"As soon as the bat met the ball, I knew it was gone": outcome prediction, hindsight bias, and the representation and control of action in expert and novice baseball players.

PubMed

Gray, Rob; Beilock, Sun L; Carr, Thomas H

2007-08-01

A virtual-reality batting task compared novice and expert baseball players' ability to predict the outcomes of their swings as well as the susceptibility of these outcome predictions to hindsight bias--a measure of strength and resistance to distortion of memory for predicted action outcomes. During each swing the simulation stopped when the bat met the ball. Batters marked where on the field they thought the ball would land. Correct feedback was then displayed, after which batters attempted to remark the location they had indicated prior to feedback. Expert batters were more accurate than less-skilled individuals in the initial marking and showed less hindsight bias in the postfeedback marking. Furthermore, experts' number of hits in the previous block of trials was positively correlated with prediction accuracy and negatively correlated with hindsight bias. The reverse was true for novices. Thus the ability to predict the outcome of one's performance before such information is available in the environment is not only based on one's overall skill level, but how one is performing at a given moment.

The nutrition advisor expert system

NASA Technical Reports Server (NTRS)

Huse, Scott M.; Shyne, Scott S.

1991-01-01

The Nutrition Advisor Expert System (NAES) is an expert system written in the C Language Integrated Production System (CLIPS). NAES provides expert knowledge and guidance into the complex world of nutrition management by capturing the knowledge of an expert and placing it at the user's fingertips. Specifically, NAES enables the user to: (1) obtain precise nutrition information for food items; (2) perform nutritional analysis of meal(s), flagging deficiencies based upon the U.S. Recommended Daily Allowances; (3) predict possible ailments based upon observed nutritional deficiency trends; (4) obtain a top ten listing of food items for a given nutrient; and (5) conveniently upgrade the data base. An explanation facility for the ailment prediction feature is also provided to document the reasoning process.

What do the experts know? Calibration, precision, and the wisdom of crowds among forensic handwriting experts.

PubMed

Martire, Kristy A; Growns, Bethany; Navarro, Danielle J

2018-04-17

Forensic handwriting examiners currently testify to the origin of questioned handwriting for legal purposes. However, forensic scientists are increasingly being encouraged to assign probabilities to their observations in the form of a likelihood ratio. This study is the first to examine whether handwriting experts are able to estimate the frequency of US handwriting features more accurately than novices. The results indicate that the absolute error for experts was lower than novices, but the size of the effect is modest, and the overall error rate even for experts is large enough as to raise questions about whether their estimates can be sufficiently trustworthy for presentation in courts. When errors are separated into effects caused by miscalibration and those caused by imprecision, we find systematic differences between individuals. Finally, we consider several ways of aggregating predictions from multiple experts, suggesting that quite substantial improvements in expert predictions are possible when a suitable aggregation method is used.

Computer Based Expert Systems.

ERIC Educational Resources Information Center

Parry, James D.; Ferrara, Joseph M.

1985-01-01

Claims knowledge-based expert computer systems can meet needs of rural schools for affordable expert advice and support and will play an important role in the future of rural education. Describes potential applications in prediction, interpretation, diagnosis, remediation, planning, monitoring, and instruction. (NEC)

Predicting disease progression from short biomarker series using expert advice algorithm

NASA Astrophysics Data System (ADS)

Morino, Kai; Hirata, Yoshito; Tomioka, Ryota; Kashima, Hisashi; Yamanishi, Kenji; Hayashi, Norihiro; Egawa, Shin; Aihara, Kazuyuki

2015-05-01

Well-trained clinicians may be able to provide diagnosis and prognosis from very short biomarker series using information and experience gained from previous patients. Although mathematical methods can potentially help clinicians to predict the progression of diseases, there is no method so far that estimates the patient state from very short time-series of a biomarker for making diagnosis and/or prognosis by employing the information of previous patients. Here, we propose a mathematical framework for integrating other patients' datasets to infer and predict the state of the disease in the current patient based on their short history. We extend a machine-learning framework of ``prediction with expert advice'' to deal with unstable dynamics. We construct this mathematical framework by combining expert advice with a mathematical model of prostate cancer. Our model predicted well the individual biomarker series of patients with prostate cancer that are used as clinical samples.

Predicting disease progression from short biomarker series using expert advice algorithm.

PubMed

Morino, Kai; Hirata, Yoshito; Tomioka, Ryota; Kashima, Hisashi; Yamanishi, Kenji; Hayashi, Norihiro; Egawa, Shin; Aihara, Kazuyuki

2015-05-20

Well-trained clinicians may be able to provide diagnosis and prognosis from very short biomarker series using information and experience gained from previous patients. Although mathematical methods can potentially help clinicians to predict the progression of diseases, there is no method so far that estimates the patient state from very short time-series of a biomarker for making diagnosis and/or prognosis by employing the information of previous patients. Here, we propose a mathematical framework for integrating other patients' datasets to infer and predict the state of the disease in the current patient based on their short history. We extend a machine-learning framework of "prediction with expert advice" to deal with unstable dynamics. We construct this mathematical framework by combining expert advice with a mathematical model of prostate cancer. Our model predicted well the individual biomarker series of patients with prostate cancer that are used as clinical samples.

An evaluation of selected (Q)SARs/expert systems for predicting skin sensitisation potential.

PubMed

Fitzpatrick, J M; Roberts, D W; Patlewicz, G

2018-06-01

Predictive testing to characterise substances for their skin sensitisation potential has historically been based on animal models such as the Local Lymph Node Assay (LLNA) and the Guinea Pig Maximisation Test (GPMT). In recent years, EU regulations, have provided a strong incentive to develop non-animal alternatives, such as expert systems software. Here we selected three different types of expert systems: VEGA (statistical), Derek Nexus (knowledge-based) and TIMES-SS (hybrid), and evaluated their performance using two large sets of animal data: one set of 1249 substances from eChemportal and a second set of 515 substances from NICEATM. A model was considered successful at predicting skin sensitisation potential if it had at least the same balanced accuracy as the LLNA and the GPMT had in predicting the other outcomes, which ranged from 79% to 86%. We found that the highest balanced accuracy of any of the expert systems evaluated was 65% when making global predictions. For substances within the domain of TIMES-SS, however, balanced accuracies for the two datasets were found to be 79% and 82%. In those cases where a chemical was within the TIMES-SS domain, the TIMES-SS skin sensitisation hazard prediction had the same confidence as the result from LLNA or GPMT.

Estimating community health needs against a Triple Aim background: What can we learn from current predictive risk models?

PubMed

Elissen, Arianne M J; Struijs, Jeroen N; Baan, Caroline A; Ruwaard, Dirk

2015-05-01

To support providers and commissioners in accurately assessing their local populations' health needs, this study produces an overview of Dutch predictive risk models for health care, focusing specifically on the type, combination and relevance of included determinants for achieving the Triple Aim (improved health, better care experience, and lower costs). We conducted a mixed-methods study combining document analyses, interviews and a Delphi study. Predictive risk models were identified based on a web search and expert input. Participating in the study were Dutch experts in predictive risk modelling (interviews; n=11) and experts in healthcare delivery, insurance and/or funding methodology (Delphi panel; n=15). Ten predictive risk models were analysed, comprising 17 unique determinants. Twelve were considered relevant by experts for estimating community health needs. Although some compositional similarities were identified between models, the combination and operationalisation of determinants varied considerably. Existing predictive risk models provide a good starting point, but optimally balancing resources and targeting interventions on the community level will likely require a more holistic approach to health needs assessment. Development of additional determinants, such as measures of people's lifestyle and social network, may require policies pushing the integration of routine data from different (healthcare) sources. Copyright © 2014 Elsevier Ireland Ltd. All rights reserved.

Deep nets vs expert designed features in medical physics: An IMRT QA case study.

PubMed

Interian, Yannet; Rideout, Vincent; Kearney, Vasant P; Gennatas, Efstathios; Morin, Olivier; Cheung, Joey; Solberg, Timothy; Valdes, Gilmer

2018-03-30

The purpose of this study was to compare the performance of Deep Neural Networks against a technique designed by domain experts in the prediction of gamma passing rates for Intensity Modulated Radiation Therapy Quality Assurance (IMRT QA). A total of 498 IMRT plans across all treatment sites were planned in Eclipse version 11 and delivered using a dynamic sliding window technique on Clinac iX or TrueBeam Linacs. Measurements were performed using a commercial 2D diode array, and passing rates for 3%/3 mm local dose/distance-to-agreement (DTA) were recorded. Separately, fluence maps calculated for each plan were used as inputs to a convolution neural network (CNN). The CNNs were trained to predict IMRT QA gamma passing rates using TensorFlow and Keras. A set of model architectures, inspired by the convolutional blocks of the VGG-16 ImageNet model, were constructed and implemented. Synthetic data, created by rotating and translating the fluence maps during training, was created to boost the performance of the CNNs. Dropout, batch normalization, and data augmentation were utilized to help train the model. The performance of the CNNs was compared to a generalized Poisson regression model, previously developed for this application, which used 78 expert designed features. Deep Neural Networks without domain knowledge achieved comparable performance to a baseline system designed by domain experts in the prediction of 3%/3 mm Local gamma passing rates. An ensemble of neural nets resulted in a mean absolute error (MAE) of 0.70 ± 0.05 and the domain expert model resulted in a 0.74 ± 0.06. Convolutional neural networks (CNNs) with transfer learning can predict IMRT QA passing rates by automatically designing features from the fluence maps without human expert supervision. Predictions from CNNs are comparable to a system carefully designed by physicist experts. © 2018 American Association of Physicists in Medicine.

Expert Consensus on the Management of Patients with Postmenopausal Osteoporosis in the Spanish Healthcare System.

PubMed

Del Pino-Montes, Javier; Blanch, Josep; Nogués, Xavier; Moro, María Jesús; Valero, María Del Carmen; Canals, Laura; Lizán, Luis

2016-04-01

The management of postmenopausal osteoporosis (PMO) in routine clinical practice differs considerably from guideline recommendations. The objective of our study was to reach a consensus on the management of PMO, considering prevention, diagnosis, treatment and follow-up, according to expert opinion in Spain. A two-round Delphi technique was conducted, including 38 experts. The questionnaire contained 35 sections, each one including 1-10 questions (n = 308) based on a literature review and contributions from the scientific steering committee. Each question was scored by experts from the current (1 = no occurrence, 9 = occurrence in all cases), wish (1 = total rejection; 9 = wish) and prediction (1 = no occurrence at all; 9 = occurs with maximum probability) perspectives. Consensus (wish and prediction perspectives) was considered when ≥75% of experts scored 7-9 (agreement) or 1-3 (disagreement). Overall, consensus was achieved on 75% of questions. While protocols of clinical management and consultation/referral should be followed, their implementation is unlikely. Furthermore, the medical specialties currently involved in PMO management are poorly defined. PMO patients without fracture should be managed (prevention, diagnosis, treatment and follow-up) in both primary care and rheumatology settings; however, experts predicted that only treatment and follow-up will be assumed by these specialties. A multidisciplinary team should be involved in patients with fracture. No assessment tools are usually applied, and prediction indicated that they will not be used. Efforts should be focused on questions with high divergence between wishes and predictions, defining actions that will improve PMO management. Collaboration between scientific societies and health authorities to address the identified opportunities of improvement is proposed. Amgen S.A.

Effect on dynamic mechanical stability and interfragmentary movement of angle-stable locking of intramedullary nails in unstable distal tibia fractures: a biomechanical study.

PubMed

Gueorguiev, Boyko; Wähnert, Dirk; Albrecht, Daniel; Ockert, Ben; Windolf, Markus; Schwieger, Karsten

2011-02-01

Unstable distal tibia fractures are challenging injuries that require surgery. Increasingly, intramedullary nails are being used. However, fracture site anatomy may cause distal-fragment stabilization and fixation problems and lead to malunion/nonunion. We studied the influence of angle-stable nail locking on fracture gap movement and other biomechanical parameters. Eight pairs of fresh human cadaver tibiae were used. The bone mineral density (BMD) was determined. All tibiae were nailed with a Synthes Expert tibial nail. Within each pair, one tibia was randomized to receive conventional locking screws; the other, angle-stable screws with sleeves. A 7-mm osteotomy was created 10 mm above the upper distal locking screw, to simulate an AO 42-A3 fracture. Biomechanical testing involved nondestructive mediolateral and anteroposterior pure bending, followed by cyclic combined axial and torsional loading to catastrophic failure. The neutral zone was determined. Fracture gap movement was monitored with 3-D motion tracking. The angle-stable locked constructs had a significantly smaller mediolateral neutral zone (mean: 0.04 degree; p=0.039) and significantly smaller fracture gap angulation (p=0.043). The number of cycles to failure did not differ significantly between the locking configurations. BMD was a significant covariate affecting the number of cycles to failure (p=0.008). However, over the first 20,000 cycles, there was no significant correlation in the angle-stable construct. Angle-stable locking of the Expert tibial nail was associated with a significant reduction in the mediolateral neutral zone and in fracture gap movement. Angle-stable fixation also reduced the influence of BMD over the first 20,000 cycles.

Artificial Intelligence and Expert Systems

DTIC Science & Technology

1986-03-01

O R R E C T I N G • NOT P R O T E C T E D oEMOTION oFATIGUE oUNAVAILABLE oBIAS olMPERIAL • STABLE (COLD) o lNDEFAT IGABLE eAVAILABLE eLESS... oBIAS olMPERIAL • STABLE (COLD) o lNDEFAT IGABLE eAVAILABLE oLESS BIAS o lMPERSONAL DODCI 1085-.85 THE COMPUTER EVOLUTION I I I • C o m p

Shaping beliefs in experimental markets for expert services: Guilt aversion and the impact of promises and money-burning options.

PubMed

Beck, Adrian; Kerschbamer, Rudolf; Qiu, Jianying; Sutter, Matthias

2013-09-01

In a credence goods game with an expert and a consumer, we study experimentally the impact of two devices that are predicted to induce consumer-friendly behavior if the expert has a propensity to feel guilty when he believes that he violates the consumer's payoff expectations: (i) an opportunity for the expert to make a non-binding promise; and (ii) an opportunity for the consumer to burn money. In belief-based guilt aversion theory the first opportunity shapes an expert's behavior if an appropriate promise is made and if it is expected to be believed by the consumer; by contrast, the second opportunity might change behavior even though this option is never used along the predicted path. Experimental results confirm the behavioral relevance of (i) but fail to confirm (ii).

Pedophilia: an evaluation of diagnostic and risk prediction methods.

PubMed

Wilson, Robin J; Abracen, Jeffrey; Looman, Jan; Picheca, Janice E; Ferguson, Meaghan

2011-06-01

One hundred thirty child sexual abusers were diagnosed using each of following four methods: (a) phallometric testing, (b) strict application of Diagnostic and Statistical Manual of Mental Disorders (4th ed., text revision [DSM-IV-TR]) criteria, (c) Rapid Risk Assessment of Sex Offender Recidivism (RRASOR) scores, and (d) "expert" diagnoses rendered by a seasoned clinician. Comparative utility and intermethod consistency of these methods are reported, along with recidivism data indicating predictive validity for risk management. Results suggest that inconsistency exists in diagnosing pedophilia, leading to diminished accuracy in risk assessment. Although the RRASOR and DSM-IV-TR methods were significantly correlated with expert ratings, RRASOR and DSM-IV-TR were unrelated to each other. Deviant arousal was not associated with any of the other methods. Only the expert ratings and RRASOR scores were predictive of sexual recidivism. Logistic regression analyses showed that expert diagnosis did not add to prediction of sexual offence recidivism over and above RRASOR alone. Findings are discussed within a context of encouragement of clinical consistency and evidence-based practice regarding treatment and risk management of those who sexually abuse children.

SeTES, a Self-Teaching Expert System for the analysis, design and prediction of gas production from shales and a prototype for a new generation of Expert Systems in the Earth Sciences

NASA Astrophysics Data System (ADS)

Kuzma, H. A.; Boyle, K.; Pullman, S.; Reagan, M. T.; Moridis, G. J.; Blasingame, T. A.; Rector, J. W.; Nikolaou, M.

2010-12-01

A Self Teaching Expert System (SeTES) is being developed for the analysis, design and prediction of gas production from shales. An Expert System is a computer program designed to answer questions or clarify uncertainties that its designers did not necessarily envision which would otherwise have to be addressed by consultation with one or more human experts. Modern developments in computer learning, data mining, database management, web integration and cheap computing power are bringing the promise of expert systems to fruition. SeTES is a partial successor to Prospector, a system to aid in the identification and evaluation of mineral deposits developed by Stanford University and the USGS in the late 1970s, and one of the most famous early expert systems. Instead of the text dialogue used in early systems, the web user interface of SeTES helps a non-expert user to articulate, clarify and reason about a problem by navigating through a series of interactive wizards. The wizards identify potential solutions to queries by retrieving and combining together relevant records from a database. Inferences, decisions and predictions are made from incomplete and noisy inputs using a series of probabilistic models (Bayesian Networks) which incorporate records from the database, physical laws and empirical knowledge in the form of prior probability distributions. The database is mainly populated with empirical measurements, however an automatic algorithm supplements sparse data with synthetic data obtained through physical modeling. This constitutes the mechanism for how SeTES self-teaches. SeTES’ predictive power is expected to grow as users contribute more data into the system. Samples are appropriately weighted to favor high quality empirical data over low quality or synthetic data. Finally, a set of data visualization tools digests the output measurements into graphical outputs.

Can human experts predict solubility better than computers?

PubMed

Boobier, Samuel; Osbourn, Anne; Mitchell, John B O

2017-12-13

In this study, we design and carry out a survey, asking human experts to predict the aqueous solubility of druglike organic compounds. We investigate whether these experts, drawn largely from the pharmaceutical industry and academia, can match or exceed the predictive power of algorithms. Alongside this, we implement 10 typical machine learning algorithms on the same dataset. The best algorithm, a variety of neural network known as a multi-layer perceptron, gave an RMSE of 0.985 log S units and an R 2 of 0.706. We would not have predicted the relative success of this particular algorithm in advance. We found that the best individual human predictor generated an almost identical prediction quality with an RMSE of 0.942 log S units and an R 2 of 0.723. The collection of algorithms contained a higher proportion of reasonably good predictors, nine out of ten compared with around half of the humans. We found that, for either humans or algorithms, combining individual predictions into a consensus predictor by taking their median generated excellent predictivity. While our consensus human predictor achieved very slightly better headline figures on various statistical measures, the difference between it and the consensus machine learning predictor was both small and statistically insignificant. We conclude that human experts can predict the aqueous solubility of druglike molecules essentially equally well as machine learning algorithms. We find that, for either humans or algorithms, combining individual predictions into a consensus predictor by taking their median is a powerful way of benefitting from the wisdom of crowds.

"A Prophecy for the Arts" in Higher Education

ERIC Educational Resources Information Center

Merrion, Margaret

2009-01-01

This article presents a Delphi study that captured a myriad of predictions that represent the best thinking of a panel of creative minds, experts in a variety of arts and with many years of experience as arts leaders. Predictions provide a set of interlinked challenges and opportunities. In this study, the experts forecast changes in students that…

Business aspects and sustainability for healthgrids - an expert survey.

PubMed

Scholz, Stefan; Semler, Sebastian C; Breitner, Michael H

2009-01-01

Grid computing initiatives in medicine and life sciences are under pressure to prove their sustainability. While some first business model frameworks were outlined, few practical experiences were considered. This gap has been narrowed by an international survey of 33 grid computing experts with biomedical and non-biomedical background on business aspects. The experts surveyed were cautiously optimistic about a sustainable implementation of grid computing within a mid term timeline. They identified marketable application areas, stated the underlying value proposition, outlined trends and specify critical success factors. From a general perspective of their answers, they provided a stable basis for a road map of sustainable grid computing solutions for medicine and life sciences.

Take-the-best in expert-novice decision strategies for residential burglary.

PubMed

Garcia-Retamero, Rocio; Dhami, Mandeep K

2009-02-01

We examined the decision strategies and cue use of experts and novices in a consequential domain: crime. Three participant groups decided which of two residential properties was more likely to be burgled, on the basis of eight cues such as location of the property. The two expert groups were experienced burglars and police officers, and the novice group was composed of graduate students. We found that experts' choices were best predicted by a lexicographic heuristic strategy called take-the-best that implies noncompensatory information processing, whereas novices' choices were best predicted by a weighted additive linear strategy that implies compensatory processing. The two expert groups, however, differed in the cues they considered important in making their choices, and the police officers were actually more similar to novices in this regard. These findings extend the literature on judgment, decision making, and expertise, and have implications for criminal justice policy.

Fuzzy logic based expert system for the treatment of mobile tooth.

PubMed

Mago, Vijay Kumar; Mago, Anjali; Sharma, Poonam; Mago, Jagmohan

2011-01-01

The aim of this research work is to design an expert system to assist dentist in treating the mobile tooth. There is lack of consistency among dentists in choosing the treatment plan. Moreover, there is no expert system currently available to verify and support such decision making in dentistry. A Fuzzy Logic based expert system has been designed to accept imprecise and vague values of dental sign-symptoms related to mobile tooth and the system suggests treatment plan(s). The comparison of predictions made by the system with those of the dentist is conducted. Chi-square Test of homogeneity is conducted and it is found that the system is capable of predicting accurate results. With this system, dentist feels more confident while planning the treatment of mobile tooth as he can verify his decision with the expert system. The authors also argue that Fuzzy Logic provides an appropriate mechanism to handle imprecise values of dental domain.

Shaping beliefs in experimental markets for expert services: Guilt aversion and the impact of promises and money-burning options☆☆☆

PubMed Central

Beck, Adrian; Kerschbamer, Rudolf; Qiu, Jianying; Sutter, Matthias

2013-01-01

In a credence goods game with an expert and a consumer, we study experimentally the impact of two devices that are predicted to induce consumer-friendly behavior if the expert has a propensity to feel guilty when he believes that he violates the consumerʼs payoff expectations: (i) an opportunity for the expert to make a non-binding promise; and (ii) an opportunity for the consumer to burn money. In belief-based guilt aversion theory the first opportunity shapes an expertʼs behavior if an appropriate promise is made and if it is expected to be believed by the consumer; by contrast, the second opportunity might change behavior even though this option is never used along the predicted path. Experimental results confirm the behavioral relevance of (i) but fail to confirm (ii). PMID:24003266

An expert system based software sizing tool, phase 2

NASA Technical Reports Server (NTRS)

Friedlander, David

1990-01-01

A software tool was developed for predicting the size of a future computer program at an early stage in its development. The system is intended to enable a user who is not expert in Software Engineering to estimate software size in lines of source code with an accuracy similar to that of an expert, based on the program's functional specifications. The project was planned as a knowledge based system with a field prototype as the goal of Phase 2 and a commercial system planned for Phase 3. The researchers used techniques from Artificial Intelligence and knowledge from human experts and existing software from NASA's COSMIC database. They devised a classification scheme for the software specifications, and a small set of generic software components that represent complexity and apply to large classes of programs. The specifications are converted to generic components by a set of rules and the generic components are input to a nonlinear sizing function which makes the final prediction. The system developed for this project predicted code sizes from the database with a bias factor of 1.06 and a fluctuation factor of 1.77, an accuracy similar to that of human experts but without their significant optimistic bias.

CORMIX1: AN EXPERT SYSTEM FOR MIXING ZONE ANALYSIS OF TOXIC AND CONVENTIONAL, SINGLE PORT AQUATIC DISCHARGES

EPA Science Inventory

An expert system, CORMIX1, was developed to predict the dilution and trajectory of a single buoyant discharge into an unstratified aquatic environment with and without crossflow. The system uses knowledge and inference rules obtained from hydrodynamic experts to classify and pred...

Upper arm elevation and repetitive shoulder movements: a general population job exposure matrix based on expert ratings and technical measurements.

PubMed

Dalbøge, Annett; Hansson, Gert-Åke; Frost, Poul; Andersen, Johan Hviid; Heilskov-Hansen, Thomas; Svendsen, Susanne Wulff

2016-08-01

We recently constructed a general population job exposure matrix (JEM), The Shoulder JEM, based on expert ratings. The overall aim of this study was to convert expert-rated job exposures for upper arm elevation and repetitive shoulder movements to measurement scales. The Shoulder JEM covers all Danish occupational titles, divided into 172 job groups. For 36 of these job groups, we obtained technical measurements (inclinometry) of upper arm elevation and repetitive shoulder movements. To validate the expert-rated job exposures against the measured job exposures, we used Spearman rank correlations and the explained variance[Formula: see text] according to linear regression analyses (36 job groups). We used the linear regression equations to convert the expert-rated job exposures for all 172 job groups into predicted measured job exposures. Bland-Altman analyses were used to assess the agreement between the predicted and measured job exposures. The Spearman rank correlations were 0.63 for upper arm elevation and 0.64 for repetitive shoulder movements. The expert-rated job exposures explained 64% and 41% of the variance of the measured job exposures, respectively. The corresponding calibration equations were y=0.5%time+0.16×expert rating and y=27°/s+0.47×expert rating. The mean differences between predicted and measured job exposures were zero due to calibration; the 95% limits of agreement were ±2.9% time for upper arm elevation >90° and ±33°/s for repetitive shoulder movements. The updated Shoulder JEM can be used to present exposure-response relationships on measurement scales. Published by the BMJ Publishing Group Limited. For permission to use (where not already granted under a licence) please go to http://www.bmj.com/company/products-services/rights-and-licensing/

Adaptability of expert visual anticipation in baseball batting.

PubMed

Müller, Sean; Fadde, Peter J; Harbaugh, Allen G

2017-09-01

By manipulating stimulus variation in terms of opponent pitcher actions, this study investigated the capability of expert (n = 30) and near-expert (n = 95) professional baseball batters to adapt anticipation skill when using the video simulation temporal occlusion paradigm. Participants watched in-game footage of two pitchers, one after the other, that was temporally occluded at ball release and various points during ball flight. They were required to make a written prediction of pitch types and locations. Per cent accuracy was calculated for pitch type, for pitch location, and for type and location combined. Results indicated that experts and near-experts could adapt their anticipation to predict above guessing level across both pitchers, but adaptation to the left-handed pitcher was poorer than the right-handed pitcher. Small-to-moderate effect sizes were found in terms of superior adaptation by experts over near-experts at the ball release and early ball flight occlusion conditions. The findings of this study extend theoretical and applied knowledge of expertise in striking sports. Practical application of the instruments and findings are discussed in terms of applied researchers, practitioners and high-performance staff in professional sporting organisations.

Investigation of Perceptual-Motor Behavior Across the Expert Athlete to Disabled Patient Skill Continuum can Advance Theory and Practical Application.

PubMed

Müller, Sean; Vallence, Ann-Maree; Winstein, Carolee

2017-12-14

A framework is presented of how theoretical predictions can be tested across the expert athlete to disabled patient skill continuum. Common-coding theory is used as the exemplar to discuss sensory and motor system contributions to perceptual-motor behavior. Behavioral and neural studies investigating expert athletes and patients recovering from cerebral stroke are reviewed. They provide evidence of bi-directional contributions of visual and motor systems to perceptual-motor behavior. Majority of this research is focused on perceptual-motor performance or learning, with less on transfer. The field is ripe for research designed to test theoretical predictions across the expert athlete to disabled patient skill continuum. Our view has implications for theory and practice in sports science, physical education, and rehabilitation.

CRN5EXP: Expert system for statistical quality control

NASA Technical Reports Server (NTRS)

Hentea, Mariana

1991-01-01

The purpose of the Expert System CRN5EXP is to assist in checking the quality of the coils at two very important mills: Hot Rolling and Cold Rolling in a steel plant. The system interprets the statistical quality control charts, diagnoses and predicts the quality of the steel. Measurements of process control variables are recorded in a database and sample statistics such as the mean and the range are computed and plotted on a control chart. The chart is analyzed through patterns using the C Language Integrated Production System (CLIPS) and a forward chaining technique to reach a conclusion about the causes of defects and to take management measures for the improvement of the quality control techniques. The Expert System combines the certainty factors associated with the process control variables to predict the quality of the steel. The paper presents the approach to extract data from the database, the reason to combine certainty factors, the architecture and the use of the Expert System. However, the interpretation of control charts patterns requires the human expert's knowledge and lends to Expert Systems rules.

Inside the black box: starting to uncover the underlying decision rules used in one-by-one expert assessment of occupational exposure in case-control studies

PubMed Central

Wheeler, David C.; Burstyn, Igor; Vermeulen, Roel; Yu, Kai; Shortreed, Susan M.; Pronk, Anjoeka; Stewart, Patricia A.; Colt, Joanne S.; Baris, Dalsu; Karagas, Margaret R.; Schwenn, Molly; Johnson, Alison; Silverman, Debra T.; Friesen, Melissa C.

2014-01-01

Objectives Evaluating occupational exposures in population-based case-control studies often requires exposure assessors to review each study participants' reported occupational information job-by-job to derive exposure estimates. Although such assessments likely have underlying decision rules, they usually lack transparency, are time-consuming and have uncertain reliability and validity. We aimed to identify the underlying rules to enable documentation, review, and future use of these expert-based exposure decisions. Methods Classification and regression trees (CART, predictions from a single tree) and random forests (predictions from many trees) were used to identify the underlying rules from the questionnaire responses and an expert's exposure assignments for occupational diesel exhaust exposure for several metrics: binary exposure probability and ordinal exposure probability, intensity, and frequency. Data were split into training (n=10,488 jobs), testing (n=2,247), and validation (n=2,248) data sets. Results The CART and random forest models' predictions agreed with 92–94% of the expert's binary probability assignments. For ordinal probability, intensity, and frequency metrics, the two models extracted decision rules more successfully for unexposed and highly exposed jobs (86–90% and 57–85%, respectively) than for low or medium exposed jobs (7–71%). Conclusions CART and random forest models extracted decision rules and accurately predicted an expert's exposure decisions for the majority of jobs and identified questionnaire response patterns that would require further expert review if the rules were applied to other jobs in the same or different study. This approach makes the exposure assessment process in case-control studies more transparent and creates a mechanism to efficiently replicate exposure decisions in future studies. PMID:23155187

Development and Evaluation of an Expert System for Diagnosing Pest Damage of Red Pine

Treesearch

Daniel L Schmoldt; George L. Martin

1989-01-01

An expert system for diagnosing pest damage of red pine stands in Wisconsin, PREDICT, runs on IBM or compatible microcomputers and is designed to be useful for field foresters with no advanced training in forest pathology or entomology. PREDICT recognizes 28 damaging agents including species of mammals, insects, and pathogens, as well as two types of abiotic damage....

Comparison of Ordinal and Nominal Classification Trees to Predict Ordinal Expert-Based Occupational Exposure Estimates in a Case–Control Study

PubMed Central

Wheeler, David C.; Archer, Kellie J.; Burstyn, Igor; Yu, Kai; Stewart, Patricia A.; Colt, Joanne S.; Baris, Dalsu; Karagas, Margaret R.; Schwenn, Molly; Johnson, Alison; Armenti, Karla; Silverman, Debra T.; Friesen, Melissa C.

2015-01-01

Objectives: To evaluate occupational exposures in case–control studies, exposure assessors typically review each job individually to assign exposure estimates. This process lacks transparency and does not provide a mechanism for recreating the decision rules in other studies. In our previous work, nominal (unordered categorical) classification trees (CTs) generally successfully predicted expert-assessed ordinal exposure estimates (i.e. none, low, medium, high) derived from occupational questionnaire responses, but room for improvement remained. Our objective was to determine if using recently developed ordinal CTs would improve the performance of nominal trees in predicting ordinal occupational diesel exhaust exposure estimates in a case–control study. Methods: We used one nominal and four ordinal CT methods to predict expert-assessed probability, intensity, and frequency estimates of occupational diesel exhaust exposure (each categorized as none, low, medium, or high) derived from questionnaire responses for the 14983 jobs in the New England Bladder Cancer Study. To replicate the common use of a single tree, we applied each method to a single sample of 70% of the jobs, using 15% to test and 15% to validate each method. To characterize variability in performance, we conducted a resampling analysis that repeated the sample draws 100 times. We evaluated agreement between the tree predictions and expert estimates using Somers’ d, which measures differences in terms of ordinal association between predicted and observed scores and can be interpreted similarly to a correlation coefficient. Results: From the resampling analysis, compared with the nominal tree, an ordinal CT method that used a quadratic misclassification function and controlled tree size based on total misclassification cost had a slightly better predictive performance that was statistically significant for the frequency metric (Somers’ d: nominal tree = 0.61; ordinal tree = 0.63) and similar performance for the probability (nominal = 0.65; ordinal = 0.66) and intensity (nominal = 0.65; ordinal = 0.65) metrics. The best ordinal CT predicted fewer cases of large disagreement with the expert assessments (i.e. no exposure predicted for a job with high exposure and vice versa) compared with the nominal tree across all of the exposure metrics. For example, the percent of jobs with expert-assigned high intensity of exposure that the model predicted as no exposure was 29% for the nominal tree and 22% for the best ordinal tree. Conclusions: The overall agreements were similar across CT models; however, the use of ordinal models reduced the magnitude of the discrepancy when disagreements occurred. As the best performing model can vary by situation, researchers should consider evaluating multiple CT methods to maximize the predictive performance within their data. PMID:25433003

Adaptation and validation of the REGEN expert system for the Central Appalachians

Treesearch

Lance A. Vickers; Thomas R. Fox; David L. Loftis; David A. Boucugnani

2011-01-01

REGEN is an expert system that predicts future species composition at the onset of stem exclusion using preharvest stand conditions. To extend coverage into hardwood stands of the Central Appalachians, we developed REGEN knowledge bases for four site qualities (xeric, subxeric, submesic, mesic) based on relevant literature and expert opinion. Data were collected from...

Seeking help in the shadow of doubt: the sensemaking processes underlying how nurses decide whom to ask for advice.

PubMed

Hofmann, David A; Lei, Zhike; Grant, Adam M

2009-09-01

Although scholars often assume that individuals seek out experts when they need help, recent research suggests that seeking help from experts can be costly. The authors propose that perceiving potential help providers as accessible or trustworthy can reduce the costs of seeking help and thus encourage individuals to seek help from experts. They further predict that perceptions of potential help providers' expertise, accessibility, and trustworthiness are shaped by their experience, formal roles, and organizational commitment. They investigated their theoretical model in a study of 146 nurses on the front lines of healthcare. They found that the decision to seek out help depends on help-seekers' perceptions of experts' accessibility and trustworthiness, and that these perceptions are predicted by experience, formal roles, and affective organizational commitment. Theoretical and practical implications are discussed.

Differentiating experts' anticipatory skills in beach volleyball.

PubMed

Cañal-Bruland, Rouwen; Mooren, Merel; Savelsbergh, Geert J P

2011-12-01

In this study, we examined how perceptual-motor expertise and watching experience contribute to anticipating the outcome of opponents' attacking actions in beach volleyball. To this end, we invited 8 expert beach volleyball players, 8 expert coaches, 8 expert referees, and 8 control participants with no beach volleyball experience to watch videos of attack sequences that were occluded at three different times and to predict the outcome of these situations. Results showed that expert players and coaches (who were both perceptual-motor experts) outperformed the expert referees (who were watching experts but did not have the same motor expertise) and the control group in the latest occlusion condition (i.e., at spiker-ball contact). This finding suggests that perceptual-motor expertise may contribute to successful action anticipation in beach volleyball.

Towards an Online Seizure Advisory System-An Adaptive Seizure Prediction Framework Using Active Learning Heuristics.

PubMed

Karuppiah Ramachandran, Vignesh Raja; Alblas, Huibert J; Le, Duc V; Meratnia, Nirvana

2018-05-24

In the last decade, seizure prediction systems have gained a lot of attention because of their enormous potential to largely improve the quality-of-life of the epileptic patients. The accuracy of the prediction algorithms to detect seizure in real-world applications is largely limited because the brain signals are inherently uncertain and affected by various factors, such as environment, age, drug intake, etc., in addition to the internal artefacts that occur during the process of recording the brain signals. To deal with such ambiguity, researchers transitionally use active learning, which selects the ambiguous data to be annotated by an expert and updates the classification model dynamically. However, selecting the particular data from a pool of large ambiguous datasets to be labelled by an expert is still a challenging problem. In this paper, we propose an active learning-based prediction framework that aims to improve the accuracy of the prediction with a minimum number of labelled data. The core technique of our framework is employing the Bernoulli-Gaussian Mixture model (BGMM) to determine the feature samples that have the most ambiguity to be annotated by an expert. By doing so, our approach facilitates expert intervention as well as increasing medical reliability. We evaluate seven different classifiers in terms of the classification time and memory required. An active learning framework built on top of the best performing classifier is evaluated in terms of required annotation effort to achieve a high level of prediction accuracy. The results show that our approach can achieve the same accuracy as a Support Vector Machine (SVM) classifier using only 20 % of the labelled data and also improve the prediction accuracy even under the noisy condition.

Learning from the Experts: Gaining Insights into Best Practice during the Acquisition of Three Novel Motor Skills

ERIC Educational Resources Information Center

Hodges, Nicola J.; Edwards, Christopher; Luttin, Shaun; Bowcock, Alison

2011-01-01

The amount and quality of practice predicts expertise, yet optimal conditions of practice have primarily been explored with novice learners. Ten expert musicians and ten novices practiced disc-throwing skills under self-regulated conditions. A third novice group practiced with the same schedule as the music experts (yoked). The groups did not…

Retrosynthetic Reaction Prediction Using Neural Sequence-to-Sequence Models

PubMed Central

2017-01-01

We describe a fully data driven model that learns to perform a retrosynthetic reaction prediction task, which is treated as a sequence-to-sequence mapping problem. The end-to-end trained model has an encoder–decoder architecture that consists of two recurrent neural networks, which has previously shown great success in solving other sequence-to-sequence prediction tasks such as machine translation. The model is trained on 50,000 experimental reaction examples from the United States patent literature, which span 10 broad reaction types that are commonly used by medicinal chemists. We find that our model performs comparably with a rule-based expert system baseline model, and also overcomes certain limitations associated with rule-based expert systems and with any machine learning approach that contains a rule-based expert system component. Our model provides an important first step toward solving the challenging problem of computational retrosynthetic analysis. PMID:29104927

Expert System Diagnosis of Cataract Eyes Using Fuzzy Mamdani Method

NASA Astrophysics Data System (ADS)

Santosa, I.; Romla, L.; Herawati, S.

2018-01-01

Cataracts are eye diseases characterized by cloudy or opacity of the lens of the eye by changing the colour of black into grey-white which slowly continues to grow and develop without feeling pain and pain that can cause blindness in human vision. Therefore, researchers make an expert system of cataract eye disease diagnosis by using Fuzzy Mamdani and how to care. The fuzzy method can convert the crisp value to linguistic value by fuzzification and includes in the rule. So this system produces an application program that can help the public in knowing cataract eye disease and how to care based on the symptoms suffered. From the results of the design implementation and testing of expert system applications to diagnose eye disease cataracts, it can be concluded that from a trial of 50 cases of data, obtained test results accuracy between system predictions with expert predictions obtained a value of 78% truth.

Prediction of homoprotein and heteroprotein complexes by protein docking and template‐based modeling: A CASP‐CAPRI experiment

PubMed Central

Velankar, Sameer; Kryshtafovych, Andriy; Huang, Shen‐You; Schneidman‐Duhovny, Dina; Sali, Andrej; Segura, Joan; Fernandez‐Fuentes, Narcis; Viswanath, Shruthi; Elber, Ron; Grudinin, Sergei; Popov, Petr; Neveu, Emilie; Lee, Hasup; Baek, Minkyung; Park, Sangwoo; Heo, Lim; Rie Lee, Gyu; Seok, Chaok; Qin, Sanbo; Zhou, Huan‐Xiang; Ritchie, David W.; Maigret, Bernard; Devignes, Marie‐Dominique; Ghoorah, Anisah; Torchala, Mieczyslaw; Chaleil, Raphaël A.G.; Bates, Paul A.; Ben‐Zeev, Efrat; Eisenstein, Miriam; Negi, Surendra S.; Weng, Zhiping; Vreven, Thom; Pierce, Brian G.; Borrman, Tyler M.; Yu, Jinchao; Ochsenbein, Françoise; Guerois, Raphaël; Vangone, Anna; Rodrigues, João P.G.L.M.; van Zundert, Gydo; Nellen, Mehdi; Xue, Li; Karaca, Ezgi; Melquiond, Adrien S.J.; Visscher, Koen; Kastritis, Panagiotis L.; Bonvin, Alexandre M.J.J.; Xu, Xianjin; Qiu, Liming; Yan, Chengfei; Li, Jilong; Ma, Zhiwei; Cheng, Jianlin; Zou, Xiaoqin; Shen, Yang; Peterson, Lenna X.; Kim, Hyung‐Rae; Roy, Amit; Han, Xusi; Esquivel‐Rodriguez, Juan; Kihara, Daisuke; Yu, Xiaofeng; Bruce, Neil J.; Fuller, Jonathan C.; Wade, Rebecca C.; Anishchenko, Ivan; Kundrotas, Petras J.; Vakser, Ilya A.; Imai, Kenichiro; Yamada, Kazunori; Oda, Toshiyuki; Nakamura, Tsukasa; Tomii, Kentaro; Pallara, Chiara; Romero‐Durana, Miguel; Jiménez‐García, Brian; Moal, Iain H.; Férnandez‐Recio, Juan; Joung, Jong Young; Kim, Jong Yun; Joo, Keehyoung; Lee, Jooyoung; Kozakov, Dima; Vajda, Sandor; Mottarella, Scott; Hall, David R.; Beglov, Dmitri; Mamonov, Artem; Xia, Bing; Bohnuud, Tanggis; Del Carpio, Carlos A.; Ichiishi, Eichiro; Marze, Nicholas; Kuroda, Daisuke; Roy Burman, Shourya S.; Gray, Jeffrey J.; Chermak, Edrisse; Cavallo, Luigi; Oliva, Romina; Tovchigrechko, Andrey

2016-01-01

ABSTRACT We present the results for CAPRI Round 30, the first joint CASP‐CAPRI experiment, which brought together experts from the protein structure prediction and protein–protein docking communities. The Round comprised 25 targets from amongst those submitted for the CASP11 prediction experiment of 2014. The targets included mostly homodimers, a few homotetramers, and two heterodimers, and comprised protein chains that could readily be modeled using templates from the Protein Data Bank. On average 24 CAPRI groups and 7 CASP groups submitted docking predictions for each target, and 12 CAPRI groups per target participated in the CAPRI scoring experiment. In total more than 9500 models were assessed against the 3D structures of the corresponding target complexes. Results show that the prediction of homodimer assemblies by homology modeling techniques and docking calculations is quite successful for targets featuring large enough subunit interfaces to represent stable associations. Targets with ambiguous or inaccurate oligomeric state assignments, often featuring crystal contact‐sized interfaces, represented a confounding factor. For those, a much poorer prediction performance was achieved, while nonetheless often providing helpful clues on the correct oligomeric state of the protein. The prediction performance was very poor for genuine tetrameric targets, where the inaccuracy of the homology‐built subunit models and the smaller pair‐wise interfaces severely limited the ability to derive the correct assembly mode. Our analysis also shows that docking procedures tend to perform better than standard homology modeling techniques and that highly accurate models of the protein components are not always required to identify their association modes with acceptable accuracy. Proteins 2016; 84(Suppl 1):323–348. © 2016 The Authors Proteins: Structure, Function, and Bioinformatics Published by Wiley Periodicals, Inc. PMID:27122118

An evaluation of the lamb vision system as a predictor of lamb carcass red meat yield percentage.

PubMed

Brady, A S; Belk, K E; LeValley, S B; Dalsted, N L; Scanga, J A; Tatum, J D; Smith, G C

2003-06-01

An objective method for predicting red meat yield in lamb carcasses is needed to accurately assess true carcass value. This study was performed to evaluate the ability of the lamb vision system (LVS; Research Management Systems USA, Fort Collins, CO) to predict fabrication yields of lamb carcasses. Lamb carcasses (n = 246) were evaluated using LVS and hot carcass weight (HCW), as well as by USDA expert and on-line graders, before fabrication of carcass sides to either bone-in or boneless cuts. On-line whole number, expert whole-number, and expert nearest-tenth USDA yield grades and LVS + HCW estimates accounted for 53, 52, 58, and 60%, respectively, of the observed variability in boneless, saleable meat yields, and accounted for 56, 57, 62, and 62%, respectively, of the variation in bone-in, saleable meat yields. The LVS + HCW system predicted 77, 65, 70, and 87% of the variation in weights of boneless shoulders, racks, loins, and legs, respectively, and 85, 72, 75, and 86% of the variation in weights of bone-in shoulders, racks, loins, and legs, respectively. Addition of longissimus muscle area (REA), adjusted fat thickness (AFT), or both REA and AFT to LVS + HCW models resulted in improved prediction of boneless saleable meat yields by 5, 3, and 5 percentage points, respectively. Bone-in, saleable meat yield estimations were improved in predictive accuracy by 7.7, 6.6, and 10.1 percentage points, and in precision, when REA alone, AFT alone, or both REA and AFT, respectively, were added to the LVS + HCW output models. Use of LVS + HCW to predict boneless red meat yields of lamb carcasses was more accurate than use of current on-line whole-number, expert whole-number, or expert nearest-tenth USDA yield grades. Thus, LVS + HCW output, when used alone or in combination with AFT and/or REA, improved on-line estimation of boneless cut yields from lamb carcasses. The ability of LVS + HCW to predict yields of wholesale cuts suggests that LVS could be used as an objective means for pricing carcasses in a value-based marketing system.

Experts correctly describe demography associated with historical decline of the endangered Indiana bat, but not recent period of stationarity

USGS Publications Warehouse

Thogmartin, Wayne E.; Sanders-Reed, Carol A.; Szymanski, Jennifer; Pruitt, Lori; Runge, Michael C.

2017-01-01

Demographic characteristics of bats are often insufficiently described for modeling populations. In data poor situations, experts are often relied upon for characterizing ecological systems. In concert with the development of a matrix model describing Indiana bat (Myotis sodalis) demography, we elicited estimates for parameterizing this model from 12 experts. We conducted this elicitation in two stages, requesting expert values for 12 demographic rates. These rates were adult and juvenile seasonal (winter, summer, fall) survival rates, pup survival in fall, and propensity and success at breeding. Experts were most in agreement about adult fall survival (3% Coefficient of Variation) and least in agreement about propensity of juveniles to breed (37% CV). The experts showed greater concordance for adult ( mean CV, adult = 6.2%) than for juvenile parameters ( mean CV, juvenile = 16.4%), and slightly more agreement for survival (mean CV, survival = 9.8%) compared to reproductive rates ( mean CV, reproduction = 15.1%). However, survival and reproduction were negatively and positively biased, respectively, relative to a stationary dynamic. Despite the species exhibiting near stationary dynamics for two decades prior to the onset of a potential extinction-causing agent, white-nose syndrome, expert estimates indicated a population decline of -11% per year (95% CI = -2%, -20%); quasi-extinction was predicted within a century ( mean = 61 years to QE, range = 32, 97) by 10 of the 12 experts. Were we to use these expert estimates in our modeling efforts, we would have errantly trained our models to a rapidly declining demography asymptomatic of recent demographic behavior. While experts are sometimes the only source of information, a clear understanding of the temporal and spatial context of the information being elicited is necessary to guard against wayward predictions.

The roles of deliberate practice and innate ability in developing expertise: evidence and implications.

PubMed

Kulasegaram, Kulamakan M; Grierson, Lawrence E M; Norman, Geoffrey R

2013-10-01

Medical education research focuses extensively on experience and deliberate practice (DP) as key factors in the development of expert performance. The research on DP minimises the role of individual ability in expert performance. This claim ignores a large body of research supporting the importance of innate individual cognitive differences. We review the relationship between DP and an innate individual ability, working memory (WM) capacity, to illustrate how both DP and individual ability predict expert performance. This narrative review examines the relationship between DP and WM in accounting for expert performance. Studies examining DP, WM and individual differences were identified through a targeted search. Although all studies support extensive DP as a factor in explaining expertise, much research suggests individual cognitive differences, such as WM capacity, predict expert performance after controlling for DP. The extent to which this occurs may be influenced by the nature of the task under study and the cognitive processes used by experts. The importance of WM capacity is greater for tasks that are non-routine or functionally complex. Clinical reasoning displays evidence of this task-dependent importance of individual ability. No single factor is both necessary and sufficient in explaining expertise, and individual abilities such as WM can be important. These individual abilities are likely to contribute to expert performance in clinical settings. Medical education research and practice should identify the individual differences in novices and experts that are important to clinical performance. © 2013 John Wiley & Sons Ltd.

77 FR 68773 - FIFRA Scientific Advisory Panel; Notice of Public Meeting

Federal Register 2010, 2011, 2012, 2013, 2014

2012-11-16

... for physical chemical properties that cannot be easily tested in in vitro systems or stable enough for.... Quantitative structural-activity relationship (QSAR) models and estrogen receptor (ER) expert systems development. High-throughput data generation and analysis (expertise focused on how this methodology can be...

Design of an expert system for the development and formulation of push-pull osmotic pump tablets containing poorly water-soluble drugs.

PubMed

Zhang, Zhi-hong; Dong, Hong-ye; Peng, Bo; Liu, Hong-fei; Li, Chun-lei; Liang, Min; Pan, Wei-san

2011-05-30

The purpose of this article was to build an expert system for the development and formulation of push-pull osmotic pump tablets (PPOP). Hundreds of PPOP formulations were studied according to different poorly water-soluble drugs and pharmaceutical acceptable excipients. The knowledge base including database and rule base was built based on the reported results of hundreds of PPOP formulations containing different poorly water-soluble drugs and pharmaceutical excipients and the experiences available from other researchers. The prediction model of release behavior was built using back propagation (BP) neural network, which is good at nonlinear mapping and learning function. Formulation design model was established based on the prediction model of release behavior, which was the nucleus of the inference engine. Finally, the expert system program was constructed by VB.NET associating with SQL Server. Expert system is one of the most popular aspects in artificial intelligence. To date there is no expert system available for the formulation of controlled release dosage forms yet. Moreover, osmotic pump technology (OPT) is gradually getting consummate all over the world. It is meaningful to apply expert system on OPT. Famotidine, a water insoluble drug was chosen as the model drug to validate the applicability of the developed expert system. Copyright © 2011 Elsevier B.V. All rights reserved.

Processing of musical syntax tonic versus subdominant: an event-related potential study.

PubMed

Poulin-Charronnat, Bénédicte; Bigand, Emmanuel; Koelsch, Stefan

2006-09-01

The present study investigates the effect of a change in syntactic-like musical function on event-related brain potentials (ERPs). Eight-chord piano sequences were presented to musically expert and novice listeners. Instructed to watch a movie and to ignore the musical sequences, the participants had to react when a chord was played with a different instrument than the piano. Participants were not informed that the relevant manipulation was the musical function of the last chord (target) of the sequences. The target chord acted either as a syntactically stable tonic chord (i.e., a C major chord in the key of C major) or as a less syntactically stable subdominant chord (i.e., a C major chord in the key of G major). The critical aspect of the results related to the impact such a manipulation had on the ERPs. An N5-like frontal negative component was found to be larger for subdominant than for tonic chords and attained significance only in musically expert listeners. These findings suggest that the subdominant chord is more difficult to integrate with the previous context than the tonic chord (as indexing by the observed N5) and that the processing of a small change in musical function occurs in an automatic way in musically expert listeners. The present results are discussed in relation to previous studies investigating harmonic violations with ERPs.

Developing and Testing a Model to Predict Outcomes of Organizational Change

PubMed Central

Gustafson, David H; Sainfort, François; Eichler, Mary; Adams, Laura; Bisognano, Maureen; Steudel, Harold

2003-01-01

Objective To test the effectiveness of a Bayesian model employing subjective probability estimates for predicting success and failure of health care improvement projects. Data Sources Experts' subjective assessment data for model development and independent retrospective data on 221 healthcare improvement projects in the United States, Canada, and the Netherlands collected between 1996 and 2000 for validation. Methods A panel of theoretical and practical experts and literature in organizational change were used to identify factors predicting the outcome of improvement efforts. A Bayesian model was developed to estimate probability of successful change using subjective estimates of likelihood ratios and prior odds elicited from the panel of experts. A subsequent retrospective empirical analysis of change efforts in 198 health care organizations was performed to validate the model. Logistic regression and ROC analysis were used to evaluate the model's performance using three alternative definitions of success. Data Collection For the model development, experts' subjective assessments were elicited using an integrative group process. For the validation study, a staff person intimately involved in each improvement project responded to a written survey asking questions about model factors and project outcomes. Results Logistic regression chi-square statistics and areas under the ROC curve demonstrated a high level of model performance in predicting success. Chi-square statistics were significant at the 0.001 level and areas under the ROC curve were greater than 0.84. Conclusions A subjective Bayesian model was effective in predicting the outcome of actual improvement projects. Additional prospective evaluations as well as testing the impact of this model as an intervention are warranted. PMID:12785571

Estrogen receptor expert system overview and examples

EPA Science Inventory

The estrogen receptor expert system (ERES) is a rule-based system developed to prioritize chemicals based upon their potential for binding to the ER. The ERES was initially developed to predict ER affinity of chemicals from two specific EPA chemical inventories, antimicrobial pe...

Computer-assisted expert case definition in electronic health records.

PubMed

Walker, Alexander M; Zhou, Xiaofeng; Ananthakrishnan, Ashwin N; Weiss, Lisa S; Shen, Rongjun; Sobel, Rachel E; Bate, Andrew; Reynolds, Robert F

2016-02-01

To describe how computer-assisted presentation of case data can lead experts to infer machine-implementable rules for case definition in electronic health records. As an illustration the technique has been applied to obtain a definition of acute liver dysfunction (ALD) in persons with inflammatory bowel disease (IBD). The technique consists of repeatedly sampling new batches of case candidates from an enriched pool of persons meeting presumed minimal inclusion criteria, classifying the candidates by a machine-implementable candidate rule and by a human expert, and then updating the rule so that it captures new distinctions introduced by the expert. Iteration continues until an update results in an acceptably small number of changes to form a final case definition. The technique was applied to structured data and terms derived by natural language processing from text records in 29,336 adults with IBD. Over three rounds the technique led to rules with increasing predictive value, as the experts identified exceptions, and increasing sensitivity, as the experts identified missing inclusion criteria. In the final rule inclusion and exclusion terms were often keyed to an ALD onset date. When compared against clinical review in an independent test round, the derived final case definition had a sensitivity of 92% and a positive predictive value of 79%. An iterative technique of machine-supported expert review can yield a case definition that accommodates available data, incorporates pre-existing medical knowledge, is transparent and is open to continuous improvement. The expert updates to rules may be informative in themselves. In this limited setting, the final case definition for ALD performed better than previous, published attempts using expert definitions. Copyright © 2015 Elsevier Ireland Ltd. All rights reserved.

Results from the centers for disease control and prevention's predict the 2013-2014 Influenza Season Challenge.

PubMed

Biggerstaff, Matthew; Alper, David; Dredze, Mark; Fox, Spencer; Fung, Isaac Chun-Hai; Hickmann, Kyle S; Lewis, Bryan; Rosenfeld, Roni; Shaman, Jeffrey; Tsou, Ming-Hsiang; Velardi, Paola; Vespignani, Alessandro; Finelli, Lyn

2016-07-22

Early insights into the timing of the start, peak, and intensity of the influenza season could be useful in planning influenza prevention and control activities. To encourage development and innovation in influenza forecasting, the Centers for Disease Control and Prevention (CDC) organized a challenge to predict the 2013-14 Unites States influenza season. Challenge contestants were asked to forecast the start, peak, and intensity of the 2013-2014 influenza season at the national level and at any or all Health and Human Services (HHS) region level(s). The challenge ran from December 1, 2013-March 27, 2014; contestants were required to submit 9 biweekly forecasts at the national level to be eligible. The selection of the winner was based on expert evaluation of the methodology used to make the prediction and the accuracy of the prediction as judged against the U.S. Outpatient Influenza-like Illness Surveillance Network (ILINet). Nine teams submitted 13 forecasts for all required milestones. The first forecast was due on December 2, 2013; 3/13 forecasts received correctly predicted the start of the influenza season within one week, 1/13 predicted the peak within 1 week, 3/13 predicted the peak ILINet percentage within 1 %, and 4/13 predicted the season duration within 1 week. For the prediction due on December 19, 2013, the number of forecasts that correctly forecasted the peak week increased to 2/13, the peak percentage to 6/13, and the duration of the season to 6/13. As the season progressed, the forecasts became more stable and were closer to the season milestones. Forecasting has become technically feasible, but further efforts are needed to improve forecast accuracy so that policy makers can reliably use these predictions. CDC and challenge contestants plan to build upon the methods developed during this contest to improve the accuracy of influenza forecasts.

The influence of expertise on brain activation of the action observation network during anticipation of tennis and volleyball serves.

PubMed

Balser, Nils; Lorey, Britta; Pilgramm, Sebastian; Naumann, Tim; Kindermann, Stefan; Stark, Rudolf; Zentgraf, Karen; Williams, A Mark; Munzert, Jörn

2014-01-01

In many daily activities, and especially in sport, it is necessary to predict the effects of others' actions in order to initiate appropriate responses. Recently, researchers have suggested that the action-observation network (AON) including the cerebellum plays an essential role during such anticipation, particularly in sport expert performers. In the present study, we examined the influence of task-specific expertise on the AON by investigating differences between two expert groups trained in different sports while anticipating action effects. Altogether, 15 tennis and 16 volleyball experts anticipated the direction of observed tennis and volleyball serves while undergoing functional magnetic resonance imaging (fMRI). The expert group in each sport acted as novice controls in the other sport with which they had only little experience. When contrasting anticipation in both expertise conditions with the corresponding untrained sport, a stronger activation of AON areas (SPL, SMA), and particularly of cerebellar structures, was observed. Furthermore, the neural activation within the cerebellum and the SPL was linearly correlated with participant's anticipation performance, irrespective of the specific expertise. For the SPL, this relationship also holds when an expert performs a domain-specific anticipation task. Notably, the stronger activation of the cerebellum as well as of the SMA and the SPL in the expertise conditions suggests that experts rely on their more fine-tuned perceptual-motor representations that have improved during years of training when anticipating the effects of others' actions in their preferred sport. The association of activation within the SPL and the cerebellum with the task achievement suggests that these areas are the predominant brain sites involved in fast motor predictions. The SPL reflects the processing of domain-specific contextual information and the cerebellum the usage of a predictive internal model to solve the anticipation task.

Subthreshold Symptoms of Depression in Preadolescent Girls Are Stable and Predictive of Depressive Disorders

ERIC Educational Resources Information Center

Keenan, Kate; Hipwell, Alsion; Feng, Xin; Babinski, Dara; Hinze, Amanda; Rischall, Michal; Henneberger, Angela

2008-01-01

Symptoms of depression are investigated among 232 preadolescent girls to study if they were predictive and stable of depression. Findings show that early symptoms of depression among preadolescent girls predict depressive disorders. Implications for preventive measures are discussed.

Comparison of climate envelope models developed using expert-selected variables versus statistical selection

USGS Publications Warehouse

Brandt, Laura A.; Benscoter, Allison; Harvey, Rebecca G.; Speroterra, Carolina; Bucklin, David N.; Romañach, Stephanie; Watling, James I.; Mazzotti, Frank J.

2017-01-01

Climate envelope models are widely used to describe potential future distribution of species under different climate change scenarios. It is broadly recognized that there are both strengths and limitations to using climate envelope models and that outcomes are sensitive to initial assumptions, inputs, and modeling methods Selection of predictor variables, a central step in modeling, is one of the areas where different techniques can yield varying results. Selection of climate variables to use as predictors is often done using statistical approaches that develop correlations between occurrences and climate data. These approaches have received criticism in that they rely on the statistical properties of the data rather than directly incorporating biological information about species responses to temperature and precipitation. We evaluated and compared models and prediction maps for 15 threatened or endangered species in Florida based on two variable selection techniques: expert opinion and a statistical method. We compared model performance between these two approaches for contemporary predictions, and the spatial correlation, spatial overlap and area predicted for contemporary and future climate predictions. In general, experts identified more variables as being important than the statistical method and there was low overlap in the variable sets (<40%) between the two methods Despite these differences in variable sets (expert versus statistical), models had high performance metrics (>0.9 for area under the curve (AUC) and >0.7 for true skill statistic (TSS). Spatial overlap, which compares the spatial configuration between maps constructed using the different variable selection techniques, was only moderate overall (about 60%), with a great deal of variability across species. Difference in spatial overlap was even greater under future climate projections, indicating additional divergence of model outputs from different variable selection techniques. Our work is in agreement with other studies which have found that for broad-scale species distribution modeling, using statistical methods of variable selection is a useful first step, especially when there is a need to model a large number of species or expert knowledge of the species is limited. Expert input can then be used to refine models that seem unrealistic or for species that experts believe are particularly sensitive to change. It also emphasizes the importance of using multiple models to reduce uncertainty and improve map outputs for conservation planning. Where outputs overlap or show the same direction of change there is greater certainty in the predictions. Areas of disagreement can be used for learning by asking why the models do not agree, and may highlight areas where additional on-the-ground data collection could improve the models.

The use of subjective expert opinions in cost optimum design of aerospace structures. [probabilistic failure models

NASA Technical Reports Server (NTRS)

Thomas, J. M.; Hanagud, S.

1975-01-01

The results of two questionnaires sent to engineering experts are statistically analyzed and compared with objective data from Saturn V design and testing. Engineers were asked how likely it was for structural failure to occur at load increments above and below analysts' stress limit predictions. They were requested to estimate the relative probabilities of different failure causes, and of failure at each load increment given a specific cause. Three mathematical models are constructed based on the experts' assessment of causes. The experts' overall assessment of prediction strength fits the Saturn V data better than the models do, but a model test option (T-3) based on the overall assessment gives more design change likelihood to overstrength structures than does an older standard test option. T-3 compares unfavorably with the standard option in a cost optimum structural design problem. The report reflects a need for subjective data when objective data are unavailable.

Meta-knowledge for charity: Learnings from a non-market-based prediction platform for climate scientists

NASA Astrophysics Data System (ADS)

Kriss, P.

2016-12-01

We present the results from Vision Prize, an online platform for capturing expert opinion on climate risks and solutions. Expert panelists provided their own opinions, and also predicted the views of their scientific colleagues. This approach (Prelec, 2004 Nature) gives new insight into the level of scientific consensus on various issues, which in some cases may be just as important as knowing the majority view. Questions ranged from causal attributions of past events to predictions about future risks and beliefs about possible solutions. Across all topics, we find that our expert participants agree with each other more than they think they do, often in surprising ways. Data collection for the Vision Prize project was run in collaboration with Environmental Research Web (IOP). Panelists were pre-screened to ensure they have relevant expertise and independently collected h-scores provide an approximate measure of research impact of those giving each response. Charity prizes were awarded for exceptional meta-knowledge, according to Prelec's algorithm.

Parameterization of the InVEST Crop Pollination Model to spatially predict abundance of wild blueberry (Vaccinium angustifolium Aiton) native bee pollinators in Maine, USA

USGS Publications Warehouse

Groff, Shannon C.; Loftin, Cynthia S.; Drummond, Frank; Bushmann, Sara; McGill, Brian J.

2016-01-01

Non-native honeybees historically have been managed for crop pollination, however, recent population declines draw attention to pollination services provided by native bees. We applied the InVEST Crop Pollination model, developed to predict native bee abundance from habitat resources, in Maine's wild blueberry crop landscape. We evaluated model performance with parameters informed by four approaches: 1) expert opinion; 2) sensitivity analysis; 3) sensitivity analysis informed model optimization; and, 4) simulated annealing (uninformed) model optimization. Uninformed optimization improved model performance by 29% compared to expert opinion-informed model, while sensitivity-analysis informed optimization improved model performance by 54%. This suggests that expert opinion may not result in the best parameter values for the InVEST model. The proportion of deciduous/mixed forest within 2000 m of a blueberry field also reliably predicted native bee abundance in blueberry fields, however, the InVEST model provides an efficient tool to estimate bee abundance beyond the field perimeter.

SUMOFLUX: A Generalized Method for Targeted 13C Metabolic Flux Ratio Analysis

PubMed Central

Kogadeeva, Maria

2016-01-01

Metabolic fluxes are a cornerstone of cellular physiology that emerge from a complex interplay of enzymes, carriers, and nutrients. The experimental assessment of in vivo intracellular fluxes using stable isotopic tracers is essential if we are to understand metabolic function and regulation. Flux estimation based on 13C or 2H labeling relies on complex simulation and iterative fitting; processes that necessitate a level of expertise that ordinarily preclude the non-expert user. To overcome this, we have developed SUMOFLUX, a methodology that is broadly applicable to the targeted analysis of 13C-metabolic fluxes. By combining surrogate modeling and machine learning, we trained a predictor to specialize in estimating flux ratios from measurable 13C-data. SUMOFLUX targets specific flux features individually, which makes it fast, user-friendly, applicable to experimental design and robust in terms of experimental noise and exchange flux magnitude. Collectively, we predict that SUMOFLUX's properties realistically pave the way to high-throughput flux analyses. PMID:27626798

Hazard perception, risk perception, and the need for decontamination by residents exposed to soil pollution: the role of sustainability and the limits of expert knowledge.

PubMed

Vandermoere, Frédéric

2008-04-01

This case study examines the hazard and risk perception and the need for decontamination according to people exposed to soil pollution. Using an ecological-symbolic approach (ESA), a multidisciplinary model is developed that draws upon psychological and sociological perspectives on risk perception and includes ecological variables by using data from experts' risk assessments. The results show that hazard perception is best predicted by objective knowledge, subjective knowledge, estimated knowledge of experts, and the assessed risks. However, experts' risk assessments induce an increase in hazard perception only when residents know the urgency of decontamination. Risk perception is best predicted by trust in the risk management. Additionally, need for decontamination relates to hazard perception, risk perception, estimated knowledge of experts, and thoughts about sustainability. In contrast to the knowledge deficit model, objective and subjective knowledge did not significantly relate to risk perception and need for decontamination. The results suggest that residents can make a distinction between hazards in terms of the seriousness of contamination on the one hand, and human health risks on the other hand. Moreover, next to the importance of social determinants of environmental risk perception, this study shows that the output of experts' risk assessments-or the objective risks-can create a hazard awareness rather than an alarming risk consciousness, despite residents' distrust of scientific knowledge.

Mining data from hemodynamic simulations for generating prediction and explanation models.

PubMed

Bosnić, Zoran; Vračar, Petar; Radović, Milos D; Devedžić, Goran; Filipović, Nenad D; Kononenko, Igor

2012-03-01

One of the most common causes of human death is stroke, which can be caused by carotid bifurcation stenosis. In our work, we aim at proposing a prototype of a medical expert system that could significantly aid medical experts to detect hemodynamic abnormalities (increased artery wall shear stress). Based on the acquired simulated data, we apply several methodologies for1) predicting magnitudes and locations of maximum wall shear stress in the artery, 2) estimating reliability of computed predictions, and 3) providing user-friendly explanation of the model's decision. The obtained results indicate that the evaluated methodologies can provide a useful tool for the given problem domain. © 2012 IEEE

A rule-based expert system for chemical prioritization using effects-based chemical categories

EPA Science Inventory

A rule-based expert system (ES) was developed to predict chemical binding to the estrogen receptor (ER) patterned on the research approaches championed by Gilman Veith to whom this article and journal issue are dedicated. The ERES was built to be mechanistically-transparent and m...

How Experts Practice: A Novel Test of Deliberate Practice Theory

ERIC Educational Resources Information Center

Coughlan, Edward K.; Williams, A. Mark; McRobert, Allistair P.; Ford, Paul R.

2014-01-01

Performance improvement is thought to occur through engagement in deliberate practice. Deliberate practice is predicted to be challenging, effortful, and not inherently enjoyable. Expert and intermediate level Gaelic football players executed two types of kicks during an acquisition phase and pre-, post-, and retention tests. During acquisition,…

Aeroaging - A New Collaboration between Life Sciences Experts and Aerospace Engineers.

PubMed

Vellas, M; Fualdes, C; Morley, J E; Dray, C; Rodriguez-Manas, L; Meyer, A; Michel, L; Rolland, Y; Gourinat, Y

2017-01-01

An open discussion between experts from life sciences and aeronautics has been held in order to investigate how both area of research overlap and could be relevant to each other, precisely on the topic of aging. Similarities in aging processes and prediction methodologies have been identified between human aging and aircraft aging. Two axis of collaboration have been raised: 1) The identification of the determinants in Aircraft aging (structural aging). 2) The development of P4 Systems medicine inspired new methodologies in the predictive maintenance.

Expert system technology

NASA Technical Reports Server (NTRS)

Prince, Mary Ellen

1987-01-01

The expert system is a computer program which attempts to reproduce the problem-solving behavior of an expert, who is able to view problems from a broad perspective and arrive at conclusions rapidly, using intuition, shortcuts, and analogies to previous situations. Expert systems are a departure from the usual artificial intelligence approach to problem solving. Researchers have traditionally tried to develop general modes of human intelligence that could be applied to many different situations. Expert systems, on the other hand, tend to rely on large quantities of domain specific knowledge, much of it heuristic. The reasoning component of the system is relatively simple and straightforward. For this reason, expert systems are often called knowledge based systems. The report expands on the foregoing. Section 1 discusses the architecture of a typical expert system. Section 2 deals with the characteristics that make a problem a suitable candidate for expert system solution. Section 3 surveys current technology, describing some of the software aids available for expert system development. Section 4 discusses the limitations of the latter. The concluding section makes predictions of future trends.

Comparison of the Belgian Rheumatoid Arthritis Disability Assessment and Health Assessment Questionnaires as Tools to Predict the Need for Support Measures in Patients with Rheumatoid Arthritis

PubMed Central

Janssens, Xavier; Decuman, Saskia; De Keyser, Filip

2016-01-01

Objective Scores on the Health Assessment Questionnaire (HAQ) predict the need for support measures in patients with rheumatoid arthritis (RA). In this study we compare the performance of the HAQ in this context with that of the more disease-specific Belgian Rheumatoid Arthritis Disability Assessment (BRADA) questionnaire. Methods In this multicenter observational study, patients with RA and disease duration of at least one year who consulted their rheumatologist for a routine follow-up visit filled out the HAQ, and BRADA questionnaires. The performance of HAQ and BRADA to predict the need for support measures available to patients with RA was evaluated using Receiver Operator Characteristic (ROC) curves, with the expert opinion of the rheumatologist as a reference. Results The study analyzed data of 301 patients with RA (70.8% females) with mean age 59.8±12.8, disease duration 11.4±9.3 years, and DAS28 values of 2.84±1.18. HAQ scores averaged 0.97±0.73 and BRADA scores were 3.92±3.49 over the last week and 3.89±3.50 over the last 3 months. The area under the ROC curves for the BRADA scores for the support measures investigated ranged from 0.702 to 0.862 and did not differ significantly from those of the HAQ (range 0.725–0.860). Conclusion The disease-specific BRADA questionnaire is equivalent to the HAQ in predicting the need for support measures in patients with stable RA. PMID:26800345

Comparison of the Belgian Rheumatoid Arthritis Disability Assessment and Health Assessment Questionnaires as Tools to Predict the Need for Support Measures in Patients with Rheumatoid Arthritis.

PubMed

Janssens, Xavier; Decuman, Saskia; De Keyser, Filip

2016-01-01

Scores on the Health Assessment Questionnaire (HAQ) predict the need for support measures in patients with rheumatoid arthritis (RA). In this study we compare the performance of the HAQ in this context with that of the more disease-specific Belgian Rheumatoid Arthritis Disability Assessment (BRADA) questionnaire. In this multicenter observational study, patients with RA and disease duration of at least one year who consulted their rheumatologist for a routine follow-up visit filled out the HAQ, and BRADA questionnaires. The performance of HAQ and BRADA to predict the need for support measures available to patients with RA was evaluated using Receiver Operator Characteristic (ROC) curves, with the expert opinion of the rheumatologist as a reference. The study analyzed data of 301 patients with RA (70.8% females) with mean age 59.8 ± 12.8, disease duration 11.4 ± 9.3 years, and DAS28 values of 2.84 ± 1.18. HAQ scores averaged 0.97 ± 0.73 and BRADA scores were 3.92 ± 3.49 over the last week and 3.89 ± 3.50 over the last 3 months. The area under the ROC curves for the BRADA scores for the support measures investigated ranged from 0.702 to 0.862 and did not differ significantly from those of the HAQ (range 0.725-0.860). The disease-specific BRADA questionnaire is equivalent to the HAQ in predicting the need for support measures in patients with stable RA.

Common problems in the elicitation and analysis of expert opinion affecting probabilistic safety assessments

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

Meyer, M.A.; Booker, J.M.

1990-01-01

Expert opinion is frequently used in probabilistic safety assessment (PSA), particularly in estimating low probability events. In this paper, we discuss some of the common problems encountered in eliciting and analyzing expert opinion data and offer solutions or recommendations. The problems are: that experts are not naturally Bayesian. People fail to update their existing information to account for new information as it becomes available, as would be predicted by the Bayesian philosophy; that experts cannot be fully calibrated. To calibrate experts, the feedback from the known quantities must be immediate, frequent, and specific to the task; that experts are limitedmore » in the number of things that they can mentally juggle at a time to 7 {plus minus} 2; that data gatherers and analysts can introduce bias by unintentionally causing an altering of the expert's thinking or answers; that the level of detail the data, or granularity, can affect the analyses; and the conditioning effect poses difficulties in gathering and analyzing of the expert data. The data that the expert gives can be conditioned on a variety of factors that can affect the analysis and the interpretation of the results. 31 refs.« less

Online evaluation of a commercial video image analysis system (Computer Vision System) to predict beef carcass red meat yield and for augmenting the assignment of USDA yield grades. United States Department of Agriculture.

PubMed

Cannell, R C; Belk, K E; Tatum, J D; Wise, J W; Chapman, P L; Scanga, J A; Smith, G C

2002-05-01

Objective quantification of differences in wholesale cut yields of beef carcasses at plant chain speeds is important for the application of value-based marketing. This study was conducted to evaluate the ability of a commercial video image analysis system, the Computer Vision System (CVS) to 1) predict commercially fabricated beef subprimal yield and 2) augment USDA yield grading, in order to improve accuracy of grade assessment. The CVS was evaluated as a fully installed production system, operating on a full-time basis at chain speeds. Steer and heifer carcasses (n = 296) were evaluated using CVS, as well as by USDA expert and online graders, before the fabrication of carcasses into industry-standard subprimal cuts. Expert yield grade (YG), online YG, CVS estimated carcass yield, and CVS measured ribeye area in conjunction with expert grader estimates of the remaining YG factors (adjusted fat thickness, percentage of kidney-pelvic-heart fat, hot carcass weight) accounted for 67, 39, 64, and 65% of the observed variation in fabricated yields of closely trimmed subprimals. The dual component CVS predicted wholesale cut yields more accurately than current online yield grading, and, in an augmentation system, CVS ribeye measurement replaced estimated ribeye area in determination of USDA yield grade, and the accuracy of cutability prediction was improved, under packing plant conditions and speeds, to a level close to that of expert graders applying grades at a comfortable rate of speed offline.

Adaptive reliance on the most stable sensory predictions enhances perceptual feature extraction of moving stimuli.

PubMed

Kumar, Neeraj; Mutha, Pratik K

2016-03-01

The prediction of the sensory outcomes of action is thought to be useful for distinguishing self- vs. externally generated sensations, correcting movements when sensory feedback is delayed, and learning predictive models for motor behavior. Here, we show that aspects of another fundamental function-perception-are enhanced when they entail the contribution of predicted sensory outcomes and that this enhancement relies on the adaptive use of the most stable predictions available. We combined a motor-learning paradigm that imposes new sensory predictions with a dynamic visual search task to first show that perceptual feature extraction of a moving stimulus is poorer when it is based on sensory feedback that is misaligned with those predictions. This was possible because our novel experimental design allowed us to override the "natural" sensory predictions present when any action is performed and separately examine the influence of these two sources on perceptual feature extraction. We then show that if the new predictions induced via motor learning are unreliable, rather than just relying on sensory information for perceptual judgments, as is conventionally thought, then subjects adaptively transition to using other stable sensory predictions to maintain greater accuracy in their perceptual judgments. Finally, we show that when sensory predictions are not modified at all, these judgments are sharper when subjects combine their natural predictions with sensory feedback. Collectively, our results highlight the crucial contribution of sensory predictions to perception and also suggest that the brain intelligently integrates the most stable predictions available with sensory information to maintain high fidelity in perceptual decisions. Copyright © 2016 the American Physiological Society.

Predicting landscape connectivity for the Asian elephant in its largest remaining subpopulation

Treesearch

J.-P. Puyravaud; Samuel Cushman; P. Davidar; D. Madappa

2016-01-01

Landscape connectivity between protected areas is crucial for the conservation of megafauna. But often, corridor identification relies on expert knowledge that is subjective and not spatially synoptic. Landscape analysis allows generalization of expert knowledge when satellite tracking or genetic data are not available. The Nilgiri Biosphere Reserve in southern India...

Classification of Word Levels with Usage Frequency, Expert Opinions and Machine Learning

ERIC Educational Resources Information Center

Sohsah, Gihad N.; Ünal, Muhammed Esad; Güzey, Onur

2015-01-01

Educational applications for language teaching can utilize the language levels of words to target proficiency levels of students. This paper and the accompanying data provide a methodology for making educational standard-aligned language-level predictions for all English words. The methodology involves expert opinions on language levels and…

Underwater Munitions Expert System to Predict Mobility and Burial

DTIC Science & Technology

2017-11-14

exposure and aggregation for underwater munitions. 15. SUBJECT TERMS Underwater Munitions, Mobility, Burial, Application Programmer Interface...Munitions Expert System: Demonstration and Evaluation Report Acronyms API – Application Programmer Interface APL – Applied Physics...comparisons and traditional metrics such as the coefficient of correlation. The summary statistic for the comparisons of burial results

Foveal and peripheral fields of vision influences perceptual skill in anticipating opponents' attacking position in volleyball.

PubMed

Schorer, Jörg; Rienhoff, Rebecca; Fischer, Lennart; Baker, Joseph

2013-09-01

The importance of perceptual-cognitive expertise in sport has been repeatedly demonstrated. In this study we examined the role of different sources of visual information (i.e., foveal versus peripheral) in anticipating volleyball attack positions. Expert (n = 11), advanced (n = 13) and novice (n = 16) players completed an anticipation task that involved predicting the location of volleyball attacks. Video clips of volleyball attacks (n = 72) were spatially and temporally occluded to provide varying amounts of information to the participant. In addition, participants viewed the attacks under three visual conditions: full vision, foveal vision only, and peripheral vision only. Analysis of variance revealed significant between group differences in prediction accuracy with higher skilled players performing better than lower skilled players. Additionally, we found significant differences between temporal and spatial occlusion conditions. Both of those factors interacted separately, but not combined with expertise. Importantly, for experts the sum of both fields of vision was superior to either source in isolation. Our results suggest different sources of visual information work collectively to facilitate expert anticipation in time-constrained sports and reinforce the complexity of expert perception.

Mediating the Cognitive Walkthrough with Patient Groups to achieve Personalized Health in Chronic Disease Self-Management System Evaluation.

PubMed

Georgsson, Mattias; Kushniruk, Andre

2016-01-01

The cognitive walkthrough (CW) is a task-based, expert inspection usability evaluation method involving benefits such as cost effectiveness and efficiency. A drawback of the method is that it doesn't involve the user perspective from real users but instead is based on experts' predictions about the usability of the system and how users interact. In this paper, we propose a way of involving the user in an expert evaluation method by modifying the CW with patient groups as mediators. This along with other modifications include a dual domain session facilitator, specific patient groups and three different phases: 1) a preparation phase where suitable tasks are developed by a panel of experts and patients, validated through the content validity index 2) a patient user evaluation phase including an individual and collaborative process part 3) an analysis and coding phase where all data is digitalized and synthesized making use of Qualitative Data Analysis Software (QDAS) to determine usability deficiencies. We predict that this way of evaluating will utilize the benefits of the expert methods, also providing a way of including the patient user of these self-management systems. Results from this prospective study should provide evidence of the usefulness of this method modification.

A Semi-automated Approach to Create Purposeful Mechanistic Datasets from Heterogeneous Data: Data Mining Towards the in silico Predictions for Oestrogen Receptor Modulation and Teratogenicity.

PubMed

Bashir Surfraz, M; Fowkes, Adrian; Plante, Jeffrey P

2017-08-01

The need to find an alternative to costly animal studies for developmental and reproductive toxicity testing has shifted the focus considerably to the assessment of in vitro developmental toxicology models and the exploitation of pharmacological data for relevant molecular initiating events. We hereby demonstrate how automation can be applied successfully to handle heterogeneous oestrogen receptor data from ChEMBL. Applying expert-derived thresholds to specific bioactivities allowed an activity call to be attributed to each data entry. Human intervention further improved this mechanistic dataset which was mined to develop structure-activity relationship alerts and an expert model covering 45 chemical classes for the prediction of oestrogen receptor modulation. The evaluation of the model using FDA EDKB and Tox21 data was quite encouraging. This model can also provide a teratogenicity prediction along with the additional information it provides relevant to the query compound, all of which will require careful assessment of potential risk by experts. © 2017 Wiley-VCH Verlag GmbH & Co. KGaA, Weinheim.

Predicting Mycobacterium tuberculosis Complex Clades Using Knowledge-Based Bayesian Networks

PubMed Central

Bennett, Kristin P.

2014-01-01

We develop a novel approach for incorporating expert rules into Bayesian networks for classification of Mycobacterium tuberculosis complex (MTBC) clades. The proposed knowledge-based Bayesian network (KBBN) treats sets of expert rules as prior distributions on the classes. Unlike prior knowledge-based support vector machine approaches which require rules expressed as polyhedral sets, KBBN directly incorporates the rules without any modification. KBBN uses data to refine rule-based classifiers when the rule set is incomplete or ambiguous. We develop a predictive KBBN model for 69 MTBC clades found in the SITVIT international collection. We validate the approach using two testbeds that model knowledge of the MTBC obtained from two different experts and large DNA fingerprint databases to predict MTBC genetic clades and sublineages. These models represent strains of MTBC using high-throughput biomarkers called spacer oligonucleotide types (spoligotypes), since these are routinely gathered from MTBC isolates of tuberculosis (TB) patients. Results show that incorporating rules into problems can drastically increase classification accuracy if data alone are insufficient. The SITVIT KBBN is publicly available for use on the World Wide Web. PMID:24864238

A Statistical Evaluation of the Diagnostic Performance of MEDAS-The Medical Emergency Decision Assistance System

PubMed Central

Georgakis, D. Christine; Trace, David A.; Naeymi-Rad, Frank; Evens, Martha

1990-01-01

Medical expert systems require comprehensive evaluation of their diagnostic accuracy. The usefulness of these systems is limited without established evaluation methods. We propose a new methodology for evaluating the diagnostic accuracy and the predictive capacity of a medical expert system. We have adapted to the medical domain measures that have been used in the social sciences to examine the performance of human experts in the decision making process. Thus, in addition to the standard summary measures, we use measures of agreement and disagreement, and Goodman and Kruskal's λ and τ measures of predictive association. This methodology is illustrated by a detailed retrospective evaluation of the diagnostic accuracy of the MEDAS system. In a study using 270 patients admitted to the North Chicago Veterans Administration Hospital, diagnoses produced by MEDAS are compared with the discharge diagnoses of the attending physicians. The results of the analysis confirm the high diagnostic accuracy and predictive capacity of the MEDAS system. Overall, the agreement of the MEDAS system with the “gold standard” diagnosis of the attending physician has reached a 90% level.

System of experts for intelligent data management (SEIDAM)

NASA Technical Reports Server (NTRS)

Goodenough, David G.; Iisaka, Joji; Fung, KO

1993-01-01

A proposal to conduct research and development on a system of expert systems for intelligent data management (SEIDAM) is being developed. CCRS has much expertise in developing systems for integrating geographic information with space and aircraft remote sensing data and in managing large archives of remotely sensed data. SEIDAM will be composed of expert systems grouped in three levels. At the lowest level, the expert systems will manage and integrate data from diverse sources, taking account of symbolic representation differences and varying accuracies. Existing software can be controlled by these expert systems, without rewriting existing software into an Artificial Intelligence (AI) language. At the second level, SEIDAM will take the interpreted data (symbolic and numerical) and combine these with data models. at the top level, SEIDAM will respond to user goals for predictive outcomes given existing data. The SEIDAM Project will address the research areas of expert systems, data management, storage and retrieval, and user access and interfaces.

System of Experts for Intelligent Data Management (SEIDAM)

NASA Technical Reports Server (NTRS)

Goodenough, David G.; Iisaka, Joji; Fung, KO

1992-01-01

It is proposed to conduct research and development on a system of expert systems for intelligent data management (SEIDAM). CCRS has much expertise in developing systems for integrating geographic information with space and aircraft remote sensing data and in managing large archives of remotely sensed data. SEIDAM will be composed of expert systems grouped in three levels. At the lowest level, the expert systems will manage and integrate data from diverse sources, taking account of symbolic representation differences and varying accuracies. Existing software can be controlled by these expert systems, without rewriting existing software into an Artificial Intelligence (AI) language. At the second level, SEIDAM will take the interpreted data (symbolic and numerical) and combine these with data models. At the top level, SEIDAM will respond to user goals for predictive outcomes given existing data. The SEIDAM Project will address the research areas of expert systems, data management, storage and retrieval, and user access and interfaces.

The influence of expertise on brain activation of the action observation network during anticipation of tennis and volleyball serves

PubMed Central

Balser, Nils; Lorey, Britta; Pilgramm, Sebastian; Naumann, Tim; Kindermann, Stefan; Stark, Rudolf; Zentgraf, Karen; Williams, A. Mark; Munzert, Jörn

2014-01-01

In many daily activities, and especially in sport, it is necessary to predict the effects of others' actions in order to initiate appropriate responses. Recently, researchers have suggested that the action–observation network (AON) including the cerebellum plays an essential role during such anticipation, particularly in sport expert performers. In the present study, we examined the influence of task-specific expertise on the AON by investigating differences between two expert groups trained in different sports while anticipating action effects. Altogether, 15 tennis and 16 volleyball experts anticipated the direction of observed tennis and volleyball serves while undergoing functional magnetic resonance imaging (fMRI). The expert group in each sport acted as novice controls in the other sport with which they had only little experience. When contrasting anticipation in both expertise conditions with the corresponding untrained sport, a stronger activation of AON areas (SPL, SMA), and particularly of cerebellar structures, was observed. Furthermore, the neural activation within the cerebellum and the SPL was linearly correlated with participant's anticipation performance, irrespective of the specific expertise. For the SPL, this relationship also holds when an expert performs a domain-specific anticipation task. Notably, the stronger activation of the cerebellum as well as of the SMA and the SPL in the expertise conditions suggests that experts rely on their more fine-tuned perceptual-motor representations that have improved during years of training when anticipating the effects of others' actions in their preferred sport. The association of activation within the SPL and the cerebellum with the task achievement suggests that these areas are the predominant brain sites involved in fast motor predictions. The SPL reflects the processing of domain-specific contextual information and the cerebellum the usage of a predictive internal model to solve the anticipation task. PMID:25136305

Use of cccupancy models to evaluate expert knowledge-based species-habitat relationships

USGS Publications Warehouse

Iglecia, Monica N.; Collazo, Jaime A.; McKerrow, Alexa

2012-01-01

Expert knowledge-based species-habitat relationships are used extensively to guide conservation planning, particularly when data are scarce. Purported relationships describe the initial state of knowledge, but are rarely tested. We assessed support in the data for suitability rankings of vegetation types based on expert knowledge for three terrestrial avian species in the South Atlantic Coastal Plain of the United States. Experts used published studies, natural history, survey data, and field experience to rank vegetation types as optimal, suitable, and marginal. We used single-season occupancy models, coupled with land cover and Breeding Bird Survey data, to examine the hypothesis that patterns of occupancy conformed to species-habitat suitability rankings purported by experts. Purported habitat suitability was validated for two of three species. As predicted for the Eastern Wood-Pewee (Contopus virens) and Brown-headed Nuthatch (Sitta pusilla), occupancy was strongly influenced by vegetation types classified as “optimal habitat” by the species suitability rankings for nuthatches and wood-pewees. Contrary to predictions, Red-headed Woodpecker (Melanerpes erythrocephalus) models that included vegetation types as covariates received similar support by the data as models without vegetation types. For all three species, occupancy was also related to sampling latitude. Our results suggest that covariates representing other habitat requirements might be necessary to model occurrence of generalist species like the woodpecker. The modeling approach described herein provides a means to test expert knowledge-based species-habitat relationships, and hence, help guide conservation planning.

Shared Mechanisms in the Estimation of Self-Generated Actions and the Prediction of Other’s Actions by Humans

PubMed Central

Ganesh, Gowrishankar

2017-01-01

Abstract The question of how humans predict outcomes of observed motor actions by others is a fundamental problem in cognitive and social neuroscience. Previous theoretical studies have suggested that the brain uses parts of the forward model (used to estimate sensory outcomes of self-generated actions) to predict outcomes of observed actions. However, this hypothesis has remained controversial due to the lack of direct experimental evidence. To address this issue, we analyzed the behavior of darts experts in an understanding learning paradigm and utilized computational modeling to examine how outcome prediction of observed actions affected the participants’ ability to estimate their own actions. We recruited darts experts because sports experts are known to have an accurate outcome estimation of their own actions as well as prediction of actions observed in others. We first show that learning to predict the outcomes of observed dart throws deteriorates an expert’s abilities to both produce his own darts actions and estimate the outcome of his own throws (or self-estimation). Next, we introduce a state-space model to explain the trial-by-trial changes in the darts performance and self-estimation through our experiment. The model-based analysis reveals that the change in an expert’s self-estimation is explained only by considering a change in the individual’s forward model, showing that an improvement in an expert’s ability to predict outcomes of observed actions affects the individual’s forward model. These results suggest that parts of the same forward model are utilized in humans to both estimate outcomes of self-generated actions and predict outcomes of observed actions. PMID:29340300

The prospects for hybrid electric vehicles, 2005-2020 : results of a Delphi Study.

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

Ng, H. K.; Santini, D. J.; Vyas, A. D.

1999-07-22

The introduction of Toyota's hybrid electric vehicle (HEV), the Prius, in Japan has generated considerable interest in HEV technology among US automotive experts. In a follow-up survey to Argonne National Laboratory's two-stage Delphi Study on electric and hybrid electric vehicles (EVs and HEVs) during 1994-1996, Argonne researchers gathered the latest opinions of automotive experts on the future ''top-selling'' HEV attributes and costs. The experts predicted that HEVs would have a spark-ignition gasoline engine as a power plant in 2005 and a fuel cell power plant by 2020. The projected 2020 fuel shares were about equal for gasoline and hydrogen, withmore » methanol a distant third. In 2020, HEVs are predicted to have series-drive, moderate battery-alone range and cost significantly more than conventional vehicles (CVs). The HEV is projected to cost 66% more than a $20,000 CV initially and 33% more by 2020. Survey respondents view batteries as the component that contributes the most to the HEV cost increment. The mean projection for battery-alone range is 49 km in 2005, 70 km in 2010, and 92 km in 2020. Responding to a question relating to their personal vision of the most desirable HEV and its likely characteristics when introduced in the US market in the next decade, the experts predicted their ''vision'' HEV to have attributes very similar to those of the ''top-selling'' HEV. However, the ''vision'' HEV would cost significantly less. The experts projected attributes of three leading batteries for HEVs and projected acceleration times on battery power alone. The resulting battery packs are evaluated, and their initial and replacement costs are analyzed. These and several other opinions are summarized.« less

Catching on it early: Bodily and brain anticipatory mechanisms for excellence in sport.

PubMed

Abreu, Ana M; Candidi, Matteo; Aglioti, Salvatore M

2017-01-01

Programming and executing a subsequent move is inherently linked to the ability to anticipate the actions of others when interacting. Such fundamental social ability is particularly important in sport. Here, we discuss the possible mechanisms behind the highly sophisticated anticipation skills that characterize experts. We contend that prediction in sports might rely on a finely tuned perceptual system that endows experts with a fast, partially unconscious, pickup of relevant cues. Furthermore, we discuss the role of the multimodal, perceptuomotor, multiple-duty cells (mirror neurons) that play an important function in action anticipation by means of an inner motor simulation process. Finally, we suggest the role of predictive coding, interoception, and the enteric nervous system as the processual and biological support for intuition and "gut feelings" in sports-the missing link that might explain outstanding expert performance based on action anticipation. © 2017 Elsevier B.V. All rights reserved.

An expert system for prediction of aquatic toxicity of contaminants

USGS Publications Warehouse

Hickey, James P.; Aldridge, Andrew J.; Passino, Dora R. May; Frank, Anthony M.; Hushon, Judith M.

1990-01-01

The National Fisheries Research Center-Great Lakes has developed an interactive computer program in muLISP that runs on an IBM-compatible microcomputer and uses a linear solvation energy relationship (LSER) to predict acute toxicity to four representative aquatic species from the detailed structure of an organic molecule. Using the SMILES formalism for a chemical structure, the expert system identifies all structural components and uses a knowledge base of rules based on an LSER to generate four structure-related parameter values. A separate module then relates these values to toxicity. The system is designed for rapid screening of potential chemical hazards before laboratory or field investigations are conducted and can be operated by users with little toxicological background. This is the first expert system based on LSER, relying on the first comprehensive compilation of rules and values for the estimation of LSER parameters.

ARGES: an Expert System for Fault Diagnosis Within Space-Based ECLS Systems

NASA Technical Reports Server (NTRS)

Pachura, David W.; Suleiman, Salem A.; Mendler, Andrew P.

1988-01-01

ARGES (Atmospheric Revitalization Group Expert System) is a demonstration prototype expert system for fault management for the Solid Amine, Water Desorbed (SAWD) CO2 removal assembly, associated with the Environmental Control and Life Support (ECLS) System. ARGES monitors and reduces data in real time from either the SAWD controller or a simulation of the SAWD assembly. It can detect gradual degradations or predict failures. This allows graceful shutdown and scheduled maintenance, which reduces crew maintenance overhead. Status and fault information is presented in a user interface that simulates what would be seen by a crewperson. The user interface employs animated color graphics and an object oriented approach to provide detailed status information, fault identification, and explanation of reasoning in a rapidly assimulated manner. In addition, ARGES recommends possible courses of action for predicted and actual faults. ARGES is seen as a forerunner of AI-based fault management systems for manned space systems.

The Evonik-Mainz Eye Care-Study (EMECS): Development of an Expert System for Glaucoma Risk Detection in a Working Population

PubMed Central

Wahl, Jochen; Barleon, Lorenz; Morfeld, Peter; Lichtmeß, Andrea; Haas-Brähler, Sibylle; Pfeiffer, Norbert

2016-01-01

Purpose To develop an expert system for glaucoma screening in a working population based on a human expert procedure using images of optic nerve head (ONH), visual field (frequency doubling technology, FDT) and intraocular pressure (IOP). Methods 4167 of 13037 (32%) employees between 40 and 65 years of Evonik Industries were screened. An experienced glaucoma expert (JW) assessed papilla parameters and evaluated all individual screening results. His classification into “no glaucoma”, “possible glaucoma” and “probable glaucoma” was defined as “gold standard”. A screening model was developed which was tested versus the gold-standard. This model took into account the assessment of the ONH. Values and relationships of CDR and IOP and the FDT were considered additionally and a glaucoma score was generated. The structure of the screening model was specified a priori whereas values of the parameters were chosen post-hoc to optimize sensitivity and specificity of the algorithm. Simple screening models based on IOP and / or FDT were investigated for comparison. Results 111 persons (2.66%) were classified as glaucoma suspects, thereof 13 (0.31%) as probable and 98 (2.35%) as possible glaucoma suspects by the expert. Re-evaluation by the screening model revealed a sensitivity of 83.8% and a specificity of 99.6% for all glaucoma suspects. The positive predictive value of the model was 80.2%, the negative predictive value 99.6%. Simple screening models showed insufficient diagnostic accuracy. Conclusion Adjustment of ONH and symmetry parameters with respect to excavation and IOP in an expert system produced sufficiently satisfying diagnostic accuracy. This screening model seems to be applicable in such a working population with relatively low age and low glaucoma prevalence. Different experts should validate the model in different populations. PMID:27479301

The Evonik-Mainz Eye Care-Study (EMECS): Development of an Expert System for Glaucoma Risk Detection in a Working Population.

PubMed

Wahl, Jochen; Barleon, Lorenz; Morfeld, Peter; Lichtmeß, Andrea; Haas-Brähler, Sibylle; Pfeiffer, Norbert

2016-01-01

To develop an expert system for glaucoma screening in a working population based on a human expert procedure using images of optic nerve head (ONH), visual field (frequency doubling technology, FDT) and intraocular pressure (IOP). 4167 of 13037 (32%) employees between 40 and 65 years of Evonik Industries were screened. An experienced glaucoma expert (JW) assessed papilla parameters and evaluated all individual screening results. His classification into "no glaucoma", "possible glaucoma" and "probable glaucoma" was defined as "gold standard". A screening model was developed which was tested versus the gold-standard. This model took into account the assessment of the ONH. Values and relationships of CDR and IOP and the FDT were considered additionally and a glaucoma score was generated. The structure of the screening model was specified a priori whereas values of the parameters were chosen post-hoc to optimize sensitivity and specificity of the algorithm. Simple screening models based on IOP and / or FDT were investigated for comparison. 111 persons (2.66%) were classified as glaucoma suspects, thereof 13 (0.31%) as probable and 98 (2.35%) as possible glaucoma suspects by the expert. Re-evaluation by the screening model revealed a sensitivity of 83.8% and a specificity of 99.6% for all glaucoma suspects. The positive predictive value of the model was 80.2%, the negative predictive value 99.6%. Simple screening models showed insufficient diagnostic accuracy. Adjustment of ONH and symmetry parameters with respect to excavation and IOP in an expert system produced sufficiently satisfying diagnostic accuracy. This screening model seems to be applicable in such a working population with relatively low age and low glaucoma prevalence. Different experts should validate the model in different populations.

WHEN AND WHY DO HEDGEHOGS AND FOXES DIFFER?

PubMed

Keil, Frank C

2010-01-01

Philip E. Tetlock's finding that "hedgehog" experts (those with one big theory) are worse predictors than "foxes" (those with multiple, less comprehensive theories) offers fertile ground for future research. Are experts as likely to exhibit hedgehog- or fox-like tendencies in areas that call for explanatory, diagnostic, and skill-based expertise-as they did when Tetlock called on experts to make predictions? Do particular domains of expertise curtail or encourage different styles of expertise? Can we trace these different styles to childhood? Finally, can we nudge hedgehogs to be more like foxes? Current research can only grope at the answers to these questions, but they are essential to gauging the health of expert political judgment.

Prospective Analysis of Behavioral Economic Predictors of Stable Moderation Drinking Among Problem Drinkers Attempting Natural Recovery

PubMed Central

Tucker, Jalie A.; Cheong, JeeWon; Chandler, Susan D.; Lambert, Brice H.; Pietrzak, Brittney; Kwok, Heather; Davies, Susan L.

2016-01-01

Background As interventions have expanded beyond clinical treatment to include brief interventions for persons with less severe alcohol problems, predicting who can achieve stable moderation drinking has gained importance. Recent behavioral economic (BE) research on natural recovery has shown that active problem drinkers who allocate their monetary expenditures on alcohol and saving for the future over longer time horizons tend to have better subsequent recovery outcomes, including maintenance of stable moderation drinking. The present study compared the predictive utility of this money-based “Alcohol-Savings Discretionary Expenditure” (ASDE) index with multiple BE analogue measures of behavioral impulsivity and self-control, which have seldom been investigated together, to predict outcomes of natural recovery attempts. Methods Community-dwelling problem drinkers, enrolled shortly after stopping abusive drinking without treatment, were followed prospectively for up to a year (N = 175 [75.4% male], M age = 50.65 years). They completed baseline assessments of pre-resolution drinking practices and problems; analogue behavioral choice tasks (Delay Discounting, Melioration-Maximization, and Alcohol Purchase Tasks); and a Timeline Followback interview including expenditures on alcohol compared to voluntary savings (ASDE index) during the pre-resolution year. Results Multinomial logistic regression models showed that, among the BE measures, only the ASDE index predicted stable moderation drinking compared to stable abstinence or unstable resolutions involving relapse. As hypothesized, stable moderation was associated with more balanced pre-resolution allocations to drinking and savings (OR = 1.77, 95% CI = 1.02 ∼ 3.08, p < .05), suggesting it is associated with longer term behavior regulation processes than abstinence. Conclusions The ASDE's unique predictive utility may rest on its comprehensive representation of contextual elements to support this patterning of behavioral allocation. Stable low risk drinking, but not abstinence, requires such regulatory processes. PMID:27775161

Experts and the Operational Bias of Television News: The Case of the Persian Gulf War.

ERIC Educational Resources Information Center

Steele, Janet E.

1995-01-01

Finds that news organizations chose expert sources to interpret the news during the Persian Gulf War according to how well their specialized knowledge conformed with television's "operational bias," or an emphasis on players, policies, and predictions of what will happen next. Argues that these processes undermine the ideals of balance…

AN EXPERT SYSTEM FOR HYDRODYNAMIC MIXING ZONE ANAYLSIS OF CONVENTIONAL AND TOXIC SUBMERGED SINGLE PORT DISCHARGES (CORMIX1)

EPA Science Inventory

U.S. water quality policy includes the concept of a mixing zone, a limited area or volume of water where the initial dilution of a discharge occurs. he Cornell Mixing Zone Expert System (CORMIX1) was developed to predict the dilution and trajectory of a submerged single port disc...

Predicting and explaining the movement of mesoscale oceanographic features using CLIPS

NASA Technical Reports Server (NTRS)

Bridges, Susan; Chen, Liang-Chun; Lybanon, Matthew

1994-01-01

The Naval Research Laboratory has developed an oceanographic expert system that describes the evolution of mesoscale features in the Gulf Stream region of the northwest Atlantic Ocean. These features include the Gulf Stream current and the warm and cold core eddies associated with the Gulf Stream. An explanation capability was added to the eddy prediction component of the expert system in order to allow the system to justify the reasoning process it uses to make predictions. The eddy prediction and explanation components of the system have recently been redesigned and translated from OPS83 to C and CLIPS and the new system is called WATE (Where Are Those Eddies). The new design has improved the system's readability, understandability and maintainability and will also allow the system to be incorporated into the Semi-Automated Mesoscale Analysis System which will eventually be embedded into the Navy's Tactical Environmental Support System, Third Generation, TESS(3).

Evolving biomarkers improve prediction of long-term mortality in patients with stable coronary artery disease: the BIO-VILCAD score.

PubMed

Kleber, M E; Goliasch, G; Grammer, T B; Pilz, S; Tomaschitz, A; Silbernagel, G; Maurer, G; März, W; Niessner, A

2014-08-01

Algorithms to predict the future long-term risk of patients with stable coronary artery disease (CAD) are rare. The VIenna and Ludwigshafen CAD (VILCAD) risk score was one of the first scores specifically tailored for this clinically important patient population. The aim of this study was to refine risk prediction in stable CAD creating a new prediction model encompassing various pathophysiological pathways. Therefore, we assessed the predictive power of 135 novel biomarkers for long-term mortality in patients with stable CAD. We included 1275 patients with stable CAD from the LUdwigshafen RIsk and Cardiovascular health study with a median follow-up of 9.8 years to investigate whether the predictive power of the VILCAD score could be improved by the addition of novel biomarkers. Additional biomarkers were selected in a bootstrapping procedure based on Cox regression to determine the most informative predictors of mortality. The final multivariable model encompassed nine clinical and biochemical markers: age, sex, left ventricular ejection fraction (LVEF), heart rate, N-terminal pro-brain natriuretic peptide, cystatin C, renin, 25OH-vitamin D3 and haemoglobin A1c. The extended VILCAD biomarker score achieved a significantly improved C-statistic (0.78 vs. 0.73; P = 0.035) and net reclassification index (14.9%; P < 0.001) compared to the original VILCAD score. Omitting LVEF, which might not be readily measureable in clinical practice, slightly reduced the accuracy of the new BIO-VILCAD score but still significantly improved risk classification (net reclassification improvement 12.5%; P < 0.001). The VILCAD biomarker score based on routine parameters complemented by novel biomarkers outperforms previous risk algorithms and allows more accurate classification of patients with stable CAD, enabling physicians to choose more personalized treatment regimens for their patients.

Application of predictive modelling techniques in industry: from food design up to risk assessment.

PubMed

Membré, Jeanne-Marie; Lambert, Ronald J W

2008-11-30

In this communication, examples of applications of predictive microbiology in industrial contexts (i.e. Nestlé and Unilever) are presented which cover a range of applications in food safety from formulation and process design to consumer safety risk assessment. A tailor-made, private expert system, developed to support safe product/process design assessment is introduced as an example of how predictive models can be deployed for use by non-experts. Its use in conjunction with other tools and software available in the public domain is discussed. Specific applications of predictive microbiology techniques are presented relating to investigations of either growth or limits to growth with respect to product formulation or process conditions. An example of a probabilistic exposure assessment model for chilled food application is provided and its potential added value as a food safety management tool in an industrial context is weighed against its disadvantages. The role of predictive microbiology in the suite of tools available to food industry and some of its advantages and constraints are discussed.

Thinking about Language: What Political Theorists Need to Know about Language in the Real World

ERIC Educational Resources Information Center

Ricento, Thomas

2014-01-01

Political theorists, generally non-experts in the language sciences, whose principal aim is often to advance normative theories on desirable states of affairs within liberal democratic states, tend to deal with language as a stable nominal category, as something that one "has" or "doesn't have", that can be labeled as one…

Work after Prison: One-Year Findings from the Transitional Jobs Reentry Demonstration

ERIC Educational Resources Information Center

Redcross, Cindy; Bloom, Dan; Jacobs, Erin; Manno, Michelle; Muller-Ravett, Sara; Seefeldt, Kristin; Yahner, Jennifer; Young, Alford A., Jr.; Zweig, Janine

2010-01-01

More than 2 million people are incarcerated in the United States, and around 700,000 are released from prison each year. Those who are released face daunting obstacles as they seek to reenter their communities, and rates of recidivism are high. Many experts believe that stable employment is critical to a successful transition from prison to the…

Work after Prison: One-Year Findings from the Transitional Jobs Reentry Demonstration. Executive Summary

ERIC Educational Resources Information Center

Redcross, Cindy; Bloom, Dan; Jacobs, Erin; Manno, Michelle; Muller-Ravett, Sara; Seefeldt, Kristin; Yahner, Jennifer; Young, Alford A., Jr.; Zweig, Janine

2010-01-01

More than 2 million people are incarcerated in the United States, and around 700,000 are released from prison each year. Those who are released face daunting obstacles as they seek to reenter their communities, and rates of recidivism are high. Many experts believe that stable employment is critical to a successful transition from prison to the…

Analyses of Buckling and Stable Tearing in Thin-Sheet Materials

NASA Technical Reports Server (NTRS)

Seshadri, B. R.; Newman, J. C., Jr.

1998-01-01

This paper was to verify the STAGS (general shell, geometric and material nonlinear) code and the critical crack tip opening angle (CTOA) fracture criterion for predicting stable tearing in cracked panels that fail with severe out of plane buckling. Materials considered ranged from brittle to ductile behavior. Test data used in this study are reported elsewhere. The STAGS code was used to model stable tearing using a critical CTOA value that was determined from a cracked panel that was 'restrained' from buckling. ne analysis methodology was then used to predict the influence of buckling on stable tearing and failure loads. Parameters like crack length to specimen width ratio, crack configuration, thickness, and material tensile properties had a significant influence on the buckling behavior of cracked thin sheet materials. Experimental and predicted results showed a varied buckling response for different crack length to sheet thickness ratios because different buckling modes were activated. Effects of material tensile properties and fracture toughness on buckling response were presented. The STAGS code and the CTOA fracture criterion were able to predict the influence of buckling on stable tearing behavior and failure loads on a variety of materials and crack configurations.

The ALICE-HMPID Detector Control System: Its evolution towards an expert and adaptive system

NASA Astrophysics Data System (ADS)

De Cataldo, G.; Franco, A.; Pastore, C.; Sgura, I.; Volpe, G.

2011-05-01

The High Momentum Particle IDentification (HMPID) detector is a proximity focusing Ring Imaging Cherenkov (RICH) for charged hadron identification. The HMPID is based on liquid C 6F 14 as the radiator medium and on a 10 m 2 CsI coated, pad segmented photocathode of MWPCs for UV Cherenkov photon detection. To ensure full remote control, the HMPID is equipped with a detector control system (DCS) responding to industrial standards for robustness and reliability. It has been implemented using PVSS as Slow Control And Data Acquisition (SCADA) environment, Programmable Logic Controller as control devices and Finite State Machines for modular and automatic command execution. In the perspective of reducing human presence at the experiment site, this paper focuses on DCS evolution towards an expert and adaptive control system, providing, respectively, automatic error recovery and stable detector performance. HAL9000, the first prototype of the HMPID expert system, is then presented. Finally an analysis of the possible application of the adaptive features is provided.

Climate Prediction Center - Expert Assessments: East Pacific Hurricane

Science.gov Websites

influence seasonal eastern Pacific hurricane activity, along with climate model forecasts. The outlook also National Weather Service NWS logo - Click to go to the NWS home page Climate Prediction Center Site Map Administration (NOAA) Climate Prediction Center (CPC), and is produced in collaboration with scientists from the

A topological substructural molecular design approach for predicting mutagenesis end-points of alpha, beta-unsaturated carbonyl compounds.

PubMed

Pérez-Garrido, Alfonso; Helguera, Aliuska Morales; López, Gabriel Caravaca; Cordeiro, M Natália D S; Escudero, Amalio Garrido

2010-01-31

Chemically reactive, alpha, beta-unsaturated carbonyl compounds are common environmental pollutants able to produce a wide range of adverse effects, including, e.g. mutagenicity. This toxic property can often be related to chemical structure, in particular to specific molecular substructures or fragments (alerts), which can then be used in specialized software or expert systems for predictive purposes. In the past, there have been many attempts to predict the mutagenicity of alpha, beta-unsaturated carbonyl compounds through quantitative structure activity relationships (QSAR) but considering only one exclusive endpoint: the Ames test. Besides, even though those studies give a comprehensive understanding of the phenomenon, they do not provide substructural information that could be useful forward improving expert systems based on structural alerts (SAs). This work reports an evaluation of classification models to probe the mutagenic activity of alpha, beta-unsaturated carbonyl compounds over two endpoints--the Ames and mammalian cell gene mutation tests--based on linear discriminant analysis along with the topological Substructure molecular design (TOPS-MODE) approach. The obtained results showed the better ability of the TOPS-MODE approach in flagging structural alerts for the mutagenicity of these compounds compared to the expert system TOXTREE. Thus, the application of the present QSAR models can aid toxicologists in risk assessment and in prioritizing testing, as well as in the improvement of expert systems, such as the TOXTREE software, where SAs are implemented. 2009 Elsevier Ireland Ltd. All rights reserved.

Examining corporate reputation judgments with generalizability theory.

PubMed

Highhouse, Scott; Broadfoot, Alison; Yugo, Jennifer E; Devendorf, Shelba A

2009-05-01

The researchers used generalizability theory to examine whether reputation judgments about corporations function in a manner consistent with contemporary theory in the corporate-reputation literature. University professors (n = 86) of finance, marketing, and human resources management made repeated judgments about the general reputations of highly visible American companies. Minimal variability in the judgments is explained by items, time, persons, and field of specialization. Moreover, experts from the different specializations reveal considerable agreement in how they weigh different aspects of corporate performance in arriving at their global reputation judgments. The results generally support the theory of the reputation construct and suggest that stable estimates of global reputation can be achieved with a small number of items and experts. (c) 2009 APA, all rights reserved.

Referral Consultant: An Expert System for Guiding Teachers in Referring Students for Special Education Placement. Final Report.

ERIC Educational Resources Information Center

Baer, Richard; And Others

In light of evidence indicating that referral itself often predicts student placement, an expert system was designed to assist educators to reduce bias in the process of referring students with suspected disabilities. A preliminary review of the literature looks at teacher perceptions as a predictor of handicapping conditions, referral bias, and…

Expertise facilitates the transfer of anticipation skill across domains.

PubMed

Rosalie, Simon M; Müller, Sean

2014-02-01

It is unclear whether perceptual-motor skill transfer is based upon similarity between the learning and transfer domains per identical elements theory, or facilitated by an understanding of underlying principles in accordance with general principle theory. Here, the predictions of identical elements theory, general principle theory, and aspects of a recently proposed model for the transfer of perceptual-motor skill with respect to expertise in the learning and transfer domains are examined. The capabilities of expert karate athletes, near-expert karate athletes, and novices to anticipate and respond to stimulus skills derived from taekwondo and Australian football were investigated in ecologically valid contexts using an in situ temporal occlusion paradigm and complex whole-body perceptual-motor skills. Results indicated that the karate experts and near-experts are as capable of using visual information to anticipate and guide motor skill responses as domain experts and near-experts in the taekwondo transfer domain, but only karate experts could perform like domain experts in the Australian football transfer domain. Findings suggest that transfer of anticipation skill is based upon expertise and an understanding of principles but may be supplemented by similarities that exist between the stimulus and response elements of the learning and transfer domains.

Expert elicitation survey on future wind energy costs

DOE PAGES

Wiser, Ryan; Jenni, Karen; Seel, Joachim; ...

2016-09-12

Wind energy supply has grown rapidly over the last decade. However, the long-term contribution of wind to future energy supply, and the degree to which policy support is necessary to motivate higher levels of deployment, depends - in part - on the future costs of both onshore and offshore wind. In this paper, we summarize the results of an expert elicitation survey of 163 of the world's foremost wind experts, aimed at better understanding future costs and technology advancement possibilities. Results suggest significant opportunities for cost reductions, but also underlying uncertainties. Under the median scenario, experts anticipate 24-30% reductions bymore » 2030 and 35-41% reductions by 2050 across the three wind applications studied. Costs could be even lower: experts predict a 10% chance that reductions will be more than 40% by 2030 and more than 50% by 2050. Insights gained through expert elicitation complement other tools for evaluating cost-reduction potential, and help inform policy and planning, R & D and industry strategy.« less

Expert elicitation survey on future wind energy costs

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

Wiser, Ryan; Jenni, Karen; Seel, Joachim

Wind energy supply has grown rapidly over the last decade. However, the long-term contribution of wind to future energy supply, and the degree to which policy support is necessary to motivate higher levels of deployment, depends -- in part -- on the future costs of both onshore and offshore wind. Here, we summarize the results of an expert elicitation survey of 163 of the world's foremost wind experts, aimed at better understanding future costs and technology advancement possibilities. Results suggest significant opportunities for cost reductions, but also underlying uncertainties. Under the median scenario, experts anticipate 24-30% reductions by 2030 andmore » 35-41% reductions by 2050 across the three wind applications studied. Costs could be even lower: experts predict a 10% chance that reductions will be more than 40% by 2030 and more than 50% by 2050. Insights gained through expert elicitation complement other tools for evaluating cost-reduction potential, and help inform policy and planning, R&D and industry strategy.« less

Expert elicitation survey on future wind energy costs

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

Wiser, Ryan; Jenni, Karen; Seel, Joachim

Wind energy supply has grown rapidly over the last decade. However, the long-term contribution of wind to future energy supply, and the degree to which policy support is necessary to motivate higher levels of deployment, depends - in part - on the future costs of both onshore and offshore wind. In this paper, we summarize the results of an expert elicitation survey of 163 of the world's foremost wind experts, aimed at better understanding future costs and technology advancement possibilities. Results suggest significant opportunities for cost reductions, but also underlying uncertainties. Under the median scenario, experts anticipate 24-30% reductions bymore » 2030 and 35-41% reductions by 2050 across the three wind applications studied. Costs could be even lower: experts predict a 10% chance that reductions will be more than 40% by 2030 and more than 50% by 2050. Insights gained through expert elicitation complement other tools for evaluating cost-reduction potential, and help inform policy and planning, R & D and industry strategy.« less

Developing a comprehensive training curriculum for integrated predictive maintenance

NASA Astrophysics Data System (ADS)

Wurzbach, Richard N.

2002-03-01

On-line equipment condition monitoring is a critical component of the world-class production and safety histories of many successful nuclear plant operators. From addressing availability and operability concerns of nuclear safety-related equipment to increasing profitability through support system reliability and reduced maintenance costs, Predictive Maintenance programs have increasingly become a vital contribution to the maintenance and operation decisions of nuclear facilities. In recent years, significant advancements have been made in the quality and portability of many of the instruments being used, and software improvements have been made as well. However, the single most influential component of the success of these programs is the impact of a trained and experienced team of personnel putting this technology to work. Changes in the nature of the power generation industry brought on by competition, mergers, and acquisitions, has taken the historically stable personnel environment of power generation and created a very dynamic situation. As a result, many facilities have seen a significant turnover in personnel in key positions, including predictive maintenance personnel. It has become the challenge for many nuclear operators to maintain the consistent contribution of quality data and information from predictive maintenance that has become important in the overall equipment decision process. These challenges can be met through the implementation of quality training to predictive maintenance personnel and regular updating and re-certification of key technology holders. The use of data management tools and services aid in the sharing of information across sites within an operating company, and with experts who can contribute value-added data management and analysis. The overall effectiveness of predictive maintenance programs can be improved through the incorporation of newly developed comprehensive technology training courses. These courses address the use of key technologies such as vibration analysis, infrared thermography, and oil analysis not as singular entities, but as a toolbox resource from which to address overall equipment and plant reliability in a structured program and decision environment.

Network approaches for expert decisions in sports.

PubMed

Glöckner, Andreas; Heinen, Thomas; Johnson, Joseph G; Raab, Markus

2012-04-01

This paper focuses on a model comparison to explain choices based on gaze behavior via simulation procedures. We tested two classes of models, a parallel constraint satisfaction (PCS) artificial neuronal network model and an accumulator model in a handball decision-making task from a lab experiment. Both models predict action in an option-generation task in which options can be chosen from the perspective of a playmaker in handball (i.e., passing to another player or shooting at the goal). Model simulations are based on a dataset of generated options together with gaze behavior measurements from 74 expert handball players for 22 pieces of video footage. We implemented both classes of models as deterministic vs. probabilistic models including and excluding fitted parameters. Results indicated that both classes of models can fit and predict participants' initially generated options based on gaze behavior data, and that overall, the classes of models performed about equally well. Early fixations were thereby particularly predictive for choices. We conclude that the analyses of complex environments via network approaches can be successfully applied to the field of experts' decision making in sports and provide perspectives for further theoretical developments. Copyright © 2011 Elsevier B.V. All rights reserved.

WHEN AND WHY DO HEDGEHOGS AND FOXES DIFFER?

PubMed Central

Keil, Frank C.

2011-01-01

Philip E. Tetlock’s finding that “hedgehog” experts (those with one big theory) are worse predictors than “foxes” (those with multiple, less comprehensive theories) offers fertile ground for future research. Are experts as likely to exhibit hedgehog- or fox-like tendencies in areas that call for explanatory, diagnostic, and skill-based expertise—as they did when Tetlock called on experts to make predictions? Do particular domains of expertise curtail or encourage different styles of expertise? Can we trace these different styles to childhood? Finally, can we nudge hedgehogs to be more like foxes? Current research can only grope at the answers to these questions, but they are essential to gauging the health of expert political judgment. PMID:21698070

A Conjoint Analysis Framework for Evaluating User Preferences in Machine Translation

PubMed Central

Kirchhoff, Katrin; Capurro, Daniel; Turner, Anne M.

2013-01-01

Despite much research on machine translation (MT) evaluation, there is surprisingly little work that directly measures users’ intuitive or emotional preferences regarding different types of MT errors. However, the elicitation and modeling of user preferences is an important prerequisite for research on user adaptation and customization of MT engines. In this paper we explore the use of conjoint analysis as a formal quantitative framework to assess users’ relative preferences for different types of translation errors. We apply our approach to the analysis of MT output from translating public health documents from English into Spanish. Our results indicate that word order errors are clearly the most dispreferred error type, followed by word sense, morphological, and function word errors. The conjoint analysis-based model is able to predict user preferences more accurately than a baseline model that chooses the translation with the fewest errors overall. Additionally we analyze the effect of using a crowd-sourced respondent population versus a sample of domain experts and observe that main preference effects are remarkably stable across the two samples. PMID:24683295

Waste treatment by bacterial additions

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

Deutsch, D.J.; Stigall, E.; Barth, E.

1979-04-23

Companies such as General Environmental Science Corp. and Polybac Corp., which market specialized bacterial cultures for treating industrial wastes, claim that the cultures improve the operation of activated-sludge, trickling-filter, and lagoon-treatment plants, and provide faster system response to startups, variable and shock loads, and cold weather. The effectiveness of the special cultures is difficult to verify and has been questioned by environmental experts, including R. L. Raymond (Suntech Inc.) and E. Barth (EPA), although E. Stigall (EPA) believes they may aid plant recovery after upsets. A study by Business Communications Co. has predicted that the market for such additives willmore » reach $50 million by 1987, from $5 million in 1979. The use of such cultures in Exxon Corp.'s 1 million gal/day activated sludge system at the Benicia, Calif., oil refinery improved the system's performance by 32Vertical Bar3<, resulted in faster unit startups and more stable operation, and reduced foaming. J. T. Baker Co. has used successfully two broad-spectrum dried additives for ammonia removal and hydrocarbon degradation at its 3 million gal/day secondary treatment plant at Phillipsburg, N.J.« less

Use (and abuse) of expert elicitation in support of decision making for public policy

PubMed Central

Morgan, M. Granger

2014-01-01

The elicitation of scientific and technical judgments from experts, in the form of subjective probability distributions, can be a valuable addition to other forms of evidence in support of public policy decision making. This paper explores when it is sensible to perform such elicitation and how that can best be done. A number of key issues are discussed, including topics on which there are, and are not, experts who have knowledge that provides a basis for making informed predictive judgments; the inadequacy of only using qualitative uncertainty language; the role of cognitive heuristics and of overconfidence; the choice of experts; the development, refinement, and iterative testing of elicitation protocols that are designed to help experts to consider systematically all relevant knowledge when they make their judgments; the treatment of uncertainty about model functional form; diversity of expert opinion; and when it does or does not make sense to combine judgments from different experts. Although it may be tempting to view expert elicitation as a low-cost, low-effort alternative to conducting serious research and analysis, it is neither. Rather, expert elicitation should build on and use the best available research and analysis and be undertaken only when, given those, the state of knowledge will remain insufficient to support timely informed assessment and decision making. PMID:24821779

Spelling is Just a Click Away - A User-Centered Brain-Computer Interface Including Auto-Calibration and Predictive Text Entry.

PubMed

Kaufmann, Tobias; Völker, Stefan; Gunesch, Laura; Kübler, Andrea

2012-01-01

Brain-computer interfaces (BCI) based on event-related potentials (ERP) allow for selection of characters from a visually presented character-matrix and thus provide a communication channel for users with neurodegenerative disease. Although they have been topic of research for more than 20 years and were multiply proven to be a reliable communication method, BCIs are almost exclusively used in experimental settings, handled by qualified experts. This study investigates if ERP-BCIs can be handled independently by laymen without expert support, which is inevitable for establishing BCIs in end-user's daily life situations. Furthermore we compared the classic character-by-character text entry against a predictive text entry (PTE) that directly incorporates predictive text into the character-matrix. N = 19 BCI novices handled a user-centered ERP-BCI application on their own without expert support. The software individually adjusted classifier weights and control parameters in the background, invisible to the user (auto-calibration). All participants were able to operate the software on their own and to twice correctly spell a sentence with the auto-calibrated classifier (once with PTE, once without). Our PTE increased spelling speed and, importantly, did not reduce accuracy. In sum, this study demonstrates feasibility of auto-calibrating ERP-BCI use, independently by laymen and the strong benefit of integrating predictive text directly into the character-matrix.

Spelling is Just a Click Away – A User-Centered Brain–Computer Interface Including Auto-Calibration and Predictive Text Entry

PubMed Central

Kaufmann, Tobias; Völker, Stefan; Gunesch, Laura; Kübler, Andrea

2012-01-01

Brain–computer interfaces (BCI) based on event-related potentials (ERP) allow for selection of characters from a visually presented character-matrix and thus provide a communication channel for users with neurodegenerative disease. Although they have been topic of research for more than 20 years and were multiply proven to be a reliable communication method, BCIs are almost exclusively used in experimental settings, handled by qualified experts. This study investigates if ERP–BCIs can be handled independently by laymen without expert support, which is inevitable for establishing BCIs in end-user’s daily life situations. Furthermore we compared the classic character-by-character text entry against a predictive text entry (PTE) that directly incorporates predictive text into the character-matrix. N = 19 BCI novices handled a user-centered ERP–BCI application on their own without expert support. The software individually adjusted classifier weights and control parameters in the background, invisible to the user (auto-calibration). All participants were able to operate the software on their own and to twice correctly spell a sentence with the auto-calibrated classifier (once with PTE, once without). Our PTE increased spelling speed and, importantly, did not reduce accuracy. In sum, this study demonstrates feasibility of auto-calibrating ERP–BCI use, independently by laymen and the strong benefit of integrating predictive text directly into the character-matrix. PMID:22833713

What defines an Expert? - Uncertainty in the interpretation of seismic data

NASA Astrophysics Data System (ADS)

Bond, C. E.

2008-12-01

Studies focusing on the elicitation of information from experts are concentrated primarily in economics and world markets, medical practice and expert witness testimonies. Expert elicitation theory has been applied in the natural sciences, most notably in the prediction of fluid flow in hydrological studies. In the geological sciences expert elicitation has been limited to theoretical analysis with studies focusing on the elicitation element, gaining expert opinion rather than necessarily understanding the basis behind the expert view. In these cases experts are defined in a traditional sense, based for example on: standing in the field, no. of years of experience, no. of peer reviewed publications, the experts position in a company hierarchy or academia. Here traditional indicators of expertise have been compared for significance on affective seismic interpretation. Polytomous regression analysis has been used to assess the relative significance of length and type of experience on the outcome of a seismic interpretation exercise. Following the initial analysis the techniques used by participants to interpret the seismic image were added as additional variables to the analysis. Specific technical skills and techniques were found to be more important for the affective geological interpretation of seismic data than the traditional indicators of expertise. The results of a seismic interpretation exercise, the techniques used to interpret the seismic and the participant's prior experience have been combined and analysed to answer the question - who is and what defines an expert?

As of 2012, what are the key predictive risk factors for pressure ulcers? Developing French guidelines for clinical practice.

PubMed

Michel, J-M; Willebois, S; Ribinik, P; Barrois, B; Colin, D; Passadori, Y

2012-10-01

An evaluation of predictive risk factors for pressure ulcers is essential in development of a preventive strategy on admission to hospitals and/or nursing homes. Identification of the predictive factors for pressure ulcers as of 2012. Systematic review of the literature querying the databases PASCAL Biomed, Cochrane Library and PubMed from 2000 through 2010. Immobility should be considered as a predictive risk factor for pressure ulcers (grade B). Undernutrition/malnutrition may also be a predictive risk factor for pressure ulcers (grade C). Even if the level of evidence is low, once these risk factors have been detected, management is essential. Sensitizing and mobilizing health care teams requires training in ways of tracking and screening. According to the experts, risk scales should be used. As decision aids, they should always be balanced and complemented by the clinical judgment of the treatment team. According to experts, it is important to know and predictively evaluate risk of pressure ulcers at the time of hospital admission. The predictive risk factors found in this study are identical to those highlighted at the 2001 consensus conference of which was PERSE was the promoter. Copyright © 2012. Published by Elsevier Masson SAS.

Use of visible and near-infrared spectroscopy to predict pork longissimus lean color stability.

PubMed

King, D A; Shackelford, S D; Wheeler, T L

2011-12-01

This study evaluated the use of visible and near-infrared (VISNIR) spectroscopy to predict lean color stability in pork loin chops. Spectra were collected immediately after and approximately 1 h after rib removal on 1,208 loins. Loins were aged for 14 d before a 2.54-cm chop was placed in simulated retail display. Spectra were collected on aged loins immediately after removal from the vacuum package and on chops 10 min after cutting. Instrumental color measurements [L*, a*, b*, hue angle, chroma, and E (overall color change)] were determined on d 0, 1, 7, 11, and 14 of display. Principal components analysis of display d 0 and 14 values of these traits identified a factor (first principal component; PC1) explaining 67% of the variance that was related to color change. Partial least squares regression was used to develop 3 models to predict PC1 values by using VISNIR spectra collected in the plant, on aged loins, and on chops. Loins with predicted PC1 values less than 0 were classified as having a stable color, whereas values greater than 0 were classified as having a labile lean color. Loins classified as stable by the in-plant model had smaller (P < 0.05) L* values than those classified as labile. Hue angle and ΔE values were less (P < 0.05) and a* and chroma values were greater (P < 0.05) after d 7 of display in loins predicted to have a stable color than in loins predicted to have a labile lean color. Similarly, chops from loins classified as stable using the aged loin model had smaller (P < 0.05) L* values than those from loins classified as labile. Furthermore, loins predicted to be stable had smaller (P < 0.05) hue angle and ΔE values and greater (P < 0.05) a* and chroma values after d 7 of display than did loins predicted to be labile. Results for the chop model were similar to those from the 2 loin models. Chops predicted to have a stable lean color had smaller (P < 0.05) L* values than did those predicted to have a labile lean color. Chops classified as stable had smaller (P < 0.05) hue angle and ΔE values and greater (P < 0.05) a* and chroma values after d 7 of display compared with chops classified as labile. All 3 models effectively segregated chops based on color stability, particularly with regard to redness. Regardless of the model being used, d 14 display values for a*, hue angle, and ΔE in loins classified as stable were similar to the d 7 values of loins classified as labile. Thus, these results suggest that VISNIR spectroscopy would be an effective technology for sorting pork loins with regard to lean color stability.

The Prediction of Item Parameters Based on Classical Test Theory and Latent Trait Theory

ERIC Educational Resources Information Center

Anil, Duygu

2008-01-01

In this study, the prediction power of the item characteristics based on the experts' predictions on conditions try-out practices cannot be applied was examined for item characteristics computed depending on classical test theory and two-parameters logistic model of latent trait theory. The study was carried out on 9914 randomly selected students…

Generalizable Aspects of the Development of Expertise in Ballet across Countries and Cultures: A Perspective from the Expert-Performance Approach

ERIC Educational Resources Information Center

Hutchinson, Carla U.; Sachs-Ericsson, Natalie J.; Ericsson, K. Anders

2013-01-01

The expert-performance approach guided the collection of survey data on the developmental history of elite professional ballet dancers from three different countries/cultures (USA, Mexico, and Russia). The level of ballet expertise attained by age 18 was found to be uniquely predicted by only two factors, namely the total number of accumulated…

Expert system and process optimization techniques for real-time monitoring and control of plasma processes

NASA Astrophysics Data System (ADS)

Cheng, Jie; Qian, Zhaogang; Irani, Keki B.; Etemad, Hossein; Elta, Michael E.

1991-03-01

To meet the ever-increasing demand of the rapidly-growing semiconductor manufacturing industry it is critical to have a comprehensive methodology integrating techniques for process optimization real-time monitoring and adaptive process control. To this end we have accomplished an integrated knowledge-based approach combining latest expert system technology machine learning method and traditional statistical process control (SPC) techniques. This knowledge-based approach is advantageous in that it makes it possible for the task of process optimization and adaptive control to be performed consistently and predictably. Furthermore this approach can be used to construct high-level and qualitative description of processes and thus make the process behavior easy to monitor predict and control. Two software packages RIST (Rule Induction and Statistical Testing) and KARSM (Knowledge Acquisition from Response Surface Methodology) have been developed and incorporated with two commercially available packages G2 (real-time expert system) and ULTRAMAX (a tool for sequential process optimization).

Expert panel consensus recommendations for home blood pressure monitoring in Asia: the Hope Asia Network.

PubMed

Park, Sungha; Buranakitjaroen, Peera; Chen, Chen-Huan; Chia, Yook-Chin; Divinagracia, Romeo; Hoshide, Satoshi; Shin, Jinho; Siddique, Saulat; Sison, Jorge; Soenarta, Arieska Ann; Sogunuru, Guru Prasad; Tay, Jam Chin; Turana, Yuda; Wang, Ji-Guang; Zhang, Yuqing; Kario, Kazuomi

2018-04-01

Hypertension is the leading cause of mortality throughout Asia. Home blood pressure monitoring has the potential to improve hypertension control and is a useful adjunct to conventional office blood pressure measurements due to its diagnostic accuracy and prognostic value in predicting cardiovascular outcomes. At present, there are no region-specific guidelines addressing the use of home blood pressure monitoring in Asia. Therefore, an expert panel was convened to address the use of home blood pressure monitoring and develop key recommendations to help guide clinical practice throughout the Asia region. The resulting recommendations support the use of home blood pressure monitoring with a validated device as an accurate adjunct for diagnosing hypertension and predicting cardiovascular outcome. Diagnosis and treatment of hypertension should still be guided by conventional office/clinic blood pressure measurements. The expert panel encourages the incorporation of home blood pressure monitoring into local clinical guidelines and offers practical recommendations to ensure continuity of care where a validated home blood pressure device is not available.

"The cough game": are there characteristic urethrovesical movement patterns associated with stress incontinence?

PubMed

Lewicky-Gaupp, Christina; Blaivas, Jerry; Clark, Amanda; McGuire, Edward J; Schaer, Gabriel; Tumbarello, Julie; Tunn, Ralf; DeLancey, John O L

2009-02-01

This study was carried out to determine whether five experts in female stress urinary incontinence (SUI) could discover a pattern of urethrovesical movement characteristic of SUI on dynamic perineal ultrasound. A secondary analysis of data from a case-control study was performed. Ultrasounds from 31 cases (daily SUI) and 42 controls (continent volunteers) of similar age and parity were analyzed. Perineal ultrasound was performed during a single cough. The five experts, blinded to continence status and urodynamics, classified each woman as stress continent or incontinent. Correct responses ranged from 45.7% to 65.8% (mean 57.4 +/- 7.6). Sensitivity was 53.0 +/- 8.8% and specificity 61.2 +/- 12.4%. The positive predictive value was 48.8 +/- 8.2% and negative predictive value was 65.0 +/- 7.3%. Inter-rater reliability, evaluated by Cohen's kappa statistic, averaged 0.47 [95% CI 0.40-0.50]. Experts could not identify a pattern of urethrovesical movement characteristic of SUI on ultrasound.

“The Cough Game”: Are there characteristic urethrovesical movement patterns associated with stress incontinence?

PubMed Central

LEWICKY-GAUPP, Christina; BLAIVAS, Jerry; CLARK, Amanda; McGUIRE, Edward J.; SCHAER, Gabriel; TUMBARELLO, Julie; TUNN, Ralf; DeLANCEY, John O.L.

2009-01-01

Introduction and Hypothesis To determine if 5 experts in female stress urinary incontinence (SUI) could discover a pattern of urethrovesical movement characteristic of SUI on dynamic perineal ultrasound. Methods A secondary analysis of data from a case-control study was performed. Ultrasounds from 31 cases (daily SUI) and 42 controls (continent volunteers) of similar age and parity were analyzed. Perineal ultrasound was performed during a single cough. The 5 experts, blinded to continence status and urodynamics, classified each woman as stress continent or incontinent. Results Correct responses ranged from 45.7% to 65.8% (mean 57.4 ± 7.6). Sensitivity was 53.0 ± 8.8% and specificity 61.2 ± 12.4%. The positive predictive value was 48.8 ± 8.2% and negative predictive value was 65.0 ± 7.3%. Inter-rater reliability, evaluated by Cohen's kappa statistic, averaged 0.47 [95% CI 0.40 – 0.50]. Conclusions Experts could not identify a pattern of urethrovesical movement characteristic of SUI on ultrasound. PMID:18850057

Automated robot-assisted surgical skill evaluation: Predictive analytics approach.

PubMed

Fard, Mahtab J; Ameri, Sattar; Darin Ellis, R; Chinnam, Ratna B; Pandya, Abhilash K; Klein, Michael D

2018-02-01

Surgical skill assessment has predominantly been a subjective task. Recently, technological advances such as robot-assisted surgery have created great opportunities for objective surgical evaluation. In this paper, we introduce a predictive framework for objective skill assessment based on movement trajectory data. Our aim is to build a classification framework to automatically evaluate the performance of surgeons with different levels of expertise. Eight global movement features are extracted from movement trajectory data captured by a da Vinci robot for surgeons with two levels of expertise - novice and expert. Three classification methods - k-nearest neighbours, logistic regression and support vector machines - are applied. The result shows that the proposed framework can classify surgeons' expertise as novice or expert with an accuracy of 82.3% for knot tying and 89.9% for a suturing task. This study demonstrates and evaluates the ability of machine learning methods to automatically classify expert and novice surgeons using global movement features. Copyright © 2017 John Wiley & Sons, Ltd.

Prospective Analysis of Behavioral Economic Predictors of Stable Moderation Drinking Among Problem Drinkers Attempting Natural Recovery.

PubMed

Tucker, Jalie A; Cheong, JeeWon; Chandler, Susan D; Lambert, Brice H; Pietrzak, Brittney; Kwok, Heather; Davies, Susan L

2016-12-01

As interventions have expanded beyond clinical treatment to include brief interventions for persons with less severe alcohol problems, predicting who can achieve stable moderation drinking has gained importance. Recent behavioral economic (BE) research on natural recovery has shown that active problem drinkers who allocate their monetary expenditures on alcohol and saving for the future over longer time horizons tend to have better subsequent recovery outcomes, including maintenance of stable moderation drinking. This study compared the predictive utility of this money-based "Alcohol-Savings Discretionary Expenditure" (ASDE) index with multiple BE analogue measures of behavioral impulsivity and self-control, which have seldom been investigated together, to predict outcomes of natural recovery attempts. Community-dwelling problem drinkers, enrolled shortly after stopping abusive drinking without treatment, were followed prospectively for up to a year (N = 175 [75.4% male], M age = 50.65 years). They completed baseline assessments of preresolution drinking practices and problems, analogue behavioral choice tasks (Delay Discounting, Melioration-Maximization, and Alcohol Purchase Tasks), and a Timeline Followback interview including expenditures on alcohol compared to voluntary savings (ASDE index) during the preresolution year. Multinomial logistic regression models showed that, among the BE measures, only the ASDE index predicted stable moderation drinking compared to stable abstinence or unstable resolutions involving relapse. As hypothesized, stable moderation was associated with more balanced preresolution allocations to drinking and savings (odds ratio = 1.77, 95% confidence interval = 1.02 to 3.08, p < 0.05), suggesting it is associated with longer-term behavior regulation processes than abstinence. The ASDE's unique predictive utility may rest on its comprehensive representation of contextual elements to support this patterning of behavioral allocation. Stable low-risk drinking, but not abstinence, requires such regulatory processes. Copyright © 2016 by the Research Society on Alcoholism.

Overview of the status of predictive computer models for skin sensitization (JRC Expert meeting on pre- and pro-haptens )

EPA Science Inventory

No abstract was prepared or requested. This is a short presentation aiming to present a status of what in silico models and approaches exists in the prediction of skin sensitization potential and/or potency.

Smallholder farms as stepping stone corridors for crop-raiding elephant in northern Tanzania: integration of Bayesian expert system and network simulator.

PubMed

Pittiglio, Claudia; Skidmore, Andrew K; van Gils, Hein A M J; McCall, Michael K; Prins, Herbert H T

2014-03-01

Crop-raiding elephants affect local livelihoods, undermining conservation efforts. Yet, crop-raiding patterns are poorly understood, making prediction and protection difficult. We hypothesized that raiding elephants use corridors between daytime refuges and farmland. Elephant counts, crop-raiding records, household surveys, Bayesian expert system, and least-cost path simulation were used to predict four alternative categories of daily corridors: (1) footpaths, (2) dry river beds, (3) stepping stones along scattered small farms, and (4) trajectories of shortest distance to refuges. The corridor alignments were compared in terms of their minimum cumulative resistance to elephant movement and related to crop-raiding zones quantified by a kernel density function. The "stepping stone" corridors predicted the crop-raiding patterns. Elephant presence was confirmed along these corridors, demonstrating that small farms located between refuges and contiguous farmland increase habitat connectivity for elephant. Our analysis successfully predicted elephant occurrence in farmland where daytime counts failed to detect nocturnal presence. These results have conservation management implications.

Combination and selection of traffic safety expert judgments for the prevention of driving risks.

PubMed

Cabello, Enrique; Conde, Cristina; de Diego, Isaac Martín; Moguerza, Javier M; Redchuk, Andrés

2012-11-02

In this paper, we describe a new framework to combine experts’ judgments for the prevention of driving risks in a cabin truck. In addition, the methodology shows how to choose among the experts the one whose predictions fit best the environmental conditions. The methodology is applied over data sets obtained from a high immersive cabin truck simulator in natural driving conditions. A nonparametric model, based in Nearest Neighbors combined with Restricted Least Squared methods is developed. Three experts were asked to evaluate the driving risk using a Visual Analog Scale (VAS), in order to measure the driving risk in a truck simulator where the vehicle dynamics factors were stored. Numerical results show that the methodology is suitable for embedding in real time systems.

Dual-component video image analysis system (VIASCAN) as a predictor of beef carcass red meat yield percentage and for augmenting application of USDA yield grades.

PubMed

Cannell, R C; Tatum, J D; Belk, K E; Wise, J W; Clayton, R P; Smith, G C

1999-11-01

An improved ability to quantify differences in the fabrication yields of beef carcasses would facilitate the application of value-based marketing. This study was conducted to evaluate the ability of the Dual-Component Australian VIASCAN to 1) predict fabricated beef subprimal yields as a percentage of carcass weight at each of three fat-trim levels and 2) augment USDA yield grading, thereby improving accuracy of grade placement. Steer and heifer carcasses (n = 240) were evaluated using VIASCAN, as well as by USDA expert and online graders, before fabrication of carcasses to each of three fat-trim levels. Expert yield grade (YG), online YG, VIASCAN estimates, and VIASCAN estimated ribeye area used to augment actual and expert grader estimates of the remaining YG factors (adjusted fat thickness, percentage of kidney-pelvic-heart fat, and hot carcass weight), respectively, 1) accounted for 51, 37, 46, and 55% of the variation in fabricated yields of commodity-trimmed subprimals, 2) accounted for 74, 54, 66, and 75% of the variation in fabricated yields of closely trimmed subprimals, and 3) accounted for 74, 54, 71, and 75% of the variation in fabricated yields of very closely trimmed subprimals. The VIASCAN system predicted fabrication yields more accurately than current online yield grading and, when certain VIASCAN-measured traits were combined with some USDA yield grade factors in an augmentation system, the accuracy of cutability prediction was improved, at packing plant line speeds, to a level matching that of expert graders applying grades at a comfortable rate.

Orbitofrontal Cortex Signals Expected Outcomes with Predictive Codes When Stable Contingencies Promote the Integration of Reward History

PubMed Central

Shapiro, Matthew L.

2017-01-01

Memory can inform goal-directed behavior by linking current opportunities to past outcomes. The orbitofrontal cortex (OFC) may guide value-based responses by integrating the history of stimulus–reward associations into expected outcomes, representations of predicted hedonic value and quality. Alternatively, the OFC may rapidly compute flexible “online” reward predictions by associating stimuli with the latest outcome. OFC neurons develop predictive codes when rats learn to associate arbitrary stimuli with outcomes, but the extent to which predictive coding depends on most recent events and the integrated history of rewards is unclear. To investigate how reward history modulates OFC activity, we recorded OFC ensembles as rats performed spatial discriminations that differed only in the number of rewarded trials between goal reversals. The firing rate of single OFC neurons distinguished identical behaviors guided by different goals. When >20 rewarded trials separated goal switches, OFC ensembles developed stable and anticorrelated population vectors that predicted overall choice accuracy and the goal selected in single trials. When <10 rewarded trials separated goal switches, OFC population vectors decorrelated rapidly after each switch, but did not develop anticorrelated firing patterns or predict choice accuracy. The results show that, whereas OFC signals respond rapidly to contingency changes, they predict choices only when reward history is relatively stable, suggesting that consecutive rewarded episodes are needed for OFC computations that integrate reward history into expected outcomes. SIGNIFICANCE STATEMENT Adapting to changing contingencies and making decisions engages the orbitofrontal cortex (OFC). Previous work shows that OFC function can either improve or impair learning depending on reward stability, suggesting that OFC guides behavior optimally when contingencies apply consistently. The mechanisms that link reward history to OFC computations remain obscure. Here, we examined OFC unit activity as rodents performed tasks controlled by contingencies that varied reward history. When contingencies were stable, OFC neurons signaled past, present, and pending events; when contingencies were unstable, past and present coding persisted, but predictive coding diminished. The results suggest that OFC mechanisms require stable contingencies across consecutive episodes to integrate reward history, represent predicted outcomes, and inform goal-directed choices. PMID:28115481

Cardiac risk stratification in renal transplantation using a form of artificial intelligence.

PubMed

Heston, T F; Norman, D J; Barry, J M; Bennett, W M; Wilson, R A

1997-02-15

The purpose of this study was to determine if an expert network, a form of artificial intelligence, could effectively stratify cardiac risk in candidates for renal transplant. Input into the expert network consisted of clinical risk factors and thallium-201 stress test data. Clinical risk factor screening alone identified 95 of 189 patients as high risk. These 95 patients underwent thallium-201 stress testing, and 53 had either reversible or fixed defects. The other 42 patients were classified as low risk. This algorithm made up the "expert system," and during the 4-year follow-up period had a sensitivity of 82%, specificity of 77%, and accuracy of 78%. An artificial neural network was added to the expert system, creating an expert network. Input into the neural network consisted of both clinical variables and thallium-201 stress test data. There were 5 hidden nodes and the output (end point) was cardiac death. The expert network increased the specificity of the expert system alone from 77% to 90% (p < 0.001), the accuracy from 78% to 89% (p < 0.005), and maintained the overall sensitivity at 88%. An expert network based on clinical risk factor screening and thallium-201 stress testing had an accuracy of 89% in predicting the 4-year cardiac mortality among 189 renal transplant candidates.

Brain mechanisms of persuasion: how 'expert power' modulates memory and attitudes.

PubMed

Klucharev, Vasily; Smidts, Ale; Fernández, Guillén

2008-12-01

Human behaviour is affected by various forms of persuasion. The general persuasive effect of high expertise of the communicator, often referred to as 'expert power', is well documented. We found that a single exposure to a combination of an expert and an object leads to a long-lasting positive effect on memory for and attitude towards the object. Using functional magnetic resonance imaging, we probed the neural processes predicting these behavioural effects. Expert context was associated with distributed left-lateralized brain activity in prefrontal and temporal cortices related to active semantic elaboration. Furthermore, experts enhanced subsequent memory effects in the medial temporal lobe (i.e. in hippocampus and parahippocampal gyrus) involved in memory formation. Experts also affected subsequent attitude effects in the caudate nucleus involved in trustful behaviour, reward processing and learning. These results may suggest that the persuasive effect of experts is mediated by modulation of caudate activity resulting in a re-evaluation of the object in terms of its perceived value. Results extend our view of the functional role of the dorsal striatum in social interaction and enable us to make the first steps toward a neuroscientific model of persuasion.

Brain mechanisms of persuasion: how ‘expert power’ modulates memory and attitudes

PubMed Central

Smidts, Ale; Fernández, Guillén

2008-01-01

Human behaviour is affected by various forms of persuasion. The general persuasive effect of high expertise of the communicator, often referred to as ’expert power’, is well documented. We found that a single exposure to a combination of an expert and an object leads to a long-lasting positive effect on memory for and attitude towards the object. Using functional magnetic resonance imaging, we probed the neural processes predicting these behavioural effects. Expert context was associated with distributed left-lateralized brain activity in prefrontal and temporal cortices related to active semantic elaboration. Furthermore, experts enhanced subsequent memory effects in the medial temporal lobe (i.e. in hippocampus and parahippocampal gyrus) involved in memory formation. Experts also affected subsequent attitude effects in the caudate nucleus involved in trustful behaviour, reward processing and learning. These results may suggest that the persuasive effect of experts is mediated by modulation of caudate activity resulting in a re-evaluation of the object in terms of its perceived value. Results extend our view of the functional role of the dorsal striatum in social interaction and enable us to make the first steps toward a neuroscientific model of persuasion. PMID:19015077

The Development of Selective Copying: Children's Learning from an Expert versus Their Mother

ERIC Educational Resources Information Center

Lucas, Amanda J.; Burdett, Emily R. R.; Burgess, Vanessa; Wood, Lara A.; McGuigan, Nicola; Harris, Paul L.; Whiten, Andrew

2017-01-01

This study tested the prediction that, with age, children should rely less on familiarity and more on expertise in their selective social learning. Experiment 1 (N = 50) found that 5- to 6-year-olds copied the technique their mother used to extract a prize from a novel puzzle box, in preference to both a stranger and an established expert. This…

Evidence reasoning method for constructing conditional probability tables in a Bayesian network of multimorbidity.

PubMed

Du, Yuanwei; Guo, Yubin

2015-01-01

The intrinsic mechanism of multimorbidity is difficult to recognize and prediction and diagnosis are difficult to carry out accordingly. Bayesian networks can help to diagnose multimorbidity in health care, but it is difficult to obtain the conditional probability table (CPT) because of the lack of clinically statistical data. Today, expert knowledge and experience are increasingly used in training Bayesian networks in order to help predict or diagnose diseases, but the CPT in Bayesian networks is usually irrational or ineffective for ignoring realistic constraints especially in multimorbidity. In order to solve these problems, an evidence reasoning (ER) approach is employed to extract and fuse inference data from experts using a belief distribution and recursive ER algorithm, based on which evidence reasoning method for constructing conditional probability tables in Bayesian network of multimorbidity is presented step by step. A multimorbidity numerical example is used to demonstrate the method and prove its feasibility and application. Bayesian network can be determined as long as the inference assessment is inferred by each expert according to his/her knowledge or experience. Our method is more effective than existing methods for extracting expert inference data accurately and is fused effectively for constructing CPTs in a Bayesian network of multimorbidity.

Future leisure environments

Treesearch

Elwood L. Shafer; George H. Moeller; Russell E. Getty

1974-01-01

As an aid to policy- and decision-making about future environmental problems, a panel of experts was asked to predict the probabilities of future events associated with natural-resource management, wildland-recreation management, environmental pollution, population-workforce-leisure, and urban environments. Though some of the predictions projected to the year 2050 may...

Expert identification of visual primitives used by CNNs during mammogram classification

NASA Astrophysics Data System (ADS)

Wu, Jimmy; Peck, Diondra; Hsieh, Scott; Dialani, Vandana; Lehman, Constance D.; Zhou, Bolei; Syrgkanis, Vasilis; Mackey, Lester; Patterson, Genevieve

2018-02-01

This work interprets the internal representations of deep neural networks trained for classification of diseased tissue in 2D mammograms. We propose an expert-in-the-loop inter- pretation method to label the behavior of internal units in convolutional neural networks (CNNs). Expert radiologists identify that the visual patterns detected by the units are correlated with meaningful medical phenomena such as mass tissue and calcificated vessels. We demonstrate that several trained CNN models are able to produce explanatory descriptions to support the final classification decisions. We view this as an important first step toward interpreting the internal representations of medical classification CNNs and explaining their predictions.

Complex method to calculate objective assessments of information systems protection to improve expert assessments reliability

NASA Astrophysics Data System (ADS)

Abdenov, A. Zh; Trushin, V. A.; Abdenova, G. A.

2018-01-01

The paper considers the questions of filling the relevant SIEM nodes based on calculations of objective assessments in order to improve the reliability of subjective expert assessments. The proposed methodology is necessary for the most accurate security risk assessment of information systems. This technique is also intended for the purpose of establishing real-time operational information protection in the enterprise information systems. Risk calculations are based on objective estimates of the adverse events implementation probabilities, predictions of the damage magnitude from information security violations. Calculations of objective assessments are necessary to increase the reliability of the proposed expert assessments.

Beef quality grading using machine vision

NASA Astrophysics Data System (ADS)

Jeyamkondan, S.; Ray, N.; Kranzler, Glenn A.; Biju, Nisha

2000-12-01

A video image analysis system was developed to support automation of beef quality grading. Forty images of ribeye steaks were acquired. Fat and lean meat were differentiated using a fuzzy c-means clustering algorithm. Muscle longissimus dorsi (l.d.) was segmented from the ribeye using morphological operations. At the end of each iteration of erosion and dilation, a convex hull was fitted to the image and compactness was measured. The number of iterations was selected to yield the most compact l.d. Match between the l.d. muscle traced by an expert grader and that segmented by the program was 95.9%. Marbling and color features were extracted from the l.d. muscle and were used to build regression models to predict marbling and color scores. Quality grade was predicted using another regression model incorporating all features. Grades predicted by the model were statistically equivalent to the grades assigned by expert graders.

Ironic and Reinvestment Effects in Baseball Pitching: How Information About an Opponent Can Influence Performance Under Pressure.

PubMed

Gray, Rob; Orn, Anders; Woodman, Tim

2017-02-01

Are pressure-induced performance errors in experts associated with novice-like skill execution (as predicted by reinvestment/conscious processing theories) or expert execution toward a result that the performer typically intends to avoid (as predicted by ironic processes theory)? The present study directly compared these predictions using a baseball pitching task with two groups of experienced pitchers. One group was shown only their target, while the other group was shown the target and an ironic (avoid) zone. Both groups demonstrated significantly fewer target hits under pressure. For the target-only group, this was accompanied by significant changes in expertise-related kinematic variables. In the ironic group, the number of pitches thrown in the ironic zone was significantly higher under pressure, and there were no significant changes in kinematics. These results suggest that information about an opponent can influence the mechanisms underlying pressure-induced performance errors.

An expert system for prediction of chemical toxicity

USGS Publications Warehouse

Hickey, James P.; Aldridge, Andrew J.; Passino-Reader, Dora R.; Frank, Anthony M.

1992-01-01

The National Fisheries Research Center- Great Lakes has developed an interactive computer program that uses the structure of an organic molecule to predict its acute toxicity to four aquatic species. The expert system software, written in the muLISP language, identifies the skeletal structures and substituent groups of an organic molecule from a user-supplied standard chemical notation known as a SMILES string, and then generates values for four solvatochromic parameters. Multiple regression equations relate these parameters to the toxicities (expressed as log10LC50s and log10EC50s, along with 95% confidence intervals) for four species. The system is demonstrated by prediction of toxicity for anilide-type pesticides to the fathead minnow (Pimephales promelas). This software is designed for use on an IBM-compatible personal computer by personnel with minimal toxicology background for rapid estimation of chemical toxicity. The system has numerous applications, with much potential for use in the pharmaceutical industry

Automated Predictive Diagnosis (APD): A 3-tiered shell for building expert systems for automated predictions and decision making

NASA Technical Reports Server (NTRS)

Steib, Michael

1991-01-01

The APD software features include: On-line help, Three level architecture, (Logic environments, Setup/Application environment, Data environment), Explanation capability, and File handling. The kinds of experimentation and record keeping that leads to effective expert systems is facilitated by: (1) a library of inferencing modules (in the logic environment); (2) an explanation capability which reveals logic strategies to users; (3) automated file naming conventions; (4) an information retrieval system; and (5) on-line help. These aid with effective use of knowledge, debugging and experimentation. Since the APD software anticipates the logical rules becoming complicated, it is embedded in a production system language (CLIPS) to insure the full power of the production system paradigm of CLIPS and availability of the procedural language C. The development is discussed of the APD software and three example applications: toy, experimental, and operational prototype for submarine maintenance predictions.

Adaptive neuro-fuzzy and expert systems for power quality analysis and prediction of abnormal operation

NASA Astrophysics Data System (ADS)

Ibrahim, Wael Refaat Anis

The present research involves the development of several fuzzy expert systems for power quality analysis and diagnosis. Intelligent systems for the prediction of abnormal system operation were also developed. The performance of all intelligent modules developed was either enhanced or completely produced through adaptive fuzzy learning techniques. Neuro-fuzzy learning is the main adaptive technique utilized. The work presents a novel approach to the interpretation of power quality from the perspective of the continuous operation of a single system. The research includes an extensive literature review pertaining to the applications of intelligent systems to power quality analysis. Basic definitions and signature events related to power quality are introduced. In addition, detailed discussions of various artificial intelligence paradigms as well as wavelet theory are included. A fuzzy-based intelligent system capable of identifying normal from abnormal operation for a given system was developed. Adaptive neuro-fuzzy learning was applied to enhance its performance. A group of fuzzy expert systems that could perform full operational diagnosis were also developed successfully. The developed systems were applied to the operational diagnosis of 3-phase induction motors and rectifier bridges. A novel approach for learning power quality waveforms and trends was developed. The technique, which is adaptive neuro fuzzy-based, learned, compressed, and stored the waveform data. The new technique was successfully tested using a wide variety of power quality signature waveforms, and using real site data. The trend-learning technique was incorporated into a fuzzy expert system that was designed to predict abnormal operation of a monitored system. The intelligent system learns and stores, in compressed format, trends leading to abnormal operation. The system then compares incoming data to the retained trends continuously. If the incoming data matches any of the learned trends, an alarm is instigated predicting the advent of system abnormal operation. The incoming data could be compared to previous trends as well as matched to trends developed through computer simulations and stored using fuzzy learning.

[National disease management guidelines (NVL) for chronic CAD : What is new, what is particularly important?].

PubMed

Werdan, K

2016-09-01

Coronary heart disease (CAD) is widespread and affects 1 in 10 of the population in the age group 40-79 years in Germany. The German national management guidelines on chronic CAD comprise evidence and expert-based recommendations for the diagnostics of chronic stable CAD as well as for interdisciplinary/multidisciplinary therapy and care of patients with stable CAD. The focus is on the diagnostics, prevention, medication therapy, revascularization, rehabilitation, general practitioner care and coordination of care. Recommendations for optimizing cooperation between all medical specialties involved as well as the definition of mandatory and appropriate measures are essential aims of the guidelines both to improve the quality of care and to strengthen the position of the patient.

[Development and Application of a Performance Prediction Model for Home Care Nursing Based on a Balanced Scorecard using the Bayesian Belief Network].

PubMed

Noh, Wonjung; Seomun, Gyeongae

2015-06-01

This study was conducted to develop key performance indicators (KPIs) for home care nursing (HCN) based on a balanced scorecard, and to construct a performance prediction model of strategic objectives using the Bayesian Belief Network (BBN). This methodological study included four steps: establishment of KPIs, performance prediction modeling, development of a performance prediction model using BBN, and simulation of a suggested nursing management strategy. An HCN expert group and a staff group participated. The content validity index was analyzed using STATA 13.0, and BBN was analyzed using HUGIN 8.0. We generated a list of KPIs composed of 4 perspectives, 10 strategic objectives, and 31 KPIs. In the validity test of the performance prediction model, the factor with the greatest variance for increasing profit was maximum cost reduction of HCN services. The factor with the smallest variance for increasing profit was a minimum image improvement for HCN. During sensitivity analysis, the probability of the expert group did not affect the sensitivity. Furthermore, simulation of a 10% image improvement predicted the most effective way to increase profit. KPIs of HCN can estimate financial and non-financial performance. The performance prediction model for HCN will be useful to improve performance.

20170921 - An evaluation of selected (Q)SARs/expert systems for the Prediction of Skin Sensitization Potential (ASCCT)

EPA Science Inventory

Predictive testing to characterize substances for their skin sensitization potential has historically been based on animal models such as the Local Lymph Node Assay (LLNA) and the Guinea Pig Maximization Test (GPMT). In recent years, EU regulations have provided a strong incentiv...

Stable Isotope Ratio and Elemental Profile Combined with Support Vector Machine for Provenance Discrimination of Oolong Tea (Wuyi-Rock Tea)

PubMed Central

Lou, Yun-xiao; Fu, Xian-shu; Yu, Xiao-ping; Zhang, Ya-fen

2017-01-01

This paper focused on an effective method to discriminate the geographical origin of Wuyi-Rock tea by the stable isotope ratio (SIR) and metallic element profiling (MEP) combined with support vector machine (SVM) analysis. Wuyi-Rock tea (n = 99) collected from nine producing areas and non-Wuyi-Rock tea (n = 33) from eleven nonproducing areas were analysed for SIR and MEP by established methods. The SVM model based on coupled data produced the best prediction accuracy (0.9773). This prediction shows that instrumental methods combined with a classification model can provide an effective and stable tool for provenance discrimination. Moreover, every feature variable in stable isotope and metallic element data was ranked by its contribution to the model. The results show that δ2H, δ18O, Cs, Cu, Ca, and Rb contents are significant indications for provenance discrimination and not all of the metallic elements improve the prediction accuracy of the SVM model. PMID:28473941

STEMing the tide: using ingroup experts to inoculate women's self-concept in science, technology, engineering, and mathematics (STEM).

PubMed

Stout, Jane G; Dasgupta, Nilanjana; Hunsinger, Matthew; McManus, Melissa A

2011-02-01

Three studies tested a stereotype inoculation model, which proposed that contact with same-sex experts (advanced peers, professionals, professors) in academic environments involving science, technology, engineering, and mathematics (STEM) enhances women's self-concept in STEM, attitudes toward STEM, and motivation to pursue STEM careers. Two cross-sectional controlled experiments and 1 longitudinal naturalistic study in a calculus class revealed that exposure to female STEM experts promoted positive implicit attitudes and stronger implicit identification with STEM (Studies 1-3), greater self-efficacy in STEM (Study 3), and more effort on STEM tests (Study 1). Studies 2 and 3 suggested that the benefit of seeing same-sex experts is driven by greater subjective identification and connectedness with these individuals, which in turn predicts enhanced self-efficacy, domain identification, and commitment to pursue STEM careers. Importantly, women's own self-concept benefited from contact with female experts even though negative stereotypes about their gender and STEM remained active. (PsycINFO Database Record (c) 2010 APA, all rights reserved).

Holistic processing of musical notation: Dissociating failures of selective attention in experts and novices.

PubMed

Wong, Yetta Kwailing; Gauthier, Isabel

2010-12-01

Holistic processing (i.e., the tendency to process objects as wholes) is associated with face perception and also with expertise individuating novel objects. Surprisingly, recent work also reveals holistic effects in novice observers. It is unclear whether the same mechanisms support holistic effects in experts and in novices. In the present study, we measured holistic processing of music sequences using a selective attention task in participants who vary in music-reading expertise. We found that holistic effects were strategic in novices but were relatively automatic in experts. Correlational analyses revealed that individual holistic effects were predicted by both individual music-reading ability and neural responses for musical notation in the right fusiform face area (rFFA), but in opposite directions for experts and novices, suggesting that holistic effects in the two groups may be of different natures. To characterize expert perception, it is important not only to measure the tendency to process objects as wholes, but also to test whether this effect is dependent on task constraints.

A rule-based expert system applied to moisture durability of building envelopes

DOE PAGES

Boudreaux, Philip R.; Pallin, Simon B.; Accawi, Gina K.; ...

2018-01-09

The moisture durability of an envelope component such as a wall or roof is difficult to predict. Moisture durability depends on all the construction materials used, as well as the climate, orientation, air tightness, and indoor conditions. Modern building codes require more insulation and tighter construction but provide little guidance about how to ensure these energy-efficient assemblies remain moisture durable. Furthermore, as new products and materials are introduced, builders are increasingly uncertain about the long-term durability of their building envelope designs. Oak Ridge National Laboratory and the US Department of Energy’s Building America Program are applying a rule-based expert systemmore » methodology in a web tool to help designers determine whether a given wall design is likely to be moisture durable and provide expert guidance on moisture risk management specific to a wall design and climate. Finally, the expert system is populated with knowledge from both expert judgment and probabilistic hygrothermal simulation results.« less

A rule-based expert system applied to moisture durability of building envelopes

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

Boudreaux, Philip R.; Pallin, Simon B.; Accawi, Gina K.

The moisture durability of an envelope component such as a wall or roof is difficult to predict. Moisture durability depends on all the construction materials used, as well as the climate, orientation, air tightness, and indoor conditions. Modern building codes require more insulation and tighter construction but provide little guidance about how to ensure these energy-efficient assemblies remain moisture durable. Furthermore, as new products and materials are introduced, builders are increasingly uncertain about the long-term durability of their building envelope designs. Oak Ridge National Laboratory and the US Department of Energy’s Building America Program are applying a rule-based expert systemmore » methodology in a web tool to help designers determine whether a given wall design is likely to be moisture durable and provide expert guidance on moisture risk management specific to a wall design and climate. Finally, the expert system is populated with knowledge from both expert judgment and probabilistic hygrothermal simulation results.« less

Risk taking in adversarial situations: Civilization differences in chess experts.

PubMed

Chassy, Philippe; Gobet, Fernand

2015-08-01

The projections of experts in politics predict that a new world order will emerge within two decades. Being multipolar, this world will inevitably lead to frictions where civilizations and states will have to decide whether to risk conflict. Very often these decisions are informed if not taken by experts. To estimate risk-taking across civilizations, we examined strategies used in 667,599 chess games played over eleven years by chess experts from 11 different civilizations. We show that some civilizations are more inclined to settle for peace. Similarly, we show that once engaged in the battle, the level of risk taking varies significantly across civilizations, the boldest civilization using the riskiest strategy about 35% more than the most conservative civilization. We discuss which psychological factors might underpin these civilizational differences. Copyright © 2015. Published by Elsevier B.V.

Use of an expert system data analysis manager for space shuttle main engine test evaluation

NASA Technical Reports Server (NTRS)

Abernethy, Ken

1988-01-01

The ability to articulate, collect, and automate the application of the expertise needed for the analysis of space shuttle main engine (SSME) test data would be of great benefit to NASA liquid rocket engine experts. This paper describes a project whose goal is to build a rule-based expert system which incorporates such expertise. Experiential expertise, collected directly from the experts currently involved in SSME data analysis, is used to build a rule base to identify engine anomalies similar to those analyzed previously. Additionally, an alternate method of expertise capture is being explored. This method would generate rules inductively based on calculations made using a theoretical model of the SSME's operation. The latter rules would be capable of diagnosing anomalies which may not have appeared before, but whose effects can be predicted by the theoretical model.

Monocyte to HDL ratio in prediction of BMS restenosis in subjects with stable and unstable angina pectoris.

PubMed

Tok, Derya; Turak, Osman; Yayla, Çağrı; Ozcan, Fırat; Tok, Duran; Çağlı, Kumral

2016-08-01

This study aims to assess the predictive role of the preprocedural circulating monocyte to high-density lipoprotein (HDL) cholesterol ratio (MHR) on the occurrence of stent restenosis (SR) in patients with stable and unstable angina pectoris undergoing successful bare-metal stenting (BMS). Between February 2008 and June 2014, a total of 831 patients with stable and unstable angina pectoris who underwent successful BMS were retrospectively analyzed. Demographic and clinical characteristics of the patients were recorded. Left ventricular ejection fraction and laboratory data were also noted. In the receiver operating characteristics curve analysis, MHR >14 had 71% sensitivity and 69% specificity in predicting SR. Our study results show that preprocedural MHR is an independent predictor of SR in this patient population.

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

Pilat, Joseph F

The application of the methodology developed by the GenIV International Forum's (GIF's) Proliferation Resistance and Physical Protection (PR&PP) Working Group is an expert elicitation. Although the framework of the methodology is structured and systematic, it does not by itself constitute or require a formal elicitation. However, formal elicitation can be utilized in the PR&PP context to provide a systematic, credible and transparent qualitative analysis and develop input for quantitative analyses. This section provides an overview of expert elicitations, a discussion of the role formal expert elicitations can play in the PR&PP methodology, an outline of the formal expert elicitation processmore » and a brief practical guide to conducting formal expert elicitations. Expert elicitation is a process utilizing knowledgeable people in cases, for example, when an assessment is needed but physically based data is absent or open to interpretation. More specifically, it can be used to: (1) predict future events; (2) provide estimates on new, rare, complex or poorly understood phenomena; (3) integrate or interpret existing information; or (4) determine what is currently known, how well it is known or what is worth learning in a field. Expert elicitation can be informal or formal. The informal application of expert judgment is frequently used. Although it can produce good results, it often provides demonstrably biased or otherwise flawed answers to problems. This along with the absence of transparency can result in a loss of confidence when experts speak on issues. More formal expert elicitation is a structured process that makes use of people knowledgeable in certain areas to make assessments. The reason for advocating formal use is that the quality and accuracy of expert judgment comes from the completeness of the expert's understanding of the phenomena and the process used to elicit and analyze the data. The use of a more formal process to obtain, lU1derstand and analyze expert judgment has led to an improved acceptance of expert judgment because of the rigor and transparency of the results.« less

Development of a five-year mortality model in systemic sclerosis patients by different analytical approaches.

PubMed

Beretta, Lorenzo; Santaniello, Alessandro; Cappiello, Francesca; Chawla, Nitesh V; Vonk, Madelon C; Carreira, Patricia E; Allanore, Yannick; Popa-Diaconu, D A; Cossu, Marta; Bertolotti, Francesca; Ferraccioli, Gianfranco; Mazzone, Antonino; Scorza, Raffaella

2010-01-01

Systemic sclerosis (SSc) is a multiorgan disease with high mortality rates. Several clinical features have been associated with poor survival in different populations of SSc patients, but no clear and reproducible prognostic model to assess individual survival prediction in scleroderma patients has ever been developed. We used Cox regression and three data mining-based classifiers (Naïve Bayes Classifier [NBC], Random Forests [RND-F] and logistic regression [Log-Reg]) to develop a robust and reproducible 5-year prognostic model. All the models were built and internally validated by means of 5-fold cross-validation on a population of 558 Italian SSc patients. Their predictive ability and capability of generalisation was then tested on an independent population of 356 patients recruited from 5 external centres and finally compared to the predictions made by two SSc domain experts on the same population. The NBC outperformed the Cox-based classifier and the other data mining algorithms after internal cross-validation (area under receiving operator characteristic curve, AUROC: NBC=0.759; RND-F=0.736; Log-Reg=0.754 and Cox= 0.724). The NBC had also a remarkable and better trade-off between sensitivity and specificity (e.g. Balanced accuracy, BA) than the Cox-based classifier, when tested on an independent population of SSc patients (BA: NBC=0.769, Cox=0.622). The NBC was also superior to domain experts in predicting 5-year survival in this population (AUROC=0.829 vs. AUROC=0.788 and BA=0.769 vs. BA=0.67). We provide a model to make consistent 5-year prognostic predictions in SSc patients. Its internal validity, as well as capability of generalisation and reduced uncertainty compared to human experts support its use at bedside. Available at: http://www.nd.edu/~nchawla/survival.xls.

EULAR recommendations for women's health and the management of family planning, assisted reproduction, pregnancy and menopause in patients with systemic lupus erythematosus and/or antiphospholipid syndrome

PubMed Central

Bertsias, G K; Agmon-Levin, N; Brown, S; Cervera, R; Costedoat-Chalumeau, N; Doria, A; Fischer-Betz, R; Forger, F; Moraes-Fontes, M F; Khamashta, M; King, J; Lojacono, A; Marchiori, F; Meroni, P L; Mosca, M; Motta, M; Ostensen, M; Pamfil, C; Raio, L; Schneider, M; Svenungsson, E; Tektonidou, M; Yavuz, S; Boumpas, D; Tincani, A

2017-01-01

Objectives Develop recommendations for women's health issues and family planning in systemic lupus erythematosus (SLE) and/or antiphospholipid syndrome (APS). Methods Systematic review of evidence followed by modified Delphi method to compile questions, elicit expert opinions and reach consensus. Results Family planning should be discussed as early as possible after diagnosis. Most women can have successful pregnancies and measures can be taken to reduce the risks of adverse maternal or fetal outcomes. Risk stratification includes disease activity, autoantibody profile, previous vascular and pregnancy morbidity, hypertension and the use of drugs (emphasis on benefits from hydroxychloroquine and antiplatelets/anticoagulants). Hormonal contraception and menopause replacement therapy can be used in patients with stable/inactive disease and low risk of thrombosis. Fertility preservation with gonadotropin-releasing hormone analogues should be considered prior to the use of alkylating agents. Assisted reproduction techniques can be safely used in patients with stable/inactive disease; patients with positive antiphospholipid antibodies/APS should receive anticoagulation and/or low-dose aspirin. Assessment of disease activity, renal function and serological markers is important for diagnosing disease flares and monitoring for obstetrical adverse outcomes. Fetal monitoring includes Doppler ultrasonography and fetal biometry, particularly in the third trimester, to screen for placental insufficiency and small for gestational age fetuses. Screening for gynaecological malignancies is similar to the general population, with increased vigilance for cervical premalignant lesions if exposed to immunosuppressive drugs. Human papillomavirus immunisation can be used in women with stable/inactive disease. Conclusions Recommendations for women's health issues in SLE and/or APS were developed using an evidence-based approach followed by expert consensus. PMID:27457513

Coexistence of collapse and stable spatiotemporal solitons in multimode fibers

NASA Astrophysics Data System (ADS)

Shtyrina, Olga V.; Fedoruk, Mikhail P.; Kivshar, Yuri S.; Turitsyn, Sergei K.

2018-01-01

We analyze spatiotemporal solitons in multimode optical fibers and demonstrate the existence of stable solitons, in a sharp contrast to earlier predictions of collapse of multidimensional solitons in three-dimensional media. We discuss the coexistence of blow-up solutions and collapse stabilization by a low-dimensional external potential in graded-index media, and also predict the existence of stable higher-order nonlinear waves such as dipole-mode spatiotemporal solitons. To support the main conclusions of our numerical studies we employ a variational approach and derive analytically the stability criterion for input powers for the collapse stabilization.

Forensic comparison and matching of fingerprints: using quantitative image measures for estimating error rates through understanding and predicting difficulty.

PubMed

Kellman, Philip J; Mnookin, Jennifer L; Erlikhman, Gennady; Garrigan, Patrick; Ghose, Tandra; Mettler, Everett; Charlton, David; Dror, Itiel E

2014-01-01

Latent fingerprint examination is a complex task that, despite advances in image processing, still fundamentally depends on the visual judgments of highly trained human examiners. Fingerprints collected from crime scenes typically contain less information than fingerprints collected under controlled conditions. Specifically, they are often noisy and distorted and may contain only a portion of the total fingerprint area. Expertise in fingerprint comparison, like other forms of perceptual expertise, such as face recognition or aircraft identification, depends on perceptual learning processes that lead to the discovery of features and relations that matter in comparing prints. Relatively little is known about the perceptual processes involved in making comparisons, and even less is known about what characteristics of fingerprint pairs make particular comparisons easy or difficult. We measured expert examiner performance and judgments of difficulty and confidence on a new fingerprint database. We developed a number of quantitative measures of image characteristics and used multiple regression techniques to discover objective predictors of error as well as perceived difficulty and confidence. A number of useful predictors emerged, and these included variables related to image quality metrics, such as intensity and contrast information, as well as measures of information quantity, such as the total fingerprint area. Also included were configural features that fingerprint experts have noted, such as the presence and clarity of global features and fingerprint ridges. Within the constraints of the overall low error rates of experts, a regression model incorporating the derived predictors demonstrated reasonable success in predicting objective difficulty for print pairs, as shown both in goodness of fit measures to the original data set and in a cross validation test. The results indicate the plausibility of using objective image metrics to predict expert performance and subjective assessment of difficulty in fingerprint comparisons.

Scratching the surface of tomorrow's diagnostics: the Editor-in-Chief's opinion at the 15th year of Expert Review of Molecular Diagnostics.

PubMed

Lorincz, Attila; Raison, Claire

2015-01-01

Interview with Attila Lorincz by Claire Raison (Commissioning Editor) To mark the beginning of the 15th year of Expert Review of Molecular Diagnostics, the journal's Editor-in-Chief shares his expert knowledge on translational diagnostics, his opinion on recent controversies and his predictions for molecular diagnostics in 2015 and beyond. Attila Lorincz received his doctorate from Trinity College, Dublin, Republic of Ireland, and went on to become a research fellow at the University of California, Santa Barbara, CA, USA. During Professor Lorincz's research on human papillomavirus (HPV), he found several important and novel carcinogenic HPV types and pioneered the use of HPV DNA testing for clinical diagnostics. In 1988, Professor Lorincz's team produced the first HPV test to be FDA-approved for patients and in 2003, for general population cervical precancer screening. Now Professor of Molecular Epidemiology at the Centre for Cancer Prevention, Queen Mary University of London, UK, he and his team are furthering translational research into DNA methylation assays for cancer risk prediction.

THE DEVELOPMENT OF A PREDICTIVE TOLL USING LARGEMOUTH BASS (MICROPTERUS SALMOIDES) SCALES TO ESTIMATE MERCURY (HG) CONCENTRATIONS AND STABLE-NITROGEN (15N/14N) ISOTOPE RATIOS IN FISH MUSCLE TISSUE

EPA Science Inventory

Knowledge of the trophic structure of biota in aquatic sites offers potential for the construction of models to allow the prediction of contaminant bioaccumulation. Measurements of trophic position have been conducted using stable-nitrogen isotope ratios ( 15N) measured in fish m...

Changing predictions, stable recognition: Children's representations of downward incline motion.

PubMed

Hast, Michael; Howe, Christine

2017-11-01

Various studies to-date have demonstrated children hold ill-conceived expressed beliefs about the physical world such as that one ball will fall faster than another because it is heavier. At the same time, they also demonstrate accurate recognition of dynamic events. How these representations relate is still unresolved. This study examined 5- to 11-year-olds' (N = 130) predictions and recognition of motion down inclines. Predictions were typically in error, matching previous work, but children largely recognized correct events as correct and rejected incorrect ones. The results also demonstrate while predictions change with increasing age, recognition shows signs of stability. The findings provide further support for a hybrid model of object representations and argue in favour of stable core cognition existing alongside developmental changes. Statement of contribution What is already known on this subject? Children's predictions of physical events show limitations in accuracy Their recognition of such events suggests children may use different knowledge sources in their reasoning What the present study adds? Predictions fluctuate more strongly than recognition, suggesting stable core cognition But recognition also shows some fluctuation, arguing for a hybrid model of knowledge representation. © 2017 The British Psychological Society.

A Multicriteria Approach to Find Predictive and Sparse Models with Stable Feature Selection for High-Dimensional Data.

PubMed

Bommert, Andrea; Rahnenführer, Jörg; Lang, Michel

2017-01-01

Finding a good predictive model for a high-dimensional data set can be challenging. For genetic data, it is not only important to find a model with high predictive accuracy, but it is also important that this model uses only few features and that the selection of these features is stable. This is because, in bioinformatics, the models are used not only for prediction but also for drawing biological conclusions which makes the interpretability and reliability of the model crucial. We suggest using three target criteria when fitting a predictive model to a high-dimensional data set: the classification accuracy, the stability of the feature selection, and the number of chosen features. As it is unclear which measure is best for evaluating the stability, we first compare a variety of stability measures. We conclude that the Pearson correlation has the best theoretical and empirical properties. Also, we find that for the stability assessment behaviour it is most important that a measure contains a correction for chance or large numbers of chosen features. Then, we analyse Pareto fronts and conclude that it is possible to find models with a stable selection of few features without losing much predictive accuracy.

Statistical model selection for better prediction and discovering science mechanisms that affect reliability

DOE PAGES

Anderson-Cook, Christine M.; Morzinski, Jerome; Blecker, Kenneth D.

2015-08-19

Understanding the impact of production, environmental exposure and age characteristics on the reliability of a population is frequently based on underlying science and empirical assessment. When there is incomplete science to prescribe which inputs should be included in a model of reliability to predict future trends, statistical model/variable selection techniques can be leveraged on a stockpile or population of units to improve reliability predictions as well as suggest new mechanisms affecting reliability to explore. We describe a five-step process for exploring relationships between available summaries of age, usage and environmental exposure and reliability. The process involves first identifying potential candidatemore » inputs, then second organizing data for the analysis. Third, a variety of models with different combinations of the inputs are estimated, and fourth, flexible metrics are used to compare them. As a result, plots of the predicted relationships are examined to distill leading model contenders into a prioritized list for subject matter experts to understand and compare. The complexity of the model, quality of prediction and cost of future data collection are all factors to be considered by the subject matter experts when selecting a final model.« less

Predictive Data Tools Find Uses in Schools

ERIC Educational Resources Information Center

Sparks, Sarah D.

2011-01-01

The use of analytic tools to predict student performance is exploding in higher education, and experts say the tools show even more promise for K-12 schools, in everything from teacher placement to dropout prevention. Use of such statistical techniques is hindered in precollegiate schools, however, by a lack of researchers trained to help…

Climate Prediction Center - Expert Assessments Index

Science.gov Websites

Weather Service NWS logo - Click to go to the NWS home page Climate Prediction Center Home Site Map News Web resources and services. HOME > Monitoring and Data > Global Climate Data & Maps > ; Global Regional Climate Maps Regional Climate Maps Banner The Monthly regional analyses products are

Assessing the impact of climate change on vector-borne viruses in the EU through the elicitation of expert opinion.

PubMed

Gale, P; Brouwer, A; Ramnial, V; Kelly, L; Kosmider, R; Fooks, A R; Snary, E L

2010-02-01

Expert opinion was elicited to undertake a qualitative risk assessment to estimate the current and future risks to the European Union (EU) from five vector-borne viruses listed by the World Organization for Animal Health. It was predicted that climate change will increase the risk of incursions of African horse sickness virus (AHSV), Crimean-Congo haemorrhagic fever virus (CCHFV) and Rift Valley fever virus (RVFV) into the EU from other parts of the world, with African swine fever virus (ASFV) and West Nile virus (WNV) being less affected. Currently the predicted risks of incursion were lowest for RVFV and highest for ASFV. Risks of incursion were considered for six routes of entry (namely vectors, livestock, meat products, wildlife, pets and people). Climate change was predicted to increase the risk of incursion from entry of vectors for all five viruses to some degree, the strongest effects being predicted for AHSV, CCHFV and WNV. This work will facilitate identification of appropriate risk management options in relation to adaptations to climate change.

The next scientific revolution.

PubMed

Hey, Tony

2010-11-01

For decades, computer scientists have tried to teach computers to think like human experts. Until recently, most of those efforts have failed to come close to generating the creative insights and solutions that seem to come naturally to the best researchers, doctors, and engineers. But now, Tony Hey, a VP of Microsoft Research, says we're witnessing the dawn of a new generation of powerful computer tools that can "mash up" vast quantities of data from many sources, analyze them, and help produce revolutionary scientific discoveries. Hey and his colleagues call this new method of scientific exploration "machine learning." At Microsoft, a team has already used it to innovate a method of predicting with impressive accuracy whether a patient with congestive heart failure who is released from the hospital will be readmitted within 30 days. It was developed by directing a computer program to pore through hundreds of thousands of data points on 300,000 patients and "learn" the profiles of patients most likely to be rehospitalized. The economic impact of this prediction tool could be huge: If a hospital understands the likelihood that a patient will "bounce back," it can design programs to keep him stable and save thousands of dollars in health care costs. Similar efforts to uncover important correlations that could lead to scientific breakthroughs are under way in oceanography, conservation, and AIDS research. And in business, deep data exploration has the potential to unearth critical insights about customers, supply chains, advertising effectiveness, and more.

Modeling postshock evolution of large electropores

NASA Astrophysics Data System (ADS)

Neu, John C.; Krassowska, Wanda

2003-02-01

The Smoluchowski equation (SE), which describes the evolution of pores created by electric shocks, cannot be applied to modeling large and long-lived pores for two reasons: (1) it does not predict pores of radius above 20 nm without also predicting membrane rupture; (2) it does not predict postshock growth of pores. This study proposes a model in which pores are coupled by membrane tension, resulting in a nonlinear generalization of SE. The predictions of the model are explored using examples of homogeneous (all pore radii r are equal) and heterogeneous (0⩽r⩽rmax) distributions of pores. Pores in a homogeneous population either shrink to zero or assume a stable radius corresponding to the minimum of the bilayer energy. For a heterogeneous population, such a stable radius does not exist. All pores, except rmax, shrink to zero and rmax grows to infinity. However, the unbounded growth of rmax is not physical because the number of pores per cell decreases in time and the continuum model loses validity. When the continuum formulation is replaced by the discrete one, the model predicts the coarsening process: all pores, except rmax, shrink to zero and rmax assumes a stable radius. Thus, the model with tension-coupled pores does not predict membrane rupture and the predicted postshock growth of pores is consistent with experimental evidence.

Research in space commercialization, technology transfer, and communications, volume 2

NASA Technical Reports Server (NTRS)

Dunn, D. A.; Agnew, C. E.

1983-01-01

Spectrum management, models for evaluating communication systems, the communications regulatory environment, expert prediction and consensus, remote sensing, and manned space operations research are discussed.

DeepMirTar: a deep-learning approach for predicting human miRNA targets.

PubMed

Wen, Ming; Cong, Peisheng; Zhang, Zhimin; Lu, Hongmei; Li, Tonghua

2018-06-01

MicroRNAs (miRNAs) are small noncoding RNAs that function in RNA silencing and post-transcriptional regulation of gene expression by targeting messenger RNAs (mRNAs). Because the underlying mechanisms associated with miRNA binding to mRNA are not fully understood, a major challenge of miRNA studies involves the identification of miRNA-target sites on mRNA. In silico prediction of miRNA-target sites can expedite costly and time-consuming experimental work by providing the most promising miRNA-target-site candidates. In this study, we reported the design and implementation of DeepMirTar, a deep-learning-based approach for accurately predicting human miRNA targets at the site level. The predicted miRNA-target sites are those having canonical or non-canonical seed, and features, including high-level expert-designed, low-level expert-designed, and raw-data-level, were used to represent the miRNA-target site. Comparison with other state-of-the-art machine-learning methods and existing miRNA-target-prediction tools indicated that DeepMirTar improved overall predictive performance. DeepMirTar is freely available at https://github.com/Bjoux2/DeepMirTar_SdA. lith@tongji.edu.cn, hongmeilu@csu.edu.cn. Supplementary data are available at Bioinformatics online.

a Novel Approach to Support Majority Voting in Spatial Group Mcdm Using Density Induced Owa Operator for Seismic Vulnerability Assessment

NASA Astrophysics Data System (ADS)

Moradi, M.; Delavar, M. R.; Moshiri, B.; Khamespanah, F.

2014-10-01

Being one of the most frightening disasters, earthquakes frequently cause huge damages to buildings, facilities and human beings. Although the prediction of characteristics of an earthquake seems to be impossible, its loss and damage is predictable in advance. Seismic loss estimation models tend to evaluate the extent to which the urban areas are vulnerable to earthquakes. Many factors contribute to the vulnerability of urban areas against earthquakes including age and height of buildings, the quality of the materials, the density of population and the location of flammable facilities. Therefore, seismic vulnerability assessment is a multi-criteria problem. A number of multi criteria decision making models have been proposed based on a single expert. The main objective of this paper is to propose a model which facilitates group multi criteria decision making based on the concept of majority voting. The main idea of majority voting is providing a computational tool to measure the degree to which different experts support each other's opinions and make a decision regarding this measure. The applicability of this model is examined in Tehran metropolitan area which is located in a seismically active region. The results indicate that neglecting the experts which get lower degrees of support from others enables the decision makers to avoid the extreme strategies. Moreover, a computational method is proposed to calculate the degree of optimism in the experts' opinions.

Expert forecasts and the emergence of water scarcity on public agendas

USGS Publications Warehouse

Graffy, E.A.

2006-01-01

Expert forecasts of worldwide water scarcity depict conditions that call for proactive, preventive, coordinated water governance, but they have not been matched by public agendas of commensurate scope and urgency in the United States. This disconnect can not be adequately explained without some attention to attributes of forecasts themselves. I propose that the institutional fragmentation of water expertise and prevailing patterns of communication about water scarcity militate against the formulation of a common public definition of the problem and encourage reliance on unambiguous crises to stimulate social and policy agenda setting. I do not argue that expert forecasts should drive public agendas deterministically, but if their purpose is to help prevent water crises (not just predict them), then a greater effort is needed to overcome the barriers to meaningful public scrutiny of expert claims and evaluation of water strategies presently in place. Copyright ?? 2006 Taylor & Francis Group, LLC.

[Medical expert consensus in AH on the clinical use of triple fixed-dose antihypertensive therapy in Spain].

PubMed

Mazón, P; Galve, E; Gómez, J; Gorostidi, M; Górriz, J L; Mediavilla, J D

The opinion of experts (different specialties) on the triple fixed-dose antihypertensive therapy in clinical practice may differ. Online questionnaire with controversial aspects of the triple therapy answered by panel of experts in hypertension (HT) using two-round modified Delphi method. The questionnaire was completed by 158 experts: Internal Medicine (49), Nephrology (26), Cardiology (83). Consensus was reached (agreement) on 27/45 items (60%); 7 items showed differences statistically significant. Consensus was reached regarding: Predictive factors in the need for combination therapy and its efficacy vs. increasing the dose of a pretreatment, and advantage of triple therapy (prescription/adherence/cost/pressure control) vs. free combination. This consensus provides an overview of the clinical use of triple therapy in moderate-severe and resistant/difficult to control HT. Copyright © 2016 SEH-LELHA. Publicado por Elsevier España, S.L.U. All rights reserved.

Wine Expertise Predicts Taste Phenotype

PubMed Central

Hayes, John E; Pickering, Gary J

2011-01-01

Taste phenotypes have long been studied in relation to alcohol intake, dependence, and family history, with contradictory findings. However, on balance – with appropriate caveats about populations tested, outcomes measured and psychophysical methods used – an association between variation in taste responsiveness and some alcohol behaviors is supported. Recent work suggests super-tasting (operationalized via propylthiouracil (PROP) bitterness) not only associates with heightened response but also with more acute discrimination between stimuli. Here, we explore relationships between food and beverage adventurousness and taste phenotype. A convenience sample of wine drinkers (n=330) were recruited in Ontario and phenotyped for PROP bitterness via filter paper disk. They also filled out a short questionnaire regarding willingness to try new foods, alcoholic beverages and wines as well as level of wine involvement, which was used to classify them as a wine expert (n=110) or wine consumer (n=220). In univariate logisitic models, food adventurousness predicted trying new wines and beverages but not expertise. Likewise, wine expertise predicted willingness to try new wines and beverages but not foods. In separate multivariate logistic models, willingness to try new wines and beverages was predicted by expertise and food adventurousness but not PROP. However, mean PROP bitterness was higher among wine experts than wine consumers, and the conditional distribution functions differed between experts and consumers. In contrast, PROP means and distributions did not differ with food adventurousness. These data suggest individuals may self-select for specific professions based on sensory ability (i.e., an active gene-environment correlation) but phenotype does not explain willingness to try new stimuli. PMID:22888174

Developing and validating a model to predict the success of an IHCS implementation: the Readiness for Implementation Model.

PubMed

Wen, Kuang-Yi; Gustafson, David H; Hawkins, Robert P; Brennan, Patricia F; Dinauer, Susan; Johnson, Pauley R; Siegler, Tracy

2010-01-01

To develop and validate the Readiness for Implementation Model (RIM). This model predicts a healthcare organization's potential for success in implementing an interactive health communication system (IHCS). The model consists of seven weighted factors, with each factor containing five to seven elements. Two decision-analytic approaches, self-explicated and conjoint analysis, were used to measure the weights of the RIM with a sample of 410 experts. The RIM model with weights was then validated in a prospective study of 25 IHCS implementation cases. Orthogonal main effects design was used to develop 700 conjoint-analysis profiles, which varied on seven factors. Each of the 410 experts rated the importance and desirability of the factors and their levels, as well as a set of 10 different profiles. For the prospective 25-case validation, three time-repeated measures of the RIM scores were collected for comparison with the implementation outcomes. Two of the seven factors, 'organizational motivation' and 'meeting user needs,' were found to be most important in predicting implementation readiness. No statistically significant difference was found in the predictive validity of the two approaches (self-explicated and conjoint analysis). The RIM was a better predictor for the 1-year implementation outcome than the half-year outcome. The expert sample, the order of the survey tasks, the additive model, and basing the RIM cut-off score on experience are possible limitations of the study. The RIM needs to be empirically evaluated in institutions adopting IHCS and sustaining the system in the long term.

Effects of expertise on football betting.

PubMed

Khazaal, Yasser; Chatton, Anne; Billieux, Joël; Bizzini, Lucio; Monney, Grégoire; Fresard, Emmanuelle; Thorens, Gabriel; Bondolfi, Guido; El-Guebaly, Nady; Zullino, Daniele; Khan, Riaz

2012-05-11

Football (soccer) is one of the most popular sports in the world, including Europe. It is associated with important betting activities. A common belief, widely spread among those who participate in gambling activities, is that knowledge and expertise on football lead to better prediction skills for match outcomes. If unfounded, however, this belief should be considered as a form of "illusion of control." The aim of this study was to examine whether football experts are better than nonexperts at predicting football match scores. Two hundred and fifty-eight persons took part in the study: 21.3% as football experts, 54.3% as laypersons (non-initiated to football), and 24.4% as football amateurs. They predicted the scores of the first 10 matches of the 2008 UEFA European Football Championship. Logistic regressions were carried out to assess the link between the accuracy of the forecasted scores and the expertise of the participants (expert, amateur, layperson), controlling for age and gender. The variables assessed did not predict the accuracy of scoring prognosis (R2 ranged from 1% to 6%). Expertise, age, and gender did not appear to have an impact on the accuracy of the football match prognoses. Therefore, the belief that football expertise improves betting skills is no more than a cognitive distortion called the "illusion of control." Gamblers may benefit from psychological interventions that target the illusion of control related to their believed links between betting skills and football expertise. Public health policies may need to consider the phenomenon in order to prevent problem gambling related to football betting.

Wine Expertise Predicts Taste Phenotype.

PubMed

Hayes, John E; Pickering, Gary J

2012-03-01

Taste phenotypes have long been studied in relation to alcohol intake, dependence, and family history, with contradictory findings. However, on balance - with appropriate caveats about populations tested, outcomes measured and psychophysical methods used - an association between variation in taste responsiveness and some alcohol behaviors is supported. Recent work suggests super-tasting (operationalized via propylthiouracil (PROP) bitterness) not only associates with heightened response but also with more acute discrimination between stimuli. Here, we explore relationships between food and beverage adventurousness and taste phenotype. A convenience sample of wine drinkers (n=330) were recruited in Ontario and phenotyped for PROP bitterness via filter paper disk. They also filled out a short questionnaire regarding willingness to try new foods, alcoholic beverages and wines as well as level of wine involvement, which was used to classify them as a wine expert (n=110) or wine consumer (n=220). In univariate logisitic models, food adventurousness predicted trying new wines and beverages but not expertise. Likewise, wine expertise predicted willingness to try new wines and beverages but not foods. In separate multivariate logistic models, willingness to try new wines and beverages was predicted by expertise and food adventurousness but not PROP. However, mean PROP bitterness was higher among wine experts than wine consumers, and the conditional distribution functions differed between experts and consumers. In contrast, PROP means and distributions did not differ with food adventurousness. These data suggest individuals may self-select for specific professions based on sensory ability (i.e., an active gene-environment correlation) but phenotype does not explain willingness to try new stimuli.

Fixed points, stable manifolds, weather regimes, and their predictability

DOE PAGES

Deremble, Bruno; D'Andrea, Fabio; Ghil, Michael

2009-10-27

In a simple, one-layer atmospheric model, we study the links between low-frequency variability and the model’s fixed points in phase space. The model dynamics is characterized by the coexistence of multiple ''weather regimes.'' To investigate the transitions from one regime to another, we focus on the identification of stable manifolds associated with fixed points. We show that these manifolds act as separatrices between regimes. We track each manifold by making use of two local predictability measures arising from the meteorological applications of nonlinear dynamics, namely, ''bred vectors'' and singular vectors. These results are then verified in the framework of ensemblemore » forecasts issued from clouds (ensembles) of initial states. The divergence of the trajectories allows us to establish the connections between zones of low predictability, the geometry of the stable manifolds, and transitions between regimes.« less

Fixed points, stable manifolds, weather regimes, and their predictability.

PubMed

Deremble, Bruno; D'Andrea, Fabio; Ghil, Michael

2009-12-01

In a simple, one-layer atmospheric model, we study the links between low-frequency variability and the model's fixed points in phase space. The model dynamics is characterized by the coexistence of multiple "weather regimes." To investigate the transitions from one regime to another, we focus on the identification of stable manifolds associated with fixed points. We show that these manifolds act as separatrices between regimes. We track each manifold by making use of two local predictability measures arising from the meteorological applications of nonlinear dynamics, namely, "bred vectors" and singular vectors. These results are then verified in the framework of ensemble forecasts issued from "clouds" (ensembles) of initial states. The divergence of the trajectories allows us to establish the connections between zones of low predictability, the geometry of the stable manifolds, and transitions between regimes.

Collaborations for Arctic Sea Ice Information and Tools

NASA Astrophysics Data System (ADS)

Sheffield Guy, L.; Wiggins, H. V.; Turner-Bogren, E. J.; Rich, R. H.

2017-12-01

The dramatic and rapid changes in Arctic sea ice require collaboration across boundaries, including between disciplines, sectors, institutions, and between scientists and decision-makers. This poster will highlight several projects that provide knowledge to advance the development and use of sea ice knowledge. Sea Ice for Walrus Outlook (SIWO: https://www.arcus.org/search-program/siwo) - SIWO is a resource for Alaskan Native subsistence hunters and other interested stakeholders. SIWO provides weekly reports, during April-June, of sea ice conditions relevant to walrus in the northern Bering and southern Chukchi seas. Collaboration among scientists, Alaskan Native sea-ice experts, and the Eskimo Walrus Commission is fundamental to this project's success. Sea Ice Prediction Network (SIPN: https://www.arcus.org/sipn) - A collaborative, multi-agency-funded project focused on seasonal Arctic sea ice predictions. The goals of SIPN include: coordinate and evaluate Arctic sea ice predictions; integrate, assess, and guide observations; synthesize predictions and observations; and disseminate predictions and engage key stakeholders. The Sea Ice Outlook—a key activity of SIPN—is an open process to share and synthesize predictions of the September minimum Arctic sea ice extent and other variables. Other SIPN activities include workshops, webinars, and communications across the network. Directory of Sea Ice Experts (https://www.arcus.org/researchers) - ARCUS has undertaken a pilot project to develop a web-based directory of sea ice experts across institutions, countries, and sectors. The goal of the project is to catalyze networking between individual investigators, institutions, funding agencies, and other stakeholders interested in Arctic sea ice. Study of Environmental Arctic Change (SEARCH: https://www.arcus.org/search-program) - SEARCH is a collaborative program that advances research, synthesizes research findings, and broadly communicates the results to support informed decision-making. One of SEARCH's primary science topics is focused on Arctic sea ice; the SEARCH Sea Ice Action Team is leading efforts to advance understanding and awareness of the impacts of Arctic sea-ice loss.

Molecular classification of gastric cancer.

PubMed

Röcken, Christoph

2017-03-01

Gastric cancer is among the most common cancers worldwide. Despite declining incidences, the prognosis remains dismal in Western countries and is better in Asian countries with national cancer screening programs. Complete endoscopic or surgical resection of the primary tumor with or without lymphadenectomy offers the only chance of cure in the early stage of the disease. Survival of more locally advanced gastric cancers was improved by the introduction of perioperative, adjuvant and palliative chemotherapy. However, the identification and usage of novel predictive and diagnostic targets is urgently needed. Areas covered: Recent comprehensive molecular profiling of gastric cancer proposed four molecular subtypes, i.e. Epstein-Barr virus-associated, microsatellite instable, chromosomal instable and genomically stable carcinomas. The new molecular classification will spur clinical trials exploring novel targeted therapeutics. This review summarizes recent advancements of the molecular classification, and based on that, putative pitfalls for the development of tissue-based companion diagnostics, i.e. prevalence of actionable targets and therapeutic efficacy, tumor heterogeneity and tumor evolution, impact of ethnicity on gastric cancer biology, and standards of care in the East and West. Expert commentary: The overall low prevalence of actionable targets and tumor heterogeneity are the two main obstacles of precision medicine for gastric cancer.

Expending Role of Microsatellite Instability in Diagnosis and Treatment of Colorectal Cancers.

PubMed

Chang, Liisa; Chang, Minna; Chang, Hanna M; Chang, Fuju

2017-12-01

Colorectal carcinomas with high-frequency microsatellite instability (MSI-H) account for 15% of all colorectal cancers, including 12% of sporadic cases and 3% of cancers associated with Lynch syndrome (also known as hereditary nonpolyposis colorectal cancer syndrome, HNPCC). Lynch syndrome is an autosomal dominant hereditary cancer syndrome, caused by germline mutations in mismatch repair genes, including MLH1, MSH2, MSH6 and PMS2. Published articles from peer-reviewed journals were obtained from PubMed, Google Scholar and Clinicaltrials.gov . Based on the recent research data, we provide an update on the MSI testing, along with the evolving role of MSI in diagnosis, prognosis and treatment of colorectal cancers. Studies have led to significant advances in the molecular pathogenesis and clinicopathological characteristics of MSI-H colorectal cancers. Emerging evidence suggests that colorectal cancers with MSI-H show different outcome and treatment response from those with microsatellite stable (MSS) tumors. Therefore, MSI testing is essential not only in the genetic context, but it may also have important prognostic and predictive value of response to chemotherapy and immunotherapy. Many experts and professional authorities have recommended a universal MSI testing in all individuals newly diagnosed with colorectal cancers.

Evaluation of WRF-Predicted Near-Hub-Height Winds and Ramp Events over a Pacific Northwest Site with Complex Terrain

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

Yang, Qing; Berg, Larry K.; Pekour, Mikhail

The WRF model version 3.3 is used to simulate near hub-height winds and power ramps utilizing three commonly used planetary boundary-layer (PBL) schemes: Mellor-Yamada-Janjic (MYJ), University of Washington (UW), and Yonsei University (YSU). The predicted winds have small mean biases compared with observations. Power ramps and step changes (changes within an hour) consistently show that the UW scheme performed better in predicting up ramps under stable conditions with higher prediction accuracy and capture rates. Both YSU and UW scheme show good performance predicting up- and down- ramps under unstable conditions with YSU being slightly better for ramp durations longer thanmore » an hour. MYJ is the most successful simulating down-ramps under stable conditions. The high wind speed and large shear associated with low-level jets are frequently associated with power ramps, and the biases in predicted low-level jet explain some of the shown differences in ramp predictions among different PBL schemes. Low-level jets were observed as low as ~200 m in altitude over the Columbia Basin Wind Energy Study (CBWES) site, located in an area of complex terrain. The shear, low-level peak wind speeds, as well as the height of maximum wind speed are not well predicted. Model simulations with 3 PBL schemes show the largest variability among them under stable conditions.« less

Biomarker-Based Risk Model to Predict Cardiovascular Mortality in Patients With Stable Coronary Disease.

PubMed

Lindholm, Daniel; Lindbäck, Johan; Armstrong, Paul W; Budaj, Andrzej; Cannon, Christopher P; Granger, Christopher B; Hagström, Emil; Held, Claes; Koenig, Wolfgang; Östlund, Ollie; Stewart, Ralph A H; Soffer, Joseph; White, Harvey D; de Winter, Robbert J; Steg, Philippe Gabriel; Siegbahn, Agneta; Kleber, Marcus E; Dressel, Alexander; Grammer, Tanja B; März, Winfried; Wallentin, Lars

2017-08-15

Currently, there is no generally accepted model to predict outcomes in stable coronary heart disease (CHD). This study evaluated and compared the prognostic value of biomarkers and clinical variables to develop a biomarker-based prediction model in patients with stable CHD. In a prospective, randomized trial cohort of 13,164 patients with stable CHD, we analyzed several candidate biomarkers and clinical variables and used multivariable Cox regression to develop a clinical prediction model based on the most important markers. The primary outcome was cardiovascular (CV) death, but model performance was also explored for other key outcomes. It was internally bootstrap validated, and externally validated in 1,547 patients in another study. During a median follow-up of 3.7 years, there were 591 cases of CV death. The 3 most important biomarkers were N-terminal pro-B-type natriuretic peptide (NT-proBNP), high-sensitivity cardiac troponin T (hs-cTnT), and low-density lipoprotein cholesterol, where NT-proBNP and hs-cTnT had greater prognostic value than any other biomarker or clinical variable. The final prediction model included age (A), biomarkers (B) (NT-proBNP, hs-cTnT, and low-density lipoprotein cholesterol), and clinical variables (C) (smoking, diabetes mellitus, and peripheral arterial disease). This "ABC-CHD" model had high discriminatory ability for CV death (c-index 0.81 in derivation cohort, 0.78 in validation cohort), with adequate calibration in both cohorts. This model provided a robust tool for the prediction of CV death in patients with stable CHD. As it is based on a small number of readily available biomarkers and clinical factors, it can be widely employed to complement clinical assessment and guide management based on CV risk. (The Stabilization of Atherosclerotic Plaque by Initiation of Darapladib Therapy Trial [STABILITY]; NCT00799903). Copyright © 2017 American College of Cardiology Foundation. Published by Elsevier Inc. All rights reserved.

Learning Latent Variable and Predictive Models of Dynamical Systems

DTIC Science & Technology

2009-10-01

stable over the full 1000 frame image sequence without significant damping. C. Sam- ples drawn from a least squares synthesized sequences (top), and...LDS stabilizing algorithms, LB-1 and LB-2. Bars at every 20 timesteps denote variance in the results. CG provides the best stable short term predictions...observations. This thesis contributes (1) novel learning algorithms for existing dynamical system models that overcome significant limitations of previous

Diagnostic value of a pancreatic mass on computed tomography in patients undergoing pancreatoduodenectomy for presumed pancreatic cancer.

PubMed

Gerritsen, Arja; Bollen, Thomas L; Nio, C Yung; Molenaar, I Quintus; Dijkgraaf, Marcel G W; van Santvoort, Hjalmar C; Offerhaus, G Johan; Brosens, Lodewijk A; Biermann, Katharina; Sieders, Egbert; de Jong, Koert P; van Dam, Ronald M; van der Harst, Erwin; van Goor, Harry; van Ramshorst, Bert; Bonsing, Bert A; de Hingh, Ignace H; Gerhards, Michael F; van Eijck, Casper H; Gouma, Dirk J; Borel Rinkes, Inne H M; Busch, Olivier R C; Besselink, Marc G H

2015-07-01

Previous studies have shown that 5-14% of patients undergoing pancreatoduodenectomy for suspected malignancy ultimately are diagnosed with benign disease. A "pancreatic mass" on computed tomography (CT) is considered to be the strongest predictor of malignancy, but studies describing its diagnostic value are lacking. The aim of this study was to determine the diagnostic value of a pancreatic mass on CT in patients with presumed pancreatic cancer, as well as the interobserver agreement among radiologists and the additional value of reassessment by expert-radiologists. Reassessment of preoperative CT scans was performed within a previously described multicenter retrospective cohort study in 344 patients undergoing pancreatoduodenectomy for suspected malignancy (2003-2010). Preoperative CT scans were reassessed by 2 experienced abdominal radiologists separately and subsequently in a consensus meeting, after defining a pancreatic mass as "a measurable space occupying soft tissue density, except for an enlarged papilla or focal steatosis". CT scans of 86 patients with benign and 258 patients with (pre)malignant disease were reassessed. In 66% of patients a pancreatic mass was reported in the original CT report, versus 48% and 50% on reassessment by the 2 expert radiologists separately and 44% in consensus (P < .001 vs original report). Interobserver agreement between the original CT report and expert consensus was fair (kappa = 0.32, 95% confidence interval 0.23-0.42). Among both expert-radiologists agreement was moderate (kappa = 0.47, 95% confidence interval 0.38-0.56), with disagreement on the presence of a pancreatic mass in 29% of cases. The specificity for malignancy of pancreatic masses identified in expert consensus was twice as high compared with the original CT report (87% vs 42%, respectively). Positive predictive value increased to 98% after expert consensus, but negative predictive value was low (12%). Clinicians need to be aware of potential considerable disagreement among radiologists about the presence of a pancreatic mass. The specificity for malignancy doubled by expert radiologist reassessment when a uniform definition of "pancreatic mass" was used. Copyright © 2015 Elsevier Inc. All rights reserved.

A biomechanical comparison between expert and novice manual materials handlers using a multi-joint EMG-assisted optimization musculoskeletal model of the lumbar spine.

PubMed

Gagnon, Denis; Plamondon, André; Larivière, Christian

2016-09-06

Expertise is a key factor modulating the risk of low back disorders (LBD). Through years of practice in the workplace, the typical expert acquires high level specific skills and maintains a clean record of work-related injuries. Ergonomic observations of manual materials handling (MMH) tasks show that expert techniques differ from those of novices, leading to the idea that expert techniques are safer. Biomechanical studies of MMH tasks performed by experts/novices report mixed results for kinematic/kinetic variables, evoking potential internal effect of expertise. In the context of series of box transfers simulated by actual workers, detailed internal loads predicted by a multiple-joint EMG-assisted optimization lumbar spine model are compared between experts and novices. The results confirmed that the distribution of internal moments are modulated by worker expertise. Experts flexed less their lumbar spine and exerted more active muscle forces while novices relied more on passive resistance of the muscles and ligamentous spine. More specifically for novices, the passive contributions came from global extensor muscles, selected local extensor muscles, and passive structures of the lumbar spine (ligaments and discs). The distinctive distribution of internal forces was not concomitant with a similar effect on joint forces, these forces being dependent on external loading which was equivalent between experts and novices. From a safety standpoint, the present results suggest that experts were more efficient than novices in partitioning internal moment contributions to balance net (external) loading. Thus, safer handling practices might be seen as a result of experts׳ experience. Copyright © 2016 Elsevier Ltd. All rights reserved.

The integration of automated knowledge acquisition with computer-aided software engineering for space shuttle expert systems

NASA Technical Reports Server (NTRS)

Modesitt, Kenneth L.

1990-01-01

A prediction was made that the terms expert systems and knowledge acquisition would begin to disappear over the next several years. This is not because they are falling into disuse; it is rather that practitioners are realizing that they are valuable adjuncts to software engineering, in terms of problem domains addressed, user acceptance, and in development methodologies. A specific problem was discussed, that of constructing an automated test analysis system for the Space Shuttle Main Engine. In this domain, knowledge acquisition was part of requirements systems analysis, and was performed with the aid of a powerful inductive ESBT in conjunction with a computer aided software engineering (CASE) tool. The original prediction is not a very risky one -- it has already been accomplished.

exprso: an R-package for the rapid implementation of machine learning algorithms.

PubMed

Quinn, Thomas; Tylee, Daniel; Glatt, Stephen

2016-01-01

Machine learning plays a major role in many scientific investigations. However, non-expert programmers may struggle to implement the elaborate pipelines necessary to build highly accurate and generalizable models. We introduce exprso , a new R package that is an intuitive machine learning suite designed specifically for non-expert programmers. Built initially for the classification of high-dimensional data, exprso uses an object-oriented framework to encapsulate a number of common analytical methods into a series of interchangeable modules. This includes modules for feature selection, classification, high-throughput parameter grid-searching, elaborate cross-validation schemes (e.g., Monte Carlo and nested cross-validation), ensemble classification, and prediction. In addition, exprso also supports multi-class classification (through the 1-vs-all generalization of binary classifiers) and the prediction of continuous outcomes.

Preliminary development of POEAW in enhancing K-11 students’ understanding level on impulse and momentum

NASA Astrophysics Data System (ADS)

Luthfiani, T. A.; Sinaga, P.; Samsudin, A.

2018-05-01

We have been analyzed that there were limited research about Predict-Observe- Explain which use writing process with conceptual change text strategy. This study aims to develop a learning model namely Predict-Observe-Explain-Apply-Writing (POEAW) which is able to enhance students’ understanding level. The research method utilized the 4D model (Defining, Designing, Developing and Disseminating) that is formally limited to Developing Stage. There are four experts who judge the learning component (syntax, lesson plan, teaching material and student worksheet) and matter component (learning quality and content component). The result of this study are obtained expert validity test score average of 87% for learning content and 89% for matter component that means the POEAW is valid and can be tested in classroom learning. This research producing POEAW learning model that has five main steps, Predict, Observe, Explain, Apply and Write. To sum up, we have early developed POEAW in enhancing K-11 students’ understanding levels on impulse and momentum.

Explosion probability of unexploded ordnance: expert beliefs.

PubMed

MacDonald, Jacqueline Anne; Small, Mitchell J; Morgan, M G

2008-08-01

This article reports on a study to quantify expert beliefs about the explosion probability of unexploded ordnance (UXO). Some 1,976 sites at closed military bases in the United States are contaminated with UXO and are slated for cleanup, at an estimated cost of $15-140 billion. Because no available technology can guarantee 100% removal of UXO, information about explosion probability is needed to assess the residual risks of civilian reuse of closed military bases and to make decisions about how much to invest in cleanup. This study elicited probability distributions for the chance of UXO explosion from 25 experts in explosive ordnance disposal, all of whom have had field experience in UXO identification and deactivation. The study considered six different scenarios: three different types of UXO handled in two different ways (one involving children and the other involving construction workers). We also asked the experts to rank by sensitivity to explosion 20 different kinds of UXO found at a case study site at Fort Ord, California. We found that the experts do not agree about the probability of UXO explosion, with significant differences among experts in their mean estimates of explosion probabilities and in the amount of uncertainty that they express in their estimates. In three of the six scenarios, the divergence was so great that the average of all the expert probability distributions was statistically indistinguishable from a uniform (0, 1) distribution-suggesting that the sum of expert opinion provides no information at all about the explosion risk. The experts' opinions on the relative sensitivity to explosion of the 20 UXO items also diverged. The average correlation between rankings of any pair of experts was 0.41, which, statistically, is barely significant (p= 0.049) at the 95% confidence level. Thus, one expert's rankings provide little predictive information about another's rankings. The lack of consensus among experts suggests that empirical studies are needed to better understand the explosion risks of UXO.

[Study on expert system of infrared spectral characteristic of combustible smoke agent].

PubMed

Song, Dong-ming; Guan, Hua; Hou, Wei; Pan, Gong-pei

2009-05-01

The present paper studied the application of expert system in prediction of infrared spectral characteristic of combustible anti-infrared smoke agent. The construction of the expert system was founded, based on the theory of minimum free energy and infrared spectral addition. After the direction of smoke agent was input, the expert system could figure out the final combustion products. Then infrared spectrogram of smoke could also be simulated by adding the spectra of all of the combustion products. Meanwhile, the screening index of smoke was provided in the wave bands of 3-5 im and 8-14 microm. FTIR spectroscope was used to investigate the performance of one kind of HC smoke. The combustion products calculated by the expert system were coincident with the actual data, and the simulant infrared spectrum was also similar to the real one of the smoke. The screening index given by the system was consistent with the known facts. It was showed that a new approach was offered for the fast discrimination of varieties of directions of smoke agent.

BAYESIAN META-ANALYSIS ON MEDICAL DEVICES: APPLICATION TO IMPLANTABLE CARDIOVERTER DEFIBRILLATORS

PubMed Central

Youn, Ji-Hee; Lord, Joanne; Hemming, Karla; Girling, Alan; Buxton, Martin

2012-01-01

Objectives: The aim of this study is to describe and illustrate a method to obtain early estimates of the effectiveness of a new version of a medical device. Methods: In the absence of empirical data, expert opinion may be elicited on the expected difference between the conventional and modified devices. Bayesian Mixed Treatment Comparison (MTC) meta-analysis can then be used to combine this expert opinion with existing trial data on earlier versions of the device. We illustrate this approach for a new four-pole implantable cardioverter defibrillator (ICD) compared with conventional ICDs, Class III anti-arrhythmic drugs, and conventional drug therapy for the prevention of sudden cardiac death in high risk patients. Existing RCTs were identified from a published systematic review, and we elicited opinion on the difference between four-pole and conventional ICDs from experts recruited at a cardiology conference. Results: Twelve randomized controlled trials were identified. Seven experts provided valid probability distributions for the new ICDs compared with current devices. The MTC model resulted in estimated relative risks of mortality of 0.74 (0.60–0.89) (predictive relative risk [RR] = 0.77 [0.41–1.26]) and 0.83 (0.70–0.97) (predictive RR = 0.84 [0.55–1.22]) with the new ICD therapy compared to Class III anti-arrhythmic drug therapy and conventional drug therapy, respectively. These results showed negligible differences from the preliminary results for the existing ICDs. Conclusions: The proposed method incorporating expert opinion to adjust for a modification made to an existing device may play a useful role in assisting decision makers to make early informed judgments on the effectiveness of frequently modified healthcare technologies. PMID:22559753

A Theory-Based Methodology for Analyzing Domain Suitability for Expert Systems Technology Applications

DTIC Science & Technology

1989-06-01

amount of data now available as a result of these experiments, we are still unable to explain the "why" or " how " of successful systems or to predict for...order to better understand the potential contribution of this research, it is important to first discuss how expert systems are developed and the...task performance through internal and external feedback. 9. Knowing how to act upon the feedback received. 10. Implementing the action based on the

A Quantitative Model of Expert Transcription Typing

DTIC Science & Technology

1993-03-08

side of pure psychology, several researchers have argued that transcription typing is a particularly good activity for the study of human skilled...phenomenon with a quantitative METT prediction. The first, quick and dirty analysis gives a good prediction of the copy span, in fact, it is even...typing, it should be demonstrated that the mechanism of the model does not get in the way of good predictions. If situations occur where the entire

Intuition and Professional Competence: Intuitive Versus Rational Forecasting of the Stock Market

ERIC Educational Resources Information Center

Harteis, Christian; Gruber, Hans

2008-01-01

This article argues that intuition is a crucial component of professional competence, and provides empirical evidence to support this claim. It was found that in most cases intuitive predictions of stock market development are better than rationally justified ones and that experts predict more precisely than novices on a descriptive data level.…

Dynamic Risk Assessment of Sexual Offenders: Validity and Dimensional Structure of the Stable-2007.

PubMed

Etzler, Sonja; Eher, Reinhard; Rettenberger, Martin

2018-02-01

In this study, the predictive and incremental validity of the Stable-2007 beyond the Static-99 was evaluated in an updated sample of N = 638 adult male sexual offenders followed-up for an average of M = 8.2 years. Data were collected at the Federal Evaluation Center for Violent and Sexual Offenders (FECVSO) in Austria within a prospective-longitudinal research design. Scores and risk categories of the Static-99 (AUC = .721; p < .001) and of the Stable-2007 (AUC = .623, p = .005) were found to be significantly related to sexual recidivism. The Stable-2007 risk categories contributed incrementally to the prediction of sexual recidivism beyond the Static-99. Analyzing the dimensional structure of the Stable-2007 yielded three factors, named Antisociality, Sexual Deviance, and Hypersexuality. Antisociality and Sexual Deviance were significant predictors for sexual recidivism. Sexual Deviance was negatively associated with non-sexual violent recidivism. Comparisons with latent dimensions of other risk assessment instruments are made and implications for applied risk assessment are discussed.

Validity and validation of expert (Q)SAR systems.

PubMed

Hulzebos, E; Sijm, D; Traas, T; Posthumus, R; Maslankiewicz, L

2005-08-01

At a recent workshop in Setubal (Portugal) principles were drafted to assess the suitability of (quantitative) structure-activity relationships ((Q)SARs) for assessing the hazards and risks of chemicals. In the present study we applied some of the Setubal principles to test the validity of three (Q)SAR expert systems and validate the results. These principles include a mechanistic basis, the availability of a training set and validation. ECOSAR, BIOWIN and DEREK for Windows have a mechanistic or empirical basis. ECOSAR has a training set for each QSAR. For half of the structural fragments the number of chemicals in the training set is >4. Based on structural fragments and log Kow, ECOSAR uses linear regression to predict ecotoxicity. Validating ECOSAR for three 'valid' classes results in predictivity of > or = 64%. BIOWIN uses (non-)linear regressions to predict the probability of biodegradability based on fragments and molecular weight. It has a large training set and predicts non-ready biodegradability well. DEREK for Windows predictions are supported by a mechanistic rationale and literature references. The structural alerts in this program have been developed with a training set of positive and negative toxicity data. However, to support the prediction only a limited number of chemicals in the training set is presented to the user. DEREK for Windows predicts effects by 'if-then' reasoning. The program predicts best for mutagenicity and carcinogenicity. Each structural fragment in ECOSAR and DEREK for Windows needs to be evaluated and validated separately.

Computational and Matrix Isolation Studies of (2- and 3-Furyl)methylene

DTIC Science & Technology

1994-01-01

ynal, (Appendix 3) Simple HF calculations using the 6-31 G basis set + ZPE (zero point energy correction applied) predict 2.2 to be more stable in both...QCISD(T)/6-31 1 G** + ZPE predict the triplet to more stable by 2.9 Kcal/mol. However, calculations using MP4SDTQ/6-31 1 G + ZPE predict the singlet to...calculated frequencies were scaled by a factor of 0.9. 53 Table 2.30 Calculated ZPE for 2-Oxabicyclo(3.1.0]hexa-3,5-diene.a Zero Point Energy 49.9 (KcaVmol

Harnessing expert knowledge: Defining a Bayesian network decision model with limited data-Model structure for the vibration qualification problem

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

Rizzo, Davinia B.; Blackburn, Mark R.

As systems become more complex, systems engineers rely on experts to inform decisions. There are few experts and limited data in many complex new technologies. This challenges systems engineers as they strive to plan activities such as qualification in an environment where technical constraints are coupled with the traditional cost, risk, and schedule constraints. Bayesian network (BN) models provide a framework to aid systems engineers in planning qualification efforts with complex constraints by harnessing expert knowledge and incorporating technical factors. By quantifying causal factors, a BN model can provide data about the risk of implementing a decision supplemented with informationmore » on driving factors. This allows a systems engineer to make informed decisions and examine “what-if” scenarios. This paper discusses a novel process developed to define a BN model structure based primarily on expert knowledge supplemented with extremely limited data (25 data sets or less). The model was developed to aid qualification decisions—specifically to predict the suitability of six degrees of freedom (6DOF) vibration testing for qualification. The process defined the model structure with expert knowledge in an unbiased manner. Finally, validation during the process execution and of the model provided evidence the process may be an effective tool in harnessing expert knowledge for a BN model.« less

Harnessing expert knowledge: Defining a Bayesian network decision model with limited data-Model structure for the vibration qualification problem

DOE PAGES

Rizzo, Davinia B.; Blackburn, Mark R.

2018-03-30

As systems become more complex, systems engineers rely on experts to inform decisions. There are few experts and limited data in many complex new technologies. This challenges systems engineers as they strive to plan activities such as qualification in an environment where technical constraints are coupled with the traditional cost, risk, and schedule constraints. Bayesian network (BN) models provide a framework to aid systems engineers in planning qualification efforts with complex constraints by harnessing expert knowledge and incorporating technical factors. By quantifying causal factors, a BN model can provide data about the risk of implementing a decision supplemented with informationmore » on driving factors. This allows a systems engineer to make informed decisions and examine “what-if” scenarios. This paper discusses a novel process developed to define a BN model structure based primarily on expert knowledge supplemented with extremely limited data (25 data sets or less). The model was developed to aid qualification decisions—specifically to predict the suitability of six degrees of freedom (6DOF) vibration testing for qualification. The process defined the model structure with expert knowledge in an unbiased manner. Finally, validation during the process execution and of the model provided evidence the process may be an effective tool in harnessing expert knowledge for a BN model.« less

Systematic methods for knowledge acquisition and expert system development

NASA Technical Reports Server (NTRS)

Belkin, Brenda L.; Stengel, Robert F.

1991-01-01

Nine cooperating rule-based systems, collectively called AUTOCREW, were designed to automate functions and decisions associated with a combat aircraft's subsystem. The organization of tasks within each system is described; performance metrics were developed to evaluate the workload of each rule base, and to assess the cooperation between the rule-bases. Each AUTOCREW subsystem is composed of several expert systems that perform specific tasks. AUTOCREW's NAVIGATOR was analyzed in detail to understand the difficulties involved in designing the system and to identify tools and methodologies that ease development. The NAVIGATOR determines optimal navigation strategies from a set of available sensors. A Navigation Sensor Management (NSM) expert system was systematically designed from Kalman filter covariance data; four ground-based, a satellite-based, and two on-board INS-aiding sensors were modeled and simulated to aid an INS. The NSM Expert was developed using the Analysis of Variance (ANOVA) and the ID3 algorithm. Navigation strategy selection is based on an RSS position error decision metric, which is computed from the covariance data. Results show that the NSM Expert predicts position error correctly between 45 and 100 percent of the time for a specified navaid configuration and aircraft trajectory. The NSM Expert adapts to new situations, and provides reasonable estimates of hybrid performance. The systematic nature of the ANOVA/ID3 method makes it broadly applicable to expert system design when experimental or simulation data is available.

Expert Game experiment predicts emergence of trust in professional communication networks.

PubMed

Bendtsen, Kristian Moss; Uekermann, Florian; Haerter, Jan O

2016-10-25

Strong social capital is increasingly recognized as an organizational advantage. Better knowledge sharing and reduced transaction costs increase work efficiency. To mimic the formation of the associated communication network, we propose the Expert Game, where each individual must find a specific expert and receive her help. Participants act in an impersonal environment and under time constraints that provide short-term incentives for noncooperative behavior. Despite these constraints, we observe cooperation between individuals and the self-organization of a sustained trust network, which facilitates efficient communication channels with increased information flow. We build a behavioral model that explains the experimental dynamics. Analysis of the model reveals an exploitation protection mechanism and measurable social capital, which quantitatively describe the economic utility of trust.

Bayesian methods in reliability

NASA Astrophysics Data System (ADS)

Sander, P.; Badoux, R.

1991-11-01

The present proceedings from a course on Bayesian methods in reliability encompasses Bayesian statistical methods and their computational implementation, models for analyzing censored data from nonrepairable systems, the traits of repairable systems and growth models, the use of expert judgment, and a review of the problem of forecasting software reliability. Specific issues addressed include the use of Bayesian methods to estimate the leak rate of a gas pipeline, approximate analyses under great prior uncertainty, reliability estimation techniques, and a nonhomogeneous Poisson process. Also addressed are the calibration sets and seed variables of expert judgment systems for risk assessment, experimental illustrations of the use of expert judgment for reliability testing, and analyses of the predictive quality of software-reliability growth models such as the Weibull order statistics.

Sports betting: can gamblers beat randomness?

PubMed

Cantinotti, Michael; Ladouceur, Robert; Jacques, Christian

2004-06-01

Although skills are not considered relevant in chance-governed activities, only a few studies have assessed the extent to which sport expert skills in wagering are a manifestation of the illusion of control. This study examined (a) whether expert hockey bettors could make better predictions than chance, (b) whether expert hockey bettors could achieve greater monetary gains than chance, and (c) what kind of strategies hockey gamblers rely on when betting. Accordingly, 30 participants were asked to report their state lottery hockey bets on 6 occasions. We suggest that the information used by bettors, along with near-misses, reinforces their perception of expertise. The results of this experiment suggest that the so-called "skills" of the sports bettors are cognitive distortions. (c) 2004 APA, all rights reserved

From Zero to Integration in Eight Months, the Dawn Ground Data System Engineering Challenge

NASA Technical Reports Server (NTRS)

Dubon, Lydia P.

2006-01-01

The Dawn GDS Team met the SC Sim integration challenge in eight months. The GDS System Engineering approach in response to the SC Simintegration challenge, focused on a set of key practices: decomposition of project request into manageable requirements; integration of multiple ground disciplines and experts into a focused team effort; risk management thru management of expectations; and aggregation of intermediate products into a final product. By maintaining a a system-level focus, the overall systems engineering process unified team GDS Team members with a common goal: the success of the ground system as a whole and not just the success of their individual expert contributions. Incorporation of Agile-type development efforts were aligned with a risk strategy based on team-oriented principles and expectations management, thus achieving a more stable baseline solution without compromising the integrity of the GDS design.

Development of casthouse expert system for tapping

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

Takihira, K.; Ino, K.; Yamana, S.

1993-01-01

Although the standardization of casting operations is necessary to secure stable blast furnace operation, intuitive practices (which are by definition non-quantifiable) and experience are prevalent. Because BF operation is a field which is difficult to standardize and reduce to documentary form, the present work had as its goal the standardization of judgments and systematization of information related to taphole opening and closing. The project was carried out in the highly computerized environment at Mizushima No. 3 BF, where the authors introduced an expert system guidance function in February, 1992. Standardization of operations through the use of this guidance system andmore » the completion of guidance function development resulted in better consistency in taphole depths and optimization of the size of the taphole (taphole volume), which have in turn led to improvement in the pig/slag balance and a reduction in the time required for taphole opening.« less

Haptic simulation framework for determining virtual dental occlusion.

PubMed

Wu, Wen; Chen, Hui; Cen, Yuhai; Hong, Yang; Khambay, Balvinder; Heng, Pheng Ann

2017-04-01

The surgical treatment of many dentofacial deformities is often complex due to its three-dimensional nature. To determine the dental occlusion in the most stable position is essential for the success of the treatment. Computer-aided virtual planning on individualized patient-specific 3D model can help formulate the surgical plan and predict the surgical change. However, in current computer-aided planning systems, it is not possible to determine the dental occlusion of the digital models in the intuitive way during virtual surgical planning because of absence of haptic feedback. In this paper, a physically based haptic simulation framework is proposed, which can provide surgeons with the intuitive haptic feedback to determine the dental occlusion of the digital models in their most stable position. To provide the physically realistic force feedback when the dental models contact each other during the searching process, the contact model is proposed to describe the dynamic and collision properties of the dental models during the alignment. The simulated impulse/contact-based forces are integrated into the unified simulation framework. A validation study has been conducted on fifteen sets of virtual dental models chosen at random and covering a wide range of the dental relationships found clinically. The dental occlusions obtained by an expert were employed as a benchmark to compare the virtual occlusion results. The mean translational and angular deviations of the virtual occlusion results from the benchmark were small. The experimental results show the validity of our method. The simulated forces can provide valuable insights to determine the virtual dental occlusion. The findings of this work and the validation of proposed concept lead the way for full virtual surgical planning on patient-specific virtual models allowing fully customized treatment plans for the surgical correction of dentofacial deformities.

A Decision Support System Coupling Fuzzy Logic and Probabilistic Graphical Approaches for the Agri-Food Industry: Prediction of Grape Berry Maturity

PubMed Central

Brousset, Jean Marie; Abbal, Philippe; Guillemin, Hervé; Perret, Bruno; Goulet, Etienne; Guerin, Laurence; Barbeau, Gérard; Picque, Daniel

2015-01-01

Agri-food is one of the most important sectors of the industry and a major contributor to the global warming potential in Europe. Sustainability issues pose a huge challenge for this sector. In this context, a big issue is to be able to predict the multiscale dynamics of those systems using computing science. A robust predictive mathematical tool is implemented for this sector and applied to the wine industry being easily able to be generalized to other applications. Grape berry maturation relies on complex and coupled physicochemical and biochemical reactions which are climate dependent. Moreover one experiment represents one year and the climate variability could not be covered exclusively by the experiments. Consequently, harvest mostly relies on expert predictions. A big challenge for the wine industry is nevertheless to be able to anticipate the reactions for sustainability purposes. We propose to implement a decision support system so called FGRAPEDBN able to (1) capitalize the heterogeneous fragmented knowledge available including data and expertise and (2) predict the sugar (resp. the acidity) concentrations with a relevant RMSE of 7 g/l (resp. 0.44 g/l and 0.11 g/kg). FGRAPEDBN is based on a coupling between a probabilistic graphical approach and a fuzzy expert system. PMID:26230334

Predictive Value of Early Tumor Shrinkage and Density Reduction of Lung Metastases in Patients With Metastatic Colorectal Cancer Treated With Regorafenib.

PubMed

Vanwynsberghe, Hannes; Verbeke, Xander; Coolen, Johan; Van Cutsem, Eric

2017-12-01

The benefit of regorafenib in colorectal cancer is not very pronounced. At present, there is lack of predictive biological or radiological markers. We studied if density reduction or small changes in size of lung metastases could be a predictive marker. We retrospectively measured density in size of lung metastases of all patients included in the CORRECT and CONSIGN trials at our center. Contrast-enhanced CT scan at baseline and at week 8 were compared. Data of progressive-free survival and overall survival were collected from the CORRECT and CONSIGN trials. A significant difference in progressive-free survival was seen in 3 groups: response or stable disease in size (5.36 vs. 3.96 months), response in density (6.03 vs. 2.72 months), and response in corrected density (6.14 vs. 3.08 months). No difference was seen for response in size versus stable disease or progressive disease in size. For overall survival, a difference was observed in the same 3 groups: response or stable disease in size (9.89 vs. 6.44 months), response in density (9.59 vs. 7.04 months), and response in corrected density (9.09 vs. 7.16 months). No difference was seen for response in size versus stable disease or progressive disease in size. Density reduction in lung metastases might be a good predictive parameter to predict outcome for regorafenib. Early tumor progression might be a negative predictive factor. If further validated, density reduction and early tumor progression might be useful to ameliorate the cost-benefit of regorafenib. Copyright © 2017 Elsevier Inc. All rights reserved.

Process consistency in models: The importance of system signatures, expert knowledge, and process complexity

NASA Astrophysics Data System (ADS)

Hrachowitz, M.; Fovet, O.; Ruiz, L.; Euser, T.; Gharari, S.; Nijzink, R.; Freer, J.; Savenije, H. H. G.; Gascuel-Odoux, C.

2014-09-01

Hydrological models frequently suffer from limited predictive power despite adequate calibration performances. This can indicate insufficient representations of the underlying processes. Thus, ways are sought to increase model consistency while satisfying the contrasting priorities of increased model complexity and limited equifinality. In this study, the value of a systematic use of hydrological signatures and expert knowledge for increasing model consistency was tested. It was found that a simple conceptual model, constrained by four calibration objective functions, was able to adequately reproduce the hydrograph in the calibration period. The model, however, could not reproduce a suite of hydrological signatures, indicating a lack of model consistency. Subsequently, testing 11 models, model complexity was increased in a stepwise way and counter-balanced by "prior constraints," inferred from expert knowledge to ensure a model which behaves well with respect to the modeler's perception of the system. We showed that, in spite of unchanged calibration performance, the most complex model setup exhibited increased performance in the independent test period and skill to better reproduce all tested signatures, indicating a better system representation. The results suggest that a model may be inadequate despite good performance with respect to multiple calibration objectives and that increasing model complexity, if counter-balanced by prior constraints, can significantly increase predictive performance of a model and its skill to reproduce hydrological signatures. The results strongly illustrate the need to balance automated model calibration with a more expert-knowledge-driven strategy of constraining models.

Computer-Aided Decision Making.

DTIC Science & Technology

1988-04-01

Center at Gunter APS, Alabama, 1% predicts that 150.000 more microcomputers, with integrated software, will be VP aided !,: the A:r Fcrce inventory...a computer’s power when he said, ’it is also useful to anticipate or predict changes in the data Pondering ’what if’ situations enabled me to answer... predict future b) experts forecast In Isolation, then consensus is found C. Group decision making (3t30-34) Slide i-i 1. Advantages a. broader background 1

Functional magnetic resonance imaging examination of two modular architectures for switching multiple internal models.

PubMed

Imamizu, Hiroshi; Kuroda, Tomoe; Yoshioka, Toshinori; Kawato, Mitsuo

2004-02-04

An internal model is a neural mechanism that can mimic the input-output properties of a controlled object such as a tool. Recent research interests have moved on to how multiple internal models are learned and switched under a given context of behavior. Two representative computational models for task switching propose distinct neural mechanisms, thus predicting different brain activity patterns in the switching of internal models. In one model, called the mixture-of-experts architecture, switching is commanded by a single executive called a "gating network," which is different from the internal models. In the other model, called the MOSAIC (MOdular Selection And Identification for Control), the internal models themselves play crucial roles in switching. Consequently, the mixture-of-experts model predicts that neural activities related to switching and internal models can be temporally and spatially segregated, whereas the MOSAIC model predicts that they are closely intermingled. Here, we directly examined the two predictions by analyzing functional magnetic resonance imaging activities during the switching of one common tool (an ordinary computer mouse) and two novel tools: a rotated mouse, the cursor of which appears in a rotated position, and a velocity mouse, the cursor velocity of which is proportional to the mouse position. The switching and internal model activities temporally and spatially overlapped each other in the cerebellum and in the parietal cortex, whereas the overlap was very small in the frontal cortex. These results suggest that switching mechanisms in the frontal cortex can be explained by the mixture-of-experts architecture, whereas those in the cerebellum and the parietal cortex are explained by the MOSAIC model.

Program Manager: Journal of the Defense Systems Management College. Volume 20, Number 4, July-August 1991

DTIC Science & Technology

1991-08-01

national aritificial intelligence technologies, phase is intended to establish a stable headline news when front-line which are key to linking computer and... intelligence and S&T own alternative. communities. There are experts from Assembly of potential material the S&T community through contin- alternatives...cidents to SEC. i chief inform him that he am earlier work, Designing Defense intelligent cififrhitathIeS’ysterns, and adds the current spin of -FEI

Computational Discovery of New Materials Under Pressure

NASA Astrophysics Data System (ADS)

Zurek, Eva

The pressure variable opens the door towards the synthesis of materials with unique properties, ie. superconductivity, hydrogen storage media, high-energy density and superhard materials, to name a few. Indeed, recently superconductivity has been observed below 203 K and 103 K in samples of compressed sulfur dihydride and phosphine, respectively. Under pressure elements that would not normally combine may form stable compounds, or may mix in novel proportions. As a result using our chemical intuition developed at 1 atm to theoretically predict stable phases is bound to fail. In order to enable our search for superconducting hydrogen-rich systems under pressure, we have developed XtalOpt, an open-source evolutionary algorithm for crystal structure prediction. New advances in XtalOpt that enable the prediction of unit cells with greater complexity will be described. XtalOpt has been employed to find the most stable structures of hydrides with unique stoichiometries under pressure. The electronic structure and bonding of the predicted phases has been analyzed by detailed first-principles calculations based on density functional theory. The results of our computational experiments are helping us to build chemical and physical intuition for compressed solids.

A Reinvestigation of the Dimer of para-Benzoquinone with Pyrimidine with MP2, CCSD(T) and DFT using Functionals including those Designed to Describe Dispersion

PubMed Central

Marianski, Mateusz; Oliva, Antoni

2012-01-01

We reevaluate the interaction of pyridine and p-benzoquinone using functionals designed to treat dispersion. We compare the relative energies of four different structures: stacked, T-shaped (identified for the first time) and two planar H-bonded geometries using these functionals (B97-D, ωB97x-D, M05, M05-2X, M06, M06L, M06-2X), other functionals (PBE1PBE, B3LYP, X3LYP), MP2 and CCSD(T) using basis sets as large as cc-pVTZ. The functionals designed to treat dispersion behave erratically as the predictions of the most stable structure vary considerably. MP2 predicts the experimentally observed structure (H-bonded) to be the least stable, while single point CCSD(T) at the MP2 optimized geometry correctly predicts the observed structure to be most stable. We have confirmed the assignment of the experimental structure using new calculations of the vibrational frequency shifts previously used to identify the structure. The MP2/cc-pVTZ vibrational calculations are in excellent agreement with the observations. All methods used to calculate the energies provide vibrational shifts that agree with the observed structure even though most do not predict this structure to be most stable. The implications for evaluating possible π-stacking in biologically important systems are discussed. PMID:22765283

A reinvestigation of the dimer of para-benzoquinone and pyrimidine with MP2, CCSD(T), and DFT using functionals including those designed to describe dispersion.

PubMed

Marianski, Mateusz; Oliva, Antoni; Dannenberg, J J

2012-08-02

We reevaluate the interaction of pyridine and p-benzoquinone using functionals designed to treat dispersion. We compare the relative energies of four different structures: stacked, T-shaped (identified for the first time), and two planar H-bonded geometries using these functionals (B97-D, ωB97x-D, M05, M05-2X, M06, M06L, and M06-2X), other functionals (PBE1PBE, B3LYP, X3LYP), MP2, and CCSD(T) using basis sets as large as cc-pVTZ. The functionals designed to treat dispersion behave erratically as the predictions of the most stable structure vary considerably. MP2 predicts the experimentally observed structure (H-bonded) to be the least stable, while single-point CCSD(T) at the MP2 optimized geometry correctly predicts the observed structure to be the most stable. We have confirmed the assignment of the experimental structure using new calculations of the vibrational frequency shifts previously used to identify the structure. The MP2/cc-pVTZ vibrational calculations are in excellent agreement with the observations. All methods used to calculate the energies provide vibrational shifts that agree with the observed structure even though most do not predict this structure to be most stable. The implications for evaluating possible π-stacking in biologically important systems are discussed.

Deep learning based tissue analysis predicts outcome in colorectal cancer.

PubMed

Bychkov, Dmitrii; Linder, Nina; Turkki, Riku; Nordling, Stig; Kovanen, Panu E; Verrill, Clare; Walliander, Margarita; Lundin, Mikael; Haglund, Caj; Lundin, Johan

2018-02-21

Image-based machine learning and deep learning in particular has recently shown expert-level accuracy in medical image classification. In this study, we combine convolutional and recurrent architectures to train a deep network to predict colorectal cancer outcome based on images of tumour tissue samples. The novelty of our approach is that we directly predict patient outcome, without any intermediate tissue classification. We evaluate a set of digitized haematoxylin-eosin-stained tumour tissue microarray (TMA) samples from 420 colorectal cancer patients with clinicopathological and outcome data available. The results show that deep learning-based outcome prediction with only small tissue areas as input outperforms (hazard ratio 2.3; CI 95% 1.79-3.03; AUC 0.69) visual histological assessment performed by human experts on both TMA spot (HR 1.67; CI 95% 1.28-2.19; AUC 0.58) and whole-slide level (HR 1.65; CI 95% 1.30-2.15; AUC 0.57) in the stratification into low- and high-risk patients. Our results suggest that state-of-the-art deep learning techniques can extract more prognostic information from the tissue morphology of colorectal cancer than an experienced human observer.

Experts Foresee a Major Shift From Inpatient to Ambulatory Care.

PubMed

Beans, Bruce E

2016-04-01

An American Society of Health-System Pharmacists Research and Education Foundation report predicts trends in health care delivery and financing, drug development and therapeutics, pharmaceutical marketplace, pharmacy workforce, and more.

Development of an expert system for analysis of Shuttle atmospheric revitalization and pressure control subsystem anomalies

NASA Technical Reports Server (NTRS)

Lafuse, Sharon A.

1991-01-01

The paper describes the Shuttle Leak Management Expert System (SLMES), a preprototype expert system developed to enable the ECLSS subsystem manager to analyze subsystem anomalies and to formulate flight procedures based on flight data. The SLMES combines the rule-based expert system technology with the traditional FORTRAN-based software into an integrated system. SLMES analyzes the data using rules, and, when it detects a problem that requires simulation, it sets up the input for the FORTRAN-based simulation program ARPCS2AT2, which predicts the cabin total pressure and composition as a function of time. The program simulates the pressure control system, the crew oxygen masks, the airlock repress/depress valves, and the leakage. When the simulation has completed, other SLMES rules are triggered to examine the results of simulation contrary to flight data and to suggest methods for correcting the problem. Results are then presented in form of graphs and tables.

Fuzzy Expert System for Heart Attack Diagnosis

NASA Astrophysics Data System (ADS)

Hassan, Norlida; Arbaiy, Nureize; Shah, Noor Aziyan Ahmad; Afizah Afif@Afip, Zehan

2017-08-01

Heart attack is one of the serious illnesses and reported as the main killer disease. Early prevention is significant to reduce the risk of having the disease. The prevention efforts can be strengthen through awareness and education about risk factor and healthy lifestyle. Therefore the knowledge dissemination is needed to play role in order to distribute and educate public in health care management and disease prevention. Since the knowledge dissemination in medical is important, there is a need to develop a knowledge based system that can emulate human intelligence to assist decision making process. Thereby, this study utilized hybrid artificial intelligence (AI) techniques to develop a Fuzzy Expert System for Diagnosing Heart Attack Disease (HAD). This system integrates fuzzy logic with expert system, which helps the medical practitioner and people to predict the risk and as well as diagnosing heart attack based on given symptom. The development of HAD is expected not only providing expert knowledge but potentially become one of learning resources to help citizens to develop awareness about heart-healthy lifestyle.

Stabilizing l1-norm prediction models by supervised feature grouping.

PubMed

Kamkar, Iman; Gupta, Sunil Kumar; Phung, Dinh; Venkatesh, Svetha

2016-02-01

Emerging Electronic Medical Records (EMRs) have reformed the modern healthcare. These records have great potential to be used for building clinical prediction models. However, a problem in using them is their high dimensionality. Since a lot of information may not be relevant for prediction, the underlying complexity of the prediction models may not be high. A popular way to deal with this problem is to employ feature selection. Lasso and l1-norm based feature selection methods have shown promising results. But, in presence of correlated features, these methods select features that change considerably with small changes in data. This prevents clinicians to obtain a stable feature set, which is crucial for clinical decision making. Grouping correlated variables together can improve the stability of feature selection, however, such grouping is usually not known and needs to be estimated for optimal performance. Addressing this problem, we propose a new model that can simultaneously learn the grouping of correlated features and perform stable feature selection. We formulate the model as a constrained optimization problem and provide an efficient solution with guaranteed convergence. Our experiments with both synthetic and real-world datasets show that the proposed model is significantly more stable than Lasso and many existing state-of-the-art shrinkage and classification methods. We further show that in terms of prediction performance, the proposed method consistently outperforms Lasso and other baselines. Our model can be used for selecting stable risk factors for a variety of healthcare problems, so it can assist clinicians toward accurate decision making. Copyright © 2015 Elsevier Inc. All rights reserved.

Verification of Pharmacogenetics-Based Warfarin Dosing Algorithms in Han-Chinese Patients Undertaking Mechanic Heart Valve Replacement

PubMed Central

Zhao, Li; Chen, Chunxia; Li, Bei; Dong, Li; Guo, Yingqiang; Xiao, Xijun; Zhang, Eryong; Qin, Li

2014-01-01

Objective To study the performance of pharmacogenetics-based warfarin dosing algorithms in the initial and the stable warfarin treatment phases in a cohort of Han-Chinese patients undertaking mechanic heart valve replacement. Methods We searched PubMed, Chinese National Knowledge Infrastructure and Wanfang databases for selecting pharmacogenetics-based warfarin dosing models. Patients with mechanic heart valve replacement were consecutively recruited between March 2012 and July 2012. The predicted warfarin dose of each patient was calculated and compared with the observed initial and stable warfarin doses. The percentage of patients whose predicted dose fell within 20% of their actual therapeutic dose (percentage within 20%), and the mean absolute error (MAE) were utilized to evaluate the predictive accuracy of all the selected algorithms. Results A total of 8 algorithms including Du, Huang, Miao, Wei, Zhang, Lou, Gage, and International Warfarin Pharmacogenetics Consortium (IWPC) model, were tested in 181 patients. The MAE of the Gage, IWPC and 6 Han-Chinese pharmacogenetics-based warfarin dosing algorithms was less than 0.6 mg/day in accuracy and the percentage within 20% exceeded 45% in all of the selected models in both the initial and the stable treatment stages. When patients were stratified according to the warfarin dose range, all of the equations demonstrated better performance in the ideal-dose range (1.88–4.38 mg/day) than the low-dose range (<1.88 mg/day). Among the 8 algorithms compared, the algorithms of Wei, Huang, and Miao showed a lower MAE and higher percentage within 20% in both the initial and the stable warfarin dose prediction and in the low-dose and the ideal-dose ranges. Conclusions All of the selected pharmacogenetics-based warfarin dosing regimens performed similarly in our cohort. However, the algorithms of Wei, Huang, and Miao showed a better potential for warfarin prediction in the initial and the stable treatment phases in Han-Chinese patients undertaking mechanic heart valve replacement. PMID:24728385

Verification of pharmacogenetics-based warfarin dosing algorithms in Han-Chinese patients undertaking mechanic heart valve replacement.

PubMed

Zhao, Li; Chen, Chunxia; Li, Bei; Dong, Li; Guo, Yingqiang; Xiao, Xijun; Zhang, Eryong; Qin, Li

2014-01-01

To study the performance of pharmacogenetics-based warfarin dosing algorithms in the initial and the stable warfarin treatment phases in a cohort of Han-Chinese patients undertaking mechanic heart valve replacement. We searched PubMed, Chinese National Knowledge Infrastructure and Wanfang databases for selecting pharmacogenetics-based warfarin dosing models. Patients with mechanic heart valve replacement were consecutively recruited between March 2012 and July 2012. The predicted warfarin dose of each patient was calculated and compared with the observed initial and stable warfarin doses. The percentage of patients whose predicted dose fell within 20% of their actual therapeutic dose (percentage within 20%), and the mean absolute error (MAE) were utilized to evaluate the predictive accuracy of all the selected algorithms. A total of 8 algorithms including Du, Huang, Miao, Wei, Zhang, Lou, Gage, and International Warfarin Pharmacogenetics Consortium (IWPC) model, were tested in 181 patients. The MAE of the Gage, IWPC and 6 Han-Chinese pharmacogenetics-based warfarin dosing algorithms was less than 0.6 mg/day in accuracy and the percentage within 20% exceeded 45% in all of the selected models in both the initial and the stable treatment stages. When patients were stratified according to the warfarin dose range, all of the equations demonstrated better performance in the ideal-dose range (1.88-4.38 mg/day) than the low-dose range (<1.88 mg/day). Among the 8 algorithms compared, the algorithms of Wei, Huang, and Miao showed a lower MAE and higher percentage within 20% in both the initial and the stable warfarin dose prediction and in the low-dose and the ideal-dose ranges. All of the selected pharmacogenetics-based warfarin dosing regimens performed similarly in our cohort. However, the algorithms of Wei, Huang, and Miao showed a better potential for warfarin prediction in the initial and the stable treatment phases in Han-Chinese patients undertaking mechanic heart valve replacement.

Forensic Comparison and Matching of Fingerprints: Using Quantitative Image Measures for Estimating Error Rates through Understanding and Predicting Difficulty

PubMed Central

Kellman, Philip J.; Mnookin, Jennifer L.; Erlikhman, Gennady; Garrigan, Patrick; Ghose, Tandra; Mettler, Everett; Charlton, David; Dror, Itiel E.

2014-01-01

Latent fingerprint examination is a complex task that, despite advances in image processing, still fundamentally depends on the visual judgments of highly trained human examiners. Fingerprints collected from crime scenes typically contain less information than fingerprints collected under controlled conditions. Specifically, they are often noisy and distorted and may contain only a portion of the total fingerprint area. Expertise in fingerprint comparison, like other forms of perceptual expertise, such as face recognition or aircraft identification, depends on perceptual learning processes that lead to the discovery of features and relations that matter in comparing prints. Relatively little is known about the perceptual processes involved in making comparisons, and even less is known about what characteristics of fingerprint pairs make particular comparisons easy or difficult. We measured expert examiner performance and judgments of difficulty and confidence on a new fingerprint database. We developed a number of quantitative measures of image characteristics and used multiple regression techniques to discover objective predictors of error as well as perceived difficulty and confidence. A number of useful predictors emerged, and these included variables related to image quality metrics, such as intensity and contrast information, as well as measures of information quantity, such as the total fingerprint area. Also included were configural features that fingerprint experts have noted, such as the presence and clarity of global features and fingerprint ridges. Within the constraints of the overall low error rates of experts, a regression model incorporating the derived predictors demonstrated reasonable success in predicting objective difficulty for print pairs, as shown both in goodness of fit measures to the original data set and in a cross validation test. The results indicate the plausibility of using objective image metrics to predict expert performance and subjective assessment of difficulty in fingerprint comparisons. PMID:24788812

Functional MRI reveals expert-novice differences during sport-related anticipation.

PubMed

Wright, Michael J; Bishop, Daniel T; Jackson, Robin C; Abernethy, Bruce

2010-01-27

We examined the effect of expertise on cortical activation during sports anticipation using functional MRI. In experiment 1, recreational players predicted badminton stroke direction and the pattern of active clusters was consistent with a proposed perception-of-action network. This pattern was not replicated in a stimulus-matched, action-unrelated control task. In experiment 2, players of three different skill levels anticipated stroke direction from clips occluded either 160 ms before or 80 ms after racquet-shuttle contact. Early-occluded sequences produced more activation than late-occluded sequences overall, in most cortical regions of interest, but experts showed an additional enhancement in medial, dorsolateral and ventrolateral frontal cortex. Anticipation in open-skill sports engages cortical areas integral to observing and understanding others' actions; such activity is enhanced in experts.

Complex Causal Process Diagrams for Analyzing the Health Impacts of Policy Interventions

PubMed Central

Joffe, Michael; Mindell, Jennifer

2006-01-01

Causal diagrams are rigorous tools for controlling confounding. They also can be used to describe complex causal systems, which is done routinely in communicable disease epidemiology. The use of change diagrams has advantages over static diagrams, because change diagrams are more tractable, relate better to interventions, and have clearer interpretations. Causal diagrams are a useful basis for modeling. They make assumptions explicit, provide a framework for analysis, generate testable predictions, explore the effects of interventions, and identify data gaps. Causal diagrams can be used to integrate different types of information and to facilitate communication both among public health experts and between public health experts and experts in other fields. Causal diagrams allow the use of instrumental variables, which can help control confounding and reverse causation. PMID:16449586

Developmental trajectories of physical aggression: prediction of overt and covert antisocial behaviors from self- and mothers' reports

PubMed Central

Di Giunta, Laura; Pastorelli, Concetta; Eisenberg, Nancy; Gerbino, Maria; Castellani, Valeria; Bombi, Anna Silvia

2010-01-01

Physical aggression declines for the majority of children from preschool to elementary school. Although this desistance generally continues during adolescence and early adulthood, a small group of children maintain a high level of physical aggression over time and develop other serious overt and covert antisocial behaviors. Typically, researchers have examined relations of developmental changes in physical aggression to later violence with teachers' or mothers' reports on surveys. Little is known about the degree to which children's self-reported physical aggression predicts later antisocial behavior. The longitudinal study in this article had a staggered, multiple cohort design. Measures of physical aggression were collected through self- and mother reports from age 11–14 years, which were used to construct trajectory groups (attrition was 6 and 14% from age 11–14, respectively, for self- and mother reports). Overt and covert antisocial behaviors were self-reported at age 18–19 years (attrition was 36% from age 11 to 18–19). Four trajectory groups (low stable, 11%; moderate-low declining, 34%; moderate declining, 39%; high stable, 16%) were identified from self-reports, whereas three trajectories (low declining, 33%; moderate declining, 49%; high stable, 18%) were identified from mothers' ratings. We examined the prediction of overt and covert antisocial behaviors in early adulthood from the high stable and the moderate declining trajectories. According to both informants, higher probability of belonging to the high stable group was associated with higher overt and covert antisocial behavior, whereas higher probability of belonging to the moderate declining group was associated with higher covert antisocial behavior. Our results support the value of children's as well as mothers' reports of children's aggression for predicting different types of serious antisocial behavior in adulthood. PMID:20878197

Developmental trajectories of physical aggression: prediction of overt and covert antisocial behaviors from self- and mothers' reports.

PubMed

Di Giunta, Laura; Pastorelli, Concetta; Eisenberg, Nancy; Gerbino, Maria; Castellani, Valeria; Bombi, Anna Silvia

2010-12-01

Physical aggression declines for the majority of children from preschool to elementary school. Although this desistance generally continues during adolescence and early adulthood, a small group of children maintain a high level of physical aggression over time and develop other serious overt and covert antisocial behaviors. Typically, researchers have examined relations of developmental changes in physical aggression to later violence with teachers' or mothers' reports on surveys. Little is known about the degree to which children's self-reported physical aggression predicts later antisocial behavior. The longitudinal study in this article had a staggered, multiple cohort design. Measures of physical aggression were collected through self- and mother reports from age 11-14 years, which were used to construct trajectory groups (attrition was 6 and 14% from age 11-14, respectively, for self- and mother reports). Overt and covert antisocial behaviors were self-reported at age 18-19 years (attrition was 36% from age 11 to 18-19). Four trajectory groups (low stable, 11%; moderate-low declining, 34%; moderate declining, 39%; high stable, 16%) were identified from self-reports, whereas three trajectories (low declining, 33%; moderate declining, 49%; high stable, 18%) were identified from mothers' ratings. We examined the prediction of overt and covert antisocial behaviors in early adulthood from the high stable and the moderate declining trajectories. According to both informants, higher probability of belonging to the high stable group was associated with higher overt and covert antisocial behavior, whereas higher probability of belonging to the moderate declining group was associated with higher covert antisocial behavior. Our results support the value of children's as well as mothers' reports of children's aggression for predicting different types of serious antisocial behavior in adulthood.

Prediction of neutral noble gas insertion compounds with heavier pnictides: FNgY (Ng = Kr and Xe; Y = As, Sb and Bi).

PubMed

Ghosh, Ayan; Manna, Debashree; Ghanty, Tapan K

2016-04-28

A novel class of interesting insertion compounds obtained through the insertion of a noble gas atom into the heavier pnictides have been explored by various ab initio quantum chemical techniques. Recently, the first neutral noble gas insertion compounds, FXeY (Y = P, N), were theoretically predicted to be stable; the triplet state was found to be the most stable state, with a high triplet-singlet energy gap, by our group. In this study, we investigated another noble gas inserted compound, FNgY (Ng = Kr and Xe; Y = As, Sb and Bi), with a triplet ground state. Density functional theory (DFT), second order Møller-Plesset perturbation theory (MP2), coupled-cluster theory (CCSD(T)) and multi-reference configuration interaction (MRCI) based techniques have been utilized to investigate the structures, stabilities, harmonic vibrational frequencies, charge distributions and topological properties of these compounds. These predicted species, FNgY (Ng = Kr and Xe; Y = As, Sb and Bi) are found to be energetically stable with respect to all the probable 2-body and 3-body dissociation pathways, except for the 2-body channel leading to the global minimum products (FY + Ng). Nevertheless, the finite barrier height corresponding to the saddle points of the compounds connected to their respective global minima products indicates that these compounds are kinetically stable. The structural parameters, energetics, and charge distribution results as well as atoms-in-molecules (AIM) analysis suggest that these predicted molecules can be best represented as F(-)[(3)NgY](+). Thus, all the aforementioned computed results clearly indicate that it may be possible to experimentally prepare the most stable triplet state of FNgY molecules under cryogenic conditions through a matrix isolation technique.

Population variation in isotopic composition of shorebird feathers: Implications for determining molting grounds

USGS Publications Warehouse

Torres-Dowdall, J.; Farmer, A.H.; Bucher, E.H.; Rye, R.O.; Landis, G.

2009-01-01

Stable isotope analyses have revolutionized the study of migratory connectivity. However, as with all tools, their limitations must be understood in order to derive the maximum benefit of a particular application. The goal of this study was to evaluate the efficacy of stable isotopes of C, N, H, O and S for assigning known-origin feathers to the molting sites of migrant shorebird species wintering and breeding in Argentina. Specific objectives were to: 1) compare the efficacy of the technique for studying shorebird species with different migration patterns, life histories and habitat-use patterns; 2) evaluate the grouping of species with similar migration and habitat use patterns in a single analysis to potentially improve prediction accuracy; and 3) evaluate the potential gains in prediction accuracy that might be achieved from using multiple stable isotopes. The efficacy of stable isotope ratios to determine origin was found to vary with species. While one species (White-rumped Sandpiper, Calidris fuscicollis) had high levels of accuracy assigning samples to known origin (91% of samples correctly assigned), another (Collared Plover, Charadrius collaris) showed low levels of accuracy (52% of samples correctly assigned). Intra-individual variability may account for this difference in efficacy. The prediction model for three species with similar migration and habitat-use patterns performed poorly compared with the model for just one of the species (71% versus 91% of samples correctly assigned). Thus, combining multiple sympatric species may not improve model prediction accuracy. Increasing the number of stable isotopes in the analyses increased the accuracy of assigning shorebirds to their molting origin, but the best combination - involving a subset of all the isotopes analyzed - varied among species.

Scientists versus regulators: precaution, novelty & regulatory oversight as predictors of perceived risks of engineered nanomaterials.

PubMed

Beaudrie, Christian E H; Satterfield, Terre; Kandlikar, Milind; Harthorn, Barbara H

2014-01-01

Engineered nanoscale materials (ENMs) present a difficult challenge for risk assessors and regulators. Continuing uncertainty about the potential risks of ENMs means that expert opinion will play an important role in the design of policies to minimize harmful implications while supporting innovation. This research aims to shed light on the views of 'nano experts' to understand which nanomaterials or applications are regarded as more risky than others, to characterize the differences in risk perceptions between expert groups, and to evaluate the factors that drive these perceptions. Our analysis draws from a web-survey (N = 404) of three groups of US and Canadian experts: nano-scientists and engineers, nano-environmental health and safety scientists, and regulatory scientists and decision-makers. Significant differences in risk perceptions were found across expert groups; differences found to be driven by underlying attitudes and perceptions characteristic of each group. Nano-scientists and engineers at the upstream end of the nanomaterial life cycle perceived the lowest levels of risk, while those who are responsible for assessing and regulating risks at the downstream end perceived the greatest risk. Perceived novelty of nanomaterial risks, differing preferences for regulation (i.e. the use of precaution versus voluntary or market-based approaches), and perceptions of the risk of technologies in general predicted variation in experts' judgments of nanotechnology risks. Our findings underscore the importance of involving a diverse selection of experts, particularly those with expertise at different stages along the nanomaterial lifecycle, during policy development.

A multimodel approach to interannual and seasonal prediction of Danube discharge anomalies

NASA Astrophysics Data System (ADS)

Rimbu, Norel; Ionita, Monica; Patrut, Simona; Dima, Mihai

2010-05-01

Interannual and seasonal predictability of Danube river discharge is investigated using three model types: 1) time series models 2) linear regression models of discharge with large-scale climate mode indices and 3) models based on stable teleconnections. All models are calibrated using discharge and climatic data for the period 1901-1977 and validated for the period 1978-2008 . Various time series models, like autoregressive (AR), moving average (MA), autoregressive and moving average (ARMA) or singular spectrum analysis and autoregressive moving average (SSA+ARMA) models have been calibrated and their skills evaluated. The best results were obtained using SSA+ARMA models. SSA+ARMA models proved to have the highest forecast skill also for other European rivers (Gamiz-Fortis et al. 2008). Multiple linear regression models using large-scale climatic mode indices as predictors have a higher forecast skill than the time series models. The best predictors for Danube discharge are the North Atlantic Oscillation (NAO) and the East Atlantic/Western Russia patterns during winter and spring. Other patterns, like Polar/Eurasian or Tropical Northern Hemisphere (TNH) are good predictors for summer and autumn discharge. Based on stable teleconnection approach (Ionita et al. 2008) we construct prediction models through a combination of sea surface temperature (SST), temperature (T) and precipitation (PP) from the regions where discharge and SST, T and PP variations are stable correlated. Forecast skills of these models are higher than forecast skills of the time series and multiple regression models. The models calibrated and validated in our study can be used for operational prediction of interannual and seasonal Danube discharge anomalies. References Gamiz-Fortis, S., D. Pozo-Vazquez, R.M. Trigo, and Y. Castro-Diez, Quantifying the predictability of winter river flow in Iberia. Part I: intearannual predictability. J. Climate, 2484-2501, 2008. Gamiz-Fortis, S., D. Pozo-Vazquez, R.M. Trigo, and Y. Castro-Diez, Quantifying the predictability of winter river flow in Iberia. Part II: seasonal predictability. J. Climate, 2503-2518, 2008. Ionita, M., G. Lohmann, and N. Rimbu, Prediction of spring Elbe river discharge based on stable teleconnections with global temperature and precipitation. J. Climate. 6215-6226, 2008.

Simulation Of Combat With An Expert System

NASA Technical Reports Server (NTRS)

Provenzano, J. P.

1989-01-01

Proposed expert system predicts outcomes of combat situations. Called "COBRA", combat outcome based on rules for attrition, system selects rules for mathematical modeling of losses and discrete events in combat according to previous experiences. Used with another software module known as the "Game". Game/COBRA software system, consisting of Game and COBRA modules, provides for both quantitative aspects and qualitative aspects in simulations of battles. COBRA intended for simulation of large-scale military exercises, concepts embodied in it have much broader applicability. In industrial research, knowledge-based system enables qualitative as well as quantitative simulations.

FUTURE APPLICATIONS OF EXPERT SYSTEMS FOR THE EVALUATION OF ENERGY RESOURCES.

USGS Publications Warehouse

Miller, Betty M.

1988-01-01

The loss of professional experience and expertise in the domain of the earth sciences may prove to be one of the most serious outcomes of the boom-and-bust cyclic nature of the volatile energy and mining industries. Promising new applications of powerful computer systems, known as 'expert systems' or 'knowledge-based systems', are predicted for use in the earth science. These systems have the potential capability to capture and preserve the invaluable knowledge bases essential to the evaluation of US energy and mineral resources.

FUTURE APPLICATIONS OF EXPERT SYSTEMS FOR THE EVALUATION OF ENERGY RESOURCES.

USGS Publications Warehouse

Miller, B.M.

1987-01-01

The loss of professional experience and expertise in the domain of the earth sciences may prove to be one of the most serious outcomes of the boom-and-bust cyclic nature of the volatile energy and mining industries. Promising new applications of powerful computer systems, known as 'expert systems' or 'knowledge-based systems', are predicted for use in the earth sciences. These systems have the potential capability to capture and preserve the invaluable knowledge bases essential to the evaluation of the Nation's energy and mineral resources.

Prediction of genotoxic potential of cosmetic ingredients by an in silico battery system consisting of a combination of an expert rule-based system and a statistics-based system.

PubMed

Aiba née Kaneko, Maki; Hirota, Morihiko; Kouzuki, Hirokazu; Mori, Masaaki

2015-02-01

Genotoxicity is the most commonly used endpoint to predict the carcinogenicity of chemicals. The International Conference on Harmonization (ICH) M7 Guideline on Assessment and Control of DNA Reactive (Mutagenic) Impurities in Pharmaceuticals to Limit Potential Carcinogenic Risk offers guidance on (quantitative) structure-activity relationship ((Q)SAR) methodologies that predict the outcome of bacterial mutagenicity assay for actual and potential impurities. We examined the effectiveness of the (Q)SAR approach with the combination of DEREK NEXUS as an expert rule-based system and ADMEWorks as a statistics-based system for the prediction of not only mutagenic potential in the Ames test, but also genotoxic potential in mutagenicity and clastogenicity tests, using a data set of 342 chemicals extracted from the literature. The prediction of mutagenic potential or genotoxic potential by DEREK NEXUS or ADMEWorks showed high values of sensitivity and concordance, while prediction by the combination of DEREK NEXUS and ADMEWorks (battery system) showed the highest values of sensitivity and concordance among the three methods, but the lowest value of specificity. The number of false negatives was reduced with the battery system. We also separately predicted the mutagenic potential and genotoxic potential of 41 cosmetic ingredients listed in the International Nomenclature of Cosmetic Ingredients (INCI) among the 342 chemicals. Although specificity was low with the battery system, sensitivity and concordance were high. These results suggest that the battery system consisting of DEREK NEXUS and ADMEWorks is useful for prediction of genotoxic potential of chemicals, including cosmetic ingredients.

Crohn's Disease and Ulcerative Colitis: A Guide for Parents

MedlinePlus

... for cures; participate in a clinical trial of experimental treatments. Interactive Disease Tracker Use GI Buddy to ... to target them and block inflammation. With many experimental treatments for IBD in clinical trials, experts predict ...

Prompt comprehension in UNIX command production.

PubMed

Doane, S M; McNamara, D S; Kintsch, W; Polson, P G; Clawson, D M

1992-07-01

We hypothesize that a cognitive analysis based on the construction-integration theory of comprehension (Kintsch, 1988) can predict what is difficult about generating complex composite commands in the UNIX operating system. We provide empirical support for assumptions of the Doane, Kintsch, and Polson (1989, 1990) construction-integration model for generating complex commands in UNIX. We asked users whose UNIX experience varied to produce complex UNIX commands, and then provided help prompts whenever the commands that they produced were erroneous. The help prompts were designed to assist subjects with respect to both the knowledge and the memory processes that our UNIX modeling efforts have suggested are lacking in less expert users. It appears that experts respond to different prompts than do novices. Expert performance is helped by the presentation of abstract information, whereas novice and intermediate performance is modified by presentation of concrete information. Second, while presentation of specific prompts helps less expert subjects, they do not provide sufficient information to obtain correct performance. Our analyses suggest that information about the ordering of commands is required to help the less expert with both knowledge and memory load problems in a manner consistent with skill acquisition theories.

An expert system for water quality modelling.

PubMed

Booty, W G; Lam, D C; Bobba, A G; Wong, I; Kay, D; Kerby, J P; Bowen, G S

1992-12-01

The RAISON-micro (Regional Analysis by Intelligent System ON a micro-computer) expert system is being used to predict the effects of mine effluents on receiving waters in Ontario. The potential of this system to assist regulatory agencies and mining industries to define more acceptable effluent limits was shown in an initial study. This system has been further developed so that the expert system helps the model user choose the most appropriate model for a particular application from a hierarchy of models. The system currently contains seven models which range from steady state to time dependent models, for both conservative and nonconservative substances in rivers and lakes. The menu driven expert system prompts the model user for information such as the nature of the receiving water system, the type of effluent being considered, and the range of background data available for use as input to the models. The system can also be used to determine the nature of the environmental conditions at the site which are not available in the textual information database, such as the components of river flow. Applications of the water quality expert system are presented for representative mine sites in the Timmins area of Ontario.

Trajectories of dental anxiety in a birth cohort

PubMed Central

Thomson, W. M.; Broadbent, J. M.; Locker, D.; Poulton, R.

2010-01-01

Objective To examine predictors of dental anxiety trajectories in a longitudinal study of New Zealanders. Methods Prospective study of a complete birth cohort born in 1972/73 in Dunedin, New Zealand, with dental anxiety scale (DAS) scores and dental utilization determined at ages 15, 18, 26 and 32 years. Personality traits were assessed at a superfactor and (more fine-grained) subscale level via the Multidimensional Personality Questionnaire at age 18 years. Group-based trajectory analysis was used to identify dental anxiety trajectories. Results DAS scores from at least three assessments were available for 828 participants. Six dental anxiety trajectories were observed: stable nonanxious low (39.6%); stable nonanxious medium (37.9%); recovery (1.6%); adult-onset anxious (7.7%); stable anxious (7.2%) and adolescent-onset anxious (5.9%). Multivariate analysis showed that males and those with higher DMFS at age 15 years were more likely to be in the stable nonanxious low trajectory group. Membership of the stable nonanxious medium group was predicted by the dental caries experience at age 15 years. Participants who had lost one or more teeth between ages 26 and 32 years had almost twice the relative risk for membership of the adult-onset anxious group. Personality traits predicted group membership. Specifically, high scorers (via median split) on the ‘stress reaction’ subscale had over twice the risk of being in the stable anxious group; low scorers on the traditionalism subscale were more likely to be members of the recovery trajectory group; and high scorers on the ‘social closeness’ subscale had half the risk of being in the stable anxious group. Dental caries experience at age 5 years was also a predictor for the stable anxious group. Membership of the late-adolescent-onset anxious group was predicted by higher dental caries experience by age 15 years, but none of the other predictors was significant. Conclusion Six discrete trajectories of dental anxiety have been observed. Some trajectories (totalling more than 90% of the cohort) had clear associations with external influences, but others were more strongly associated with characteristics such as personality traits. A mix of both influences was observed with only the stable anxious dental anxiety trajectory. PMID:19508269

Motivation and emotion predict medical students' attention to computer-based feedback.

PubMed

Naismith, Laura M; Lajoie, Susanne P

2017-12-14

Students cannot learn from feedback unless they pay attention to it. This study investigated relationships between the personal factors of achievement goal orientations, achievement emotions, and attention to feedback in BioWorld, a computer environment for learning clinical reasoning. Novice medical students (N = 28) completed questionnaires to measure their achievement goal orientations and then thought aloud while solving three endocrinology patient cases and reviewing corresponding expert solutions. Questionnaires administered after each case measured participants' experiences of five feedback emotions: pride, relief, joy, shame, and anger. Attention to individual text segments of the expert solutions was modelled using logistic regression and the method of generalized estimating equations. Participants did not attend to all of the feedback that was available to them. Performance-avoidance goals and shame positively predicted attention to feedback, and performance-approach goals and relief negatively predicted attention to feedback. Aspects of how the feedback was displayed also influenced participants' attention. Findings are discussed in terms of their implications for educational theory as well as the design and use of computer learning environments in medical education.

Intelligent instrumentation applied in environment management

NASA Astrophysics Data System (ADS)

Magheti, Mihnea I.; Walsh, Patrick; Delassus, Patrick

2005-06-01

The use of information and communications technology in environment management and research has witnessed a renaissance in recent years. From optical sensor technology, expert systems, GIS and communications technologies to computer aided harvesting and yield prediction, these systems are increasable used for applications developing in the management sector of natural resources and biodiversity. This paper presents an environmental decision support system, used to monitor biodiversity and present a risk rating for the invasion of pests into the particular systems being examined. This system will utilise expert mobile technology coupled with artificial intelligence and predictive modelling, and will emphasize the potential for expansion into many areas of intelligent remote sensing and computer aided decision-making for environment management or certification. Monitoring and prediction in natural systems, harnessing the potential of computing and communication technologies is an emerging technology within the area of environmental management. This research will lead to the initiation of a hardware and software multi tier decision support system for environment management allowing an evaluation of areas for biodiversity or areas at risk from invasive species, based upon environmental factors/systems.

Critical thinking traits of top-tier experts and implications for computer science education

NASA Astrophysics Data System (ADS)

Bushey, Dean E.

A documented shortage of technical leadership and top-tier performers in computer science jeopardizes the technological edge, security, and economic well-being of the nation. The 2005 President's Information and Technology Advisory Committee (PITAC) Report on competitiveness in computational sciences highlights the major impact of science, technology, and innovation in keeping America competitive in the global marketplace. It stresses the fact that the supply of science, technology, and engineering experts is at the core of America's technological edge, national competitiveness and security. However, recent data shows that both undergraduate and postgraduate production of computer scientists is falling. The decline is "a quiet crisis building in the United States," a crisis that, if allowed to continue unchecked, could endanger America's well-being and preeminence among the world's nations. Past research on expert performance has shown that the cognitive traits of critical thinking, creativity, and problem solving possessed by top-tier performers can be identified, observed and measured. The studies show that the identified attributes are applicable across many domains and disciplines. Companies have begun to realize that cognitive skills are important for high-level performance and are reevaluating the traditional academic standards they have used to predict success for their top-tier performers in computer science. Previous research in the computer science field has focused either on programming skills of its experts or has attempted to predict the academic success of students at the undergraduate level. This study, on the other hand, examines the critical-thinking skills found among experts in the computer science field in order to explore the questions, "What cognitive skills do outstanding performers possess that make them successful?" and "How do currently used measures of academic performance correlate to critical-thinking skills among students?" The results of this study suggest a need to examine how critical-thinking abilities are learned in the undergraduate computer science curriculum and the need to foster these abilities in order to produce the high-level, critical-thinking professionals necessary to fill the growing need for these experts. Due to the fact that current measures of academic performance do not adequately depict students' cognitive abilities, assessment of these skills must be incorporated into existing curricula.

EULAR recommendations for women's health and the management of family planning, assisted reproduction, pregnancy and menopause in patients with systemic lupus erythematosus and/or antiphospholipid syndrome.

PubMed

Andreoli, L; Bertsias, G K; Agmon-Levin, N; Brown, S; Cervera, R; Costedoat-Chalumeau, N; Doria, A; Fischer-Betz, R; Forger, F; Moraes-Fontes, M F; Khamashta, M; King, J; Lojacono, A; Marchiori, F; Meroni, P L; Mosca, M; Motta, M; Ostensen, M; Pamfil, C; Raio, L; Schneider, M; Svenungsson, E; Tektonidou, M; Yavuz, S; Boumpas, D; Tincani, A

2017-03-01

Develop recommendations for women's health issues and family planning in systemic lupus erythematosus (SLE) and/or antiphospholipid syndrome (APS). Systematic review of evidence followed by modified Delphi method to compile questions, elicit expert opinions and reach consensus. Family planning should be discussed as early as possible after diagnosis. Most women can have successful pregnancies and measures can be taken to reduce the risks of adverse maternal or fetal outcomes. Risk stratification includes disease activity, autoantibody profile, previous vascular and pregnancy morbidity, hypertension and the use of drugs (emphasis on benefits from hydroxychloroquine and antiplatelets/anticoagulants). Hormonal contraception and menopause replacement therapy can be used in patients with stable/inactive disease and low risk of thrombosis. Fertility preservation with gonadotropin-releasing hormone analogues should be considered prior to the use of alkylating agents. Assisted reproduction techniques can be safely used in patients with stable/inactive disease; patients with positive antiphospholipid antibodies/APS should receive anticoagulation and/or low-dose aspirin. Assessment of disease activity, renal function and serological markers is important for diagnosing disease flares and monitoring for obstetrical adverse outcomes. Fetal monitoring includes Doppler ultrasonography and fetal biometry, particularly in the third trimester, to screen for placental insufficiency and small for gestational age fetuses. Screening for gynaecological malignancies is similar to the general population, with increased vigilance for cervical premalignant lesions if exposed to immunosuppressive drugs. Human papillomavirus immunisation can be used in women with stable/inactive disease. Recommendations for women's health issues in SLE and/or APS were developed using an evidence-based approach followed by expert consensus. Published by the BMJ Publishing Group Limited. For permission to use (where not already granted under a licence) please go to http://www.bmj.com/company/products-services/rights-and-licensing/.

Materials Screening for the Discovery of New Half-Heuslers: Machine Learning versus ab Initio Methods.

PubMed

Legrain, Fleur; Carrete, Jesús; van Roekeghem, Ambroise; Madsen, Georg K H; Mingo, Natalio

2018-01-18

Machine learning (ML) is increasingly becoming a helpful tool in the search for novel functional compounds. Here we use classification via random forests to predict the stability of half-Heusler (HH) compounds, using only experimentally reported compounds as a training set. Cross-validation yields an excellent agreement between the fraction of compounds classified as stable and the actual fraction of truly stable compounds in the ICSD. The ML model is then employed to screen 71 178 different 1:1:1 compositions, yielding 481 likely stable candidates. The predicted stability of HH compounds from three previous high-throughput ab initio studies is critically analyzed from the perspective of the alternative ML approach. The incomplete consistency among the three separate ab initio studies and between them and the ML predictions suggests that additional factors beyond those considered by ab initio phase stability calculations might be determinant to the stability of the compounds. Such factors can include configurational entropies and quasiharmonic contributions.

High-pressure phase of brucite stable at Earth's mantle transition zone and lower mantle conditions.

PubMed

Hermann, Andreas; Mookherjee, Mainak

2016-12-06

We investigate the high-pressure phase diagram of the hydrous mineral brucite, Mg(OH) 2 , using structure search algorithms and ab initio simulations. We predict a high-pressure phase stable at pressure and temperature conditions found in cold subducting slabs in Earth's mantle transition zone and lower mantle. This prediction implies that brucite can play a much more important role in water transport and storage in Earth's interior than hitherto thought. The predicted high-pressure phase, stable in calculations between 20 and 35 GPa and up to 800 K, features MgO 6 octahedral units arranged in the anatase-TiO 2 structure. Our findings suggest that brucite will transform from a layered to a compact 3D network structure before eventual decomposition into periclase and ice. We show that the high-pressure phase has unique spectroscopic fingerprints that should allow for straightforward detection in experiments. The phase also has distinct elastic properties that might make its direct detection in the deep Earth possible with geophysical methods.

Developing Expert Systems

DOT National Transportation Integrated Search

1974-10-01

The basic manual, published as the first volume of this report, is intended for use as a tool in predicting noise levels which will be generated by freely-flowing vehicle traffic along a highway of known characteristics. The first volume explains the...

Ontology-based tools to expedite predictive model construction.

PubMed

Haug, Peter; Holmen, John; Wu, Xinzi; Mynam, Kumar; Ebert, Matthew; Ferraro, Jeffrey

2014-01-01

Large amounts of medical data are collected electronically during the course of caring for patients using modern medical information systems. This data presents an opportunity to develop clinically useful tools through data mining and observational research studies. However, the work necessary to make sense of this data and to integrate it into a research initiative can require substantial effort from medical experts as well as from experts in medical terminology, data extraction, and data analysis. This slows the process of medical research. To reduce the effort required for the construction of computable, diagnostic predictive models, we have developed a system that hybridizes a medical ontology with a large clinical data warehouse. Here we describe components of this system designed to automate the development of preliminary diagnostic models and to provide visual clues that can assist the researcher in planning for further analysis of the data behind these models.

Feared consequences of panic attacks in panic disorder: a qualitative and quantitative analysis.

PubMed

Raffa, Susan D; White, Kamila S; Barlow, David H

2004-01-01

Cognitions are hypothesized to play a central role in panic disorder (PD). Previous studies have used questionnaires to assess cognitive content, focusing on prototypical cognitions associated with PD; however, few studies have qualitatively examined cognitions associated with the feared consequences of panic attacks. The purpose of this study was to conduct a qualitative and quantitative analysis of feared consequences of panic attacks. The initial, qualitative analysis resulted in the development of 32 categories of feared consequences. The categories were derived from participant responses to a standardized, semi-structured question (n = 207). Five expert-derived categories were then utilized to quantitatively examine the relationship between cognitions and indicators of PD severity. Cognitions did not predict PD severity; however, correlational analyses indicated some predictive validity to the expert-derived categories. The qualitative analysis identified additional areas of patient-reported concern not included in previous research that may be important in the assessment and treatment of PD.

Individual and Joint Expert Judgments as Reference Standards in Artifact Detection

PubMed Central

Verduijn, Marion; Peek, Niels; de Keizer, Nicolette F.; van Lieshout, Erik-Jan; de Pont, Anne-Cornelie J.M.; Schultz, Marcus J.; de Jonge, Evert; de Mol, Bas A.J.M.

2008-01-01

Objective To investigate the agreement among clinical experts in their judgments of monitoring data with respect to artifacts, and to examine the effect of reference standards that consist of individual and joint expert judgments on the performance of artifact filters. Design Individual judgments of four physicians, a majority vote judgment, and a consensus judgment were obtained for 30 time series of three monitoring variables: mean arterial blood pressure (ABPm), central venous pressure (CVP), and heart rate (HR). The individual and joint judgments were used to tune three existing automated filtering methods and to evaluate the performance of the resulting filters. Measurements The interrater agreement was calculated in terms of positive specific agreement (PSA). The performance of the artifact filters was quantified in terms of sensitivity and positive predictive value (PPV). Results PSA values between 0.33 and 0.85 were observed among clinical experts in their selection of artifacts, with relatively high values for CVP data. Artifact filters developed using judgments of individual experts were found to moderately generalize to new time series and other experts; sensitivity values ranged from 0.40 to 0.60 for ABPm and HR filters (PPV: 0.57–0.84), and from 0.63 to 0.80 for CVP filters (PPV: 0.71–0.86). A higher performance value for the filters was found for the three variable types when joint judgments were used for tuning the filtering methods. Conclusion Given the disagreement among experts in their individual judgment of monitoring data with respect to artifacts, the use of joint reference standards obtained from multiple experts is recommended for development of automatic artifact filters. PMID:18096912

Earlier Visual N1 Latencies in Expert Video-Game Players: A Temporal Basis of Enhanced Visuospatial Performance?

PubMed Central

Latham, Andrew J.; Patston, Lucy L. M.; Westermann, Christine; Kirk, Ian J.; Tippett, Lynette J.

2013-01-01

Increasing behavioural evidence suggests that expert video game players (VGPs) show enhanced visual attention and visuospatial abilities, but what underlies these enhancements remains unclear. We administered the Poffenberger paradigm with concurrent electroencephalogram (EEG) recording to assess occipital N1 latencies and interhemispheric transfer time (IHTT) in expert VGPs. Participants comprised 15 right-handed male expert VGPs and 16 non-VGP controls matched for age, handedness, IQ and years of education. Expert VGPs began playing before age 10, had a minimum 8 years experience, and maintained playtime of at least 20 hours per week over the last 6 months. Non-VGPs had little-to-no game play experience (maximum 1.5 years). Participants responded to checkerboard stimuli presented to the left and right visual fields while 128-channel EEG was recorded. Expert VGPs responded significantly more quickly than non-VGPs. Expert VGPs also had significantly earlier occipital N1s in direct visual pathways (the hemisphere contralateral to the visual field in which the stimulus was presented). IHTT was calculated by comparing the latencies of occipital N1 components between hemispheres. No significant between-group differences in electrophysiological estimates of IHTT were found. Shorter N1 latencies may enable expert VGPs to discriminate attended visual stimuli significantly earlier than non-VGPs and contribute to faster responding in visual tasks. As successful video-game play requires precise, time pressured, bimanual motor movements in response to complex visual stimuli, which in this sample began during early childhood, these differences may reflect the experience and training involved during the development of video-game expertise, but training studies are needed to test this prediction. PMID:24058667

Earlier visual N1 latencies in expert video-game players: a temporal basis of enhanced visuospatial performance?

PubMed

Latham, Andrew J; Patston, Lucy L M; Westermann, Christine; Kirk, Ian J; Tippett, Lynette J

2013-01-01

Increasing behavioural evidence suggests that expert video game players (VGPs) show enhanced visual attention and visuospatial abilities, but what underlies these enhancements remains unclear. We administered the Poffenberger paradigm with concurrent electroencephalogram (EEG) recording to assess occipital N1 latencies and interhemispheric transfer time (IHTT) in expert VGPs. Participants comprised 15 right-handed male expert VGPs and 16 non-VGP controls matched for age, handedness, IQ and years of education. Expert VGPs began playing before age 10, had a minimum 8 years experience, and maintained playtime of at least 20 hours per week over the last 6 months. Non-VGPs had little-to-no game play experience (maximum 1.5 years). Participants responded to checkerboard stimuli presented to the left and right visual fields while 128-channel EEG was recorded. Expert VGPs responded significantly more quickly than non-VGPs. Expert VGPs also had significantly earlier occipital N1s in direct visual pathways (the hemisphere contralateral to the visual field in which the stimulus was presented). IHTT was calculated by comparing the latencies of occipital N1 components between hemispheres. No significant between-group differences in electrophysiological estimates of IHTT were found. Shorter N1 latencies may enable expert VGPs to discriminate attended visual stimuli significantly earlier than non-VGPs and contribute to faster responding in visual tasks. As successful video-game play requires precise, time pressured, bimanual motor movements in response to complex visual stimuli, which in this sample began during early childhood, these differences may reflect the experience and training involved during the development of video-game expertise, but training studies are needed to test this prediction.

Expert opinion on landslide susceptibility elicted by probabilistic inversion from scenario rankings

NASA Astrophysics Data System (ADS)

Lee, Katy; Dashwood, Claire; Lark, Murray

2016-04-01

For many natural hazards the opinion of experts, with experience in assessing susceptibility under different circumstances, is a valuable source of information on which to base risk assessments. This is particularly important where incomplete process understanding, and limited data, limit the scope to predict susceptibility by mechanistic or statistical modelling. The expert has a tacit model of a system, based on their understanding of processes and their field experience. This model may vary in quality, depending on the experience of the expert. There is considerable interest in how one may elicit expert understanding by a process which is transparent and robust, to provide a basis for decision support. One approach is to provide experts with a set of scenarios, and then to ask them to rank small overlapping subsets of these with respect to susceptibility. Methods of probabilistic inversion have been used to compute susceptibility scores for each scenario, implicit in the expert ranking. It is also possible to model these scores as functions of measurable properties of the scenarios. This approach has been used to assess susceptibility of animal populations to invasive diseases, to assess risk to vulnerable marine environments and to assess the risk in hypothetical novel technologies for food production. We will present the results of a study in which a group of geologists with varying degrees of expertise in assessing landslide hazards were asked to rank sets of hypothetical simplified scenarios with respect to land slide susceptibility. We examine the consistency of their rankings and the importance of different properties of the scenarios in the tacit susceptibility model that their rankings implied. Our results suggest that this is a promising approach to the problem of how experts can communicate their tacit model of uncertain systems to those who want to make use of their expertise.

Consensus coding sequence (CCDS) database: a standardized set of human and mouse protein-coding regions supported by expert curation

PubMed Central

Pujar, Shashikant; O’Leary, Nuala A; Farrell, Catherine M; Mudge, Jonathan M; Wallin, Craig; Diekhans, Mark; Barnes, If; Bennett, Ruth; Berry, Andrew E; Cox, Eric; Davidson, Claire; Goldfarb, Tamara; Gonzalez, Jose M; Hunt, Toby; Jackson, John; Joardar, Vinita; Kay, Mike P; Kodali, Vamsi K; McAndrews, Monica; McGarvey, Kelly M; Murphy, Michael; Rajput, Bhanu; Rangwala, Sanjida H; Riddick, Lillian D; Seal, Ruth L; Webb, David; Zhu, Sophia; Aken, Bronwen L; Bult, Carol J; Frankish, Adam; Pruitt, Kim D

2018-01-01

Abstract The Consensus Coding Sequence (CCDS) project provides a dataset of protein-coding regions that are identically annotated on the human and mouse reference genome assembly in genome annotations produced independently by NCBI and the Ensembl group at EMBL-EBI. This dataset is the product of an international collaboration that includes NCBI, Ensembl, HUGO Gene Nomenclature Committee, Mouse Genome Informatics and University of California, Santa Cruz. Identically annotated coding regions, which are generated using an automated pipeline and pass multiple quality assurance checks, are assigned a stable and tracked identifier (CCDS ID). Additionally, coordinated manual review by expert curators from the CCDS collaboration helps in maintaining the integrity and high quality of the dataset. The CCDS data are available through an interactive web page (https://www.ncbi.nlm.nih.gov/CCDS/CcdsBrowse.cgi) and an FTP site (ftp://ftp.ncbi.nlm.nih.gov/pub/CCDS/). In this paper, we outline the ongoing work, growth and stability of the CCDS dataset and provide updates on new collaboration members and new features added to the CCDS user interface. We also present expert curation scenarios, with specific examples highlighting the importance of an accurate reference genome assembly and the crucial role played by input from the research community. PMID:29126148

Positive and negative affect dimensions in chronic knee osteoarthritis: effects on clinical and laboratory pain.

PubMed

Finan, Patrick H; Quartana, Phillip J; Smith, Michael T

2013-06-01

This study investigated whether daily and laboratory assessed pain differs as a function of the temporal stability and valence of affect in individuals with chronic knee osteoarthritis (KOA). One hundred fifty-one men and women with KOA completed 14 days of electronic diaries assessing positive affect (PA), negative affect (NA), and clinical pain. A subset of participants (n =79) engaged in quantitative sensory testing (QST). State PA and NA were assessed prior to administration of stimuli that induced suprathreshold pain and temporal summation. Multilevel modeling and multiple regression evaluated associations of affect and pain as a function of valence (i.e., positive versus negative) and stability (i.e., stable versus state). In the diary, stable NA (B = -.63, standard error [SE] = .13, p < .001) was a stronger predictor of clinical KOA pain than stable PA (B = -.18, SE = .11, p = .091), and state PA (B = -.09, p < .001) was a stronger predictor of concurrent daily clinical pain than state NA (B = .04, SE = .02, p = .068). In the laboratory, state PA (B = -.05, SE = .02, p = .042), but not state NA (p = .46), predicted diminished temporal summation of mechanical pain. Stable NA is more predictive of clinical pain than stable PA, whereas state PA is more predictive of both clinical and laboratory pain than state NA. The findings suggest that dynamic affect-pain processes in the field may reflect individual differences in central pain facilitation.

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

PubMed Central

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. PMID:28686651

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

PubMed

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.

Medicine is not science: guessing the future, predicting the past.

PubMed

Miller, Clifford

2014-12-01

Irregularity limits human ability to know, understand and predict. A better understanding of irregularity may improve the reliability of knowledge. Irregularity and its consequences for knowledge are considered. Reliable predictive empirical knowledge of the physical world has always been obtained by observation of regularities, without needing science or theory. Prediction from observational knowledge can remain reliable despite some theories based on it proving false. A naïve theory of irregularity is outlined. Reducing irregularity and/or increasing regularity can increase the reliability of knowledge. Beyond long experience and specialization, improvements include implementing supporting knowledge systems of libraries of appropriately classified prior cases and clinical histories and education about expertise, intuition and professional judgement. A consequence of irregularity and complexity is that classical reductionist science cannot provide reliable predictions of the behaviour of complex systems found in nature, including of the human body. Expertise, expert judgement and their exercise appear overarching. Diagnosis involves predicting the past will recur in the current patient applying expertise and intuition from knowledge and experience of previous cases and probabilistic medical theory. Treatment decisions are an educated guess about the future (prognosis). Benefits of the improvements suggested here are likely in fields where paucity of feedback for practitioners limits development of reliable expert diagnostic intuition. Further analysis, definition and classification of irregularity is appropriate. Observing and recording irregularities are initial steps in developing irregularity theory to improve the reliability and extent of knowledge, albeit some forms of irregularity present inherent difficulties. © 2014 John Wiley & Sons, Ltd.

Longitudinal quasi-static stability predicts changes in dog gait on rough terrain

PubMed Central

Reeve, Michelle A.; Haynes, G. Clark; Revzen, Shai; Koditschek, Daniel E.; Spence, Andrew J.

2017-01-01

ABSTRACT Legged animals utilize gait selection to move effectively and must recover from environmental perturbations. We show that on rough terrain, domestic dogs, Canis lupus familiaris, spend more time in longitudinal quasi-statically stable patterns of movement. Here, longitudinal refers to the rostro-caudal axis. We used an existing model in the literature to quantify the longitudinal quasi-static stability of gaits neighbouring the walk, and found that trot-like gaits are more stable. We thus hypothesized that when perturbed, the rate of return to a stable gait would depend on the direction of perturbation, such that perturbations towards less quasi-statically stable patterns of movement would be more rapid than those towards more stable patterns of movement. The net result of this would be greater time spent in longitudinally quasi-statically stable patterns of movement. Limb movement patterns in which diagonal limbs were more synchronized (those more like a trot) have higher longitudinal quasi-static stability. We therefore predicted that as dogs explored possible limb configurations on rough terrain at walking speeds, the walk would shift towards trot. We gathered experimental data quantifying dog gait when perturbed by rough terrain and confirmed this prediction using GPS and inertial sensors (n=6, P<0.05). By formulating gaits as trajectories on the n-torus we are able to make tractable the analysis of gait similarity. These methods can be applied in a comparative study of gait control which will inform the ultimate role of the constraints and costs impacting locomotion, and have applications in diagnostic procedures for gait abnormalities, and in the development of agile legged robots. PMID:28264903

Longitudinal quasi-static stability predicts changes in dog gait on rough terrain.

PubMed

Wilshin, Simon; Reeve, Michelle A; Haynes, G Clark; Revzen, Shai; Koditschek, Daniel E; Spence, Andrew J

2017-05-15

Legged animals utilize gait selection to move effectively and must recover from environmental perturbations. We show that on rough terrain, domestic dogs, Canis lupus familiaris , spend more time in longitudinal quasi-statically stable patterns of movement. Here, longitudinal refers to the rostro-caudal axis. We used an existing model in the literature to quantify the longitudinal quasi-static stability of gaits neighbouring the walk, and found that trot-like gaits are more stable. We thus hypothesized that when perturbed, the rate of return to a stable gait would depend on the direction of perturbation, such that perturbations towards less quasi-statically stable patterns of movement would be more rapid than those towards more stable patterns of movement. The net result of this would be greater time spent in longitudinally quasi-statically stable patterns of movement. Limb movement patterns in which diagonal limbs were more synchronized (those more like a trot) have higher longitudinal quasi-static stability. We therefore predicted that as dogs explored possible limb configurations on rough terrain at walking speeds, the walk would shift towards trot. We gathered experimental data quantifying dog gait when perturbed by rough terrain and confirmed this prediction using GPS and inertial sensors ( n =6, P <0.05). By formulating gaits as trajectories on the n -torus we are able to make tractable the analysis of gait similarity. These methods can be applied in a comparative study of gait control which will inform the ultimate role of the constraints and costs impacting locomotion, and have applications in diagnostic procedures for gait abnormalities, and in the development of agile legged robots. © 2017. Published by The Company of Biologists Ltd.

Comparison of the Performance of the Warfarin Pharmacogenetics Algorithms in Patients with Surgery of Heart Valve Replacement and Heart Valvuloplasty.

PubMed

Xu, Hang; Su, Shi; Tang, Wuji; Wei, Meng; Wang, Tao; Wang, Dongjin; Ge, Weihong

2015-09-01

A large number of warfarin pharmacogenetics algorithms have been published. Our research was aimed to evaluate the performance of the selected pharmacogenetic algorithms in patients with surgery of heart valve replacement and heart valvuloplasty during the phase of initial and stable anticoagulation treatment. 10 pharmacogenetic algorithms were selected by searching PubMed. We compared the performance of the selected algorithms in a cohort of 193 patients during the phase of initial and stable anticoagulation therapy. Predicted dose was compared to therapeutic dose by using a predicted dose percentage that falls within 20% threshold of the actual dose (percentage within 20%) and mean absolute error (MAE). The average warfarin dose for patients was 3.05±1.23mg/day for initial treatment and 3.45±1.18mg/day for stable treatment. The percentages of the predicted dose within 20% of the therapeutic dose were 44.0±8.8% and 44.6±9.7% for the initial and stable phases, respectively. The MAEs of the selected algorithms were 0.85±0.18mg/day and 0.93±0.19mg/day, respectively. All algorithms had better performance in the ideal group than in the low dose and high dose groups. The only exception is the Wadelius et al. algorithm, which had better performance in the high dose group. The algorithms had similar performance except for the Wadelius et al. and Miao et al. algorithms, which had poor accuracy in our study cohort. The Gage et al. algorithm had better performance in both phases of initial and stable treatment. Algorithms had relatively higher accuracy in the >50years group of patients on the stable phase. Copyright © 2015 Elsevier Ltd. All rights reserved.

Increasing atmospheric CO2 overrides the historical legacy of multiple stable biome states in Africa.

PubMed

Moncrieff, Glenn R; Scheiter, Simon; Bond, William J; Higgins, Steven I

2014-02-01

The dominant vegetation over much of the global land surface is not predetermined by contemporary climate, but also influenced by past environmental conditions. This confounds attempts to predict current and future biome distributions, because even a perfect model would project multiple possible biomes without knowledge of the historical vegetation state. Here we compare the distribution of tree- and grass-dominated biomes across Africa simulated using a dynamic global vegetation model (DGVM). We explicitly evaluate where and under what conditions multiple stable biome states are possible for current and projected future climates. Our simulation results show that multiple stable biomes states are possible for vast areas of tropical and subtropical Africa under current conditions. Widespread loss of the potential for multiple stable biomes states is projected in the 21st Century, driven by increasing atmospheric CO2 . Many sites where currently both tree-dominated and grass-dominated biomes are possible become deterministically tree-dominated. Regions with multiple stable biome states are widespread and require consideration when attempting to predict future vegetation changes. Testing for behaviour characteristic of systems with multiple stable equilibria, such as hysteresis and dependence on historical conditions, and the resulting uncertainty in simulated vegetation, will lead to improved projections of global change impacts. © 2013 The Authors. New Phytologist © 2013 New Phytologist Trust.

Trends in Fetal Medicine: A 10-Year Bibliometric Analysis of Prenatal Diagnosis

PubMed Central

Dhombres, Ferdinand; Bodenreider, Olivier

2018-01-01

The objective is to automatically identify trends in Fetal Medicine over the past 10 years through a bibliometric analysis of articles published in Prenatal Diagnosis, using text mining techniques. We processed 2,423 full-text articles published in Prenatal Diagnosis between 2006 and 2015. We extracted salient terms, calculated their frequencies over time, and established evolution profiles for terms, from which we derived falling, stable, and rising trends. We identified 618 terms with a falling trend, 2,142 stable terms, and 839 terms with a rising trend. Terms with increasing frequencies include those related to statistics and medical study design. The most recent of these terms reflect the new opportunities of next- generation sequencing. Many terms related to cytogenetics exhibit a falling trend. A bibliometric analysis based on text mining effectively supports identification of trends over time. This scalable approach is complementary to analyses based on metadata or expert opinion. PMID:29295220

The local lymph node assay and the assessment of relative potency: status of validation.

PubMed

Basketter, David A; Gerberick, Frank; Kimber, Ian

2007-08-01

For the prediction of skin sensitization potential, the local lymph node assay (LLNA) is a fully validated alternative to guinea-pig tests. More recently, information from LLNA dose-response analyses has been used to assess the relative potency of skin sensitizing chemicals. These data are then deployed for risk assessment and risk management. In this commentary, the utility and validity of these relative potency measurements are reviewed. It is concluded that the LLNA does provide a valuable assessment of relative sensitizing potency in the form of the estimated concentration of a chemical required to produce a threefold stimulation of draining lymph node cell proliferation compared with concurrent controls (EC3 value) and that all reasonable validation requirements have been addressed successfully. EC3 measurements are reproducible in both intra- and interlaboratory evaluations and are stable over time. It has been shown also, by several independent groups, that EC3 values correlate closely with data on relative human skin sensitization potency. Consequently, the recommendation made here is that LLNA EC3 measurements should now be regarded as a validated method for the determination of the relative potency of skin sensitizing chemicals, a conclusion that has already been reached by a number of independent expert groups.

Implications of HLA-allele associations for the study of type IV drug hypersensitivity reactions.

PubMed

Sullivan, A; Watkinson, J; Waddington, J; Park, B K; Naisbitt, D J

2018-03-01

Type IV drug hypersensitivity remains an important clinical problem and an obstacle to the development of new drugs. Several forms of drug hypersensitivity are associated with expression of specific HLA alleles. Furthermore, drug-specific T-lymphocytes have been isolated from patients with reactions. Despite this, controversy remains as to how drugs interact with immune receptors to stimulate a T-cell response. Areas covered: This article reviews the pathways of T-cell activation by drugs and how the ever increasing number of associations between expression of HLA alleles and susceptibility to hypersensitivity is impacting on our research effort to understanding this form of iatrogenic disease. Expert opinion: For a drug to activate a T-cell, a complex is formed between HLA molecules, an HLA binding peptide, the drug and the T-cell receptor. T-cell responses can involve drugs and stable or reactive metabolites bound covalently or non-covalently to any component of this complex. Recent research has linked the HLA associations to the disease through the characterization of drug-specific T-cell responses restricted to specific alleles. However, there is now a need to identify the additional genetic or environment factors that determine susceptibility and use our increased knowledge to develop predictive immunogenicity tests that offer benefit to Pharma developing new drugs.

Developments in REDES: The rocket engine design expert system

NASA Technical Reports Server (NTRS)

Davidian, Kenneth O.

1990-01-01

The Rocket Engine Design Expert System (REDES) is being developed at the NASA-Lewis to collect, automate, and perpetuate the existing expertise of performing a comprehensive rocket engine analysis and design. Currently, REDES uses the rigorous JANNAF methodology to analyze the performance of the thrust chamber and perform computational studies of liquid rocket engine problems. The following computer codes were included in REDES: a gas properties program named GASP, a nozzle design program named RAO, a regenerative cooling channel performance evaluation code named RTE, and the JANNAF standard liquid rocket engine performance prediction code TDK (including performance evaluation modules ODE, ODK, TDE, TDK, and BLM). Computational analyses are being conducted by REDES to provide solutions to liquid rocket engine thrust chamber problems. REDES is built in the Knowledge Engineering Environment (KEE) expert system shell and runs on a Sun 4/110 computer.

Developments in REDES: The Rocket Engine Design Expert System

NASA Technical Reports Server (NTRS)

Davidian, Kenneth O.

1990-01-01

The Rocket Engine Design Expert System (REDES) was developed at NASA-Lewis to collect, automate, and perpetuate the existing expertise of performing a comprehensive rocket engine analysis and design. Currently, REDES uses the rigorous JANNAF methodology to analyze the performance of the thrust chamber and perform computational studies of liquid rocket engine problems. The following computer codes were included in REDES: a gas properties program named GASP; a nozzle design program named RAO; a regenerative cooling channel performance evaluation code named RTE; and the JANNAF standard liquid rocket engine performance prediction code TDK (including performance evaluation modules ODE, ODK, TDE, TDK, and BLM). Computational analyses are being conducted by REDES to provide solutions to liquid rocket engine thrust chamber problems. REDES was built in the Knowledge Engineering Environment (KEE) expert system shell and runs on a Sun 4/110 computer.

An expert system-based approach to prediction of year-to-year climatic variations in the North Atlantic region

NASA Astrophysics Data System (ADS)

Rodionov, S. N.; Martin, J. H.

1999-07-01

A novel approach to climate forecasting on an interannual time scale is described. The approach is based on concepts and techniques from artificial intelligence and expert systems. The suitability of this approach to climate diagnostics and forecasting problems and its advantages compared with conventional forecasting techniques are discussed. The article highlights some practical aspects of the development of climatic expert systems (CESs) and describes an implementation of such a system for the North Atlantic (CESNA). Particular attention is paid to the content of CESNA's knowledge base and those conditions that make climatic forecasts one to several years in advance possible. A detailed evaluation of the quality of the experimental real-time forecasts made by CESNA for the winters of 1995-1996, 1996-1997 and 1997-1998 are presented.

[Systematic detection of physical child abuse at emergency rooms].

PubMed

Sittig, J S; Uiterwaal, C S P M; Moons, K G M; Russel, I M B; Nievelstein, R A J; Nieuwenhuis, E E S; van de Putte, E M

2016-01-01

The aim of our diagnostic accuracy study Child Abuse Inventory at Emergency Rooms (CHAIN-ER) was to establish whether a widely used checklist accurately detects or excludes physical abuse among children presenting to ERs with physical injury. A large multicentre study with a 6-month follow-up in 4 ERs in The Netherlands. Participants were 4290 children aged 0-7 years, attending the ER because of physical injury. All children were systematically tested with an easy-to-use child abuse checklist (index test). A national expert panel (reference standard) retrospectively assessed all children with positive screens and a 15% random sample of the children with negative screens for physical abuse, using additional information, namely, an injury history taken by a paediatrician, information provided by the general practitioner, youth doctor and social services by structured questionnaires, and 6-month follow-up information. Our main outcome measure was physical child abuse; secondary outcome measure was injury due to neglect and need for help. 4253/4290 (99%) parents agreed to follow-up. At a prevalence of 0.07% (3/4253) for inflicted injury by expert panel decision, the positive predictive value of the checklist was 0.03 (95% CI 0.006 to 0.085), and the negative predictive value 1.0 (0.994 to 1.0). There was 100% (93 to 100) agreement about inflicted injury in children, with positive screens between the expert panel and child abuse experts. Rare cases of inflicted injury among preschool children presenting at ERs for injury are very likely captured by easy-to-use checklists, but at very high false-positive rates. Subsequent assessment by child abuse experts can be safely restricted to children with positive screens at very low risk of missing cases of inflicted injury. Because of the high false positive rate, we do advise careful prior consideration of cost-effectiveness and clinical and societal implications before de novo implementation.

Does experience in hysteroscopy improve accuracy and inter-observer agreement in the management of abnormal uterine bleeding?

PubMed

Bourdel, Nicolas; Modaffari, Paola; Tognazza, Enrica; Pertile, Riccardo; Chauvet, Pauline; Botchorishivili, Revaz; Savary, Dennis; Pouly, Jean Luc; Rabischong, Benoit; Canis, Michel

2016-12-01

Hysteroscopic reliability may be influenced by the experience of the operator and by a lack of morphological diagnostic criteria for endometrial malignant pathologies. The aim of this study was to evaluate the diagnostic accuracy and the inter-observer agreement (IOA) in the management of abnormal uterine bleeding (AUB) among different experienced gynecologists. Each gynecologist, without any other clinical information, was asked to evaluate the anonymous video recordings of 51 consecutive patients who underwent hysteroscopy and endometrial resection for AUB. Experts (>500 hysteroscopies), seniors (20-499 procedures) and junior (≤19 procedures) gynecologists were asked to judge endometrial macroscopic appearance (benign, suspicious or frankly malignant). They also had to propose the histological diagnosis (atrophic or proliferative endometrium; simple, glandulocystic or atypical endometrial hyperplasia and endometrial carcinoma). Observers were free to indicate whether the quality of recordings were not good enough for adequate assessment. IOA (k coefficient), sensitivity, specificity, predictive value and the likelihood ratio were calculated. Five expert, five senior and six junior gynecologists were involved in the study. Considering endometrial cancer and endometrial atypical hyperplasia, sensitivity and specificity were respectively 55.5 % and 84.5 % for juniors, 66.6 % and 81.2 % for seniors and 86.6 % and 87.3 % for experts. Concerning endometrial macroscopic appearance, IOA was poor for juniors (k = 0.10) and fair for seniors and experts (k = 0.23 and 0.22, respectively). IOA was poor for juniors and experts (k = 0.18 and 0.20, respectively) and fair for seniors (k = 0.30) in predicting the histological diagnosis. Sensitivity improves with the observer's experience, but inter-observer agreement and reproducibility of hysteroscopy for endometrial malignancies are not satisfying no matter the level of expertise. Therefore, an accurate and complete endometrial sampling is still needed.

Improved artificial neural networks in prediction of malignancy of lesions in contrast-enhanced MR-mammography.

PubMed

Vomweg, T W; Buscema, M; Kauczor, H U; Teifke, A; Intraligi, M; Terzi, S; Heussel, C P; Achenbach, T; Rieker, O; Mayer, D; Thelen, M

2003-09-01

The aim of this study was to evaluate the capability of improved artificial neural networks (ANN) and additional novel training methods in distinguishing between benign and malignant breast lesions in contrast-enhanced magnetic resonance-mammography (MRM). A total of 604 histologically proven cases of contrast-enhanced lesions of the female breast at MRI were analyzed. Morphological, dynamic and clinical parameters were collected and stored in a database. The data set was divided into several groups using random or experimental methods [Training & Testing (T&T) algorithm] to train and test different ANNs. An additional novel computer program for input variable selection was applied. Sensitivity and specificity were calculated and compared with a statistical method and an expert radiologist. After optimization of the distribution of cases among the training and testing sets by the T & T algorithm and the reduction of input variables by the Input Selection procedure a highly sophisticated ANN achieved a sensitivity of 93.6% and a specificity of 91.9% in predicting malignancy of lesions within an independent prediction sample set. The best statistical method reached a sensitivity of 90.5% and a specificity of 68.9%. An expert radiologist performed better than the statistical method but worse than the ANN (sensitivity 92.1%, specificity 85.6%). Features extracted out of dynamic contrast-enhanced MRM and additional clinical data can be successfully analyzed by advanced ANNs. The quality of the resulting network strongly depends on the training methods, which are improved by the use of novel training tools. The best results of an improved ANN outperform expert radiologists.

Use of a machine learning algorithm to classify expertise: analysis of hand motion patterns during a simulated surgical task.

PubMed

Watson, Robert A

2014-08-01

To test the hypothesis that machine learning algorithms increase the predictive power to classify surgical expertise using surgeons' hand motion patterns. In 2012 at the University of North Carolina at Chapel Hill, 14 surgical attendings and 10 first- and second-year surgical residents each performed two bench model venous anastomoses. During the simulated tasks, the participants wore an inertial measurement unit on the dorsum of their dominant (right) hand to capture their hand motion patterns. The pattern from each bench model task performed was preprocessed into a symbolic time series and labeled as expert (attending) or novice (resident). The labeled hand motion patterns were processed and used to train a Support Vector Machine (SVM) classification algorithm. The trained algorithm was then tested for discriminative/predictive power against unlabeled (blinded) hand motion patterns from tasks not used in the training. The Lempel-Ziv (LZ) complexity metric was also measured from each hand motion pattern, with an optimal threshold calculated to separately classify the patterns. The LZ metric classified unlabeled (blinded) hand motion patterns into expert and novice groups with an accuracy of 70% (sensitivity 64%, specificity 80%). The SVM algorithm had an accuracy of 83% (sensitivity 86%, specificity 80%). The results confirmed the hypothesis. The SVM algorithm increased the predictive power to classify blinded surgical hand motion patterns into expert versus novice groups. With further development, the system used in this study could become a viable tool for low-cost, objective assessment of procedural proficiency in a competency-based curriculum.

Predicting general criminal recidivism in mentally disordered offenders using a random forest approach.

PubMed

Pflueger, Marlon O; Franke, Irina; Graf, Marc; Hachtel, Henning

2015-03-29

Psychiatric expert opinions are supposed to assess the accused individual's risk of reoffending based on a valid scientific foundation. In contrast to specific recidivism, general recidivism has only been poorly considered in Continental Europe; we therefore aimed to develop a valid instrument for assessing the risk of general criminal recidivism of mentally ill offenders. Data of 259 mentally ill offenders with a median time at risk of 107 months were analyzed and combined with the individuals' criminal records. We derived risk factors for general criminal recidivism and classified re-offences by using a random forest approach. In our sample of mentally ill offenders, 51% were reconvicted. The most important predictive factors for general criminal recidivism were: number of prior convictions, age, type of index offence, diversity of criminal history, and substance abuse. With our statistical approach we were able to correctly identify 58-95% of all reoffenders and 65-97% of all committed offences (AUC = .90). Our study presents a new statistical approach to forensic-psychiatric risk-assessment, allowing experts to evaluate general risk of reoffending in mentally disordered individuals, with a special focus on high-risk groups. This approach might serve not only for expert opinions in court, but also for risk management strategies and therapeutic interventions.

Including Thermal Fluctuations in Actomyosin Stable States Increases the Predicted Force per Motor and Macroscopic Efficiency in Muscle Modelling

PubMed Central

2016-01-01

Muscle contractions are generated by cyclical interactions of myosin heads with actin filaments to form the actomyosin complex. To simulate actomyosin complex stable states, mathematical models usually define an energy landscape with a corresponding number of wells. The jumps between these wells are defined through rate constants. Almost all previous models assign these wells an infinite sharpness by imposing a relatively simple expression for the detailed balance, i.e., the ratio of the rate constants depends exponentially on the sole myosin elastic energy. Physically, this assumption corresponds to neglecting thermal fluctuations in the actomyosin complex stable states. By comparing three mathematical models, we examine the extent to which this hypothesis affects muscle model predictions at the single cross-bridge, single fiber, and organ levels in a ceteris paribus analysis. We show that including fluctuations in stable states allows the lever arm of the myosin to easily and dynamically explore all possible minima in the energy landscape, generating several backward and forward jumps between states during the lifetime of the actomyosin complex, whereas the infinitely sharp minima case is characterized by fewer jumps between states. Moreover, the analysis predicts that thermal fluctuations enable a more efficient contraction mechanism, in which a higher force is sustained by fewer attached cross-bridges. PMID:27626630

A route to possible civil engineering materials: the case of high-pressure phases of lime

NASA Astrophysics Data System (ADS)

Bouibes, A.; Zaoui, A.

2015-07-01

Lime system has a chemical composition CaO, which is known as thermodynamically stable. The purpose here is to explore further possible phases under pressure, by means of variable-composition ab initio evolutionary algorithm. The present investigation shows surprisingly new stable compounds of lime. At ambient pressure we predict, in addition to CaO, CaO2 as new thermodynamically stable compound. The latter goes through two phases transition from C2/c space group structure to Pna21 at 1.5 GPa, and Pna21 space group structure to I4/mcm at 23.4 GPa. Under increasing pressure, further compounds such as CaO3 become the most stable and stabilize in P-421m space group structure above 65 GPa. For the necessary knowledge of the new predicted compounds, we have computed their mechanical and electronic properties in order to show and to explain the main reasons leading to the structural changes.

A route to possible civil engineering materials: the case of high-pressure phases of lime.

PubMed

Bouibes, A; Zaoui, A

2015-07-23

Lime system has a chemical composition CaO, which is known as thermodynamically stable. The purpose here is to explore further possible phases under pressure, by means of variable-composition ab initio evolutionary algorithm. The present investigation shows surprisingly new stable compounds of lime. At ambient pressure we predict, in addition to CaO, CaO2 as new thermodynamically stable compound. The latter goes through two phases transition from C2/c space group structure to Pna21 at 1.5 GPa, and Pna21 space group structure to I4/mcm at 23.4 GPa. Under increasing pressure, further compounds such as CaO3 become the most stable and stabilize in P-421m space group structure above 65 GPa. For the necessary knowledge of the new predicted compounds, we have computed their mechanical and electronic properties in order to show and to explain the main reasons leading to the structural changes.

Controlling misses and false alarms in a machine learning framework for predicting uniformity of printed pages

NASA Astrophysics Data System (ADS)

Nguyen, Minh Q.; Allebach, Jan P.

2015-01-01

In our previous work1 , we presented a block-based technique to analyze printed page uniformity both visually and metrically. The features learned from the models were then employed in a Support Vector Machine (SVM) framework to classify the pages into one of the two categories of acceptable and unacceptable quality. In this paper, we introduce a set of tools for machine learning in the assessment of printed page uniformity. This work is primarily targeted to the printing industry, specifically the ubiquitous laser, electrophotographic printer. We use features that are well-correlated with the rankings of expert observers to develop a novel machine learning framework that allows one to achieve the minimum "false alarm" rate, subject to a chosen "miss" rate. Surprisingly, most of the research that has been conducted on machine learning does not consider this framework. During the process of developing a new product, test engineers will print hundreds of test pages, which can be scanned and then analyzed by an autonomous algorithm. Among these pages, most may be of acceptable quality. The objective is to find the ones that are not. These will provide critically important information to systems designers, regarding issues that need to be addressed in improving the printer design. A "miss" is defined to be a page that is not of acceptable quality to an expert observer that the prediction algorithm declares to be a "pass". Misses are a serious problem, since they represent problems that will not be seen by the systems designers. On the other hand, "false alarms" correspond to pages that an expert observer would declare to be of acceptable quality, but which are flagged by the prediction algorithm as "fails". In a typical printer testing and development scenario, such pages would be examined by an expert, and found to be of acceptable quality after all. "False alarm" pages result in extra pages to be examined by expert observers, which increases labor cost. But "false alarms" are not nearly as catastrophic as "misses", which represent potentially serious problems that are never seen by the systems developers. This scenario motivates us to develop a machine learning framework that will achieve the minimum "false alarm" rate subject to a specified "miss" rate. In order to construct such a set of receiver operating characteristic2 (ROC) curves, we examine various tools for the prediction, ranging from an exhaustive search over the space of the nonlinear discriminants to a Cost-Sentitive SVM3 framework. We then compare the curves gained from those methods. Our work shows promise for applying a standard framework to obtain a full ROC curve when it comes to tackling other machine learning problems in industry.

Geospatial Analytics in Retail Site Selection and Sales Prediction.

PubMed

Ting, Choo-Yee; Ho, Chiung Ching; Yee, Hui Jia; Matsah, Wan Razali

2018-03-01

Studies have shown that certain features from geography, demography, trade area, and environment can play a vital role in retail site selection, largely due to the impact they asserted on retail performance. Although the relevant features could be elicited by domain experts, determining the optimal feature set can be intractable and labor-intensive exercise. The challenges center around (1) how to determine features that are important to a particular retail business and (2) how to estimate retail sales performance given a new location? The challenges become apparent when the features vary across time. In this light, this study proposed a nonintervening approach by employing feature selection algorithms and subsequently sales prediction through similarity-based methods. The results of prediction were validated by domain experts. In this study, data sets from different sources were transformed and aggregated before an analytics data set that is ready for analysis purpose could be obtained. The data sets included data about feature location, population count, property type, education status, and monthly sales from 96 branches of a telecommunication company in Malaysia. The finding suggested that (1) optimal retail performance can only be achieved through fulfillment of specific location features together with the surrounding trade area characteristics and (2) similarity-based method can provide solution to retail sales prediction.

Outcomes Research in Cardiovascular Imaging

PubMed Central

Douglas, Pamela S.; Taylor, Allen; Bild, Diane; Bonow, Robert; Greenland, Philip; Lauer, Michael; Peacock, Frank; Udelson, James

2009-01-01

In July of 2008, the National Heart, Lung, and Blood Institute convened experts in noninvasive cardiovascular imaging, outcomes research, statistics, and clinical trials to develop recommendations for future randomized controlled trials of the use of imaging in: 1) screening the asymptomatic patient for coronary artery disease; 2) assessment of patients with stable angina; 3) identification of acute coronary syndromes in the emergency room; and 4) assessment of heart failure patients with chronic coronary artery disease with reduced left ventricular ejection fraction. This study highlights several possible trial designs for each clinical situation. PMID:19560655

Mixtures of beta distributions in models of the duration of a project affected by risk

NASA Astrophysics Data System (ADS)

Gładysz, Barbara; Kuchta, Dorota

2017-07-01

This article presents a method for timetabling a project affected by risk. The times required to carry out tasks are modelled using mixtures of beta distributions. The parameters of these beta distributions are given by experts: one corresponding to the duration of a task in stable conditions, with no risks materializing, and the other corresponding to the duration of a task in the case when risks do occur. Finally, a case study will be presented and analysed: the project of constructing a shopping mall in Poland.

High Entropy Alloys: Criteria for Stable Structure

NASA Astrophysics Data System (ADS)

Tripathy, Snehashish; Gupta, Gaurav; Chowdhury, Sandip Ghosh

2018-01-01

An effort has been made to reassess the phase predicting capability of various thermodynamic and topological parameters across a wide range of HEA systems. These parameters are valence electron concentration, atomic mismatch ( δ), electronegativity difference (Δ χ), mixing entropy (Δ S mix), entropy of fusion (Δ S f), and mismatch entropy ( S σ ). In continuation of that, two new parameters (a) Modified Darken-Gurry parameter ( A = Sσ * χ) and (b) Modified Mismatch Entropy parameter ( B = δ* Sσ) have been designed to predict the stable crystal structure that would form in the HEA systems considered for assessment.

Reduced Antiplatelet Effect of Aspirin Does Not Predict Cardiovascular Events in Patients With Stable Coronary Artery Disease.

PubMed

Larsen, Sanne Bøjet; Grove, Erik Lerkevang; Neergaard-Petersen, Søs; Würtz, Morten; Hvas, Anne-Mette; Kristensen, Steen Dalby

2017-08-05

Increased platelet aggregation during antiplatelet therapy may predict cardiovascular events in patients with coronary artery disease. The majority of these patients receive aspirin monotherapy. We aimed to investigate whether high platelet-aggregation levels predict cardiovascular events in stable coronary artery disease patients treated with aspirin. We included 900 stable coronary artery disease patients with either previous myocardial infarction, type 2 diabetes mellitus, or both. All patients received single antithrombotic therapy with 75 mg aspirin daily. Platelet aggregation was evaluated 1 hour after aspirin intake using the VerifyNow Aspirin Assay (Accriva Diagnostics) and Multiplate Analyzer (Roche; agonists: arachidonic acid and collagen). Adherence to aspirin was confirmed by serum thromboxane B 2 . The primary end point was the composite of nonfatal myocardial infarction, ischemic stroke, and cardiovascular death. At 3-year follow-up, 78 primary end points were registered. The primary end point did not occur more frequently in patients with high platelet-aggregation levels (first versus fourth quartile) assessed by VerifyNow (hazard ratio: 0.5 [95% CI, 0.3-1.1], P =0.08) or Multiplate using arachidonic acid (hazard ratio: 1.0 [95% CI, 0.5-2.1], P =0.92) or collagen (hazard ratio: 1.4 [95% CI, 0.7-2.8], P =0.38). Similar results were found for the composite secondary end point (nonfatal myocardial infarction, ischemic stroke, stent thrombosis, and all-cause death) and the single end points. Thromboxane B 2 levels did not predict any end points. Renal insufficiency was the only clinical risk factor predicting the primary and secondary end points. This study is the largest to investigate platelet aggregation in stable coronary artery disease patients receiving aspirin as single antithrombotic therapy. We found that high platelet-aggregation levels did not predict cardiovascular events. © 2017 The Authors. Published on behalf of the American Heart Association, Inc., by Wiley.

Mathematical modeling of control subsystems for CELSS: Application to diet

NASA Technical Reports Server (NTRS)

Waleh, Ahmad; Nguyen, Thoi K.; Kanevsky, Valery

1991-01-01

The dynamic control of a Closed Ecological Life Support System (CELSS) in a closed space habitat is of critical importance. The development of a practical method of control is also a necessary step for the selection and design of realistic subsystems and processors for a CELSS. Diet is one of the dynamic factors that strongly influences, and is influenced, by the operational states of all major CELSS subsystems. The problems of design and maintenance of a stable diet must be obtained from well characterized expert subsystems. The general description of a mathematical model that forms the basis of an expert control program for a CELSS is described. The formulation is expressed in terms of a complete set of time dependent canonical variables. System representation is dynamic and includes time dependent storage buffers. The details of the algorithm are described. The steady state results of the application of the method for representative diets made from wheat, potato, and soybean are presented.

Postural control and perceptive configuration: influence of expertise in gymnastics.

PubMed

Gautier, Geoffroy; Thouvarecq, Régis; Vuillerme, Nicolas

2008-07-01

The purpose of the present experiment was to investigate how postural adaptations to the perceptive configuration are modified by specific gymnastics experience. Two groups, one expert in gymnastics and the other non-expert, had to maintain the erected posture while optical flow was imposed as follows: 20s motionless, 30s approaching motion, and 20s motionless. The centre of pressure and head displacements were analysed. The postural adaptations were characterised by the variability of movements for the flow conditions and by the postural latencies for the flow transitions. The results showed that the gymnasts tended to minimise their body movements and were more stationary (head) but not more stable (COP) than the non-gymnasts. These results suggest that gymnastics experience develops a specific postural adaptability relative to the perceptive configuration. We conclude that a specific postural experience could be considered as an intrinsic constraint, which leads to modification in the patterns of functional adaptation in the perceptive motor space.

The Holistic Processing Account of Visual Expertise in Medical Image Perception: A Review

PubMed Central

Sheridan, Heather; Reingold, Eyal M.

2017-01-01

In the field of medical image perception, the holistic processing perspective contends that experts can rapidly extract global information about the image, which can be used to guide their subsequent search of the image (Swensson, 1980; Nodine and Kundel, 1987; Kundel et al., 2007). In this review, we discuss the empirical evidence supporting three different predictions that can be derived from the holistic processing perspective: Expertise in medical image perception is domain-specific, experts use parafoveal and/or peripheral vision to process large regions of the image in parallel, and experts benefit from a rapid initial glimpse of an image. In addition, we discuss a pivotal recent study (Litchfield and Donovan, 2016) that seems to contradict the assumption that experts benefit from a rapid initial glimpse of the image. To reconcile this finding with the existing literature, we suggest that global processing may serve multiple functions that extend beyond the initial glimpse of the image. Finally, we discuss future research directions, and we highlight the connections between the holistic processing account and similar theoretical perspectives and findings from other domains of visual expertise. PMID:29033865

The Holistic Processing Account of Visual Expertise in Medical Image Perception: A Review.

PubMed

Sheridan, Heather; Reingold, Eyal M

2017-01-01

In the field of medical image perception, the holistic processing perspective contends that experts can rapidly extract global information about the image, which can be used to guide their subsequent search of the image (Swensson, 1980; Nodine and Kundel, 1987; Kundel et al., 2007). In this review, we discuss the empirical evidence supporting three different predictions that can be derived from the holistic processing perspective: Expertise in medical image perception is domain-specific, experts use parafoveal and/or peripheral vision to process large regions of the image in parallel, and experts benefit from a rapid initial glimpse of an image. In addition, we discuss a pivotal recent study (Litchfield and Donovan, 2016) that seems to contradict the assumption that experts benefit from a rapid initial glimpse of the image. To reconcile this finding with the existing literature, we suggest that global processing may serve multiple functions that extend beyond the initial glimpse of the image. Finally, we discuss future research directions, and we highlight the connections between the holistic processing account and similar theoretical perspectives and findings from other domains of visual expertise.

Analysis of the Structure of Surgical Activity for a Suturing and Knot-Tying Task

PubMed Central

Vedula, S. Swaroop; Malpani, Anand O.; Tao, Lingling; Chen, George; Gao, Yixin; Poddar, Piyush; Ahmidi, Narges; Paxton, Christopher; Vidal, Rene; Khudanpur, Sanjeev; Hager, Gregory D.; Chen, Chi Chiung Grace

2016-01-01

Background Surgical tasks are performed in a sequence of steps, and technical skill evaluation includes assessing task flow efficiency. Our objective was to describe differences in task flow for expert and novice surgeons for a basic surgical task. Methods We used a hierarchical semantic vocabulary to decompose and annotate maneuvers and gestures for 135 instances of a surgeon’s knot performed by 18 surgeons. We compared counts of maneuvers and gestures, and analyzed task flow by skill level. Results Experts used fewer gestures to perform the task (26.29; 95% CI = 25.21 to 27.38 for experts vs. 31.30; 95% CI = 29.05 to 33.55 for novices) and made fewer errors in gestures than novices (1.00; 95% CI = 0.61 to 1.39 vs. 2.84; 95% CI = 2.3 to 3.37). Transitions among maneuvers, and among gestures within each maneuver for expert trials were more predictable than novice trials. Conclusions Activity segments and state flow transitions within a basic surgical task differ by surgical skill level, and can be used to provide targeted feedback to surgical trainees. PMID:26950551

Visualising probabilistic flood forecast information: expert preferences and perceptions of best practice in uncertainty communication

NASA Astrophysics Data System (ADS)

Pappenberger, F.; Stephens, E. M.; Thielen, J.; Salomon, P.; Demeritt, D.; van Andel, S.; Wetterhall, F.; Alfieri, L.

2011-12-01

The aim of this paper is to understand and to contribute to improved communication of the probabilistic flood forecasts generated by Hydrological Ensemble Prediction Systems (HEPS) with particular focus on the inter expert communication. Different users are likely to require different kinds of information from HEPS and thus different visualizations. The perceptions of this expert group are important both because they are the designers and primary users of existing HEPS. Nevertheless, they have sometimes resisted the release of uncertainty information to the general public because of doubts about whether it can be successfully communicated in ways that would be readily understood to non-experts. In this paper we explore the strengths and weaknesses of existing HEPS visualization methods and thereby formulate some wider recommendations about best practice for HEPS visualization and communication. We suggest that specific training on probabilistic forecasting would foster use of probabilistic forecasts with a wider range of applications. The result of a case study exercise showed that there is no overarching agreement between experts on how to display probabilistic forecasts and what they consider essential information that should accompany plots and diagrams. In this paper we propose a list of minimum properties that, if consistently displayed with probabilistic forecasts, would make the products more easily understandable.

Vulnerability of bridges to scour: insights from an international expert elicitation workshop

NASA Astrophysics Data System (ADS)

Lamb, Rob; Aspinall, Willy; Odbert, Henry; Wagener, Thorsten

2017-08-01

Scour (localised erosion) during flood events is one of the most significant threats to bridges over rivers and estuaries, and has been the cause of numerous bridge failures, with damaging consequences. Mitigation of the risk of bridges being damaged by scour is therefore important to many infrastructure owners, and is supported by industry guidance. Even after mitigation, some residual risk remains, though its extent is difficult to quantify because of the uncertainties inherent in the prediction of scour and the assessment of the scour risk. This paper summarises findings from an international expert workshop on bridge scour risk assessment that explores uncertainties about the vulnerability of bridges to scour. Two specialised structured elicitation methods were applied to explore the factors that experts in the field consider important when assessing scour risk and to derive pooled expert judgements of bridge failure probabilities that are conditional on a range of assumed scenarios describing flood event severity, bridge and watercourse types and risk mitigation protocols. The experts' judgements broadly align with industry good practice, but indicate significant uncertainty about quantitative estimates of bridge failure probabilities, reflecting the difficulty in assessing the residual risk of failure. The data and findings presented here could provide a useful context for the development of generic scour fragility models and their associated uncertainties.

Patterns and Predictors of Language and Literacy Abilities 4-10 Years in the Longitudinal Study of Australian Children.

PubMed

Zubrick, Stephen R; Taylor, Catherine L; Christensen, Daniel

2015-01-01

Oral language is the foundation of literacy. Naturally, policies and practices to promote children's literacy begin in early childhood and have a strong focus on developing children's oral language, especially for children with known risk factors for low language ability. The underlying assumption is that children's progress along the oral to literate continuum is stable and predictable, such that low language ability foretells low literacy ability. This study investigated patterns and predictors of children's oral language and literacy abilities at 4, 6, 8 and 10 years. The study sample comprised 2,316 to 2,792 children from the first nationally representative Longitudinal Study of Australian Children (LSAC). Six developmental patterns were observed, a stable middle-high pattern, a stable low pattern, an improving pattern, a declining pattern, a fluctuating low pattern, and a fluctuating middle-high pattern. Most children (69%) fit a stable middle-high pattern. By contrast, less than 1% of children fit a stable low pattern. These results challenged the view that children's progress along the oral to literate continuum is stable and predictable. Multivariate logistic regression was used to investigate risks for low literacy ability at 10 years and sensitivity-specificity analysis was used to examine the predictive utility of the multivariate model. Predictors were modelled as risk variables with the lowest level of risk as the reference category. In the multivariate model, substantial risks for low literacy ability at 10 years, in order of descending magnitude, were: low school readiness, Aboriginal and/or Torres Strait Islander status and low language ability at 8 years. Moderate risks were high temperamental reactivity, low language ability at 4 years, and low language ability at 6 years. The following risk factors were not statistically significant in the multivariate model: Low maternal consistency, low family income, health care card, child not read to at home, maternal smoking, maternal education, family structure, temperamental persistence, and socio-economic area disadvantage. The results of the sensitivity-specificity analysis showed that a well-fitted multivariate model featuring risks of substantive magnitude did not do particularly well in predicting low literacy ability at 10 years.

Bomb Strike Experiment for Mine Countermeasure

DTIC Science & Technology

2006-01-01

Domestic Product ( GDP ), up from 11 percent in 1970, and experts agree that this figure will only continue to increase in coming years (Frittelli...Prediction Model – Technical Description of Recent Changes and Developments. Defense Scientific Establishment, Auckland , New Zealand, Report 149. Seventh

Rehabilitation in patients with pulmonary arterial hypertension.

PubMed

Keusch, Stephan; Turk, Alexander; Saxer, Stéphanie; Ehlken, Nicola; Grunig, Ekkehard; Ulrich, Silvia; On Behalf Of The Swiss Society Of Pulmonary Hypertension

2017-07-11

Exertional dyspnoea is a leading symptom in patients with pulmonary arterial hypertension (PAH). Patients suffering from PAH report poor quality of life, have skeletal muscle dysfunction and in the absence of advanced medical therapy deteriorate progressively due to right heart failure which can lead to death. For decades, patients with PAH were advised to avoid exercise in fear of exacerbated right heart failure. Recently, it has been shown that a highly supervised rehabilitation programme in expert centres leads to significant improvements in symptoms, quality of life, exercise capacity and may even enhance haemodynamics in selected stable patients treated with advanced regimens of PAH-targeted drugs. As a consequence of these promising results, pulmonary rehabilitation performed in an expert centre has been included in recent guidelines. The underlying mechanisms are not completely understood, but positive effects can be measured in different organ systems such as skeletal muscles, the cardiopulmonary system and immune system (inflammation), and also on the psychological level. Thus, improvements in 6-minute walking distance (6MWD), peak oxygen uptake (VO2 peak), muscle strength and muscle endurance, as well as physical and mental quality of life scores (SF-36 questionnaire) have been shown. Different training protocols have been used. Essential are qualified patient selection in expert centres, a low workload endurance and dumbbell (weight lifting) training avoiding strenuous exercise and exhaustion, thorough patient education and close supervision by experts especially during the first weeks. Adverse events may occur (e.g., pre-/syncope, arrhythmia, respiratory infections). PAH patients tend to overestimate their physical capacity, not perceiving their own limits properly, which makes education and expert advice even more important as exercise training can also worsen the right heart failure. Therefore, a core issue of the multidisciplinary rehabilitation is the close cooperation between the experienced rehabilitation clinic offering a specialised programme for PAH patients and the PAH expert centre, which takes care of the patient and is thoroughly involved in the training programme. Further multicentre international randomised trials are needed to evaluate whether this specialised programme is feasible within different healthcare systems and to assess long term effects and survival.

Stable Early Maternal Report of Behavioral Inhibition Predicts Lifetime Social Anxiety Disorder in Adolescence

ERIC Educational Resources Information Center

Chronis-Tuscano, Andrea; Degnan, Kathryn Amey; Pine, Daniel S.; Perez-Edgar, Koraly; Henderson, Heather A.; Diaz, Yamalis; Raggi, Veronica L.; Fox, Nathan A.

2009-01-01

The odds of a lifetime diagnosis of social anxiety disorder increased by 3.79 times for children who had a stable report of behavioral inhibition from their mothers. This finding has important implications for the early identification and prevention of social anxiety disorder.

Module 5: Applications of Stable Isotope Analyses: Data Interpretation and Data Quality Issues

EPA Science Inventory

When organic contaminants such as benzene, TCE or MTBE are degraded, the ratio of the stable isotopes of carbon in the organic contaminants will often change in a predictable fashion. In the last ten years, advances in analytical chemistry have made it possible to measure these ...

Scientists versus Regulators: Precaution, Novelty & Regulatory Oversight as Predictors of Perceived Risks of Engineered Nanomaterials

PubMed Central

Beaudrie, Christian E. H.; Satterfield, Terre; Kandlikar, Milind; Harthorn, Barbara H.

2014-01-01

Engineered nanoscale materials (ENMs) present a difficult challenge for risk assessors and regulators. Continuing uncertainty about the potential risks of ENMs means that expert opinion will play an important role in the design of policies to minimize harmful implications while supporting innovation. This research aims to shed light on the views of ‘nano experts’ to understand which nanomaterials or applications are regarded as more risky than others, to characterize the differences in risk perceptions between expert groups, and to evaluate the factors that drive these perceptions. Our analysis draws from a web-survey (N = 404) of three groups of US and Canadian experts: nano-scientists and engineers, nano-environmental health and safety scientists, and regulatory scientists and decision-makers. Significant differences in risk perceptions were found across expert groups; differences found to be driven by underlying attitudes and perceptions characteristic of each group. Nano-scientists and engineers at the upstream end of the nanomaterial life cycle perceived the lowest levels of risk, while those who are responsible for assessing and regulating risks at the downstream end perceived the greatest risk. Perceived novelty of nanomaterial risks, differing preferences for regulation (i.e. the use of precaution versus voluntary or market-based approaches), and perceptions of the risk of technologies in general predicted variation in experts' judgments of nanotechnology risks. Our findings underscore the importance of involving a diverse selection of experts, particularly those with expertise at different stages along the nanomaterial lifecycle, during policy development. PMID:25222742

Simultaneous production of detergent stable keratinolytic protease, amylase and biosurfactant by Bacillus subtilis PF1 using agro industrial waste.

PubMed

Bhange, Khushboo; Chaturvedi, Venkatesh; Bhatt, Renu

2016-06-01

The present study is an attempt to optimize simultaneous production of keratinolytic protease, amylase and biosurfactant from feather meal, potato peel and rape seed cake in a single media by response surface methodology to evaluate their biochemical properties for detergent additive. The optimization was carried out using 20 run, 3 factor and 5-level of central composite design on design expert software which resulted in a 1.2, 0.84 and 2.28 fold increase in protease, amylase and biosurfactant production. The proteolytic activity was found to be optimum at pH 9.0 and 60 °C while optimum amylolytic activity was recorded at pH 6.0 and 70 °C respectively. Both enzymes were found to be stable in the presence of organic solvents, ionic and commercial detergent and oxidizing agents. The biosurfactant was extracted with chloroform and was found to be stable at varying pH and temperature; however a reduction in the activity was observed at temperature higher than 70 °C. The isolated enzymes and biosurfactants may find applications in the effective removal of stains.

A knowledge-based support system for mechanical ventilation of the lungs. The KUSIVAR concept and prototype.

PubMed

Rudowski, R; Frostell, C; Gill, H

1989-09-01

The KUSIVAR is an expert system for mechanical ventilation of adult patients suffering from respiratory insufficiency. Its main objective is to provide guidance in respirator management. The knowledge base includes both qualitative, rule-based knowledge and quantitative knowledge expressed in the form of mathematical models (expert control) which is used for prediction of arterial gas tensions and optimization purposes. The system is data driven and uses a forward chaining mechanism for rule invocation. The interaction with the user will be performed in advisory, critiquing, semi-automatic and automatic modes. The system is at present in an advanced prototype stage. Prototyping is performed using KEE (Knowledge Engineering Environment) on a Sperry Explorer workstation. For further development and clinical use the expert system will be downloaded to an advanced PC. The system is intended to support therapy with a Siemens-Elema Servoventilator 900 C.

Register of experts for information on mechanics of structural failure

NASA Technical Reports Server (NTRS)

Carpenter, J. L., Jr.; Stuhrke, W. F.

1975-01-01

This register is comprised of a list of approximately 300 experts from approximately 90 organizations who have published results of theoretical and/or experimental research related to six problem areas in the mechanics of structural failure: (1) life prediction for structural materials, (2) fracture toughness testing, (3) fracture mechanics analysis; (4) hydrogen embrittlement; (5) protective coatings; and (6) composite materials. The criteria for the selection of names for the register are recent contributions to the literature, participation in or support of relevant research programs, and referral by peers. Each author included is listed by organizational affiliation, address, and principal field of expertise. The purpose of the register is to present, in easy reference form, sources for dependable information regarding failure modes and mechanisms of aerospace structures. The register includes two indexes; an alphabetical listing of the experts and an alphabetical listing of the organizations with whom they are affiliated.

Development and validation of equations utilizing lamb vision system output to predict lamb carcass fabrication yields.

PubMed

Cunha, B C N; Belk, K E; Scanga, J A; LeValley, S B; Tatum, J D; Smith, G C

2004-07-01

This study was performed to validate previous equations and to develop and evaluate new regression equations for predicting lamb carcass fabrication yields using outputs from a lamb vision system-hot carcass component (LVS-HCC) and the lamb vision system-chilled carcass LM imaging component (LVS-CCC). Lamb carcasses (n = 149) were selected after slaughter, imaged hot using the LVS-HCC, and chilled for 24 to 48 h at -3 to 1 degrees C. Chilled carcasses yield grades (YG) were assigned on-line by USDA graders and by expert USDA grading supervisors with unlimited time and access to the carcasses. Before fabrication, carcasses were ribbed between the 12th and 13th ribs and imaged using the LVS-CCC. Carcasses were fabricated into bone-in subprimal/primal cuts. Yields calculated included 1) saleable meat yield (SMY); 2) subprimal yield (SPY); and 3) fat yield (FY). On-line (whole-number) USDA YG accounted for 59, 58, and 64%; expert (whole-number) USDA YG explained 59, 59, and 65%; and expert (nearest-tenth) USDA YG accounted for 60, 60, and 67% of the observed variation in SMY, SPY, and FY, respectively. The best prediction equation developed in this trial using LVS-HCC output and hot carcass weight as independent variables explained 68, 62, and 74% of the variation in SMY, SPY, and FY, respectively. Addition of output from LVS-CCC improved predictive accuracy of the equations; the combined output equations explained 72 and 66% of the variability in SMY and SPY, respectively. Accuracy and repeatability of measurement of LM area made with the LVS-CCC also was assessed, and results suggested that use of LVS-CCC provided reasonably accurate (R2 = 0.59) and highly repeatable (repeatability = 0.98) measurements of LM area. Compared with USDA YG, use of the dual-component lamb vision system to predict cut yields of lamb carcasses improved accuracy and precision, suggesting that this system could have an application as an objective means for pricing carcasses in a value-based marketing system.

The KIDROP model of combining strategies for providing retinopathy of prematurity screening in underserved areas in India using wide-field imaging, tele-medicine, non-physician graders and smart phone reporting

PubMed Central

Vinekar, Anand; Gilbert, Clare; Dogra, Mangat; Kurian, Mathew; Shainesh, Gangadharan; Shetty, Bhujang; Bauer, Noel

2014-01-01

Aim: To report the Karnataka Internet Assisted Diagnosis of Retinopathy of Prematurity (KIDROP) program for retinopathy of prematurity (ROP) screening in underserved rural areas using an indigenously developed tele-ROP model. Materials and Methods: KIDROP currently provides ROP screening and treatment services in three zones and 81 neonatal units in Karnataka, India. Technicians were trained to use a portable Retcam Shuttle (Clarity, USA) and validated against ROP experts performing indirect ophthalmoscopy. An indigenously developed 20-point score (STAT score) graded their ability (Level I to III) to image and decide follow-up based on a three-way algorithm. Images were also uploaded on a secure tele-ROP platform and accessed and reported by remote experts on their smart phones (iPhone, Apple). Results: 6339 imaging sessions of 1601 infants were analyzed. A level III technician agreed with 94.3% of all expert decisions. The sensitivity, specificity, positive predictive value and negative predictive value for treatment grade disease were 95.7, 93.2, 81.5 and 98.6 respectively. The kappa for technicians to decide discharge of babies was 0.94 (P < 0.001). Only 0.4% of infants needing treatment were missed. The kappa agreement of experts reporting on the iPhone vs Retcam for treatment requiring and mild ROP were 0.96 and 0.94 (P < 0.001) respectively. Conclusions: This is the first and largest real-world program to employ accredited non-physicians to grade and report ROP. The KIDROP tele-ROP model demonstrates that ROP services can be delivered to the outreach despite lack of specialists and may be useful in other middle-income countries with similar demographics. PMID:24492500

Value of biologic therapy: a forecasting model in three disease areas.

PubMed

Paramore, L Clark; Hunter, Craig A; Luce, Bryan R; Nordyke, Robert J; Halbert, R J

2010-01-01

Forecast the return on investment (ROI) for advances in biologic therapies in years 2015 and 2030, based upon impact on disease prevalence, morbidity, and mortality for asthma, diabetes, and colorectal cancer. A deterministic, spreadsheet-based, forecasting model was developed based on trends in demographics and disease epidemiology. 'Return' was defined as reductions in disease burden (prevalence, morbidity, mortality) translated into monetary terms; 'investment' was defined as the incremental costs of biologic therapy advances. Data on disease prevalence, morbidity, mortality, and associated costs were obtained from government survey statistics or published literature. Expected impact of advances in biologic therapies was based on expert opinion. Gains in quality-adjusted life years (QALYs) were valued at $100,000 per QALY. The base case analysis, in which reductions in disease prevalence and mortality predicted by the expert panel are not considered, shows the resulting ROIs remain positive for asthma and diabetes but fall below $1 for colorectal cancer. Analysis involving expert panel predictions indicated positive ROI results for all three diseases at both time points, ranging from $207 for each incremental dollar spent on biologic therapies to treat asthma in 2030, to $4 for each incremental dollar spent on biologic therapies to treat colorectal cancer in 2015. If QALYs are not considered, the resulting ROIs remain positive for all three diseases at both time points. Society may expect substantial returns from investments in innovative biologic therapies. These benefits are most likely to be realized in an environment of appropriate use of new molecules. The potential variance between forecasted (from expert opinion) and actual future health outcomes could be significant. Similarly, the forecasted growth in use of biologic therapies relied upon unvalidated market forecasts.

Change in the relative contributions of habit and working memory facilitates serial reversal learning expertise in rhesus monkeys.

PubMed

Hassett, Thomas C; Hampton, Robert R

2017-05-01

Functionally distinct memory systems likely evolved in response to incompatible demands placed on learning by distinct environmental conditions. Working memory appears adapted, in part, for conditions that change frequently, making rapid acquisition and brief retention of information appropriate. In contrast, habits form gradually over many experiences, adapting organisms to contingencies of reinforcement that are stable over relatively long intervals. Serial reversal learning provides an opportunity to simultaneously examine the processes involved in adapting to rapidly changing and relatively stable contingencies. In serial reversal learning, selecting one of the two simultaneously presented stimuli is positively reinforced, while selection of the other is not. After a preference for the positive stimulus develops, the contingencies of reinforcement reverse. Naïve subjects adapt to such reversals gradually, perseverating in selection of the previously rewarded stimulus. Experts reverse rapidly according to a win-stay, lose-shift response pattern. We assessed whether a change in the relative control of choice by habit and working memory accounts for the development of serial reversal learning expertise. Across three experiments, we applied manipulations intended to attenuate the contribution of working memory but leave the contribution of habit intact. We contrasted performance following long and short intervals in Experiments 1 and 2, and we interposed a competing cognitive load between trials in Experiment 3. These manipulations slowed the acquisition of reversals in expert subjects, but not naïve subjects, indicating that serial reversal learning expertise is facilitated by a shift in the control of choice from passively acquired habit to actively maintained working memory.

Thermal stability comparison of nanocrystalline Fe-based binary alloy pairs

DOE PAGES

Clark, Blythe G.; Hattar, Khalid Mikhiel; Marshall, Michael Thomas; ...

2016-03-24

Here, the widely recognized property improvements of nanocrystalline (NC) materials have generated significant interest, yet have been difficult to realize in engineering applications due to the propensity for grain growth in these interface-dense systems. While traditional pathways to thermal stabilization can slow the mobility of grain boundaries, recent theories suggest that solute segregation in NC alloy can reduce the grain boundary energy such that thermodynamic stabilization is achieved. Following the predictions of Murdock et al., here we compare for the first time the thermal stability of a predicted NC stable alloy (Fe-10at.% Mg) with a predicted non-NC stable alloy (Fe-10at.%more » Cu) using the same processing and characterization methodologies. Results indicate improved thermal stability of the Fe-Mg alloy in comparison to the Fe-Cu, and observed microstructures are consistent with those predicted by Monte Carlo simulations.« less

A high-throughput exploration of magnetic materials by using structure predicting methods

NASA Astrophysics Data System (ADS)

Arapan, S.; Nieves, P.; Cuesta-López, S.

2018-02-01

We study the capability of a structure predicting method based on genetic/evolutionary algorithm for a high-throughput exploration of magnetic materials. We use the USPEX and VASP codes to predict stable and generate low-energy meta-stable structures for a set of representative magnetic structures comprising intermetallic alloys, oxides, interstitial compounds, and systems containing rare-earths elements, and for both types of ferromagnetic and antiferromagnetic ordering. We have modified the interface between USPEX and VASP codes to improve the performance of structural optimization as well as to perform calculations in a high-throughput manner. We show that exploring the structure phase space with a structure predicting technique reveals large sets of low-energy metastable structures, which not only improve currently exiting databases, but also may provide understanding and solutions to stabilize and synthesize magnetic materials suitable for permanent magnet applications.

Pascal's Snowshoes

ERIC Educational Resources Information Center

Akcay, Behiye

2004-01-01

The chief purpose of this activity is to strengthen students' understanding of concepts of floatation such as surface area and pressure (weight per unit area) via snowshoes. Students brainstorm, make predictions, perform calculations, and practice communication skills through interviewing elders and experts. This activity lets students see the…

The designer of the 90's: A live demonstration

NASA Technical Reports Server (NTRS)

Green, Tommy L.; Jordan, Basil M., Jr.; Oglesby, Timothy L.

1989-01-01

A survey of design tools to be used by the aircraft designer is given. Structural reliability, maintainability, cost and predictability, and acoustics expert systems are discussed, as well as scheduling, drawing, engineering systems, sizing functions, and standard parts and materials data bases.

Are rapid diagnostic tests more accurate in diagnosis of plasmodium falciparum malaria compared to microscopy at rural health centres?

PubMed

Batwala, Vincent; Magnussen, Pascal; Nuwaha, Fred

2010-12-02

Prompt, accurate diagnosis and treatment with artemisinin combination therapy remains vital to current malaria control. Blood film microscopy the current standard test for diagnosis of malaria has several limitations that necessitate field evaluation of alternative diagnostic methods especially in low income countries of sub-Saharan Africa where malaria is endemic. The accuracy of axillary temperature, health centre (HC) microscopy, expert microscopy and a HRP2-based rapid diagnostic test (Paracheck) was compared in predicting malaria infection using polymerase chain reaction (PCR) as the gold standard. Three hundred patients with a clinical suspicion of malaria based on fever and or history of fever from a low and high transmission setting in Uganda were consecutively enrolled and provided blood samples for all tests. Accuracy of each test was calculated overall with 95% confidence interval and then adjusted for age-groups and level of transmission intensity using a stratified analysis. The endpoints were: sensitivity, specificity, positive predictive value (PPV) and negative predictive value (NPV). This study is registered with Clinicaltrials.gov, NCT00565071. Of the 300 patients, 88(29.3%) had fever, 56(18.7%) were positive by HC microscopy, 47(15.7%) by expert microscopy, 110(36.7%) by Paracheck and 89(29.7%) by PCR. The overall sensitivity >90% was only shown by Paracheck 91.0% [95%CI: 83.1-96.0]. The sensitivity of expert microscopy was 46%, similar to HC microscopy. The superior sensitivity of Paracheck compared to microscopy was maintained when data was stratified for transmission intensity and age. The overall specificity rates were: Paracheck 86.3% [95%CI: 80.9-90.6], HC microscopy 93.4% [95%CI: 89.1-96.3] and expert microscopy 97.2% [95%CI: 93.9-98.9]. The NPV >90% was shown by Paracheck 95.8% [95%CI: 91.9-98.2]. The overall PPV was <88% for all methods. The HRP2-based RDT has shown superior sensitivity compared to microscopy in diagnosis of malaria and may be more suitable for screening of malaria infection.

Microsaccades and interest areas during free-viewing sport task.

PubMed

Piras, Alessandro; Raffi, Milena; Perazzolo, Monica; Malagoli Lanzoni, Ivan; Squatrito, Salvatore

2017-09-18

Microsaccades are important fixation eye movements for visual scene perception. Compared to novices, athletes make fewer fixations of longer duration toward limited interest areas crucial for action prediction. Thus, our aim was to study the microsaccade features during those fixations. Gaze behaviour of expert and novice table tennis players was recorder during a task in which subjects were instructed to predict the direction of the ball after the opponent's throw. Three interest areas from the opponent's body and one from the ball trajectory were identified. We analysed correctness of predictions, fixations, microsaccades and saccades to estimate the relationship between eye movements toward interest areas and success in the task. Compared to novices, experts fixated more on hand-racket during forehand and on trunk during backhand drive technique. Longer fixations on hand-racket and trunk were associated with higher microsaccade rate with a narrower directional distribution of them. It probably means that athletes focused their gaze on these small areas, suggesting enhanced attention mainly to them, and fewer consideration for the surrounding regions. We can assume that microsaccade rate and average direction could be related to the salience of interest areas during performance.

Predicting adherence of patients with HF through machine learning techniques.

PubMed

Karanasiou, Georgia Spiridon; Tripoliti, Evanthia Eleftherios; Papadopoulos, Theofilos Grigorios; Kalatzis, Fanis Georgios; Goletsis, Yorgos; Naka, Katerina Kyriakos; Bechlioulis, Aris; Errachid, Abdelhamid; Fotiadis, Dimitrios Ioannis

2016-09-01

Heart failure (HF) is a chronic disease characterised by poor quality of life, recurrent hospitalisation and high mortality. Adherence of patient to treatment suggested by the experts has been proven a significant deterrent of the above-mentioned serious consequences. However, the non-adherence rates are significantly high; a fact that highlights the importance of predicting the adherence of the patient and enabling experts to adjust accordingly patient monitoring and management. The aim of this work is to predict the adherence of patients with HF, through the application of machine learning techniques. Specifically, it aims to classify a patient not only as medication adherent or not, but also as adherent or not in terms of medication, nutrition and physical activity (global adherent). Two classification problems are addressed: (i) if the patient is global adherent or not and (ii) if the patient is medication adherent or not. About 11 classification algorithms are employed and combined with feature selection and resampling techniques. The classifiers are evaluated on a dataset of 90 patients. The patients are characterised as medication and global adherent, based on clinician estimation. The highest detection accuracy is 82 and 91% for the first and the second classification problem, respectively.

Information Uncertainty to Compare Qualitative Reasoning Security Risk Assessment Results

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

Chavez, Gregory M; Key, Brian P; Zerkle, David K

2009-01-01

The security risk associated with malevolent acts such as those of terrorism are often void of the historical data required for a traditional PRA. Most information available to conduct security risk assessments for these malevolent acts is obtained from subject matter experts as subjective judgements. Qualitative reasoning approaches such as approximate reasoning and evidential reasoning are useful for modeling the predicted risk from information provided by subject matter experts. Absent from these approaches is a consistent means to compare the security risk assessment results. Associated with each predicted risk reasoning result is a quantifiable amount of information uncertainty which canmore » be measured and used to compare the results. This paper explores using entropy measures to quantify the information uncertainty associated with conflict and non-specificity in the predicted reasoning results. The measured quantities of conflict and non-specificity can ultimately be used to compare qualitative reasoning results which are important in triage studies and ultimately resource allocation. Straight forward extensions of previous entropy measures are presented here to quantify the non-specificity and conflict associated with security risk assessment results obtained from qualitative reasoning models.« less

Modeling methods for merging computational and experimental aerodynamic pressure data

NASA Astrophysics Data System (ADS)

Haderlie, Jacob C.

This research describes a process to model surface pressure data sets as a function of wing geometry from computational and wind tunnel sources and then merge them into a single predicted value. The described merging process will enable engineers to integrate these data sets with the goal of utilizing the advantages of each data source while overcoming the limitations of both; this provides a single, combined data set to support analysis and design. The main challenge with this process is accurately representing each data source everywhere on the wing. Additionally, this effort demonstrates methods to model wind tunnel pressure data as a function of angle of attack as an initial step towards a merging process that uses both location on the wing and flow conditions (e.g., angle of attack, flow velocity or Reynold's number) as independent variables. This surrogate model of pressure as a function of angle of attack can be useful for engineers that need to predict the location of zero-order discontinuities, e.g., flow separation or normal shocks. Because, to the author's best knowledge, there is no published, well-established merging method for aerodynamic pressure data (here, the coefficient of pressure Cp), this work identifies promising modeling and merging methods, and then makes a critical comparison of these methods. Surrogate models represent the pressure data for both data sets. Cubic B-spline surrogate models represent the computational simulation results. Machine learning and multi-fidelity surrogate models represent the experimental data. This research compares three surrogates for the experimental data (sequential--a.k.a. online--Gaussian processes, batch Gaussian processes, and multi-fidelity additive corrector) on the merits of accuracy and computational cost. The Gaussian process (GP) methods employ cubic B-spline CFD surrogates as a model basis function to build a surrogate model of the WT data, and this usage of the CFD surrogate in building the WT data could serve as a "merging" because the resulting WT pressure prediction uses information from both sources. In the GP approach, this model basis function concept seems to place more "weight" on the Cp values from the wind tunnel (WT) because the GP surrogate uses the CFD to approximate the WT data values. Conversely, the computationally inexpensive additive corrector method uses the CFD B-spline surrogate to define the shape of the spanwise distribution of the Cp while minimizing prediction error at all spanwise locations for a given arc length position; this, too, combines information from both sources to make a prediction of the 2-D WT-based Cp distribution, but the additive corrector approach gives more weight to the CFD prediction than to the WT data. Three surrogate models of the experimental data as a function of angle of attack are also compared for accuracy and computational cost. These surrogates are a single Gaussian process model (a single "expert"), product of experts, and generalized product of experts. The merging approach provides a single pressure distribution that combines experimental and computational data. The batch Gaussian process method provides a relatively accurate surrogate that is computationally acceptable, and can receive wind tunnel data from port locations that are not necessarily parallel to a variable direction. On the other hand, the sequential Gaussian process and additive corrector methods must receive a sufficient number of data points aligned with one direction, e.g., from pressure port bands (tap rows) aligned with the freestream. The generalized product of experts best represents wind tunnel pressure as a function of angle of attack, but at higher computational cost than the single expert approach. The format of the application data from computational and experimental sources in this work precluded the merging process from including flow condition variables (e.g., angle of attack) in the independent variables, so the merging process is only conducted in the wing geometry variables of arc length and span. The merging process of Cp data allows a more "hands-off" approach to aircraft design and analysis, (i.e., not as many engineers needed to debate the Cp distribution shape) and generates Cp predictions at any location on the wing. However, the cost with these benefits are engineer time (learning how to build surrogates), computational time in constructing the surrogates, and surrogate accuracy (surrogates introduce error into data predictions). This dissertation effort used the Trap Wing / First AIAA CFD High-Lift Prediction Workshop as a relevant transonic wing with a multi-element high-lift system, and this work identified that the batch GP model for the WT data and the B-spline surrogate for the CFD might best be combined using expert belief weights to describe Cp as a function of location on the wing element surface. (Abstract shortened by ProQuest.).

Evaluating the ability of artificial neural network and PCA-M5P models in predicting leachate COD load in landfills.

PubMed

Azadi, Sama; Amiri, Hamid; Rakhshandehroo, G Reza

2016-09-01

Waste burial in uncontrolled landfills can cause serious environmental damages and unpleasant consequences. Leachates produced in landfills have the potential to contaminate soil and groundwater resources. Leachate management is one of the major issues with respect to landfills environmental impacts. Improper design of landfills can lead to leachate spread in the environment, and hence, engineered landfills are required to have leachate monitoring programs. The high cost of such programs may be greatly reduced and cost efficiency of the program may be optimized if one can predict leachate contamination level and foresee management and treatment strategies. The aim of this study is to develop two expert systems consisting of Artificial Neural Network (ANN) and Principal Component Analysis-M5P (PCA-M5P) models to predict Chemical Oxygen Demand (COD) load in leachates produced in lab-scale landfills. Measured data from three landfill lysimeters, including rainfall depth, number of days after waste deposition, thickness of top and bottom Compacted Clay Liners (CCLs), and thickness of top cover over the lysimeter, were utilized to develop, train, validate, and test the expert systems and predict the leachate COD load. Statistical analysis of the prediction results showed that both models possess good prediction ability with a slight superiority for ANN over PCA-M5P. Based on test datasets, the mean absolute percentage error for ANN and PCA-M5P models were 4% and 12%, respectively, and the correlation coefficient for both models was greater than 0.98. Developed models may be used as a rough estimate for leachate COD load prediction in primary landfill designs, where the effect of a top and/or bottom liner is disputed. Copyright © 2016 Elsevier Ltd. All rights reserved.

Prognostics using Engineering and Environmental Parameters as Applied to State of Health (SOH) Radionuclide Aerosol Sampler Analyzer (RASA) Real-Time Monitoring

NASA Astrophysics Data System (ADS)

Hutchenson, K. D.; Hartley-McBride, S.; Saults, T.; Schmidt, D. P.

2006-05-01

The International Monitoring System (IMS) is composed in part of radionuclide particulate and gas monitoring systems. Monitoring the operational status of these systems is an important aspect of nuclear weapon test monitoring. Quality data, process control techniques, and predictive models are necessary to detect and predict system component failures. Predicting failures in advance provides time to mitigate these failures, thus minimizing operational downtime. The Provisional Technical Secretariat (PTS) requires IMS radionuclide systems be operational 95 percent of the time. The United States National Data Center (US NDC) offers contributing components to the IMS. This effort focuses on the initial research and process development using prognostics for monitoring and predicting failures of the RASA two (2) days into the future. The predictions, using time series methods, are input to an expert decision system, called SHADES (State of Health Airflow and Detection Expert System). The results enable personnel to make informed judgments about the health of the RASA system. Data are read from a relational database, processed, and displayed to the user in a GIS as a prototype GUI. This procedure mimics the real time application process that could be implemented as an operational system, This initial proof-of-concept effort developed predictive models focused on RASA components for a single site (USP79). Future work shall include the incorporation of other RASA systems, as well as their environmental conditions that play a significant role in performance. Similarly, SHADES currently accommodates specific component behaviors at this one site. Future work shall also include important environmental variables that play an important part of the prediction algorithms.

Objective Assessment of the Interfrontal Angle for Severity Grading and Operative Decision-Making in Metopic Synostosis.

PubMed

Anolik, Rachel A; Allori, Alexander C; Pourtaheri, Navid; Rogers, Gary F; Marcus, Jeffrey R

2016-05-01

The purpose of this study was to evaluate the utility of a previously validated interfrontal angle for classification of severity of metopic synostosis and as an aid to operative decision-making. An expert panel was asked to study 30 cases ranging from minor to severe metopic synostosis. Based on computed tomographic images of the skull and clinical photographs, they classified the severity of trigonocephaly (1 = normal, 2 = mild, 3 = moderate, and 4 = severe) and management (0 = nonoperative and 1 = operative). The severity scores and management reported by experts were then pooled and matched with the interfrontal angle computed from each respective computed tomographic scan. A threshold was identified at which most experts agree on operative management. Expert severity scores were higher for more acute interfrontal angles. There was a high concordance at the extremes of classifications, severe (4) and normal (1) (p < 0.0001); however, between interfrontal angles of 114.3 and 136.1 degrees, there exists a "gray zone," with severe discordance in expert rankings. An operative threshold of 118.2 degrees was identified, with the interfrontal angle able to predict the expert panel's decision to proceed with surgery 87.6 percent of the time. The interfrontal angle has been previously validated as a simple, accurate, and reproducible means for diagnosing trigonocephaly, but must be obtained from computed tomographic data. In this article, the authors demonstrate that the interfrontal angle can be used to further characterize the severity of trigonocephaly. It also correlated with expert decision-making for operative versus nonoperative management. This tool may be used as an adjunct to clinical decision-making when the decision to proceed with surgery may not be straightforward. Diagnostic, V.

Chronic obstructive lung disease "expert system": validation of a predictive tool for assisting diagnosis.

PubMed

Braido, Fulvio; Santus, Pierachille; Corsico, Angelo Guido; Di Marco, Fabiano; Melioli, Giovanni; Scichilone, Nicola; Solidoro, Paolo

2018-01-01

The purposes of this study were development and validation of an expert system (ES) aimed at supporting the diagnosis of chronic obstructive lung disease (COLD). A questionnaire and a WebFlex code were developed and validated in silico. An expert panel pilot validation on 60 cases and a clinical validation on 241 cases were performed. The developed questionnaire and code validated in silico resulted in a suitable tool to support the medical diagnosis. The clinical validation of the ES was performed in an academic setting that included six different reference centers for respiratory diseases. The results of the ES expressed as a score associated with the risk of suffering from COLD were matched and compared with the final clinical diagnoses. A set of 60 patients were evaluated by a pilot expert panel validation with the aim of calculating the sample size for the clinical validation study. The concordance analysis between these preliminary ES scores and diagnoses performed by the experts indicated that the accuracy was 94.7% when both experts and the system confirmed the COLD diagnosis and 86.3% when COLD was excluded. Based on these results, the sample size of the validation set was established in 240 patients. The clinical validation, performed on 241 patients, resulted in ES accuracy of 97.5%, with confirmed COLD diagnosis in 53.6% of the cases and excluded COLD diagnosis in 32% of the cases. In 11.2% of cases, a diagnosis of COLD was made by the experts, although the imaging results showed a potential concomitant disorder. The ES presented here (COLD ES ) is a safe and robust supporting tool for COLD diagnosis in primary care settings.

An algebraic method for constructing stable and consistent autoregressive filters

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

Harlim, John, E-mail: jharlim@psu.edu; Department of Meteorology, the Pennsylvania State University, University Park, PA 16802; Hong, Hoon, E-mail: hong@ncsu.edu

2015-02-15

In this paper, we introduce an algebraic method to construct stable and consistent univariate autoregressive (AR) models of low order for filtering and predicting nonlinear turbulent signals with memory depth. By stable, we refer to the classical stability condition for the AR model. By consistent, we refer to the classical consistency constraints of Adams–Bashforth methods of order-two. One attractive feature of this algebraic method is that the model parameters can be obtained without directly knowing any training data set as opposed to many standard, regression-based parameterization methods. It takes only long-time average statistics as inputs. The proposed method provides amore » discretization time step interval which guarantees the existence of stable and consistent AR model and simultaneously produces the parameters for the AR models. In our numerical examples with two chaotic time series with different characteristics of decaying time scales, we find that the proposed AR models produce significantly more accurate short-term predictive skill and comparable filtering skill relative to the linear regression-based AR models. These encouraging results are robust across wide ranges of discretization times, observation times, and observation noise variances. Finally, we also find that the proposed model produces an improved short-time prediction relative to the linear regression-based AR-models in forecasting a data set that characterizes the variability of the Madden–Julian Oscillation, a dominant tropical atmospheric wave pattern.« less

An evaluation of consensus techniques for diagnostic interpretation

NASA Astrophysics Data System (ADS)

Sauter, Jake N.; LaBarre, Victoria M.; Furst, Jacob D.; Raicu, Daniela S.

2018-02-01

Learning diagnostic labels from image content has been the standard in computer-aided diagnosis. Most computer-aided diagnosis systems use low-level image features extracted directly from image content to train and test machine learning classifiers for diagnostic label prediction. When the ground truth for the diagnostic labels is not available, reference truth is generated from the experts diagnostic interpretations of the image/region of interest. More specifically, when the label is uncertain, e.g. when multiple experts label an image and their interpretations are different, techniques to handle the label variability are necessary. In this paper, we compare three consensus techniques that are typically used to encode the variability in the experts labeling of the medical data: mean, median and mode, and their effects on simple classifiers that can handle deterministic labels (decision trees) and probabilistic vectors of labels (belief decision trees). Given that the NIH/NCI Lung Image Database Consortium (LIDC) data provides interpretations for lung nodules by up to four radiologists, we leverage the LIDC data to evaluate and compare these consensus approaches when creating computer-aided diagnosis systems for lung nodules. First, low-level image features of nodules are extracted and paired with their radiologists semantic ratings (1= most likely benign, , 5 = most likely malignant); second, machine learning multi-class classifiers that handle deterministic labels (decision trees) and probabilistic vectors of labels (belief decision trees) are built to predict the lung nodules semantic ratings. We show that the mean-based consensus generates the most robust classi- fier overall when compared to the median- and mode-based consensus. Lastly, the results of this study show that, when building CAD systems with uncertain diagnostic interpretation, it is important to evaluate different strategies for encoding and predicting the diagnostic label.

Chemistry of atmosphere-surface interactions on Venus and Mars

NASA Astrophysics Data System (ADS)

Fegley, Bruce, Jr.; Treiman, Allan H.

Earth-based, earth-orbital, and spacecraft observational data are used in the present evaluation of Venus atmosphere-surface interactions to quantitatively characterize the reactions between C, H, S, Cl, F, and N gases and plausible surface minerals. Calculation results are used to predict stable minerals and mineral assemblages on the Venus surface, in order to ascertain which (if any) of the atmospheric gases are buffeted by mineral assemblages. Chemical equilibrium calculations using extant thermodynamic data on scapolite minerals predict that carbonate-bearing scapolite and sulfate meionite are unstable on the surface of Venus, while chloride-bearing scapolite is stable.

A nomogram for predicting complications in patients with solid tumours and seemingly stable febrile neutropenia.

PubMed

Fonseca, Paula Jiménez; Carmona-Bayonas, Alberto; García, Ignacio Matos; Marcos, Rosana; Castañón, Eduardo; Antonio, Maite; Font, Carme; Biosca, Mercè; Blasco, Ana; Lozano, Rebeca; Ramchandani, Avinash; Beato, Carmen; de Castro, Eva Martínez; Espinosa, Javier; Martínez-García, Jerónimo; Ghanem, Ismael; Cubero, Jorge Hernando; Manrique, Isabel Aragón; Navalón, Francisco García; Sevillano, Elena; Manzano, Aránzazu; Virizuela, Juan; Garrido, Marcelo; Mondéjar, Rebeca; Arcusa, María Ángeles; Bonilla, Yaiza; Pérez, Quionia; Gallardo, Elena; Del Carmen Soriano, Maria; Cardona, Mercè; Lasheras, Fernando Sánchez; Cruz, Juan Jesús; Ayala, Francisco

2016-05-24

We sought to develop and externally validate a nomogram and web-based calculator to individually predict the development of serious complications in seemingly stable adult patients with solid tumours and episodes of febrile neutropenia (FN). The data from the FINITE study (n=1133) and University of Salamanca Hospital (USH) FN registry (n=296) were used to develop and validate this tool. The main eligibility criterion was the presence of apparent clinical stability, defined as events without acute organ dysfunction, abnormal vital signs, or major infections. Discriminatory ability was measured as the concordance index and stratification into risk groups. The rate of infection-related complications in the FINITE and USH series was 13.4% and 18.6%, respectively. The nomogram used the following covariates: Eastern Cooperative Group (ECOG) Performance Status ⩾2, chronic obstructive pulmonary disease, chronic cardiovascular disease, mucositis of grade ⩾2 (National Cancer Institute Common Toxicity Criteria), monocytes <200/mm(3), and stress-induced hyperglycaemia. The nomogram predictions appeared to be well calibrated in both data sets (Hosmer-Lemeshow test, P>0.1). The concordance index was 0.855 and 0.831 in each series. Risk group stratification revealed a significant distinction in the proportion of complications. With a ⩾116-point cutoff, the nomogram yielded the following prognostic indices in the USH registry validation series: 66% sensitivity, 83% specificity, 3.88 positive likelihood ratio, 48% positive predictive value, and 91% negative predictive value. We have developed and externally validated a nomogram and web calculator to predict serious complications that can potentially impact decision-making in patients with seemingly stable FN.

FibroMeters: a family of blood tests for liver fibrosis.

PubMed

Calès, P; Boursier, J; Oberti, F; Hubert, I; Gallois, Y; Rousselet, M-C; Dib, N; Moal, V; Macchi, L; Chevailler, A; Michalak, S; Hunault, G; Chaigneau, J; Sawadogo, A; Lunel, F

2008-09-01

FibroMeters are blood tests for liver fibrosis with several specificities: two main diagnostic targets (fibrosis stage and area of fibrosis); adaptation to specific causes; and results confirmed by an expert system. Thus, FibroMeters comprise six different tests: one for staging and one for quantitation of liver fibrosis in each of the three main causes of chronic liver disease-chronic viral hepatitis, alcoholic liver disease (ALD) and non-alcoholic fatty liver disease (NAFLD). FibroMeters display a high overall diagnostic accuracy and are the only tests to correctly classify 100% of HCV patients without fibrosis or with cirrhosis. They have 90% predictive values in a higher proportion of patients than with other usual blood tests. A 90% correct classification is available in 100% of HCV patients with the following reliable diagnostic intervals: F0/1, F1/2, F2+/-1, F3+/-1. In real-life conditions, the reproducibility of FibroMeters is higher than that of liver biopsy or ultrasonographic elastometry. FibroMeters are robust tests with the most stable diagnostic performance across different centers. Optional tests are also available, such as a specific one for cirrhosis, which has a diagnostic accuracy of 93.0% (AUROC: 0.92) and a 100% positive predictive value for diagnosis of HCV cirrhosis. Determination by FibroMeters of the area of fibrosis - the only direct, non-invasive, quantitative measurement of liver fibrosis - are especially useful for following-up cirrhosis as it correlates well with clinical events. FibroMeters are also very accurate in HVB or HIV-HCV co-infected patients. The tests specific for ALD and NAFLD also have a high diagnostic accuracy (AUROCs: 0.96 and 0.94, respectively, for significant fibrosis).

Biomass offsets little or none of permafrost carbon release from soils, streams, and wildfire: an expert assessment

USGS Publications Warehouse

Benjamin W. Abbott,; Jeremy B. Jones,; Edward A.G. Schuur,; F.S. Chapin, III; Bowden, William B.; M. Syndonia Bret-Harte,; Howard E. Epstein,; Michael D. Flannigan,; Tamara K. Harms,; Teresa N. Hollingsworth,; Mack, Michelle C.; McGuire, A. David; Susan M. Natali,; Adrian V. Rocha,; Tank, Suzanne E.; Merrit R. Turetsky,; Jorien E. Vonk,; Wickland, Kimberly P.; Aiken, George R.

2016-01-01

As the permafrost region warms, its large organic carbon pool will be increasingly vulnerable to decomposition, combustion, and hydrologic export. Models predict that some portion of this release will be offset by increased production of Arctic and boreal biomass; however, the lack of robust estimates of net carbon balance increases the risk of further overshooting international emissions targets. Precise empirical or model-based assessments of the critical factors driving carbon balance are unlikely in the near future, so to address this gap, we present estimates from 98 permafrost-region experts of the response of biomass, wildfire, and hydrologic carbon flux to climate change. Results suggest that contrary to model projections, total permafrost-region biomass could decrease due to water stress and disturbance, factors that are not adequately incorporated in current models. Assessments indicate that end-of-the-century organic carbon release from Arctic rivers and collapsing coastlines could increase by 75% while carbon loss via burning could increase four-fold. Experts identified water balance, shifts in vegetation community, and permafrost degradation as the key sources of uncertainty in predicting future system response. In combination with previous findings, results suggest the permafrost region will become a carbon source to the atmosphere by 2100 regardless of warming scenario but that 65%–85% of permafrost carbon release can still be avoided if human emissions are actively reduced.

Assessment of long-term transgene expression in barley: Ds-mediated delivery of bar results in robust, stable, and heritable expression

USDA-ARS?s Scientific Manuscript database

The utility of transgenic plants for both experimental and practical agronomic purposes is highly dependent on stable, predictable, and heritable expression of the introduced genes. This requirement is frequently unfulfilled, and transgenes are frequently subject to silencing. Studies of the charact...

A Guide for Assessing Biodegradation and Source Identification of Organic Groundwater Contaminants Using Compound Specific Isotope Analysis (CSIA)

EPA Science Inventory

When organic contaminants are degraded in the environment, the ratio of stable isotopes will often change, and the extent of degradation can be recognized and predicted from the change in the ratio of stable isotopes. Recent advances in analytical chemistry make it possible to p...

Possible Potentials Responsible for Stable Circular Relativistic Orbits

ERIC Educational Resources Information Center

Kumar, Prashant; Bhattacharya, Kaushik

2011-01-01

Bertrand's theorem in classical mechanics of the central force fields attracts us because of its predictive power. It categorically proves that there can only be two types of forces which can produce stable, circular orbits. In this paper an attempt has been made to generalize Bertrand's theorem to the central force problem of relativistic…

Consensus coding sequence (CCDS) database: a standardized set of human and mouse protein-coding regions supported by expert curation.

PubMed

Pujar, Shashikant; O'Leary, Nuala A; Farrell, Catherine M; Loveland, Jane E; Mudge, Jonathan M; Wallin, Craig; Girón, Carlos G; Diekhans, Mark; Barnes, If; Bennett, Ruth; Berry, Andrew E; Cox, Eric; Davidson, Claire; Goldfarb, Tamara; Gonzalez, Jose M; Hunt, Toby; Jackson, John; Joardar, Vinita; Kay, Mike P; Kodali, Vamsi K; Martin, Fergal J; McAndrews, Monica; McGarvey, Kelly M; Murphy, Michael; Rajput, Bhanu; Rangwala, Sanjida H; Riddick, Lillian D; Seal, Ruth L; Suner, Marie-Marthe; Webb, David; Zhu, Sophia; Aken, Bronwen L; Bruford, Elspeth A; Bult, Carol J; Frankish, Adam; Murphy, Terence; Pruitt, Kim D

2018-01-04

The Consensus Coding Sequence (CCDS) project provides a dataset of protein-coding regions that are identically annotated on the human and mouse reference genome assembly in genome annotations produced independently by NCBI and the Ensembl group at EMBL-EBI. This dataset is the product of an international collaboration that includes NCBI, Ensembl, HUGO Gene Nomenclature Committee, Mouse Genome Informatics and University of California, Santa Cruz. Identically annotated coding regions, which are generated using an automated pipeline and pass multiple quality assurance checks, are assigned a stable and tracked identifier (CCDS ID). Additionally, coordinated manual review by expert curators from the CCDS collaboration helps in maintaining the integrity and high quality of the dataset. The CCDS data are available through an interactive web page (https://www.ncbi.nlm.nih.gov/CCDS/CcdsBrowse.cgi) and an FTP site (ftp://ftp.ncbi.nlm.nih.gov/pub/CCDS/). In this paper, we outline the ongoing work, growth and stability of the CCDS dataset and provide updates on new collaboration members and new features added to the CCDS user interface. We also present expert curation scenarios, with specific examples highlighting the importance of an accurate reference genome assembly and the crucial role played by input from the research community. Published by Oxford University Press on behalf of Nucleic Acids Research 2017.

Conservative management of idiopathic scoliosis--guidelines based on SOSORT 2006 Consensus.

PubMed

Kotwicki, Tomasz; Durmała, Jacek; Czaprowski, Dariusz; Głowacki, Maciej; Kołban, Maciej; Snela, Sławomir; Sliwiński, Zbigniew; Kowalski, Ireneusz M

2009-01-01

Idiopathic scoliosis, defined as a lateral curvature of the spine of above 10 degrees (Cobb angle), is seen in 2-3% of the growing age population, while curves above 20 degrees , requiring conservative treatment, are found in 0.3-0.5%. In our observation, both under-treatment of progressive curves and over-treatment of stable cases are common during conservative management of scoliosis. A model of therapeutic management is presented based on the experience of Polish clinicians specialising in the treatment of scoliosis as well as the effects of work of a panel of experts of SOSORT (Society on Scoliosis Orthopaedic and Rehabilitation Treatment). The model comprises the indications for conservative treatment according to age, curve type and size and Risser grading. The aetiology, classifications, usefulness of the Lonstein and Carlson factor of progression and other methods of determining the probability of scoliosis progression, as well as the psychological aspects of conservative management are presented. Based on the knowledge of the natural history of idiopathic scoliosis, factors of progression and on the SOSORT experts' opinion, guidelines are proposed for clinicians treating children and adolescents with idiopathic scoliosis, including the timing and course of brace treatment and the types of exercises. Uniform practical guidelines developed by experts may represent an essential step towards establishing standards of conservative scoliosis care in our country.

Profits without People.

ERIC Educational Resources Information Center

Boutwell, Clinton E.

1997-01-01

America's corporate executives consider a huge world-class workforce superfluous. Corporate restructuring's bottom line was the massive shedding of workers, a reduction in future job opportunities, and a concomitant plunge in income, benefits, and living standards for millions. Experts predict that only 20% of well-trained college graduates will…

Multidimensional Perception of Counselor Behavior

ERIC Educational Resources Information Center

Barak, Azy; LaCrosse, Michael B.

1975-01-01

Investigated Strong's prediction of the existence of three dimensions of perceived counselor behavior--expertness, attractiveness, and trustworthiness. Films of interviews given by Rogers, Ellis, and Perls were watched by 202 subjects, who rated each counselor on 36 bipolar scales. Results supported the existence of the hypothesized dimensions for…

Confirmation of the Conditional Outdoor Leadership Theory.

ERIC Educational Resources Information Center

Dixon, Tim; Priest, Simon

1991-01-01

Responses of 75 expert outdoor leaders from Canada and the United States concerning leadership in 12 hypothetical backpacking scenarios provided partial support for a theory that predicted probability of leadership style (democratic, autocratic, or abdicratic) based on favorability of conditions, task orientation, and relationship orientation.…

Blowout Monitor

NASA Technical Reports Server (NTRS)

1994-01-01

C Language Integrated Production System (CLIPS), a NASA-developed software shell for developing expert systems, has been embedded in a PC-based expert system for training oil rig personnel in monitoring oil drilling. Oil drilling rigs if not properly maintained for possible blowouts pose hazards to human life, property and the environment may be destroyed. CLIPS is designed to permit the delivery of artificial intelligence on computer. A collection of rules is set up and, as facts become known, these rules are applied. In the Well Site Advisor, CLIPS provides the capability to accurately process, predict and interpret well data in a real time mode. CLIPS was provided to INTEQ by COSMIC.

Perception-action coupling and anticipatory performance in baseball batting.

PubMed

Ranganathan, Rajiv; Carlton, Les G

2007-09-01

The authors examined 10 expert and 10 novice baseball batters' ability to distinguish between a fastball and a change-up in a virtual environment. They used 2 different response modes: (a) an uncoupled response in which the batters verbally predicted the type of pitch and (b) a coupled response in which the batters swung a baseball bat to try and hit the virtual ball. The authors manipulated visual information from the pitcher and ball in 6 visual conditions. The batters were more accurate in predicting the type of pitch when the response was uncoupled. In coupled responses, experts were better able to use the first 100 ms of ball flight independently of the pitcher's kinematics. In addition, the skilled batters' stepping patterns were related to the pitcher's kinematics, whereas their swing time was related to ball speed. Those findings suggest that specific task requirements determine whether a highly coupled perception-action environment improves anticipatory performance. The authors also highlight the need for research on interceptive actions to be conducted in the performer's natural environment.

An Expert System for Diagnosis of Sleep Disorder Using Fuzzy Rule-Based Classification Systems

NASA Astrophysics Data System (ADS)

Septem Riza, Lala; Pradini, Mila; Fitrajaya Rahman, Eka; Rasim

2017-03-01

Sleep disorder is an anomaly that could cause problems for someone’ sleeping pattern. Nowadays, it becomes an issue since people are getting busy with their own business and have no time to visit the doctors. Therefore, this research aims to develop a system used for diagnosis of sleep disorder using Fuzzy Rule-Based Classification System (FRBCS). FRBCS is a method based on the fuzzy set concepts. It consists of two steps: (i) constructing a model/knowledge involving rulebase and database, and (ii) prediction over new data. In this case, the knowledge is obtained from experts whereas in the prediction stage, we perform fuzzification, inference, and classification. Then, a platform implementing the method is built with a combination between PHP and the R programming language using the “Shiny” package. To validate the system that has been made, some experiments have been done using data from a psychiatric hospital in West Java, Indonesia. Accuracy of the result and computation time are 84.85% and 0.0133 seconds, respectively.

Invited Speaker Support for SBP Conference Series (SBP 2014) held in April, 2014 in Washington, DC.

DTIC Science & Technology

2014-07-23

Experts in Social Media Wenhui Liao, Sameena Shah and Masoud Makrehchi Talk 2 Predicting Social Ties in Massively Multiplayer Online Games Jina...sweets, beverages SBP Poster The Needs of Metaphor David Bracewell SBP Poster Predicting Guild Membership in Massively Multiplayer Online ...Science series. These proceedings can be accessed online through the following link: http://link.springer.com/book/10.1007%2F978-3-319-05579-4 (Springer

In silico tools for sharing data and knowledge on toxicity and metabolism: derek for windows, meteor, and vitic.

PubMed

Marchant, Carol A; Briggs, Katharine A; Long, Anthony

2008-01-01

ABSTRACT Lhasa Limited is a not-for-profit organization that exists to promote the sharing of data and knowledge in chemistry and the life sciences. It has developed the software tools Derek for Windows, Meteor, and Vitic to facilitate such sharing. Derek for Windows and Meteor are knowledge-based expert systems that predict the toxicity and metabolism of a chemical, respectively. Vitic is a chemically intelligent toxicity database. An overview of each software system is provided along with examples of the sharing of data and knowledge in the context of their development. These examples include illustrations of (1) the use of data entry and editing tools for the sharing of data and knowledge within organizations; (2) the use of proprietary data to develop nonconfidential knowledge that can be shared between organizations; (3) the use of shared expert knowledge to refine predictions; (4) the sharing of proprietary data between organizations through the formation of data-sharing groups; and (5) the use of proprietary data to validate predictions. Sharing of chemical toxicity and metabolism data and knowledge in this way offers a number of benefits including the possibilities of faster scientific progress and reductions in the use of animals in testing. Maximizing the accessibility of data also becomes increasingly crucial as in silico systems move toward the prediction of more complex phenomena for which limited data are available.

An Expert System For Multispectral Threat Assessment And Response

NASA Astrophysics Data System (ADS)

Steinberg, Alan N.

1987-05-01

A concept has been defined for an automatic system to manage the self-defense of a combat aircraft. Distinctive new features of this concept include: a. the flexible prioritization of tasks and coordinated use of sensor, countermeasures, flight systems and weapons assets by means of an automated planning function; b. the integration of state-of-the-art data fusion algorithms with event prediction processing; c. the use of advanced Artificial Intelligence tools to emulate the decision processes of tactical EW experts. Threat Assessment functions (a) estimate threat identity, lethality and intent on the basis of multi-spectral sensor data, and (b) predict the time to critical events in threat engagements (e.g., target acquisition, tracking, weapon launch, impact). Response Management functions (a) select candidate responses to reported threat situations; (b) estimate the effects of candidate actions on survival; and (c) coordinate the assignment of sensors, weapons and countermeasures with the flight plan. The system employs Finite State Models to represent current engagements and to predict subsequent events. Each state in a model is associated with a set of observable features, allowing interpretation of sensor data and adaptive use of sensor assets. Defined conditions on state transitions allow prediction of times to critical future states and are used in planning self-defensive responses, which are designed either to impede a particular state transition or to force a transition to a lower threat state.

Differences between naïve and expert observers’ vergence and accommodative responses to a range of targets

PubMed Central

Horwood, Anna M; Riddell, Patricia M

2015-01-01

Purpose Vergence and accommodation studies often use adult participants with experience of vision science. Reports of infant and clinical responses are generally more variable and of lower gain, with the implication that differences lie in immaturity or sub-optimal clinical characteristics but expert /naïve differences are rarely considered or quantified. Methods Sixteen undergraduates, naïve to vision science were individually matched by age, visual acuity, refractive error, heterophoria, stereoacuity and near point of accommodation to 2nd & 3rd year orthoptics and optometry undergraduates (“experts”). Accommodation and vergence responses were assessed to targets moving between 33cm, 50 cm, 1m and 2m using a haploscopic device incorporating a PlusoptiX SO4 autorefractor. Disparity, blur and looming cues were separately available or minimised in all combinations. Instruction set was minimal. Results In all cases, vergence and accommodation response slopes (gain) were steeper and closer to 1.0 in the expert group (p=0.001), with the largest expert /naïve differences for both vergence and accommodation being for near targets (p=0.012). For vergence, the differences between expert and naïve response slopes increased with increasingly open-loop targets (linear trend p=0.025). Although we predicted that proximal cues would drive additional response in the experts, the proximity-only cue was the only condition that showed no statistical effect of experience. Conclusions Expert observers provide more accurate responses to near target demand than closely matched naïve observers. We suggest that attention, practice, voluntary and proprioceptive effects may enhance responses in experienced participants when compared to a more typical general population. Differences between adult reports and the developmental and clinical literature may partially reflect expert / naïve effects, as well as developmental change. If developmental and clinical studies are to be compared to adult normative data, uninstructed naïve adult data should be used. PMID:20444119

Expert Elicitations of 2100 Emission of CO2

NASA Astrophysics Data System (ADS)

Ho, Emily; Bosetti, Valentina; Budescu, David; Keller, Klaus; van Vuuren, Detlef

2017-04-01

Emission scenarios such as Shared Socioeconomic Pathways (SSPs) and Representative Concentration Pathways (RCPs) are used intensively for climate research (e.g. climate change projections) and policy analysis. While the range of these scenarios provides an indication of uncertainty, these scenarios are typically not associated with probability values. Some studies (e.g. Vuuren et al, 2007; Gillingham et al., 2015) took a different approach associating baseline emission pathways (conditionally) with probability distributions. This paper summarizes three studies where climate change experts were asked to conduct pair-wise comparisons of possible ranges of 2100 greenhouse gas emissions and rate the relative likelihood of the ranges. The elicitation was performed under two sets of assumptions: 1) a situation where no climate policies are introduced beyond the ones already in place (baseline scenario), and 2) a situation in which countries have ratified the voluntary policies in line with the long term target embedded in the 2015 Paris Agreement. These indirect relative judgments were used to construct subjective cumulative distribution functions. We show that by using a ratio scaling method that invokes relative likelihoods of scenarios, a subjective probability distribution can be derived for each expert that expresses their beliefs in the projected greenhouse gas emissions range in 2100. This method is shown to elicit stable estimates that require minimal adjustment and is relatively invariant to the partition of the domain of interest. Experts also rated the method as being easy and intuitive to use. We also report results of a study that allowed participants to choose their own ranges of greenhouse gas emissions to remove potential anchoring bias. We discuss the implications of the use of this method for facilitating comparison and communication of beliefs among diverse users of climate science research.

Evolutionary Dynamics on Protein Bi-stability Landscapes can Potentially Resolve Adaptive Conflicts

PubMed Central

Sikosek, Tobias; Bornberg-Bauer, Erich; Chan, Hue Sun

2012-01-01

Experimental studies have shown that some proteins exist in two alternative native-state conformations. It has been proposed that such bi-stable proteins can potentially function as evolutionary bridges at the interface between two neutral networks of protein sequences that fold uniquely into the two different native conformations. Under adaptive conflict scenarios, bi-stable proteins may be of particular advantage if they simultaneously provide two beneficial biological functions. However, computational models that simulate protein structure evolution do not yet recognize the importance of bi-stability. Here we use a biophysical model to analyze sequence space to identify bi-stable or multi-stable proteins with two or more equally stable native-state structures. The inclusion of such proteins enhances phenotype connectivity between neutral networks in sequence space. Consideration of the sequence space neighborhood of bridge proteins revealed that bi-stability decreases gradually with each mutation that takes the sequence further away from an exactly bi-stable protein. With relaxed selection pressures, we found that bi-stable proteins in our model are highly successful under simulated adaptive conflict. Inspired by these model predictions, we developed a method to identify real proteins in the PDB with bridge-like properties, and have verified a clear bi-stability gradient for a series of mutants studied by Alexander et al. (Proc Nat Acad Sci USA 2009, 106:21149–21154) that connect two sequences that fold uniquely into two different native structures via a bridge-like intermediate mutant sequence. Based on these findings, new testable predictions for future studies on protein bi-stability and evolution are discussed. PMID:23028272

Predicting the graft survival for heart-lung transplantation patients: an integrated data mining methodology.

PubMed

Oztekin, Asil; Delen, Dursun; Kong, Zhenyu James

2009-12-01

Predicting the survival of heart-lung transplant patients has the potential to play a critical role in understanding and improving the matching procedure between the recipient and graft. Although voluminous data related to the transplantation procedures is being collected and stored, only a small subset of the predictive factors has been used in modeling heart-lung transplantation outcomes. The previous studies have mainly focused on applying statistical techniques to a small set of factors selected by the domain-experts in order to reveal the simple linear relationships between the factors and survival. The collection of methods known as 'data mining' offers significant advantages over conventional statistical techniques in dealing with the latter's limitations such as normality assumption of observations, independence of observations from each other, and linearity of the relationship between the observations and the output measure(s). There are statistical methods that overcome these limitations. Yet, they are computationally more expensive and do not provide fast and flexible solutions as do data mining techniques in large datasets. The main objective of this study is to improve the prediction of outcomes following combined heart-lung transplantation by proposing an integrated data-mining methodology. A large and feature-rich dataset (16,604 cases with 283 variables) is used to (1) develop machine learning based predictive models and (2) extract the most important predictive factors. Then, using three different variable selection methods, namely, (i) machine learning methods driven variables-using decision trees, neural networks, logistic regression, (ii) the literature review-based expert-defined variables, and (iii) common sense-based interaction variables, a consolidated set of factors is generated and used to develop Cox regression models for heart-lung graft survival. The predictive models' performance in terms of 10-fold cross-validation accuracy rates for two multi-imputed datasets ranged from 79% to 86% for neural networks, from 78% to 86% for logistic regression, and from 71% to 79% for decision trees. The results indicate that the proposed integrated data mining methodology using Cox hazard models better predicted the graft survival with different variables than the conventional approaches commonly used in the literature. This result is validated by the comparison of the corresponding Gains charts for our proposed methodology and the literature review based Cox results, and by the comparison of Akaike information criteria (AIC) values received from each. Data mining-based methodology proposed in this study reveals that there are undiscovered relationships (i.e. interactions of the existing variables) among the survival-related variables, which helps better predict the survival of the heart-lung transplants. It also brings a different set of variables into the scene to be evaluated by the domain-experts and be considered prior to the organ transplantation.

Thermal, Structural, and Optical Analysis of a Balloon-Based Imaging System

NASA Astrophysics Data System (ADS)

Borden, Michael; Lewis, Derek; Ochoa, Hared; Jones-Wilson, Laura; Susca, Sara; Porter, Michael; Massey, Richard; Clark, Paul; Netterfield, Barth

2017-03-01

The Subarcsecond Telescope And BaLloon Experiment, STABLE, is the fine stage of a guidance system for a high-altitude ballooning platform designed to demonstrate subarcsecond pointing stability over one minute using relatively dim guide stars in the visible spectrum. The STABLE system uses an attitude rate sensor and the motion of the guide star on a detector to control a Fast Steering Mirror to stabilize the image. The characteristics of the thermal-optical-mechanical elements in the system directly affect the quality of the point-spread function of the guide star on the detector, so a series of thermal, structural, and optical models were built to simulate system performance and ultimately inform the final pointing stability predictions. This paper describes the modeling techniques employed in each of these subsystems. The results from those models are discussed in detail, highlighting the development of the worst-case cold and hot cases, the optical metrics generated from the finite element model, and the expected STABLE residual wavefront error and decenter. Finally, the paper concludes with the predicted sensitivities in the STABLE system, which show that thermal deadbanding, structural pre-loading, and self-deflection under different loading conditions, and the speed of individual optical elements were particularly important to the resulting STABLE optical performance.

Behavioral Changes Predicting Temporal Changes in Perceived Popular Status

PubMed Central

Bowker, Julie C.; Rubin, Kenneth H.; Buskirk-Cohen, Alison; Rose-Krasnor, Linda; Booth-LaForce, Cathryn

2009-01-01

The primary objectives of this investigation were to determine the extent to which young adolescents are stable in high perceived popular status across the middle school transition and to examine whether changes in social behaviors predict the stability, gain, and loss of perceived popular status after the transition. The sample included 672 young adolescents (323 boys) who completed peer-nomination assessments of social behavior and perceived popularity at the end of elementary school (5th grade) and the beginning of middle school (6th grade). Findings indicated that 62 percent of perceived popular adolescents remained stable in their high popular status across the middle school transition. Multinomial logistic regression analyses revealed that a combination of aggression and arrogance/conceit was associated with stable and newly-gained perceived popular status after the middle school transition. Taken together, findings highlight the significance of contextual and temporal changes in adolescents’ perceived popular status. PMID:20209113

Molybdenum-titanium phase diagram evaluated from ab initio calculations

NASA Astrophysics Data System (ADS)

Barzilai, Shmuel; Toher, Cormac; Curtarolo, Stefano; Levy, Ohad

2017-07-01

The design of next generation β -type titanium implants requires detailed knowledge of the relevant stable and metastable phases at temperatures where metallurgical heat treatments can be performed. Recently, a standard specification for surgical implant applications was established for Mo-Ti alloys. However, the thermodynamic properties of this binary system are not well known and two conflicting descriptions of the β -phase stability have been presented in the literature. In this study, we use ab initio calculations to investigate the Mo-Ti phase diagram. These calculations predict that the β phase is stable over a wide concentration range, in qualitative agreement with one of the reported phase diagrams. In addition, they predict stoichiometric compounds, stable at temperatures below 300 ∘C , which have not yet been detected by experiments. The resulting solvus, which defines the transition to the β -phase solid solution, therefore occurs at lower temperatures and is more complex than previously anticipated.

Variation of δ2H, δ18O & δ13C in crude palm oil from different regions in Malaysia: Potential of stable isotope signatures as a key traceability parameter.

PubMed

Muhammad, Syahidah Akmal; Seow, Eng-Keng; Mohd Omar, A K; Rodhi, Ainolsyakira Mohd; Mat Hassan, Hasnuri; Lalung, Japareng; Lee, Sze-Chi; Ibrahim, Baharudin

2018-01-01

A total of 33 crude palm oil samples were randomly collected from different regions in Malaysia. Stable carbon isotopic composition (δ 13 C) was determined using Flash 2000 elemental analyzer while hydrogen and oxygen isotopic compositions (δ 2 H and δ 18 O) were analyzed by Thermo Finnigan TC/EA, wherein both instruments were coupled to an isotope ratio mass spectrometer. The bulk δ 2 H, δ 18 O and δ 13 C of the samples were analyzed by Hierarchical Cluster Analysis (HCA), Principal Component Analysis (PCA) and Orthogonal Partial Least Square-Discriminant Analysis (OPLS-DA). Unsupervised HCA and PCA methods have demonstrated that crude palm oil samples were grouped into clusters according to respective state. A predictive model was constructed by supervised OPLS-DA with good predictive power of 52.60%. Robustness of the predictive model was validated with overall accuracy of 71.43%. Blind test samples were correctly assigned to their respective cluster except for samples from southern region. δ 18 O was proposed as the promising discriminatory marker for discerning crude palm oil samples obtained from different regions. Stable isotopes profile was proven to be useful for origin traceability of crude palm oil samples at a narrower geographical area, i.e. based on regions in Malaysia. Predictive power and accuracy of the predictive model was expected to improve with the increase in sample size. Conclusively, the results in this study has fulfilled the main objective of this work where the simple approach of combining stable isotope analysis with chemometrics can be used to discriminate crude palm oil samples obtained from different regions in Malaysia. Overall, this study shows the feasibility of this approach to be used as a traceability assessment of crude palm oils. Copyright © 2017 The Chartered Society of Forensic Sciences. Published by Elsevier B.V. All rights reserved.

Predicting rates of isotopic turnover across the animal kingdom: a synthesis of existing data.

PubMed

Thomas, Stephen M; Crowther, Thomas W

2015-05-01

The stable isotopes of carbon ((12)C, (13)C) and nitrogen ((14)N, (15)N) represent powerful tools in food web ecology, providing a wide range of dietary information in animal consumers. However, identifying the temporal window over which a consumer's isotopic signature reflects its diet requires an understanding of elemental incorporation, a process that varies from days to years across species and tissue types. Though theory predicts body size and temperature are likely to control incorporation rates, this has not been tested empirically across a morphologically and phylogenetically diverse range of taxa. Readily available estimates of this relationship would, however, aid in the design of stable isotope food web investigations and improve the interpretation of isotopic data collected from natural systems. Using literature-derived turnover estimates from animal species ranging in size from 1 mg to 2000 kg, we develop a predictive tool for stable isotope ecologists, allowing for estimation of incorporation rates in the structural tissues of entirely novel taxa. In keeping with metabolic scaling theory, we show that isotopic turnover rates of carbon and nitrogen in whole organisms and muscle tissue scale allometrically with body mass raised approximately to the power -0.19, an effect modulated by body temperature. This relationship did not, however, apply to incorporation rates in splanchnic tissues, which were instead dependent on the thermoregulation tactic employed by an organism, being considerably faster in endotherms than ectotherms. We believe the predictive turnover equations we provide can improve the design of experiments and interpretation of results obtained in future stable isotopic food web studies. © 2014 The Authors. Journal of Animal Ecology © 2014 British Ecological Society.

Maximum entropy approach to fuzzy control

NASA Technical Reports Server (NTRS)

Ramer, Arthur; Kreinovich, Vladik YA.

1992-01-01

For the same expert knowledge, if one uses different &- and V-operations in a fuzzy control methodology, one ends up with different control strategies. Each choice of these operations restricts the set of possible control strategies. Since a wrong choice can lead to a low quality control, it is reasonable to try to loose as few possibilities as possible. This idea is formalized and it is shown that it leads to the choice of min(a + b,1) for V and min(a,b) for &. This choice was tried on NASA Shuttle simulator; it leads to a maximally stable control.

"Ipsilateral, high, single-hand, sideways"-Ruijin rule for camera assistant in uniportal video-assisted thoracoscopic surgery.

PubMed

Gao, Taotao; Xiang, Jie; Jin, Runsen; Zhang, Yajie; Wu, Han; Li, Hecheng

2016-10-01

Camera assistant plays a very important role in uniportal video-assisted thoracoscopic surgery (VATS), who acts as the eye of the surgeon, providing the VATS team with a stable and clear operating view. Thus, a good assistant should cooperate with surgeon and manipulate the camera expertly, to ensure eye-hand coordination. We have performed more than 100 uniportal VATS in the Department Of Thoracic Surgery in Ruijin Hospital. Based on our experiences, we summarized the method of holding camera, known as "ipsilateral, high, single-hand, sideways", which largely improves the comfort and fluency of surgery.

Does Expert Advice Improve Educational Choice?

PubMed Central

2015-01-01

This paper reports evidence that an individual meeting with a study counselor at high school significantly improves the quality of choice of tertiary educational field, as self-assessed 18 months after graduation from college. To address endogeneity, we explore the variation in study counseling practices between schools as an instrumental variable (IV). Following careful scrutiny of the validity of the IV, our results indicate a significant and positive influence of study counseling on the quality of educational choice, foremost among males and those with low educated parents. The overall result is stable across a number of robustness checks. PMID:26692388

Defining landscape resistance values in least-cost connectivity models for the invasive grey squirrel: a comparison of approaches using expert-opinion and habitat suitability modelling.

PubMed

Stevenson-Holt, Claire D; Watts, Kevin; Bellamy, Chloe C; Nevin, Owen T; Ramsey, Andrew D

2014-01-01

Least-cost models are widely used to study the functional connectivity of habitat within a varied landscape matrix. A critical step in the process is identifying resistance values for each land cover based upon the facilitating or impeding impact on species movement. Ideally resistance values would be parameterised with empirical data, but due to a shortage of such information, expert-opinion is often used. However, the use of expert-opinion is seen as subjective, human-centric and unreliable. This study derived resistance values from grey squirrel habitat suitability models (HSM) in order to compare the utility and validity of this approach with more traditional, expert-led methods. Models were built and tested with MaxEnt, using squirrel presence records and a categorical land cover map for Cumbria, UK. Predictions on the likelihood of squirrel occurrence within each land cover type were inverted, providing resistance values which were used to parameterise a least-cost model. The resulting habitat networks were measured and compared to those derived from a least-cost model built with previously collated information from experts. The expert-derived and HSM-inferred least-cost networks differ in precision. The HSM-informed networks were smaller and more fragmented because of the higher resistance values attributed to most habitats. These results are discussed in relation to the applicability of both approaches for conservation and management objectives, providing guidance to researchers and practitioners attempting to apply and interpret a least-cost approach to mapping ecological networks.

A new intelligent electronic nose system for measuring and analysing livestock and poultry farm odours.

PubMed

Pan, Leilei; Yang, Simon X

2007-12-01

This paper introduces a new portable intelligent electronic nose system developed especially for measuring and analysing livestock and poultry farm odours. It can be used in both laboratory and field. The sensor array of the proposed electronic nose consists of 14 gas sensors, a humidity sensor, and a temperature sensor. The gas sensors were especially selected for the main compounds from the livestock farm odours. An expert system called "Odour Expert" was developed to support researchers' and farmers' decision making on odour control strategies for livestock and poultry operations. "Odour Expert" utilises several advanced artificial intelligence technologies tailored to livestock and poultry farm odours. It can provide more advanced odour analysis than existing commercially available products. In addition, a rank of odour generation factors is provided, which refines the focus of odour control research. Field experiments were conducted downwind from the barns on 14 livestock and poultry farms. Experimental results show that the predicted odour strengths by the electronic nose yield higher consistency in comparison to the perceived odour intensity by human panel. The "Odour Expert" is a useful tool for assisting farmers' odour management practises.

USA Track & Field Coaching Manual. USA Track & Field.

ERIC Educational Resources Information Center

USA Track and Field, Inc., Indianapolis, IN.

This book presents comprehensive, ready-to-apply information from 33 world-class coaches and experts about major track and field events for high school and college coaches. The volume features proven predictive testing procedures; detailed event-specific technique instruction; carefully crafted training programs; and preparation and performance…

Field Testing Of An Expert Model: Can The Model Predict Habitat Potential For Saltmarsh Birds?

EPA Science Inventory

Salt marshes are valuable resources, which provide numerous ecosystem services, including flood protection, fish nursery habitat, and nesting habitat for a number of threatened and endangered species. At the present time, due primarily to coastal development and sea level rise,...

Prediction of crude protein and oil content of soybeans using Raman spectroscopy

USDA-ARS?s Scientific Manuscript database

While conventional chemical analysis methods for food nutrients require time-consuming, labor-intensive, and invasive pretreatment procedures, Raman spectroscopy can be used to measure a variety of food components rapidly and non-destructively and does not require supervision from experts. The purpo...

School Administration.

ERIC Educational Resources Information Center

Bete, Tim, Ed.

1998-01-01

Presents predictions from four administration experts on what the future holds for U.S. schools. Questions addressed concern the following: will schools ever include pre-K programs; will standardized testing disappear; will high schools adopt the flexible, independent study model; will K-12 education ever be run by big business, and will…

Mapping the Climate of Puerto Rico, Vieques and Culebra.

Treesearch

CHRISTOPHER DALY; E. H. HELMER; MAYA QUINONES

2003-01-01

Spatially explicit climate data contribute to watershed resource management, mapping vegetation type with satellite imagery, mapping present and hypothetical future ecological zones, and predicting species distributions. The regression based Parameter-elevation Regressions on Independent Slopes Model (PRISM) uses spatial data sets, a knowledge base and expert...

Viewing Knowledge Bases as Qualitative Models.

ERIC Educational Resources Information Center

Clancey, William J.

The concept of a qualitative model provides a unifying perspective for understanding how expert systems differ from conventional programs. Knowledge bases contain qualitative models of systems in the world, that is, primarily non-numeric descriptions that provide a basis for explaining and predicting behavior and formulating action plans. The…

Cost Risk Analysis Based on Perception of the Engineering Process

NASA Technical Reports Server (NTRS)

Dean, Edwin B.; Wood, Darrell A.; Moore, Arlene A.; Bogart, Edward H.

1986-01-01

In most cost estimating applications at the NASA Langley Research Center (LaRC), it is desirable to present predicted cost as a range of possible costs rather than a single predicted cost. A cost risk analysis generates a range of cost for a project and assigns a probability level to each cost value in the range. Constructing a cost risk curve requires a good estimate of the expected cost of a project. It must also include a good estimate of expected variance of the cost. Many cost risk analyses are based upon an expert's knowledge of the cost of similar projects in the past. In a common scenario, a manager or engineer, asked to estimate the cost of a project in his area of expertise, will gather historical cost data from a similar completed project. The cost of the completed project is adjusted using the perceived technical and economic differences between the two projects. This allows errors from at least three sources. The historical cost data may be in error by some unknown amount. The managers' evaluation of the new project and its similarity to the old project may be in error. The factors used to adjust the cost of the old project may not correctly reflect the differences. Some risk analyses are based on untested hypotheses about the form of the statistical distribution that underlies the distribution of possible cost. The usual problem is not just to come up with an estimate of the cost of a project, but to predict the range of values into which the cost may fall and with what level of confidence the prediction is made. Risk analysis techniques that assume the shape of the underlying cost distribution and derive the risk curve from a single estimate plus and minus some amount usually fail to take into account the actual magnitude of the uncertainty in cost due to technical factors in the project itself. This paper addresses a cost risk method that is based on parametric estimates of the technical factors involved in the project being costed. The engineering process parameters are elicited from the engineer/expert on the project and are based on that expert's technical knowledge. These are converted by a parametric cost model into a cost estimate. The method discussed makes no assumptions about the distribution underlying the distribution of possible costs, and is not tied to the analysis of previous projects, except through the expert calibrations performed by the parametric cost analyst.

Potential predictability of a Colombian river flow

NASA Astrophysics Data System (ADS)

Córdoba-Machado, Samir; Palomino-Lemus, Reiner; Quishpe-Vásquez, César; García-Valdecasas-Ojeda, Matilde; Raquel Gámiz-Fortis, Sonia; Castro-Díez, Yolanda; Jesús Esteban-Parra, María

2017-04-01

In this study the predictability of an important Colombian river (Cauca) has been analysed based on the use of climatic variables as potential predictors. Cauca River is considered one of the most important rivers of Colombia because its basin supports important productive activities related with the agriculture, such as the production of coffee or sugar. Potential relationships between the Cauca River seasonal streamflow anomalies and different climatic variables such as sea surface temperature (SST), precipitation (Pt), temperature over land (Tm) and soil water (Sw) have been analysed for the period 1949-2009. For this end, moving correlation analysis of 30 years have been carried out for lags from one to four seasons for the global SST, and from one to two seasons for South America Pt, Tm and Sw. Also, the stability of the significant correlations have been also studied, identifying the regions used as potential predictors of streamflow. Finally, in order to establish a prediction scheme based on the previous stable correlations, a Principal Component Analysis (PCA) applied on the potential predictor regions has been carried out in order to obtain a representative time series for each predictor field. Significant and stable correlations between the seasonal streamflow and the tropical Pacific SST (El Niño region) are found for lags from one to four (one-year) season. Additionally, some regions in the Indian and Atlantic Oceans also show significant and stable correlations at different lags, highlighting the importance that exerts the Atlantic SST on the hydrology of Colombia. Also significant and stable correlations are found with the Pt, Tm and Sw for some regions over South America, at lags of one and two seasons. The prediction of Cauca seasonal streamflow based on this scheme shows an acceptable skill and represents a relative improvement compared with the predictability obtained using the teleconnection indices associated with El Niño. Keywords: Streamflow, predictability, Cauca, Colombia. Acknowledgements: This work has been financed by the projects P11-RNM-7941 (Junta de Andalucía-Spain) and CGL2013-48539-R (MINECO-Spain, FEDER).

Recent advances in the management of chronic stable angina I: Approach to the patient, diagnosis, pathophysiology, risk stratification, and gender disparities

PubMed Central

Kones, Richard

2010-01-01

The potential importance of both prevention and personal responsibility in controlling heart disease, the leading cause of death in the USA and elsewhere, has attracted renewed attention. Coronary artery disease is preventable, using relatively simple and inexpensive lifestyle changes. The inexorable rise in the prevalence of obesity, diabetes, dyslipidemia, and hypertension, often in the risk cluster known as the metabolic syndrome, drives the ever-increasing incidence of heart disease. Population-wide improvements in personal health habits appear to be a fundamental, evidence based public health measure, yet numerous barriers prevent implementation. A common symptom in patients with coronary artery disease, classical angina refers to the typical chest pressure or discomfort that results when myocardial oxygen demand rises and coronary blood flow is reduced by fixed, atherosclerotic, obstructive lesions. Different forms of angina and diagnosis, with a short description of the significance of pain and silent ischemia, are discussed in this review. The well accepted concept of myocardial oxygen imbalance in the genesis of angina is presented with new data about clinical pathology of stable angina and acute coronary syndromes. The roles of stress electrocardiography and stress myocardial perfusion scintigraphic imaging are reviewed, along with the information these tests provide about risk and prognosis. Finally, the current status of gender disparities in heart disease is summarized. Enhanced risk stratification and identification of patients in whom procedures will meaningfully change management is an ongoing quest. Current guidelines emphasize efficient triage of patients with suspected coronary artery disease. Many experts believe the predictive value of current decision protocols for coronary artery disease still needs improvement in order to optimize outcomes, yet avoid unnecessary coronary angiograms and radiation exposure. Coronary angiography remains the gold standard in the diagnosis of coronary artery obstructive disease. Part II of this two part series will address anti-ischemic therapies, new agents, cardiovascular risk reduction, options to treat refractory angina, and revascularization. PMID:20730020

Recent advances in the management of chronic stable angina I: approach to the patient, diagnosis, pathophysiology, risk stratification, and gender disparities.

PubMed

Kones, Richard

2010-08-09

The potential importance of both prevention and personal responsibility in controlling heart disease, the leading cause of death in the USA and elsewhere, has attracted renewed attention. Coronary artery disease is preventable, using relatively simple and inexpensive lifestyle changes. The inexorable rise in the prevalence of obesity, diabetes, dyslipidemia, and hypertension, often in the risk cluster known as the metabolic syndrome, drives the ever-increasing incidence of heart disease. Population-wide improvements in personal health habits appear to be a fundamental, evidence based public health measure, yet numerous barriers prevent implementation. A common symptom in patients with coronary artery disease, classical angina refers to the typical chest pressure or discomfort that results when myocardial oxygen demand rises and coronary blood flow is reduced by fixed, atherosclerotic, obstructive lesions. Different forms of angina and diagnosis, with a short description of the significance of pain and silent ischemia, are discussed in this review. The well accepted concept of myocardial oxygen imbalance in the genesis of angina is presented with new data about clinical pathology of stable angina and acute coronary syndromes. The roles of stress electrocardiography and stress myocardial perfusion scintigraphic imaging are reviewed, along with the information these tests provide about risk and prognosis. Finally, the current status of gender disparities in heart disease is summarized. Enhanced risk stratification and identification of patients in whom procedures will meaningfully change management is an ongoing quest. Current guidelines emphasize efficient triage of patients with suspected coronary artery disease. Many experts believe the predictive value of current decision protocols for coronary artery disease still needs improvement in order to optimize outcomes, yet avoid unnecessary coronary angiograms and radiation exposure. Coronary angiography remains the gold standard in the diagnosis of coronary artery obstructive disease. Part II of this two part series will address anti-ischemic therapies, new agents, cardiovascular risk reduction, options to treat refractory angina, and revascularization.

Use of the Violence Risk Scale-Sexual Offender Version and the Stable 2007 to assess dynamic sexual violence risk in a sample of treated sexual offenders.

PubMed

Sowden, Justina N; Olver, Mark E

2017-03-01

The present study provides an examination of dynamic sexual violence risk featuring the Stable-2007 (Hanson, Harris, Scott, & Helmus, 2007) and the Violence Risk Scale-Sexual Offender version (VRS-SO; Wong, Olver, Nicholaichuk, & Gordon, 2003) in a Canadian sample of 180 federally incarcerated sexual offenders who attended a high-intensity sexual offender treatment program. Archival pretreatment and posttreatment ratings were completed on the VRS-SO and Stable-2007, and recidivism data were obtained from official criminal records, with the sample being followed up approximately 10 years postrelease. VRS-SO pre- and posttreatment dynamic scores demonstrated significant predictive accuracy for sexual, nonsexual violent, any violent (including sexual), and general recidivism, while Stable-2007 pre- and posttreatment scores were significantly associated with the latter 3 outcomes; these associations were maintained after controlling for the Static-99R (Helmus, Thornton, Hanson, & Babchishin, 2012). Finally, significant pre-post differences, amounting to approximately three quarters of a standard deviation, were found on Stable-2007 and VRS-SO scores. VRS-SO change scores were significantly associated with reductions in nonsexual violent, any violent, and general recidivism (but not sexual recidivism) after controlling for baseline risk or pretreatment score, while Stable-2007 change scores did not significantly predict reductions in any recidivism outcomes. Applications of these tools within the context of dynamic sexual violence risk assessment incorporating the use of change information are discussed. (PsycINFO Database Record (c) 2017 APA, all rights reserved).

Comment on "Multiyear prediction of monthly mean Atlantic Meridional Overturning Circulation at 26.5°N".

PubMed

Vecchi, Gabriel A; Msadek, Rym; Delworth, Thomas L; Dixon, Keith W; Guilyardi, Eric; Hawkins, Ed; Karspeck, Alicia R; Mignot, Juliette; Robson, Jon; Rosati, Anthony; Zhang, Rong

2012-11-02

Matei et al. (Reports, 6 January 2012, p. 76) claim to show skillful multiyear predictions of the Atlantic Meridional Overturning Circulation (AMOC). However, these claims are not justified, primarily because the predictions of AMOC transport do not outperform simple reference forecasts based on climatological annual cycles. Accordingly, there is no justification for the "confident" prediction of a stable AMOC through 2014.

Mechanical Isolation of Highly Stable Antimonene under Ambient Conditions.

PubMed

Ares, Pablo; Aguilar-Galindo, Fernando; Rodríguez-San-Miguel, David; Aldave, Diego A; Díaz-Tendero, Sergio; Alcamí, Manuel; Martín, Fernando; Gómez-Herrero, Julio; Zamora, Félix

2016-08-01

Antimonene fabricated by mechanical exfoliation is highly stable under atmospheric conditions over periods of months and even when immersed in water. Density functional theory confirms the experiments and predicts an electronic gap of ≈1 eV. These results highlight the use of antimonene for optoelectronics applications. © 2016 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

Patterns and Predictors of Language and Literacy Abilities 4-10 Years in the Longitudinal Study of Australian Children

PubMed Central

Zubrick, Stephen R.; Taylor, Catherine L.; Christensen, Daniel

2015-01-01

Aims Oral language is the foundation of literacy. Naturally, policies and practices to promote children’s literacy begin in early childhood and have a strong focus on developing children’s oral language, especially for children with known risk factors for low language ability. The underlying assumption is that children’s progress along the oral to literate continuum is stable and predictable, such that low language ability foretells low literacy ability. This study investigated patterns and predictors of children’s oral language and literacy abilities at 4, 6, 8 and 10 years. The study sample comprised 2,316 to 2,792 children from the first nationally representative Longitudinal Study of Australian Children (LSAC). Six developmental patterns were observed, a stable middle-high pattern, a stable low pattern, an improving pattern, a declining pattern, a fluctuating low pattern, and a fluctuating middle-high pattern. Most children (69%) fit a stable middle-high pattern. By contrast, less than 1% of children fit a stable low pattern. These results challenged the view that children’s progress along the oral to literate continuum is stable and predictable. Findings Multivariate logistic regression was used to investigate risks for low literacy ability at 10 years and sensitivity-specificity analysis was used to examine the predictive utility of the multivariate model. Predictors were modelled as risk variables with the lowest level of risk as the reference category. In the multivariate model, substantial risks for low literacy ability at 10 years, in order of descending magnitude, were: low school readiness, Aboriginal and/or Torres Strait Islander status and low language ability at 8 years. Moderate risks were high temperamental reactivity, low language ability at 4 years, and low language ability at 6 years. The following risk factors were not statistically significant in the multivariate model: Low maternal consistency, low family income, health care card, child not read to at home, maternal smoking, maternal education, family structure, temperamental persistence, and socio-economic area disadvantage. The results of the sensitivity-specificity analysis showed that a well-fitted multivariate model featuring risks of substantive magnitude did not do particularly well in predicting low literacy ability at 10 years. PMID:26352436

Use of QSARs in international decision-making frameworks to predict health effects of chemical substances.

PubMed Central

Cronin, Mark T D; Jaworska, Joanna S; Walker, John D; Comber, Michael H I; Watts, Christopher D; Worth, Andrew P

2003-01-01

This article is a review of the use of quantitative (and qualitative) structure-activity relationships (QSARs and SARs) by regulatory agencies and authorities to predict acute toxicity, mutagenicity, carcinogenicity, and other health effects. A number of SAR and QSAR applications, by regulatory agencies and authorities, are reviewed. These include the use of simple QSAR analyses, as well as the use of multivariate QSARs, and a number of different expert system approaches. PMID:12896862

Computational intelligence in earth sciences and environmental applications: issues and challenges.

PubMed

Cherkassky, V; Krasnopolsky, V; Solomatine, D P; Valdes, J

2006-03-01

This paper introduces a generic theoretical framework for predictive learning, and relates it to data-driven and learning applications in earth and environmental sciences. The issues of data quality, selection of the error function, incorporation of the predictive learning methods into the existing modeling frameworks, expert knowledge, model uncertainty, and other application-domain specific problems are discussed. A brief overview of the papers in the Special Issue is provided, followed by discussion of open issues and directions for future research.

Detecting, anticipating, and predicting critical transitions in spatially extended systems.

PubMed

Kwasniok, Frank

2018-03-01

A data-driven linear framework for detecting, anticipating, and predicting incipient bifurcations in spatially extended systems based on principal oscillation pattern (POP) analysis is discussed. The dynamics are assumed to be governed by a system of linear stochastic differential equations which is estimated from the data. The principal modes of the system together with corresponding decay or growth rates and oscillation frequencies are extracted as the eigenvectors and eigenvalues of the system matrix. The method can be applied to stationary datasets to identify the least stable modes and assess the proximity to instability; it can also be applied to nonstationary datasets using a sliding window approach to track the changing eigenvalues and eigenvectors of the system. As a further step, a genuinely nonstationary POP analysis is introduced. Here, the system matrix of the linear stochastic model is time-dependent, allowing for extrapolation and prediction of instabilities beyond the learning data window. The methods are demonstrated and explored using the one-dimensional Swift-Hohenberg equation as an example, focusing on the dynamics of stochastic fluctuations around the homogeneous stable state prior to the first bifurcation. The POP-based techniques are able to extract and track the least stable eigenvalues and eigenvectors of the system; the nonstationary POP analysis successfully predicts the timing of the first instability and the unstable mode well beyond the learning data window.

Characteristics of Socially Successful Elementary School-Aged Children with Autism

PubMed Central

Locke, Jill; Williams, Justin; Shih, Wendy; Kasari, Connie

2016-01-01

Background The extant literature demonstrates that children with autism spectrum disorder (ASD) often have difficulty interacting and socially connecting with typically developing classmates. However, some children with ASD have social outcomes that are consistent with their typically developing counterparts. Little is known about this subgroup of children with ASD. This study examined the stable (unlikely to change) and malleable (changeable) characteristics of socially successful children with ASD. Methods This study used baseline data from three intervention studies performed in public schools in the Southwestern United States. A total of 148 elementary-aged children with ASD in 130 classrooms in 47 public schools participated. Measures of playground peer engagement and social network salience (inclusion in informal peer groups) were obtained. Results The results demonstrated that a number of malleable factors significantly predicted playground peer engagement (class size, autism symptom severity, peer connections) and social network salience (autism symptom severity, peer connections, received friendships). In addition, age was the only stable factor that significantly predicted social network salience. Interestingly, two malleable (i.e., peer connections and received friendships) and no stable factors (i.e., age, IQ, sex) predicted overall social success (e.g., high playground peer engagement and social network salience) in children with ASD. Conclusions School-based interventions should address malleable factors such as the number of peer connections and received friendships that predict the best social outcomes for children with ASD. PMID:27620949

Detecting, anticipating, and predicting critical transitions in spatially extended systems

NASA Astrophysics Data System (ADS)

Kwasniok, Frank

2018-03-01

A data-driven linear framework for detecting, anticipating, and predicting incipient bifurcations in spatially extended systems based on principal oscillation pattern (POP) analysis is discussed. The dynamics are assumed to be governed by a system of linear stochastic differential equations which is estimated from the data. The principal modes of the system together with corresponding decay or growth rates and oscillation frequencies are extracted as the eigenvectors and eigenvalues of the system matrix. The method can be applied to stationary datasets to identify the least stable modes and assess the proximity to instability; it can also be applied to nonstationary datasets using a sliding window approach to track the changing eigenvalues and eigenvectors of the system. As a further step, a genuinely nonstationary POP analysis is introduced. Here, the system matrix of the linear stochastic model is time-dependent, allowing for extrapolation and prediction of instabilities beyond the learning data window. The methods are demonstrated and explored using the one-dimensional Swift-Hohenberg equation as an example, focusing on the dynamics of stochastic fluctuations around the homogeneous stable state prior to the first bifurcation. The POP-based techniques are able to extract and track the least stable eigenvalues and eigenvectors of the system; the nonstationary POP analysis successfully predicts the timing of the first instability and the unstable mode well beyond the learning data window.

Theoretical prediction of novel ultrafine nanowires formed by Si12C12 cage-like clusters

NASA Astrophysics Data System (ADS)

Yong, Yongliang; Song, Bin; He, Pimo

2014-02-01

Using density functional theory calculations, we predict that novel SiC ultrafine nanowires can be produced via the coalescence of stable Si12C12 clusters. For the isolated Si12C12 clusters, we find that the cage-like structure with a distinct segregation between Si and C atoms is energetically more favourable than the fullerene-like structure with alternating Si-C bonds. Via the coalescence of Si12C12 clusters, three novel stable nanowires have been characterised. The band structure reveals that these nanowires are semiconductors with narrow gap, indicating that they may be used as infrared detectors and thermoelectrics.

Evidence of Microbial Regulation of Biogeochemical Cycles from a Study on Methane Flux and Land Use Change

PubMed Central

Nazaries, Loïc; Pan, Yao; Bodrossy, Levente; Baggs, Elizabeth M.; Millard, Peter; Murrell, J. Colin

2013-01-01

Microbes play an essential role in ecosystem functions, including carrying out biogeochemical cycles, but are currently considered a black box in predictive models and all global biodiversity debates. This is due to (i) perceived temporal and spatial variations in microbial communities and (ii) lack of ecological theory explaining how microbes regulate ecosystem functions. Providing evidence of the microbial regulation of biogeochemical cycles is key for predicting ecosystem functions, including greenhouse gas fluxes, under current and future climate scenarios. Using functional measures, stable-isotope probing, and molecular methods, we show that microbial (community diversity and function) response to land use change is stable over time. We investigated the change in net methane flux and associated microbial communities due to afforestation of bog, grassland, and moorland. Afforestation resulted in the stable and consistent enhancement in sink of atmospheric methane at all sites. This change in function was linked to a niche-specific separation of microbial communities (methanotrophs). The results suggest that ecological theories developed for macroecology may explain the microbial regulation of the methane cycle. Our findings provide support for the explicit consideration of microbial data in ecosystem/climate models to improve predictions of biogeochemical cycles. PMID:23624469

A nomogram for predicting complications in patients with solid tumours and seemingly stable febrile neutropenia

PubMed Central

Fonseca, Paula Jiménez; Carmona-Bayonas, Alberto; García, Ignacio Matos; Marcos, Rosana; Castañón, Eduardo; Antonio, Maite; Font, Carme; Biosca, Mercè; Blasco, Ana; Lozano, Rebeca; Ramchandani, Avinash; Beato, Carmen; de Castro, Eva Martínez; Espinosa, Javier; Martínez-García, Jerónimo; Ghanem, Ismael; Cubero, Jorge Hernando; Manrique, Isabel Aragón; Navalón, Francisco García; Sevillano, Elena; Manzano, Aránzazu; Virizuela, Juan; Garrido, Marcelo; Mondéjar, Rebeca; Arcusa, María Ángeles; Bonilla, Yaiza; Pérez, Quionia; Gallardo, Elena; del Carmen Soriano, Maria; Cardona, Mercè; Lasheras, Fernando Sánchez; Cruz, Juan Jesús; Ayala, Francisco

2016-01-01

Background: We sought to develop and externally validate a nomogram and web-based calculator to individually predict the development of serious complications in seemingly stable adult patients with solid tumours and episodes of febrile neutropenia (FN). Patients and methods: The data from the FINITE study (n=1133) and University of Salamanca Hospital (USH) FN registry (n=296) were used to develop and validate this tool. The main eligibility criterion was the presence of apparent clinical stability, defined as events without acute organ dysfunction, abnormal vital signs, or major infections. Discriminatory ability was measured as the concordance index and stratification into risk groups. Results: The rate of infection-related complications in the FINITE and USH series was 13.4% and 18.6%, respectively. The nomogram used the following covariates: Eastern Cooperative Group (ECOG) Performance Status ⩾2, chronic obstructive pulmonary disease, chronic cardiovascular disease, mucositis of grade ⩾2 (National Cancer Institute Common Toxicity Criteria), monocytes <200/mm3, and stress-induced hyperglycaemia. The nomogram predictions appeared to be well calibrated in both data sets (Hosmer–Lemeshow test, P>0.1). The concordance index was 0.855 and 0.831 in each series. Risk group stratification revealed a significant distinction in the proportion of complications. With a ⩾116-point cutoff, the nomogram yielded the following prognostic indices in the USH registry validation series: 66% sensitivity, 83% specificity, 3.88 positive likelihood ratio, 48% positive predictive value, and 91% negative predictive value. Conclusions: We have developed and externally validated a nomogram and web calculator to predict serious complications that can potentially impact decision-making in patients with seemingly stable FN. PMID:27187687

Predicting the Occurrence of Hypotension in Stable Patients With Nonvariceal Upper Gastrointestinal Bleeding: Point-of-Care Lactate Testing.

PubMed

Ko, Byuk Sung; Kim, Won Young; Ryoo, Seung Mok; Ahn, Shin; Sohn, Chang Hwan; Seo, Dong Woo; Lee, Yoon-Seon; Lim, Kyoung Soo; Jung, Hwoon-Yong

2015-11-01

It is difficult to assess risk in normotensive patients with upper gastrointestinal bleeding. The aim of this study was to evaluate whether the initial lactate value can predict the in-hospital occurrence of hypotension in stable patients with acute nonvariceal upper gastrointestinal bleeding. Retrospective, observational, single-center study. Emergency department of a tertiary-care, university-affiliated hospital during a 5-year period. Medical records of 3,489 patients with acute upper gastrointestinal bleeding who were normotensive at presentation to the emergency department. We analyzed the ability of point-of-care testing of lactate at emergency department admission to predict hypotension development (defined as systolic blood pressure <90 mm Hg) within 24 hours after emergency department admission. None. Of the 1,003 patients with acute nonvariceal upper gastrointestinal bleeding, 157 patients experienced hypotension within 24 hours. Lactate was independently associated with hypotension development (odds ratio, 1.6; 95% CI, 1.4-1.7), and the risk of hypotension significantly increased as the lactate increased from 2.5-4.9 mmol/L (odds ratio, 2.2) to 5.0-7.4 mmol/L (odds ratio, 4.0) and to greater than or equal to 7.5 mmol/L (odds ratio, 39.2) (p<0.001). Lactate elevation (≥2.5 mmol/L) was associated with 90% specificity and an 84% negative predictive value for hypotension development. When the lactate levels were greater than 5.0 mmol/L, the specificity and negative predictive value increased to 98% and 87%, respectively. Point-of-care testing of lactate can predict in-hospital occurrence of hypotension in stable patients with acute nonvariceal upper gastrointestinal bleeding. However, subsequently, prospective validate research will be required to clarify this.

Estimation of soil organic carbon in forests of the United States

NASA Astrophysics Data System (ADS)

Domke, G. M.; Perry, C. H.; Walters, B. F.; Woodall, C. W.; Nave, L. E.; Swanston, C.

2015-12-01

Soil organic carbon (SOC) is the largest terrestrial carbon (C) sink on earth and management of this pool is a critical component of global efforts to mitigate atmospheric C concentrations. Soil organic carbon is also a key indicator of soil quality as it affects essential biological, chemical, and physical soil functions such as nutrient cycling, water retention, and soil structure maintenance. Much of the SOC on earth is found in forest ecosystems and is thought to be relatively stable. That said, there is growing evidence that SOC may be sensitive to disturbance and global change drivers. In the United States (US), SOC in forests is monitored by the national forest inventory (NFI) conducted by the Forest Inventory and Analysis (FIA) program within the US Department of Agriculture, Forest Service. The FIA program currently uses SOC predictions based on SSURGO/STATSGO data to populate the NFI. Most of estimates of SOC in forests from the SSURGO/STATSGO data are based primarily upon expert opinion and lack systematic field observations. The FIA program has been consistently measuring soil attributes as part of the NFI since 2001 and has amassed an extensive inventory of SOC in forests in the conterminous US and coastal Alaska. Here we present estimates of SOC obtained using data from the NFI and International Soil Carbon Network and describe the modeling framework used to compile estimates for United Nations Framework Convention on Climate Change reporting.

Chemical properties of ground water and their corrosion and encrustation effects on wells

USGS Publications Warehouse

Barnes, Ivan; Clarke, Frank Eldridge

1969-01-01

Well waters in Egypt, Nigeria, and West Pakistan were studied for their chemical properties and corrosive or encrusting behavior. From the chemical composition of the waters, reaction states with reference to equilibrium were tested for 29 possible coexisting oxides, carbonates, sulfides, and elements. Of the 29 solids considered, only calcite, CaCO3, and ferric hydroxide, Fe(OH)3, showed any correlation with the corrosiveness of the waters to mild steel (iron metal). All 39 of the waters tested were out of equilibrium with iron metal, but those waters in equilibrium or supersaturated with both calcite and ferric hydroxide were the least corrosive. Supersaturation with other solid phases apparently was unrelated to corrosion. A number of solids may form surface deposits in wells and lead to decreased yields by fouling well intakes (screens and gravel packs) or increasing friction losses in casings. Calcite, CaCO3; ferric hydroxide, Fe(OH)3; magnetite, Fe3O4; siderite, FeCO3; hausmannite, Mn304 (tetragonal); manganese spinel, Mn3O4 (isometric); three iron sulfides mackinawite, FeS (tetragonal); greigite, Fe3S4 (isometric); and smythite, Fe3S4 (rhombohedral)-copper hydroxide, Co(OH)2; and manganese hydroxide, Mn(OH)2, were all at least tentatively identified in the deposits sampled. Of geochemical interest is the demonstration that simple stable equilibrium models fail in nearly every case to predict compositions of water yielded by the wells studied. Only one stable phase (calcite) was found to exhibit behavior approximately predictable from stable equilibrium considerations. No other stable phase was found to behave as would be predicted from equilibrium considerations. All the solids found to precipitate (except calcite) are metastable in that they are not the least soluble phases possible in the systems studied. In terms of metastable equilibrium, siderite and ferric hydroxide behave approximately as would be predicted from equilibrium considerations, but both are metastable and the presence of neither would be anticipated if only the most stable phases were considered. The behaviors of none of the other solids would be predictable from either stable or metastable equilibrium considerations. An unanswered problem raised by the study reported here is how, or by what paths, truly stable phases form if first precipitates are generally metastable.The utility of the findings in well design and operation is in no way impaired by the general lack of equilibrium. Conditions leading to either corrosion (which is related to lack of supersaturation with protective phases), or encrustation (supersaturation with phases that were found to precipitate), or both, apparently can be identified. The application of the methods described can be of great importance in developing unexploited ground-water resources in that certain practical problems can be identified before extensive well construction and unnecessary well failure.

Kansas Department of Transportation column expert : ultimate shear capacity of circular columns using the simplified modified compression field theory.

DOT National Transportation Integrated Search

2015-09-01

The importance of the analysis of circular columns to accurately predict their ultimate confined : capacity under shear-flexure-axial force interaction domain is recognized in light of the extreme load event : imposed by the current American Associat...

CORMIX2: AN EXPERT SYSTEM FOR HYDRODYNAMIC MIXING ZONE ANALYSIS OF CONVENTIONAL AND TOXIC MULTIPORT DIFFUSER DISCHARGES

EPA Science Inventory

CORMIX is a series of software systems for the analysis, prediction, and design of aqueous toxic or conventional pollutant discharges into watercourses, with emphasis on the geometry and dilution characteristics of the initial mixing zone. ubsystem CORMIX1 deals with submerged si...

Sensory Cues, Visualization and Physics Learning

ERIC Educational Resources Information Center

Reiner, Miriam

2009-01-01

Bodily manipulations, such as juggling, suggest a well-synchronized physical interaction as if the person were a physics expert. The juggler uses "knowledge" that is rooted in bodily experience, to interact with the environment. Such enacted bodily knowledge is powerful, efficient, predictive, and relates to sensory perception of the dynamics of…

The Perfect Learner: An Expert Debate on Learning Styles.

ERIC Educational Resources Information Center

Delahoussaye, Martin

2002-01-01

Presents a discussion of learning styles by Lynn Curry, Rick Daly, Ashley Fields, Peter Honey, David Kolb, Patrick O'Brien and Gary Salton. Addresses learning style theories, style predictability, whether to teach exclusively to one style, and ways to make use of learning styles in corporate settings. (Author/JOW)

25 Years Down the Line

ERIC Educational Resources Information Center

McLester, Susan

2005-01-01

In this final of three Special 25th Anniversary Reports, the authors attempt to paint a picture of what the future of education should, could, or might be. They asked readers, industry experts, authors, tech gurus and scientists, "What will "school" look like in the year 2030?" This compendium reflects their varied predictions,…

Diagnostic Accuracy of Chinese Medicine Diagnosis Scale of Phlegm and Blood Stasis Syndrome in Coronary Heart Disease: A Study Protocol.

PubMed

Liu, Xiao-Qi; Peng, Dan-Hong; Wang, Yan-Ping; Xie, Rong; Chen, Xin-Lin; Yu, Chun-Quan; Li, Xian-Tao

2018-05-03

Phlegm and blood stasis syndrome (PBSS) is one of the main syndromes in coronary heart disease (CHD). Syndromes of Chinese medicine (CM) are lack of quantitative and easyimplementation diagnosis standards. To quantify and standardize the diagnosis of PBSS, scales are usually applied. To evaluate the diagnostic accuracy of CM diagnosis scale of PBSS in CHD. Six hundred patients with stable angina pectoris of CHD, 300 in case group and 300 in control group, will be recruited from 5 hospitals across China. Diagnosis from 2 experts will be considered as the "gold standard". The study design consists of 2 phases: pilot test is used to evaluate the reliability and validity, and diagnostic test is used to assess the diagnostic accuracy of the scale, including sensitivity, specififi city, likelihood ratio and area under the receiver operator characteristic (ROC) curve. This study will evaluate the diagnostic accuracy of CM diagnosis scale of PBSS in CHD. The consensus of 2 experts may not be ideal as a "gold standard", and itself still requires further study. (No. ChiCTR-OOC-15006599).

Detached mindfulness reduced both depression and anxiety in elderly women with major depressive disorders.

PubMed

Ahmadpanah, Mohammad; Akbari, Tayebe; Akhondi, Amineh; Haghighi, Mohammad; Jahangard, Leila; Sadeghi Bahmani, Dena; Bajoghli, Hafez; Holsboer-Trachsler, Edith; Brand, Serge

2017-11-01

We investigated the influence of detached mindfulness (DM) in treating symptoms of depression and anxiety among elderly women. Thirty-four elderly females (mean age: 69.23 years) suffering from moderate major depressive disorders (MDD) and treated with a standard medication (citalopram) at therapeutic doses were randomly assigned either to an intervention condition (DM; group treatment, twice weekly) or to a control condition (with leisure activities, twice weekly). At baseline (BL), four weeks later at study completion (SC), and four weeks after that at follow-up (FU), participants completed ratings for symptoms of depression and anxiety; experts blind to patients' group assignments rated patients' symptoms of depression. Symptoms of depression (self and experts' ratings) and anxiety declined significantly over time in the DM, but not in the control condition. Effects remained stable at FU. The pattern of results suggests that, compared to a control condition, a specific psychotherapeutic intervention such as DM can have a beneficial effect in elderly female patients with MDD. Copyright © 2017 Elsevier B.V. All rights reserved.

PREVAIL: Predicting Recovery through Estimation and Visualization of Active and Incident Lesions.

PubMed

Dworkin, Jordan D; Sweeney, Elizabeth M; Schindler, Matthew K; Chahin, Salim; Reich, Daniel S; Shinohara, Russell T

2016-01-01

The goal of this study was to develop a model that integrates imaging and clinical information observed at lesion incidence for predicting the recovery of white matter lesions in multiple sclerosis (MS) patients. Demographic, clinical, and magnetic resonance imaging (MRI) data were obtained from 60 subjects with MS as part of a natural history study at the National Institute of Neurological Disorders and Stroke. A total of 401 lesions met the inclusion criteria and were used in the study. Imaging features were extracted from the intensity-normalized T1-weighted (T1w) and T2-weighted sequences as well as magnetization transfer ratio (MTR) sequence acquired at lesion incidence. T1w and MTR signatures were also extracted from images acquired one-year post-incidence. Imaging features were integrated with clinical and demographic data observed at lesion incidence to create statistical prediction models for long-term damage within the lesion. The performance of the T1w and MTR predictions was assessed in two ways: first, the predictive accuracy was measured quantitatively using leave-one-lesion-out cross-validated (CV) mean-squared predictive error. Then, to assess the prediction performance from the perspective of expert clinicians, three board-certified MS clinicians were asked to individually score how similar the CV model-predicted one-year appearance was to the true one-year appearance for a random sample of 100 lesions. The cross-validated root-mean-square predictive error was 0.95 for normalized T1w and 0.064 for MTR, compared to the estimated measurement errors of 0.48 and 0.078 respectively. The three expert raters agreed that T1w and MTR predictions closely resembled the true one-year follow-up appearance of the lesions in both degree and pattern of recovery within lesions. This study demonstrates that by using only information from a single visit at incidence, we can predict how a new lesion will recover using relatively simple statistical techniques. The potential to visualize the likely course of recovery has implications for clinical decision-making, as well as trial enrichment.

Parenting and Infant Difficulty: Testing a Mutual Exacerbation Hypothesis to Predict Early Onset Conduct Problems

ERIC Educational Resources Information Center

Lorber, Michael F.; Egeland, Byron

2011-01-01

The prediction of conduct problems (CPs) from infant difficulty and parenting measured in the first 6 months of life was studied in a sample of 267 high-risk mother-child dyads. Stable, cross-situational CPs at school entry (5-6 years) were predicted by negative infancy parenting, mediated by mutually angry and hostile mother-toddler interactions…

Residual Strength Prediction of Fuselage Structures with Multiple Site Damage

NASA Technical Reports Server (NTRS)

Chen, Chuin-Shan; Wawrzynek, Paul A.; Ingraffea, Anthony R.

1999-01-01

This paper summarizes recent results on simulating full-scale pressure tests of wide body, lap-jointed fuselage panels with multiple site damage (MSD). The crack tip opening angle (CTOA) fracture criterion and the FRANC3D/STAGS software program were used to analyze stable crack growth under conditions of general yielding. The link-up of multiple cracks and residual strength of damaged structures were predicted. Elastic-plastic finite element analysis based on the von Mises yield criterion and incremental flow theory with small strain assumption was used. A global-local modeling procedure was employed in the numerical analyses. Stress distributions from the numerical simulations are compared with strain gage measurements. Analysis results show that accurate representation of the load transfer through the rivets is crucial for the model to predict the stress distribution accurately. Predicted crack growth and residual strength are compared with test data. Observed and predicted results both indicate that the occurrence of small MSD cracks substantially reduces the residual strength. Modeling fatigue closure is essential to capture the fracture behavior during the early stable crack growth. Breakage of a tear strap can have a major influence on residual strength prediction.

Predicting New Materials for Hydrogen Storage Application

PubMed Central

Vajeeston, Ponniah; Ravindran, Ponniah; Fjellvåg, Helmer

2009-01-01

Knowledge about the ground-state crystal structure is a prerequisite for the rational understanding of solid-state properties of new materials. To act as an efficient energy carrier, hydrogen should be absorbed and desorbed in materials easily and in high quantities. Owing to the complexity in structural arrangements and difficulties involved in establishing hydrogen positions by x-ray diffraction methods, the structural information of hydrides are very limited compared to other classes of materials (like oxides, intermetallics, etc.). This can be overcome by conducting computational simulations combined with selected experimental study which can save environment, money, and man power. The predicting capability of first-principles density functional theory (DFT) is already well recognized and in many cases structural and thermodynamic properties of single/multi component system are predicted. This review will focus on possible new classes of materials those have high hydrogen content, demonstrate the ability of DFT to predict crystal structure, and search for potential meta-stable phases. Stabilization of such meta-stable phases is also discussed.

Prediction Model for Relativistic Electrons at Geostationary Orbit

NASA Technical Reports Server (NTRS)

Khazanov, George V.; Lyatsky, Wladislaw

2008-01-01

We developed a new prediction model for forecasting relativistic (greater than 2MeV) electrons, which provides a VERY HIGH correlation between predicted and actually measured electron fluxes at geostationary orbit. This model implies the multi-step particle acceleration and is based on numerical integrating two linked continuity equations for primarily accelerated particles and relativistic electrons. The model includes a source and losses, and used solar wind data as only input parameters. We used the coupling function which is a best-fit combination of solar wind/interplanetary magnetic field parameters, responsible for the generation of geomagnetic activity, as a source. The loss function was derived from experimental data. We tested the model for four year period 2004-2007. The correlation coefficient between predicted and actual values of the electron fluxes for whole four year period as well as for each of these years is stable and incredibly high (about 0.9). The high and stable correlation between the computed and actual electron fluxes shows that the reliable forecasting these electrons at geostationary orbit is possible.

Experimental verification of the Neuber relation at room and elevated temperatures. M.S. Thesis; [to predict stress-strain behavior in notched specimens of hastelloy x

NASA Technical Reports Server (NTRS)

Lucas, L. J.

1982-01-01

The accuracy of the Neuber equation at room temperature and 1,200 F as experimentally determined under cyclic load conditions with hold times. All strains were measured with an interferometric technique at both the local and remote regions of notched specimens. At room temperature, strains were obtained for the initial response at one load level and for cyclically stable conditions at four load levels. Stresses in notched members were simulated by subjecting smooth specimens to he same strains as were recorded on the notched specimen. Local stress-strain response was then predicted with excellent accuracy by subjecting a smooth specimen to limits established by the Neuber equation. Data at 1,200 F were obtained with the same experimental techniques but only in the cyclically stable conditions. The Neuber prediction at this temperature gave relatively accurate results in terms of predicting stress and strain points.

Predicting Time Series Outputs and Time-to-Failure for an Aircraft Controller Using Bayesian Modeling

NASA Technical Reports Server (NTRS)

He, Yuning

2015-01-01

Safety of unmanned aerial systems (UAS) is paramount, but the large number of dynamically changing controller parameters makes it hard to determine if the system is currently stable, and the time before loss of control if not. We propose a hierarchical statistical model using Treed Gaussian Processes to predict (i) whether a flight will be stable (success) or become unstable (failure), (ii) the time-to-failure if unstable, and (iii) time series outputs for flight variables. We first classify the current flight input into success or failure types, and then use separate models for each class to predict the time-to-failure and time series outputs. As different inputs may cause failures at different times, we have to model variable length output curves. We use a basis representation for curves and learn the mappings from input to basis coefficients. We demonstrate the effectiveness of our prediction methods on a NASA neuro-adaptive flight control system.

Stabilization of acetylcholine receptors at the neuromuscular synapse: the role of the nerve.

PubMed

Ramsay, D A; Drachman, D B; Drachman, R J; Stanley, E F

1992-05-29

The majority of acetylcholine receptors (AChRs) at innervated neuromuscular junctions (NMJs) are stable, with half-lives averaging about 11 days in rodent muscles. In addition to the stable AChRs, approximately 18% of AChRs at these innervated junctions are rapidly turned over (RTOs), with half lives of less than 24 h. We have postulated that RTOs may be precursors of stable AChRs, and that the motor nerve may influence their stabilization. This hypothesis was tested by: (i) labeling AChRs in mouse sternomastoid (SM) muscles with 125I-alpha-BuTx; (ii) denervating one SM muscle in each mouse, and (iii) following the fate of the labeled AChRs through a 5-day period when RTOs were either stabilized or degraded. The hypothesis predicts that denervation should preclude stabilization of RTOs, resulting in a deficit of stable AChRs in denervated muscles. The results showed a highly significant (P less than 0.002) deficit of stable AChRs in denervated as compared with innervated muscles. Control experiments excluded the possibility that this deficit could be attributed to independent accelerated degradation of either RTOs or pre-existing stable AChRs. The observed deficit was quantitatively consistent with the deficit predicted by a mathematical model based on interruption of stabilization following denervation. We conclude that: (i) the observed deficit after denervation of NMJs is due to failure of stabilization of pre-existing RTOs; (ii) RTOs at normally innervated NMJs are precursors of stable AChRs; (iii) stabilization occurs after the insertion of AChRs at NMJs, and (iv) motor nerves play a key role in stabilization of RTOs. The concept of receptor stabilization has important implications for understanding the biology of the neuromuscular junction and post-synaptic plasticity.

Visual prediction and perceptual expertise

PubMed Central

Cheung, Olivia S.; Bar, Moshe

2012-01-01

Making accurate predictions about what may happen in the environment requires analogies between perceptual input and associations in memory. These elements of predictions are based on cortical representations, but little is known about how these processes can be enhanced by experience and training. On the other hand, studies on perceptual expertise have revealed that the acquisition of expertise leads to strengthened associative processing among features or objects, suggesting that predictions and expertise may be tightly connected. Here we review the behavioral and neural findings regarding the mechanisms involving prediction and expert processing, and highlight important possible overlaps between them. Future investigation should examine the relations among perception, memory and prediction skills as a function of expertise. The knowledge gained by this line of research will have implications for visual cognition research, and will advance our understanding of how the human brain can improve its ability to predict by learning from experience. PMID:22123523

Stable Atlas-based Mapped Prior (STAMP) machine-learning segmentation for multicenter large-scale MRI data.

PubMed

Kim, Eun Young; Magnotta, Vincent A; Liu, Dawei; Johnson, Hans J

2014-09-01

Machine learning (ML)-based segmentation methods are a common technique in the medical image processing field. In spite of numerous research groups that have investigated ML-based segmentation frameworks, there remains unanswered aspects of performance variability for the choice of two key components: ML algorithm and intensity normalization. This investigation reveals that the choice of those elements plays a major part in determining segmentation accuracy and generalizability. The approach we have used in this study aims to evaluate relative benefits of the two elements within a subcortical MRI segmentation framework. Experiments were conducted to contrast eight machine-learning algorithm configurations and 11 normalization strategies for our brain MR segmentation framework. For the intensity normalization, a Stable Atlas-based Mapped Prior (STAMP) was utilized to take better account of contrast along boundaries of structures. Comparing eight machine learning algorithms on down-sampled segmentation MR data, it was obvious that a significant improvement was obtained using ensemble-based ML algorithms (i.e., random forest) or ANN algorithms. Further investigation between these two algorithms also revealed that the random forest results provided exceptionally good agreement with manual delineations by experts. Additional experiments showed that the effect of STAMP-based intensity normalization also improved the robustness of segmentation for multicenter data sets. The constructed framework obtained good multicenter reliability and was successfully applied on a large multicenter MR data set (n>3000). Less than 10% of automated segmentations were recommended for minimal expert intervention. These results demonstrate the feasibility of using the ML-based segmentation tools for processing large amount of multicenter MR images. We demonstrated dramatically different result profiles in segmentation accuracy according to the choice of ML algorithm and intensity normalization chosen. Copyright © 2014 Elsevier Inc. All rights reserved.

Diagnostic accuracy of ultrasonography in detection of blunt abdominal trauma and comparison of early and late ultrasonography 24 hours after trauma.

PubMed

Feyzi, Ali; Rad, Masoud Pezeshki; Ahanchi, Navid; Firoozabadi, Jalil

2015-01-01

Despite the advantages of ultrasound scan, its use as a screening tool in blunt abdominal trauma is controversial. The aim of this study was to evaluate the diagnostic value of early and late ultrasound in patients with blunt abdominal trauma (BAT). In this study which was performed in a level I trauma center, firstly, 2418 patients with BAT had ultrasound (US) examination by two trauma expert radiologists. Results were compared with the best available gold standards such as laparotomy, CT, repeated ultrasound or clinical course follow-up. Then, 400 patients with BAT were examined by a trained residency student. In the first phase, sensitivity, specificity, negative predictive value, positive predictive value and accuracy of ultrasound were 97%, 98.1%, 99.7%, 83% and 98% respectively. In the second phase, they were 97.3%, 97.2%, 97.7%, 96.8% and 97.3% for the early and 98.5%, 97.6%, 98.5%, 97.5% and 98% for the late ultrasound respectively. Results obtained from this study indicate that negative ultrasound findings associated with negative clinical observation virtually exclude abdominal injury, and confirmation by performing other tests is unnecessary. High sensitivity and negative predictive value is achieved if ultrasound is performed by expert trauma radiologist.

Extending (Q)SARs to incorporate proprietary knowledge for regulatory purposes: A case study using aromatic amine mutagenicity.

PubMed

Ahlberg, Ernst; Amberg, Alexander; Beilke, Lisa D; Bower, David; Cross, Kevin P; Custer, Laura; Ford, Kevin A; Van Gompel, Jacky; Harvey, James; Honma, Masamitsu; Jolly, Robert; Joossens, Elisabeth; Kemper, Raymond A; Kenyon, Michelle; Kruhlak, Naomi; Kuhnke, Lara; Leavitt, Penny; Naven, Russell; Neilan, Claire; Quigley, Donald P; Shuey, Dana; Spirkl, Hans-Peter; Stavitskaya, Lidiya; Teasdale, Andrew; White, Angela; Wichard, Joerg; Zwickl, Craig; Myatt, Glenn J

2016-06-01

Statistical-based and expert rule-based models built using public domain mutagenicity knowledge and data are routinely used for computational (Q)SAR assessments of pharmaceutical impurities in line with the approach recommended in the ICH M7 guideline. Knowledge from proprietary corporate mutagenicity databases could be used to increase the predictive performance for selected chemical classes as well as expand the applicability domain of these (Q)SAR models. This paper outlines a mechanism for sharing knowledge without the release of proprietary data. Primary aromatic amine mutagenicity was selected as a case study because this chemical class is often encountered in pharmaceutical impurity analysis and mutagenicity of aromatic amines is currently difficult to predict. As part of this analysis, a series of aromatic amine substructures were defined and the number of mutagenic and non-mutagenic examples for each chemical substructure calculated across a series of public and proprietary mutagenicity databases. This information was pooled across all sources to identify structural classes that activate or deactivate aromatic amine mutagenicity. This structure activity knowledge, in combination with newly released primary aromatic amine data, was incorporated into Leadscope's expert rule-based and statistical-based (Q)SAR models where increased predictive performance was demonstrated. Copyright © 2016 Elsevier Inc. All rights reserved.

Control at stability's edge minimizes energetic costs: expert stick balancing

PubMed Central

Meyer, Ryan; Zhvanetsky, Max; Ridge, Sarah; Insperger, Tamás

2016-01-01

Stick balancing on the fingertip is a complex voluntary motor task that requires the stabilization of an unstable system. For seated expert stick balancers, the time delay is 0.23 s, the shortest stick that can be balanced for 240 s is 0.32 m and there is a ° dead zone for the estimation of the vertical displacement angle in the saggital plane. These observations motivate a switching-type, pendulum–cart model for balance control which uses an internal model to compensate for the time delay by predicting the sensory consequences of the stick's movements. Numerical simulations using the semi-discretization method suggest that the feedback gains are tuned near the edge of stability. For these choices of the feedback gains, the cost function which takes into account the position of the fingertip and the corrective forces is minimized. Thus, expert stick balancers optimize control with a combination of quick manoeuvrability and minimum energy expenditures. PMID:27278361

The Lifecycle of Bayesian Network Models Developed for Multi-Source Signature Assessment of Nuclear Programs

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

Gastelum, Zoe N.; White, Amanda M.; Whitney, Paul D.

2013-06-04

The Multi-Source Signatures for Nuclear Programs project, part of Pacific Northwest National Laboratory’s (PNNL) Signature Discovery Initiative, seeks to computationally capture expert assessment of multi-type information such as text, sensor output, imagery, or audio/video files, to assess nuclear activities through a series of Bayesian network (BN) models. These models incorporate knowledge from a diverse range of information sources in order to help assess a country’s nuclear activities. The models span engineering topic areas, state-level indicators, and facility-specific characteristics. To illustrate the development, calibration, and use of BN models for multi-source assessment, we present a model that predicts a country’s likelihoodmore » to participate in the international nuclear nonproliferation regime. We validate this model by examining the extent to which the model assists non-experts arrive at conclusions similar to those provided by nuclear proliferation experts. We also describe the PNNL-developed software used throughout the lifecycle of the Bayesian network model development.« less

Born with an ear for dialects? Structural plasticity in the expert phonetician brain.

PubMed

Golestani, Narly; Price, Cathy J; Scott, Sophie K

2011-03-16

Are experts born with particular predispositions, or are they made through experience? We examined brain structure in expert phoneticians, individuals who are highly trained to analyze and transcribe speech. We found a positive correlation between the size of left pars opercularis and years of phonetic transcription training experience, illustrating how learning may affect brain structure. Phoneticians were also more likely to have multiple or split left transverse gyri in the auditory cortex than nonexpert controls, and the amount of phonetic transcription training did not predict auditory cortex morphology. The transverse gyri are thought to be established in utero; our results thus suggest that this gross morphological difference may have existed before the onset of phonetic training, and that its presence confers an advantage of sufficient magnitude to affect career choices. These results suggest complementary influences of domain-specific predispositions and experience-dependent brain malleability, influences that likely interact in determining not only how experience shapes the human brain but also why some individuals become engaged by certain fields of expertise.

A Rocket Engine Design Expert System

NASA Technical Reports Server (NTRS)

Davidian, Kenneth J.

1989-01-01

The overall structure and capabilities of an expert system designed to evaluate rocket engine performance are described. The expert system incorporates a JANNAF standard reference computer code to determine rocket engine performance and a state of the art finite element computer code to calculate the interactions between propellant injection, energy release in the combustion chamber, and regenerative cooling heat transfer. Rule-of-thumb heuristics were incorporated for the H2-O2 coaxial injector design, including a minimum gap size constraint on the total number of injector elements. One dimensional equilibrium chemistry was used in the energy release analysis of the combustion chamber. A 3-D conduction and/or 1-D advection analysis is used to predict heat transfer and coolant channel wall temperature distributions, in addition to coolant temperature and pressure drop. Inputting values to describe the geometry and state properties of the entire system is done directly from the computer keyboard. Graphical display of all output results from the computer code analyses is facilitated by menu selection of up to five dependent variables per plot.

The effect of food label cues on perceptions of quality and purchase intentions among high-involvement consumers with varying levels of nutrition knowledge.

PubMed

Walters, Amber; Long, Marilee

2012-01-01

To determine whether differences in nutrition knowledge affected how women (a high-involvement group) interpreted intrinsic cues (ingredient list) and extrinsic cues ("all natural" label) on food labels. A 2 (intrinsic cue) × 2 (extrinsic cue) × 2 (nutrition knowledge expert vs novice) within-subject factorial design was used. Participants were 106 female college students (61 experts, 45 novices). Dependent variables were perception of product quality and purchase intention. As predicted by the elaboration likelihood model, experts used central route processing to scrutinize intrinsic cues and make judgments about food products. Novices used peripheral route processing to make simple inferences about the extrinsic cues in labels. Consumers' levels of nutrition knowledge influenced their ability to process food labels. The United States Food and Drug Administration should regulate the "all natural" food label, because this claim is likely to mislead most consumers. Copyright © 2012 Society for Nutrition Education and Behavior. Published by Elsevier Inc. All rights reserved.

Psychology and psychiatry in Singapore courts: A baseline survey of the mental health landscape in the legal arena.

PubMed

Gwee, Kenji

Despite the increasing prevalence and involvement of mental health professionals in local courts, there has been no systematic study of the role played by these expert witnesses in Singapore courtrooms. An empirical study of all existing recorded cases on Lawnet (Singapore's legal database of all court trial cases) from 1975-2014 involving psychologists and psychiatrists was conducted. Results revealed that, not only were these mental health experts increasingly dotting the landscape of the legal arena, the variety of their contributions has also been gradually growing. Furthermore, there were marked differences across criminal, civil and custody cases with regards to the issues of how these experts were consulted and how their inputs utilized and appreciated by judges. Differences between psychology and psychiatry were also apparent. A future with more assistance rendered by these professions to courts, as well as greater synergy between law and mental health, was predicted for Singapore courts. Copyright © 2017 Elsevier Ltd. All rights reserved.

A Data-Driven Solution for Performance Improvement

NASA Technical Reports Server (NTRS)

2002-01-01

Marketed as the "Software of the Future," Optimal Engineering Systems P.I. EXPERT(TM) technology offers statistical process control and optimization techniques that are critical to businesses looking to restructure or accelerate operations in order to gain a competitive edge. Kennedy Space Center granted Optimal Engineering Systems the funding and aid necessary to develop a prototype of the process monitoring and improvement software. Completion of this prototype demonstrated that it was possible to integrate traditional statistical quality assurance tools with robust optimization techniques in a user- friendly format that is visually compelling. Using an expert system knowledge base, the software allows the user to determine objectives, capture constraints and out-of-control processes, predict results, and compute optimal process settings.

Personality stability is associated with better cognitive performance in adulthood: are the stable more able?

PubMed

Graham, Eileen K; Lachman, Margie E

2012-09-01

Although personality is relatively stable over time, there are individual differences in the patterns and magnitude of change. There is some evidence that personality change in adulthood is related to physical health and longevity. The present study expanded this work to consider whether personality stability or change would be associated with better cognitive functioning, especially in later adulthood. A total of 4,974 individuals participated in two waves of The Midlife in the United States Study (MIDUS) in 1994-1995 and 2004-2005. Participants completed the MIDUS personality inventory at both times and the Brief Test of Adult Cognition by Telephone cognitive battery at Time 2. Multiple regression and analysis of covariance analyses showed that, consistent with predictions, individuals remaining stable in openness to experience and neuroticism had faster reaction times and better inductive reasoning than those who changed. Among older adults, those who remained stable or decreased in neuroticism had significantly faster reaction times than those who increased. As predicted, personality stability on some traits was associated with more adaptive cognitive performance on reasoning and reaction time. Personality is discussed as a possible resource for protecting against or minimizing age-related declines in cognition.

Why Bother to Calibrate? Model Consistency and the Value of Prior Information

NASA Astrophysics Data System (ADS)

Hrachowitz, Markus; Fovet, Ophelie; Ruiz, Laurent; Euser, Tanja; Gharari, Shervan; Nijzink, Remko; Savenije, Hubert; Gascuel-Odoux, Chantal

2015-04-01

Hydrological models frequently suffer from limited predictive power despite adequate calibration performances. This can indicate insufficient representations of the underlying processes. Thus ways are sought to increase model consistency while satisfying the contrasting priorities of increased model complexity and limited equifinality. In this study the value of a systematic use of hydrological signatures and expert knowledge for increasing model consistency was tested. It was found that a simple conceptual model, constrained by 4 calibration objective functions, was able to adequately reproduce the hydrograph in the calibration period. The model, however, could not reproduce 20 hydrological signatures, indicating a lack of model consistency. Subsequently, testing 11 models, model complexity was increased in a stepwise way and counter-balanced by using prior information about the system to impose "prior constraints", inferred from expert knowledge and to ensure a model which behaves well with respect to the modeller's perception of the system. We showed that, in spite of unchanged calibration performance, the most complex model set-up exhibited increased performance in the independent test period and skill to reproduce all 20 signatures, indicating a better system representation. The results suggest that a model may be inadequate despite good performance with respect to multiple calibration objectives and that increasing model complexity, if efficiently counter-balanced by available prior constraints, can increase predictive performance of a model and its skill to reproduce hydrological signatures. The results strongly illustrate the need to balance automated model calibration with a more expert-knowledge driven strategy of constraining models.

Why Bother and Calibrate? Model Consistency and the Value of Prior Information.

NASA Astrophysics Data System (ADS)

Hrachowitz, M.; Fovet, O.; Ruiz, L.; Euser, T.; Gharari, S.; Nijzink, R.; Freer, J. E.; Savenije, H.; Gascuel-Odoux, C.

2014-12-01

Hydrological models frequently suffer from limited predictive power despite adequate calibration performances. This can indicate insufficient representations of the underlying processes. Thus ways are sought to increase model consistency while satisfying the contrasting priorities of increased model complexity and limited equifinality. In this study the value of a systematic use of hydrological signatures and expert knowledge for increasing model consistency was tested. It was found that a simple conceptual model, constrained by 4 calibration objective functions, was able to adequately reproduce the hydrograph in the calibration period. The model, however, could not reproduce 20 hydrological signatures, indicating a lack of model consistency. Subsequently, testing 11 models, model complexity was increased in a stepwise way and counter-balanced by using prior information about the system to impose "prior constraints", inferred from expert knowledge and to ensure a model which behaves well with respect to the modeller's perception of the system. We showed that, in spite of unchanged calibration performance, the most complex model set-up exhibited increased performance in the independent test period and skill to reproduce all 20 signatures, indicating a better system representation. The results suggest that a model may be inadequate despite good performance with respect to multiple calibration objectives and that increasing model complexity, if efficiently counter-balanced by available prior constraints, can increase predictive performance of a model and its skill to reproduce hydrological signatures. The results strongly illustrate the need to balance automated model calibration with a more expert-knowledge driven strategy of constraining models.

Prospective evaluation of a rapid nanoparticle-based lateral flow immunoassay (STic Expert(®) HIT) for the diagnosis of heparin-induced thrombocytopenia.

PubMed

Leroux, Dorothée; Hezard, Nathalie; Lebreton, Aurélien; Bauters, Anne; Suchon, Pierre; de Maistre, Emmanuel; Biron, Christine; Huisse, Marie-Genevieve; Ternisien, Catherine; Voisin, Sophie; Gruel, Yves; Pouplard, Claire

2014-09-01

A rapid lateral flow immunoassay (LFIA) (STic Expert(®) HIT), recently developed for the diagnosis of heparin-induced thrombocytopenia (HIT), was evaluated in a prospective multicentre cohort of 334 consecutive patients. The risk of HIT was estimated by the 4Ts score as low, intermediate and high in 28·7%, 61·7% and 9·6% of patients, respectively. Definite HIT was diagnosed in 40 patients (12·0%) with positive results on both enzyme-linked immunosorbent assay (Asserachrom(®) HPIA IgG) and serotonin release assay. The inter-reader reproducibility of results obtained was excellent (kappa ratio > 0·9). The negative predictive value of LFIA with plasma samples was 99·6% with a negative likelihood ratio (LR) of 0·03, and was comparable to those of the particle gel immunoassay (H/PF4-PaGIA(®) ) performed in 124 cases. Positive predictive value and positive LR were 44·4% and 5·87, respectively, and the results were similar for serum samples. The probability of HIT in intermediate risk patients decreased from 11·2% to 0·4% when the LFIA result was negative and increased to 42·5% when it was positive. In conclusion, the STic Expert(®) HIT combined with the 4Ts score is a reliable tool to rule out the diagnosis of HIT. © 2014 John Wiley & Sons Ltd.

EFFECT OF FLOW REGIME ON FISH-HABITAT RELATIONSHIPS IN A MID-WESTERN RIVER

EPA Science Inventory

Numerous studies have shown interrelationships among stream fishes, habitat and land use, but it is unclear how flow regime affects these relationships. We hypothesized that habitat would better predict fishes in streams with stable flows. Habitat should be less predictive in u...

A STATISTICAL MODELING METHODOLOGY FOR THE DETECTION, QUANTIFICATION, AND PREDICTION OF ECOLOGICAL THRESHOLDS

EPA Science Inventory

This study will provide a general methodology for integrating threshold information from multiple species ecological metrics, allow for prediction of changes of alternative stable states, and provide a risk assessment tool that can be applied to adaptive management. The integr...

Predicting the solubility and lability of Zn, Cd, and Pb in soils from a minespoil-contaminated catchment by stable isotopic exchange

NASA Astrophysics Data System (ADS)

Marzouk, E. R.; Chenery, S. R.; Young, S. D.

2013-12-01

The Rookhope catchment of Weardale, England, has a diverse legacy of contaminated soils due to extensive lead mining activity over four centuries. We measured the isotopically exchangeable content of Pb, Cd and Zn (E-values) in a large representative subset of the catchment soils (n = 246) using stable isotope dilution. All three metals displayed a wide range of %E-values (c. 1-100%) but relative lability followed the sequence Cd > Pb > Zn. A refinement of the stable isotope dilution approach also enabled detection of non-reactive metal contained within suspended sub-micron (<0.22 μm) colloidal particles (SCP-metal). For most soils, the presence of non-labile SCP-metal caused only minor over-estimation of E-values (<2%) but the effect was greater for soils with particularly large humus or carbonate contents. Approximately 80%, 53% and 66% of the variability in Zn, Cd and Pb %E-values (respectively) could be explained by pH, loss on ignition and total metal content. E-values were affected by the presence of ore minerals at high metal contents leading to an inconsistent trend in the relationship between %E-value and soil metal concentration. Metal solubility, in the soil suspensions used to measure E-values, was predicted using the WHAM geochemical speciation model (versions VI and VII). The use of total and isotopically exchangeable metal as alternative input variables was compared; the latter provided significantly better predictions of solubility, especially in the case of Zn. Lead solubility was less well predicted by either version of WHAM, with over-prediction at low pH and under-prediction at high soil pH values. Quantify the isotopically exchangeable fractions of Zn, Cd and Pb (E-values), and assess their local and regional variability, using multi-element stable isotope dilution, in a diverse range of soil ecosystems within the catchment of an old Pb/Zn mining area. Assess the controlling influences of soil properties on metal lability and develop predictive algorithms for metal lability in the contaminated catchment based on simple soil properties (such as pH, organic matter (LOI), and total metal content). Examine the incidence of non-isotopically-exchangeable metal held within suspended colloidal particles (SCP-metal) in filtered soil solutions (<0.22 μm) by comparing E-values from isotopic abundance in solutions equilibrated with soil and in a resin phase equilibrated with the separated solution. Assess the ability of a geochemical speciation model, WHAM(VII), to predict metal solubility using isotopically exchangeable metal as an input variable.

Comparison of Expert Adjudicated Coronary Heart Disease and Cardiovascular Disease Mortality With the National Death Index: Results From the REasons for Geographic And Racial Differences in Stroke (REGARDS) Study.

PubMed

Olubowale, Olusola Tope; Safford, Monika M; Brown, Todd M; Durant, Raegan W; Howard, Virginia J; Gamboa, Christopher; Glasser, Stephen P; Rhodes, J David; Levitan, Emily B

2017-05-03

The National Death Index (NDI) is widely used to detect coronary heart disease (CHD) and cardiovascular disease (CVD) deaths, but its reliability has not been examined recently. We compared CHD and CVD deaths detected by NDI with expert adjudication of 4010 deaths that occurred between 2003 and 2013 among participants in the REGARDS (REasons for Geographic And Racial Differences in Stroke) cohort of black and white adults in the United States. NDI derived CHD mortality had sensitivity 53.6%, specificity 90.3%, positive predictive value 54.2%, and negative predictive value 90.1%. NDI-derived CVD mortality had sensitivity 73.4%, specificity 84.5%, positive predictive value 70.6%, and negative predictive value 86.2%. Among NDI-derived CHD and CVD deaths, older age (odds ratios, 1.06 and 1.04 per 1-year increase) was associated with a higher probability of disagreement with the adjudicated cause of death, whereas among REGARDS adjudicated CHD and CVD deaths a history of CHD or CVD was associated with a lower probability of disagreement with the NDI-derived causes of death (odds ratios, 0.59 and 0.67, respectively). The modest accuracy and differential performance of NDI-derived cause of death may impact CHD and CVD mortality statistics. © 2017 The Authors. Published on behalf of the American Heart Association, Inc., by Wiley.

Can We Determine Sasang Constitutional Body Type Merely by Facial Inspection?

PubMed

Rhee, Seung Chul; Bae, Hyo-Sang; Lee, Yung-Seop; Hwang, Rahil

2017-05-01

This study aimed to assess the inter-observer concordance rate of anthroscopic examination on facial features among experts in Sasang constitutional medicine (SCM) in order to evaluate the presence of statistical differences in facial structural characteristics among different body types of Sasang constitution (SC), and to develop an objective method for facial analysis for diagnosing SC types to prevent SCM experts from misdiagnosis by their perceptional errors about faces. This was a double-blinded cross-sectional study conducted on 174 people's faces. Ten SCM experts participated in this study. Frontal and lateral photographs of subjects were standardized and displayed to 10 SCM experts for diagnosing the SC type by anthroscopic examination alone (experiment 1). The subjects' faces were analyzed by photogrammetric method to investigate the presence of any typical structural characteristics of the faces to differentiate SC type (experiment 2). Comparing subjects' SC type with anthroscopic diagnosis by 10 SCM experts, the inter-observer concordance rates were measured (experiment 1). Using photogrammetric facial analysis, a multinomial logistic model was made for analyzing the correlation of SC type and subjects' facial structural configuration (experiment 2). The inter-observer concordance rate of anthroscopic examination was 2.9% in experiment 1. Using a multinomial logistic fitting model, the predicted probability for determining SC type was 52.8-57.6% in experiment 2 (p < 0.05). Prototype composite faces were also created from photographs of subjects who received the same SC type from the SCM experts. As SC type cannot be precisely diagnosed using anthroscopic examination alone, SCM needs a definitive objective and scientific diagnosing method to be a scientifically verified alternative medicine and be globalized in future.

A condition metric for Eucalyptus woodland derived from expert evaluations.

PubMed

Sinclair, Steve J; Bruce, Matthew J; Griffioen, Peter; Dodd, Amanda; White, Matthew D

2018-02-01

The evaluation of ecosystem quality is important for land-management and land-use planning. Evaluation is unavoidably subjective, and robust metrics must be based on consensus and the structured use of observations. We devised a transparent and repeatable process for building and testing ecosystem metrics based on expert data. We gathered quantitative evaluation data on the quality of hypothetical grassy woodland sites from experts. We used these data to train a model (an ensemble of 30 bagged regression trees) capable of predicting the perceived quality of similar hypothetical woodlands based on a set of 13 site variables as inputs (e.g., cover of shrubs, richness of native forbs). These variables can be measured at any site and the model implemented in a spreadsheet as a metric of woodland quality. We also investigated the number of experts required to produce an opinion data set sufficient for the construction of a metric. The model produced evaluations similar to those provided by experts, as shown by assessing the model's quality scores of expert-evaluated test sites not used to train the model. We applied the metric to 13 woodland conservation reserves and asked managers of these sites to independently evaluate their quality. To assess metric performance, we compared the model's evaluation of site quality with the managers' evaluations through multidimensional scaling. The metric performed relatively well, plotting close to the center of the space defined by the evaluators. Given the method provides data-driven consensus and repeatability, which no single human evaluator can provide, we suggest it is a valuable tool for evaluating ecosystem quality in real-world contexts. We believe our approach is applicable to any ecosystem. © 2017 State of Victoria.

Discus: investigating subjective judgment of optic disc damage.

PubMed

Denniss, Jonathan; Echendu, Damian; Henson, David B; Artes, Paul H

2011-01-01

To describe a software package (Discus) for investigating clinicians' subjective assessment of optic disc damage [diagnostic accuracy in detecting visual field (VF) damage, decision criteria, and agreement with a panel of experts] and to provide reference data from a group of expert observers. Optic disc images were selected from patients with manifest or suspected glaucoma or ocular hypertension who attended the Manchester Royal Eye Hospital. Eighty images came from eyes without evidence of VF loss in at least four consecutive tests (VF negatives), and 20 images from eyes with repeatable VF loss (VF positives). Software was written to display these images in randomized order, for up to 60 s. Expert observers (n = 12) rated optic disc damage on a 5-point scale (definitely healthy, probably healthy, not sure, probably damaged, and definitely damaged). Optic disc damage as determined by the expert observers predicted VF loss with less than perfect accuracy (mean area under receiver-operating characteristic curve, 0.78; range, 0.72 to 0.85). When the responses were combined across the panel of experts, the area under receiver-operating characteristic curve reached 0.87, corresponding to a sensitivity of ∼60% at 90% specificity. Although the observers' performances were similar, there were large differences between the criteria they adopted (p < 0.001), even though all observers had been given identical instructions. Discus provides a simple and rapid means for assessing important aspects of optic disc interpretation. The data from the panel of expert observers provide a reference against which students, trainees, and clinicians may compare themselves. The program and the analyses described in this article are freely accessible from http://www.discusproject.blogspot.com/.

Risk factors perceived predictive of ISA spread in Chile: applications to decision support.

PubMed

Gustafson, L; Antognoli, M; Lara Fica, M; Ibarra, R; Mancilla, J; Sandoval Del Valle, O; Enriquez Sais, R; Perez, A; Aguilar, D; Madrid, E; Bustos, P; Clement, A; Godoy, M G; Johnson, C; Remmenga, M

2014-11-01

Aquaculture is anticipated to be a critical element in future solutions to global food shortage. However, diseases can impede industry efficiency and sustainability. Consequently, diseases can and have led to dramatic re-structuring in industry or regulatory practices. The emergence of infectious salmon anemia (ISA) in Chile is one such example. As in other countries, many mitigations were instituted universally, and many incurred considerable costs as they introduced a new layer of coordination of farming activities of marine sites within common geographic areas (termed 'neighborhoods' or 'barrios'). The aggregate response led to a strong reduction in ISA incidence and impact. However, the relative value of individual mitigations is less clear, especially where response policies were universally applied and retrospective analyses are missing 'controls' (i.e., areas where a mitigation was not applied). Further, re-focusing policies around disease prevention following resolution of an outbreak is important to renew sustainable production; though, again, field data to guide this shift in purpose are often lacking. Expert panels can offer timely decision support in the absence of empirical data. We convened a panel of fish health experts to weight risk factors predictive of ISA virus (ISAV) introduction or spread between Atlantic salmon barrios in Chile. Barrios, rather than sites, were the unit of interest because many of the new mitigations operate at this level and few available studies examine their efficacy. Panelists identified barrio processing plant biosecurity, fallowing strategies, adult live fish transfers, fish and site density, smolt quality, hydrographic connection with other neighborhoods, presence of sea lice (Caligus rogercresseyi), and harvest vessel biosecurity as factors with the greatest predictive strength for ISAV virulent genotype ('HPR-deleted') occurrence. Fewer factors were considered predictive of ISAV HPR0 genotype ('HPR0') occurrence, with greatest strengths assigned to fish and site density, adult live fish transfers, and smolt facility HPR0 status. Field validation based on ISAV and risk factor occurrence after panel completion generally supports expert estimates, and highlights a few factors (e.g., broodstock HPR0 status) less conclusive in the original study. Results inform legislation, industry best management practices and surveillance design. Published by Elsevier B.V.

Effects of sport expertise on representational momentum during timing control.

PubMed

Nakamoto, Hiroki; Mori, Shiro; Ikudome, Sachi; Unenaka, Satoshi; Imanaka, Kuniyasu

2015-04-01

Sports involving fast visual perception require players to compensate for delays in neural processing of visual information. Memory for the final position of a moving object is distorted forward along its path of motion (i.e., "representational momentum," RM). This cognitive extrapolation of visual perception might compensate for the neural delay in interacting appropriately with a moving object. The present study examined whether experienced batters cognitively extrapolate the location of a fast-moving object and whether this extrapolation is associated with coincident timing control. Nine expert and nine novice baseball players performed a prediction motion task in which a target moved from one end of a straight 400-cm track at a constant velocity. In half of the trials, vision was suddenly occluded when the target reached the 200-cm point (occlusion condition). Participants had to press a button concurrently with the target arrival at the end of the track and verbally report their subjective assessment of the first target-occluded position. Experts showed larger RM magnitude (cognitive extrapolation) than did novices in the occlusion condition. RM magnitude and timing errors were strongly correlated in the fast velocity condition in both experts and novices, whereas in the slow velocity condition, a significant correlation appeared only in experts. This suggests that experts can cognitively extrapolate the location of a moving object according to their anticipation and, as a result, potentially circumvent neural processing delays. This process might be used to control response timing when interacting with moving objects.

Hierarchical mixture of experts and diagnostic modeling approach to reduce hydrologic model structural uncertainty: STRUCTURAL UNCERTAINTY DIAGNOSTICS

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

Moges, Edom; Demissie, Yonas; Li, Hong-Yi

2016-04-01

In most water resources applications, a single model structure might be inadequate to capture the dynamic multi-scale interactions among different hydrological processes. Calibrating single models for dynamic catchments, where multiple dominant processes exist, can result in displacement of errors from structure to parameters, which in turn leads to over-correction and biased predictions. An alternative to a single model structure is to develop local expert structures that are effective in representing the dominant components of the hydrologic process and adaptively integrate them based on an indicator variable. In this study, the Hierarchical Mixture of Experts (HME) framework is applied to integratemore » expert model structures representing the different components of the hydrologic process. Various signature diagnostic analyses are used to assess the presence of multiple dominant processes and the adequacy of a single model, as well as to identify the structures of the expert models. The approaches are applied for two distinct catchments, the Guadalupe River (Texas) and the French Broad River (North Carolina) from the Model Parameter Estimation Experiment (MOPEX), using different structures of the HBV model. The results show that the HME approach has a better performance over the single model for the Guadalupe catchment, where multiple dominant processes are witnessed through diagnostic measures. Whereas, the diagnostics and aggregated performance measures prove that French Broad has a homogeneous catchment response, making the single model adequate to capture the response.« less

Artificial intelligence against breast cancer (A.N.N.E.S-B.C.-Project).

PubMed

Parmeggiani, Domenico; Avenia, Nicola; Sanguinetti, Alessandro; Ruggiero, Roberto; Docimo, Giovanni; Siciliano, Mattia; Ambrosino, Pasquale; Madonna, Imma; Peltrini, Roberto; Parmeggiani, Umberto

2012-01-01

Our preliminary study examined the development of an advanced innovative technology with the objectives of--developing methodologies and algorithms for a Artificial Neural Network (ANN) system, improving mammography and ultra-sonography images interpretation;--creating autonomous software as a diagnostic tool for the physicians, allowing the possibility for the advanced application of databases using Artificial Intelligence (Expert System). Since 2004 550 F patients over 40 yrs old were divided in two groups: 1) 310 pts underwent echo every 6 months and mammography every year by expert radiologists. 2) 240 pts had the same screening program and were also examined by our diagnosis software, developed with ANN-ES technology by the Engineering Aircraft Research Project team. The information was continually updated and returned to the Expert System, defining the principal rules of automatic diagnosis. In the second group we selected: Expert radiologist decision; ANN-ES decision; Expert radiologists with ANN-ES decision. The second group had significantly better diagnosis for cancer and better specificity for breast lesions risk as well as the highest percentage account when the radiologist's decision was helped by the ANN software. The ANN-ES group was able to select, by anamnestic, diagnostic and genetic means, 8 patients for prophylactic surgery, finding 4 cancers in a very early stage. Although it is only a preliminary study, this innovative diagnostic tool seems to provide better positive and negative predictive value in cancer diagnosis as well as in breast risk lesion identification.

The ability of video image analysis to predict lean meat yield and EUROP score of lamb carcasses.

PubMed

Einarsson, E; Eythórsdóttir, E; Smith, C R; Jónmundsson, J V

2014-07-01

A total of 862 lamb carcasses that were evaluated by both the VIAscan® and the current EUROP classification system were deboned and the actual yield was measured. Models were derived for predicting lean meat yield of the legs (Leg%), loin (Loin%) and shoulder (Shldr%) using the best VIAscan® variables selected by stepwise regression analysis of a calibration data set (n=603). The equations were tested on validation data set (n=259). The results showed that the VIAscan® predicted lean meat yield in the leg, loin and shoulder with an R 2 of 0.60, 0.31 and 0.47, respectively, whereas the current EUROP system predicted lean yield with an R 2 of 0.57, 0.32 and 0.37, respectively, for the three carcass parts. The VIAscan® also predicted the EUROP score of the trial carcasses, using a model derived from an earlier trial. The EUROP classification from VIAscan® and the current system were compared for their ability to explain the variation in lean yield of the whole carcass (LMY%) and trimmed fat (FAT%). The predicted EUROP scores from the VIAscan® explained 36% of the variation in LMY% and 60% of the variation in FAT%, compared with the current EUROP system that explained 49% and 72%, respectively. The EUROP classification obtained by the VIAscan® was tested against a panel of three expert classifiers (n=696). The VIAscan® classification agreed with 82% of conformation and 73% of the fat classes assigned by a panel of expert classifiers. It was concluded that VIAscan® provides a technology that can directly predict LMY% of lamb carcasses with more accuracy than the current EUROP classification system. The VIAscan® is also capable of classifying lamb carcasses into EUROP classes with an accuracy that fulfils minimum demands for the Icelandic sheep industry. Although the VIAscan® prediction of the Loin% is low, it is comparable to the current EUROP system, and should not hinder the adoption of the technology to estimate the yield of Icelandic lambs as it delivered a more accurate prediction for the Leg%, Shldr% and overall LMY% with negligible prediction bias.

Two Stochastic Phases of Tick-wise Price Fluctuation and the Price Prediction Generator

NASA Astrophysics Data System (ADS)

Tanaka-Yamawaki, Mieko; Tokuoka, Seiji

2007-07-01

We report in this paper the existence of two different stochastic phases in the tick-wise price fluctuations. Based on this observation, we improve our old method of developing the evolutional strategy to predict the direction of the tick-wise price movements. We obtain a stable predictive power even in the region where the old method had a difficulty.

Sparse Zero-Sum Games as Stable Functional Feature Selection

PubMed Central

Sokolovska, Nataliya; Teytaud, Olivier; Rizkalla, Salwa; Clément, Karine; Zucker, Jean-Daniel

2015-01-01

In large-scale systems biology applications, features are structured in hidden functional categories whose predictive power is identical. Feature selection, therefore, can lead not only to a problem with a reduced dimensionality, but also reveal some knowledge on functional classes of variables. In this contribution, we propose a framework based on a sparse zero-sum game which performs a stable functional feature selection. In particular, the approach is based on feature subsets ranking by a thresholding stochastic bandit. We provide a theoretical analysis of the introduced algorithm. We illustrate by experiments on both synthetic and real complex data that the proposed method is competitive from the predictive and stability viewpoints. PMID:26325268

Ferromagnetism in two-dimensional hole-doped SnO

NASA Astrophysics Data System (ADS)

Houssa, M.; Iordanidou, K.; Pourtois, G.; Afanas'ev, V. V.; Stesmans, A.

2018-05-01

Hole-doped monolayer SnO has been recently predicted to be a ferromagnetic material, for a hole density typically above 5x1013/cm2. The possibility to induce a hole-doped stable ferromagnetic order in this two-dimensional material, either by intrinsic or extrinsic defects, is theoretically studied, using first-principles simulations. Sn vacancies and Sn vacancy-hydrogen complexes are predicted to be shallow acceptors, with relatively low formation energies in SnO monolayers grown under O-rich conditions. These defects produce spin-polarized gap states near the valence band-edge, potentially stabilizing the ferromagnetic order in 2D SnO. Hole-doping resulting from substitutional doping is also investigated. Among the considered possible dopants, As, substituting O, is predicted to produce shallow spin-polarized gap states near the valence band edge, also potentially resulting in a stable ferromagnetic order in SnO monolayers.

Parent and Peer Links to Trajectories of Anxious Withdrawal From Grades 5 to 8

PubMed Central

Booth-LaForce, Cathryn; Oh, Wonjung; Kennedy, Amy E.; Rubin, Kenneth H.; Rose-Krasnor, Linda; Laursen, Brett

2013-01-01

Individual differences in trajectories of anxious withdrawal were examined from Grades 5 to 8 across the transition to middle school in a community sample (N = 283), using General Growth Mixture Modeling. Three distinct pathways of anxious withdrawal were identified: low-stable (78%), high-decreasing (12%), and high-increasing (10%). In Grade 6, relative to the low-stable class, greater peer exclusion and more free time spent with mother predicted membership in the high-decreasing class; higher peer exclusion predicted membership in the high-increasing class. Within the high-increasing class, the growth of anxious withdrawal was predicted by lower parental autonomy-granting, less free time with mother, both nurturing and restrictive parenting, and greater peer exclusion. Results highlight the role of both parent–child relationship and peer difficulties in increasing the adjustment risk among youth who are anxiously withdrawn prior to the middle-school transition. PMID:22417188

New multifunctional tungsten nitride with energetic N6 and extreme hardness predicted from first principles

NASA Astrophysics Data System (ADS)

Li, Qian; Sha, Lei; Zhu, Chunye; Yao, Yansun

2017-05-01

We report a new member to the family of tungsten nitrides, WN6, predicted from the structure search. Ground-state convex hull calculation reveals that crystalline WN6 is thermodynamically stable at pressures above 16 GPa, but remains dynamically stable at ambient conditions. The predicted high-pressure WN6 structure contains chaired \\text{cyclo-N}6{6-} rings isoelectronic to cyclo-hexasulfur (S6), which is unprecedented in nitrogen. In the \\text{cyclo-N}6{6-} unit all nitrogen atoms are singly bonded and therefore contain a high energy density. By means of efficiently packing the covalent-bonded species, WN6 is estimated to have extremely high Vickers hardness greater than 40 GPa at ambient conditions, placing it as one of the hardest materials. The present results reveal that WN6 may be used as a superhard material but simultaneously maintaining other desirable properties, which represents an interesting example of multifunctional materials.

Stability and Social-Behavioral Consequences of Toddlers' Inhibited Temperament and Parenting Behaviors.

ERIC Educational Resources Information Center

Rubin, Kenneth H.; Burgess, Kim B.; Hastings, Paul D.

2002-01-01

Used prospective longitudinal design to ascertain whether different types of behavioral inhibition were stable from toddler to preschool age, and whether inhibited temperament or parenting style predicted children's subsequent social/behavioral problems. Found that traditional and peer-social toddler inhibition predicted socially reticent behavior…

Precision Efficacy Analysis for Regression.

ERIC Educational Resources Information Center

Brooks, Gordon P.

When multiple linear regression is used to develop a prediction model, sample size must be large enough to ensure stable coefficients. If the derivation sample size is inadequate, the model may not predict well for future subjects. The precision efficacy analysis for regression (PEAR) method uses a cross- validity approach to select sample sizes…

PREDICTING SUSTAINABLE GROUND WATER TO CONSTRUCTED RIPARIAN WETLANDS: SHAKER TRACE, OHIO, USA

EPA Science Inventory

Water isotopy is introduced as a best management practice for the prediction of sustained ground water inflows to prospective constructed wetlands. A primer and application of the stable isotopes, ¹⁸O and ²H, are discussed for riparian wetland restoration ar...

Predicting non-linear dynamics by stable local learning in a recurrent spiking neural network.

PubMed

Gilra, Aditya; Gerstner, Wulfram

2017-11-27

The brain needs to predict how the body reacts to motor commands, but how a network of spiking neurons can learn non-linear body dynamics using local, online and stable learning rules is unclear. Here, we present a supervised learning scheme for the feedforward and recurrent connections in a network of heterogeneous spiking neurons. The error in the output is fed back through fixed random connections with a negative gain, causing the network to follow the desired dynamics. The rule for Feedback-based Online Local Learning Of Weights (FOLLOW) is local in the sense that weight changes depend on the presynaptic activity and the error signal projected onto the postsynaptic neuron. We provide examples of learning linear, non-linear and chaotic dynamics, as well as the dynamics of a two-link arm. Under reasonable approximations, we show, using the Lyapunov method, that FOLLOW learning is uniformly stable, with the error going to zero asymptotically.

Predicting non-linear dynamics by stable local learning in a recurrent spiking neural network

PubMed Central

Gerstner, Wulfram

2017-01-01

The brain needs to predict how the body reacts to motor commands, but how a network of spiking neurons can learn non-linear body dynamics using local, online and stable learning rules is unclear. Here, we present a supervised learning scheme for the feedforward and recurrent connections in a network of heterogeneous spiking neurons. The error in the output is fed back through fixed random connections with a negative gain, causing the network to follow the desired dynamics. The rule for Feedback-based Online Local Learning Of Weights (FOLLOW) is local in the sense that weight changes depend on the presynaptic activity and the error signal projected onto the postsynaptic neuron. We provide examples of learning linear, non-linear and chaotic dynamics, as well as the dynamics of a two-link arm. Under reasonable approximations, we show, using the Lyapunov method, that FOLLOW learning is uniformly stable, with the error going to zero asymptotically. PMID:29173280

Virtual Schooling: A Guide to Optimizing Your Child's Education

ERIC Educational Resources Information Center

Kanna, Elizabeth; Gillis, Lisa

2009-01-01

Today, millions of school-age children are learning outside of a traditional classroom and using cutting edge educational options. Policy experts predict that in a decade half of all education will be delivered virtually. In "Virtual Schooling" three top authorities help you navigate the fastest growing movement in education--regardless of whether…

Development of a special topics course on civil engineering project finance for the Zachry Department of Civil Engineering of Texas A&M University.

DOT National Transportation Integrated Search

2011-05-01

Experts predict that the highway trust fund will deteriorate rapidly over the course of the next several : years. This situation has led many state agencies to seek alternative financing methods that can meet both : social and economic needs. One pos...

Developmental Activities that Lead to Dropout and Investment in Sport

ERIC Educational Resources Information Center

Wall, Michael; Cote, Jean

2007-01-01

Background: Studies suggest that expert performance in sport is the result of long-term engagement in a highly specialized form of training termed deliberate practice. The relationship between accumulated deliberate practice and performance predicts that those who begin deliberate practice at a young age accumulate more practice hours over time…

Abstinence Self-Efficacy and Abstinence 1 Year After Substance Use Disorder Treatment

ERIC Educational Resources Information Center

Ilgen, Mark; McKellar, John; Tiet, Quyen

2005-01-01

To better understand the relationship between abstinence self-efficacy and treatment outcomes in substance use disorder patients, experts in the field need more information about the levels of abstinence self-efficacy most predictive of treatment outcomes. Participants (N = 2,967) from 15 residential substance use disorder treatment programs were…

Discursive "Policy Logics" of Mergers in US Higher Education: Strategy or Tragedy?

ERIC Educational Resources Information Center

Stephenson, Sandria S.

2011-01-01

Mergers are part of the historical fabric of US higher education. However, the current economic recession and other policy issues have experts and academicians predicting an increase in higher education mergers in the USA. Consequently, this study analysed the discursive "policy logics" surrounding merger negotiations in US higher…

Decision support systems for plant disease and insect management in commercial nurseries in the Midwest: A perspective review

USDA-ARS?s Scientific Manuscript database

Decision-support systems (DDSs) are techniques that help decision makers utilize models to solve problems under complex and uncertain conditions. Predicting conditions that warrant intervention is a key tenet of the concept of integrated pest management (IPM) with the use of expert systems and pest ...

Meaning as a Nonlinear Effect: The Birth of Cool

ERIC Educational Resources Information Center

Blommaert, Jan

2015-01-01

Saussurean and Chomskyan "conduit" views of meaning in communication, dominant in much of expert and lay linguistic semantics, presuppose a simple, closed and linear system in which outcomes can be predicted and explained in terms of finite sets of rules. Summarizing critical traditions of scholarship, notably those driven by Bateson's…

Synthesising empirical results to improve predictions of post-wildfire runoff and erosion response

Treesearch

Richard A. Shakesby; John A. Moody; Deborah A. Martin; Pete Robichaud

2016-01-01

Advances in research into wildfire impacts on runoff and erosion have demonstrated increasing complexity of controlling factors and responses, which, combined with changing fire frequency, present challenges for modellers. We convened a conference attended by experts and practitioners in post-wildfire impacts, meteorology and related research, including...

Causes and Management of Treatment-Resistant Panic Disorder and Agoraphobia: A Survey of Expert Therapists

ERIC Educational Resources Information Center

Sanderson, William C.; Bruce, Timothy J.

2007-01-01

Cognitive behavior therapy (CBT) is recognized as an effective psychological treatment for panic disorder (PD). Despite its efficacy, some clients do not respond optimally to this treatment. Unfortunately, literatures on the prediction, prevention, and management of suboptimal response are not well developed. Considering this lack of empirical…

Measuring Research Quality Using the Journal Impact Factor, Citations and "Ranked Journals": Blunt Instruments or Inspired Metrics?

ERIC Educational Resources Information Center

Jarwal, Som D.; Brion, Andrew M.; King, Maxwell L.

2009-01-01

This paper examines whether three bibliometric indicators--the journal impact factor, citations per paper and the Excellence in Research for Australia (ERA) initiative's list of "ranked journals"--can predict the quality of individual research articles as assessed by international experts, both overall and within broad disciplinary…

Tutoring Styles That Encourage Learner Satisfaction, Academic Engagement, and Achievement in an Online Environment

ERIC Educational Resources Information Center

Chae, Soo Eun; Shin, Jae-Han

2016-01-01

This study was aimed to find which tutoring styles significantly predict learners' satisfaction with an e-learning service, academic involvement, and academic achievement. The tutoring styles included subject expert, facilitator, guider, and administrator. In this study, 818 Korean sixth-grade students (ages 11-12 years), enrolled in the…

A Multidisciplined Teaching Reform of Biomaterials Course for Undergraduate Students

ERIC Educational Resources Information Center

Li, Xiaoming; Zhao, Feng; Pu, Fang; Liu, Haifeng; Niu, Xufeng; Zhou, Gang; Li, Deyu; Fan, Yubo; Feng, Qingling; Cui, Fu-zhai; Watari, Fumio

2015-01-01

The biomaterials science has advanced in a high speed with global science and technology development during the recent decades, which experts predict to be more obvious in the near future with a more significant position for medicine and health care. Although the three traditional subjects, such as medical science, materials science and biology…

Comparing Three Patterns of Strengths and Weaknesses Models for the Identification of Specific Learning Disabilities

ERIC Educational Resources Information Center

Miller, Daniel C.; Maricle, Denise E.; Jones, Alicia M.

2016-01-01

Processing Strengths and Weaknesses (PSW) models have been proposed as a method for identifying specific learning disabilities. Three PSW models were examined for their ability to predict expert identified specific learning disabilities cases. The Dual Discrepancy/Consistency Model (DD/C; Flanagan, Ortiz, & Alfonso, 2013) as operationalized by…

Assessing wildland fire risk transmission to communities in northern Spain

Treesearch

Fermín J. Alcasena; Michele Salis; Alan A. Ager; Rafael Castell; Cristina Vega-García

2017-01-01

We assessed potential economic losses and transmission to residential houses from wildland fires in a rural area of central Navarra (Spain). Expected losses were quantified at the individual structure level (n = 306) in 14 rural communities by combining fire model predictions of burn probability and fire intensity with susceptibility functions derived from expert...

Chunks in expert memory: evidence for the magical number four ... or is it two?

PubMed

Gobet, Fernand; Clarkson, Gary

2004-11-01

This study aims to test the divergent predictions of the chunking theory (Chase & Simon, 1973) and template theory (Gobet & Simon, 1996a, 2000) with respect to the number of chunks held in visual short-term memory and the size of chunks used by experts. We presented game and random chessboards in both a copy and a recall task. In a within-subject design, the stimuli were displayed using two presentation media: (a) physical board and pieces, as in Chase and Simon's (1973) study; and (b) a computer display, as in Gobet and Simon's (1998) study. Results show that, in most cases, no more than three chunks were replaced in the recall task, as predicted by template theory. In addition, with game positions in the computer condition, chess Masters replaced very large chunks (up to 15 pieces), again in line with template theory. Overall, the results suggest that the original chunking theory overestimated short-term memory capacity and underestimated the size of chunks used, in particular with Masters. They also suggest that Cowan's (2001) proposal that STM holds four chunks may be an overestimate.

[Locally advanced head and neck cancers: recommendations of an expert panel and perspectives for the use of TPF regimen (docetaxel, cisplatin and fluoro-uracil) as induction therapy].

PubMed

Bardet, E; Bourhis, J; Cals, L; Fayette, J; Guigay, J; Hans, S; Saint-Guily, J Lacau; Lagarde, F; Lallemant, B; Milano, G; Rolland, F; Lefebvre, J-L

2009-10-01

The purpose of the present article was to evaluate indications, regimens, treatment modalities, and predictive factors of response to treatment in locally advanced squamous cell carcinoma of the head and neck (SCCHN). An expert panel including otolaryngology and head and neck surgery specialists, oncologists, radiotherapists and biologists analyzed the literature providing a synthesis and giving some recommendations. Findings from the main randomized phase III trials highlight that the TPF regimen (docetaxel, cisplatin, fluorouracil) represent a preferential option when induction chemotherapy is indicated in either operable or non-operable patients. Given the potential fragility of patients presenting with SCCHN, treatment modalities in routine use require applying preventive measures and tailored follow-up according to each patient's profile. As regards predictive factors of response to TPF regimen, no factor is currently validated, but ongoing trials should provide better knowledge. Progresses in induction chemotherapy have allowed improving the prognosis of patients with locally advanced SCCHN. The TPF regimen represents a major improvement in this indication, and ongoing strategic clinical trials should refine its indications.

Musical Expertise and the Ability to Imagine Loudness

PubMed Central

Bishop, Laura; Bailes, Freya; Dean, Roger T.

2013-01-01

Most perceived parameters of sound (e.g. pitch, duration, timbre) can also be imagined in the absence of sound. These parameters are imagined more veridically by expert musicians than non-experts. Evidence for whether loudness is imagined, however, is conflicting. In music, the question of whether loudness is imagined is particularly relevant due to its role as a principal parameter of performance expression. This study addressed the hypothesis that the veridicality of imagined loudness improves with increasing musical expertise. Experts, novices and non-musicians imagined short passages of well-known classical music under two counterbalanced conditions: 1) while adjusting a slider to indicate imagined loudness of the music and 2) while tapping out the rhythm to indicate imagined timing. Subtests assessed music listening abilities and working memory span to determine whether these factors, also hypothesised to improve with increasing musical expertise, could account for imagery task performance. Similarity between each participant’s imagined and listening loudness profiles and reference recording intensity profiles was assessed using time series analysis and dynamic time warping. The results suggest a widespread ability to imagine the loudness of familiar music. The veridicality of imagined loudness tended to be greatest for the expert musicians, supporting the predicted relationship between musical expertise and musical imagery ability. PMID:23460791

Musical expertise and the ability to imagine loudness.

PubMed

Bishop, Laura; Bailes, Freya; Dean, Roger T

2013-01-01

Most perceived parameters of sound (e.g. pitch, duration, timbre) can also be imagined in the absence of sound. These parameters are imagined more veridically by expert musicians than non-experts. Evidence for whether loudness is imagined, however, is conflicting. In music, the question of whether loudness is imagined is particularly relevant due to its role as a principal parameter of performance expression. This study addressed the hypothesis that the veridicality of imagined loudness improves with increasing musical expertise. Experts, novices and non-musicians imagined short passages of well-known classical music under two counterbalanced conditions: 1) while adjusting a slider to indicate imagined loudness of the music and 2) while tapping out the rhythm to indicate imagined timing. Subtests assessed music listening abilities and working memory span to determine whether these factors, also hypothesised to improve with increasing musical expertise, could account for imagery task performance. Similarity between each participant's imagined and listening loudness profiles and reference recording intensity profiles was assessed using time series analysis and dynamic time warping. The results suggest a widespread ability to imagine the loudness of familiar music. The veridicality of imagined loudness tended to be greatest for the expert musicians, supporting the predicted relationship between musical expertise and musical imagery ability.

Development and testing of a cancer appetite and symptom questionnaire.

PubMed

Halliday, V; Porock, D; Arthur, A; Manderson, C; Wilcock, A

2012-06-01

Poor appetite and weight loss are common in patients with cancer, contributing to an increase in morbidity and mortality. Early identification of those at greatest risk is problematic. The Council on Nutrition Appetite Questionnaire (CNAQ) is short and easy to use, although it is not specific to cancer populations. The present study aimed to build on the CNAQ to develop a cancer appetite and symptom questionnaire (CASQ) for predicting weight loss in patients with cancer. The content validity of the CNAQ was assessed by an expert panel (n = 41) using the content validity index (CVI). The resulting CASQ was tested for reliability among patients receiving radiotherapy (n = 34). Predictive validity of the CASQ was determined in patients with lung or upper gastrointestinal cancer (n = 185), comparing CASQ scores (possible range 0-48) recorded at baseline with percentage weight change after 12 weeks.  In all but one CNAQ item, the CVI was above the minimum level of agreement (>0.70). Comments from expert panel members led to minor modifications and the introduction of new items resulting in the 12-item CASQ. The intraclass correlation coefficient of the CASQ was 0.80 [95% confidence interval (CI) = 0.68-0.92] and the difference between total scores at two time points was -0.20 (95% CI = -1.21 to 0.80). The optimum cut-off point of the instrument to predict >10% weight loss was 29/30 (area under curve = 0.75; sensitivity 71%, specificity 66%, positive predictive value 19%, negative predictive value 95%) [Correction added on 30 April 2012, after first online publication: in the preceding sentence, <10% was corrected to >10%]. The CASQ can predict weight loss among patients with lung and upper gastrointestinal cancer. Acknowledgment of the low positive predictive value is needed if the instrument is to be used within clinical practice. © 2012 The Authors. Journal of Human Nutrition and Dietetics © 2012 The British Dietetic Association Ltd.

“Ipsilateral, high, single-hand, sideways”—Ruijin rule for camera assistant in uniportal video-assisted thoracoscopic surgery

PubMed Central

Gao, Taotao; Xiang, Jie; Jin, Runsen; Zhang, Yajie; Wu, Han

2016-01-01

Camera assistant plays a very important role in uniportal video-assisted thoracoscopic surgery (VATS), who acts as the eye of the surgeon, providing the VATS team with a stable and clear operating view. Thus, a good assistant should cooperate with surgeon and manipulate the camera expertly, to ensure eye-hand coordination. We have performed more than 100 uniportal VATS in the Department Of Thoracic Surgery in Ruijin Hospital. Based on our experiences, we summarized the method of holding camera, known as “ipsilateral, high, single-hand, sideways”, which largely improves the comfort and fluency of surgery. PMID:27867573

Molecular structures of carotenoids as predicted by MNDO-AM1 molecular orbital calculations

NASA Astrophysics Data System (ADS)

Hashimoto, Hideki; Yoda, Takeshi; Kobayashi, Takayoshi; Young, Andrew J.

2002-02-01

Semi-empirical molecular orbital calculations using AM1 Hamiltonian (MNDO-AM1 method) were performed for a number of biologically important carotenoid molecules, namely all- trans-β-carotene, all- trans-zeaxanthin, and all- trans-violaxanthin (found in higher plants and algae) together with all- trans-canthaxanthin, all- trans-astaxanthin, and all- trans-tunaxanthin in order to predict their stable structures. The molecular structures of all- trans-β-carotene, all- trans-canthaxanthin, and all- trans-astaxanthin predicted based on molecular orbital calculations were compared with those determined by X-ray crystallography. Predicted bond lengths, bond angles, and dihedral angles showed an excellent agreement with those determined experimentally, a fact that validated the present theoretical calculations. Comparison of the bond lengths, bond angles and dihedral angles of the most stable conformer among all the carotenoid molecules showed that the displacements are localized around the substituent groups and hence around the cyclohexene rings. The most stable conformers of all- trans-zeaxanthin and all- trans-violaxanthin gave rise to a torsion angle around the C6-C7 bond to be ±48.7 and -84.8°, respectively. This difference is a key factor in relation to the biological function of these two carotenoids in plants and algae (the xanthophyll cycle). Further analyses by calculating the atomic charges and using enpartment calculations (division of bond energies between component atoms) were performed to ascribe the cause of the different observed torsion angles.

Acoustic Cavitation-Based Monitoring of the Reversibility and Permeability of Ultrasound-Induced Blood-Brain Barrier Opening

PubMed Central

Sun, Tao; Samiotaki, Gesthimani; Wang, Shutao; Acosta, Camilo; Chen, Cherry C.; Konofagou, Elisa E.

2015-01-01

Cavitation events seeded by microbubbles have been previously reported to be associated with MR- or fluorescent-contrast enhancement after focused ultrasound (FUS)-induced blood-brain barrier (BBB) opening. However, it is still unknown whether bubble activity can be correlated with the reversibility (the duration of opening and the likelihood of safe reinstatement) and the permeability of opened BBB, which is critical for the clinical translation of using passive cavitation detection to monitor, predict and control the opening. In this study, the dependence of acoustic cavitation on the BBB opening duration, permeability coefficient and histological damage occurrence were thus investigated. Transcranial pulsed FUS at 1.5 MHz in the presence of systemically circulating microbubbles was applied in the mouse hippocampi (n = 60). The stable and inertial cavitation activities were monitored during sonication. Contrast-enhanced MRI was performed immediately after sonication and every 24 h up to 6 days thereafter, to assess BBB opening, brain tissue permeability and potential edema. Histological evaluations were used to assess the occurrence of neurovascular damages. It was found that stable cavitation was well correlated with: 1) the duration of the BBB opening (r2 = 0.77); 2) the permeability of the opened BBB (r2 = 0.82); 3) the likelihood of safe opening (P < 0.05, safe opening compared to cases of damage; P < 0.0001, no opening compared to safe opening). The inertial cavitation dose was correlated with the resulting BBB permeability (r2 = 0.72). Stable cavitation was found to be more reliable than inertial cavitation at assessing the BBB opening within the pressure range used in this study. This study demonstrates that the stable cavitation response during BBB opening holds promise for predicting and controlling the restoration and pharmacokinetics of FUS-opened BBB. The stable cavitation response therefore showed great promise in predicting the BBB opening duration, enabling thus control of opening according to the drug circulation time. In addition, avoiding adverse effects in the brain and assessing the pharmacokinetics of the compounds delivered can also be achieved by monitoring and controlling the stable cavitation emissions. PMID:26562661

Stability of lava lakes

NASA Astrophysics Data System (ADS)

Witham, Fred; Llewellin, Edward W.

2006-11-01

A physical model of a generic lava lake system is developed. We derive the requisite conditions for the existence of an 'equilibrium lava lake' in which magmastatic pressure at the base of the conduit balances the pressure in the underlying magmatic reservoir. The stability of this lava lake system is tested by investigating the response of the system to perturbation. We develop a graphical method, based on the system's pressure-depth profile, to predict the subsequent behaviour of the system. Despite the simplicity of the modelled system, we find a broad behavioural spectrum. Initially, the rise of bubbles through the magma is ignored. In this case, both stable, long-lived lava lakes, and unstable lakes that are prone to sudden draining, are predicted. The stability of the system is shown to be controlled by lake-conduit geometry, the solubility and gas expansion laws and the magma's volatile content. We show that an unstable lake must collapse to a new, stable equilibrium. Subsequent recharge of the system by, for example, conduit overturn, would promote a return to the original equilibrium, giving rise to cyclic behaviour. Such a mechanism is consistent with lava lake behaviour during the 1983-1984 Pu'u 'O'o eruption of Kilauea. When the rise of bubbles through the magma is considered, our model predicts that stable lakes must drain over time. We, therefore, deduce that persistently degassing, stable lava lakes, such as those observed at Mt. Erebus, Antarctica, and Mauna Ulu, Kilauea, Hawaii, must have an effective conduit convection mechanism or an exogenous supply of bubbles from depth.

Stable-isotope fingerprints of biological agents as forensic tools.

PubMed

Horita, Juske; Vass, Arpad A

2003-01-01

Naturally occurring stable isotopes of light elements in chemical and biological agents may possess unique "stable-isotope fingerprints" depending on their sources and manufacturing processes. To test this hypothesis, two strains of bacteria (Bacillus globigii and Erwinia agglomerans) were grown under controlled laboratory conditions. We observed that cultured bacteria cells faithfully inherited the isotopic composition (hydrogen, carbon, and nitrogen) of media waters and substrates in predictable manners in terms of bacterial metabolism and that even bacterial cells of the same strain, which grew in media water and substrates of different isotopic compositions, have readily distinguishable isotopic signatures. These "stable-isotopic fingerprints" of chemical and biological agents can be used as forensic tools in the event of biochemical terrorist attacks.

Autonomous orientation predicts longevity: New findings from the Nun Study.

PubMed

Weinstein, Netta; Legate, Nicole; Ryan, William S; Hemmy, Laura

2018-03-10

Work on longevity has found protective social, cognitive, and emotional factors, but to date we have little understanding of the impact of motivational dynamics. Autonomy orientation, or stable patterns of self-regulation, is theorized to be a protective factor for long-term mental and physical health (Ryan & Deci, 2017), and it is therefore a prime candidate for examining how stable psychosocial factors are linked to longevity, or life expectancy. Essays written in the 1930s by participants in the Nun Study were coded for indicators of an autonomy orientation. These were selected in line with an extensive theoretical literature based in self-determination theory (Deci & Ryan, 1985). Essays were coded for the propensity for choice in action, susceptibility to pressure, self-reflection, integration of experiences, and parental support for autonomy. These coded variables were used to predict age of death. Using 176 codable essays provided by now-deceased participants, linear regression analyses revealed that choiceful behavior, self-reflection, and parent autonomy support predicted age of death. Participants who demonstrated these stable and beneficial motivational characteristics lived longer. Personality constructs reflecting a healthy form of self-regulation are associated with long-term health. Implications for health interventions are discussed. © 2018 The Authors. Journal of Personality Published by Wiley Periodicals, Inc.

Intermittent Turbulence in the Stable Boundary Layer over Land. Part III: A Classification for Observations during CASES-99.

NASA Astrophysics Data System (ADS)

van de Wiel, B. J. H.; Moene, A. F.; Hartogensis, O. K.; de Bruin, H. A. R.; Holtslag, A. A. M.

2003-10-01

In this paper a classification of stable boundary layer regimes is presented based on observations of near-surface turbulence during the Cooperative Atmosphere-Surface Exchange Study-1999 (CASES-99). It is found that the different nights can be divided into three subclasses: a turbulent regime, an intermittent regime, and a radiative regime, which confirms the findings of two companion papers that use a simplified theoretical model (it is noted that its simpliflied structure limits the model generality to near-surface flows). The papers predict the occurrence of stable boundary layer regimes in terms of external forcing parameters such as the (effective) pressure gradient and radiative forcing. The classification in the present work supports these predictions and shows that the predictions are robust in a qualitative sense. As such, it is, for example, shown that intermittent turbulence is most likely to occur in clear-sky conditions with a moderately weak effective pressure gradient. The quantitative features of the theoretical classification are, however, rather sensitive to (often uncertain) local parameter estimations, such as the bulk heat conductance of the vegetation layer. This sensitivity limits the current applicability of the theoretical classification in a strict quantitative sense, apart from its conceptual value.

Prognostic evaluation of febrile neutropenia in apparently stable adult cancer patients

PubMed Central

Carmona-Bayonas, A; Gómez, J; González-Billalabeitia, E; Canteras, M; Navarrete, A; Gonzálvez, M L; Vicente, V; Ayala de la Peña, F

2011-01-01

Background: Predictive models to identify low-risk febrile neutropenia (FN) have been developed with heterogeneous samples, which included stable and unstable patients, solid tumours, acute leukaemia and bone marrow transplantation. These models fail to recognise 5–15% of cases with unexpected complications, and literature specifically addressing apparently stable patients (ASPs) is scarce. Methods: We reviewed 861 episodes of FN in outpatients with solid tumours, including 692 (80%) episodes with apparent clinical stability. We aimed to investigate the prognosis of this latter group and explore the possibility of stratifying it according to the presenting features. A case–control study was performed and the MASCC index was evaluated. Results: The rates of complications and bacteraemia in ASPs were 7.3% and 6.2%, respectively. The MASCC index yielded a low sensitivity to detect complications (36%). Prognostic factors were identified: ECOG performance status ⩾2, chronic bronchitis, chronic heart failure, stomatitis NCI grade ⩾2, monocytes <200 mm−3 and stress hyperglycaemia. Conclusion: A very simple assessment is useful to classify the patients with FN according to the risk of complications. A few additional variables may predict the clinical course of the patients. We additionally show that the MASCC index applied to this specific group has a low sensitivity to predict complications. PMID:21811253

Seasonally Varying Predation Behavior and Climate Shifts Are Predicted to Affect Predator-Prey Cycles.

PubMed

Tyson, Rebecca; Lutscher, Frithjof

2016-11-01

The functional response of some predator species changes from a pattern characteristic for a generalist to that for a specialist according to seasonally varying prey availability. Current theory does not address the dynamic consequences of this phenomenon. Since season length correlates strongly with altitude and latitude and is predicted to change under future climate scenarios, including this phenomenon in theoretical models seems essential for correct prediction of future ecosystem dynamics. We develop and analyze a two-season model for the great horned owl (Bubo virginialis) and snowshoe hare (Lepus americanus). These species form a predator-prey system in which the generalist to specialist shift in predation pattern has been documented empirically. We study the qualitative behavior of this predator-prey model community as summer season length changes. We find that relatively small changes in summer season length can have a profound impact on the system. In particular, when the predator has sufficient alternative resources available during the summer season, it can drive the prey to extinction, there can be coexisting stable states, and there can be stable large-amplitude limit cycles coexisting with a stable steady state. Our results illustrate that the impacts of global change on local ecosystems can be driven by internal system dynamics and can potentially have catastrophic consequences.

Science in 60 – Tabletop Fire Prediction

ScienceCinema

Cary, Lyle

2018-01-16

At the Interagency Fire Center at Los Alamos National Laboratory, experts rely on the state-of-the-art Simtable to help them predict the unpredictable. With algorithms that include camera-based object-tracking and projection developed by the Laboratory, the emergency operations team can simulate a wildland fire spreading across any terrain. The table system, developed and marketed by Simtable, a Santa Fe, N.M., company, takes into account weather, vegetation and fuel conditions. The project also received funding from the LANS Venture Acceleration Fund to improve the user interface.

Science in 60 – Tabletop Fire Prediction

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

Cary, Lyle

At the Interagency Fire Center at Los Alamos National Laboratory, experts rely on the state-of-the-art Simtable to help them predict the unpredictable. With algorithms that include camera-based object-tracking and projection developed by the Laboratory, the emergency operations team can simulate a wildland fire spreading across any terrain. The table system, developed and marketed by Simtable, a Santa Fe, N.M., company, takes into account weather, vegetation and fuel conditions. The project also received funding from the LANS Venture Acceleration Fund to improve the user interface.

Assessing risk factors for early hip osteoarthritis in activity-related hip pain: a Delphi study

PubMed Central

Jackson, K A; Glyn-Jones, S; Batt, M E; Arden, N K; Newton, J L

2015-01-01

Objective Hip pain and injury as a result of activity can lead to the development of early hip osteoarthritis (OA) in susceptible individuals. Our understanding of the factors that increase susceptibility continues to evolve. The ability to clearly identify individuals (and cohorts) with activity-related hip pain who are at risk of early hip OA is currently lacking. The purpose of this study was to gain expert consensus on which key clinical measures might help predict the risk of early hip OA in individuals presenting with activity-related hip pain. The agreed measures would constitute a standardised approach to initial clinical assessment to help identify these individuals. Methods This Dephi study used online surveys to gain concordance of expert opinion in a structured process of ‘rounds’. In this study, we asked ‘What outcome measures are useful in predicting hip OA in activity-related hip pain?’ The Delphi panel consisted of experts from sport and exercise medicine, orthopaedics, rheumatology, physiotherapy and OA research. Results The study identified key clinical measures in the history, examination and investigations (plain anteroposterior radiograph and femoroacetabular impingement views) that the panel agreed would be useful in predicting future risk of hip OA when assessing activity-related hip pain. The panel also agreed that certain investigations and tests (eg, MR angiography) did not currently have a role in routine assessment. There was a lack of consensus regarding the role of MRI, patient-reported outcome measures (PROMs) and certain biomechanical and functional assessments. Conclusions We provide a standardised approach to the clinical assessment of patients with activity-related hip pain. Assessment measures rejected by the Delphi panel were newer, more expensive investigations that currently lack evidence. Assessment measures that did not reach consensus include MRI and PROMs. Their role remains ambiguous and would benefit from further research. PMID:26419679

An early validation of the Society for Vascular Surgery lower extremity threatened limb classification system.

PubMed

Cull, David L; Manos, Ginger; Hartley, Michael C; Taylor, Spence M; Langan, Eugene M; Eidt, John F; Johnson, Brent L

2014-12-01

The Society for Vascular Surgery (SVS) recently established the Lower Extremity Threatened Limb Classification System, a staging system using Wound characteristic, Ischemia, and foot Infection (WIfI) to stratify the risk for limb amputation at 1 year. Although intuitive in nature, this new system has not been validated. The purpose of the following study was to determine whether the WIfI system is predictive of limb amputation and wound healing. Between 2007 and 2010, we prospectively obtained data related to wound characteristics, extent of infection, and degree of postrevascularization ischemia in 139 patients with foot wounds who presented for lower extremity revascularization (158 revascularization procedures). After adapting those data to the WIfI classifications, we analyzed the influence of wound characteristics, extent of infection, and degree of ischemia on time to wound healing; empirical Kaplan-Meier survival curves were compared with theoretical outcomes predicted by WIfI expert consensus opinion. Of the 158 foot wounds, 125 (79%) healed. The median time to wound healing was 2.7 months (range, 1-18 months). Factors associated with wound healing included presence of diabetes mellitus (P = .013), wound location (P = .049), wound size (P = .007), wound depth (P = .004), and degree of ischemia (P < .001). The WIfI clinical stage was predictive of 1-year limb amputation (stage 1, 3%; stage 2, 10%; stage 3, 23%; stage 4, 40%) and wound nonhealing (stage 1, 8%; stage 2, 10%; stage 3, 23%; stage 4, 40%) and correlated with the theoretical outcome estimated by the SVS expert panel. The theoretical framework for risk stratification among patients with critical limb ischemia provided by the SVS expert panel appears valid. Further validation of the WIfI classification system with multicenter data is justified. Copyright © 2014 Society for Vascular Surgery. Published by Elsevier Inc. All rights reserved.

Predicting the Benefits of Percutaneous Coronary Intervention on 1-Year Angina and Quality of Life in Stable Ischemic Heart Disease: Risk Models From the COURAGE Trial (Clinical Outcomes Utilizing Revascularization and Aggressive Drug Evaluation).

PubMed

Zhang, Zugui; Jones, Philip; Weintraub, William S; Mancini, G B John; Sedlis, Steven; Maron, David J; Teo, Koon; Hartigan, Pamela; Kostuk, William; Berman, Daniel; Boden, William E; Spertus, John A

2018-05-01

Percutaneous coronary intervention (PCI) is a therapy to reduce angina and improve quality of life in patients with stable ischemic heart disease. However, it is unclear whether the quality of life after PCI is more dependent on the PCI or other patient-related factors. To address this question, we created models to predict angina and quality of life 1 year after PCI and medical therapy. Using data from the 2287 stable ischemic heart disease patients randomized in the COURAGE trial (Clinical Outcomes Utilizing Revascularization and Aggressive Drug Evaluation) to PCI plus optimal medical therapy (OMT) versus OMT alone, we built prediction models for 1-year Seattle Angina Questionnaire angina frequency, physical limitation, and quality of life scores, both as continuous outcomes and categorized by clinically desirable states, using multivariable techniques. Although most patients improved regardless of treatment, marked variability was observed in Seattle Angina Questionnaire scores 1 year after randomization. Adding PCI conferred a greater mean improvement (about 2 points) in Seattle Angina Questionnaire scores that were not affected by patient characteristics ( P values for all interactions >0.05). The proportion of patients free of angina or having very good/excellent physical limitation (physical function) or quality of life at 1 year was 57%, 58%, 66% with PCI+OMT and 50%, 55%, 59% with OMT alone group, respectively. However, other characteristics, such as baseline symptoms, age, diabetes mellitus, and the magnitude of myocardium subtended by narrowed coronary arteries were as, or more, important than revascularization in predicting symptoms (partial R 2 =0.07 versus 0.29, 0.03 versus 0.22, and 0.05 versus 0.24 in the domain of angina frequency, physical limitation, and quality of life, respectively). There was modest/good discrimination of the models (C statistic=0.72-0.82) and excellent calibration (coefficients of determination for predicted versus observed deciles=0.83-0.97). The health status outcomes of stable ischemic heart disease patients treated by OMT+PCI versus OMT alone can be predicted with modest accuracy. Angina and quality of life at 1 year is improved by PCI but is more strongly associated with other patient characteristics. URL: https://www.clinicaltrials.gov. Unique identifier: NCT00007657. © 2018 American Heart Association, Inc.

NetMHCstab – predicting stability of peptide–MHC-I complexes; impacts for cytotoxic T lymphocyte epitope discovery

PubMed Central

Jørgensen, Kasper W; Rasmussen, Michael; Buus, Søren; Nielsen, Morten

2014-01-01

Major histocompatibility complex class I (MHC-I) molecules play an essential role in the cellular immune response, presenting peptides to cytotoxic T lymphocytes (CTLs) allowing the immune system to scrutinize ongoing intracellular production of proteins. In the early 1990s, immunogenicity and stability of the peptide–MHC-I (pMHC-I) complex were shown to be correlated. At that time, measuring stability was cumbersome and time consuming and only small data sets were analysed. Here, we investigate this fairly unexplored area on a large scale compared with earlier studies. A recent small-scale study demonstrated that pMHC-I complex stability was a better correlate of CTL immunogenicity than peptide–MHC-I affinity. We here extended this study and analysed a total of 5509 distinct peptide stability measurements covering 10 different HLA class I molecules. Artificial neural networks were used to construct stability predictors capable of predicting the half-life of the pMHC-I complex. These predictors were shown to predict T-cell epitopes and MHC ligands from SYFPEITHI and IEDB to form significantly more stable MHC-I complexes compared with affinity-matched non-epitopes. Combining the stability predictions with a state-of-the-art affinity predictions NetMHCcons significantly improved the performance for identification of T-cell epitopes and ligands. For the HLA alleles included in the study, we could identify distinct sub-motifs that differentiate between stable and unstable peptide binders and demonstrate that anchor positions in the N-terminal of the binding motif (primarily P2 and P3) play a critical role for the formation of stable pMHC-I complexes. A webserver implementing the method is available at http://www.cbs.dtu.dk/services/NetMHCstab. PMID:23927693

Predictors of need for noninvasive ventilation during respiratory tract infections in medically stable, non-ventilated subjects with amyotrophic lateral sclerosis.

PubMed

Sancho, Jesus; Servera, Emilio; Bañuls, Pilar; Marin, Julio

2015-04-01

Acute lower respiratory infections can impair muscle strength in patients with amyotrophic lateral sclerosis (ALS). When associated with an increase in load on the respiratory system, this situation may precipitate hypercapnic respiratory failure in non-ventilated patients with ALS. The aim of this study was to determine whether a clinical or functional parameter can predict the need for noninvasive ventilation (NIV) during an acute respiratory infection for medically stable, non-ventilated patients with ALS. This was a prospective study involving all non-ventilated subjects with ALS admitted due to an acute respiratory infection to a respiratory care unit from a tertiary hospital. Thirty-two non-ventilated subjects with ALS were admitted to our respiratory care unit due to an acute respiratory infection: 60.72 ± 10.54 y, 13 males, 23 with spinal onset, FVC of 1.58 ± 0.83 L, FVC of 56.21 ± 23.15% of predicted, peak cough flow of 3.41 ± 1.77 L/s, maximum insufflation capacity of 1.87 ± 0.94 L, revised Amyotrophic Lateral Sclerosis Functional Rating Scale score of 22.80 ± 8.83, and Norris bulbar score of 23.48 ± 12.14. Fifteen subjects required NIV during the episode. Logistic regression analysis showed that the only predictors of need for NIV were percent-of-predicted FVC (odds ratio of 1.06, 95% CI 1.01-1.11, P = .02) and peak cough flow (odds ratio of 2.57, 95% CI 1.18-5.59, P = .02). In medically stable, non-ventilated patients with ALS, measurement of percent-of-predicted FVC and peak cough flow can predict the need for NIV during an acute lower respiratory tract infection. Copyright © 2015 by Daedalus Enterprises.

Risk prediction in stable cardiovascular disease using a high-sensitivity cardiac troponin T single biomarker strategy compared to the ESC-SCORE.

PubMed

Biener, Moritz; Giannitsis, Evangelos; Kuhner, Manuel; Zelniker, Thomas; Mueller-Hennessen, Matthias; Vafaie, Mehrshad; Stoyanov, Kiril M; Neumann, Franz-Josef; Katus, Hugo A; Hochholzer, Willibald; Valina, Christian Marc

2018-01-01

To evaluate the prognostic performance of high-sensitivity cardiac troponin T (hs-cTnT) compared with the ESC-SCORE. We included low-risk outpatients with stable cardiovascular (CV) disease categorised into need for non-secondary and secondary prevention. The prognostication of hs-cTnT at index visit was compared with the European Society of Cardiology-Systematic COronary Risk Evaluation (ESC-SCORE) with respect to all-cause mortality (ACM) and two composite endpoints (ACM, acute myocardial infarction (AMI) and stroke and ACM, AMI, stroke and rehospitalisation for acute coronary syndrome (ACS) and decompensated heart failure (DHF)). Within a median follow-up of 796 days, a total of 16 deaths, 32 composite endpoints of ACM, AMI and stroke and 83 composite endpoints of ACM, AMI, stroke, rehospitalisation for ACS and DHF were observed among 693 stable low-risk outpatients. Using C-statistics, measurement of hs-cTnT alone outperformed the ESC-SCORE for the prediction of ACM in the entire study population (Δarea under the curve (AUC) 0.221, p=0.0039) and both prevention groups (non-secondary: ΔAUC 0.164, p=0.0208; secondary: ΔAUC 0.264, p=0.0134). For the prediction of all other secondary endpoints, hs-cTnT was at least as effective as the ESC-SCORE, both in secondary and non-secondary prevention. Using continuous and categorical net reclassification improvement and integrated discrimination improvement, hs-cTnT significantly improved reclassification regarding all endpoints in the entire population and in the secondary prevention cohort. In non-secondary prevention, hs-cTnT improved reclassification only for ACM. The results were confirmed in an independent external cohort on 2046 patients. Hs-cTnT is superior to the multivariable ESC-SCORE for the prediction of ACM and a composite endpoint in stable outpatients with and without relevant CV disease. NCT01954303; Pre-results.

A Test of Carbon and Oxygen Stable Isotope Ratio Process Models in Tree Rings.

NASA Astrophysics Data System (ADS)

Roden, J. S.; Farquhar, G. D.

2008-12-01

Stable isotopes ratios of carbon and oxygen in tree ring cellulose have been used to infer environmental change. Process-based models have been developed to clarify the potential of historic tree ring records for meaningful paleoclimatic reconstructions. However, isotopic variation can be influenced by multiple environmental factors making simplistic interpretations problematic. Recently, the dual isotope approach, where the variation in one stable isotope ratio (e.g. oxygen) is used to constrain the interpretation of variation in another (e.g. carbon), has been shown to have the potential to de-convolute isotopic analysis. However, this approach requires further testing to determine its applicability for paleo-reconstructions using tree-ring time series. We present a study where the information needed to parameterize mechanistic models for both carbon and oxygen stable isotope ratios were collected in controlled environment chambers for two species (Pinus radiata and Eucalyptus globulus). The seedlings were exposed to treatments designed to modify leaf temperature, transpiration rates, stomatal conductance and photosynthetic capacity. Both species were grown for over 100 days under two humidity regimes that differed by 20%. Stomatal conductance was significantly different between species and for seedlings under drought conditions but not between other treatments or humidity regimes. The treatments produced large differences in transpiration rate and photosynthesis. Treatments that effected photosynthetic rates but not stomatal conductance influenced carbon isotope discrimination more than those that influenced primarily conductance. The various treatments produced a range in oxygen isotope ratios of 7 ‰. Process models predicted greater oxygen isotope enrichment in tree ring cellulose than observed. The oxygen isotope ratios of bulk leaf water were reasonably well predicted by current steady-state models. However, the fractional difference between models that predict bulk leaf water versus the site of evaporation did not increase with transpiration rates. In conclusion, although the dual isotope approach may better constrain interpretation of isotopic variation, more work is required before its predictive power can be applied to tree-ring archives.

Potential application of machine vision technology to saffron (Crocus sativus L.) quality characterization.

PubMed

Kiani, Sajad; Minaei, Saeid

2016-12-01

Saffron quality characterization is an important issue in the food industry and of interest to the consumers. This paper proposes an expert system based on the application of machine vision technology for characterization of saffron and shows how it can be employed in practical usage. There is a correlation between saffron color and its geographic location of production and some chemical attributes which could be properly used for characterization of saffron quality and freshness. This may be accomplished by employing image processing techniques coupled with multivariate data analysis for quantification of saffron properties. Expert algorithms can be made available for prediction of saffron characteristics such as color as well as for product classification. Copyright © 2016. Published by Elsevier Ltd.

A stable compound of helium and sodium at high pressure

DOE PAGES

Dong, Xiao; Oganov, Artem R.; Goncharov, Alexander F.; ...

2017-02-06

Helium is generally understood to be chemically inert and this is due to its extremely stable closed-shell electronic configuration, zero electron affinity and an unsurpassed ionization potential. It is not known to form thermodynamically stable compounds, except a few inclusion compounds. Here, using the ab initio evolutionary algorithm USPEX and subsequent high-pressure synthesis in a diamond anvil cell, we report the discovery of a thermodynamically stable compound of helium and sodium, Na 2He, which has a fluorite-type structure and is stable at pressures >113 GPa. We show that the presence of He atoms causes strong electron localization and makes thismore » material insulating. This phase is an electride, with electron pairs localized in interstices, forming eight-centre two-electron bonds within empty Na 8 cubes. As a result, we also predict the existence of Na 2HeO with a similar structure at pressures above 15 GPa.« less

A stable compound of helium and sodium at high pressure

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

Dong, Xiao; Oganov, Artem R.; Goncharov, Alexander F.

Helium is generally understood to be chemically inert and this is due to its extremely stable closed-shell electronic configuration, zero electron affinity and an unsurpassed ionization potential. It is not known to form thermodynamically stable compounds, except a few inclusion compounds. Here, using the ab initio evolutionary algorithm USPEX and subsequent high-pressure synthesis in a diamond anvil cell, we report the discovery of a thermodynamically stable compound of helium and sodium, Na 2He, which has a fluorite-type structure and is stable at pressures >113 GPa. We show that the presence of He atoms causes strong electron localization and makes thismore » material insulating. This phase is an electride, with electron pairs localized in interstices, forming eight-centre two-electron bonds within empty Na 8 cubes. We also predict the existence of Na 2HeO with a similar structure at pressures above 15 GPa.« less

A stable compound of helium and sodium at high pressure

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

Dong, Xiao; Oganov, Artem R.; Goncharov, Alexander F.

Helium is generally understood to be chemically inert and this is due to its extremely stable closed-shell electronic configuration, zero electron affinity and an unsurpassed ionization potential. It is not known to form thermodynamically stable compounds, except a few inclusion compounds. Here, using the ab initio evolutionary algorithm USPEX and subsequent high-pressure synthesis in a diamond anvil cell, we report the discovery of a thermodynamically stable compound of helium and sodium, Na 2He, which has a fluorite-type structure and is stable at pressures >113 GPa. We show that the presence of He atoms causes strong electron localization and makes thismore » material insulating. This phase is an electride, with electron pairs localized in interstices, forming eight-centre two-electron bonds within empty Na 8 cubes. As a result, we also predict the existence of Na 2HeO with a similar structure at pressures above 15 GPa.« less

On Nash-Equilibria of Approximation-Stable Games

NASA Astrophysics Data System (ADS)

Awasthi, Pranjal; Balcan, Maria-Florina; Blum, Avrim; Sheffet, Or; Vempala, Santosh

One reason for wanting to compute an (approximate) Nash equilibrium of a game is to predict how players will play. However, if the game has multiple equilibria that are far apart, or ɛ-equilibria that are far in variation distance from the true Nash equilibrium strategies, then this prediction may not be possible even in principle. Motivated by this consideration, in this paper we define the notion of games that are approximation stable, meaning that all ɛ-approximate equilibria are contained inside a small ball of radius Δ around a true equilibrium, and investigate a number of their properties. Many natural small games such as matching pennies and rock-paper-scissors are indeed approximation stable. We show furthermore there exist 2-player n-by-n approximation-stable games in which the Nash equilibrium and all approximate equilibria have support Ω(log n). On the other hand, we show all (ɛ,Δ) approximation-stable games must have an ɛ-equilibrium of support O(Δ^{2-o(1)}/ɛ2{log n}), yielding an immediate n^{O(Δ^{2-o(1)}/ɛ^2log n)}-time algorithm, improving over the bound of [11] for games satisfying this condition. We in addition give a polynomial-time algorithm for the case that Δ and ɛ are sufficiently close together. We also consider an inverse property, namely that all non-approximate equilibria are far from some true equilibrium, and give an efficient algorithm for games satisfying that condition.

Electrical resistivity and geotechnical assessment of subgrade soils in southwestern part of Nigeria

NASA Astrophysics Data System (ADS)

Adebisi, N. O.; Ariyo, S. O.; Sotikare, P. B.

2016-07-01

The subgrade soils in areas underlain by the slightly Migmatized to Non-migmatized Metasedimentary and Metaigneous rocks of Southwestern Nigeria have been considerably investigated. However, a serious research which employs electrical resistivity method for insight into the profile development, as well as estimation of resistance to deformation for predicting the stability of flexible highway pavements is yet to be carried out. In this study, Vertical Electrical Sounding (VES) were carried out after a reconnaissance survey based on stable and unstable locations on the road. Index and strength tests related to road construction were also carried out on bulk samples obtained from stable and failed (unstable) locations of the Ago-Iwoye/Ishara highway. Results show mostly three (3) layers in the profiles with H, HK, and HKH curve types. The subgrade soils below the stable locations have better vertical and interval variations in the resistivities (89-1095 Ωm) to a depth of 3.4 m as against those from the failed portions. Those from the stable locations also have higher specific gravity (2.72), low-medium plasticity and A-2-6 kaolinitic clayey soils with higher compacted density (2090 kg/m3) compared to subgrade soils from the failed locations. On the basis of Califonia Bearing Ratio (CBR), subgrade soils at stable locations have greater strength than those obtained from failed locations. Estimated resistance to deformation (R-value) and resilient modulus (MR) proved to be the overriding parameters for predicting the stability of the flexible highway pavements.

Fragile-to-fragile liquid transition at Tg and stable-glass phase nucleation rate maximum at the Kauzmann temperature TK

NASA Astrophysics Data System (ADS)

Tournier, Robert F.

2014-12-01

An undercooled liquid is unstable. The driving force of the glass transition at Tg is a change of the undercooled-liquid Gibbs free energy. The classical Gibbs free energy change for a crystal formation is completed including an enthalpy saving. The crystal growth critical nucleus is used as a probe to observe the Laplace pressure change Δp accompanying the enthalpy change -Vm×Δp at Tg where Vm is the molar volume. A stable glass-liquid transition model predicts the specific heat jump of fragile liquids at T≤Tg, the Kauzmann temperature TK where the liquid entropy excess with regard to crystal goes to zero, the equilibrium enthalpy between TK and Tg, the maximum nucleation rate at TK of superclusters containing magic atom numbers, and the equilibrium latent heats at Tg and TK. Strong-to-fragile and strong-to-strong liquid transitions at Tg are also described and all their thermodynamic parameters are determined from their specific heat jumps. The existence of fragile liquids quenched in the amorphous state, which do not undergo liquid-liquid transition during heating preceding their crystallization, is predicted. Long ageing times leading to the formation at TK of a stable glass composed of superclusters containing up to 147 atom, touching and interpenetrating, are evaluated from nucleation rates. A fragile-to-fragile liquid transition occurs at Tg without stable-glass formation while a strong glass is stable after transition.

Investigating the Energetic Ordering of Stable and Metastable TiO 2 Polymorphs Using DFT+ U and Hybrid Functionals

DOE PAGES

Curnan, Matthew T.; Kitchin, John R.

2015-08-12

Prediction of transition metal oxide BO 2 (B = Ti, V, etc.) polymorph energetic properties is critical to tunable material design and identifying thermodynamically accessible structures. Determining procedures capable of synthesizing particular polymorphs minimally requires prior knowledge of their relative energetic favorability. Information concerning TiO 2 polymorph relative energetic favorability has been ascertained from experimental research. In this study, the consistency of first-principles predictions and experimental results involving the relative energetic ordering of stable (rutile), metastable (anatase and brookite), and unstable (columbite) TiO 2 polymorphs is assessed via density functional theory (DFT). Considering the issues involving electron–electron interaction and chargemore » delocalization in TiO 2 calculations, relative energetic ordering predictions are evaluated over trends varying Ti Hubbard U 3d or exact exchange fraction parameter values. Energetic trends formed from varying U 3d predict experimentally consistent energetic ordering over U 3d intervals when using GGA-based functionals, regardless of pseudopotential selection. Given pertinent linear response calculated Hubbard U values, these results enable TiO 2 polymorph energetic ordering prediction. Here, the hybrid functional calculations involving rutile–anatase relative energetics, though demonstrating experimentally consistent energetic ordering over exact exchange fraction ranges, are not accompanied by predicted fractions, for a first-principles methodology capable of calculating exact exchange fractions precisely predicting TiO 2 polymorph energetic ordering is not available.« less

Predicting the Impacts of Intravehicular Displays on Driving Performance with Human Performance Modeling

NASA Technical Reports Server (NTRS)

Mitchell, Diane Kuhl; Wojciechowski, Josephine; Samms, Charneta

2012-01-01

A challenge facing the U.S. National Highway Traffic Safety Administration (NHTSA), as well as international safety experts, is the need to educate car drivers about the dangers associated with performing distraction tasks while driving. Researchers working for the U.S. Army Research Laboratory have developed a technique for predicting the increase in mental workload that results when distraction tasks are combined with driving. They implement this technique using human performance modeling. They have predicted workload associated with driving combined with cell phone use. In addition, they have predicted the workload associated with driving military vehicles combined with threat detection. Their technique can be used by safety personnel internationally to demonstrate the dangers of combining distracter tasks with driving and to mitigate the safety risks.

Sugeno-Fuzzy Expert System Modeling for Quality Prediction of Non-Contact Machining Process

NASA Astrophysics Data System (ADS)

Sivaraos; Khalim, A. Z.; Salleh, M. S.; Sivakumar, D.; Kadirgama, K.

2018-03-01

Modeling can be categorised into four main domains: prediction, optimisation, estimation and calibration. In this paper, the Takagi-Sugeno-Kang (TSK) fuzzy logic method is examined as a prediction modelling method to investigate the taper quality of laser lathing, which seeks to replace traditional lathe machines with 3D laser lathing in order to achieve the desired cylindrical shape of stock materials. Three design parameters were selected: feed rate, cutting speed and depth of cut. A total of twenty-four experiments were conducted with eight sequential runs and replicated three times. The results were found to be 99% of accuracy rate of the TSK fuzzy predictive model, which suggests that the model is a suitable and practical method for non-linear laser lathing process.

Is Approximate Number Precision a Stable Predictor of Math Ability?

ERIC Educational Resources Information Center

Libertus, Melissa E.; Feigenson, Lisa; Halberda, Justin

2013-01-01

Previous research shows that children's ability to estimate numbers of items using their Approximate Number System (ANS) predicts later math ability. To more closely examine the predictive role of early ANS acuity on later abilities, we assessed the ANS acuity, math ability, and expressive vocabulary of preschoolers twice, six months apart. We…

Resolving phase stability in the Ti-O binary with first-principles statistical mechanics methods

NASA Astrophysics Data System (ADS)

Gunda, N. S. Harsha; Puchala, Brian; Van der Ven, Anton

2018-03-01

The Ti-O system consists of a multitude of stable and metastable oxides that are used in wide ranging applications. In this work we investigate phase stability in the Ti-O binary from first principles. We perform a systematic search for ground state structures as a function of oxygen concentration by considering oxygen-vacancy and/or titanium-vacancy orderings over four parent crystal structures: (i) hcp Ti, (ii) ω -Ti, (iii) rocksalt, and (iv) hcp oxygen containing interstitial titanium. We explore phase stability at finite temperature using cluster expansion Hamiltonians and Monte Carlo simulations. The calculations predict a high oxygen solubility in hcp Ti and the stability of suboxide phases that undergo order-disorder transitions upon heating. Vacancy ordered rocksalt phases are also predicted at low temperature that disorder to form an extended solid solution at high temperatures. Predicted stable and metastable phase diagrams are qualitatively consistent with experimental observations, however, important discrepancies are revealed between first-principles density functional theory predictions of phase stability and the current understanding of phase stability in this system.

A Semi-Empirical Model for Forecasting Relativistic Electrons at Geostationary Orbit

NASA Technical Reports Server (NTRS)

Lyatsky, Wladislaw; Khazanov, George V.

2008-01-01

We developed a new prediction model for forecasting relativistic (>2MeV) electrons, which provides a VERY HIGH correlation between predicted and actually measured electron fluxes at geostationary orbit. This model implies the multi-step particle acceleration and is based on numerical integrating two linked continuity equations for primarily accelerated particles and relativistic electrons. The model includes a source and losses, and used solar wind data as only input parameters. We used the coupling function which is a best-fit combination of solar wind/Interplanetary Magnetic Field parameters, responsible for the generation of geomagnetic activity, as a source. The loss function was derived from experimental data. We tested the model for four year period 2004-2007. The correlation coefficient between predicted and actual values of the electron fluxes for whole four year period as well as for each of these years is about 0.9. The high and stable correlation between the computed and actual electron fluxes shows that the reliable forecasting these electrons at geostationary orbit is possible. The correlation coefficient between predicted and actual electron fluxes is stable and incredibly high.

Predicting flow at work: investigating the activities and job characteristics that predict flow states at work.

PubMed

Nielsen, Karina; Cleal, Bryan

2010-04-01

Flow (a state of consciousness where people become totally immersed in an activity and enjoy it intensely) has been identified as a desirable state with positive effects for employee well-being and innovation at work. Flow has been studied using both questionnaires and Experience Sampling Method (ESM). In this study, we used a newly developed 9-item flow scale in an ESM study combined with a questionnaire to examine the predictors of flow at two levels: the activities (brainstorming, planning, problem solving and evaluation) associated with transient flow states and the more stable job characteristics (role clarity, influence and cognitive demands). Participants were 58 line managers from two companies in Denmark; a private accountancy firm and a public elder care organization. We found that line managers in elder care experienced flow more often than accountancy line managers, and activities such as planning, problem solving, and evaluation predicted transient flow states. The more stable job characteristics included in this study were not, however, found to predict flow at work. Copyright 2010 APA, all rights reserved.

Stable clustering and the resolution of dissipationless cosmological N-body simulations

NASA Astrophysics Data System (ADS)

Benhaiem, David; Joyce, Michael; Sylos Labini, Francesco

2017-10-01

The determination of the resolution of cosmological N-body simulations, I.e. the range of scales in which quantities measured in them represent accurately the continuum limit, is an important open question. We address it here using scale-free models, for which self-similarity provides a powerful tool to control resolution. Such models also provide a robust testing ground for the so-called stable clustering approximation, which gives simple predictions for them. Studying large N-body simulations of such models with different force smoothing, we find that these two issues are in fact very closely related: our conclusion is that the accuracy of two-point statistics in the non-linear regime starts to degrade strongly around the scale at which their behaviour deviates from that predicted by the stable clustering hypothesis. Physically the association of the two scales is in fact simple to understand: stable clustering fails to be a good approximation when there are strong interactions of structures (in particular merging) and it is precisely such non-linear processes which are sensitive to fluctuations at the smaller scales affected by discretization. Resolution may be further degraded if the short distance gravitational smoothing scale is larger than the scale to which stable clustering can propagate. We examine in detail the very different conclusions of studies by Smith et al. and Widrow et al. and find that the strong deviations from stable clustering reported by these works are the results of over-optimistic assumptions about scales resolved accurately by the measured power spectra, and the reliance on Fourier space analysis. We emphasize the much poorer resolution obtained with the power spectrum compared to the two-point correlation function.

Cost-effectiveness of novel relapsed-refractory multiple myeloma therapies in Norway: lenalidomide plus dexamethasone vs bortezomib.

PubMed

Möller, Jörgen; Nicklasson, Lars; Murthy, Ananthram

2011-01-01

To estimate the cost-effectiveness (cost per additional life-year [LY] and quality-adjusted life-year [QALY] gained) of lenalidomide plus dexamethasone (LEN/DEX) compared with bortezomib for the treatment of relapsed-refractory multiple myeloma (rrMM) in Norway. A discrete-event simulation model was developed to predict patients? disease course using patient data, best response, and efficacy levels obtained from LEN/DEX MM-009/-010 trials and the bortezomib (APEX) published clinical trial. Predictive equations for time-to-progression (TTP) and post-progression survival (PPS) were developed by identifying the best fitting parametric survival distributions and selecting the most significant predictors. Disease and adverse event management was obtained via survey from Norwegian experts. Costs, derived from official Norwegian pricing data bases, included drug, administration, monitoring, and adverse event management costs. Complete or partial responders were 65% for LEN/DEX compared to 43% for bortezomib. Derived median TTP was 11.45 months for LEN/DEX compared to 5.15 months for bortezomib. LYs and QALYs were higher for LEN/DEX (4.06 and 2.95, respectively) than for bortezomib (3.11 and 2.19, respectively). The incremental costs per QALY and LY gained from LEN/DEX were NOK 247,978 and NOK 198,714, respectively, compared to bortezomib. Multiple sensitivity analyses indicated the findings were stable. The parameters with the greatest impact were 4-year time horizon (NOK 441,457/QALY) and higher bound confidence intervals for PPS (NOK 118,392). The model analyzed two therapies not compared in head-to-head trials, and predicted results using an equation incorporating patient-level characteristics. It is a limited estimation of the costs and outcomes in a Norwegian setting. The simulation model showed that treatment with LEN/DEX leads to greater LYs and QALYs when compared to bortezomib in the treatment of rrMM patients. The incremental cost-effectiveness ratio indicated treatment with LEN/DEX to be cost-effective and was the basis of the reimbursement approval of LEN/DEX in Norway.