid base of the Project for a future network on which to build, but were aware of the need for funding and governmental support. Participants and Work Package Leaders have expressed support for a future network that will improve national and international collaboration in HTA based on the experience from the EUnetHTA project.

A new approach to probabilistic belief change

CSIR Research Space (South Africa)

Rens, G

2015-05-01

Full Text Available One way for an agent to deal with uncertainty about its beliefs is to maintain a probability distribution over the worlds it believes are possible. A belief change operation may recommend some previously believed worlds to become impossible and some...

Lay belief in biopolitics and political prejudice

NARCIS (Netherlands)

Suhay, E; Brandt, M.J.; Proulx, T.

2017-01-01

Building on psychological research linking essentialist beliefs about human differences with prejudice, we test whether lay belief in the biological basis of political ideology is associated with political intolerance and social avoidance. In two studies of American adults (Study 1: N = 288, Study

Pluto behaving badly: false beliefs and their consequences.

Science.gov (United States)

Berkowitz, Shari R; Laney, Cara; Morris, Erin K; Garry, Maryanne; Loftus, Elizabeth F

2008-01-01

We exposed college students to suggestive materials in order to lead them to believe that, as children, they had a negative experience at Disneyland involving the Pluto character. A sizable minority of subjects developed a false belief or memory that Pluto had uncomfortably licked their ear. Suggestions about a positive experience with Pluto led to even greater acceptance of a lovable ear-licking episode. False beliefs and memories had repercussions; those seduced by the bad suggestions were not willing to pay as much for a Pluto souvenir. These findings are among the first to demonstrate that false beliefs can have repercussions for people, meaning that they can influence their later thoughts, beliefs, and behaviors.

Selectively altering belief formation in the human brain

Science.gov (United States)

Sharot, Tali; Kanai, Ryota; Marston, David; Korn, Christoph W.; Rees, Geraint; Dolan, Raymond J.

2012-01-01

Humans form beliefs asymmetrically; we tend to discount bad news but embrace good news. This reduced impact of unfavorable information on belief updating may have important societal implications, including the generation of financial market bubbles, ill preparedness in the face of natural disasters, and overly aggressive medical decisions. Here, we selectively improved people’s tendency to incorporate bad news into their beliefs by disrupting the function of the left (but not right) inferior frontal gyrus using transcranial magnetic stimulation, thereby eliminating the engrained “good news/bad news effect.” Our results provide an instance of how selective disruption of regional human brain function paradoxically enhances the ability to incorporate unfavorable information into beliefs of vulnerability. PMID:23011798