A new optimized GA-RBF neural network algorithm.

PubMed

Jia, Weikuan; Zhao, Dean; Shen, Tian; Su, Chunyang; Hu, Chanli; Zhao, Yuyan

2014-01-01

When confronting the complex problems, radial basis function (RBF) neural network has the advantages of adaptive and self-learning ability, but it is difficult to determine the number of hidden layer neurons, and the weights learning ability from hidden layer to the output layer is low; these deficiencies easily lead to decreasing learning ability and recognition precision. Aiming at this problem, we propose a new optimized RBF neural network algorithm based on genetic algorithm (GA-RBF algorithm), which uses genetic algorithm to optimize the weights and structure of RBF neural network; it chooses new ways of hybrid encoding and optimizing simultaneously. Using the binary encoding encodes the number of the hidden layer's neurons and using real encoding encodes the connection weights. Hidden layer neurons number and connection weights are optimized simultaneously in the new algorithm. However, the connection weights optimization is not complete; we need to use least mean square (LMS) algorithm for further leaning, and finally get a new algorithm model. Using two UCI standard data sets to test the new algorithm, the results show that the new algorithm improves the operating efficiency in dealing with complex problems and also improves the recognition precision, which proves that the new algorithm is valid.

Evaluation of the Effects of Hidden Node Problems in IEEE 802.15.7 Uplink Performance

PubMed Central

Ley-Bosch, Carlos; Alonso-González, Itziar; Sánchez-Rodríguez, David; Ramírez-Casañas, Carlos

2016-01-01

In the last few years, the increasing use of LEDs in illumination systems has been conducted due to the emergence of Visible Light Communication (VLC) technologies, in which data communication is performed by transmitting through the visible band of the electromagnetic spectrum. In 2011, the Institute of Electrical and Electronics Engineers (IEEE) published the IEEE 802.15.7 standard for Wireless Personal Area Networks based on VLC. Due to limitations in the coverage of the transmitted signal, wireless networks can suffer from the hidden node problems, when there are nodes in the network whose transmissions are not detected by other nodes. This problem can cause an important degradation in communications when they are made by means of the Carrier Sense Multiple Access with Collision Avoidance (CSMA/CA) access control method, which is used in IEEE 802.15.7 This research work evaluates the effects of the hidden node problem in the performance of the IEEE 802.15.7 standard We implement a simulator and analyze VLC performance in terms of parameters like end-to-end goodput and message loss rate. As part of this research work, a solution to the hidden node problem is proposed, based on the use of idle patterns defined in the standard. Idle patterns are sent by the network coordinator node to communicate to the other nodes that there is an ongoing transmission. The validity of the proposed solution is demonstrated with simulation results. PMID:26861352

Evaluation of the Effects of Hidden Node Problems in IEEE 802.15.7 Uplink Performance.

PubMed

Ley-Bosch, Carlos; Alonso-González, Itziar; Sánchez-Rodríguez, David; Ramírez-Casañas, Carlos

2016-02-06

In the last few years, the increasing use of LEDs in illumination systems has been conducted due to the emergence of Visible Light Communication (VLC) technologies, in which data communication is performed by transmitting through the visible band of the electromagnetic spectrum. In 2011, the Institute of Electrical and Electronics Engineers (IEEE) published the IEEE 802.15.7 standard for Wireless Personal Area Networks based on VLC. Due to limitations in the coverage of the transmitted signal, wireless networks can suffer from the hidden node problems, when there are nodes in the network whose transmissions are not detected by other nodes. This problem can cause an important degradation in communications when they are made by means of the Carrier Sense Multiple Access with Collision Avoidance (CSMA/CA) access control method, which is used in IEEE 802.15.7 This research work evaluates the effects of the hidden node problem in the performance of the IEEE 802.15.7 standard We implement a simulator and analyze VLC performance in terms of parameters like end-to-end goodput and message loss rate. As part of this research work, a solution to the hidden node problem is proposed, based on the use of idle patterns defined in the standard. Idle patterns are sent by the network coordinator node to communicate to the other nodes that there is an ongoing transmission. The validity of the proposed solution is demonstrated with simulation results.

Exploring the application of latent class cluster analysis for investigating pedestrian crash injury severities in Switzerland.

PubMed

Sasidharan, Lekshmi; Wu, Kun-Feng; Menendez, Monica

2015-12-01

One of the major challenges in traffic safety analyses is the heterogeneous nature of safety data, due to the sundry factors involved in it. This heterogeneity often leads to difficulties in interpreting results and conclusions due to unrevealed relationships. Understanding the underlying relationship between injury severities and influential factors is critical for the selection of appropriate safety countermeasures. A method commonly employed to address systematic heterogeneity is to focus on any subgroup of data based on the research purpose. However, this need not ensure homogeneity in the data. In this paper, latent class cluster analysis is applied to identify homogenous subgroups for a specific crash type-pedestrian crashes. The manuscript employs data from police reported pedestrian (2009-2012) crashes in Switzerland. The analyses demonstrate that dividing pedestrian severity data into seven clusters helps in reducing the systematic heterogeneity of the data and to understand the hidden relationships between crash severity levels and socio-demographic, environmental, vehicle, temporal, traffic factors, and main reason for the crash. The pedestrian crash injury severity models were developed for the whole data and individual clusters, and were compared using receiver operating characteristics curve, for which results favored clustering. Overall, the study suggests that latent class clustered regression approach is suitable for reducing heterogeneity and revealing important hidden relationships in traffic safety analyses. Copyright © 2015 Elsevier Ltd. All rights reserved.

Detecting targets hidden in random forests

NASA Astrophysics Data System (ADS)

Kouritzin, Michael A.; Luo, Dandan; Newton, Fraser; Wu, Biao

2009-05-01

Military tanks, cargo or troop carriers, missile carriers or rocket launchers often hide themselves from detection in the forests. This plagues the detection problem of locating these hidden targets. An electro-optic camera mounted on a surveillance aircraft or unmanned aerial vehicle is used to capture the images of the forests with possible hidden targets, e.g., rocket launchers. We consider random forests of longitudinal and latitudinal correlations. Specifically, foliage coverage is encoded with a binary representation (i.e., foliage or no foliage), and is correlated in adjacent regions. We address the detection problem of camouflaged targets hidden in random forests by building memory into the observations. In particular, we propose an efficient algorithm to generate random forests, ground, and camouflage of hidden targets with two dimensional correlations. The observations are a sequence of snapshots consisting of foliage-obscured ground or target. Theoretically, detection is possible because there are subtle differences in the correlations of the ground and camouflage of the rocket launcher. However, these differences are well beyond human perception. To detect the presence of hidden targets automatically, we develop a Markov representation for these sequences and modify the classical filtering equations to allow the Markov chain observation. Particle filters are used to estimate the position of the targets in combination with a novel random weighting technique. Furthermore, we give positive proof-of-concept simulations.

Nonparametric model validations for hidden Markov models with applications in financial econometrics

PubMed Central

Zhao, Zhibiao

2011-01-01

We address the nonparametric model validation problem for hidden Markov models with partially observable variables and hidden states. We achieve this goal by constructing a nonparametric simultaneous confidence envelope for transition density function of the observable variables and checking whether the parametric density estimate is contained within such an envelope. Our specification test procedure is motivated by a functional connection between the transition density of the observable variables and the Markov transition kernel of the hidden states. Our approach is applicable for continuous time diffusion models, stochastic volatility models, nonlinear time series models, and models with market microstructure noise. PMID:21750601

An alternative approach for neural network evolution with a genetic algorithm: crossover by combinatorial optimization.

PubMed

García-Pedrajas, Nicolás; Ortiz-Boyer, Domingo; Hervás-Martínez, César

2006-05-01

In this work we present a new approach to crossover operator in the genetic evolution of neural networks. The most widely used evolutionary computation paradigm for neural network evolution is evolutionary programming. This paradigm is usually preferred due to the problems caused by the application of crossover to neural network evolution. However, crossover is the most innovative operator within the field of evolutionary computation. One of the most notorious problems with the application of crossover to neural networks is known as the permutation problem. This problem occurs due to the fact that the same network can be represented in a genetic coding by many different codifications. Our approach modifies the standard crossover operator taking into account the special features of the individuals to be mated. We present a new model for mating individuals that considers the structure of the hidden layer and redefines the crossover operator. As each hidden node represents a non-linear projection of the input variables, we approach the crossover as a problem on combinatorial optimization. We can formulate the problem as the extraction of a subset of near-optimal projections to create the hidden layer of the new network. This new approach is compared to a classical crossover in 25 real-world problems with an excellent performance. Moreover, the networks obtained are much smaller than those obtained with classical crossover operator.

Measurement problem and local hidden variables with entangled photons

NASA Astrophysics Data System (ADS)

Muchowski, Eugen

2017-12-01

It is shown that there is no remote action with polarization measurements of photons in singlet state. A model is presented introducing a hidden parameter which determines the polarizer output. This model is able to explain the polarization measurement results with entangled photons. It is not ruled out by Bell's Theorem.

Hidden Markov models and other machine learning approaches in computational molecular biology

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

Baldi, P.

1995-12-31

This tutorial was one of eight tutorials selected to be presented at the Third International Conference on Intelligent Systems for Molecular Biology which was held in the United Kingdom from July 16 to 19, 1995. Computational tools are increasingly needed to process the massive amounts of data, to organize and classify sequences, to detect weak similarities, to separate coding from non-coding regions, and reconstruct the underlying evolutionary history. The fundamental problem in machine learning is the same as in scientific reasoning in general, as well as statistical modeling: to come up with a good model for the data. In thismore » tutorial four classes of models are reviewed. They are: Hidden Markov models; artificial Neural Networks; Belief Networks; and Stochastic Grammars. When dealing with DNA and protein primary sequences, Hidden Markov models are one of the most flexible and powerful alignments and data base searches. In this tutorial, attention is focused on the theory of Hidden Markov Models, and how to apply them to problems in molecular biology.« less

Image segmentation using hidden Markov Gauss mixture models.

PubMed

Pyun, Kyungsuk; Lim, Johan; Won, Chee Sun; Gray, Robert M

2007-07-01

Image segmentation is an important tool in image processing and can serve as an efficient front end to sophisticated algorithms and thereby simplify subsequent processing. We develop a multiclass image segmentation method using hidden Markov Gauss mixture models (HMGMMs) and provide examples of segmentation of aerial images and textures. HMGMMs incorporate supervised learning, fitting the observation probability distribution given each class by a Gauss mixture estimated using vector quantization with a minimum discrimination information (MDI) distortion. We formulate the image segmentation problem using a maximum a posteriori criteria and find the hidden states that maximize the posterior density given the observation. We estimate both the hidden Markov parameter and hidden states using a stochastic expectation-maximization algorithm. Our results demonstrate that HMGMM provides better classification in terms of Bayes risk and spatial homogeneity of the classified objects than do several popular methods, including classification and regression trees, learning vector quantization, causal hidden Markov models (HMMs), and multiresolution HMMs. The computational load of HMGMM is similar to that of the causal HMM.

Infinite hidden conditional random fields for human behavior analysis.

PubMed

Bousmalis, Konstantinos; Zafeiriou, Stefanos; Morency, Louis-Philippe; Pantic, Maja

2013-01-01

Hidden conditional random fields (HCRFs) are discriminative latent variable models that have been shown to successfully learn the hidden structure of a given classification problem (provided an appropriate validation of the number of hidden states). In this brief, we present the infinite HCRF (iHCRF), which is a nonparametric model based on hierarchical Dirichlet processes and is capable of automatically learning the optimal number of hidden states for a classification task. We show how we learn the model hyperparameters with an effective Markov-chain Monte Carlo sampling technique, and we explain the process that underlines our iHCRF model with the Restaurant Franchise Rating Agencies analogy. We show that the iHCRF is able to converge to a correct number of represented hidden states, and outperforms the best finite HCRFs--chosen via cross-validation--for the difficult tasks of recognizing instances of agreement, disagreement, and pain. Moreover, the iHCRF manages to achieve this performance in significantly less total training, validation, and testing time.

The Self-Adapting Focused Review System. Probability sampling of medical records to monitor utilization and quality of care.

PubMed

Ash, A; Schwartz, M; Payne, S M; Restuccia, J D

1990-11-01

Medical record review is increasing in importance as the need to identify and monitor utilization and quality of care problems grow. To conserve resources, reviews are usually performed on a subset of cases. If judgment is used to identify subgroups for review, this raises the following questions: How should subgroups be determined, particularly since the locus of problems can change over time? What standard of comparison should be used in interpreting rates of problems found in subgroups? How can population problem rates be estimated from observed subgroup rates? How can the bias be avoided that arises because reviewers know that selected cases are suspected of having problems? How can changes in problem rates over time be interpreted when evaluating intervention programs? Simple random sampling, an alternative to subgroup review, overcomes the problems implied by these questions but is inefficient. The Self-Adapting Focused Review System (SAFRS), introduced and described here, provides an adaptive approach to record selection that is based upon model-weighted probability sampling. It retains the desirable inferential properties of random sampling while allowing reviews to be concentrated on cases currently thought most likely to be problematic. Model development and evaluation are illustrated using hospital data to predict inappropriate admissions.

Effect of different postoperative limb positions on blood loss and range of motion in total knee arthroplasty: An updated meta-analysis of randomized controlled trials.

PubMed

Wu, Yuangang; Yang, Timin; Zeng, Yi; Si, Haibo; Li, Canfeng; Shen, Bin

2017-01-01

Postoperative limb positioning has been reported to be an efficient and simple way to reduce blood loss and improve range of motion following total knee arthroplasty (TKA). This meta-analysis was designed to compare the effectiveness of two different limb positions in primary TKA. A meta-analysis of the PubMed, CENTRAL, Web of Science, EMBASE and Google Search Engine electronic databases was performed. In this meta-analysis, two postoperative limb positions were considered: mild-flexion (flexion less than 60°) and high-flexion (flexion at 60° or more). The subgroups were analysed using RevMan 5.3. Nine RCTs were included with a total sample size of 913 patients. The mild- and high-flexion positions significantly reduced postoperative total blood loss (P = 0.04 and P = 0.01; respectively). Subgroup analysis indicated that knee flexion significantly reduced hidden blood loss when the knee was fixed in mild-flexion (P = 0.0004) and significantly reduced transfusion requirements (P = 0.03) and improved range of motion (ROM) (P < 0.00001) when the knee was fixed in high-flexion. However, the rates of wound-related infection, deep venous thrombosis (DVT) and pulmonary embolism (PE) did not significantly differ between the two flexion groups. This meta-analysis suggests that mild- and high-flexion positions have similar efficacy in reducing total blood loss. In addition, subgroup analysis indicates that the mild-flexion position is superior in decreasing hidden blood loss compared with high-flexion; the high-flexion position is superior to mild-flexion in reducing transfusion requirements and improving postoperative ROM. Thus, the use of the high-flexion position is a viable option to reduce blood loss in patients following primary TKA without increasing the risk of wound-related infection, DVT or PE. Copyright © 2016 IJS Publishing Group Ltd. Published by Elsevier Ltd. All rights reserved.

Tracking problem solving by multivariate pattern analysis and Hidden Markov Model algorithms.

PubMed

Anderson, John R

2012-03-01

Multivariate pattern analysis can be combined with Hidden Markov Model algorithms to track the second-by-second thinking as people solve complex problems. Two applications of this methodology are illustrated with a data set taken from children as they interacted with an intelligent tutoring system for algebra. The first "mind reading" application involves using fMRI activity to track what students are doing as they solve a sequence of algebra problems. The methodology achieves considerable accuracy at determining both what problem-solving step the students are taking and whether they are performing that step correctly. The second "model discovery" application involves using statistical model evaluation to determine how many substates are involved in performing a step of algebraic problem solving. This research indicates that different steps involve different numbers of substates and these substates are associated with different fluency in algebra problem solving. Copyright © 2011 Elsevier Ltd. All rights reserved.

Mrs. Miniver's Girls: Plucky Girls in "Hidden Figures," "The Zookeeper's Wife," "Their Finest," and "Colossal"

ERIC Educational Resources Information Center

Beck, Bernard

2017-01-01

Four recent movies, "Hidden Figures," "The Zookeeper's Wife," "Their Finest," and "Colossal" exemplify a new cultural version of the movie heroine. This version combines feminism with commitment to solving an overwhelming problem. These heroines, thus, display the character virtues of Wonder Woman and Mrs.…

Early Prediction of Students' Grade Point Averages at Graduation: A Data Mining Approach

ERIC Educational Resources Information Center

Tekin, Ahmet

2014-01-01

Problem Statement: There has recently been interest in educational databases containing a variety of valuable but sometimes hidden data that can be used to help less successful students to improve their academic performance. The extraction of hidden information from these databases often implements aspects of the educational data mining (EDM)…

Dramatising the Hidden Hurt: Acting against Covert Bullying by Adolescent Girls

ERIC Educational Resources Information Center

Burton, Bruce

2010-01-01

This paper, delivered at the International Drama in Education Research Institute (IDIERI) conference in Sydney in July 2009, explores the outcomes of a project designed to apply the applied theatre techniques developed for the Acting Against Bullying programme to the specific problem of covert or hidden bullying by adolescent girls. Conducted in a…

Detection of Problem Gambler Subgroups Using Recursive Partitioning

ERIC Educational Resources Information Center

Markham, Francis; Young, Martin; Doran, Bruce

2013-01-01

The multivariate socio-demographic risk factors for problem gambling have been well documented. While this body of research is valuable in determining risk factors aggregated across various populations, the majority of studies tend not to specifically identify particular subgroups of problem gamblers based on the interaction between variables. The…

Dynamic extreme learning machine and its approximation capability.

PubMed

Zhang, Rui; Lan, Yuan; Huang, Guang-Bin; Xu, Zong-Ben; Soh, Yeng Chai

2013-12-01

Extreme learning machines (ELMs) have been proposed for generalized single-hidden-layer feedforward networks which need not be neuron alike and perform well in both regression and classification applications. The problem of determining the suitable network architectures is recognized to be crucial in the successful application of ELMs. This paper first proposes a dynamic ELM (D-ELM) where the hidden nodes can be recruited or deleted dynamically according to their significance to network performance, so that not only the parameters can be adjusted but also the architecture can be self-adapted simultaneously. Then, this paper proves in theory that such D-ELM using Lebesgue p-integrable hidden activation functions can approximate any Lebesgue p-integrable function on a compact input set. Simulation results obtained over various test problems demonstrate and verify that the proposed D-ELM does a good job reducing the network size while preserving good generalization performance.

[Autism Spectrum Disorder and DSM-5: Spectrum or Cluster?].

PubMed

Kienle, Xaver; Freiberger, Verena; Greulich, Heide; Blank, Rainer

2015-01-01

Within the new DSM-5, the currently differentiated subgroups of "Autistic Disorder" (299.0), "Asperger's Disorder" (299.80) and "Pervasive Developmental Disorder" (299.80) are replaced by the more general "Autism Spectrum Disorder". With regard to a patient-oriented and expedient advising therapy planning, however, the issue of an empirically reproducible and clinically feasible differentiation into subgroups must still be raised. Based on two Autism-rating-scales (ASDS and FSK), an exploratory two-step cluster analysis was conducted with N=103 children (age: 5-18) seen in our social-pediatric health care centre to examine potentially autistic symptoms. In the two-cluster solution of both rating scales, mainly the problems in social communication grouped the children into a cluster "with communication problems" (51 % and 41 %), and a cluster "without communication problems". Within the three-cluster solution of the ASDS, sensory hypersensitivity, cleaving to routines and social-communicative problems generated an "autistic" subgroup (22%). The children of the second cluster ("communication problems", 35%) were only described by social-communicative problems, and the third group did not show any problems (38%). In the three-cluster solution of the FSK, the "autistic cluster" of the two-cluster solution differentiated in a subgroup with mainly social-communicative problems (cluster 1) and a second subgroup described by restrictive, repetitive behavior. The different cluster solutions will be discussed with a view to the new DSM-5 diagnostic criteria, for following studies a further specification of some of the ASDS and FSK items could be helpful.

Using Bayesian Nonparametric Hidden Semi-Markov Models to Disentangle Affect Processes during Marital Interaction

PubMed Central

Griffin, William A.; Li, Xun

2016-01-01

Sequential affect dynamics generated during the interaction of intimate dyads, such as married couples, are associated with a cascade of effects—some good and some bad—on each partner, close family members, and other social contacts. Although the effects are well documented, the probabilistic structures associated with micro-social processes connected to the varied outcomes remain enigmatic. Using extant data we developed a method of classifying and subsequently generating couple dynamics using a Hierarchical Dirichlet Process Hidden semi-Markov Model (HDP-HSMM). Our findings indicate that several key aspects of existing models of marital interaction are inadequate: affect state emissions and their durations, along with the expected variability differences between distressed and nondistressed couples are present but highly nuanced; and most surprisingly, heterogeneity among highly satisfied couples necessitate that they be divided into subgroups. We review how this unsupervised learning technique generates plausible dyadic sequences that are sensitive to relationship quality and provide a natural mechanism for computational models of behavioral and affective micro-social processes. PMID:27187319

Reputation and Competition in a Hidden Action Model

PubMed Central

Fedele, Alessandro; Tedeschi, Piero

2014-01-01

The economics models of reputation and quality in markets can be classified in three categories. (i) Pure hidden action, where only one type of seller is present who can provide goods of different quality. (ii) Pure hidden information, where sellers of different types have no control over product quality. (iii) Mixed frameworks, which include both hidden action and hidden information. In this paper we develop a pure hidden action model of reputation and Bertrand competition, where consumers and firms interact repeatedly in a market with free entry. The price of the good produced by the firms is contractible, whilst the quality is noncontractible, hence it is promised by the firms when a contract is signed. Consumers infer future quality from all available information, i.e., both from what they know about past quality and from current prices. According to early contributions, competition should make reputation unable to induce the production of high-quality goods. We provide a simple solution to this problem by showing that high quality levels are sustained as an outcome of a stationary symmetric equilibrium. PMID:25329387

Reputation and competition in a hidden action model.

PubMed

Fedele, Alessandro; Tedeschi, Piero

2014-01-01

The economics models of reputation and quality in markets can be classified in three categories. (i) Pure hidden action, where only one type of seller is present who can provide goods of different quality. (ii) Pure hidden information, where sellers of different types have no control over product quality. (iii) Mixed frameworks, which include both hidden action and hidden information. In this paper we develop a pure hidden action model of reputation and Bertrand competition, where consumers and firms interact repeatedly in a market with free entry. The price of the good produced by the firms is contractible, whilst the quality is noncontractible, hence it is promised by the firms when a contract is signed. Consumers infer future quality from all available information, i.e., both from what they know about past quality and from current prices. According to early contributions, competition should make reputation unable to induce the production of high-quality goods. We provide a simple solution to this problem by showing that high quality levels are sustained as an outcome of a stationary symmetric equilibrium.

Symbolic Insight and Inhibitory Control: Two Problems Facing Young Children on Symbolic Retrieval Tasks

ERIC Educational Resources Information Center

Kuhlmeier, Valerie

2005-01-01

Many recent studies have explored young children's ability to use information from physical representations of space to guide search within the real world. In one commonly used procedure, children are asked to find a hidden toy in a room after observing a smaller toy being hidden in the analogous location in a scale model of the room.…

Passing from Mesoscopy to Macroscopy. The Mesoscopic Parameter \\bar k

NASA Astrophysics Data System (ADS)

Maslov, V. P.

2018-01-01

In previous papers of the author it was shown that, depending on the hidden parameter, purely quantum problems behave like classical ones. In the present paper, it is shown that the Bose-Einstein and the Fermi-Dirac distributions, which until now were regarded as dealing with quantum particles, describe, for the appropriate values of the hidden parameter, the macroscopic thermodynamics of classical molecules.

Harnessing the Hidden Curriculum: A Four-Step Approach to Developing and Reinforcing Reflective Competencies in Medical Clinical Clerkship

ERIC Educational Resources Information Center

Holmes, Cheryl L.; Harris, Ilene B.; Schwartz, Alan J.; Regehr, Glenn

2015-01-01

Changing the culture of medicine through the education of medical students has been proposed as a solution to the intractable problems of our profession. Yet few have explored the issues associated with making students partners in this change. There is a powerful hidden curriculum that perpetuates not only desired attitudes and behaviors but also…

The use of neutrons for the detection of explosives in Civil Security Applications

NASA Astrophysics Data System (ADS)

Pesente, S.; Fabris, D.; Lunardon, M.; Moretto, S.; Nebbia, G.; Viesti, G.

2007-02-01

The search for hidden explosives has been simulated in laboratory conditions by using our Tagged Neutron Inspection System (TNIS). Applications of the TNIS concept to Civil Security problems are discussed in the light of our projects for cargo container inspections. Moreover, neutron attenuation and scattering can be used to search in real time for large quantity of explosive hidden in vehicles.

THE DIFFERENCES IN THE TORUS GEOMETRY BETWEEN HIDDEN AND NON-HIDDEN BROAD LINE ACTIVE GALACTIC NUCLEI

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

Ichikawa, Kohei; Ueda, Yoshihiro; Packham, Christopher

2015-04-20

We present results from the fitting of infrared (IR) spectral energy distributions of 21 active galactic nuclei (AGNs) with clumpy torus models. We compiled high spatial resolution (∼0.3–0.7 arcsec) mid-IR (MIR) N-band spectroscopy, Q-band imaging, and nuclear near- and MIR photometry from the literature. Combining these nuclear near- and MIR observations, far-IR photometry, and clumpy torus models enables us to put constraints on the torus properties and geometry. We divide the sample into three types according to the broad line region (BLR) properties: type-1s, type-2s with scattered or hidden broad line region (HBLR) previously observed, and type-2s without any publishedmore » HBLR signature (NHBLR). Comparing the torus model parameters gives us the first quantitative torus geometrical view for each subgroup. We find that NHBLR AGNs have smaller torus opening angles and larger covering factors than HBLR AGNs. This suggests that the chance to observe scattered (polarized) flux from the BLR in NHBLR could be reduced by the dual effects of (a) less scattering medium due to the reduced scattering volume given the small torus opening angle and (b) the increased torus obscuration between the observer and the scattering region. These effects give a reasonable explanation for the lack of observed HBLR in some type-2 AGNs.« less

Characterizing a Hidden Group of At-Risk Drinkers: Epidemiological Profiles of Alcohol-Use Disorder Diagnostic Orphans.

PubMed

Gilbert, Paul A; Marzell, Miesha

2017-11-29

Drinkers who report some symptoms of alcohol-use disorder (AUD) but fail to meet full criteria are "diagnostic orphans." To improve risk-reduction efforts, we sought to develop better epidemiologic profiles of this underrecognized subgroup. This study estimated the population prevalence and described AUD symptoms of diagnostic orphans using the 2012-2013 National Epidemiological Survey of Alcohol and Related Conditions-III. Multivariate logistic regression was used to model odds of being a diagnostic orphan or meeting mild, moderate, and severe AUD criteria versus no AUD symptoms. Models were adjusted for the complex survey design using sampling weights and survey procedures (e.g., proc surveylogistic). Among drinkers, 14% of men and 11% of women were classified as diagnostic orphans. The most common symptoms were drinking more or for longer periods than intended, wanting or trying unsuccessfully to quit or cut back, and drinking in ways that increased risk of injury. We noted broad similarities between diagnostic orphans and mild/moderate AUD groups. There were no differences in odds of diagnostic orphans status by race/ethnicity; however, female gender was associated with lower odds of diagnostic orphan status and all levels of AUD. Individual history of AUD, family history of problem drinking, concurrent smoking, and concurrent marijuana use were associated with greater odds of problem drinking, with stronger associations as AUD severity increased. Diagnostic orphans remain a sizeable and overlooked population of problem drinkers. Clarifying the array of symptoms and cooccurring disorders can improve screening and facilitate alcohol risk-reduction intervention efforts.

Efficient Learning of Continuous-Time Hidden Markov Models for Disease Progression

PubMed Central

Liu, Yu-Ying; Li, Shuang; Li, Fuxin; Song, Le; Rehg, James M.

2016-01-01

The Continuous-Time Hidden Markov Model (CT-HMM) is an attractive approach to modeling disease progression due to its ability to describe noisy observations arriving irregularly in time. However, the lack of an efficient parameter learning algorithm for CT-HMM restricts its use to very small models or requires unrealistic constraints on the state transitions. In this paper, we present the first complete characterization of efficient EM-based learning methods for CT-HMM models. We demonstrate that the learning problem consists of two challenges: the estimation of posterior state probabilities and the computation of end-state conditioned statistics. We solve the first challenge by reformulating the estimation problem in terms of an equivalent discrete time-inhomogeneous hidden Markov model. The second challenge is addressed by adapting three approaches from the continuous time Markov chain literature to the CT-HMM domain. We demonstrate the use of CT-HMMs with more than 100 states to visualize and predict disease progression using a glaucoma dataset and an Alzheimer’s disease dataset. PMID:27019571

Intelligent classifier for dynamic fault patterns based on hidden Markov model

NASA Astrophysics Data System (ADS)

Xu, Bo; Feng, Yuguang; Yu, Jinsong

2006-11-01

It's difficult to build precise mathematical models for complex engineering systems because of the complexity of the structure and dynamics characteristics. Intelligent fault diagnosis introduces artificial intelligence and works in a different way without building the analytical mathematical model of a diagnostic object, so it's a practical approach to solve diagnostic problems of complex systems. This paper presents an intelligent fault diagnosis method, an integrated fault-pattern classifier based on Hidden Markov Model (HMM). This classifier consists of dynamic time warping (DTW) algorithm, self-organizing feature mapping (SOFM) network and Hidden Markov Model. First, after dynamic observation vector in measuring space is processed by DTW, the error vector including the fault feature of being tested system is obtained. Then a SOFM network is used as a feature extractor and vector quantization processor. Finally, fault diagnosis is realized by fault patterns classifying with the Hidden Markov Model classifier. The importing of dynamic time warping solves the problem of feature extracting from dynamic process vectors of complex system such as aeroengine, and makes it come true to diagnose complex system by utilizing dynamic process information. Simulating experiments show that the diagnosis model is easy to extend, and the fault pattern classifier is efficient and is convenient to the detecting and diagnosing of new faults.

Bell's theorem and the problem of decidability between the views of Einstein and Bohr.

PubMed

Hess, K; Philipp, W

2001-12-04

Einstein, Podolsky, and Rosen (EPR) have designed a gedanken experiment that suggested a theory that was more complete than quantum mechanics. The EPR design was later realized in various forms, with experimental results close to the quantum mechanical prediction. The experimental results by themselves have no bearing on the EPR claim that quantum mechanics must be incomplete nor on the existence of hidden parameters. However, the well known inequalities of Bell are based on the assumption that local hidden parameters exist and, when combined with conflicting experimental results, do appear to prove that local hidden parameters cannot exist. This fact leaves only instantaneous actions at a distance (called "spooky" by Einstein) to explain the experiments. The Bell inequalities are based on a mathematical model of the EPR experiments. They have no experimental confirmation, because they contradict the results of all EPR experiments. In addition to the assumption that hidden parameters exist, Bell tacitly makes a variety of other assumptions; for instance, he assumes that the hidden parameters are governed by a single probability measure independent of the analyzer settings. We argue that the mathematical model of Bell excludes a large set of local hidden variables and a large variety of probability densities. Our set of local hidden variables includes time-like correlated parameters and a generalized probability density. We prove that our extended space of local hidden variables does permit derivation of the quantum result and is consistent with all known experiments.

Phenomenology of pure-gauge hidden valleys at hadron colliders

NASA Astrophysics Data System (ADS)

Juknevich, Jose E.

Expectations for new physics at the LHC have been greatly influenced by the Hierarchy problem of electroweak symmetry breaking. However, there are reasons to believe that the LHC may still discover new physics, but not directly related to the resolution of the Hierarchy problem. To ensure that such a physics does not go undiscovered requires precise understanding of how new phenomena will reveal themselves in the current and future generation of particle-physics experiments. Given this fact it seems sensible to explore other approaches to this problem; we study three alternatives here. In this thesis I argue for the plausibility that the standard model is coupled, through new massive charged or colored particles, to a hidden sector whose low energy dynamics is controlled by a pure Yang-Mills theory, with no light matter. Such a sector would have numerous metastable "hidden glueballs" built from the hidden gluons. These states would decay to particles of the standard model. I consider the phenomenology of this scenario, and find formulas for the lifetimes and branching ratios of the most important of these states. The dominant decays are to two standard model gauge bosons or to fermion-antifermion pairs, or by radiative decays with photon or Higgs emission, leading to jet- and photon-rich signals, and some occasional leptons. The presence of effective operators of different mass dimensions, often competing with each other, together with a great diversity of states, leads to a great variability in the lifetimes and decay modes of the hidden glueballs. I find that most of the operators considered in this work are not heavily constrained by precision electroweak physics, therefore leaving plenty of room in the parameter space to be explored by the future experiments at the LHC. Finally, I discuss several issues on the phenomenology of the new massive particles as well as an outlook for experimental searches.

The effect of food environments on fruit and vegetable intake as modified by time spent at home: a cross-sectional study.

PubMed

Chum, Antony; Farrell, Eddie; Vaivada, Tyler; Labetski, Anna; Bohnert, Arianne; Selvaratnam, Inthuja; Larsen, Kristian; Pinter, Theresa; O'Campo, Patricia

2015-06-04

There is a growing body of research that investigates how the residential neighbourhood context relates to individual diet. However, previous studies ignore participants' time spent in the residential environment and this may be a problem because time-use studies show that adults' time-use pattern can significantly vary. To better understand the role of exposure duration, we designed a study to examine 'time spent at home' as a moderator to the residential food environment-diet association. Cross-sectional observational study. City of Toronto, Ontario, Canada. 2411 adults aged 25-65. Frequency of vegetable and fruit intake (VFI) per day. To examine how time spent at home may moderate the relationship between residential food environment and VFI, the full sample was split into three equal subgroups--short, medium and long duration spent at home. We detected significant associations between density of food stores in the residential food environment and VFI for subgroups that spend medium and long durations at home (ie, spending a mean of 8.0 and 12.3 h at home, respectively--not including sleep time), but no associations exist for people who spend the lowest amount of time at home (mean=4.7 h). Also, no associations were detected in analyses using the full sample. Our study is the first to demonstrate that time spent at home may be an important variable to identify hidden population patterns regarding VFI. Time spent at home can impact the association between the residential food environment and individual VFI. Published by the BMJ Publishing Group Limited. For permission to use (where not already granted under a licence) please go to http://group.bmj.com/group/rights-licensing/permissions.

Synchronization behaviors of coupled systems composed of hidden attractors

NASA Astrophysics Data System (ADS)

Zhang, Ge; Wu, Fuqiang; Wang, Chunni; Ma, Jun

2017-10-01

Based on a class of chaotic system composed of hidden attractors, in which the equilibrium points are described by a circular function, complete synchronization between two identical systems, pattern formation and synchronization of network is investigated, respectively. A statistical factor of synchronization is defined and calculated by using the mean field theory, the dependence of synchronization on bifurcation parameters discussed in numerical way. By setting a chain network, which local kinetic is described by hidden attractors, synchronization approach is investigated. It is found that the synchronization and pattern formation are dependent on the coupling intensity and also the selection of coupling variables. In the end, open problems are proposed for readers’ extensive guidance and investigation.

StegoWall: blind statistical detection of hidden data

NASA Astrophysics Data System (ADS)

Voloshynovskiy, Sviatoslav V.; Herrigel, Alexander; Rytsar, Yuri B.; Pun, Thierry

2002-04-01

Novel functional possibilities, provided by recent data hiding technologies, carry out the danger of uncontrolled (unauthorized) and unlimited information exchange that might be used by people with unfriendly interests. The multimedia industry as well as the research community recognize the urgent necessity for network security and copyright protection, or rather the lack of adequate law for digital multimedia protection. This paper advocates the need for detecting hidden data in digital and analog media as well as in electronic transmissions, and for attempting to identify the underlying hidden data. Solving this problem calls for the development of an architecture for blind stochastic hidden data detection in order to prevent unauthorized data exchange. The proposed architecture is called StegoWall; its key aspects are the solid investigation, the deep understanding, and the prediction of possible tendencies in the development of advanced data hiding technologies. The basic idea of our complex approach is to exploit all information about hidden data statistics to perform its detection based on a stochastic framework. The StegoWall system will be used for four main applications: robust watermarking, secret communications, integrity control and tamper proofing, and internet/network security.

Gauging hidden symmetries in two dimensions

NASA Astrophysics Data System (ADS)

Samtleben, Henning; Weidner, Martin

2007-08-01

We initiate the systematic construction of gauged matter-coupled supergravity theories in two dimensions. Subgroups of the affine global symmetry group of toroidally compactified supergravity can be gauged by coupling vector fields with minimal couplings and a particular topological term. The gauge groups typically include hidden symmetries that are not among the target-space isometries of the ungauged theory. The gaugings constructed in this paper are described group-theoretically in terms of a constant embedding tensor subject to a number of constraints which parametrizes the different theories and entirely encodes the gauged Lagrangian. The prime example is the bosonic sector of the maximally supersymmetric theory whose ungauged version admits an affine fraktur e9 global symmetry algebra. The various parameters (related to higher-dimensional p-form fluxes, geometric and non-geometric fluxes, etc.) which characterize the possible gaugings, combine into an embedding tensor transforming in the basic representation of fraktur e9. This yields an infinite-dimensional class of maximally supersymmetric theories in two dimensions. We work out and discuss several examples of higher-dimensional origin which can be systematically analyzed using the different gradings of fraktur e9.

Violent Female Offenders Compared With Violent Male Offenders on Psychological Determinants of Aggressive Behavior.

PubMed

Hornsveld, Ruud H J; Zwets, Almar J; Leenaars, Ellie P E M; Kraaimaat, Floris W; Bout, Ruben; Lagro-Janssen, Toine A L M; Kanters, Thijs

2018-02-01

Psychological determinants of aggressive behavior (personality traits and problem behaviors) in 59 Dutch female offenders (outpatients and detainees) were compared with those in 170 male offenders (outpatients and detainees) who were all convicted of a violent crime. The violent female offenders scored significantly higher on neuroticism and trait anger, and significantly lower on hostility than the male offenders; however, effect sizes were small. A subgroup of female forensic psychiatric outpatients did not differ from a subgroup of male outpatients on all measures, whereas a subgroup of female detainees scored significantly higher on anger and aggression, but lower on hostility and psychopathy than did a subgroup of male detainees. These first results might indicate that violent female offenders do not differ much from violent male offenders regarding personality traits and problem behaviors. The differences between both groups of violent offenders were largely borne by the subgroup of violent female detainees compared with the subgroup of violent male detainees.

ARPA surveillance technology for detection of targets hidden in foliage

NASA Astrophysics Data System (ADS)

Hoff, Lawrence E.; Stotts, Larry B.

1994-02-01

The processing of large quantities of synthetic aperture radar data in real time is a complex problem. Even the image formation process taxes today's most advanced computers. The use of complex algorithms with multiple channels adds another dimension to the computational problem. Advanced Research Projects Agency (ARPA) is currently planning on using the Paragon parallel processor for this task. The Paragon is small enough to allow its use in a sensor aircraft. Candidate algorithms will be implemented on the Paragon for evaluation for real time processing. In this paper ARPA technology developments for detecting targets hidden in foliage are reviewed and examples of signal processing techniques on field collected data are presented.

Hidden Hazards of Radon: Scanning the Country for Problem Locations.

ERIC Educational Resources Information Center

Gundersen, Linda C. S.

1992-01-01

Describes the geology of the radon problem in the United States and suggests how homeowners can cope with the radio active gas. Vignettes illustrate how and where radon is produced beneath the earth's surface, testing sites and procedures for radon in houses, and locations for potential radon problems across the United States. (MCO)

A Regularized Linear Dynamical System Framework for Multivariate Time Series Analysis.

PubMed

Liu, Zitao; Hauskrecht, Milos

2015-01-01

Linear Dynamical System (LDS) is an elegant mathematical framework for modeling and learning Multivariate Time Series (MTS). However, in general, it is difficult to set the dimension of an LDS's hidden state space. A small number of hidden states may not be able to model the complexities of a MTS, while a large number of hidden states can lead to overfitting. In this paper, we study learning methods that impose various regularization penalties on the transition matrix of the LDS model and propose a regularized LDS learning framework (rLDS) which aims to (1) automatically shut down LDSs' spurious and unnecessary dimensions, and consequently, address the problem of choosing the optimal number of hidden states; (2) prevent the overfitting problem given a small amount of MTS data; and (3) support accurate MTS forecasting. To learn the regularized LDS from data we incorporate a second order cone program and a generalized gradient descent method into the Maximum a Posteriori framework and use Expectation Maximization to obtain a low-rank transition matrix of the LDS model. We propose two priors for modeling the matrix which lead to two instances of our rLDS. We show that our rLDS is able to recover well the intrinsic dimensionality of the time series dynamics and it improves the predictive performance when compared to baselines on both synthetic and real-world MTS datasets.

Diversity within: Subgroup Differences of Youth Problem Behaviors among Asian Pacific Islander American Adolescents

ERIC Educational Resources Information Center

Choi, Yoonsun

2008-01-01

This study compares problem behaviors across a range of adolescent Asian Pacific Islander (API) subgroups using the Add Health data, and controlling for parental education or immigrant status. The study finds that Filipino, "other" API, and multiethnic API American youth are at higher risk for poorer outcomes than Chinese, Korean, and Vietnamese…

Automatic Hidden-Web Table Interpretation by Sibling Page Comparison

NASA Astrophysics Data System (ADS)

Tao, Cui; Embley, David W.

The longstanding problem of automatic table interpretation still illudes us. Its solution would not only be an aid to table processing applications such as large volume table conversion, but would also be an aid in solving related problems such as information extraction and semi-structured data management. In this paper, we offer a conceptual modeling solution for the common special case in which so-called sibling pages are available. The sibling pages we consider are pages on the hidden web, commonly generated from underlying databases. We compare them to identify and connect nonvarying components (category labels) and varying components (data values). We tested our solution using more than 2,000 tables in source pages from three different domains—car advertisements, molecular biology, and geopolitical information. Experimental results show that the system can successfully identify sibling tables, generate structure patterns, interpret tables using the generated patterns, and automatically adjust the structure patterns, if necessary, as it processes a sequence of hidden-web pages. For these activities, the system was able to achieve an overall F-measure of 94.5%.

Optimal matching for prostate brachytherapy seed localization with dimension reduction.

PubMed

Lee, Junghoon; Labat, Christian; Jain, Ameet K; Song, Danny Y; Burdette, Everette C; Fichtinger, Gabor; Prince, Jerry L

2009-01-01

In prostate brachytherapy, x-ray fluoroscopy has been used for intra-operative dosimetry to provide qualitative assessment of implant quality. More recent developments have made possible 3D localization of the implanted radioactive seeds. This is usually modeled as an assignment problem and solved by resolving the correspondence of seeds. It is, however, NP-hard, and the problem is even harder in practice due to the significant number of hidden seeds. In this paper, we propose an algorithm that can find an optimal solution from multiple projection images with hidden seeds. It solves an equivalent problem with reduced dimensional complexity, thus allowing us to find an optimal solution in polynomial time. Simulation results show the robustness of the algorithm. It was validated on 5 phantom and 18 patient datasets, successfully localizing the seeds with detection rate of > or = 97.6% and reconstruction error of < or = 1.2 mm. This is considered to be clinically excellent performance.

Object permanence in domestic dogs (Canis lupus familiaris) and gray wolves (Canis lupus).

PubMed

Fiset, Sylvain; Plourde, Vickie

2013-05-01

Recent evidence suggests that phylogenetic constraints exerted on dogs by the process of domestication have altered the ability of dogs to represent the physical world and the displacement of objects. In this study, invisible (Experiment 1) and visible (Experiment 2) displacement problems were administered to determine whether domestic dogs' and gray wolves' cognitive capacities to infer the position of a hidden object differ. The results revealed that adult dogs and wolves performed similarly in searching for disappearing objects: Both species succeeded the visible displacement tasks but failed the invisible displacement problems. We conclude that physical cognition for finding hidden objects in domestic dogs and gray wolves is alike and unrelated to the process of domestication.

Quasifixed points from scalar sequestering and the little hierarchy problem in supersymmetry

NASA Astrophysics Data System (ADS)

Martin, Stephen P.

2018-02-01

In supersymmetric models with scalar sequestering, superconformal strong dynamics in the hidden sector suppresses the low-energy couplings of mass dimension 2, compared to the squares of the dimension-1 parameters. Taking into account restrictions on the anomalous dimensions in superconformal theories, I point out that the interplay between the hidden and visible sector renormalizations gives rise to quasifixed point running for the supersymmetric Standard Model squared mass parameters, rather than driving them to 0. The extent to which this dynamics can ameliorate the little hierarchy problem in supersymmetry is studied. Models of this type in which the gaugino masses do not unify are arguably more natural, and are certainly more likely to be accessible, eventually, to the Large Hadron Collider.

Parametric inference for biological sequence analysis.

PubMed

Pachter, Lior; Sturmfels, Bernd

2004-11-16

One of the major successes in computational biology has been the unification, by using the graphical model formalism, of a multitude of algorithms for annotating and comparing biological sequences. Graphical models that have been applied to these problems include hidden Markov models for annotation, tree models for phylogenetics, and pair hidden Markov models for alignment. A single algorithm, the sum-product algorithm, solves many of the inference problems that are associated with different statistical models. This article introduces the polytope propagation algorithm for computing the Newton polytope of an observation from a graphical model. This algorithm is a geometric version of the sum-product algorithm and is used to analyze the parametric behavior of maximum a posteriori inference calculations for graphical models.

Disordered eating in a Swedish community sample of adolescent girls: subgroups, stability, and associations with body esteem, deliberate self-harm and other difficulties.

PubMed

Viborg, Njördur; Wångby-Lundh, Margit; Lundh, Lars-Gunnar; Wallin, Ulf; Johnsson, Per

2018-01-01

The developmental study of subtypes of disordered eating (DE) during adolescence may be relevant to understand the development of eating disorders. The purpose of the present study was to identify subgroups with different profiles of DE in a community sample of adolescent girls aged 13-15 years, and to study the stability of these profiles and subgroups over a one-year interval in order to find patterns that may need to be addressed in further research and prevention. Cluster analysis according to the LICUR procedure was performed on five aspects of DE, and the structural and individual stability of these clusters was analysed. The clusters were compared with regard to BMI, body esteem, deliberate self-harm, and other kinds of psychological difficulties. The analysis revealed six clusters (Multiple eating problems including purging, Multiple eating problems without purging, Social eating problems, Weight concerns, Fear of not being able to stop eating, and No eating problems) all of which had structurally stable profiles and five of which showed stability at the individual level. The more pronounced DE clusters (Multiple eating problems including/without purging) were consistently associated with higher levels of psychological difficulties and lower levels of body esteem. Furthermore, girls that reported purging reported engaging in self-harm to a larger extent. Subgroups of 13-15 year old girls show stable patterns of disordered eating that are associated with higher rates of psychological impairment and lower body esteem. The subgroup of girls who engage in purging also engage in more deliberate self-harm.

XM25 Schedule Delays, Cost Increases, and Performance Problems Continue, and Procurement Quantity Not Justified (REDACTED)

DTIC Science & Technology

2016-08-29

ammunition. (FOUO) Figure 1. XM25 Weapon System and Air Bursting Ammunition 3 Hidden refers to the enemy seeking cover in trenches; behind walls, rocks ...system that fires 25mm high-explosive, air- bursting ammunition to allow soldiers to fire at hidden enemy targets. Findings Army officials could...XM25 Weapon System The XM25 is a semiautomatic, shoulder-fired weapon system that fires 25mm high-explosive, air- bursting ammunition to allow soldiers

Solving the "Hidden Line" Problem

NASA Technical Reports Server (NTRS)

1984-01-01

David Hedgley Jr., a mathematician at Dryden Flight Research Center, has developed an accurate computer program that considers whether a line in a graphic model of a three dimensional object should or should not be visible. The Hidden Line Computer Code, program automatically removes superfluous lines and permits the computer to display an object from specific viewpoints, just as the human eye would see it. Users include Rowland Institute for Science in Cambridge, MA, several departments of Lockheed Georgia Co., and Nebraska Public Power District (NPPD).

Extracting hidden messages in steganographic images

DOE PAGES

Quach, Tu-Thach

2014-07-17

The eventual goal of steganalytic forensic is to extract the hidden messages embedded in steganographic images. A promising technique that addresses this problem partially is steganographic payload location, an approach to reveal the message bits, but not their logical order. It works by finding modified pixels, or residuals, as an artifact of the embedding process. This technique is successful against simple least-significant bit steganography and group-parity steganography. The actual messages, however, remain hidden as no logical order can be inferred from the located payload. This paper establishes an important result addressing this shortcoming: we show that the expected mean residualsmore » contain enough information to logically order the located payload provided that the size of the payload in each stego image is not fixed. The located payload can be ordered as prescribed by the mean residuals to obtain the hidden messages without knowledge of the embedding key, exposing the vulnerability of these embedding algorithms. We provide experimental results to support our analysis.« less

Distinct patterns of Internet and smartphone-related problems among adolescents by gender: Latent class analysis.

PubMed

Lee, Seung-Yup; Lee, Donghwan; Nam, Cho Rong; Kim, Da Yea; Park, Sera; Kwon, Jun-Gun; Kweon, Yong-Sil; Lee, Youngjo; Kim, Dai Jin; Choi, Jung-Seok

2018-05-23

Background and objectives The ubiquitous Internet connections by smartphones weakened the traditional boundaries between computers and mobile phones. We sought to explore whether smartphone-related problems differ from those of computer use according to gender using latent class analysis (LCA). Methods After informed consents, 555 Korean middle-school students completed surveys on gaming, Internet use, and smartphone usage patterns. They also completed various psychosocial instruments. LCA was performed for the whole group and by gender. In addition to ANOVA and χ 2 tests, post-hoc tests were conducted to examine differences among the LCA subgroups. Results In the whole group (n = 555), four subtypes were identified: dual-problem users (49.5%), problematic Internet users (7.7%), problematic smartphone users (32.1%), and "healthy" users (10.6%). Dual-problem users scored highest for addictive behaviors and other psychopathologies. The gender-stratified LCA revealed three subtypes for each gender. With dual-problem and healthy subgroup as common, problematic Internet subgroup was classified in the males, whereas problematic smartphone subgroup was classified in the females in the gender-stratified LCA. Thus, distinct patterns were observed according to gender with higher proportion of dual-problem present in males. While gaming was associated with problematic Internet use in males, aggression and impulsivity demonstrated associations with problematic smartphone use in females. Conclusions An increase in the number of digital media-related problems was associated with worse outcomes in various psychosocial scales. Gaming may play a crucial role in males solely displaying Internet-related problems. The heightened impulsivity and aggression seen in our female problematic smartphone users requires further research.

A serious game for children with Attention Deficit Hyperactivity Disorder: Who benefits the most?

PubMed Central

Franken, Ingmar H. A.; Maras, Athanasios

2018-01-01

Objective The aim of the current study was to identify which subgroups of children with Attention Deficit Hyperactivity Disorder (ADHD) benefitted the most from playing a Serious Game (SG) intervention shown in a randomized trial to improve behavioral outcomes. Method Pre-intervention characteristics [i.e., gender, age, intellectual level of functioning, medication use, computer experience, ADHD subtype, severity of inattention problems, severity of hyperactivity/impulsivity problems, comorbid Oppositional Defiant Disorder (ODD) and Conduct Disorder (CD) symptoms] were explored as potential moderators in a Virtual Twins (VT) analysis to identify subgroups for whom the SG intervention was most effective. Primary outcome measures were parent-reported time management, planning/organizing and cooperation skills. Results Two subgroups were identified. Girls (n = 26) were identified as the subgroup that was most likely to show greater improvements in planning/organizing skills as compared to the estimated treatment effect of the total group of participants. Furthermore, among the boys, those (n = 47) with lower baseline levels of hyperactivity and higher levels of CD symptoms showed more improvements in their planning/organizing skills when they played the SG intervention as compared to the estimated treatment effect of the total group of participants. Conclusion Using a VT analysis two subgroups of children with ADHD, girls, and boys with both higher levels of CD and lower levels of hyperactivity, were identified. These subgroups mostly benefit from playing the SG intervention developed to improve ADHD related behavioral problems. Our results imply that these subgroups have a higher chance of treatment success. PMID:29543891

Automation and adaptation: Nurses' problem-solving behavior following the implementation of bar coded medication administration technology.

PubMed

Holden, Richard J; Rivera-Rodriguez, A Joy; Faye, Héléne; Scanlon, Matthew C; Karsh, Ben-Tzion

2013-08-01

The most common change facing nurses today is new technology, particularly bar coded medication administration technology (BCMA). However, there is a dearth of knowledge on how BCMA alters nursing work. This study investigated how BCMA technology affected nursing work, particularly nurses' operational problem-solving behavior. Cognitive systems engineering observations and interviews were conducted after the implementation of BCMA in three nursing units of a freestanding pediatric hospital. Problem-solving behavior, associated problems, and goals, were specifically defined and extracted from observed episodes of care. Three broad themes regarding BCMA's impact on problem solving were identified. First, BCMA allowed nurses to invent new problem-solving behavior to deal with pre-existing problems. Second, BCMA made it difficult or impossible to apply some problem-solving behaviors that were commonly used pre-BCMA, often requiring nurses to use potentially risky workarounds to achieve their goals. Third, BCMA created new problems that nurses were either able to solve using familiar or novel problem-solving behaviors, or unable to solve effectively. Results from this study shed light on hidden hazards and suggest three critical design needs: (1) ecologically valid design; (2) anticipatory control; and (3) basic usability. Principled studies of the actual nature of clinicians' work, including problem solving, are necessary to uncover hidden hazards and to inform health information technology design and redesign.

Automation and adaptation: Nurses’ problem-solving behavior following the implementation of bar coded medication administration technology

PubMed Central

Holden, Richard J.; Rivera-Rodriguez, A. Joy; Faye, Héléne; Scanlon, Matthew C.; Karsh, Ben-Tzion

2012-01-01

The most common change facing nurses today is new technology, particularly bar coded medication administration technology (BCMA). However, there is a dearth of knowledge on how BCMA alters nursing work. This study investigated how BCMA technology affected nursing work, particularly nurses’ operational problem-solving behavior. Cognitive systems engineering observations and interviews were conducted after the implementation of BCMA in three nursing units of a freestanding pediatric hospital. Problem-solving behavior, associated problems, and goals, were specifically defined and extracted from observed episodes of care. Three broad themes regarding BCMA’s impact on problem solving were identified. First, BCMA allowed nurses to invent new problem-solving behavior to deal with pre-existing problems. Second, BCMA made it difficult or impossible to apply some problem-solving behaviors that were commonly used pre-BCMA, often requiring nurses to use potentially risky workarounds to achieve their goals. Third, BCMA created new problems that nurses were either able to solve using familiar or novel problem-solving behaviors, or unable to solve effectively. Results from this study shed light on hidden hazards and suggest three critical design needs: (1) ecologically valid design; (2) anticipatory control; and (3) basic usability. Principled studies of the actual nature of clinicians’ work, including problem solving, are necessary to uncover hidden hazards and to inform health information technology design and redesign. PMID:24443642

Using Educational Data Mining Methods to Assess Field-Dependent and Field-Independent Learners' Complex Problem Solving

ERIC Educational Resources Information Center

Angeli, Charoula; Valanides, Nicos

2013-01-01

The present study investigated the problem-solving performance of 101 university students and their interactions with a computer modeling tool in order to solve a complex problem. Based on their performance on the hidden figures test, students were assigned to three groups of field-dependent (FD), field-mixed (FM), and field-independent (FI)…

A Longitudinal Comparison of Systems Used to Identify Subgroups of Learning Disabled Children.

ERIC Educational Resources Information Center

Goldstein, David; Dundon, William D.

This paper addresses the problem of heterogeneity of samples of learning disabled (LD) children by comparing five different systems for identifying homogeneous subgroups in terms of their ability to predict longitudinal reading and mathematics scores. One hundred and sixty LD children served as subjects. Three of the five subgrouping systems were…

Simultaneous escaping of explicit and hidden free energy barriers: application of the orthogonal space random walk strategy in generalized ensemble based conformational sampling.

PubMed

Zheng, Lianqing; Chen, Mengen; Yang, Wei

2009-06-21

To overcome the pseudoergodicity problem, conformational sampling can be accelerated via generalized ensemble methods, e.g., through the realization of random walks along prechosen collective variables, such as spatial order parameters, energy scaling parameters, or even system temperatures or pressures, etc. As usually observed, in generalized ensemble simulations, hidden barriers are likely to exist in the space perpendicular to the collective variable direction and these residual free energy barriers could greatly abolish the sampling efficiency. This sampling issue is particularly severe when the collective variable is defined in a low-dimension subset of the target system; then the "Hamiltonian lagging" problem, which reveals the fact that necessary structural relaxation falls behind the move of the collective variable, may be likely to occur. To overcome this problem in equilibrium conformational sampling, we adopted the orthogonal space random walk (OSRW) strategy, which was originally developed in the context of free energy simulation [L. Zheng, M. Chen, and W. Yang, Proc. Natl. Acad. Sci. U.S.A. 105, 20227 (2008)]. Thereby, generalized ensemble simulations can simultaneously escape both the explicit barriers along the collective variable direction and the hidden barriers that are strongly coupled with the collective variable move. As demonstrated in our model studies, the present OSRW based generalized ensemble treatments show improved sampling capability over the corresponding classical generalized ensemble treatments.

An Intelligent Ensemble Neural Network Model for Wind Speed Prediction in Renewable Energy Systems.

PubMed

Ranganayaki, V; Deepa, S N

2016-01-01

Various criteria are proposed to select the number of hidden neurons in artificial neural network (ANN) models and based on the criterion evolved an intelligent ensemble neural network model is proposed to predict wind speed in renewable energy applications. The intelligent ensemble neural model based wind speed forecasting is designed by averaging the forecasted values from multiple neural network models which includes multilayer perceptron (MLP), multilayer adaptive linear neuron (Madaline), back propagation neural network (BPN), and probabilistic neural network (PNN) so as to obtain better accuracy in wind speed prediction with minimum error. The random selection of hidden neurons numbers in artificial neural network results in overfitting or underfitting problem. This paper aims to avoid the occurrence of overfitting and underfitting problems. The selection of number of hidden neurons is done in this paper employing 102 criteria; these evolved criteria are verified by the computed various error values. The proposed criteria for fixing hidden neurons are validated employing the convergence theorem. The proposed intelligent ensemble neural model is applied for wind speed prediction application considering the real time wind data collected from the nearby locations. The obtained simulation results substantiate that the proposed ensemble model reduces the error value to minimum and enhances the accuracy. The computed results prove the effectiveness of the proposed ensemble neural network (ENN) model with respect to the considered error factors in comparison with that of the earlier models available in the literature.

May Stakeholders be Involved in Design Without Informed Consent? The Case of Hidden Design.

PubMed

Pols, A J K

2017-06-01

Stakeholder involvement in design is desirable from both a practical and an ethical point of view. It is difficult to do well, however, and some problems recur again and again, both of a practical nature, e.g. stakeholders acting strategically rather than openly, and of an ethical nature, e.g. power imbalances unduly affecting the outcome of the process. Hidden Design has been proposed as a method to deal with the practical problems of stakeholder involvement. It aims to do so by taking the observation of stakeholder actions, rather than the outcomes of a deliberative process, as its input. Furthermore, it hides from stakeholders the fact that a design process is taking place so that they will not behave differently than they otherwise would. Both aspects of Hidden Design have raised ethical worries. In this paper I make an ethical analysis of what it means for a design process to leave participants uninformed or deceived rather than acquiring their informed consent beforehand, and to use observation of actions rather than deliberation as input for design, using Hidden Design as a case study. This analysis is based on two sets of normative guidelines: the ethical guidelines for psychological research involving deception or uninformed participants from two professional psychological organisations, and Habermasian norms for a fair and just (deliberative) process. It supports the conclusion that stakeholder involvement in design organised in this way can be ethically acceptable, though under a number of conditions and constraints.

An Intelligent Ensemble Neural Network Model for Wind Speed Prediction in Renewable Energy Systems

PubMed Central

Ranganayaki, V.; Deepa, S. N.

2016-01-01

Various criteria are proposed to select the number of hidden neurons in artificial neural network (ANN) models and based on the criterion evolved an intelligent ensemble neural network model is proposed to predict wind speed in renewable energy applications. The intelligent ensemble neural model based wind speed forecasting is designed by averaging the forecasted values from multiple neural network models which includes multilayer perceptron (MLP), multilayer adaptive linear neuron (Madaline), back propagation neural network (BPN), and probabilistic neural network (PNN) so as to obtain better accuracy in wind speed prediction with minimum error. The random selection of hidden neurons numbers in artificial neural network results in overfitting or underfitting problem. This paper aims to avoid the occurrence of overfitting and underfitting problems. The selection of number of hidden neurons is done in this paper employing 102 criteria; these evolved criteria are verified by the computed various error values. The proposed criteria for fixing hidden neurons are validated employing the convergence theorem. The proposed intelligent ensemble neural model is applied for wind speed prediction application considering the real time wind data collected from the nearby locations. The obtained simulation results substantiate that the proposed ensemble model reduces the error value to minimum and enhances the accuracy. The computed results prove the effectiveness of the proposed ensemble neural network (ENN) model with respect to the considered error factors in comparison with that of the earlier models available in the literature. PMID:27034973

Settler Colony on the Hudson: What History and Theory Tell Us about the Education Crisis in East Ramapo Central School District, New York

ERIC Educational Resources Information Center

Justice, Benjamin

2016-01-01

Scholars typically frame the subgroup problem in education in terms of protecting religious minorities from majoritarian encroachment. This essay explores a different aspect of the subgroup problem: what happens when an antidemocratic religious minority becomes a local majority responsible for the promotion of the public good? This essay uses the…

Reports of alcohol-related problems and alcohol dependence for demographic subgroups using interactive voice response versus telephone surveys: the 2005 US National Alcohol Survey.

PubMed

Midanik, Lorraine T; Greenfield, Thomas K

2010-07-01

Interactive voice response (IVR), a computer-based interviewing technique, can be used within a computer-assisted telephone interview (CATI) survey to increase privacy and the accuracy of reports of sensitive attitudes and behaviours. Previous research using the 2005 National Alcohol Survey indicated no overall significant differences between IVR and CATI responses to alcohol-related problems and alcohol dependence. To determine if this result holds for demographic subgroups that could respond differently to modes of data collection, this study compares the prevalence rates of lifetime and last-year alcohol-related problems by gender, ethnicity, age and income subgroups obtained by IVR versus continuous CATI interviewing. As part of the 2005 National Alcohol Survey, subsamples of English-speaking respondents were randomly assigned to an IVR group that received an embedded IVR module on alcohol-related problems (n = 450 lifetime drinkers) and a control group that were asked identical alcohol-related problem items using continuous CATI (n = 432 lifetime drinkers). Overall, there were few significant associations. Among lifetime drinkers, higher rates of legal problems were found for white and higher income respondents in the IVR group. For last-year drinkers, a higher percentage of indicators of alcohol dependence was found for Hispanic respondents and women respondents in the CATI group. Data on alcohol problems collected by CATI provide largely comparable results to those from an embedded IVR module. Thus, incorporation of IVR technology in a CATI interview does not appear strongly indicated even for several key subgroups.

Reservoir computing on the hypersphere

NASA Astrophysics Data System (ADS)

Andrecut, M.

Reservoir Computing (RC) refers to a Recurrent Neural Network (RNNs) framework, frequently used for sequence learning and time series prediction. The RC system consists of a random fixed-weight RNN (the input-hidden reservoir layer) and a classifier (the hidden-output readout layer). Here, we focus on the sequence learning problem, and we explore a different approach to RC. More specifically, we remove the nonlinear neural activation function, and we consider an orthogonal reservoir acting on normalized states on the unit hypersphere. Surprisingly, our numerical results show that the system’s memory capacity exceeds the dimensionality of the reservoir, which is the upper bound for the typical RC approach based on Echo State Networks (ESNs). We also show how the proposed system can be applied to symmetric cryptography problems, and we include a numerical implementation.

Differences in problem behaviour among ethnic minority and majority preschoolers in the Netherlands and the role of family functioning and parenting factors as mediators: the Generation R Study.

PubMed

Flink, Ilse J E; Jansen, Pauline W; Beirens, Tinneke M J; Tiemeier, Henning; van IJzendoorn, Marinus H; Jaddoe, Vincent W V; Hofman, Albert; Raat, Hein

2012-12-19

Studies have shown that, compared to native counterparts, preschoolers from ethnic minorities are at an increased risk of problem behaviour. Socio-economic factors only partly explain this increased risk. This study aimed to further unravel the differences in problem behaviour among ethnic minority and native preschoolers by examining the mediating role of family functioning and parenting factors. We included 4,282 preschoolers participating in the Generation R Study, an ethnically-diverse cohort study with inclusion in early pregnancy. At child age 3 years, parents completed the Child Behavior Checklist (CBCL/1,5-5); information on demographics, socio-economic status and measures of family functioning (maternal psychopathology; general family functioning) and parenting (parenting stress; harsh parenting) were retrieved from questionnaires. CBCL Total Problems scores in each ethnic subgroup were compared with scores in the Dutch reference population. Mediation was evaluated using multivariate regression models. After adjustment for confounders, preschoolers from ethnic minorities were more likely to present problem behaviour than the Dutch subgroup (e.g. CBCL Total Problems Turkish subgroup (OR 7.0 (95% CI 4.9; 10.1)). When considering generational status, children of first generation immigrants were worse off than the second generation (P<0.01). Adjustment for socio-economic factors mediated the association between the ethnic minority status and child problem behaviour (e.g. attenuation in OR by 54.4% (P<0.05) from OR 5.1 (95% CI 2.8; 9.4) to OR 2.9 (95% CI 1.5; 5.6) in Cape Verdean subgroup). However, associations remained significant in most ethnic subgroups. A final adjustment for family functioning and parenting factors further attenuated the association (e.g. attenuation in OR by 55.5% (P<0.05) from OR 2.2 (95% CI 1.3; 4.4) to OR 1.5 (95% CI 1.0; 2.4) in European other subgroup). This study showed that preschoolers from ethnic minorities and particularly children of first generation immigrants are at an increased risk of problem behaviour compared to children born to a Dutch mother. Although socio-economic factors were found to partly explain the association between the ethnic minority status and child problem behaviour, a similar part was explained by family functioning and parenting factors. Considering these findings, it is important for health care workers to also be attentive to symptoms of parental psychopathology (e.g. depression), poor family functioning, high levels of parenting stress or harsh parenting in first and second generation immigrants with young children.

Criminal justice coercion in the treatment of alcohol problems: an examination of two client subgroups.

PubMed

Polcin, D L

1999-01-01

An increasing number of individuals are being referred to alcohol treatment programs under coercion from the criminal justice system. While a substantial number of investigations have addressed coercive treatment for illicit drug-related offenses, fewer studies have focused on mandated treatment for alcohol-related problems. This article examines the treatment of two subgroups of clients coerced into alcohol treatment from criminal justice institutions. The article begins with an overview of the literature on clients coerced into treatment as a result of "driving under the influence" (DUI) charges. The characteristics of a subgroup that has received less attention are then described: lower socioeconomic clients who are coerced into alcohol treatment from the courts for non-DUI offenses, such as public inebriation, disorderly conduct, trespassing, assault, and theft. This subgroup of non-DUI coerced-treatment offenders depends primarily upon underfunded public services, although their treatment requires careful assessment and triage for multiple problem areas. The article addresses some potential political and economic roadblocks to comprehensive treatment and closes with questions and recommendations for further research.

Hidden sector monopole, vector dark matter and dark radiation with Higgs portal

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

Baek, Seungwon; Ko, P.; Park, Wan-Il, E-mail: sbaek1560@gmail.com, E-mail: pko@kias.re.kr, E-mail: wipark@kias.re.kr

2014-10-01

We show that the 't Hooft-Polyakov monopole model in the hidden sector with Higgs portal interaction makes a viable dark matter model, where monopole and massive vector dark matter (VDM) are stable due to topological conservation and the unbroken subgroup U(1 {sub X}. We show that, even though observed CMB data requires the dark gauge coupling to be quite small, a right amount of VDM thermal relic can be obtained via s-channel resonant annihilation for the mass of VDM close to or smaller than the half of SM higgs mass, thanks to Higgs portal interaction. Monopole relic density turns outmore » to be several orders of magnitude smaller than the observed dark matter relic density. Direct detection experiments, particularly, the projected XENON1T experiment, may probe the parameter space where the dark Higgs is lighter than ∼< 50 GeV. In addition, the dark photon associated with the unbroken U(1 {sub X} contributes to the radiation energy density at present, giving Δ N{sub eff}{sup ν} ∼ 0.1 as the extra relativistic neutrino species.« less

Non-Hierarchical Clustering as a Method to Analyse an Open-Ended Questionnaire on Algebraic Thinking

ERIC Educational Resources Information Center

Di Paola, Benedetto; Battaglia, Onofrio Rosario; Fazio, Claudio

2016-01-01

The problem of taking a data set and separating it into subgroups, where the members of each subgroup are more similar to each other than they are to members outside the subgroup, has been extensively studied in science and mathematics education research. Student responses to written questions and multiple-choice tests have been characterised and…

A Comparison of Bridging Methods in the Analysis of NAEP Trends with the New Race Subgroup Definitions

ERIC Educational Resources Information Center

Meyer, J. Patrick; Setzer, J. Carl

2009-01-01

Recent changes to federal guidelines for the collection of data on race and ethnicity allow respondents to select multiple race categories. Redefining race subgroups in this manner poses problems for research spanning both sets of definitions. NAEP long-term trends have used the single-race subgroup definitions for over thirty years. Little is…

Taking the Shot

ERIC Educational Resources Information Center

Grayson, Jennifer

2011-01-01

In today's high-pressure IT world, almost every opportunity comes hidden inside a problem. And when it comes to "greening" a data center, the problems can be especially daunting, given institutional inertia, budgetary concerns, politics, and more. For CIOs looking to notch up a win with a leaner, greener data center, the key to success often lies…

The Hidden Health Toll: A Cost of Work to the American Woman

ERIC Educational Resources Information Center

Stellman, Jeanne M.

1977-01-01

Large numbers of women work at jobs that present serious health hazards, although most people associate workplace hazards with traditionally "male" jobs. Physical dangers, stress, and fatigue lead to manifold health problems among working women. These problems should be investigated and conditions improved for workers of both sexes. (Author/GC)

Reverse engineering a social agent-based hidden markov model--visage.

PubMed

Chen, Hung-Ching Justin; Goldberg, Mark; Magdon-Ismail, Malik; Wallace, William A

2008-12-01

We present a machine learning approach to discover the agent dynamics that drives the evolution of the social groups in a community. We set up the problem by introducing an agent-based hidden Markov model for the agent dynamics: an agent's actions are determined by micro-laws. Nonetheless, We learn the agent dynamics from the observed communications without knowing state transitions. Our approach is to identify the appropriate micro-laws corresponding to an identification of the appropriate parameters in the model. The model identification problem is then formulated as a mixed optimization problem. To solve the problem, we develop a multistage learning process for determining the group structure, the group evolution, and the micro-laws of a community based on the observed set of communications among actors, without knowing the semantic contents. Finally, to test the quality of our approximations and the feasibility of the approach, we present the results of extensive experiments on synthetic data as well as the results on real communities, such as Enron email and Movie newsgroups. Insight into agent dynamics helps us understand the driving forces behind social evolution.

How electronic health records can unmask the hidden value of PAs.

PubMed

Ogunfiditimi, Folusho; Sherry, Scott P; Foote, Monica; Christie, Sarah L; Shock, Lisa P; Cawley, James; Browne, Aaron

2017-06-01

The Fee for Value (FFV) Task Force, a subgroup of the American Academy of PAs' Research and Strategic Initiatives Commission, has examined tools and mechanisms aimed at better clarifying the volume and value of PA work and how that work contributes to improving access to high-quality care. Establishing the value of PAs has been a challenging task for many healthcare providers. Often, PA value has been defined by their clinical productivity, without any clear direction as to what constitutes value versus productivity. The objective of this article is to unmask the value of PAs through the role of electronic health records and highlight PAs' ability to produce services that are value-oriented and quantifiably productive.

Bounds on the number of hidden neurons in three-layer binary neural networks.

PubMed

Zhang, Zhaozhi; Ma, Xiaomin; Yang, Yixian

2003-09-01

This paper investigates an important problem concerning the complexity of three-layer binary neural networks (BNNs) with one hidden layer. The neuron in the studied BNNs employs a hard limiter activation function with only integer weights and an integer threshold. The studies are focused on implementations of arbitrary Boolean functions which map from [0, 1]n into [0, 1]. A deterministic algorithm called set covering algorithm (SCA) is proposed for the construction of a three-layer BNN to implement an arbitrary Boolean function. The SCA is based on a unit sphere covering (USC) of the Hamming space (HS) which is chosen in advance. It is proved that for the implementation of an arbitrary Boolean function of n-variables (n > or = 3) by using SCA, [3L/2] hidden neurons are necessary and sufficient, where L is the number of unit spheres contained in the chosen USC of the n-dimensional HS. It is shown that by using SCA, the number of hidden neurons required is much less than that by using a two-parallel hyperplane method. In order to indicate the potential ability of three-layer BNNs, a lower bound on the required number of hidden neurons which is derived by using the method of estimating the Vapnik-Chervonenkis (VC) dimension is also given.

Tracking cohesive subgroups over time in inferred social networks

NASA Astrophysics Data System (ADS)

Chin, Alvin; Chignell, Mark; Wang, Hao

2010-04-01

As a first step in the development of community trackers for large-scale online interaction, this paper shows how cohesive subgroup analysis using the Social Cohesion Analysis of Networks (SCAN; Chin and Chignell 2008) and Data-Intensive Socially Similar Evolving Community Tracker (DISSECT; Chin and Chignell 2010) methods can be applied to the problem of identifying cohesive subgroups and tracking them over time. Three case studies are reported, and the findings are used to evaluate how well the SCAN and DISSECT methods work for different types of data. In the largest of the case studies, variations in temporal cohesiveness are identified across a set of subgroups extracted from the inferred social network. Further modifications to the DISSECT methodology are suggested based on the results obtained. The paper concludes with recommendations concerning further research that would be beneficial in addressing the community tracking problem for online data.

Analysing the hidden curriculum: use of a cultural web

PubMed Central

Mossop, Liz; Dennick, Reg; Hammond, Richard; Robbé, Iain

2013-01-01

CONTEXT Major influences on learning about medical professionalism come from the hidden curriculum. These influences can contribute positively or negatively towards the professional enculturation of clinical students. The fact that there is no validated method for identifying the components of the hidden curriculum poses problems for educators considering professionalism. The aim of this study was to analyse whether a cultural web, adapted from a business context, might assist in the identification of elements of the hidden curriculum at a UK veterinary school. METHODS A qualitative approach was used. Seven focus groups consisting of three staff groups and four student groups were organised. Questioning was framed using the cultural web, which is a model used by business owners to assess their environment and consider how it affects their employees and customers. The focus group discussions were recorded, transcribed and analysed thematically using a combination of a priori and emergent themes. RESULTS The cultural web identified elements of the hidden curriculum for both students and staff. These included: core assumptions; routines; rituals; control systems; organisational factors; power structures, and symbols. Discussions occurred about how and where these issues may affect students’ professional identity development. CONCLUSIONS The cultural web framework functioned well to help participants identify elements of the hidden curriculum. These aspects aligned broadly with previously described factors such as role models and institutional slang. The influence of these issues on a student’s development of a professional identity requires discussion amongst faculty staff, and could be used to develop learning opportunities for students. The framework is promising for the analysis of the hidden curriculum and could be developed as an instrument for implementation in other clinical teaching environments. PMID:23323652

Diagnosis and Management of Hidden Caries in a Primary Molar Tooth.

PubMed

Gera, Arwa; Zilberman, Uri

2017-01-01

Hidden caries is a dentinal lesion beneath the dentinoenamel junction, visible on radiographs. A single report described this lesion in primary dentition. This case report describes a case of hidden caries in a mandibular second primary molar, misdiagnosed as malignant swelling. A 3-year-old white girl was referred to the Department of Pediatric Dentistry with a chief complaint of pain and extraoral swelling on the right side of the mandible for the last 3 months. She was earlier referred to the surgical department for biopsy of the lesion. Radiographic and computed tomography scan examination showed a periapical lesion with buccal plate resorption and radiolucency beneath the enamel on the mesial part of tooth 85. The tooth was extracted, and follow-up of 2 years showed normal development of tooth 45. The main problem is early detection and treatment, since the outer surface of enamel may appear intact on tactile examination. Gera A, Zilberman U. Diagnosis and Management of Hidden Caries in a Primary Molar Tooth. Int J Clin Pediatr Dent 2017;10(1):99-102.

Mining Bug Databases for Unidentified Software Vulnerabilities

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

Dumidu Wijayasekara; Milos Manic; Jason Wright

2012-06-01

Identifying software vulnerabilities is becoming more important as critical and sensitive systems increasingly rely on complex software systems. It has been suggested in previous work that some bugs are only identified as vulnerabilities long after the bug has been made public. These vulnerabilities are known as hidden impact vulnerabilities. This paper discusses the feasibility and necessity to mine common publicly available bug databases for vulnerabilities that are yet to be identified. We present bug database analysis of two well known and frequently used software packages, namely Linux kernel and MySQL. It is shown that for both Linux and MySQL, amore » significant portion of vulnerabilities that were discovered for the time period from January 2006 to April 2011 were hidden impact vulnerabilities. It is also shown that the percentage of hidden impact vulnerabilities has increased in the last two years, for both software packages. We then propose an improved hidden impact vulnerability identification methodology based on text mining bug databases, and conclude by discussing a few potential problems faced by such a classifier.« less

High HIV prevalence among a high-risk subgroup of women attending sexually transmitted infection clinics in Pune, India.

PubMed

Mehta, Shruti H; Gupta, Amita; Sahay, Seema; Godbole, Sheela V; Joshi, Smita N; Reynolds, Steven J; Celentano, David D; Risbud, Arun; Mehendale, Sanjay M; Bollinger, Robert C

2006-01-01

To investigate changes over a decade in prevalence and correlates of HIV among high-risk women attending sexually transmitted infection (STI) clinics in Pune, India, who deny a history of commercial sex work (CSW). Cross-sectional. From 1993 to 2002, 2376 women attending 3 STI clinics in Pune were offered HIV screening. Women who denied CSW were included (n = 1020). Of 1020 women, 21% were HIV infected. The annual HIV prevalence increased from 14% in 1993 to 29% in 2001-2002 (P < 0.001). The change in HIV prevalence over time was paralleled by changes in clinic visitor characteristics; in later periods, women were older, more often employed, less likely to be currently married, and more likely to report condom use. In multivariate analysis, factors independently associated with HIV were calendar period (adjusted odds ratio [AOR], 1.9 for 1997-1999 vs. 1993-1996; 95% CI, 1.2-3.0; AOR, 2.3 for 2000-2002 vs. 1993-1996; 95% CI, 1.5-3.6), lack of formal education (AOR, 2.0; 95% CI, 1.4-2.9), having been widowed (AOR, 3.1; 95% CI, 1.6-6.1), current employment (AOR, 1.8; 95% CI, 1.2-2.6), and genital ulcer disease on examination (AOR, 1.8; 95% CI, 1.2-2.7). Women attending STI clinics in India who deny a history of CSW represent a small, hidden subgroup, likely put at risk for HIV because of high-risk behavior of their male partners, generally their husbands. Educational and awareness efforts that have targeted other subgroups in India (men and CSWs) should also focus on these hard-to-reach women. Risk reduction in this subgroup of Indian women would also be expected to reduce perinatal infections in India.

Experimental and Computational Studies on the Scattering of an Edge-Guided Wave by a Hidden Crack on a Racecourse Shaped Hole.

PubMed

Vien, Benjamin Steven; Rose, Louis Raymond Francis; Chiu, Wing Kong

2017-07-01

Reliable and quantitative non-destructive evaluation for small fatigue cracks, in particular those in hard-to-inspect locations, is a challenging problem. Guided waves are advantageous for structural health monitoring due to their slow geometrical decay of amplitude with propagating distance, which is ideal for rapid wide-area inspection. This paper presents a 3D laser vibrometry experimental and finite element analysis of the interaction between an edge-guided wave and a small through-thickness hidden edge crack on a racecourse shaped hole that occurs, in practice, as a fuel vent hole. A piezoelectric transducer is bonded on the straight edge of the hole to generate the incident wave. The excitation signal consists of a 5.5 cycle Hann-windowed tone burst of centre frequency 220 kHz, which is below the cut-off frequency for the first order Lamb wave modes (SH1). Two-dimensional fast Fourier transformation (2D FFT) is applied to the incident and scattered wave field along radial lines emanating from the crack mouth, so as to identify the wave modes and determine their angular variation and amplitude. It is shown experimentally and computationally that mid-plane symmetric edge waves can travel around the hole's edge to detect a hidden crack. Furthermore, the scattered wave field due to a small crack length, a , (compared to the wavelength λ of the incident wave) is shown to be equivalent to a point source consisting of a particular combination of body-force doublets. It is found that the amplitude of the scattered field increases quadratically as a function of a/λ , whereas the scattered wave pattern is independent of crack length for small cracks a < λ . This study of the forward scattering problem from a known crack size provides a useful guide for the inverse problem of hidden crack detection and sizing.

On the Role of Situational Stressors in the Disruption of Global Neural Network Stability during Problem Solving.

PubMed

Liu, Mengting; Amey, Rachel C; Forbes, Chad E

2017-12-01

When individuals are placed in stressful situations, they are likely to exhibit deficits in cognitive capacity over and above situational demands. Despite this, individuals may still persevere and ultimately succeed in these situations. Little is known, however, about neural network properties that instantiate success or failure in both neutral and stressful situations, particularly with respect to regions integral for problem-solving processes that are necessary for optimal performance on more complex tasks. In this study, we outline how hidden Markov modeling based on multivoxel pattern analysis can be used to quantify unique brain states underlying complex network interactions that yield either successful or unsuccessful problem solving in more neutral or stressful situations. We provide evidence that brain network stability and states underlying synchronous interactions in regions integral for problem-solving processes are key predictors of whether individuals succeed or fail in stressful situations. Findings also suggested that individuals utilize discriminate neural patterns in successfully solving problems in stressful or neutral situations. Findings overall highlight how hidden Markov modeling can provide myriad possibilities for quantifying and better understanding the role of global network interactions in the problem-solving process and how the said interactions predict success or failure in different contexts.

A Hidden Surface Algorithm for Computer Generated Halftone Pictures

DTIC Science & Technology

converting data describing three-dimensional objects into data that can be used to generate two-dimensional halftone images. It deals with some problems that arise in black and white, and color shading.

Proximal versus distal cue utilization in spatial navigation: the role of visual acuity?

PubMed

Carman, Heidi M; Mactutus, Charles F

2002-09-01

Proximal versus distal cue use in the Morris water maze is a widely accepted strategy for the dissociation of various problems affecting spatial navigation in rats such as aging, head trauma, lesions, and pharmacological or hormonal agents. Of the limited number of ontogenetic rat studies conducted, the majority have approached the problem of preweanling spatial navigation through a similar proximal-distal dissociation. An implicit assumption among all of these studies has been that the animal's visual system is sufficient to permit robust spatial navigation. We challenged this assumption and have addressed the role of visual acuity in spatial navigation in the preweanling Fischer 344-N rat by training animals to locate a visible (proximal) or hidden (distal) platform using double or null extramaze cues within the testing environment. All pups demonstrated improved performance across training, but animals presented with a visible platform, regardless of extramaze cues, simultaneously reached asymptotic performance levels; animals presented with a hidden platform, dependent upon location of extramaze cues, differentially reached asymptotic performance levels. Probe trial performance, defined by quadrant time and platform crossings, revealed that distal-double-cue pups demonstrated spatial navigational ability superior to that of the remaining groups. These results suggest that a pup's ability to spatially navigate a hidden platform is dependent on not only its response repertoire and task parameters, but also its visual acuity, as determined by the extramaze cue location within the testing environment. The standard hidden versus visible platform dissociation may not be a satisfactory strategy for the control of potential sensory deficits.

A general solution to the hidden-line problem. [to graphically represent aerodynamic stability derivatives

NASA Technical Reports Server (NTRS)

Hedgley, D. R., Jr.

1982-01-01

The requirements for computer-generated perspective projections of three dimensional objects has escalated. A general solution was developed. The theoretical solution to this problem is presented. The method is very efficient as it minimizes the selection of points and comparison of line segments and hence avoids the devastation of square-law growth.

Characterisation of vitamin and mineral supplement users differentiated according to their motives for using supplements: results of the German National Nutrition Monitoring (NEMONIT).

PubMed

Frey, Anne; Hoffmann, Ingrid; Heuer, Thorsten

2017-08-01

To characterise German vitamin and mineral supplement users differentiated by their motives for supplement use. Data were obtained from the German National Nutrition Monitoring (2010/11) via two 24 h dietary recalls and a telephone interview. Motive-based subgroups of supplement users were identified by factor and cluster analysis. Sociodemographic, lifestyle, health and dietary characteristics and supplement use were examined. Differences were analysed using χ 2 tests, logistic and linear regression models. Germany, nationwide. Individuals (n 1589) aged 18-80 years. Three motive-based subgroups were identified: a 'Prevention' subgroup (n 324), characterised by the motive to prevent nutrient deficiencies; a 'Prevention and additional benefits' subgroup (n 166), characterised by motives to prevent health problems and improve well-being and performance; and a 'Treatment' subgroup (n 136), characterised by motives to treat nutrient deficiencies or diseases. Members of the two prevention subgroups had a higher Healthy Eating Index score and tended to be more physically active than non-users. Those in the 'Prevention and additional benefits' subgroup supplemented with a greater number of micronutrients. Members of the 'Treatment' subgroup tended to be older and have a lower self-reported health status than non-users, and supplemented with a smaller number of micronutrients. The majority of supplement users take supplements for preventive purposes and they are more health conscious than non-users of supplements due to their concerns about developing health problems. Those supplementing for treatment purposes may have underlying health indications and may be more likely to benefit from supplementation than those supplementing for preventive purposes.

Effectiveness of AODV Protocol under Hidden Node Environment

NASA Astrophysics Data System (ADS)

Garg, Ruchi; Sharma, Himanshu; Kumar, Sumit

IEEE 802.11 is a standard for mobile ad hoc networks (MANET), implemented with various different protocols. Ad Hoc on Demand Distance Vector Routing (AODV) is one of the several protocols of IEEE 802.11, intended to provide various Quality of Service (QOS) parameters under acceptable range. To avoid the collision and interference the MAC protocol has only two solutions, one, to sense the physical carrier and second, to use the RTS/CTS handshake mechanism. But with the help of these methods AODV is not free from the problem of hidden nodes like other several protocols. Under the hidden node environment, performance of AODV depends upon various factors. The position of receiver and sender among the other nodes is very crucial and it affects the performance. Under the various situations the AODV is simulated with the help of NS2 and the outcomes are discussed.

Classification of Arnold-Beltrami flows and their hidden symmetries

NASA Astrophysics Data System (ADS)

Fré, P.; Sorin, A. S.

2015-07-01

In the context of mathematical hydrodynamics, we consider the group theory structure which underlies the so named ABC flows introduced by Beltrami, Arnold and Childress. Main reference points are Arnold's theorem stating that, for flows taking place on compact three manifolds ℳ3, the only velocity fields able to produce chaotic streamlines are those satisfying Beltrami equation and the modern topological conception of contact structures, each of which admits a representative contact one-form also satisfying Beltrami equation. We advocate that Beltrami equation is nothing else but the eigenstate equation for the first order Laplace-Beltrami operator ★ g d, which can be solved by using time-honored harmonic analysis. Taking for ℳ3, a torus T 3 constructed as ℝ3/Λ, where Λ is a crystallographic lattice, we present a general algorithm to construct solutions of the Beltrami equation which utilizes as main ingredient the orbits under the action of the point group B A of three-vectors in the momentum lattice *Λ. Inspired by the crystallographic construction of space groups, we introduce the new notion of a Universal Classifying Group which contains all space groups as proper subgroups. We show that the ★ g d eigenfunctions are naturally arranged into irreducible representations of and by means of a systematic use of the branching rules with respect to various possible subgroups we search and find Beltrami fields with non trivial hidden symmetries. In the case of the cubic lattice the point group is the proper octahedral group O24 and the Universal Classifying Group is a finite group G1536 of order |G1536| = 1536 which we study in full detail deriving all of its 37 irreducible representations and the associated character table. We show that the O24 orbits in the cubic lattice are arranged into 48 equivalence classes, the parameters of the corresponding Beltrami vector fields filling all the 37 irreducible representations of G1536. In this way we obtain an exhaustive classification of all generalized ABC- flows and of their hidden symmetries. We make several conceptual comments about the need of a field-theory yielding Beltrami equation as a field equation and/or an instanton equation and on the possible relation of Arnold-Beltrami flows with (supersymmetric) Chern-Simons gauge theories. We also suggest linear generalizations of Beltrami equation to higher odd-dimensions that are different from the non-linear one proposed by Arnold and possibly make contact with M-theory and the geometry of flux-compactifications.

Can callous-unemotional traits enhance the understanding, diagnosis, and treatment of serious conduct problems in children and adolescents? A comprehensive review.

PubMed

Frick, Paul J; Ray, James V; Thornton, Laura C; Kahn, Rachel E

2014-01-01

This article provides a comprehensive review of the research on the use of callous and unemotional (CU) traits for designating an important subgroup of children and adolescents with severe conduct problems. It focuses on the etiological significance of recognizing this subgroup of youths with severe conduct problems, its implications for diagnostic classification, and the treatment implications of this research. The review highlights limitations in existing research and provides directions for future research. The available research suggests that children and adolescents with severe conduct problems and elevated CU traits show distinct genetic, cognitive, emotional, biological, environmental, and personality characteristics that seem to implicate different etiological factors underlying their behavior problems relative to other youths with severe conduct problems. Recognizing these subgroups could be critical for guiding future research on the causes of severe conduct problems in children and adolescents. Further, children and adolescents with both severe conduct problems and elevated CU traits appear to be at risk for more severe and persistent antisocial outcomes, even controlling for the severity of their conduct problems, the age of onset of their conduct problems, and common comorbid problems, which supports the clinical importance of designating this group in diagnostic classification systems. Finally, although children and adolescents with both severe conduct problems and elevated CU traits tend to respond less positively to typical interventions provided in mental health and juvenile justice settings, they show positive responses to certain intensive interventions tailored to their unique emotional and cognitive characteristics. (PsycINFO Database Record (c) 2013 APA, all rights reserved).

Transitions in sleep problems from late adolescence to young adulthood: A longitudinal analysis of the effects of peer victimization.

PubMed

Chang, Ling-Yin; Chang, Hsing-Yi; Lin, Linen Nymphas; Wu, Chi-Chen; Yen, Lee-Lan

2018-01-01

Adolescence is a developmental period with high vulnerability to sleep problems. However, research identifying distinct patterns and underlying determinants of sleep problems is scarce. This study investigated discrete subgroups of, changes in, and stability of sleep problems. We also examined whether peer victimization influenced sleep problem subgroups and transitions in patterns of sleep problems from late adolescence to young adulthood. Sex differences in the effects of peer victimization were also explored. In total, 1,455 male and 1,399 female adolescents from northern Taiwan participated in this longitudinal study. Latent transition analysis was used to examine changes in patterns of sleep problems and the effects of peer victimization on these changes. We identified three subgroups of sleep problems in males and two in females, and found that there was a certain level of instability in patterns of sleep problems during the study period. For both sexes, those with greater increases in peer victimization over time were more likely to change from being a good sleeper to a poor sleeper. The effects of peer victimization on baseline status of sleep problems, however, was only significant for males, with those exposed to higher levels of peer victimization more likely to be poor sleepers at baseline. Our findings reveal an important role of peer victimization in predicting transitions in patterns of sleep problems. Intervention programs aimed at decreasing peer victimization may help reduce the development and escalation of sleep problems among adolescents, especially in males. © 2017 Wiley Periodicals, Inc.

Latent profiles of problem behavior within learning, peer, and teacher contexts: identifying subgroups of children at academic risk across the preschool year.

PubMed

Bulotsky-Shearer, Rebecca J; Bell, Elizabeth R; Domínguez, Ximena

2012-12-01

Employing a developmental and ecological model, the study identified initial levels and rates of change in academic skills for subgroups of preschool children exhibiting problem behavior within routine classroom situations. Six distinct latent profile types of emotional and behavioral adjustment were identified for a cohort of low-income children early in the preschool year (N=4417). Profile types provided a descriptive picture of patterns of classroom externalizing, internalizing, and situational adjustment problems common to subgroups of children early in the preschool year. The largest profile type included children who exhibited low problem behavior and were characterized as well-adjusted to the preschool classroom early in the year. The other profile types were characterized by distinct combinations of elevated internalizing, externalizing, and situational problem behavior. Multinomial logistic regression identified younger children and boys at increased risk for classification in problem types, relative to the well-adjusted type. Latent growth models indicated that children classified within the extremely socially and academically disengaged profile type, started and ended the year with the lowest academic skills, relative to all other types. Implications for future research, policy, and practice are discussed. Copyright © 2012 Society for the Study of School Psychology. Published by Elsevier Ltd. All rights reserved.

Diagnosis of hidden bronchial obstruction using computer-assessed tracheal forced expiratory noise time.

PubMed

Pochekutova, Irina A; Korenbaum, Vladimir I

2013-04-01

Increased forced expiratory time was first recognized as a marker of obstruction half a century ago. However, the reported diagnostic capabilities of both auscultated forced expiratory time (FET(as)) and spirometric forced expiratory time are contradictory. Computer analysis of respiratory noises provides a precise estimation of acoustic forced expiratory noise time (FET(a)) being the object-measured analogue of FET(as). The aim of this study was to analyse FET(a) diagnostic capabilities in patients with asthma based on the hypothesis that FET(a) could reveal hidden bronchial obstruction. A group of asthma patients involved 149 males aged 16-25 years. In this group, 71 subjects had spirometry features of bronchial obstruction, meanwhile, the remaining 78 had normal spirometry. A control group involved 77 healthy subjects. Spirometry and forced expiratory tracheal noise recording were sequentially measured for each participant. FET(a) values were estimated by means of a developed computer procedure, including bandpass filtration (200-2000 Hz), waveform envelope calculation with accumulation period of 0.01 s, automated measurement of FET(a) at 0.5% level from the peak amplitude. Specificity, sensitivity and area under Receiver Operating Characteristic curve of FET(a) and its ratios to squared chest circumference, height, weight were indistinguishable with baseline spirometry index FEV1 /forced vital capacity. Meanwhile, acoustic features of obstruction were revealed in 41%-49% of subgroup of patients with asthma but normal spirometry. FET(a) of tracheal noise and its ratio to anthropometric parameters seem to be sensitive and specific tests of hidden bronchial obstruction in young male asthma patients. © 2012 The Authors. Respirology © 2012 Asian Pacific Society of Respirology.

Problems of Indicator Weights and Multicolinearity in World University Rankings: Comparisons of Three Systems

ERIC Educational Resources Information Center

Soh, Kaycheng

2014-01-01

World university rankings (WUR) use the weight-and-sum approach to arrive at an overall measure which is then used to rank the participating universities of the world. Although the weight-and-sum procedure seems straightforward and accords with common sense, it has hidden methodological or statistical problems which render the meaning of the…

Disconnected Youth in the Research Triangle Region: An Ominous Problem Hidden in Plain Sight

ERIC Educational Resources Information Center

Dodson, David; Guillory, Ferrel; Lipsitz, Joan; Raper, Noah; Rausch, Christina

2008-01-01

In September 2006, the North Carolina GlaxoSmithKline Foundation commissioned MDC, Inc. of Chapel Hill to analyze the problem of "disconnected youth" in the Research Triangle region, determine the current state of the region's responses to the challenge, and recommend steps to deepen and accelerate action on the issue. The research process was…

A Short-Term Population Model of the Suicide Risk: The Case of Spain.

PubMed

De la Poza, Elena; Jódar, Lucas

2018-06-14

A relevant proportion of deaths by suicide have been attributed to other causes that produce the number of suicides remains hidden. The existence of a hidden number of cases is explained by the nature of the problem. Problems like this involve violence, and produce fear and social shame in victims' families. The existence of violence, fear and social shame experienced by victims favours a considerable number of suicides, identified as accidents or natural deaths. This paper proposes a short time discrete compartmental mathematical model to measure the suicidal risk for the case of Spain. The compartment model classifies and quantifies the amount of the Spanish population within the age intervals (16, 78) by their degree of suicide risk and their changes over time. Intercompartmental transits are due to the combination of quantitative and qualitative factors. Results are computed and simulations are performed to analyze the sensitivity of the model under uncertain coefficients.

Problems experienced by people with arthritis when using a computer.

PubMed

Baker, Nancy A; Rogers, Joan C; Rubinstein, Elaine N; Allaire, Saralynn H; Wasko, Mary Chester

2009-05-15

To describe the prevalence of computer use problems experienced by a sample of people with arthritis, and to determine differences in the magnitude of these problems among people with rheumatoid arthritis (RA), osteoarthritis (OA), and fibromyalgia (FM). Subjects were recruited from the Arthritis Network Disease Registry and asked to complete a survey, the Computer Problems Survey, which was developed for this study. Descriptive statistics were calculated for the total sample and the 3 diagnostic subgroups. Ordinal regressions were used to determine differences between the diagnostic subgroups with respect to each equipment item while controlling for confounding demographic variables. A total of 359 respondents completed a survey. Of the 315 respondents who reported using a computer, 84% reported a problem with computer use attributed to their underlying disorder, and approximately 77% reported some discomfort related to computer use. Equipment items most likely to account for problems and discomfort were the chair, keyboard, mouse, and monitor. Of the 3 subgroups, significantly more respondents with FM reported more severe discomfort, more problems, and greater limitations related to computer use than those with RA or OA for all 4 equipment items. Computer use is significantly affected by arthritis. This could limit the ability of a person with arthritis to participate in work and home activities. Further study is warranted to delineate disease-related limitations and develop interventions to reduce them.

Risk profiles for poor treatment response to internet-delivered CBT in people with social anxiety disorder.

PubMed

Tillfors, Maria; Furmark, Tomas; Carlbring, Per; Andersson, Gerhard

2015-06-01

In social anxiety disorder (SAD) co-morbid depressive symptoms as well as avoidance behaviors have been shown to predict insufficient treatment response. It is likely that subgroups of individuals with different profiles of risk factors for poor treatment response exist. This study aimed to identify subgroups of social avoidance and depressive symptoms in a clinical sample (N = 167) with SAD before and after guided internet-delivered CBT, and to compare these groups on diagnostic status and social anxiety. We further examined individual movement between subgroups over time. Using cluster analysis we identified four subgroups, including a high-problem cluster at both time-points. Individuals in this cluster showed less remission after treatment, exhibited higher levels of social anxiety at both assessments, and typically remained in the high-problem cluster after treatment. Thus, in individuals with SAD, high levels of social avoidance and depressive symptoms constitute a risk profile for poor treatment response. Copyright © 2015 Elsevier Ltd. All rights reserved.

A Simulation Study of Methods for Selecting Subgroup-Specific Doses in Phase I Trials

PubMed Central

Morita, Satoshi; Thall, Peter F.; Takeda, Kentaro

2016-01-01

Summary Patient heterogeneity may complicate dose-finding in phase I clinical trials if the dose-toxicity curves differ between subgroups. Conducting separate trials within subgroups may lead to infeasibly small sample sizes in subgroups having low prevalence. Alternatively, it is not obvious how to conduct a single trial while accounting for heterogeneity. To address this problem, we consider a generalization of the continual reassessment method (O’Quigley, et al., 1990) based on a hierarchical Bayesian dose-toxicity model that borrows strength between subgroups under the assumption that the subgroups are exchangeable. We evaluate a design using this model that includes subgroup-specific dose selection and safety rules. A simulation study is presented that includes comparison of this method to three alternative approaches, based on non-hierarchical models, that make different types of assumptions about within-subgroup dose-toxicity curves. The simulations show that the hierarchical model-based method is recommended in settings where the dose-toxicity curves are exchangeable between subgroups. We present practical guidelines for application, and provide computer programs for trial simulation and conduct. PMID:28111916

Hypovigilance Detection for UCAV Operators Based on a Hidden Markov Model

PubMed Central

Kwon, Namyeon; Shin, Yongwook; Ryo, Chuh Yeop; Park, Jonghun

2014-01-01

With the advance of military technology, the number of unmanned combat aerial vehicles (UCAVs) has rapidly increased. However, it has been reported that the accident rate of UCAVs is much higher than that of manned combat aerial vehicles. One of the main reasons for the high accident rate of UCAVs is the hypovigilance problem which refers to the decrease in vigilance levels of UCAV operators while maneuvering. In this paper, we propose hypovigilance detection models for UCAV operators based on EEG signal to minimize the number of occurrences of hypovigilance. To enable detection, we have applied hidden Markov models (HMMs), two of which are used to indicate the operators' dual states, normal vigilance and hypovigilance, and, for each operator, the HMMs are trained as a detection model. To evaluate the efficacy and effectiveness of the proposed models, we conducted two experiments on the real-world data obtained by using EEG-signal acquisition devices, and they yielded satisfactory results. By utilizing the proposed detection models, the problem of hypovigilance of UCAV operators and the problem of high accident rate of UCAVs can be addressed. PMID:24963338

Adult-acquired hidden penis in obese patients: a critical survey of the literature.

PubMed

Cavayero, Chase T; Cooper, Meghan A; Harlin, Stephen L

2015-03-01

Hidden penis is anatomically defined by a lack of firm attachments of the skin and dartos fascia to the underlying Buck fascia. To critically appraise the research evidence that could support the most effective surgical techniques for adult-acquired hidden penis in obese patients. Studies investigating patients with a diagnosis of hidden penis were identified. Of these studies, only those with adult patients classified as overweight or obese (body mass index >25) were included in the review. Three reviewers examined the abstracts of the studies identified in the initial Medline search, and abstracts considered potentially relevant underwent full-text review. Studies that included patients with congenital, iatrogenic (eg, circumcision issues or aesthetic genital surgery), or traumatic causes of hidden penis were excluded. Studies that did not define the diagnostic criteria for hidden penis were excluded to minimize the risk of definition bias. The quality of evidence for each study was determined after considering the following sources of bias: method of allocation to study groups, data analysis, presence of baseline differences between groups, objectivity of outcome, and completeness of follow-up. Using these criteria, studies were then graded as high, moderate, or low in quality. Seven studies with a total of 119 patients met the inclusion criteria. All but 1 of the studies were nonrandomized. One study provided a clear presentation of results and appropriate statistical analysis. Six studies accounted for individual-based differences, and 1 study failed to account for baseline differences altogether. Four studies addressed follow-up. One study was of high quality, 2 were of moderate quality, and 4 were of low quality. Building a clinical practice guideline for the surgical management of hidden penis has proven difficult because of a lack of high-quality, statistically significant data in the research synthesis. The authors elucidate the challenges and epitomize the collective wisdom of surgeons who have investigated this problem and emphasize the need for rigorous evaluative studies. © 2015 The American Osteopathic Association.

Self-growing neural network architecture using crisp and fuzzy entropy

NASA Technical Reports Server (NTRS)

Cios, Krzysztof J.

1992-01-01

The paper briefly describes the self-growing neural network algorithm, CID2, which makes decision trees equivalent to hidden layers of a neural network. The algorithm generates a feedforward architecture using crisp and fuzzy entropy measures. The results of a real-life recognition problem of distinguishing defects in a glass ribbon and of a benchmark problem of differentiating two spirals are shown and discussed.

Chronic Elementary Absenteeism: A Problem Hidden in Plain Sight. A Research Brief from Attendance Works and Child & Family Policy Center

ERIC Educational Resources Information Center

Bruner, Charles; Discher, Anne; Chang, Hedy

2011-01-01

Chronic absenteeism--or missing 10 percent or more of school days for any reason--is a proven early warning sign of academic risk and school dropout. Too often, though, this problem is overlooked, especially among elementary students, because of the way attendance data are tracked. This study confirms the premise that districts and schools may…

Fundamental Study on Quantum Nanojets

DTIC Science & Technology

2004-08-01

Pergamon Press. Bell , J. S . 1966 On the problem of hidden variables in quantum mechanics. Rev. of Modern Phys., 38, 447. Berndl, K., Daumer, M...fluid dynamics based on two quantum mechanical perspectives; Schrödinger’s wave mechanics and quantum fluid dynamics based on Hamilton-Jacoby...References 8 2). Direct Problems a). Quantum fluid dynamics formalism based on Hamilton-Jacoby equation are adapted for the numerical

Psychosocial Health Problems Associated with Increased HIV Risk Behavior among Men Who Have Sex with Men in Nepal: A Cross-Sectional Survey

PubMed Central

Deuba, Keshab; Ekström, Anna Mia; Shrestha, Rachana; Ionita, George; Bhatta, Laxmi; Karki, Deepak Kumar

2013-01-01

Background Men who have sex with men (MSM) are marginalized, hidden, underserved and at high risk for HIV in Nepal. We examined the association between MSM sub-populations, psychosocial health problems and support, access to prevention and non-use of condoms. Methods Between September-November of 2010, a cross-sectional survey on HIV-related risk behavior was performed across Nepal through snowball sampling facilitated by non-governmental organizations, recruiting 339 MSM, age 15 or older. The primary outcomes were: (a) non-use of condoms at least once in last three anal sex encounters with men and (b) non-use of condoms with women in the last encounter. The secondary outcome was participation in HIV prevention interventions in the past year. Results Among the 339 MSM interviewed, 78% did not use condoms at their last anal sex with another man, 35% did not use condoms in their last sex with a woman, 70% had experienced violence in the last 12 months, 61% were experiencing depression and 47% had thought of committing suicide. After adjustment for age, religion, marital status, and MSM subpopulations (bisexual, ta, meti, gay), non-use of condoms at last anal sex with a man was significantly associated with non-participation in HIV interventions, experience of physical and sexual violence, depression, repeated suicidal thoughts, small social support network and being dissatisfied with social support. Depression was marginally associated with non-use of condoms with women. The findings suggest that among MSM who reported non-use of condoms at last anal sex, the ta subgroup and those lacking family acceptance were the least likely to have participated in any preventive interventions. Conclusions MSM in Nepal have a prevalence of psychosocial health problems in turn associated with high risk behavior for HIV. Future HIV prevention efforts targeting MSM in Nepal should cover all MSM subpopulations and prioritize psychosocial health interventions. PMID:23516434

Psychosocial health problems associated with increased HIV risk behavior among men who have sex with men in Nepal: a cross-sectional survey.

PubMed

Deuba, Keshab; Ekström, Anna Mia; Shrestha, Rachana; Ionita, George; Bhatta, Laxmi; Karki, Deepak Kumar

2013-01-01

Men who have sex with men (MSM) are marginalized, hidden, underserved and at high risk for HIV in Nepal. We examined the association between MSM sub-populations, psychosocial health problems and support, access to prevention and non-use of condoms. Between September-November of 2010, a cross-sectional survey on HIV-related risk behavior was performed across Nepal through snowball sampling facilitated by non-governmental organizations, recruiting 339 MSM, age 15 or older. The primary outcomes were: (a) non-use of condoms at least once in last three anal sex encounters with men and (b) non-use of condoms with women in the last encounter. The secondary outcome was participation in HIV prevention interventions in the past year. Among the 339 MSM interviewed, 78% did not use condoms at their last anal sex with another man, 35% did not use condoms in their last sex with a woman, 70% had experienced violence in the last 12 months, 61% were experiencing depression and 47% had thought of committing suicide. After adjustment for age, religion, marital status, and MSM subpopulations (bisexual, ta, meti, gay), non-use of condoms at last anal sex with a man was significantly associated with non-participation in HIV interventions, experience of physical and sexual violence, depression, repeated suicidal thoughts, small social support network and being dissatisfied with social support. Depression was marginally associated with non-use of condoms with women. The findings suggest that among MSM who reported non-use of condoms at last anal sex, the ta subgroup and those lacking family acceptance were the least likely to have participated in any preventive interventions. MSM in Nepal have a prevalence of psychosocial health problems in turn associated with high risk behavior for HIV. Future HIV prevention efforts targeting MSM in Nepal should cover all MSM subpopulations and prioritize psychosocial health interventions.

Unsupervised Learning Through Randomized Algorithms for High-Volume High-Velocity Data (ULTRA-HV).

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

Pinar, Ali; Kolda, Tamara G.; Carlberg, Kevin Thomas

Through long-term investments in computing, algorithms, facilities, and instrumentation, DOE is an established leader in massive-scale, high-fidelity simulations, as well as science-leading experimentation. In both cases, DOE is generating more data than it can analyze and the problem is intensifying quickly. The need for advanced algorithms that can automatically convert the abundance of data into a wealth of useful information by discovering hidden structures is well recognized. Such efforts however, are hindered by the massive volume of the data and its high velocity. Here, the challenge is developing unsupervised learning methods to discover hidden structure in high-volume, high-velocity data.

HIPPI: highly accurate protein family classification with ensembles of HMMs.

PubMed

Nguyen, Nam-Phuong; Nute, Michael; Mirarab, Siavash; Warnow, Tandy

2016-11-11

Given a new biological sequence, detecting membership in a known family is a basic step in many bioinformatics analyses, with applications to protein structure and function prediction and metagenomic taxon identification and abundance profiling, among others. Yet family identification of sequences that are distantly related to sequences in public databases or that are fragmentary remains one of the more difficult analytical problems in bioinformatics. We present a new technique for family identification called HIPPI (Hierarchical Profile Hidden Markov Models for Protein family Identification). HIPPI uses a novel technique to represent a multiple sequence alignment for a given protein family or superfamily by an ensemble of profile hidden Markov models computed using HMMER. An evaluation of HIPPI on the Pfam database shows that HIPPI has better overall precision and recall than blastp, HMMER, and pipelines based on HHsearch, and maintains good accuracy even for fragmentary query sequences and for protein families with low average pairwise sequence identity, both conditions where other methods degrade in accuracy. HIPPI provides accurate protein family identification and is robust to difficult model conditions. Our results, combined with observations from previous studies, show that ensembles of profile Hidden Markov models can better represent multiple sequence alignments than a single profile Hidden Markov model, and thus can improve downstream analyses for various bioinformatic tasks. Further research is needed to determine the best practices for building the ensemble of profile Hidden Markov models. HIPPI is available on GitHub at https://github.com/smirarab/sepp .

Nonlinear dynamical modes of climate variability: from curves to manifolds

NASA Astrophysics Data System (ADS)

Gavrilov, Andrey; Mukhin, Dmitry; Loskutov, Evgeny; Feigin, Alexander

2016-04-01

The necessity of efficient dimensionality reduction methods capturing dynamical properties of the system from observed data is evident. Recent study shows that nonlinear dynamical mode (NDM) expansion is able to solve this problem and provide adequate phase variables in climate data analysis [1]. A single NDM is logical extension of linear spatio-temporal structure (like empirical orthogonal function pattern): it is constructed as nonlinear transformation of hidden scalar time series to the space of observed variables, i. e. projection of observed dataset onto a nonlinear curve. Both the hidden time series and the parameters of the curve are learned simultaneously using Bayesian approach. The only prior information about the hidden signal is the assumption of its smoothness. The optimal nonlinearity degree and smoothness are found using Bayesian evidence technique. In this work we do further extension and look for vector hidden signals instead of scalar with the same smoothness restriction. As a result we resolve multidimensional manifolds instead of sum of curves. The dimension of the hidden manifold is optimized using also Bayesian evidence. The efficiency of the extension is demonstrated on model examples. Results of application to climate data are demonstrated and discussed. The study is supported by Government of Russian Federation (agreement #14.Z50.31.0033 with the Institute of Applied Physics of RAS). 1. Mukhin, D., Gavrilov, A., Feigin, A., Loskutov, E., & Kurths, J. (2015). Principal nonlinear dynamical modes of climate variability. Scientific Reports, 5, 15510. http://doi.org/10.1038/srep15510

Naturalness of Electroweak Symmetry Breaking

NASA Astrophysics Data System (ADS)

Espinosa, J. R.

2007-02-01

After revisiting the hierarchy problem of the Standard Model and its implications for the scale of New Physics, I consider the fine tuning problem of electroweak symmetry breaking in two main scenarios beyond the Standard Model: SUSY and Little Higgs models. The main conclusions are that New Physics should appear on the reach of the LHC; that some SUSY models can solve the hierarchy problem with acceptable residual fine tuning and, finally, that Little Higgs models generically suffer from large tunings, many times hidden.

Gender by Preferred Gambling Activity in Treatment Seeking Problem Gamblers: A Comparison of Subgroup Characteristics and Treatment Outcomes.

PubMed

Khanbhai, Yasmin; Smith, David; Battersby, Malcolm

2017-03-01

Problem gambling is a growing public health concern and treatment incompletion levels remain high. The study aims to support and extend previous studies in relation to the heterogeneity of the gambling population based on gender and gambling type, and the implications of subgroup differences on treatment outcomes. Additionally, the concept of drop-out is addressed in terms of categorical treatment measures. The empirical findings are examined in the context of the theoretical framework of the pathways model. Participants were recruited from the Statewide Gambling Therapy Service and stratified into subgroups based on gender and gambling mode preference [Electronic Gambling Machines (EGM) or track race betters]. Baseline predictors collected and analysed using multinomial logistical regression included demographic information as well as gambling variables, while treatment outcomes consisted of three therapist rated measures. Significant differences between the subgroups were found for age, marital and employment status, gambling duration, alcohol use and the Kessler 10 measure of psychological distress. Specifically, male track race gamblers were younger, married, employed, had a longer duration of gambling, higher alcohol use and lower psychological distress relative to EGM users. No difference was found in any of the treatment outcomes, however, consistent with previous studies, all subgroups had high treatment incompletion levels. The findings demonstrate the importance of screening, assessing and treating problem gamblers as a heterogeneous group with different underlying demographics and psychopathologies. It is also hoped future studies will continue to address treatment incompletion with a re-conceptualisation of the term drop-out.

Patterns of Alcohol Use Among Canadian Military Personnel and Their Associations With Health and Well-Being.

PubMed

Richer, Isabelle; Lee, Jennifer E C; Born, Jennifer

2016-04-07

Heavy drinking increases the risk of injury, adverse physical and mental health outcomes, and loss of productivity. Nonetheless, patterns of alcohol use and related symptomatology among military personnel remain poorly understood. A latent class analysis (LCA) was used to explore the presence of subgroups of alcohol users among Canadian Armed Forces (CAF) Regular Forces members. Correlates of empirically derived subgroups were further explored. Analyses were performed on a subsample of alcohol users who participated in a 2008/09 cross-sectional survey of a stratified random sample of currently serving CAF Regular Force members (N = 1980). Multinomial logistic regression models were conducted to verify physical and mental health differences across subgroups of alcohol users. All analyses were adjusted for complex survey design. A 4-class solution was considered the best fit for the data. Subgroups were labeled as follows: Class 1 - Infrequent drinkers (27.2%); Class 2 - Moderate drinkers (41.5%); Class 3 - Regular binge drinkers with minimal problems (14.8%); and Class 4 - Problem drinkers (16.6%). Significant differences by age, sex, marital status, element, rank, recent serious injuries, chronic conditions, psychological distress, posttraumatic stress disorder, and depression symptoms were found across the subgroups. Problem drinkers demonstrated the most degraded physical and mental health. Findings highlight the heterogeneity of alcohol users and heavy drinkers among CAF members and the need for tailored interventions addressing high-risk alcohol use. Results have the potential to inform prevention strategies and screening efforts. (PsycINFO Database Record (c) 2016 APA, all rights reserved).

Confocal non-line-of-sight imaging based on the light-cone transform

NASA Astrophysics Data System (ADS)

O’Toole, Matthew; Lindell, David B.; Wetzstein, Gordon

2018-03-01

How to image objects that are hidden from a camera’s view is a problem of fundamental importance to many fields of research, with applications in robotic vision, defence, remote sensing, medical imaging and autonomous vehicles. Non-line-of-sight (NLOS) imaging at macroscopic scales has been demonstrated by scanning a visible surface with a pulsed laser and a time-resolved detector. Whereas light detection and ranging (LIDAR) systems use such measurements to recover the shape of visible objects from direct reflections, NLOS imaging reconstructs the shape and albedo of hidden objects from multiply scattered light. Despite recent advances, NLOS imaging has remained impractical owing to the prohibitive memory and processing requirements of existing reconstruction algorithms, and the extremely weak signal of multiply scattered light. Here we show that a confocal scanning procedure can address these challenges by facilitating the derivation of the light-cone transform to solve the NLOS reconstruction problem. This method requires much smaller computational and memory resources than previous reconstruction methods do and images hidden objects at unprecedented resolution. Confocal scanning also provides a sizeable increase in signal and range when imaging retroreflective objects. We quantify the resolution bounds of NLOS imaging, demonstrate its potential for real-time tracking and derive efficient algorithms that incorporate image priors and a physically accurate noise model. Additionally, we describe successful outdoor experiments of NLOS imaging under indirect sunlight.

Confocal non-line-of-sight imaging based on the light-cone transform.

PubMed

O'Toole, Matthew; Lindell, David B; Wetzstein, Gordon

2018-03-15

How to image objects that are hidden from a camera's view is a problem of fundamental importance to many fields of research, with applications in robotic vision, defence, remote sensing, medical imaging and autonomous vehicles. Non-line-of-sight (NLOS) imaging at macroscopic scales has been demonstrated by scanning a visible surface with a pulsed laser and a time-resolved detector. Whereas light detection and ranging (LIDAR) systems use such measurements to recover the shape of visible objects from direct reflections, NLOS imaging reconstructs the shape and albedo of hidden objects from multiply scattered light. Despite recent advances, NLOS imaging has remained impractical owing to the prohibitive memory and processing requirements of existing reconstruction algorithms, and the extremely weak signal of multiply scattered light. Here we show that a confocal scanning procedure can address these challenges by facilitating the derivation of the light-cone transform to solve the NLOS reconstruction problem. This method requires much smaller computational and memory resources than previous reconstruction methods do and images hidden objects at unprecedented resolution. Confocal scanning also provides a sizeable increase in signal and range when imaging retroreflective objects. We quantify the resolution bounds of NLOS imaging, demonstrate its potential for real-time tracking and derive efficient algorithms that incorporate image priors and a physically accurate noise model. Additionally, we describe successful outdoor experiments of NLOS imaging under indirect sunlight.

Phasic Triplet Markov Chains.

PubMed

El Yazid Boudaren, Mohamed; Monfrini, Emmanuel; Pieczynski, Wojciech; Aïssani, Amar

2014-11-01

Hidden Markov chains have been shown to be inadequate for data modeling under some complex conditions. In this work, we address the problem of statistical modeling of phenomena involving two heterogeneous system states. Such phenomena may arise in biology or communications, among other fields. Namely, we consider that a sequence of meaningful words is to be searched within a whole observation that also contains arbitrary one-by-one symbols. Moreover, a word may be interrupted at some site to be carried on later. Applying plain hidden Markov chains to such data, while ignoring their specificity, yields unsatisfactory results. The Phasic triplet Markov chain, proposed in this paper, overcomes this difficulty by means of an auxiliary underlying process in accordance with the triplet Markov chains theory. Related Bayesian restoration techniques and parameters estimation procedures according to the new model are then described. Finally, to assess the performance of the proposed model against the conventional hidden Markov chain model, experiments are conducted on synthetic and real data.

Nondestructive detection of infested chestnuts based on NIR spectroscopy

USDA-ARS?s Scientific Manuscript database

Insect feeding is a significant postharvest problem for processors of Chestnuts (Castanea sativa, Miller). In most cases, damage from insects is 'hidden', i.e. not visually detectable on the fruit surface. Consequently, traditional sorting techniques, including manual sorting, are generally inadequa...

A First Course in Intercultural Communication.

ERIC Educational Resources Information Center

Goodyear, F. H.; Williams, Patrick L.

The Texas Christian University course description, outline, and supporting bibliography deal with the problems of intercultural, interracial communication. The course plan begins with the thesis that racism is institutionalized and that the eradication of racism requires changes in individuals' awareness of their own hidden discriminatory…

Normal Science Education and Its Dangers: The Case of School Chemistry.

ERIC Educational Resources Information Center

Van Berkel, Berry; De Vos, Wobbe; Verdonk, Adri H.; Pilot, Albert

2000-01-01

Attempts to solve the problem of hidden structure in school chemistry. Argues that normal chemistry education is isolated from common sense, everyday life and society, the history and philosophy of science, technology, school physics, and chemical research. (Author/CCM)

National Security Policy and Security Challenges of Maldives

DTIC Science & Technology

2014-06-13

creates the true problems the Maldivians are currently facing. Hidden agendas, unprofessionalism, and low ethical standards of politicians and...based on sharia law. The theories of cultural relativism and democracy strongly advocate the freedoms of societies, thus the Maldivian decision as a

Monitoring the Future: National Survey Results on Drug Use, 1975-2008. Volume I, Secondary School Students. NIH Publication No. 09-7402

ERIC Educational Resources Information Center

Johnston, Lloyd D.; O'Malley, Patrick M.; Bachman, Jerald G.; Schulenberg, John E.

2009-01-01

The Monitoring the Future study has provided the nation with a window into the important, but largely hidden, problem behaviors of illicit drug use, alcohol use, and tobacco use. It has provided a clearer view of the changing topography of these problems among adolescents and adults, a better understanding of the dynamics of factors that drive…

Monitoring the Future: National Survey Results on Drug Use, 1975-2007. Volume I, Secondary School Students. NIH Publication No. 08-6418A

ERIC Educational Resources Information Center

Johnston, Lloyd D.; O'Malley, Patrick M.; Bachman, Jerald G.; Schulenberg, John E.

2008-01-01

The Monitoring the Future study has provided the nation with a window into the important, but largely hidden, problem behaviors of illicit drug use, alcohol use, and tobacco use. It has provided a clearer view of the changing topography of these problems among adolescents and adults, a better understanding of the dynamics of factors that drive…

Monitoring the Future: National Survey Results on Drug Use, 1975-2006. Volume I: Secondary School Students. NIH Publication No. 07-6205

ERIC Educational Resources Information Center

Johnston, Lloyd D.; O'Malley, Patrick M.; Bachman, Jerald G.; Schulenberg, John E.

2007-01-01

The Monitoring the Future study has provided the nation with a window into the important, but largely hidden, problem behaviors of illicit drug use, alcohol use, and tobacco use. It has provided a clearer view of the changing topography of these problems among adolescents and adults, a better understanding of the dynamics of factors that drive…

Immigrant sexual minority Latino men in rural North Carolina: an exploration of social context, social behaviors, and sexual outcomes.

PubMed

Gilbert, Paul A; Rhodes, Scott D

2014-01-01

Immigrant sexual minority Latino men-who may or may not self-identify as gay-constitute a minority within a minority. Often labeled "hidden" and "hard-to-reach," and marginalized along multiple dimensions, it is a subgroup about whom little is known. Informed by a social ecological framework, we sought to describe key social variables for 190 such men in rural North Carolina and to test associations with three sexual outcomes: consistent condom use, number of sex partners, and sexual compulsivity. Participants reported limited English-language use, predominantly Latino close friends, middle levels of social support despite numerous social ties, and frequent experiences of discrimination. There were unique sets of correlates for each sexual outcome. Findings may inform health promotion interventions and guide future research.

The dynamics of corruptogenic organizations.

PubMed

Kleinberg, Jeffrey

2014-10-01

Corruptogenic organizational dynamics have been largely ignored in reporting about recent corporate scandals. Using a large group framework, the author identifies factors within an organization that create a breeding ground for unethical or illegal behavior and attract individuals unconsciously looking for ways to damage themselves or others. An organizational culture that promotes questionable attitudes and behaviors along with subgroups that produce powerful corruptive forces can destroy a firm and damage the economy. Enron and the Madoff investment group are identified as corruptogenic organizations put together by founders and a leadership core bent on self-destruction and traumatizing the community-outcomes beyond that which are usually linked to greed. Suggestions are provided to organizational consultants and policy makers as to how to determine the potential for corruption hidden in their midst and to implement countervailing structures and processes.

Object permanence in the food-storing coal tit (Periparus ater) and the non-storing great tit (Parus major): Is the mental representation required?

PubMed

Marhounová, Lucie; Frynta, Daniel; Fuchs, Roman; Landová, Eva

2017-05-01

Object permanence is a cognitive ability that enables animals to mentally represent the continuous existence of temporarily hidden objects. Generally, it develops gradually through six qualitative stages, the evolution of which may be connected with some specific ecological and behavioral factors. In birds, the advanced object permanence skills were reported in several storing species of the Corvidae family. In order to test the association between food-storing and achieved performance within the stages, we compared food-storing coal tits (Periparus ater) and nonstoring great tits (Parus major) using an adapted version of Uzgiris & Hunt's Scale 1 tasks. The coal tits significantly outperformed the great tits in searching for completely hidden objects. Most of the great tits could not solve the task when the object disappeared completely. However, the upper limit for both species is likely to be Stage 4. The coal tits could solve problems with simply hidden objects, but they used alternative strategies rather than mental representation when searching for completely hidden objects, especially if choosing between two locations. Our results also suggest that neophobia did not affect the overall performance in the object permanence tasks. (PsycINFO Database Record (c) 2017 APA, all rights reserved).

Asperger syndrome and "non-verbal learning problems" in a longitudinal perspective: neuropsychological and social adaptive outcome in early adult life.

PubMed

Hagberg, Bibbi S; Nydén, Agneta; Cederlund, Mats; Gillberg, Christopher

2013-12-15

Co-existence of Asperger syndrome (AS) and non-verbal learning disability (NLD) has been proposed based on the observation that people with AS tend to have significantly higher verbal than performance IQ (VIQ > PIQ by ≥ 15 points), one of the core features of NLD. In the present study we examined neuropsychological and social adaptive profiles with "non-verbal learning problems" associated with NLD in a group of individuals with AS followed from childhood into early adult life. The group was divided into three subgroups: (i) persistent NLD (P-NLD), i.e. NLD (VIQ > PIQ) both in childhood and early adulthood occasions, (ii) childhood NLD (CO-NLD), i.e. NLD (VIQ > PIQ) only at original diagnosis, or (iii) No NLD (VIQ > PIQ) ever (NO-NLD). All three subgroups were followed prospectively from childhood into adolescence and young adult life. One in four to one in five of the whole group of males with AS had P-NLD. The P-NLD subgroup had poorer neuropsychological outcome in early adult life than did those with CO-NLD and those with NO-NLD. There were no unequivocal markers in early childhood that predicted subgroup status in early adult life, but early motor delay and a history of early speech-language problems tended to be associated with P-NLD. © 2013 Elsevier Ireland Ltd. All rights reserved.

Lazy orbits: An optimization problem on the sphere

NASA Astrophysics Data System (ADS)

Vincze, Csaba

2018-01-01

Non-transitive subgroups of the orthogonal group play an important role in the non-Euclidean geometry. If G is a closed subgroup in the orthogonal group such that the orbit of a single Euclidean unit vector does not cover the (Euclidean) unit sphere centered at the origin then there always exists a non-Euclidean Minkowski functional such that the elements of G preserve the Minkowskian length of vectors. In other words the Minkowski geometry is an alternative of the Euclidean geometry for the subgroup G. It is rich of isometries if G is "close enough" to the orthogonal group or at least to one of its transitive subgroups. The measure of non-transitivity is related to the Hausdorff distances of the orbits under the elements of G to the Euclidean sphere. Its maximum/minimum belongs to the so-called lazy/busy orbits, i.e. they are the solutions of an optimization problem on the Euclidean sphere. The extremal distances allow us to characterize the reducible/irreducible subgroups. We also formulate an upper and a lower bound for the ratio of the extremal distances. As another application of the analytic tools we introduce the rank of a closed non-transitive group G. We shall see that if G is of maximal rank then it is finite or reducible. Since the reducible and the finite subgroups form two natural prototypes of non-transitive subgroups, the rank seems to be a fundamental notion in their characterization. Closed, non-transitive groups of rank n - 1 will be also characterized. Using the general results we classify all their possible types in lower dimensional cases n = 2 , 3 and 4. Finally we present some applications of the results to the holonomy group of a metric linear connection on a connected Riemannian manifold.

Hidden Worries

ERIC Educational Resources Information Center

Reclaiming Children and Youth, 2013

2013-01-01

Sometimes children are stressed about seemingly small events that escalate into problem behavior. In this article, an insightful teacher discusses restoration of emotional balance by mobilizing positive support from both school and family using A Response Ability Pathways (RAP) intervention. The RAP techniques and how they can be used are…

The Hidden Cost of Saying No!

ERIC Educational Resources Information Center

Dyson, Freeman J.

1975-01-01

Four problems of the regulation of technological development are reviewed: Djerassi's study of the regulation of chemical birth control agents; the downfall of the American supersonic airliner; climate modification; and genetic engineering. The author examines technology and the nature of bureaucratic institutions with respect to the political…

The importance of situation-specific encodings: analysis of a simple connectionist model of letter transposition effects

NASA Astrophysics Data System (ADS)

Fang, Shin-Yi; Smith, Garrett; Tabor, Whitney

2018-04-01

This paper analyses a three-layer connectionist network that solves a translation-invariance problem, offering a novel explanation for transposed letter effects in word reading. Analysis of the hidden unit encodings provides insight into two central issues in cognitive science: (1) What is the novelty of claims of "modality-specific" encodings? and (2) How can a learning system establish a complex internal structure needed to solve a problem? Although these topics (embodied cognition and learnability) are often treated separately, we find a close relationship between them: modality-specific features help the network discover an abstract encoding by causing it to break the initial symmetries of the hidden units in an effective way. While this neural model is extremely simple compared to the human brain, our results suggest that neural networks need not be black boxes and that carefully examining their encoding behaviours may reveal how they differ from classical ideas about the mind-world relationship.

Identification of aberrantly expressed circRNAs in subgroup J avian leucosis virus induced tumor livers by RNA sequencing

USDA-ARS?s Scientific Manuscript database

ALV-J (subgroup J avian leucosis virus) is a kind of oncogenic exogenous retrovirus and diseases associated with ALV-J have caused severe reproduction problems in the poultry industry worldwide. However, the pathogenesis of ALV-J-induced tumor formation is still unclear. In recent years, circRNAs ar...

Innovative Practice in Teacher and Trainer Training in Vocational Education and Training. Advisory Forum Subgroup D Report.

ERIC Educational Resources Information Center

Oldroyd, David

Members of a subgroup of the European Training Foundation's Advisory Forum were surveyed regarding their perceptions of problems and priorities relating to initial and inservice vocational teacher and trainer training and innovation in the European Union (EU). Advisory Forum members from 10 EU countries completed the questionnaire. Priorities…

Hidden Markov random field model and Broyden-Fletcher-Goldfarb-Shanno algorithm for brain image segmentation

NASA Astrophysics Data System (ADS)

Guerrout, EL-Hachemi; Ait-Aoudia, Samy; Michelucci, Dominique; Mahiou, Ramdane

2018-05-01

Many routine medical examinations produce images of patients suffering from various pathologies. With the huge number of medical images, the manual analysis and interpretation became a tedious task. Thus, automatic image segmentation became essential for diagnosis assistance. Segmentation consists in dividing the image into homogeneous and significant regions. We focus on hidden Markov random fields referred to as HMRF to model the problem of segmentation. This modelisation leads to a classical function minimisation problem. Broyden-Fletcher-Goldfarb-Shanno algorithm referred to as BFGS is one of the most powerful methods to solve unconstrained optimisation problem. In this paper, we investigate the combination of HMRF and BFGS algorithm to perform the segmentation operation. The proposed method shows very good segmentation results comparing with well-known approaches. The tests are conducted on brain magnetic resonance image databases (BrainWeb and IBSR) largely used to objectively confront the results obtained. The well-known Dice coefficient (DC) was used as similarity metric. The experimental results show that, in many cases, our proposed method approaches the perfect segmentation with a Dice Coefficient above .9. Moreover, it generally outperforms other methods in the tests conducted.

Interpersonal differentiation within depression diagnosis: relating interpersonal subgroups to symptom load and the quality of the early therapeutic alliance.

PubMed

Grosse Holtforth, Martin; Altenstein, David; Krieger, Tobias; Flückiger, Christoph; Wright, Aidan G C; Caspar, Franz

2014-01-01

We examined interpersonal problems in psychotherapy outpatients with a principal diagnosis of a depressive disorder in routine care (n=361). These patients were compared to a normative non-clinical sample and to outpatients with other principal diagnoses (n=959). Furthermore, these patients were statistically assigned to interpersonally defined subgroups that were compared regarding symptoms and the quality of the early alliance. The sample of depressive patients reported higher levels of interpersonal problems than the normative sample and the sample of outpatients without a principal diagnosis of depression. Latent Class Analysis identified eight distinct interpersonal subgroups, which differed regarding self-reported symptom load and the quality of the early alliance. However, therapists' alliance ratings did not differentiate between the groups. This interpersonal differentiation within the group of patients with a principal diagnosis of depression may add to a personalized psychotherapy based on interpersonal profiles.

Elder Abuse: The Hidden Problem. A Briefing by the Select Committee on Aging, House of Representatives, Ninety-Sixth Congress, First Session (Boston, Massachusetts, June 23, 1979).

ERIC Educational Resources Information Center

Congress of the U.S., Washington, DC. House Select Committee on Aging.

This briefing by the Congressional Select Committee on Aging was designed to gather information on the physical and psychological abuse of the elderly. A number of witness reports are included, testifying to the seriousness and extent of the problem of elder abuse. It is pointed out that many victims refuse to admit abuse; public discussions of…

Collecting behavioural data using the world wide web: considerations for researchers

PubMed Central

Rhodes, S; Bowie, D; Hergenrather, K

2003-01-01

Objective: To identify and describe advantages, challenges, and ethical considerations of web based behavioural data collection. Methods: This discussion is based on the authors' experiences in survey development and study design, respondent recruitment, and internet research, and on the experiences of others as found in the literature. Results: The advantages of using the world wide web to collect behavioural data include rapid access to numerous potential respondents and previously hidden populations, respondent openness and full participation, opportunities for student research, and reduced research costs. Challenges identified include issues related to sampling and sample representativeness, competition for the attention of respondents, and potential limitations resulting from the much cited "digital divide", literacy, and disability. Ethical considerations include anonymity and privacy, providing and substantiating informed consent, and potential risks of malfeasance. Conclusions: Computer mediated communications, including electronic mail, the world wide web, and interactive programs will play an ever increasing part in the future of behavioural science research. Justifiable concerns regarding the use of the world wide web in research exist, but as access to, and use of, the internet becomes more widely and representatively distributed globally, the world wide web will become more applicable. In fact, the world wide web may be the only research tool able to reach some previously hidden population subgroups. Furthermore, many of the criticisms of online data collection are common to other survey research methodologies. PMID:12490652

Collecting behavioural data using the world wide web: considerations for researchers.

PubMed

Rhodes, S D; Bowie, D A; Hergenrather, K C

2003-01-01

To identify and describe advantages, challenges, and ethical considerations of web based behavioural data collection. This discussion is based on the authors' experiences in survey development and study design, respondent recruitment, and internet research, and on the experiences of others as found in the literature. The advantages of using the world wide web to collect behavioural data include rapid access to numerous potential respondents and previously hidden populations, respondent openness and full participation, opportunities for student research, and reduced research costs. Challenges identified include issues related to sampling and sample representativeness, competition for the attention of respondents, and potential limitations resulting from the much cited "digital divide", literacy, and disability. Ethical considerations include anonymity and privacy, providing and substantiating informed consent, and potential risks of malfeasance. Computer mediated communications, including electronic mail, the world wide web, and interactive programs will play an ever increasing part in the future of behavioural science research. Justifiable concerns regarding the use of the world wide web in research exist, but as access to, and use of, the internet becomes more widely and representatively distributed globally, the world wide web will become more applicable. In fact, the world wide web may be the only research tool able to reach some previously hidden population subgroups. Furthermore, many of the criticisms of online data collection are common to other survey research methodologies.

Hidden Homicide Increases in the USA, 1999–2005

PubMed Central

Hu, Guoqing; Webster, Daniel

2008-01-01

Prior to 1999, dramatic fluctuations in homicide rates were driven by changes in the rates of firearm homicide among men aged 15–24. Since 2000, the overall homicide rate has appeared stable, masking any changes in population subgroups. We analyzed recent trends in homicide rates by weapon, age, race, gender, state, and urbanization to determine whether the risk of victimization increased substantially during 1999–2005 for demographic subgroups. The analysis of WISQARS™ data and Wonder data from Centers for Disease Control and Prevention revealed no trend in the homicide rate nationally between 1999 and 2005; this obscured large increases in firearm homicide rates among black men aged 25–44 and among white men aged 25–34. Between 1999 and 2005, for ages 25–44 combined, the increase for black men was 31% compared with 12% for white men. Significant increases among men aged 25–44 occurred in Alabama, California, Michigan, Minnesota, Nebraska, Nevada, New Jersey, Ohio, Pennsylvania, Texas, and Washington. The firearm homicide rate increased the most in large central metropolitan areas (+32%) and large fringe metropolitan areas (+30%) for men aged 25–44. We conclude that the recent, unrecognized increases in firearm homicide among men aged 25–44, especially black men, in large metropolitan areas merit the attention of policymakers. PMID:18509760

Getting Data Right - and Righteous to Improve Hispanic or Latino Health.

PubMed

Rodríguez-Lainz, Alfonso; McDonald, Mariana; Penman-Aguilar, Ana; Barrett, Drue H

2016-01-01

Hispanics or Latinos constitute the largest racial/ethnic minority in the United States. They are also a very diverse population. Latino/Hispanic's health varies significantly for subgroups defined by national origin, race, primary language, and migration-related factors (place of birth, immigration status, years of residence in the United States). Most Hispanics speak Spanish at home, and one-third have limited English proficiency (LEP). There is growing awareness on the importance for population health monitoring programs to collect those data elements (Hispanic subgroup, primary language, and migration-related factors) that better capture Hispanics' diversity, and to provide language assistance (translation of data collection forms, interpreters) to ensure meaningful inclusion of all Latinos/Hispanics in national health monitoring. There are strong ethical and scientific reasons for such expansion of data collection by public health entities. First, expand data elements can help identify otherwise hidden Hispanic subpopulations' health disparities. This may promote a more just and equitable distribution of health resources to underserved populations. Second, language access is needed to ensure fair and legal treatment of LEP individuals in federally supported data collection activities. Finally, these strategies are likely to improve the quality and representativeness of data needed to monitor and address the health of all Latino/Hispanic populations in the United States.

Getting Data Right — and Righteous to Improve Hispanic or Latino Health

PubMed Central

Rodríguez-Lainz, Alfonso; McDonald, Mariana; Penman-Aguilar, Ana; Barrett, Drue H.

2017-01-01

Hispanics or Latinos constitute the largest racial/ethnic minority in the United States. They are also a very diverse population. Latino/Hispanic’s health varies significantly for subgroups defined by national origin, race, primary language, and migration-related factors (place of birth, immigration status, years of residence in the United States). Most Hispanics speak Spanish at home, and one-third have limited English proficiency (LEP). There is growing awareness on the importance for population health monitoring programs to collect those data elements (Hispanic subgroup, primary language, and migration-related factors) that better capture Hispanics’ diversity, and to provide language assistance (translation of data collection forms, interpreters) to ensure meaningful inclusion of all Latinos/Hispanics in national health monitoring. There are strong ethical and scientific reasons for such expansion of data collection by public health entities. First, expand data elements can help identify otherwise hidden Hispanic subpopulations’ health disparities. This may promote a more just and equitable distribution of health resources to underserved populations. Second, language access is needed to ensure fair and legal treatment of LEP individuals in federally supported data collection activities. Finally, these strategies are likely to improve the quality and representativeness of data needed to monitor and address the health of all Latino/Hispanic populations in the United States. PMID:29416934

Curricula Equity in Required Ninth-Grade Physical Education.

ERIC Educational Resources Information Center

Napper-Owen, Gloria E.; Kovar, Susan K.; Ermler, Kathy L.; Mehrhof, Joella H.

1999-01-01

Surveyed high school physical educators regarding required physical education programs, examining hidden curriculum about gender equity and culture. Team sports dominated the instructional units. Teachers had problems involving all students in coeducational activities. Female teachers were more apt to teach outside their socially accepted area of…

Allergies: The Hidden Hazard.

ERIC Educational Resources Information Center

Rapp, Doris J.

1990-01-01

Children can suffer from allergies that can markedly affect their behavior and school performance. Once an allergy is suspected, teachers and principals can consider allergens inside the school, outside the school, and related to problem foods or chemicals. A sidebar lists some allergy clues to watch for. Includes nine references. (MLH)

The Camp Caretaker: A Hidden Treasure.

ERIC Educational Resources Information Center

Ezersky, Eugene M.

1996-01-01

At a round-table discussion, five camp caretakers identified common camp maintenance problems. Snow loads, wooden floors, storage of lake equipment, removal of grass cuttings and leaves, local suppliers, vandalism and trespassing, swimming pools, assigning work, use of outside contractors, decisions to replace or repair, job satisfaction, and…

Computer Intelligence: Unlimited and Untapped.

ERIC Educational Resources Information Center

Staples, Betsy

1983-01-01

Herbert Simon (Nobel prize-winning economist/professor) expresses his views on human and artificial intelligence, problem solving, inventing concepts, and the future. Includes comments on expert systems, state of the art in artificial intelligence, robotics, and "Bacon," a computer program that finds scientific laws hidden in raw data.…

A meta-cognitive learning algorithm for a Fully Complex-valued Relaxation Network.

PubMed

Savitha, R; Suresh, S; Sundararajan, N

2012-08-01

This paper presents a meta-cognitive learning algorithm for a single hidden layer complex-valued neural network called "Meta-cognitive Fully Complex-valued Relaxation Network (McFCRN)". McFCRN has two components: a cognitive component and a meta-cognitive component. A Fully Complex-valued Relaxation Network (FCRN) with a fully complex-valued Gaussian like activation function (sech) in the hidden layer and an exponential activation function in the output layer forms the cognitive component. The meta-cognitive component contains a self-regulatory learning mechanism which controls the learning ability of FCRN by deciding what-to-learn, when-to-learn and how-to-learn from a sequence of training data. The input parameters of cognitive components are chosen randomly and the output parameters are estimated by minimizing a logarithmic error function. The problem of explicit minimization of magnitude and phase errors in the logarithmic error function is converted to system of linear equations and output parameters of FCRN are computed analytically. McFCRN starts with zero hidden neuron and builds the number of neurons required to approximate the target function. The meta-cognitive component selects the best learning strategy for FCRN to acquire the knowledge from training data and also adapts the learning strategies to implement best human learning components. Performance studies on a function approximation and real-valued classification problems show that proposed McFCRN performs better than the existing results reported in the literature. Copyright © 2012 Elsevier Ltd. All rights reserved.

Effective Data-Driven Calibration for a Galvanometric Laser Scanning System Using Binocular Stereo Vision.

PubMed

Tu, Junchao; Zhang, Liyan

2018-01-12

A new solution to the problem of galvanometric laser scanning (GLS) system calibration is presented. Under the machine learning framework, we build a single-hidden layer feedforward neural network (SLFN）to represent the GLS system, which takes the digital control signal at the drives of the GLS system as input and the space vector of the corresponding outgoing laser beam as output. The training data set is obtained with the aid of a moving mechanism and a binocular stereo system. The parameters of the SLFN are efficiently solved in a closed form by using extreme learning machine (ELM). By quantitatively analyzing the regression precision with respective to the number of hidden neurons in the SLFN, we demonstrate that the proper number of hidden neurons can be safely chosen from a broad interval to guarantee good generalization performance. Compared to the traditional model-driven calibration, the proposed calibration method does not need a complex modeling process and is more accurate and stable. As the output of the network is the space vectors of the outgoing laser beams, it costs much less training time and can provide a uniform solution to both laser projection and 3D-reconstruction, in contrast with the existing data-driven calibration method which only works for the laser triangulation problem. Calibration experiment, projection experiment and 3D reconstruction experiment are respectively conducted to test the proposed method, and good results are obtained.

Alexithymia predicts loss chasing for people at risk for problem gambling.

PubMed

Bibby, Peter A; Ross, Katherine E

2017-12-01

Background and aims The aim of this research was to investigate the relationship between alexithymia and loss-chasing behavior in people at risk and not at risk for problem gambling. Methods An opportunity sample of 58 (50 males and 8 females) participants completed the Problem Gambling Severity Index and the Toronto Alexithymia Scale (TAS-20). They then completed the Cambridge Gambling Task from which a measure of loss-chasing behavior was derived. Results Alexithymia and problem gambling risk were significantly positively correlated. Subgroups of non-alexithymic and at or near caseness for alexithymia by low risk and at risk for problem gambling were identified. The results show a clear difference for loss-chasing behavior for the two alexithymia conditions, but there was no evidence that low and at-risk problem gamblers were more likely to loss chase. The emotion-processing components of the TAS-20 were shown to correlate with loss chasing. Discussion and conclusion These findings suggest that loss-chasing behavior may be particularly prevalent in a subgroup of problem gamblers those who are high in alexithymia.

Selecting a Learning Management System (LMS) in Developing Countries: Instructors' Evaluation

ERIC Educational Resources Information Center

Cavus, Nadire

2013-01-01

Learning management systems (LMSs) contain hidden costs, unclear user environments, bulky developer and administration manuals, and limitations with regard to interoperability, integration, localization, and bandwidth requirements. Careful evaluation is required in selecting the most appropriate LMS for use, and this is a general problem in…

Aging and Alcohol Abuse: Increasing Counselor Awareness

ERIC Educational Resources Information Center

Williams, June M.; Ballard, Mary B.; Alessi, Hunter

2005-01-01

Alcohol abuse in older adulthood is a rapidly growing but often hidden problem. The authors provide an overview of the issues related to older adult alcohol abuse through a discussion of physiological, psychological, and social risk factors; an examination of appropriate assessment procedures; and an overview of factors related to treatment.

Sniffing out the Secret Poison: Selection Bias in Educational Research

ERIC Educational Resources Information Center

Showalter, Daniel A.; Mullet, Luke B.

2017-01-01

Selection bias is a persistent, and often hidden, problem in educational research. It is the primary obstacle standing in between increasingly available large education datasets and the ability to make valid causal inferences to inform policymaking, research, and practice (Stuart, 2010). This article provides an accessible discussion on the…

Hidden in the Middle: Culture, Value and Reward in Bioinformatics

ERIC Educational Resources Information Center

Lewis, Jamie; Bartlett, Andrew; Atkinson, Paul

2016-01-01

Bioinformatics--the so-called shotgun marriage between biology and computer science--is an interdiscipline. Despite interdisciplinarity being seen as a virtue, for having the capacity to solve complex problems and foster innovation, it has the potential to place projects and people in anomalous categories. For example, valorised…

Administrative Law: The Hidden Comparative Law Course.

ERIC Educational Resources Information Center

Strauss, Peter L.

1996-01-01

Argues that the main contribution of the Administrative Law course to law students is that it presents problems which contrast with those of the standard court-centered curriculum and can illuminate other areas of law, repeatedly confronting students with doctrinal differences. Offers several examples from civil procedure, constitutional law, and…

Influence of enzymatic hydrolysis on the allergenic reactivity of processed cashew and pistachio

USDA-ARS?s Scientific Manuscript database

Tree nuts constitute one of the main cause of fatal anaphylactic reactions due to food allergy upon direct ingestion and as ingredients (hidden allergens), and cashew and pistachio allergies are considered a serious health problem. Several previous studies have shown that thermal processing may modi...

Hispanics in the Criminal Justice System--the "Nonexistent" Problem.

ERIC Educational Resources Information Center

Mandel, Jerry

1979-01-01

Though hidden from view by being considered "non-existent", the meager evidence indicates that Hispanics have an unusually high arrest and incarceration rate. Hispanic background is rarely asked on the six major sources of criminal justice statistics--statistics of arrests, courts, prisoners, juvenile delinquency, crime victimization, and public…

Evaluating Presentation Skills of Volunteer Trainers.

ERIC Educational Resources Information Center

Mohan, Donna K.

A systematic method for evaluating the presentation skills of volunteer trainers would enable the discovery of hidden problems. It would also increase individual trainer skills and satisfaction and improve the overall effectiveness of the training program. A first step is to determine the general presentation skills a successful volunteer trainer…

Managing Food Allergies in School.

ERIC Educational Resources Information Center

Munoz-Furlong, Anne

1997-01-01

The number of students with food allergies is increasing, with peanuts the leading culprit. Peer pressure and allergens hidden in baked goods can pose problems for school staff. Children with documented life-threatening allergies are covered by the Americans with Disabilities Act. Principals should reassure parents and use Section 504 guidelines…

Off the Wall?

ERIC Educational Resources Information Center

Rittner-Heir, Robbin

2003-01-01

Vandalism is the main problem in maintaining school washrooms. Ways to help schools meet this challenge include designing washrooms with hidden moving parts to cut down on vandalism and making toilet partitions of solid polyethylene plastic which is virtually indestructible, hard to deface, and easy to clean. The article suggests it is worth…

Innovations in the Teaching of Behavioral Sciences in the Preclinical Curriculum

ERIC Educational Resources Information Center

Mack, Kevin

2005-01-01

Objective: In problem-based learning curricula, cases are usually clustered into identified themes or organ systems. While this method of aggregating cases presents clear advantages in terms of resource alignment and student focus, an alternative "hidden cluster" approach provides rich opportunities for content integration. Method: The author…

Sexuality and the Curriculum: The Politics and Practices of Sexuality Education. Critical Issues in the Curriculum.

ERIC Educational Resources Information Center

Sears, James T., Ed.

This book of essays explores the explicit and hidden curriculum of sexuality from kindergarten through college. The 15 interrelated essays challenge conventional assumptions regarding sexuality and the curriculum by applying non-traditional perspectives to traditionally unresolved problems while proposing specific curricular strategies and…

Hidden Disruptions: Technology and Technological Literacy as Influences on Professional Writing Student Teams

ERIC Educational Resources Information Center

McGrady, Lisa

2010-01-01

This article reports on a study designed to explore whether and in what ways individual students' technological literacies might impact collaborative teams. For the collaborative team discussed in this article, technological literacy--specifically, limited repertoires for solving technical problems, clashes between document management strategies,…

Latent class-derived subgroups of depressive symptoms in a community sample of older adults: the Cache County Study.

PubMed

Lee, Chien-Ti; Leoutsakos, Jeannie-Marie; Lyketsos, Constantine G; Steffens, David C; Breitner, John C S; Norton, Maria C

2012-10-01

We sought to identify possible subgroups of elders that varied in depressive symptomatology and to examine symptom patterns and health status differences between subgroups. The Cache County memory study is a population-based epidemiological study of dementia with 5092 participants. Depressive symptoms were measured with a modified version of the diagnostic interview schedule-depression. There were 400 nondemented participants who endorsed currently (i.e., in the past 2 weeks) experiencing at least one of the three "gateway" depressive symptoms and then completed a full depression interview. Responses to all nine current depressive symptoms were modeled using the latent class analysis. Three depression subgroups were identified: a significantly depressed subgroup (62%), with the remainder split evenly between a subgroup with low probability of all symptoms (21%), and a subgroup with primarily psychomotor changes, sleep symptoms, and fatigue (17%). Latent class analysis derived subgroups of depressive symptoms and Diagnostic and statistical manual of mental disorders, fourth edition depression diagnostic group were nonredundant. Age, gender, education, marital status, early or late onset, number of episodes, current episode duration, and functional status were not significant predictors of depression subgroup. The first subgroup was more likely to be recently bereaved and had less physical health problems, whereas the third subgroup were less likely to be using antidepressants compared with the second subgroup. There are distinct subgroups of depressed elders, which are not redundant with the Diagnostic and statistical manual of mental disorders, fourth edition classification scheme, offering an alternative diagnostic approach to clinicians and researchers. Future work will examine whether these depressive symptom profiles are predictive of incident dementia and earlier mortality. Copyright © 2011 John Wiley & Sons, Ltd.

A fast and accurate online sequential learning algorithm for feedforward networks.

PubMed

Liang, Nan-Ying; Huang, Guang-Bin; Saratchandran, P; Sundararajan, N

2006-11-01

In this paper, we develop an online sequential learning algorithm for single hidden layer feedforward networks (SLFNs) with additive or radial basis function (RBF) hidden nodes in a unified framework. The algorithm is referred to as online sequential extreme learning machine (OS-ELM) and can learn data one-by-one or chunk-by-chunk (a block of data) with fixed or varying chunk size. The activation functions for additive nodes in OS-ELM can be any bounded nonconstant piecewise continuous functions and the activation functions for RBF nodes can be any integrable piecewise continuous functions. In OS-ELM, the parameters of hidden nodes (the input weights and biases of additive nodes or the centers and impact factors of RBF nodes) are randomly selected and the output weights are analytically determined based on the sequentially arriving data. The algorithm uses the ideas of ELM of Huang et al. developed for batch learning which has been shown to be extremely fast with generalization performance better than other batch training methods. Apart from selecting the number of hidden nodes, no other control parameters have to be manually chosen. Detailed performance comparison of OS-ELM is done with other popular sequential learning algorithms on benchmark problems drawn from the regression, classification and time series prediction areas. The results show that the OS-ELM is faster than the other sequential algorithms and produces better generalization performance.

Probability Sampling Method for a Hidden Population Using Respondent-Driven Sampling: Simulation for Cancer Survivors.

PubMed

Jung, Minsoo

2015-01-01

When there is no sampling frame within a certain group or the group is concerned that making its population public would bring social stigma, we say the population is hidden. It is difficult to approach this kind of population survey-methodologically because the response rate is low and its members are not quite honest with their responses when probability sampling is used. The only alternative known to address the problems caused by previous methods such as snowball sampling is respondent-driven sampling (RDS), which was developed by Heckathorn and his colleagues. RDS is based on a Markov chain, and uses the social network information of the respondent. This characteristic allows for probability sampling when we survey a hidden population. We verified through computer simulation whether RDS can be used on a hidden population of cancer survivors. According to the simulation results of this thesis, the chain-referral sampling of RDS tends to minimize as the sample gets bigger, and it becomes stabilized as the wave progresses. Therefore, it shows that the final sample information can be completely independent from the initial seeds if a certain level of sample size is secured even if the initial seeds were selected through convenient sampling. Thus, RDS can be considered as an alternative which can improve upon both key informant sampling and ethnographic surveys, and it needs to be utilized for various cases domestically as well.

Berry phases for Landau Hamiltonians on deformed tori

NASA Astrophysics Data System (ADS)

Lévay, Péter

1995-06-01

Parametrized families of Landau Hamiltonians are introduced, where the parameter space is the Teichmüller space (topologically the complex upper half plane) corresponding to deformations of tori. The underlying SO(2,1) symmetry of the families enables an explicit calculation of the Berry phases picked up by the eigenstates when the torus is slowly deformed. It is also shown that apart from these phases that are local in origin, there are global non-Abelian ones too, related to the hidden discrete symmetry group Γϑ (the theta group, which is a subgroup of the modular group) of the families. The induced Riemannian structure on the parameter space is the usual Poincare metric on the upper half plane of constant negative curvature. Due to the discrete symmetry Γϑ the geodesic motion restricted to the fundamental domain of this group is chaotic.

Health-related needs of people with multiple chronic diseases: differences and underlying factors.

PubMed

Hopman, Petra; Schellevis, François G; Rijken, Mieke

2016-03-01

To examine the health-related needs of people with multiple chronic diseases in the Netherlands compared to people with one chronic disease, and to identify different subgroups of multimorbid patients based on differences in their health problems. Participants were 1092 people with one or more chronic diseases of a nationwide prospective panel study on the consequences of chronic illness in the Netherlands. They completed the EQ-6D, a multi-dimensional questionnaire on health problems (October 2013). Chi-square tests and analyses of variance were performed to test for differences between multimorbid patients and patients with one chronic disease. To identify subgroups of multimorbid patients, cluster analysis was performed and differences in EQ-6D scores between clusters were tested with Chi-square tests. Multimorbid patients (51 % of the total sample) experience more problems in most health domains than patients with one chronic disease. Almost half (44 %) of the multimorbid people had many health problems in different domains. These people were more often female, had a smaller household size, had a lower health literacy, and suffered from more chronic diseases. Remarkably, a small subgroup of multimorbid patients (4 %, mostly elderly males) is characterized by all having cognitive problems. Based on the problems they experience, we conclude that patients with multimorbidity have relatively many and diverse health-related needs. Extensive health-related needs among people with multimorbidity may relate not only to the number of chronic diseases they suffer from, but also to their patient characteristics. This should be taken into account, when identifying target groups for comprehensive support programmes.

Learning to classify in large committee machines

NASA Astrophysics Data System (ADS)

O'kane, Dominic; Winther, Ole

1994-10-01

The ability of a two-layer neural network to learn a specific non-linearly-separable classification task, the proximity problem, is investigated using a statistical mechanics approach. Both the tree and fully connected architectures are investigated in the limit where the number K of hidden units is large, but still much smaller than the number N of inputs. Both have continuous weights. Within the replica symmetric ansatz, we find that for zero temperature training, the tree architecture exhibits a strong overtraining effect. For nonzero temperature the asymptotic error is lowered, but it is still higher than the corresponding value for the simple perceptron. The fully connected architecture is considered for two regimes. First, for a finite number of examples we find a symmetry among the hidden units as each performs equally well. The asymptotic generalization error is finite, and minimal for T-->∞ where it goes to the same value as for the simple perceptron. For a large number of examples we find a continuous transition to a phase with broken hidden-unit symmetry, which has an asymptotic generalization error equal to zero.

Reinforcement learning state estimator.

PubMed

Morimoto, Jun; Doya, Kenji

2007-03-01

In this study, we propose a novel use of reinforcement learning for estimating hidden variables and parameters of nonlinear dynamical systems. A critical issue in hidden-state estimation is that we cannot directly observe estimation errors. However, by defining errors of observable variables as a delayed penalty, we can apply a reinforcement learning frame-work to state estimation problems. Specifically, we derive a method to construct a nonlinear state estimator by finding an appropriate feedback input gain using the policy gradient method. We tested the proposed method on single pendulum dynamics and show that the joint angle variable could be successfully estimated by observing only the angular velocity, and vice versa. In addition, we show that we could acquire a state estimator for the pendulum swing-up task in which a swing-up controller is also acquired by reinforcement learning simultaneously. Furthermore, we demonstrate that it is possible to estimate the dynamics of the pendulum itself while the hidden variables are estimated in the pendulum swing-up task. Application of the proposed method to a two-linked biped model is also presented.

Analysis of single ion channel data incorporating time-interval omission and sampling

PubMed Central

The, Yu-Kai; Timmer, Jens

2005-01-01

Hidden Markov models are widely used to describe single channel currents from patch-clamp experiments. The inevitable anti-aliasing filter limits the time resolution of the measurements and therefore the standard hidden Markov model is not adequate anymore. The notion of time-interval omission has been introduced where brief events are not detected. The developed, exact solutions to this problem do not take into account that the measured intervals are limited by the sampling time. In this case the dead-time that specifies the minimal detectable interval length is not defined unambiguously. We show that a wrong choice of the dead-time leads to considerably biased estimates and present the appropriate equations to describe sampled data. PMID:16849220

A simple method to derive bounds on the size and to train multilayer neural networks

NASA Technical Reports Server (NTRS)

Sartori, Michael A.; Antsaklis, Panos J.

1991-01-01

A new derivation is presented for the bounds on the size of a multilayer neural network to exactly implement an arbitrary training set; namely, the training set can be implemented with zero error with two layers and with the number of the hidden-layer neurons equal to no.1 is greater than p - 1. The derivation does not require the separation of the input space by particular hyperplanes, as in previous derivations. The weights for the hidden layer can be chosen almost arbitrarily, and the weights for the output layer can be found by solving no.1 + 1 linear equations. The method presented exactly solves (M), the multilayer neural network training problem, for any arbitrary training set.

Subgroup effects of occupational therapy-based intervention for people with advanced cancer.

PubMed

Sampedro Pilegaard, Marc; Oestergaard, Lisa Gregersen; la Cour, Karen; Thit Johnsen, Anna; Brandt, Åse

2018-03-23

Many people with advanced cancer have decreased ability to perform activities of daily living (ADL). We recently performed a randomized, controlled trial (RCT) assessing the efficacy of an occupational therapy-based program, the 'Cancer Home-Life Intervention' in people with advanced cancer (N = 242) and found no overall effects on ADL ability. However, heterogeneity of treatment effect may disguise subgroup differences. To investigate whether subgroups of people with advanced cancer gain positive effects from the 'Cancer Home-Life Intervention' on ADL ability. An exploratory subgroup analysis including 191 participants from a RCT. The outcome was ADL motor ability measured by the Assessment of Motor and Process Skills (AMPS). Subgroups were defined by age, gender, years of education, type of primary tumor, functional level, and activity problems. The 'Cancer Home-Life Intervention' had no statistically significant effect in the six subgroups. Modifying effects of age (0.30 [95% CI: -0.05 to 0.64]) and gender (0.23 [95% CI: -0.11 to 0.57]) were not found. There were no subgroup effects of the 'Cancer Home-Life Intervention'on ADL motor ability. Some indications suggest greater effects for those aged below 69 years; however, this result should be interpreted with caution.

Brief Intervention for Truant Youth Sexual Risk Behavior and Alcohol Use: A Parallel Process Growth Model Analysis

PubMed Central

Dembo, Richard; Briones-Robinson, Rhissa; Ungaro, Rocio; Barrett, Kimberly; Gulledge, Laura; Winters, Ken C.; Belenko, Steven; Karas, Lora M.; Wareham, Jennifer

2011-01-01

Truant youths represent a challenging, yet very promising group of at-risk youth to study. In addition to problems in school, they frequently experience troubled family situations, emotional/ psychological problems, involvement in substance use, and delinquency. Given the problems often experienced by truant youth, it is likely they are engaging in alcohol use and sexual risk behavior at a higher rate, than the general youth population. Identification of these youths’ problems and early placement into effective intervention services would benefit them, their families, and society. The current study presents interim findings from an ongoing, NIDA-funded experimental, Brief Intervention (BI) study involving truant youths and their parent/guardians. Baseline, 3-month, 6-month, and 12-month follow up data were analyzed to determine whether alcohol use and sexual risk behaviors were longitudinally related, examine the effects of the intervention on longitudinal alcohol use and sexual risk behaviors, identify latent subgroups of youths in the data for alcohol use and sexual risk behaviors, and determine whether the intervention influenced these subgroups. Results indicated alcohol use and sexual risk were longitudinally related. Subgroups of youth were also identified based on alcohol use and sexual risk behavior levels and trends. Further, limited treatment effects were observed for alcohol use. Implications of the results for future research and service delivery are considered. PMID:25242878

Naturalness of Electroweak Symmetry Breaking while Waiting for the LHC

NASA Astrophysics Data System (ADS)

Espinosa, J. R.

2007-06-01

After revisiting the hierarchy problem of the Standard Model and its implications for the scale of New Physics, I consider the finetuning problem of electroweak symmetry breaking in several scenarios beyond the Standard Model: SUSY, Little Higgs and "improved naturalness" models. The main conclusions are that: New Physics should appear on the reach of the LHC; some SUSY models can solve the hierarchy problem with acceptable residual tuning; Little Higgs models generically suffer from large tunings, many times hidden; and, finally, that "improved naturalness" models do not generically improve the naturalness of the SM.

Modelling with Difference Equations Supported by GeoGebra: Exploring the Kepler Problem

ERIC Educational Resources Information Center

Kovacs, Zoltan

2010-01-01

The use of difference and differential equations in the modelling is a topic usually studied by advanced students in mathematics. However difference and differential equations appear in the school curriculum in many direct or hidden ways. Difference equations first enter in the curriculum when studying arithmetic sequences. Moreover Newtonian…

Improving School Attendance through Collaboration: A Catalyst for Community Involvement and Change

ERIC Educational Resources Information Center

Childs, Joshua; Grooms, Ain A.

2018-01-01

Chronic absenteeism is often referred to as a problem hidden in plain sight (Chang & Romero, 2008). In recent years, more communities around the United States have been intentional on improving student attendance and limiting the impact of chronic absenteeism. Using qualitative interviews, we sought to understand how one community was…

Curricular Orientations in Elementary School Music: Roles, Pedagogies, and Values.

ERIC Educational Resources Information Center

Bresler, Liora

1996-01-01

Explores the day-to-day music curriculum in three elementary schools. Identifies three orientations toward the role of music education: (1) the functional, based on traditional academic goals and content; (2) the complementary, relegating music to a hidden curriculum; and (3) the expansive, focusing on enhancing perceptual and problem-solving…

Relational Aggression among Boys: Blind Spots and Hidden Dramas

ERIC Educational Resources Information Center

Eriksen, Ingunn Marie; Lyng, Selma Therese

2018-01-01

Although boys too are involved in relational aggression, their experiences are overshadowed by the focus on relational aggression among girls. This paradox mirrors the empirical puzzle that forms the starting point for this article: while teachers saw relational aggression as a 'girl problem', we found a vast undercurrent of relational aggression…

Child Abuse and Neglect in Japan: Coin-Operated-Locker Babies.

ERIC Educational Resources Information Center

Kouno, Akihisa; Johnson, Charles F.

1995-01-01

This paper reviews Japan's child abuse/neglect history, including the incidence of "coin-operated-locker babies," where murdered infants are hidden in railway and airport lockers, and actions taken to reduce this problem. The incidence of child abuse in Japan and the United States is compared, and social influences on the number of…

Is Your School a Dumping Ground?: Hidden Hazards You Can Identify and Eliminate.

ERIC Educational Resources Information Center

Cronin-Jones, Linda L.

1992-01-01

Describes how teachers and students can conduct a schoolwide hazardous waste survey. The activity is an introduction to hazardous waste management and is useful in general physical science, chemistry, and environmental science classes. Two activity worksheets are provided. Explains how schools can clean up hazardous waste problems. (PR)

The Hidden Curriculum of Whiteness: White Teachers, White Territory, and White Community.

ERIC Educational Resources Information Center

Allen, Ricky Lee

This paper suggests that space and spatiality are major features of racial identity and the formation of student resistance. It brings together critical studies of "Whiteness," human territoriality, and theories of resistance in education. The problems between white teachers and students of color can be understood better through a combination of…

Using Graphing to Reveal the Hidden Transformations in Palindrome (and Other Types of) Licence Plates

ERIC Educational Resources Information Center

Nivens, Ryan Andrew

2016-01-01

This article provides a range of activities designed to engage students in using an early form of graphing. While the "Australian Curriculum: Mathematics" (2014) highlights understanding, fluency, problem-solving, and reasoning, the National Research Council (2001) describes five strands of mathematical proficiency, with the additional…

User's Guide for SKETCH

NASA Technical Reports Server (NTRS)

Hedgley, David R., Jr.

2000-01-01

A user's guide for the computer program SKETCH is presented on this disk. SKETCH solves a popular problem in computer graphics-the removal of hidden lines from images of solid objects. Examples and illustrations are included in the guide. Also included is the SKETCH program, so a user can incorporate the information into a particular software system.

Non-Disclosing Students with Disabilities or Learning Challenges: Characteristics and Size of a Hidden Population

ERIC Educational Resources Information Center

Grimes, Susan; Scevak, Jill; Southgate, Erica; Buchanan, Rachel

2017-01-01

Internationally, university students with disabilities (SWD) are recognised as being under-represented in higher education. They face significant problems accessing appropriate accommodations for their disability. Academic outcomes for this group are lower in terms of achievement and graduation rates. The true size of the SWD group at university…

Investigating a Case of Hidden Misinterpretations of an Additive Word Problem: Structural Substitution

ERIC Educational Resources Information Center

Polotskaia, Elena; Savard, Annie; Freiman, Viktor

2016-01-01

According to numerous studies (Barrouillet & Camos 2002; Brousseau 1988; Chevallard 1988; Riley et al. 1984; Schubauer-Leoni & Ntamakiliro, "Revue Des Sciences de L'éducation," 20(1): 87-113, 1994; Vergnaud 1982; Xin, "The Journal of Educational Research," 100(6):347-360, 2007), a combination of many factors, including…

Personality and Occupational Stress in Elite Performers.

ERIC Educational Resources Information Center

Hamilton, Linda H.; Kella, John J.

Performing Arts Psychology has recently emerged as a unique subspecialty comparable to that of Sports Psychology. Attention has been focused on problems common to all performers (e.g., performance anxiety); however, the various stresses within each art form often remain hidden from view. To assess the psychological aspects of different art forms,…

The Relationship between Teachers' Views about Cultural Values and Critical Pedagogy

ERIC Educational Resources Information Center

Yilmaz, Kursad; Altinkurt, Yahya; Ozciftci, Elif

2016-01-01

Problem Statement: Known as basic elements directing individuals' lives, cultural values are hidden cultural elements that influence all evaluations and perceptions. Values, in that sense, are elements individuals are aware of and provide the answer to the "what should I do?" feeling (Schein, 1992). Critical pedagogy is a project based…

Journal of Undergraduate Psychological Research, Vol. 1, No. 1.

ERIC Educational Resources Information Center

Ladd, Sandra L., Ed.; Hughmanick, Michael, Ed.

1974-01-01

Articles resulting from studies conducted by college undergraduates in all areas of experimental psychology are provided, together with abstracts of other papers authored by students in the field of study. The articles are: The Influence of SET on Solving Hidden-Word Problems by Lana I. Boutacoff; Violation of Personal Space in Deviant Adolescents…

Credits and Credibility: Educating Professionals for Cultural Sensitivity.

ERIC Educational Resources Information Center

Morgan, Elizabeth; Weigel, Van

A four-part discussion on cultural sensitivity and good listening skills in development professionals is presented. It is noted that there is much in their educational regimen which militates against developing these habits of mind. It is hypothesized that much of this problem resides in the hidden cultural meanings of professionalism in general…

Processes Underlying Young Children's Spatial Orientation during Movement.

ERIC Educational Resources Information Center

Bremner, J. Gavin; And Others

1994-01-01

Tested children 18 months to 4 years for their ability to relocate a hidden object after self-produced movement around an array of 4 locations. Children encountered no specific difficulty in coordinating dimensions, or they solved the task without recourse to such a system. They also appeared to change strategy when the problem requires more…

Bidirectional extreme learning machine for regression problem and its learning effectiveness.

PubMed

Yang, Yimin; Wang, Yaonan; Yuan, Xiaofang

2012-09-01

It is clear that the learning effectiveness and learning speed of neural networks are in general far slower than required, which has been a major bottleneck for many applications. Recently, a simple and efficient learning method, referred to as extreme learning machine (ELM), was proposed by Huang , which has shown that, compared to some conventional methods, the training time of neural networks can be reduced by a thousand times. However, one of the open problems in ELM research is whether the number of hidden nodes can be further reduced without affecting learning effectiveness. This brief proposes a new learning algorithm, called bidirectional extreme learning machine (B-ELM), in which some hidden nodes are not randomly selected. In theory, this algorithm tends to reduce network output error to 0 at an extremely early learning stage. Furthermore, we find a relationship between the network output error and the network output weights in the proposed B-ELM. Simulation results demonstrate that the proposed method can be tens to hundreds of times faster than other incremental ELM algorithms.

Rule extraction from minimal neural networks for credit card screening.

PubMed

Setiono, Rudy; Baesens, Bart; Mues, Christophe

2011-08-01

While feedforward neural networks have been widely accepted as effective tools for solving classification problems, the issue of finding the best network architecture remains unresolved, particularly so in real-world problem settings. We address this issue in the context of credit card screening, where it is important to not only find a neural network with good predictive performance but also one that facilitates a clear explanation of how it produces its predictions. We show that minimal neural networks with as few as one hidden unit provide good predictive accuracy, while having the added advantage of making it easier to generate concise and comprehensible classification rules for the user. To further reduce model size, a novel approach is suggested in which network connections from the input units to this hidden unit are removed by a very straightaway pruning procedure. In terms of predictive accuracy, both the minimized neural networks and the rule sets generated from them are shown to compare favorably with other neural network based classifiers. The rules generated from the minimized neural networks are concise and thus easier to validate in a real-life setting.

Multilayer neural networks for reduced-rank approximation.

PubMed

Diamantaras, K I; Kung, S Y

1994-01-01

This paper is developed in two parts. First, the authors formulate the solution to the general reduced-rank linear approximation problem relaxing the invertibility assumption of the input autocorrelation matrix used by previous authors. The authors' treatment unifies linear regression, Wiener filtering, full rank approximation, auto-association networks, SVD and principal component analysis (PCA) as special cases. The authors' analysis also shows that two-layer linear neural networks with reduced number of hidden units, trained with the least-squares error criterion, produce weights that correspond to the generalized singular value decomposition of the input-teacher cross-correlation matrix and the input data matrix. As a corollary the linear two-layer backpropagation model with reduced hidden layer extracts an arbitrary linear combination of the generalized singular vector components. Second, the authors investigate artificial neural network models for the solution of the related generalized eigenvalue problem. By introducing and utilizing the extended concept of deflation (originally proposed for the standard eigenvalue problem) the authors are able to find that a sequential version of linear BP can extract the exact generalized eigenvector components. The advantage of this approach is that it's easier to update the model structure by adding one more unit or pruning one or more units when the application requires it. An alternative approach for extracting the exact components is to use a set of lateral connections among the hidden units trained in such a way as to enforce orthogonality among the upper- and lower-layer weights. The authors call this the lateral orthogonalization network (LON) and show via theoretical analysis-and verify via simulation-that the network extracts the desired components. The advantage of the LON-based model is that it can be applied in a parallel fashion so that the components are extracted concurrently. Finally, the authors show the application of their results to the solution of the identification problem of systems whose excitation has a non-invertible autocorrelation matrix. Previous identification methods usually rely on the invertibility assumption of the input autocorrelation, therefore they can not be applied to this case.

Executive Function as a Mediator in the Link between Attention-Deficit/Hyperactivity Disorder and Social Problems

ERIC Educational Resources Information Center

Tseng, Wan-Ling; Gau, Susan Shur-Fen

2013-01-01

Background: Cognitive processes and mechanisms underlying the strong link between attention-deficit/hyperactivity disorder (ADHD) and social problems remain unclear. Limited knowledge also exists regarding a subgroup of youth with ADHD who do not have social problems. This study investigated the extent to which executive function (EF) mediated the…

New evidence of heterogeneity in social anxiety disorder: defining two qualitatively different personality profiles taking into account clinical, environmental and genetic factors.

PubMed

Binelli, C; Muñiz, A; Sanches, S; Ortiz, A; Navines, R; Egmond, E; Udina, M; Batalla, A; López-Sola, C; Crippa, J A; Subirà, S; Martín-Santos, R

2015-01-01

To study qualitatively different subgroups of social anxiety disorder (SAD) based on harm avoidance (HA) and novelty seeking (NS) dimensions. One hundred and forty-two university students with SAD (SCID-DSM-IV) were included in the study. The temperament dimensions HA and NS from the Cloninger's Temperament and Character Inventory were subjected to cluster analysis to identify meaningful subgroups. The identified subgroups were compared for sociodemographics, SAD severity, substance use, history of suicide and self-harm attempts, early life events, and two serotonin transporter gene polymorphisms (5-HTTLPR and STin2.VNTR). Two subgroups of SAD were identified by cluster analysis: a larger (61% of the sample) inhibited subgroup of subjects with "high-HA/low-NS", and a smaller (39%) atypical impulsive subgroup with high-moderate HA and NS. The two groups did not differ in social anxiety severity, but did differ in history of lifetime impulsive-related-problems. History of suicide attempts and self-harm were as twice as frequent in the impulsive subgroup. Significant differences were observed in the pattern of substance misuse. Whereas subjects in the inhibited subgroup showed a greater use of alcohol (P=0.002), subjects in the impulsive subgroup showed a greater use of substances with a high-sensation-seeking profile (P<0.001). The STin2.VNTR genotype frequency showed an inverse distribution between subgroups (P=0.005). Our study provides further evidence for the presence of qualitatively different SAD subgroups and the propensity of a subset of people with SAD to exhibit impulsive, high-risk behaviors. Copyright © 2014 Elsevier Masson SAS. All rights reserved.

A novel tree-based procedure for deciphering the genomic spectrum of clinical disease entities.

PubMed

Mbogning, Cyprien; Perdry, Hervé; Toussile, Wilson; Broët, Philippe

2014-01-01

Dissecting the genomic spectrum of clinical disease entities is a challenging task. Recursive partitioning (or classification trees) methods provide powerful tools for exploring complex interplay among genomic factors, with respect to a main factor, that can reveal hidden genomic patterns. To take confounding variables into account, the partially linear tree-based regression (PLTR) model has been recently published. It combines regression models and tree-based methodology. It is however computationally burdensome and not well suited for situations for which a large number of exploratory variables is expected. We developed a novel procedure that represents an alternative to the original PLTR procedure, and considered different selection criteria. A simulation study with different scenarios has been performed to compare the performances of the proposed procedure to the original PLTR strategy. The proposed procedure with a Bayesian Information Criterion (BIC) achieved good performances to detect the hidden structure as compared to the original procedure. The novel procedure was used for analyzing patterns of copy-number alterations in lung adenocarcinomas, with respect to Kirsten Rat Sarcoma Viral Oncogene Homolog gene (KRAS) mutation status, while controlling for a cohort effect. Results highlight two subgroups of pure or nearly pure wild-type KRAS tumors with particular copy-number alteration patterns. The proposed procedure with a BIC criterion represents a powerful and practical alternative to the original procedure. Our procedure performs well in a general framework and is simple to implement.

Field Extension of Real Values of Physical Observables in Classical Theory can Help Attain Quantum Results

NASA Astrophysics Data System (ADS)

Wang, Hai; Kumar, Asutosh; Cho, Minhyung; Wu, Junde

2018-04-01

Physical quantities are assumed to take real values, which stems from the fact that an usual measuring instrument that measures a physical observable always yields a real number. Here we consider the question of what would happen if physical observables are allowed to assume complex values. In this paper, we show that by allowing observables in the Bell inequality to take complex values, a classical physical theory can actually get the same upper bound of the Bell expression as quantum theory. Also, by extending the real field to the quaternionic field, we can puzzle out the GHZ problem using local hidden variable model. Furthermore, we try to build a new type of hidden-variable theory of a single qubit based on the result.

Interferometric Computation Beyond Quantum Theory

NASA Astrophysics Data System (ADS)

Garner, Andrew J. P.

2018-03-01

There are quantum solutions for computational problems that make use of interference at some stage in the algorithm. These stages can be mapped into the physical setting of a single particle travelling through a many-armed interferometer. There has been recent foundational interest in theories beyond quantum theory. Here, we present a generalized formulation of computation in the context of a many-armed interferometer, and explore how theories can differ from quantum theory and still perform distributed calculations in this set-up. We shall see that quaternionic quantum theory proves a suitable candidate, whereas box-world does not. We also find that a classical hidden variable model first presented by Spekkens (Phys Rev A 75(3): 32100, 2007) can also be used for this type of computation due to the epistemic restriction placed on the hidden variable.

Inference of Functionally-Relevant N-acetyltransferase Residues Based on Statistical Correlations.

PubMed

Neuwald, Andrew F; Altschul, Stephen F

2016-12-01

Over evolutionary time, members of a superfamily of homologous proteins sharing a common structural core diverge into subgroups filling various functional niches. At the sequence level, such divergence appears as correlations that arise from residue patterns distinct to each subgroup. Such a superfamily may be viewed as a population of sequences corresponding to a complex, high-dimensional probability distribution. Here we model this distribution as hierarchical interrelated hidden Markov models (hiHMMs), which describe these sequence correlations implicitly. By characterizing such correlations one may hope to obtain information regarding functionally-relevant properties that have thus far evaded detection. To do so, we infer a hiHMM distribution from sequence data using Bayes' theorem and Markov chain Monte Carlo (MCMC) sampling, which is widely recognized as the most effective approach for characterizing a complex, high dimensional distribution. Other routines then map correlated residue patterns to available structures with a view to hypothesis generation. When applied to N-acetyltransferases, this reveals sequence and structural features indicative of functionally important, yet generally unknown biochemical properties. Even for sets of proteins for which nothing is known beyond unannotated sequences and structures, this can lead to helpful insights. We describe, for example, a putative coenzyme-A-induced-fit substrate binding mechanism mediated by arginine residue switching between salt bridge and π-π stacking interactions. A suite of programs implementing this approach is available (psed.igs.umaryland.edu).

Nonhomogeneous results in place learning among panic disorder patients with agoraphobia.

PubMed

Gorini, Alessandra; Schruers, Koen; Riva, Giuseppe; Griez, Eric

2010-10-30

Patients affected by panic disorder with agoraphobia (PDA) often suffer from visuo-spatial disturbances. In the present study, we tested the place-learning abilities in a sample of 31 PDA patients compared to 31 healthy controls (CTR) using the computer-generated arena (C-G Arena), a desktop-based computer program developed at the University of Arizona (Jacobs et al 1997, for further detail about the program, see http://web.arizona.edu/~arg/data.html). Subjects were asked to search the computer-generated space, over several trials, for the location of a hidden target. Results showed that control subjects rapidly learned to locate the invisible target and consistently returned to it, while PDA patients were divided in two subgroups: some of them (PDA-A) were as good as controls in place learning, while some others (PDA-B) were unable to learn the correct strategies to find the target. Further analyses revealed that PDA-A patients were significantly younger and affected by panic disorder from less time than PDA-B, indicating that age and duration of illness can be critical factors that influence the place-learning abilities. The existence of two different subgroups of PDA patients who differ in their spatial orientation abilities could provide new insight into the mechanisms of panic and open new perspectives in the cognitive-behavioral treatment of this diffuse and disabling disorder. Copyright © 2009 Elsevier Ireland Ltd. All rights reserved.

Functional neuroanatomy of the insular lobe.

PubMed

Stephani, C; Fernandez-Baca Vaca, G; Maciunas, R; Koubeissi, M; Lüders, H O

2011-06-01

The insula is the fifth lobe of the brain and it is the least known. Hidden under the temporal, frontal and parietal opercula, as well as under dense arterial and venous vessels, its accessibility is particularly restricted. Functional data on this region in humans, therefore, are scarce and the existing evidence makes conclusions on its functional and somatotopic organization difficult. 5 patients with intractable epilepsy underwent an invasive presurgical evaluation with implantation of diagnostic invasive-depth electrodes, including insular electrodes that were inserted using a mesiocaudodorsal to laterorostroventral approach. Altogether 113 contacts were found to be in the insula and were stimulated with alternating currents during preoperative monitoring. Different viscerosensitive and somatosensory phenomena were elicited by stimulation of these electrodes. A relatively high density of electrode contacts enabled us to delineate several functionally distinct areas within the insula. We found somatosensory symptoms to be restricted to the posterior insula and a subgroup of warmth or painful sensations in the dorsal posterior insula. Viscerosensory symptoms were elicited by more anterior electrode contacts with a subgroup of gustatory symptoms occurring after stimulation of electrode contacts in the central part of the insula. The anterior insula did not show reproducible responses to stimulation. In line with previous studies, we found evidence for somato- and viscerosensory cortex in the insula. In addition, our results suggest that there is a predominantly posterior and central distribution of these functions in the insular lobe.

Improving the Quality of Alerts and Predicting Intruder's Next Goal with Hidden Colored Petri-Net

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

Yu, Dong; Frincke, Deb A.

2006-06-22

Intrusion detection systems (IDS) often provide poor quality alerts, which are insufficient to support rapid identification of ongoing attacks or predict an intruder’s next likely goal. In this paper, we propose a novel approach to alert post-processing and correlation, the Hidden Colored Petri-Net (HCPN). Different from most other alert correlation methods, our approach treats the alert correlation problem as an inference problem rather than a filter problem. Our approach assumes that the intruder’s actions are unknown to the IDS and can be inferred only from the alerts generated by the IDS sensors. HCPN can describe the relationship between different stepsmore » carried out by intruders, model observations (alerts) and transitions (actions) separately, and associate each token element (system state) with a probability (or confidence). The model is an extension to Colored Petri-Net (CPN) .It is so called “hidden” because the transitions (actions) are not directly observable but can be inferred by looking through the observations (alerts). These features make HCPN especially suitable for discovering intruders’ actions from their partial observations (alerts,) and predicting intruders’ next goal. Our experiments on DARPA evaluation datasets and the attack scenarios from the Grand Challenge Problem (GCP) show that HCPN has promise as a way to reducing false positives and negatives, predicting intruder’s next possible action, uncovering intruders’ intrusion strategies after the attack scenario has happened, and providing confidence scores.« less

Reading and Writing Difficulties--A Problem? EMIR Education and Research.

ERIC Educational Resources Information Center

Ericson, Britta, Ed.

This collection of essays contains a brief description of the symptoms of dyslexia and a definition of the terminology. The meaning of being the mother of a dyslexic child and how to live with this "hidden handicap" are also described. Suggestions regarding how to treat persons with reading and writing difficulties are put forward. After…

Educational Support Group in Changing Caregivers' Psychological Elder Abuse Behavior toward Caring for Institutionalized Elders

ERIC Educational Resources Information Center

Hsieh, Hsiu-Fang; Wang, Jing-Jy; Yen, Maiofen; Liu, Tzu-Ti

2009-01-01

Institutionalized elderly who are frail and dependent are vulnerable to be abused by overwhelmed caregivers especially caregiver psychological abusive behavior is a growing but hidden problem with few evidence-based interventions. The purpose of this study was to examine the effectiveness of an educational support group in alleviating caregiver's…

Hidden Challenges to Education Systems in Transition Economies.

ERIC Educational Resources Information Center

Berryman, Sue E.

This book, published by the World Bank, sounds the alarm for education in Europe and Central Asia (ECA). It describes how the transition from communism to free-market economies has left many countries' educational systems in disarray. At the start of transition, ECA education systems had solved problems that plagued other regions of the world,…

W 4 toda example as hidden Liouville CFT

NASA Astrophysics Data System (ADS)

Furlan, P.; Petkova, V. B.

2017-03-01

We construct correlators in the W 4 Toda 2d conformal field theory for a particular class of representations and demonstrate a relation to a W 2 (Virasoro) theory with different central charge. The relevance of the classical limits of the constructed 3-point functions and braiding matrices to problems in 4d conformal theories is discussed.

Fundamentals of angled-beam ultrasonic NDE for potential characterization of hidden regions of impact damage in composites

NASA Astrophysics Data System (ADS)

Aldrin, John C.; Wertz, John N.; Welter, John T.; Wallentine, Sarah; Lindgren, Eric A.; Kramb, Victoria; Zainey, David

2018-04-01

In this study, the use of angled-beam ultrasonic NDE was explored for the potential characterization of the hidden regions of impact damage in composites. Simulated studies using CIVA FIDEL 2D were used to explore this inspection problem. Quasi-shear (qS) modes can be generated over a wide range of angles and used to reflect off the backwall and interrogate under the top delaminations of impact damage. Secondary probe signals that do propagate normal to the surface were found to be significant under certain probe conditions, and can potentially interfere with weakly scattered signals from within the composite panel. Simulations were used to evaluate the source of the multiple paths of reflections from the edge of a delamination; time-of-flight and amplitude will depend on the depth of the delamination and location of neighboring delaminations. For angled-beam inspections, noise from both the top surface roughness and internal features was found to potentially mask the detection of signals from the edge of delaminations. Lastly, the study explored the potential of generating "guided" waves along the backwall using an angled-beam source and subsequently measuring scattered signals from a far surface crack hidden under a delamination.

Graviweak Unification, Invisible Universe and Dark Energy

NASA Astrophysics Data System (ADS)

Das, C. R.; Laperashvili, L. V.; Tureanu, A.

2013-07-01

We consider a graviweak unification model with the assumption of the existence of a hidden (invisible) sector of our Universe, parallel to the visible world. This Hidden World (HW) is assumed to be a Mirror World (MW) with broken mirror parity. We start with a diffeomorphism invariant theory of a gauge field valued in a Lie algebra g, which is broken spontaneously to the direct sum of the space-time Lorentz algebra and the Yang-Mills algebra: ˜ {g} = {{su}}(2) (grav)L ⊕ {{su}}(2)L — in the ordinary world, and ˜ {g}' = {{su}}(2){' (grav)}R ⊕ {{su}}(2)'R — in the hidden world. Using an extension of the Plebanski action for general relativity, we recover the actions for gravity, SU(2) Yang-Mills and Higgs fields in both (visible and invisible) sectors of the Universe, and also the total action. After symmetry breaking, all physical constants, including the Newton's constants, cosmological constants, Yang-Mills couplings, and other parameters, are determined by a single parameter g present in the initial action, and by the Higgs VEVs. The dark energy problem of this model predicts a too large supersymmetric breaking scale (MSUSY 1010GeV), which is not within the reach of the LHC experiments.

Double Higgs mechanisms, supermassive stable particles and the vacuum energy

NASA Astrophysics Data System (ADS)

Santillán, Osvaldo P.; Gabbanelli, Luciano

2016-07-01

In the present work, a hidden scenario which cast a long-lived superheavy particle A0 and simultaneously an extremely light particle a with mass ma ˜ 10-32-10-33 eV is presented. The potential energy V (a) of the particle a models the vacuum energy density of the universe ρc ≃ 10-47GeV4. On the other hand, the A0 particle may act as superheavy dark matter at present times and the products of its decay may be observed in high energy cosmic ray events. The hidden sector proposed here include light fermions with masses near the neutrino mass mν ˜ 10-2 eV and superheavy ones with masses of the order of the GUT scale, interacting through a hidden SU(2)L interaction which also affects the ordinary sector. The construction of such combined scenario is nontrivial since the presence of light particles may spoil the stability of the heavy particle A0. However, double Higgs mechanisms may be helpful for overcoming this problem. In this context, the stability of the superheavy particle A0 is ensured due to chiral symmetry arguments elaborated in the text.

Biological engineering applications of feedforward neural networks designed and parameterized by genetic algorithms.

PubMed

Ferentinos, Konstantinos P

2005-09-01

Two neural network (NN) applications in the field of biological engineering are developed, designed and parameterized by an evolutionary method based on the evolutionary process of genetic algorithms. The developed systems are a fault detection NN model and a predictive modeling NN system. An indirect or 'weak specification' representation was used for the encoding of NN topologies and training parameters into genes of the genetic algorithm (GA). Some a priori knowledge of the demands in network topology for specific application cases is required by this approach, so that the infinite search space of the problem is limited to some reasonable degree. Both one-hidden-layer and two-hidden-layer network architectures were explored by the GA. Except for the network architecture, each gene of the GA also encoded the type of activation functions in both hidden and output nodes of the NN and the type of minimization algorithm that was used by the backpropagation algorithm for the training of the NN. Both models achieved satisfactory performance, while the GA system proved to be a powerful tool that can successfully replace the problematic trial-and-error approach that is usually used for these tasks.

An Indoor Pedestrian Positioning Method Using HMM with a Fuzzy Pattern Recognition Algorithm in a WLAN Fingerprint System

PubMed Central

Ni, Yepeng; Liu, Jianbo; Liu, Shan; Bai, Yaxin

2016-01-01

With the rapid development of smartphones and wireless networks, indoor location-based services have become more and more prevalent. Due to the sophisticated propagation of radio signals, the Received Signal Strength Indicator (RSSI) shows a significant variation during pedestrian walking, which introduces critical errors in deterministic indoor positioning. To solve this problem, we present a novel method to improve the indoor pedestrian positioning accuracy by embedding a fuzzy pattern recognition algorithm into a Hidden Markov Model. The fuzzy pattern recognition algorithm follows the rule that the RSSI fading has a positive correlation to the distance between the measuring point and the AP location even during a dynamic positioning measurement. Through this algorithm, we use the RSSI variation trend to replace the specific RSSI value to achieve a fuzzy positioning. The transition probability of the Hidden Markov Model is trained by the fuzzy pattern recognition algorithm with pedestrian trajectories. Using the Viterbi algorithm with the trained model, we can obtain a set of hidden location states. In our experiments, we demonstrate that, compared with the deterministic pattern matching algorithm, our method can greatly improve the positioning accuracy and shows robust environmental adaptability. PMID:27618053

A Hidden Markov Model for Single Particle Tracks Quantifies Dynamic Interactions between LFA-1 and the Actin Cytoskeleton

PubMed Central

Das, Raibatak; Cairo, Christopher W.; Coombs, Daniel

2009-01-01

The extraction of hidden information from complex trajectories is a continuing problem in single-particle and single-molecule experiments. Particle trajectories are the result of multiple phenomena, and new methods for revealing changes in molecular processes are needed. We have developed a practical technique that is capable of identifying multiple states of diffusion within experimental trajectories. We model single particle tracks for a membrane-associated protein interacting with a homogeneously distributed binding partner and show that, with certain simplifying assumptions, particle trajectories can be regarded as the outcome of a two-state hidden Markov model. Using simulated trajectories, we demonstrate that this model can be used to identify the key biophysical parameters for such a system, namely the diffusion coefficients of the underlying states, and the rates of transition between them. We use a stochastic optimization scheme to compute maximum likelihood estimates of these parameters. We have applied this analysis to single-particle trajectories of the integrin receptor lymphocyte function-associated antigen-1 (LFA-1) on live T cells. Our analysis reveals that the diffusion of LFA-1 is indeed approximately two-state, and is characterized by large changes in cytoskeletal interactions upon cellular activation. PMID:19893741

The hidden web and the fentanyl problem: Detection of ocfentanil as an adulterant in heroin.

PubMed

Quintana, Pol; Ventura, Mireia; Grifell, Marc; Palma, Alvaro; Galindo, Liliana; Fornís, Iván; Gil, Cristina; Carbón, Xoán; Caudevilla, Fernando; Farré, Magí; Torrens, Marta

2017-02-01

The popularization of anonymous markets such as Silk Road is challenging current drug policy and may provide a new context for old issues, such as adulteration of heroin with fentanyl derivatives. The aims of this paper are to report the presence of ocfentanil, a novel, potent, non-controlled fentanyl analog, in samples sold as heroin in the hidden web, and to summarize the effects reported by users. In 2015, four samples allegedly bought as heroin in cryptomarkets of the hidden web were sent to Energy Control for analysis. Energy Control is a Spanish harm reduction NGO that offers anonymous drug checking with the purpose of adapting counselling to the specific substances present in the drug and monitor the drug market. Identification was performed by GC/MS and LC/MS/MS. We contacted the submitters of the samples and performed an Internet search to retrieve additional information. One sample contained ocfentanil, caffeine and heroin. Three samples contained the aforementioned substances plus paracetamol. Two out of the four contacted users reported distinct short acting, opioid-like effects. No fora discussion could be found about the effects of ocfentanil, neither web pages nor individuals advertising the substance. We report the presence of a new substance detected in the hidden web as an adulterant of heroin, ocfentanil. It has short acting opioid-like effects, roughly the same potency as fentanyl, and can be injected, snorted or smoked. Severe side effects have been associated with its use, including one death. No discussion about this substance could be found in the Internet, which suggests this substance has not been sold as such. Available data about purities of drugs purchased in cryptomarkets suggest that adulteration is not a severe problem and this agrees with users' perceptions. However, this study suggests that adulteration is a real threat not only at the street level, but also for users that buy substances in cryptomarkets, and suggest the need for harm reduction initiatives in this setting. Copyright © 2016 Elsevier B.V. All rights reserved.

Influence of gender and race/ethnicity on perceived barriers to help-seeking for alcohol or drug problems.

PubMed

Verissimo, Angie Denisse Otiniano; Grella, Christine E

2017-04-01

This study examines reasons why people do not seek help for alcohol or drug problems by gender and race/ethnicity using data from the National Epidemiologic Survey on Alcohol and Related Conditions (NESARC), a nationally representative survey. Multivariate models were fit for 3 barriers to seeking help (structural, attitudinal, and readiness for change) for either alcohol or drug problems, controlling for socio-demographic characteristics and problem severity. Predicted probabilities were generated to evaluate gender differences by racial/ethnic subgroups. Over three quarters of the samples endorsed attitudinal barriers related to either alcohol or drug use. Generally, women were less likely to endorse attitudinal barriers for alcohol problems. African Americans and Latina/os were less likely than Whites to endorse attitudinal barriers for alcohol problems, Latina/os were less likely than Whites to endorse readiness for change barriers for alcohol and drug problems, however, African Americans were more likely to endorse structural barriers for alcohol problems. Comparisons within racial/ethnic subgroups by gender revealed more complex findings, although across all racial/ethnic groups women endorsed attitudinal barriers for alcohol problems more than men. Study findings suggest the need to tailor interventions to increase access to help for alcohol and drug problems that take into consideration both attitudinal and structural barriers and how these vary across groups. Copyright © 2017 Elsevier Inc. All rights reserved.

Influence of Gender and Race/Ethnicity on Perceived Barriers to Help-Seeking for Alcohol or Drug Problems

PubMed Central

Verissimo, Angie Denisse Otiniano

2017-01-01

This study examines reasons why people do not seek help for alcohol or drug problems by gender and race/ethnicity using data from the National Epidemiologic Survey on Alcohol and Related Conditions (NESARC), a nationally representative survey. Multivariate models were fit for 3 barriers to seeking help (structural, attitudinal, and readiness for change) for either alcohol or drug problems, controlling for socio-demographic characteristics and problem severity. Predicted probabilities were generated to evaluate gender differences by racial/ethnic subgroups. Over three quarters of the samples endorsed attitudinal barriers related to either alcohol or drug use. Generally, women were less likely to endorse attitudinal barriers for alcohol problems. African Americans and Latina/os were less likely than Whites to endorse attitudinal barriers for alcohol problems, Latina/os were less likely than Whites to endorse readiness for change barriers for alcohol and drug problems, however, African Americans were more likely to endorse structural barriers for alcohol problems. Comparisons within racial/ethnic subgroups by gender revealed more complex findings, although across all racial/ethnic groups women endorsed attitudinal barriers for alcohol problems more than men. Study findings suggest the need to tailor interventions to increase access to help for alcohol and drug problems that take into consideration both attitudinal and structural barriers and how these vary across groups. PMID:28237055

Software environment for implementing engineering applications on MIMD computers

NASA Technical Reports Server (NTRS)

Lopez, L. A.; Valimohamed, K. A.; Schiff, S.

1990-01-01

In this paper the concept for a software environment for developing engineering application systems for multiprocessor hardware (MIMD) is presented. The philosophy employed is to solve the largest problems possible in a reasonable amount of time, rather than solve existing problems faster. In the proposed environment most of the problems concerning parallel computation and handling of large distributed data spaces are hidden from the application program developer, thereby facilitating the development of large-scale software applications. Applications developed under the environment can be executed on a variety of MIMD hardware; it protects the application software from the effects of a rapidly changing MIMD hardware technology.

The free fall of an apple: conceptual subtleties and implications for physics teaching

NASA Astrophysics Data System (ADS)

Assis, A. K. T.; Karam, R. A. S.

2018-05-01

The study of free fall is thoroughly present in physics teaching at all levels. From the point of view of Newtonian dynamics it appears to be extremely simple, as it consists of a two-body problem with a constant force generating a constant acceleration. However, there are several important conceptual subtleties and hidden assumptions involved in this problem, which are rarely discussed in educational settings. In this work we present some of these subtleties and argue that explicitly addressing them has significant pedagogical benefits.

Area-Preserving Diffeomorphisms, W∞ and { U}q [sl(2)] in Chern-Simons Theory and the Quantum Hall System

NASA Astrophysics Data System (ADS)

Kogan, Ian I.

We discuss a quantum { U}q [sl(2)] symmetry in the Landau problem, which naturally arises due to the relation between { U}q [sl(2)] and the group of magnetic translations. The latter is connected with W∞ and area-preserving (symplectic) diffeomorphisms which are the canonical transformations in the two-dimensional phase space. We shall discuss the hidden quantum symmetry in a 2 + 1 gauge theory with the Chern-Simons term and in a quantum Hall system, which are both connected with the Landau problem.

Fast, Simple and Accurate Handwritten Digit Classification by Training Shallow Neural Network Classifiers with the ‘Extreme Learning Machine’ Algorithm

PubMed Central

McDonnell, Mark D.; Tissera, Migel D.; Vladusich, Tony; van Schaik, André; Tapson, Jonathan

2015-01-01

Recent advances in training deep (multi-layer) architectures have inspired a renaissance in neural network use. For example, deep convolutional networks are becoming the default option for difficult tasks on large datasets, such as image and speech recognition. However, here we show that error rates below 1% on the MNIST handwritten digit benchmark can be replicated with shallow non-convolutional neural networks. This is achieved by training such networks using the ‘Extreme Learning Machine’ (ELM) approach, which also enables a very rapid training time (∼ 10 minutes). Adding distortions, as is common practise for MNIST, reduces error rates even further. Our methods are also shown to be capable of achieving less than 5.5% error rates on the NORB image database. To achieve these results, we introduce several enhancements to the standard ELM algorithm, which individually and in combination can significantly improve performance. The main innovation is to ensure each hidden-unit operates only on a randomly sized and positioned patch of each image. This form of random ‘receptive field’ sampling of the input ensures the input weight matrix is sparse, with about 90% of weights equal to zero. Furthermore, combining our methods with a small number of iterations of a single-batch backpropagation method can significantly reduce the number of hidden-units required to achieve a particular performance. Our close to state-of-the-art results for MNIST and NORB suggest that the ease of use and accuracy of the ELM algorithm for designing a single-hidden-layer neural network classifier should cause it to be given greater consideration either as a standalone method for simpler problems, or as the final classification stage in deep neural networks applied to more difficult problems. PMID:26262687

Cascade Error Projection: A Learning Algorithm for Hardware Implementation

NASA Technical Reports Server (NTRS)

Duong, Tuan A.; Daud, Taher

1996-01-01

In this paper, we workout a detailed mathematical analysis for a new learning algorithm termed Cascade Error Projection (CEP) and a general learning frame work. This frame work can be used to obtain the cascade correlation learning algorithm by choosing a particular set of parameters. Furthermore, CEP learning algorithm is operated only on one layer, whereas the other set of weights can be calculated deterministically. In association with the dynamical stepsize change concept to convert the weight update from infinite space into a finite space, the relation between the current stepsize and the previous energy level is also given and the estimation procedure for optimal stepsize is used for validation of our proposed technique. The weight values of zero are used for starting the learning for every layer, and a single hidden unit is applied instead of using a pool of candidate hidden units similar to cascade correlation scheme. Therefore, simplicity in hardware implementation is also obtained. Furthermore, this analysis allows us to select from other methods (such as the conjugate gradient descent or the Newton's second order) one of which will be a good candidate for the learning technique. The choice of learning technique depends on the constraints of the problem (e.g., speed, performance, and hardware implementation); one technique may be more suitable than others. Moreover, for a discrete weight space, the theoretical analysis presents the capability of learning with limited weight quantization. Finally, 5- to 8-bit parity and chaotic time series prediction problems are investigated; the simulation results demonstrate that 4-bit or more weight quantization is sufficient for learning neural network using CEP. In addition, it is demonstrated that this technique is able to compensate for less bit weight resolution by incorporating additional hidden units. However, generation result may suffer somewhat with lower bit weight quantization.

Probabilistic hazard assessment for skin sensitization potency by dose–response modeling using feature elimination instead of quantitative structure–activity relationships

PubMed Central

McKim, James M.; Hartung, Thomas; Kleensang, Andre; Sá-Rocha, Vanessa

2016-01-01

Supervised learning methods promise to improve integrated testing strategies (ITS), but must be adjusted to handle high dimensionality and dose–response data. ITS approaches are currently fueled by the increasing mechanistic understanding of adverse outcome pathways (AOP) and the development of tests reflecting these mechanisms. Simple approaches to combine skin sensitization data sets, such as weight of evidence, fail due to problems in information redundancy and high dimension-ality. The problem is further amplified when potency information (dose/response) of hazards would be estimated. Skin sensitization currently serves as the foster child for AOP and ITS development, as legislative pressures combined with a very good mechanistic understanding of contact dermatitis have led to test development and relatively large high-quality data sets. We curated such a data set and combined a recursive variable selection algorithm to evaluate the information available through in silico, in chemico and in vitro assays. Chemical similarity alone could not cluster chemicals’ potency, and in vitro models consistently ranked high in recursive feature elimination. This allows reducing the number of tests included in an ITS. Next, we analyzed with a hidden Markov model that takes advantage of an intrinsic inter-relationship among the local lymph node assay classes, i.e. the monotonous connection between local lymph node assay and dose. The dose-informed random forest/hidden Markov model was superior to the dose-naive random forest model on all data sets. Although balanced accuracy improvement may seem small, this obscures the actual improvement in misclassifications as the dose-informed hidden Markov model strongly reduced "false-negatives" (i.e. extreme sensitizers as non-sensitizer) on all data sets. PMID:26046447

Probabilistic hazard assessment for skin sensitization potency by dose-response modeling using feature elimination instead of quantitative structure-activity relationships.

PubMed

Luechtefeld, Thomas; Maertens, Alexandra; McKim, James M; Hartung, Thomas; Kleensang, Andre; Sá-Rocha, Vanessa

2015-11-01

Supervised learning methods promise to improve integrated testing strategies (ITS), but must be adjusted to handle high dimensionality and dose-response data. ITS approaches are currently fueled by the increasing mechanistic understanding of adverse outcome pathways (AOP) and the development of tests reflecting these mechanisms. Simple approaches to combine skin sensitization data sets, such as weight of evidence, fail due to problems in information redundancy and high dimensionality. The problem is further amplified when potency information (dose/response) of hazards would be estimated. Skin sensitization currently serves as the foster child for AOP and ITS development, as legislative pressures combined with a very good mechanistic understanding of contact dermatitis have led to test development and relatively large high-quality data sets. We curated such a data set and combined a recursive variable selection algorithm to evaluate the information available through in silico, in chemico and in vitro assays. Chemical similarity alone could not cluster chemicals' potency, and in vitro models consistently ranked high in recursive feature elimination. This allows reducing the number of tests included in an ITS. Next, we analyzed with a hidden Markov model that takes advantage of an intrinsic inter-relationship among the local lymph node assay classes, i.e. the monotonous connection between local lymph node assay and dose. The dose-informed random forest/hidden Markov model was superior to the dose-naive random forest model on all data sets. Although balanced accuracy improvement may seem small, this obscures the actual improvement in misclassifications as the dose-informed hidden Markov model strongly reduced " false-negatives" (i.e. extreme sensitizers as non-sensitizer) on all data sets. Copyright © 2015 John Wiley & Sons, Ltd.

Affective State Level Recognition in Naturalistic Facial and Vocal Expressions.

PubMed

Meng, Hongying; Bianchi-Berthouze, Nadia

2014-03-01

Naturalistic affective expressions change at a rate much slower than the typical rate at which video or audio is recorded. This increases the probability that consecutive recorded instants of expressions represent the same affective content. In this paper, we exploit such a relationship to improve the recognition performance of continuous naturalistic affective expressions. Using datasets of naturalistic affective expressions (AVEC 2011 audio and video dataset, PAINFUL video dataset) continuously labeled over time and over different dimensions, we analyze the transitions between levels of those dimensions (e.g., transitions in pain intensity level). We use an information theory approach to show that the transitions occur very slowly and hence suggest modeling them as first-order Markov models. The dimension levels are considered to be the hidden states in the Hidden Markov Model (HMM) framework. Their discrete transition and emission matrices are trained by using the labels provided with the training set. The recognition problem is converted into a best path-finding problem to obtain the best hidden states sequence in HMMs. This is a key difference from previous use of HMMs as classifiers. Modeling of the transitions between dimension levels is integrated in a multistage approach, where the first level performs a mapping between the affective expression features and a soft decision value (e.g., an affective dimension level), and further classification stages are modeled as HMMs that refine that mapping by taking into account the temporal relationships between the output decision labels. The experimental results for each of the unimodal datasets show overall performance to be significantly above that of a standard classification system that does not take into account temporal relationships. In particular, the results on the AVEC 2011 audio dataset outperform all other systems presented at the international competition.

Dark matter versus Mach's principle.

NASA Astrophysics Data System (ADS)

von Borzeszkowski, H.-H.; Treder, H.-J.

1998-02-01

Empirical and theoretical evidence show that the astrophysical problem of dark matter might be solved by a theory of Einstein-Mayer type. In this theory up to global Lorentz rotations the reference system is determined by the motion of cosmic matter. Thus one is led to a "Riemannian space with teleparallelism" realizing a geometric version of the Mach-Einstein doctrine. The field equations of this gravitational theory contain hidden matter terms where the existence of hidden matter is inferred safely from its gravitational effects. It is argued that in the nonrelativistic mechanical approximation they provide an inertia-free mechanics where the inertial mass of a body is induced by the gravitational action of the comic masses. Interpreted form the Newtonian point of view this mechanics shows that the effective gravitational mass of astrophysical objects depends on r such that one expects the existence of dark matter.

Maximum likelihood: Extracting unbiased information from complex networks

NASA Astrophysics Data System (ADS)

Garlaschelli, Diego; Loffredo, Maria I.

2008-07-01

The choice of free parameters in network models is subjective, since it depends on what topological properties are being monitored. However, we show that the maximum likelihood (ML) principle indicates a unique, statistically rigorous parameter choice, associated with a well-defined topological feature. We then find that, if the ML condition is incompatible with the built-in parameter choice, network models turn out to be intrinsically ill defined or biased. To overcome this problem, we construct a class of safely unbiased models. We also propose an extension of these results that leads to the fascinating possibility to extract, only from topological data, the “hidden variables” underlying network organization, making them “no longer hidden.” We test our method on World Trade Web data, where we recover the empirical gross domestic product using only topological information.

Cognitive and Mathematical Profiles for Different Forms of Learning Difficulties

PubMed Central

Cirino, Paul T.; Fuchs, Lynn S.; Elias, John T.; Powell, Sarah R.; Schumacher, Robin F.

2014-01-01

The purpose of this study was to compare subgroups of students with various forms of learning difficulties (< 25th percentile) on cognitive and mathematics characteristics. Students with mathematics difficulty (MD, n = 105), reading difficulty (RD, n = 65), both (MDRD, n = 87), or neither (NoLD, n = 403) were evaluated on an array of cognitive measures (e.g., working memory and language) and on mathematics measures of foundational numerical competencies, computation, and problem solving. Results revealed expected level differences among groups in both domains: NoLD outperformed RD, and MD outperformed MDRD. Profile differences were noted among pairs of subgroups on cognitive measures. On mathematics measures, profile differences were noted between RD and other subgroups, but not between MD and MDRD subgroups. The most discriminating cognitive measures were processing speed and language; the most discriminating mathematics measures depended on the subgroups being compared. Results were further evaluated according to more severe (< 10th percentile) criteria for MD and RD, which generally affected level differences more than the profile patterns. Results have implications for understanding comorbid MD and RD and for conceptualizing core deficits in MD. PMID:23851137

SPEECH TO FACULTY OF HARVARD-BOSTON SUMMER PROGRAM AT PREPLANNING MEETINGS.

ERIC Educational Resources Information Center

HAIZLIP, HAROLD

THE AREA TO WHICH THIS GROUP OF TEACHERS WILL BE SENT IS CHARACTERIZED BY ITS LARGE INFLUX OF POOR NEGRO FAMILIES WITH POOR CULTURAL BACKGROUNDS. SOME OF THE PROBLEMS OF THIS AREA WILL REQUIRE A BROAD-SCALE, CAREFULLY ANALYZED, AND PLANNED ATTACK WITHIN AND BY PUBLIC SCHOOLS. EVERY SCHOOL HAS A HIDDEN OR SUBLIMINAL CURRICULUM WHICH TEACHES, IN…

Substance Abuse: A Hidden Problem within the D/deaf and Hard of Hearing Communities

ERIC Educational Resources Information Center

Guthmann, Debra; Graham, Vicki

2004-01-01

Current research indicates that D/deaf and hard of hearing clients seeking treatment for substance abuse often encounter obstacles in receiving the help they need. Many of these obstacles are the result of a lack of knowledge and experience with regard to treating D/deaf and hard of hearing people. Programs designed for hearing people that attempt…

Hidden Dangers within Our Schools: What Are These Safety Problems and How Can We Fix Them? Safety in the Schools

ERIC Educational Resources Information Center

Gunzelmann, Betsy

2005-01-01

Safety in the schools involves much more than metal detectors and disaster plans. Although such catastrophe preparation is necessary, we often overlook less obvious beliefs and practices that put children's everyday safety at risk. According to the well-known pediatrician T. Berry Brazelton and the child psychiatrist Stanley Greenspan (2000), all…

The Role of Hidden Curricula on the Resistance Behavior of Undergraduate Students in Psychological Counseling and Guidance at a Turkish University

ERIC Educational Resources Information Center

Yuksel, Sedat

2006-01-01

Student resistance can be a very important problem for the instructors in universities. Student resistance includes the conscious and preplanned behaviors towards the information presented to them in the classroom and the institutional practices. Typically, student resistance takes the form of passive or active non-compliance with roles and…

Monitoring the Future National Survey Results on Drug Use, 1975-2010. Volume I, Secondary School Students

ERIC Educational Resources Information Center

Johnston, Lloyd D.; O'Malley, Patrick M.; Bachman, Jerald G.; Schulenberg, John E.

2011-01-01

The Monitoring the Future (MTF) study involves an ongoing series of national surveys of American adolescents and adults that has provided the nation with a vital window into the important, but largely hidden, problem behaviors of illegal drug use, alcohol use, tobacco use, anabolic steroid use, and psychotherapeutic drug use. For more than a third…

On the complexity of neural network classifiers: a comparison between shallow and deep architectures.

PubMed

Bianchini, Monica; Scarselli, Franco

2014-08-01

Recently, researchers in the artificial neural network field have focused their attention on connectionist models composed by several hidden layers. In fact, experimental results and heuristic considerations suggest that deep architectures are more suitable than shallow ones for modern applications, facing very complex problems, e.g., vision and human language understanding. However, the actual theoretical results supporting such a claim are still few and incomplete. In this paper, we propose a new approach to study how the depth of feedforward neural networks impacts on their ability in implementing high complexity functions. First, a new measure based on topological concepts is introduced, aimed at evaluating the complexity of the function implemented by a neural network, used for classification purposes. Then, deep and shallow neural architectures with common sigmoidal activation functions are compared, by deriving upper and lower bounds on their complexity, and studying how the complexity depends on the number of hidden units and the used activation function. The obtained results seem to support the idea that deep networks actually implements functions of higher complexity, so that they are able, with the same number of resources, to address more difficult problems.

Neural net classification of x-ray pistachio nut data

NASA Astrophysics Data System (ADS)

Casasent, David P.; Sipe, Michael A.; Schatzki, Thomas F.; Keagy, Pamela M.; Le, Lan Chau

1996-12-01

Classification results for agricultural products are presented using a new neural network. This neural network inherently produces higher-order decision surfaces. It achieves this with fewer hidden layer neurons than other classifiers require. This gives better generalization. It uses new techniques to select the number of hidden layer neurons and adaptive algorithms that avoid other such ad hoc parameter selection problems; it allows selection of the best classifier parameters without the need to analyze the test set results. The agriculture case study considered is the inspection and classification of pistachio nuts using x- ray imagery. Present inspection techniques cannot provide good rejection of worm damaged nuts without rejecting too many good nuts. X-ray imagery has the potential to provide 100% inspection of such agricultural products in real time. Only preliminary results are presented, but these indicate the potential to reduce major defects to 2% of the crop with 1% of good nuts rejected. Future image processing techniques that should provide better features to improve performance and allow inspection of a larger variety of nuts are noted. These techniques and variations of them have uses in a number of other agricultural product inspection problems.

Clustering Multivariate Time Series Using Hidden Markov Models

PubMed Central

Ghassempour, Shima; Girosi, Federico; Maeder, Anthony

2014-01-01

In this paper we describe an algorithm for clustering multivariate time series with variables taking both categorical and continuous values. Time series of this type are frequent in health care, where they represent the health trajectories of individuals. The problem is challenging because categorical variables make it difficult to define a meaningful distance between trajectories. We propose an approach based on Hidden Markov Models (HMMs), where we first map each trajectory into an HMM, then define a suitable distance between HMMs and finally proceed to cluster the HMMs with a method based on a distance matrix. We test our approach on a simulated, but realistic, data set of 1,255 trajectories of individuals of age 45 and over, on a synthetic validation set with known clustering structure, and on a smaller set of 268 trajectories extracted from the longitudinal Health and Retirement Survey. The proposed method can be implemented quite simply using standard packages in R and Matlab and may be a good candidate for solving the difficult problem of clustering multivariate time series with categorical variables using tools that do not require advanced statistic knowledge, and therefore are accessible to a wide range of researchers. PMID:24662996

Detecting network communities beyond assortativity-related attributes

NASA Astrophysics Data System (ADS)

Liu, Xin; Murata, Tsuyoshi; Wakita, Ken

2014-07-01

In network science, assortativity refers to the tendency of links to exist between nodes with similar attributes. In social networks, for example, links tend to exist between individuals of similar age, nationality, location, race, income, educational level, religious belief, and language. Thus, various attributes jointly affect the network topology. An interesting problem is to detect community structure beyond some specific assortativity-related attributes ρ, i.e., to take out the effect of ρ on network topology and reveal the hidden community structures which are due to other attributes. An approach to this problem is to redefine the null model of the modularity measure, so as to simulate the effect of ρ on network topology. However, a challenge is that we do not know to what extent the network topology is affected by ρ and by other attributes. In this paper, we propose a distance modularity, which allows us to freely choose any suitable function to simulate the effect of ρ. Such freedom can help us probe the effect of ρ and detect the hidden communities which are due to other attributes. We test the effectiveness of distance modularity on synthetic benchmarks and two real-world networks.

Extracting duration information in a picture category decoding task using hidden Markov Models

NASA Astrophysics Data System (ADS)

Pfeiffer, Tim; Heinze, Nicolai; Frysch, Robert; Deouell, Leon Y.; Schoenfeld, Mircea A.; Knight, Robert T.; Rose, Georg

2016-04-01

Objective. Adapting classifiers for the purpose of brain signal decoding is a major challenge in brain-computer-interface (BCI) research. In a previous study we showed in principle that hidden Markov models (HMM) are a suitable alternative to the well-studied static classifiers. However, since we investigated a rather straightforward task, advantages from modeling of the signal could not be assessed. Approach. Here, we investigate a more complex data set in order to find out to what extent HMMs, as a dynamic classifier, can provide useful additional information. We show for a visual decoding problem that besides category information, HMMs can simultaneously decode picture duration without an additional training required. This decoding is based on a strong correlation that we found between picture duration and the behavior of the Viterbi paths. Main results. Decoding accuracies of up to 80% could be obtained for category and duration decoding with a single classifier trained on category information only. Significance. The extraction of multiple types of information using a single classifier enables the processing of more complex problems, while preserving good training results even on small databases. Therefore, it provides a convenient framework for online real-life BCI utilizations.

Hidden physics models: Machine learning of nonlinear partial differential equations

NASA Astrophysics Data System (ADS)

Raissi, Maziar; Karniadakis, George Em

2018-03-01

While there is currently a lot of enthusiasm about "big data", useful data is usually "small" and expensive to acquire. In this paper, we present a new paradigm of learning partial differential equations from small data. In particular, we introduce hidden physics models, which are essentially data-efficient learning machines capable of leveraging the underlying laws of physics, expressed by time dependent and nonlinear partial differential equations, to extract patterns from high-dimensional data generated from experiments. The proposed methodology may be applied to the problem of learning, system identification, or data-driven discovery of partial differential equations. Our framework relies on Gaussian processes, a powerful tool for probabilistic inference over functions, that enables us to strike a balance between model complexity and data fitting. The effectiveness of the proposed approach is demonstrated through a variety of canonical problems, spanning a number of scientific domains, including the Navier-Stokes, Schrödinger, Kuramoto-Sivashinsky, and time dependent linear fractional equations. The methodology provides a promising new direction for harnessing the long-standing developments of classical methods in applied mathematics and mathematical physics to design learning machines with the ability to operate in complex domains without requiring large quantities of data.

Exploring asynchronous brainstorming in large groups: a field comparison of serial and parallel subgroups.

PubMed

de Vreede, Gert-Jan; Briggs, Robert O; Reiter-Palmon, Roni

2010-04-01

The aim of this study was to compare the results of two different modes of using multiple groups (instead of one large group) to identify problems and develop solutions. Many of the complex problems facing organizations today require the use of very large groups or collaborations of groups from multiple organizations. There are many logistical problems associated with the use of such large groups, including the ability to bring everyone together at the same time and location. A field study involved two different organizations and compared productivity and satisfaction of group. The approaches included (a) multiple small groups, each completing the entire process from start to end and combining the results at the end (parallel mode); and (b) multiple subgroups, each building on the work provided by previous subgroups (serial mode). Groups using the serial mode produced more elaborations compared with parallel groups, whereas parallel groups produced more unique ideas compared with serial groups. No significant differences were found related to satisfaction with process and outcomes between the two modes. Preferred mode depends on the type of task facing the group. Parallel groups are more suited for tasks for which a variety of new ideas are needed, whereas serial groups are best suited when elaboration and in-depth thinking on the solution are required. Results of this research can guide the development of facilitated sessions of large groups or "teams of teams."

Handling Imbalanced Data Sets in Multistage Classification

NASA Astrophysics Data System (ADS)

López, M.

Multistage classification is a logical approach, based on a divide-and-conquer solution, for dealing with problems with a high number of classes. The classification problem is divided into several sequential steps, each one associated to a single classifier that works with subgroups of the original classes. In each level, the current set of classes is split into smaller subgroups of classes until they (the subgroups) are composed of only one class. The resulting chain of classifiers can be represented as a tree, which (1) simplifies the classification process by using fewer categories in each classifier and (2) makes it possible to combine several algorithms or use different attributes in each stage. Most of the classification algorithms can be biased in the sense of selecting the most populated class in overlapping areas of the input space. This can degrade a multistage classifier performance if the training set sample frequencies do not reflect the real prevalence in the population. Several techniques such as applying prior probabilities, assigning weights to the classes, or replicating instances have been developed to overcome this handicap. Most of them are designed for two-class (accept-reject) problems. In this article, we evaluate several of these techniques as applied to multistage classification and analyze how they can be useful for astronomy. We compare the results obtained by classifying a data set based on Hipparcos with and without these methods.

Mean-field theory of baryonic matter for QCD in the large Nc and heavy quark mass limits

NASA Astrophysics Data System (ADS)

Adhikari, Prabal; Cohen, Thomas D.

2013-11-01

We discuss theoretical issues pertaining to baryonic matter in the combined heavy-quark and large Nc limits of QCD. Witten's classic argument that baryons and interacting systems of baryons can be described in a mean-field approximation with each of the quarks moving in an average potential due to the remaining quarks is heuristic. It is important to justify this heuristic description for the case of baryonic matter since systems of interacting baryons are intrinsically more complicated than single baryons due to the possibility of hidden color states—states in which the subsystems making up the entire baryon crystal are not color-singlet nucleons but rather colorful states coupled together to make a color-singlet state. In this work, we provide a formal justification of this heuristic prescription. In order to do this, we start by taking the heavy quark limit, thus effectively reducing the problem to a many-body quantum mechanical system. This problem can be formulated in terms of integrals over coherent states, which for this problem are simple Slater determinants. We show that for the many-body problem, the support region for these integrals becomes narrow at large Nc, yielding an energy which is well approximated by a single coherent state—that is a mean-field description. Corrections to the energy are of relative order 1/Nc. While hidden color states are present in the exact state of the heavy quark system, they only influence the interaction energy below leading order in 1/Nc.

Association between Speech-Language, General Cognitive Functioning and Behaviour Problems in Individuals with Williams Syndrome

ERIC Educational Resources Information Center

Rossi, N. F.; Giacheti, C. M.

2017-01-01

Background: Williams syndrome (WS) phenotype is described as unique and intriguing. The aim of this study was to investigate the associations between speech-language abilities, general cognitive functioning and behavioural problems in individuals with WS, considering age effects and speech-language characteristics of WS sub-groups. Methods: The…

Size Matters: Increased Grey Matter in Boys with Conduct Problems and Callous-Unemotional Traits

ERIC Educational Resources Information Center

De Brito, Stephane A.; Mechelli, Andrea; Wilke, Marko; Laurens, Kristin R.; Jones, Alice P.; Barker, Gareth J.; Hodgins, Sheilagh; Viding, Essi

2009-01-01

Brain imaging studies of adults with psychopathy have identified structural and functional abnormalities in limbic and prefrontal regions that are involved in emotion recognition, decision-making, morality and empathy. Among children with conduct problems, a small subgroup presents callous-unemotional traits thought to be antecedents of…

Subjective cognitive complaints contribute to misdiagnosis of mild cognitive impairment.

PubMed

Edmonds, Emily C; Delano-Wood, Lisa; Galasko, Douglas R; Salmon, David P; Bondi, Mark W

2014-09-01

Subjective cognitive complaints are a criterion for the diagnosis of mild cognitive impairment (MCI), despite their uncertain relationship to objective memory performance in MCI. We aimed to examine self-reported cognitive complaints in subgroups of the Alzheimer's Disease Neuroimaging Initiative (ADNI) MCI cohort to determine whether they are a valuable inclusion in the diagnosis of MCI or, alternatively, if they contribute to misdiagnosis. Subgroups of MCI were derived using cluster analysis of baseline neuropsychological test data from 448 ADNI MCI participants. Cognitive complaints were assessed via the Everyday Cognition (ECog) questionnaire, and discrepancy scores were calculated between self- and informant-report. Cluster analysis revealed Amnestic and Mixed cognitive phenotypes as well as a third Cluster-Derived Normal subgroup (41.3%), whose neuropsychological and cerebrospinal fluid (CSF) Alzheimer's disease (AD) biomarker profiles did not differ from a "robust" normal control group. This cognitively intact phenotype of MCI participants overestimated their cognitive problems relative to their informant, whereas Amnestic MCI participants with objective memory impairment underestimated their cognitive problems. Underestimation of cognitive problems was associated with positive CSF AD biomarkers and progression to dementia. Overall, there was no relationship between self-reported cognitive complaints and objective cognitive functioning, but significant correlations were observed with depressive symptoms. The inclusion of self-reported complaints in MCI diagnostic criteria may cloud rather than clarify diagnosis and result in high rates of misclassification of MCI. Discrepancies between self- and informant-report demonstrate that overestimation of cognitive problems is characteristic of normal aging while underestimation may reflect greater risk for cognitive decline.

Subgroups of advanced cancer patients clustered by their symptom profiles: quality-of-life outcomes.

PubMed

Husain, Amna; Myers, Jeff; Selby, Debbie; Thomson, Barbara; Chow, Edward

2011-11-01

Symptom cluster analysis is a new frontier of research in symptom management. This study clustered patients by their symptom profiles to identify subgroups that may be at higher risk for poor quality of life (QOL) and that may, therefore, benefit most from targeted interventions. Longitudinal study of metastatic cancer patients using the Edmonton Symptom Assessment Scale (ESAS). We generated two-, three-, and four-cluster subgroups and examined the relationship of cluster membership with patient outcomes. To address the problem of missing longitudinal data, we developed a novel outcome variable (QualTime) that measures both QOL and time in study. Two hundred and twenty-one patients with a mean Palliative Performance Scale (PPS) of 59.1 were enrolled. The three-cluster model was chosen for further analysis. The low-burden subgroup had all low severity symptom scores. The intermediate subgroup separates from the low-burden group on the "debility" profile of fatigue, drowsiness, appetite, and well-being. The high-burden group separates from the intermediate-burden group on pain, depression, and anxiety. At baseline, PPS (p=0.0003) and cluster membership (p<0.0001) contributed significantly to global QOL. In univariate analysis, cluster membership was related to the longitudinal outcome, QualTime. In a multivariate model, the relationship of PPS to QualTime was still significant (p=0.0002), but subgroup membership was no longer significant (p=0.1009). PPS is a stronger predictor of the longitudinal variable than cluster subgroups; however, cluster subgroups provide a target for clinical interventions that may improve QOL.

Hidden momentum of electrons, nuclei, atoms, and molecules

NASA Astrophysics Data System (ADS)

Cameron, Robert P.; Cotter, J. P.

2018-04-01

We consider the positions and velocities of electrons and spinning nuclei and demonstrate that these particles harbour hidden momentum when located in an electromagnetic field. This hidden momentum is present in all atoms and molecules, however it is ultimately canceled by the momentum of the electromagnetic field. We point out that an electron vortex in an electric field might harbour a comparatively large hidden momentum and recognize the phenomenon of hidden hidden momentum.

The Hidden Diversity of Flagellated Protists in Soil.

PubMed

Venter, Paul Christiaan; Nitsche, Frank; Arndt, Hartmut

2018-07-01

Protists are among the most diverse and abundant eukaryotes in soil. However, gaps between described and sequenced protist morphospecies still present a pending problem when surveying environmental samples for known species using molecular methods. The number of sequences in the molecular PR 2 database (∼130,000) is limited compared to the species richness expected (>1 million protist species) - limiting the recovery rate. This is important, since high throughput sequencing (HTS) methods are used to find associative patterns between functional traits, taxa and environmental parameters. We performed HTS to survey soil flagellates in 150 grasslands of central Europe, and tested the recovery rate of ten previously isolated and cultivated cercomonad species, among locally found diversity. We recovered sequences for reference soil flagellate species, but also a great number of their phylogenetically evaluated genetic variants, among rare and dominant taxa with presumably own biogeography. This was recorded among dominant (cercozoans, Sandona), rare (apusozoans) and a large hidden diversity of predominantly aquatic protists in soil (choanoflagellates, bicosoecids) often forming novel clades associated with uncultured environmental sequences. Evaluating the reads, instead of the OTUs that individual reads are usually clustered into, we discovered that much of this hidden diversity may be lost due to clustering. Copyright © 2018 Elsevier GmbH. All rights reserved.

A Hidden Markov Model for Urban-Scale Traffic Estimation Using Floating Car Data.

PubMed

Wang, Xiaomeng; Peng, Ling; Chi, Tianhe; Li, Mengzhu; Yao, Xiaojing; Shao, Jing

2015-01-01

Urban-scale traffic monitoring plays a vital role in reducing traffic congestion. Owing to its low cost and wide coverage, floating car data (FCD) serves as a novel approach to collecting traffic data. However, sparse probe data represents the vast majority of the data available on arterial roads in most urban environments. In order to overcome the problem of data sparseness, this paper proposes a hidden Markov model (HMM)-based traffic estimation model, in which the traffic condition on a road segment is considered as a hidden state that can be estimated according to the conditions of road segments having similar traffic characteristics. An algorithm based on clustering and pattern mining rather than on adjacency relationships is proposed to find clusters with road segments having similar traffic characteristics. A multi-clustering strategy is adopted to achieve a trade-off between clustering accuracy and coverage. Finally, the proposed model is designed and implemented on the basis of a real-time algorithm. Results of experiments based on real FCD confirm the applicability, accuracy, and efficiency of the model. In addition, the results indicate that the model is practicable for traffic estimation on urban arterials and works well even when more than 70% of the probe data are missing.

Hidden Markov induced Dynamic Bayesian Network for recovering time evolving gene regulatory networks

NASA Astrophysics Data System (ADS)

Zhu, Shijia; Wang, Yadong

2015-12-01

Dynamic Bayesian Networks (DBN) have been widely used to recover gene regulatory relationships from time-series data in computational systems biology. Its standard assumption is ‘stationarity’, and therefore, several research efforts have been recently proposed to relax this restriction. However, those methods suffer from three challenges: long running time, low accuracy and reliance on parameter settings. To address these problems, we propose a novel non-stationary DBN model by extending each hidden node of Hidden Markov Model into a DBN (called HMDBN), which properly handles the underlying time-evolving networks. Correspondingly, an improved structural EM algorithm is proposed to learn the HMDBN. It dramatically reduces searching space, thereby substantially improving computational efficiency. Additionally, we derived a novel generalized Bayesian Information Criterion under the non-stationary assumption (called BWBIC), which can help significantly improve the reconstruction accuracy and largely reduce over-fitting. Moreover, the re-estimation formulas for all parameters of our model are derived, enabling us to avoid reliance on parameter settings. Compared to the state-of-the-art methods, the experimental evaluation of our proposed method on both synthetic and real biological data demonstrates more stably high prediction accuracy and significantly improved computation efficiency, even with no prior knowledge and parameter settings.

Noninvasive Fetal ECG: the PhysioNet/Computing in Cardiology Challenge 2013.

PubMed

Silva, Ikaro; Behar, Joachim; Sameni, Reza; Zhu, Tingting; Oster, Julien; Clifford, Gari D; Moody, George B

2013-03-01

The PhysioNet/CinC 2013 Challenge aimed to stimulate rapid development and improvement of software for estimating fetal heart rate (FHR), fetal interbeat intervals (FRR), and fetal QT intervals (FQT), from multichannel recordings made using electrodes placed on the mother's abdomen. For the challenge, five data collections from a variety of sources were used to compile a large standardized database, which was divided into training, open test, and hidden test subsets. Gold-standard fetal QRS and QT interval annotations were developed using a novel crowd-sourcing framework. The challenge organizers used the hidden test subset to evaluate 91 open-source software entries submitted by 53 international teams of participants in three challenge events, estimating FHR, FRR, and FQT using the hidden test subset, which was not available for study by participants. Two additional events required only user-submitted QRS annotations to evaluate FHR and FRR estimation accuracy using the open test subset available to participants. The challenge yielded a total of 91 open-source software entries. The best of these achieved average estimation errors of 187bpm 2 for FHR, 20.9 ms for FRR, and 152.7 ms for FQT. The open data sets, scoring software, and open-source entries are available at PhysioNet for researchers interested on working on these problems.

Self-growing neural network architecture using crisp and fuzzy entropy

NASA Technical Reports Server (NTRS)

Cios, Krzysztof J.

1992-01-01

The paper briefly describes the self-growing neural network algorithm, CID3, which makes decision trees equivalent to hidden layers of a neural network. The algorithm generates a feedforward architecture using crisp and fuzzy entropy measures. The results for a real-life recognition problem of distinguishing defects in a glass ribbon, and for a benchmark problen of telling two spirals apart are shown and discussed.

Monitoring the Future: National Survey Results on Drug Use, 1975-2005. Volume I. Secondary School Students

ERIC Educational Resources Information Center

Johnston, Lloyd D.; O'Malley, Patrick M.; Bachman, Jerald G.; Schulenberg, John E.

2006-01-01

In 2005, the Monitoring the Future study marked its 31st year of conducting national surveys of substance use among American young people. Beginning with the first survey of high school seniors in 1975, the study has provided the nation with a window through which to view the important, but largely hidden, problem behaviors of illicit drug use,…

Troublesome aspects of the Renyi-MaxEnt treatment.

PubMed

Plastino, A; Rocca, M C; Pennini, F

2016-07-01

We study in great detail the possible existence of a Renyi-associated thermodynamics, with negative results. In particular, we uncover a hidden relation in Renyi's variational problem (MaxEnt). This relation connects the two associated Lagrange multipliers (canonical ensemble) with the mean energy 〈U〉 and the Renyi parameter α. As a consequence of such relation, we obtain anomalous Renyi-MaxEnt thermodynamic results.

Skin Color and Latinos: The Origins and Contemporary Patterns of Ethnoracial Ambiguity among Mexican Americans and Puerto Ricans. Report Number 1.

ERIC Educational Resources Information Center

Montalvo, Frank F.

Failure to understand the role of skin color in the development of ethnoracial identity among Hispanic Americans has led to continued psychic and educational problems for them, hidden the cause of real and potential divisiveness in the community, and prevented the development of effective strategies for overcoming ethnic prejudice. The ethnic…

Test results of smart aircraft fastener for KC-135 structural integrity

NASA Astrophysics Data System (ADS)

Schoess, Jeffrey N.; Seifert, Greg

1998-07-01

Hidden and inaccessible corrosion in aircraft structures is the number one logistics problem for the US Air Force, with an estimated maintenance cost in excess of $LR 1.0B per year in 1990-equivalent dollars. The Smart Aircraft Fastener Evaluation (SAFE) system was developed to provide early warning detection of corrosion-related symptoms in hidden locations of aircraft structures. The SAFE system incorporates an in situ measurement approach that measures and autonomously records several environmental conditions within a Hi-Lok aircraft fastener that could cause corrosion. The SAFE system integrates a miniature electrochemical microsensor array and a time-of-wetness sensor with an ultra low power 8-bit microcontroller and 4- Mbyte solid-state FLASH archival memory to measure evidence of active corrosion. A summary of the technical approach and a detailed analysis of the KC-135 lap joint test coupon results are presented.

Smart fastener for KC-135 structural integrity monitoring

NASA Astrophysics Data System (ADS)

Schoess, Jeffrey N.; Seifert, Greg

1997-06-01

Hidden and inaccessible corrosion in aircraft structures is the number-one logistics problem for the U.S. Air Force, with an estimated maintenance cost in excess of $DOL1.0 billion per year in 1990-equivalent dollars. The Smart Aircraft Fastener Evaluation (SAFE) system is being developed to provide early warning detection of corrosion- related symptoms in hidden locations of aircraft structures. The SAFE incorporates an in situ measurement approach that measures and autonomously records several environmental conditions (i.e., pH, temperature, chloride, free potential, time-of-wetness) within a Hi-Lok aircraft fastener that could cause corrosion to occur. The SAFE system integrates a miniature electrochemical microsensor array and a time-of- wetness sensor with an ultra-low-power 8-bit microcontroller and 5-Mbyte solid-state FLASH archival memory to measure the evidence of active corrosion. A summary of the technical approach, system design definition, software architecture, and future field test plans will be presented.

Passive Acoustic Leak Detection for Sodium Cooled Fast Reactors Using Hidden Markov Models

NASA Astrophysics Data System (ADS)

Marklund, A. Riber; Kishore, S.; Prakash, V.; Rajan, K. K.; Michel, F.

2016-06-01

Acoustic leak detection for steam generators of sodium fast reactors have been an active research topic since the early 1970s and several methods have been tested over the years. Inspired by its success in the field of automatic speech recognition, we here apply hidden Markov models (HMM) in combination with Gaussian mixture models (GMM) to the problem. To achieve this, we propose a new feature calculation scheme, based on the temporal evolution of the power spectral density (PSD) of the signal. Using acoustic signals recorded during steam/water injection experiments done at the Indira Gandhi Centre for Atomic Research (IGCAR), the proposed method is tested. We perform parametric studies on the HMM+GMM model size and demonstrate that the proposed method a) performs well without a priori knowledge of injection noise, b) can incorporate several noise models and c) has an output distribution that simplifies false alarm rate control.

Experimental entanglement distillation and 'hidden' non-locality.

PubMed

Kwiat, P G; Barraza-Lopez, S; Stefanov, A; Gisin, N

2001-02-22

Entangled states are central to quantum information processing, including quantum teleportation, efficient quantum computation and quantum cryptography. In general, these applications work best with pure, maximally entangled quantum states. However, owing to dissipation and decoherence, practically available states are likely to be non-maximally entangled, partially mixed (that is, not pure), or both. To counter this problem, various schemes of entanglement distillation, state purification and concentration have been proposed. Here we demonstrate experimentally the distillation of maximally entangled states from non-maximally entangled inputs. Using partial polarizers, we perform a filtering process to maximize the entanglement of pure polarization-entangled photon pairs generated by spontaneous parametric down-conversion. We have also applied our methods to initial states that are partially mixed. After filtering, the distilled states demonstrate certain non-local correlations, as evidenced by their violation of a form of Bell's inequality. Because the initial states do not have this property, they can be said to possess 'hidden' non-locality.

ECG signal analysis through hidden Markov models.

PubMed

Andreão, Rodrigo V; Dorizzi, Bernadette; Boudy, Jérôme

2006-08-01

This paper presents an original hidden Markov model (HMM) approach for online beat segmentation and classification of electrocardiograms. The HMM framework has been visited because of its ability of beat detection, segmentation and classification, highly suitable to the electrocardiogram (ECG) problem. Our approach addresses a large panel of topics some of them never studied before in other HMM related works: waveforms modeling, multichannel beat segmentation and classification, and unsupervised adaptation to the patient's ECG. The performance was evaluated on the two-channel QT database in terms of waveform segmentation precision, beat detection and classification. Our waveform segmentation results compare favorably to other systems in the literature. We also obtained high beat detection performance with sensitivity of 99.79% and a positive predictivity of 99.96%, using a test set of 59 recordings. Moreover, premature ventricular contraction beats were detected using an original classification strategy. The results obtained validate our approach for real world application.

Adaptive distributed source coding.

PubMed

Varodayan, David; Lin, Yao-Chung; Girod, Bernd

2012-05-01

We consider distributed source coding in the presence of hidden variables that parameterize the statistical dependence among sources. We derive the Slepian-Wolf bound and devise coding algorithms for a block-candidate model of this problem. The encoder sends, in addition to syndrome bits, a portion of the source to the decoder uncoded as doping bits. The decoder uses the sum-product algorithm to simultaneously recover the source symbols and the hidden statistical dependence variables. We also develop novel techniques based on density evolution (DE) to analyze the coding algorithms. We experimentally confirm that our DE analysis closely approximates practical performance. This result allows us to efficiently optimize parameters of the algorithms. In particular, we show that the system performs close to the Slepian-Wolf bound when an appropriate doping rate is selected. We then apply our coding and analysis techniques to a reduced-reference video quality monitoring system and show a bit rate saving of about 75% compared with fixed-length coding.

Noise-tolerant parity learning with one quantum bit

NASA Astrophysics Data System (ADS)

Park, Daniel K.; Rhee, June-Koo K.; Lee, Soonchil

2018-03-01

Demonstrating quantum advantage with less powerful but more realistic devices is of great importance in modern quantum information science. Recently, a significant quantum speedup was achieved in the problem of learning a hidden parity function with noise. However, if all data qubits at the query output are completely depolarized, the algorithm fails. In this work, we present a quantum parity learning algorithm that exhibits quantum advantage as long as one qubit is provided with nonzero polarization in each query. In this scenario, the quantum parity learning naturally becomes deterministic quantum computation with one qubit. Then the hidden parity function can be revealed by performing a set of operations that can be interpreted as measuring nonlocal observables on the auxiliary result qubit having nonzero polarization and each data qubit. We also discuss the source of the quantum advantage in our algorithm from the resource-theoretic point of view.

Generating a New Higher-Dimensional Coupled Integrable Dispersionless System: Algebraic Structures, Bäcklund Transformation and Hidden Structural Symmetries

NASA Astrophysics Data System (ADS)

Souleymanou, Abbagari; Thomas, B. Bouetou; Timoleon, C. Kofane

2013-08-01

The prolongation structure methodologies of Wahlquist—Estabrook [H.D. Wahlquist and F.B. Estabrook, J. Math. Phys. 16 (1975) 1] for nonlinear differential equations are applied to a more general set of coupled integrable dispersionless system. Based on the obtained prolongation structure, a Lie-Algebra valued connection of a closed ideal of exterior differential forms related to the above system is constructed. A Lie-Algebra representation of some hidden structural symmetries of the previous system, its Bäcklund transformation using the Riccati form of the linear eigenvalue problem and their general corresponding Lax-representation are derived. In the wake of the previous results, we extend the above prolongation scheme to higher-dimensional systems from which a new (2 + 1)-dimensional coupled integrable dispersionless system is unveiled along with its inverse scattering formulation, which applications are straightforward in nonlinear optics where additional propagating dimension deserves some attention.

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

PubMed

Zhou, Shusen; Chen, Qingcai; Wang, Xiaolong

2014-01-01

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

Hidden reentrant and Larkin-Ovchinnikov-Fulde-Ferrell superconducting phases in a magnetic field in a (TMTSF)2ClO4.

PubMed

Lebed, A G

2011-08-19

We solve a long-standing problem about a theoretical description of the upper critical magnetic field, parallel to conducting layers and perpendicular to conducting chains, in a (TMTSF)(2)ClO(4) superconductor. In particular, we explain why the experimental upper critical field, H(c2)(b')≃6 T, is higher than both the quasiclassical upper critical field and the Clogston paramagnetic limit. We show that this property is due to the coexistence of the hidden reentrant and Larkin-Ovchinnikov-Fulde-Ferrell phases in a magnetic field in the form of three plane waves with nonzero momenta of the Cooper pairs. Our results are in good qualitative and quantitative agreement with the recent experimental measurements of H(c2)(b') and support a singlet d-wave-like scenario of superconductivity in (TMTSF)(2)ClO(4). © 2011 American Physical Society

Analysis of Accuracy and Epoch on Back-propagation BFGS Quasi-Newton

NASA Astrophysics Data System (ADS)

Silaban, Herlan; Zarlis, Muhammad; Sawaluddin

2017-12-01

Back-propagation is one of the learning algorithms on artificial neural networks that have been widely used to solve various problems, such as pattern recognition, prediction and classification. The Back-propagation architecture will affect the outcome of learning processed. BFGS Quasi-Newton is one of the functions that can be used to change the weight of back-propagation. This research tested some back-propagation architectures using classical back-propagation and back-propagation with BFGS. There are 7 architectures that have been tested on glass dataset with various numbers of neurons, 6 architectures with 1 hidden layer and 1 architecture with 2 hidden layers. BP with BFGS improves the convergence of the learning process. The average improvement convergence is 98.34%. BP with BFGS is more optimal on architectures with smaller number of neurons with decreased epoch number is 94.37% with the increase of accuracy about 0.5%.

How should we question young children's understanding of aspectuality?

PubMed

Waters, Gillian M; Beck, Sarah R

2012-09-01

In two experiments, we investigated whether 4- to 5-year-old children's ability to demonstrate their understanding of aspectuality was influenced by how the test question was phrased. In Experiment 1, 60 children chose whether to look or feel to gain information about a hidden object (identifiable by sight or touch). Test questions referred either to the perceptual aspect of the hidden object (e.g., whether it was red or blue), the modality dimension (e.g., what colour it was), or the object's identity (e.g., which one it was). Children who heard the identity question performed worse than those who heard the aspect or dimension question. Further investigation in Experiment 2 (N= 23) established that children's difficulty with the identity question was not due to a problem recalling the objects. We discuss how the results of these methodological investigations impact on researchers' assessment of the development of aspectuality understanding. ©2011 The British Psychological Society.

[Geriatric assessment. Development, status quo and perspectives].

PubMed

Lüttje, D; Varwig, D; Teigel, B; Gilhaus, B

2011-08-01

Multimorbidity is typical for geriatric patients. Problems not identified in time may lead to increased hospitalisation or prolonged hospital stay. Problems of multimorbidity are not covered by most guidelines or clinical pathways. The geriatric assessment supports standard clinical and technical assessment. Geriatric identification screening is basic for general practitioners and in emergency rooms to filter those patients bearing a special risk. Geriatric basic assessment covers most of the problems relevant for people in old age, revealing even problems that had so far been hidden. It permits to structure a comprehensive and holistic therapeutic approach and to evaluate the targets of treatment relevant for independent living and well-being. This results in reduction of morbidity and mortality. Assessment tools focusing on pain, nutrition and frailty should be added to the standardized geriatric basic assessment in Germany.

Prospects for mirage mediation

NASA Astrophysics Data System (ADS)

Pierce, Aaron; Thaler, Jesse

2006-09-01

Mirage mediation reduces the fine-tuning in the minimal supersymmetric standard model by dynamically arranging a cancellation between anomaly-mediated and modulus-mediated supersymmetry breaking. We explore the conditions under which a mirage ``messenger scale'' is generated near the weak scale and the little hierarchy problem is solved. We do this by explicitly including the dynamics of the SUSY-breaking sector needed to cancel the cosmological constant. The most plausible scenario for generating a low mirage scale does not readily admit an extra-dimensional interpretation. We also review the possibilities for solving the μ/Bμ problem in such theories, a potential hidden source of fine-tuning.

On Bayesian methods of exploring qualitative interactions for targeted treatment.

PubMed

Chen, Wei; Ghosh, Debashis; Raghunathan, Trivellore E; Norkin, Maxim; Sargent, Daniel J; Bepler, Gerold

2012-12-10

Providing personalized treatments designed to maximize benefits and minimizing harms is of tremendous current medical interest. One problem in this area is the evaluation of the interaction between the treatment and other predictor variables. Treatment effects in subgroups having the same direction but different magnitudes are called quantitative interactions, whereas those having opposite directions in subgroups are called qualitative interactions (QIs). Identifying QIs is challenging because they are rare and usually unknown among many potential biomarkers. Meanwhile, subgroup analysis reduces the power of hypothesis testing and multiple subgroup analyses inflate the type I error rate. We propose a new Bayesian approach to search for QI in a multiple regression setting with adaptive decision rules. We consider various regression models for the outcome. We illustrate this method in two examples of phase III clinical trials. The algorithm is straightforward and easy to implement using existing software packages. We provide a sample code in Appendix A. Copyright © 2012 John Wiley & Sons, Ltd.

Structure preserving clustering-object tracking via subgroup motion pattern segmentation

NASA Astrophysics Data System (ADS)

Fan, Zheyi; Zhu, Yixuan; Jiang, Jiao; Weng, Shuqin; Liu, Zhiwen

2018-01-01

Tracking clustering objects with similar appearances simultaneously in collective scenes is a challenging task in the field of collective motion analysis. Recent work on clustering-object tracking often suffers from poor tracking accuracy and terrible real-time performance due to the neglect or the misjudgment of the motion differences among objects. To address this problem, we propose a subgroup motion pattern segmentation framework based on a multilayer clustering structure and establish spatial constraints only among objects in the same subgroup, which entails having consistent motion direction and close spatial position. In addition, the subgroup segmentation results are updated dynamically because crowd motion patterns are changeable and affected by objects' destinations and scene structures. The spatial structure information combined with the appearance similarity information is used in the structure preserving object tracking framework to track objects. Extensive experiments conducted on several datasets containing multiple real-world crowd scenes validate the accuracy and the robustness of the presented algorithm for tracking objects in collective scenes.

Towards Detection of Learner Misconceptions in a Medical Learning Environment: A Subgroup Discovery Approach

ERIC Educational Resources Information Center

Poitras, Eric G.; Doleck, Tenzin; Lajoie, Susanne P.

2018-01-01

Ill-structured problems, by definition, have multiple paths to a solution and are multifaceted making automated assessment and feedback a difficult challenge. Diagnostic reasoning about medical cases meet the criteria of ill-structured problem solving since there are multiple solution paths. The goal of this study was to develop an adaptive…

Revisiting Data Related to the Age of Onset and Developmental Course of Female Conduct Problems

ERIC Educational Resources Information Center

Brennan, Lauretta M.; Shaw, Daniel S.

2013-01-01

Children who exhibit persistently elevated levels of conduct problems (CP) from early childhood, so-called early-starters, are known to be at increased risk for continued CP throughout middle childhood, adolescence, and adulthood. Theoretical and empirical work has focused on this subgroup of children characterized by similar risk factors, an…

The Structure of Problem Behavior in a Sample of Maltreated Youths

ERIC Educational Resources Information Center

Culhane, Sara E.; Taussig, Heather N.

2009-01-01

Studies of adolescent community samples suggest that substance use, risky sexual behavior, delinquency, and other problem behaviors can be explained in part by a single, underlying factor or syndrome. Of current interest is the generalizability of these findings to subgroups or special populations of youths who may be at high risk for problem…

Cognitive and mathematical profiles for different forms of learning difficulties.

PubMed

Cirino, Paul T; Fuchs, Lynn S; Elias, John T; Powell, Sarah R; Schumacher, Robin F

2015-01-01

The purpose of this study was to compare subgroups of students with various forms of learning difficulties (< 25th percentile) on cognitive and mathematics characteristics. Students with mathematics difficulty (MD, n = 105), reading difficulty (RD, n = 65), both (MDRD, n = 87), or neither (NoLD, n = 403) were evaluated on an array of cognitive measures (e.g., working memory and language) and on mathematics measures of foundational numerical competencies, computation, and problem solving. Results revealed expected level differences among groups in both domains: NoLD outperformed RD, and MD outperformed MDRD. Profile differences were noted among pairs of subgroups on cognitive measures. On mathematics measures, profile differences were noted between RD and other subgroups, but not between MD and MDRD subgroups. The most discriminating cognitive measures were processing speed and language; the most discriminating mathematics measures depended on the subgroups being compared. Results were further evaluated according to more severe (< 10th percentile) criteria for MD and RD, which generally affected level differences more than the profile patterns. Results have implications for understanding comorbid MD and RD and for conceptualizing core deficits in MD. © Hammill Institute on Disabilities 2013.

Phylogenetic analysis at deep timescales: unreliable gene trees, bypassed hidden support, and the coalescence/concatalescence conundrum.

PubMed

Gatesy, John; Springer, Mark S

2014-11-01

Large datasets are required to solve difficult phylogenetic problems that are deep in the Tree of Life. Currently, two divergent systematic methods are commonly applied to such datasets: the traditional supermatrix approach (= concatenation) and "shortcut" coalescence (= coalescence methods wherein gene trees and the species tree are not co-estimated). When applied to ancient clades, these contrasting frameworks often produce congruent results, but in recent phylogenetic analyses of Placentalia (placental mammals), this is not the case. A recent series of papers has alternatively disputed and defended the utility of shortcut coalescence methods at deep phylogenetic scales. Here, we examine this exchange in the context of published phylogenomic data from Mammalia; in particular we explore two critical issues - the delimitation of data partitions ("genes") in coalescence analysis and hidden support that emerges with the combination of such partitions in phylogenetic studies. Hidden support - increased support for a clade in combined analysis of all data partitions relative to the support evident in separate analyses of the various data partitions, is a hallmark of the supermatrix approach and a primary rationale for concatenating all characters into a single matrix. In the most extreme cases of hidden support, relationships that are contradicted by all gene trees are supported when all of the genes are analyzed together. A valid fear is that shortcut coalescence methods might bypass or distort character support that is hidden in individual loci because small gene fragments are analyzed in isolation. Given the extensive systematic database for Mammalia, the assumptions and applicability of shortcut coalescence methods can be assessed with rigor to complement a small but growing body of simulation work that has directly compared these methods to concatenation. We document several remarkable cases of hidden support in both supermatrix and coalescence paradigms and argue that in most instances, the emergent support in the shortcut coalescence analyses is an artifact. By referencing rigorous molecular clock studies of Mammalia, we suggest that inaccurate gene trees that imply unrealistically deep coalescences debilitate shortcut coalescence analyses of the placental dataset. We document contradictory coalescence results for Placentalia, and outline a critical conundrum that challenges the general utility of shortcut coalescence methods at deep phylogenetic scales. In particular, the basic unit of analysis in coalescence analysis, the coalescence-gene, is expected to shrink in size as more taxa are analyzed, but as the amount of data for reconstruction of a gene tree ratchets downward, the number of nodes in the gene tree that need to be resolved ratchets upward. Some advocates of shortcut coalescence methods have attempted to address problems with inaccurate gene trees by concatenating multiple coalescence-genes to yield "gene trees" that better match the species tree. However, this hybrid concatenation/coalescence approach, "concatalescence," contradicts the most basic biological rationale for performing a coalescence analysis in the first place. We discuss this reality in the context of recent simulation work that also suggests inaccurate reconstruction of gene trees is more problematic for shortcut coalescence methods than deep coalescence of independently segregating loci is for concatenation methods. Copyright © 2014 Elsevier Inc. All rights reserved.

A multi-group firefly algorithm for numerical optimization

NASA Astrophysics Data System (ADS)

Tong, Nan; Fu, Qiang; Zhong, Caiming; Wang, Pengjun

2017-08-01

To solve the problem of premature convergence of firefly algorithm (FA), this paper analyzes the evolution mechanism of the algorithm, and proposes an improved Firefly algorithm based on modified evolution model and multi-group learning mechanism (IMGFA). A Firefly colony is divided into several subgroups with different model parameters. Within each subgroup, the optimal firefly is responsible for leading the others fireflies to implement the early global evolution, and establish the information mutual system among the fireflies. And then, each firefly achieves local search by following the brighter firefly in its neighbors. At the same time, learning mechanism among the best fireflies in various subgroups to exchange information can help the population to obtain global optimization goals more effectively. Experimental results verify the effectiveness of the proposed algorithm.

Efficient free energy calculations by combining two complementary tempering sampling methods.

PubMed

Xie, Liangxu; Shen, Lin; Chen, Zhe-Ning; Yang, Mingjun

2017-01-14

Although energy barriers can be efficiently crossed in the reaction coordinate (RC) guided sampling, this type of method suffers from identification of the correct RCs or requirements of high dimensionality of the defined RCs for a given system. If only the approximate RCs with significant barriers are used in the simulations, hidden energy barriers with small to medium height would exist in other degrees of freedom (DOFs) relevant to the target process and consequently cause the problem of insufficient sampling. To address the sampling in this so-called hidden barrier situation, here we propose an effective approach to combine temperature accelerated molecular dynamics (TAMD), an efficient RC-guided sampling method, with the integrated tempering sampling (ITS), a generalized ensemble sampling method. In this combined ITS-TAMD method, the sampling along the major RCs with high energy barriers is guided by TAMD and the sampling of the rest of the DOFs with lower but not negligible barriers is enhanced by ITS. The performance of ITS-TAMD to three systems in the processes with hidden barriers has been examined. In comparison to the standalone TAMD or ITS approach, the present hybrid method shows three main improvements. (1) Sampling efficiency can be improved at least five times even if in the presence of hidden energy barriers. (2) The canonical distribution can be more accurately recovered, from which the thermodynamic properties along other collective variables can be computed correctly. (3) The robustness of the selection of major RCs suggests that the dimensionality of necessary RCs can be reduced. Our work shows more potential applications of the ITS-TAMD method as the efficient and powerful tool for the investigation of a broad range of interesting cases.

Efficient free energy calculations by combining two complementary tempering sampling methods

NASA Astrophysics Data System (ADS)

Xie, Liangxu; Shen, Lin; Chen, Zhe-Ning; Yang, Mingjun

2017-01-01

Although energy barriers can be efficiently crossed in the reaction coordinate (RC) guided sampling, this type of method suffers from identification of the correct RCs or requirements of high dimensionality of the defined RCs for a given system. If only the approximate RCs with significant barriers are used in the simulations, hidden energy barriers with small to medium height would exist in other degrees of freedom (DOFs) relevant to the target process and consequently cause the problem of insufficient sampling. To address the sampling in this so-called hidden barrier situation, here we propose an effective approach to combine temperature accelerated molecular dynamics (TAMD), an efficient RC-guided sampling method, with the integrated tempering sampling (ITS), a generalized ensemble sampling method. In this combined ITS-TAMD method, the sampling along the major RCs with high energy barriers is guided by TAMD and the sampling of the rest of the DOFs with lower but not negligible barriers is enhanced by ITS. The performance of ITS-TAMD to three systems in the processes with hidden barriers has been examined. In comparison to the standalone TAMD or ITS approach, the present hybrid method shows three main improvements. (1) Sampling efficiency can be improved at least five times even if in the presence of hidden energy barriers. (2) The canonical distribution can be more accurately recovered, from which the thermodynamic properties along other collective variables can be computed correctly. (3) The robustness of the selection of major RCs suggests that the dimensionality of necessary RCs can be reduced. Our work shows more potential applications of the ITS-TAMD method as the efficient and powerful tool for the investigation of a broad range of interesting cases.

The hidden costs of coastal hazards: Implications for risk assessment and mitigation

USGS Publications Warehouse

Kunreuther, H.; Platt, R.; Baruch, S.; Bernknopf, R.L.; Buckley, M.; Burkett, V.; Conrad, D.; Davidson, T.; Deutsch, K.; Geis, D.; Jannereth, M.; Knap, A.; Lane, H.; Ljung, G.; McCauley, M.; Mileti, D.; Miller, T.; Morrow, B.; Meyers, J.; Pielke, R.; Pratt, A.; Tripp, J.

2000-01-01

Society has limited hazard mitigation dollars to invest. Which actions will be most cost effective, considering the true range of impacts and costs incurred? In 1997, the H. John Heinz III Center for Science, Economics and the Environment began a two-year study with a panel of experts to help develop new strategies to identify and reduce the costs of weather-related hazards associated with rapidly increasing coastal development activities.The Hidden Costs of Coastal Hazards presents the panel's findings, offering the first in-depth study that considers the costs of coastal hazards to natural resources, social institutions, business, and the built environment. Using Hurricane Hugo, which struck South Carolina in 1989, as a case study, it provides for the first time information on the full range of economic costs caused by a major coastal hazard event. The book:describes and examines unreported, undocumented, and hidden costs such as losses due to business interruption, reduction in property values, interruption of social services, psychological trauma, damage to natural systems, and othersexamines the concepts of risk and vulnerability, and discusses conventional approaches to risk assessment and the emerging area of vulnerability assessmentrecommends a comprehensive framework for developing and implementing mitigation strategiesdocuments the human impact of Hurricane Hugo and provides insight from those who lived through it.The Hidden Costs of Coastal Hazards takes a structured approach to the problem of coastal hazards, offering a new framework for community-based hazard mitigation along with specific recommendations for implementation. Decisionmakers -- both policymakers and planners -- who are interested in coastal hazard issues will find the book a unique source of new information and insight, as will private-sector decisionmakers including lenders, investors, developers, and insurers of coastal property.

The sociocommunicative deficit subgroup in anorexia nervosa: autism spectrum disorders and neurocognition in a community-based, longitudinal study

PubMed Central

Anckarsäter, H.; Hofvander, B.; Billstedt, E.; Gillberg, I. C.; Gillberg, C.; Wentz, E.; Råstam, M.

2012-01-01

Background A subgroup of persons with anorexia nervosa (AN) have been proposed to have sociocommunicative problems corresponding to autism spectrum disorders [ASDs, i.e. DSM-IV pervasive developmental disorders (PDDs): autistic disorder, Asperger's disorder, PDD not otherwise specified (NOS)]. Here, clinical problems, personality traits, cognitive test results and outcome are compared across 16 subjects (32%) with teenage-onset AN who meet or have met ASD criteria (AN+ASD), 34 ASD-negative AN subjects and matched controls from a longitudinal Swedish study including four waves of independent assessments from the teens to the early thirties. Method The fourth wave included the Structured Clinical Interview for DSM-IV (SCID)-I and the SCID-II (cluster C, i.e. ‘anxious’ PDs) interviews, the Asperger Syndrome Diagnostic Interview, self-assessments by the Autism Spectrum Quotient and the Temperament and Character Inventory, neurocognitive tests by subscales from the Wechsler scales, continuous performance tests, Tower of London, and Happé's cartoons. Results The ASD assessments had substantial inter-rater reliability over time (Cohen's κ between 0.70 and 0.80 with previous assessments), even if only six subjects had been assigned a diagnosis of an ASD in all four waves of the study, including retrospective assessments of pre-AN neurodevelopmental problems. The AN+ASD group had the highest prevalence of personality disorders and the lowest Morgan–Russell scores. The non-ASD AN group also differed significantly from controls on personality traits related to poor interpersonal functioning and on neurocognitive tests. Conclusions A subgroup of subjects with AN meet criteria for ASDs. They may represent the extreme of neurocognitive and personality problems to be found more generally in AN. PMID:22186945

Intersections of discrimination due to unemployment and mental health problems: the role of double stigma for job- and help-seeking behaviors.

PubMed

Staiger, Tobias; Waldmann, Tamara; Oexle, Nathalie; Wigand, Moritz; Rüsch, Nicolas

2018-05-21

The everyday lives of unemployed people with mental health problems can be affected by multiple discrimination, but studies about double stigma-an overlap of identities and experiences of discrimination-in this group are lacking. We therefore studied multiple discrimination among unemployed people with mental health problems and its consequences for job- and help-seeking behaviors. Everyday discrimination and attributions of discrimination to unemployment and/or to mental health problems were examined among 301 unemployed individuals with mental health problems. Job search self-efficacy, barriers to care, and perceived need for treatment were compared among four subgroups, depending on attributions of experienced discrimination to unemployment and to mental health problems (group i); neither to unemployment nor to mental health problems (group ii); mainly to unemployment (group iii); or mainly to mental health problems (group iv). In multiple regressions among all participants, higher levels of discrimination predicted reduced job search self-efficacy and higher barriers to care; and attributions of discrimination to unemployment were associated with increased barriers to care. In ANOVAs for subgroup comparisons, group i participants, who attributed discrimination to both unemployment and mental health problems, reported lower job search self-efficacy, more perceived stigma-related barriers to care and more need for treatment than group iii participants, as well as more stigma-related barriers to care than group iv. Multiple discrimination may affect job search and help-seeking among unemployed individuals with mental health problems. Interventions to reduce public stigma and to improve coping with multiple discrimination for this group should be developed.

The effect of food environments on fruit and vegetable intake as modified by time spent at home: a cross-sectional study

PubMed Central

Chum, Antony; Farrell, Eddie; Vaivada, Tyler; Labetski, Anna; Selvaratnam, Inthuja; Larsen, Kristian; Pinter, Theresa; O'Campo, Patricia

2015-01-01

Objective There is a growing body of research that investigates how the residential neighbourhood context relates to individual diet. However, previous studies ignore participants’ time spent in the residential environment and this may be a problem because time-use studies show that adults’ time-use pattern can significantly vary. To better understand the role of exposure duration, we designed a study to examine ‘time spent at home’ as a moderator to the residential food environment-diet association. Design Cross-sectional observational study. Settings City of Toronto, Ontario, Canada. Participants 2411 adults aged 25–65. Primary outcome measure Frequency of vegetable and fruit intake (VFI) per day. Results To examine how time spent at home may moderate the relationship between residential food environment and VFI, the full sample was split into three equal subgroups—short, medium and long duration spent at home. We detected significant associations between density of food stores in the residential food environment and VFI for subgroups that spend medium and long durations at home (ie, spending a mean of 8.0 and 12.3 h at home, respectively—not including sleep time), but no associations exist for people who spend the lowest amount of time at home (mean=4.7 h). Also, no associations were detected in analyses using the full sample. Conclusions Our study is the first to demonstrate that time spent at home may be an important variable to identify hidden population patterns regarding VFI. Time spent at home can impact the association between the residential food environment and individual VFI. PMID:26044756

Improving Support for America's Hidden Heroes

PubMed Central

Terri, Tanielian; Kathryn E., Bouskill; Rajeev, Ramchand; Esther M., Friedman; Thomas E., Trail; Angela, Clague

2018-01-01

Abstract The United States is home to more than 21 million veterans, many of whom deployed to support combat operations around the globe during their military service and sustained service-related conditions or disabilities. Supporting these wounded, ill, and injured warriors once home are millions of informal caregivers—individuals who provide unpaid support with activities that enable the service member or veteran to live in a noninstitutionalized setting. In this study, researchers describe elements of a research blueprint to inform future efforts to improve support for military and veteran caregivers. To construct this blueprint, researchers inventoried currently available research on caregiving for disabled adults and children and gathered stakeholder input by conducting a survey and facilitating an online panel. The study highlights the need for more studies that examine how military and veteran caregiver needs evolve over time, how programs are working, and how caregiving affects specific subgroups. The resulting blueprint should serve as a guide for the caregiver support community to use in prioritizing and facilitating future research. PMID:29416949

Improving Support for America's Hidden Heroes: A Research Blueprint.

PubMed

Terri, Tanielian; Kathryn E, Bouskill; Rajeev, Ramchand; Esther M, Friedman; Thomas E, Trail; Angela, Clague

2018-01-01

The United States is home to more than 21 million veterans, many of whom deployed to support combat operations around the globe during their military service and sustained service-related conditions or disabilities. Supporting these wounded, ill, and injured warriors once home are millions of informal caregivers-individuals who provide unpaid support with activities that enable the service member or veteran to live in a noninstitutionalized setting. In this study, researchers describe elements of a research blueprint to inform future efforts to improve support for military and veteran caregivers. To construct this blueprint, researchers inventoried currently available research on caregiving for disabled adults and children and gathered stakeholder input by conducting a survey and facilitating an online panel. The study highlights the need for more studies that examine how military and veteran caregiver needs evolve over time, how programs are working, and how caregiving affects specific subgroups. The resulting blueprint should serve as a guide for the caregiver support community to use in prioritizing and facilitating future research.

Perceived unmet need and barriers to care amongst street-involved people who use illicit drugs.

PubMed

Hyshka, Elaine; Anderson, Jalene Tayler; Wild, T Cameron

2017-05-01

Research on perceived unmet need for care for mental health and substance use problems focuses on general populations to the detriment of hidden populations. This study describes prevalence and correlates of perceived unmet need for care in a community-based sample of street-involved people who use illicit drugs and identifies barriers to care. A sample of 320 street-involved people who use drugs participated in a structured, interviewer-assisted survey in Edmonton, Canada. The survey included the Perceived Need for Care Questionnaire, which assessed unmet need for care for mental health and substance use problems across seven service types. Logistic regression examined the associations between perceived unmet need, extent of socioeconomic marginalisation and problem severity. Barriers underlying unmet service needs were also examined. Most (82%) participants reported unmet need for one or more services during the past year. Odds of reporting one or more unmet needs were elevated amongst participants reporting substantial housing instability (adjusted odds ratio = 2.37; 95% confidence interval 1.19-4.28) and amongst participants meeting criteria for drug dependence (adjusted odds ratio = 1.22; 95% confidence interval 1.03-1.50), even after adjustment for sociodemographic covariates. Structural, rather than motivational barriers were the most commonly reported reasons underlying unmet service needs. Street-involved people who use drugs experience very high rates of perceived unmet need for care for mental health and substance use problems. General population studies on perceived unmet need are insufficient for understanding needs and barriers to care in hidden populations.[Hyshka E, Anderson JT, Wild TC. Perceived unmet need and barriers to care amongst street-involved people who use illicit drugs. Drug Alcohol Rev 2017;36:295-304]. © 2016 Australasian Professional Society on Alcohol and other Drugs.

Context Analysis of Customer Requests using a Hybrid Adaptive Neuro Fuzzy Inference System and Hidden Markov Models in the Natural Language Call Routing Problem

NASA Astrophysics Data System (ADS)

Rustamov, Samir; Mustafayev, Elshan; Clements, Mark A.

2018-04-01

The context analysis of customer requests in a natural language call routing problem is investigated in the paper. One of the most significant problems in natural language call routing is a comprehension of client request. With the aim of finding a solution to this issue, the Hybrid HMM and ANFIS models become a subject to an examination. Combining different types of models (ANFIS and HMM) can prevent misunderstanding by the system for identification of user intention in dialogue system. Based on these models, the hybrid system may be employed in various language and call routing domains due to nonusage of lexical or syntactic analysis in classification process.

Committee opinion no. 507: human trafficking.

PubMed

2011-09-01

Human trafficking is a widespread problem with estimates ranging from 14,000 to 50,000 individuals trafficked into the United States annually. This hidden population involves the commercial sex industry, agriculture, factories, hotel and restaurant businesses, domestic workers, marriage brokers, and some adoption firms. Because 80% of trafficked individuals are women and girls, women’s health care providers may better serve their diverse patient population by increasing their awareness of this problem. The exploitation of people of any race, gender, sexual orientation, or ethnicity is unacceptable at any time, in any place. The members of the American College of Obstetricians and Gynecologists should be aware of this problem and strive to recognize and assist their patients who are victims or who have been victims of human trafficking.

Total Quality Management: A Guide to Implementation

DTIC Science & Technology

1989-08-01

Kaizen. New York: Random House. 1986. Ishikawa , Kaoru . Guide to Quality Control. Asian Productivity Organization. 1984. Ishikawa , Kaoru . What is Total...with the problems and the new management principles are based on the complexities of the new Systems Age. The theories of Deming, Juran, Ishikawa , and...Progress. Jun 1985. Miller, Jeffery G. and Thomas E. Vollmann. "The Hidden Factory." Harvard Business Review. Sep-Oct 1985. Shimoyamada, Kaoru . "The

Monitoring the Future: National Survey Results on Drug Use, 1975-2009. Volume I: Secondary School Students. NIH Publication No. 10-7584

ERIC Educational Resources Information Center

Johnston, Lloyd D.; O'Malley, Patrick M.; Bachman, Jerald G.; Schulenberg, John E.

2010-01-01

The Monitoring the Future (MTF) study is an ongoing series of national surveys of American adolescents and adults that has provided the nation with a vital window into the important, but largely hidden, problem behaviors of illegal drug use, alcohol use, tobacco use, anabolic steroid use, and psychotherapeutic drug use. For more than a third of…

Proposed Test of Relative Phase as Hidden Variable in Quantum Mechanics

DTIC Science & Technology

2012-01-01

implicitly due to its ubiquity in quantum theory , but searches for dependence of measurement outcome on other parameters have been lacking. For a two -state...implemen- tation for the specific case of an atomic two -state system with laser-induced fluores- cence for measurement. Keywords Quantum measurement...Measurement postulate · Born rule 1 Introduction 1.1 Problems with Quantum Measurement Quantum theory prescribes probabilities for outcomes of measurements

Lymphogranuloma venereum: a hidden emerging problem, Barcelona, 2011.

PubMed

Vargas-Leguas, H; Garcia de Olalla, P; Arando, M; Armengol, P; Barbera, Mj; Vall, M; Vives, A; Martin-Ezquerra, G; Alsina, M; Blanco, J; Munoz, C; Caballero, E; Andreu, A; Ros, M; Gorrindo, P; Dominguez, A; Cayla, Ja

2012-01-12

From the beginning of 2007 until the end of 2011, 146 cases of lymphogranuloma venereum (LGV) were notified to the Barcelona Public Health Agency. Some 49% of them were diagnosed and reported in 2011, mainly in men who have sex with men. Almost half of them, 32 cases, were reported between July and September. This cluster represents the largest since 2004. This article presents the ongoing outbreak of LGV in Barcelona.

Monitoring the Future: National Survey Results on Drug Use, 1975-2004. Volume I: Secondary School Students, 2004

ERIC Educational Resources Information Center

Johnston, Lloyd D.; O'Malley, Patrick M.; Bachman, Jerald G.; Schulenberg, John E.

2005-01-01

In 2004 the Monitoring the Future study marked its 30th year of conducting national surveys of substance use among American young people. Beginning with the first survey of high school seniors in 1975, the study has provided the nation with a window through which to view the important, but largely hidden, problem behaviors of illicit drug use,…

Hidden Realities inside PBL Design Processes: Is Consensus Design an Impossible Clash of Interest between the Individual and the Collective, and Is Architecture Its First Victim?

ERIC Educational Resources Information Center

Pihl, Ole

2015-01-01

How do architecture students experience the contradictions between the individual and the group at the Department of Architecture and Design of Aalborg University? The Problem-Based Learning model has been extensively applied to the department's degree programs in coherence with the Integrated Design Process, but is a group-based architecture and…

Attentional Selection in Object Recognition

DTIC Science & Technology

1993-02-01

order. It also affects the choice of strategies in both the 24 A Computational Model of Attentional Selection filtering and arbiter stages. The set...such processing. In Treisman’s model this was hidden in the concept of the selection filter . Later computational models of attention tried to...This thesis presents a novel approach to the selection problem by propos. ing a computational model of visual attentional selection as a paradigm for

Monitoring the Future. National Survey Results on Drug Use, 1975-2009. Volume I, Secondary School Students. NIH Publication Number 10-7584

ERIC Educational Resources Information Center

Johnston, Lloyd D.; O'Malley, Patrick M.; Bachman, Jerald G.; Schulenberg, John E.

2010-01-01

The Monitoring the Future (MTF) study is an ongoing series of national surveys of American adolescents and adults that has provided the nation with a vital window into the important, but largely hidden, problem behaviors of illegal drug use, alcohol use, tobacco use, anabolic steroid use, and psychotherapeutic drug use. For more than a third of a…

Working memory, worry, and algebraic ability.

PubMed

Trezise, Kelly; Reeve, Robert A

2014-05-01

Math anxiety (MA)-working memory (WM) relationships have typically been examined in the context of arithmetic problem solving, and little research has examined the relationship in other math domains (e.g., algebra). Moreover, researchers have tended to examine MA/worry separate from math problem solving activities and have used general WM tasks rather than domain-relevant WM measures. Furthermore, it seems to have been assumed that MA affects all areas of math. It is possible, however, that MA is restricted to particular math domains. To examine these issues, the current research assessed claims about the impact on algebraic problem solving of differences in WM and algebraic worry. A sample of 80 14-year-old female students completed algebraic worry, algebraic WM, algebraic problem solving, nonverbal IQ, and general math ability tasks. Latent profile analysis of worry and WM measures identified four performance profiles (subgroups) that differed in worry level and WM capacity. Consistent with expectations, subgroup membership was associated with algebraic problem solving performance: high WM/low worry>moderate WM/low worry=moderate WM/high worry>low WM/high worry. Findings are discussed in terms of the conceptual relationship between emotion and cognition in mathematics and implications for the MA-WM-performance relationship. Copyright © 2013 Elsevier Inc. All rights reserved.

Search protocols for hidden forensic objects beneath floors and within walls.

PubMed

Ruffell, Alastair; Pringle, Jamie K; Forbes, Shari

2014-04-01

The burial of objects (human remains, explosives, weapons) below or behind concrete, brick, plaster or tiling may be associated with serious crime and are difficult locations to search. These are quite common forensic search scenarios but little has been published on them to-date. Most documented discoveries are accidental or from suspect/witness testimony. The problem in locating such hidden objects means a random or chance-based approach is not advisable. A preliminary strategy is presented here, based on previous studies, augmented by primary research where new technology or applications are required. This blend allows a rudimentary search workflow, from remote desktop study, to non-destructive investigation through to recommendations as to how the above may inform excavation, demonstrated here with a case study from a homicide investigation. Published case studies on the search for human remains demonstrate the problems encountered when trying to find and recover sealed-in and sealed-over locations. Established methods include desktop study, photography, geophysics and search dogs: these are integrated with new technology (LiDAR and laser scanning; photographic rectification; close-quarter aerial imagery; ground-penetrating radar on walls and gamma-ray/neutron activation radiography) to propose this possible search strategy. Copyright © 2014 Elsevier Ireland Ltd. All rights reserved.

Binary space partitioning trees and their uses

NASA Technical Reports Server (NTRS)

Bell, Bradley N.

1989-01-01

Binary Space Partitioning (BSP) trees have some qualities that make them useful in solving many graphics related problems. The purpose is to describe what a BSP tree is, and how it can be used to solve the problem of hidden surface removal, and constructive solid geometry. The BSP tree is based on the idea that a plane acting as a divider subdivides space into two parts with one being on the positive side and the other on the negative. A polygonal solid is then represented as the volume defined by the collective interior half spaces of the solid's bounding surfaces. The nature of how the tree is organized lends itself well for sorting polygons relative to an arbitrary point in 3 space. The speed at which the tree can be traversed for depth sorting is fast enough to provide hidden surface removal at interactive speeds. The fact that a BSP tree actually represents a polygonal solid as a bounded volume also makes it quite useful in performing the boolean operations used in constructive solid geometry. Due to the nature of the BSP tree, polygons can be classified as they are subdivided. The ability to classify polygons as they are subdivided can enhance the simplicity of implementing constructive solid geometry.

Nonlinear inversion of electrical resistivity imaging using pruning Bayesian neural networks

NASA Astrophysics Data System (ADS)

Jiang, Fei-Bo; Dai, Qian-Wei; Dong, Li

2016-06-01

Conventional artificial neural networks used to solve electrical resistivity imaging (ERI) inversion problem suffer from overfitting and local minima. To solve these problems, we propose to use a pruning Bayesian neural network (PBNN) nonlinear inversion method and a sample design method based on the K-medoids clustering algorithm. In the sample design method, the training samples of the neural network are designed according to the prior information provided by the K-medoids clustering results; thus, the training process of the neural network is well guided. The proposed PBNN, based on Bayesian regularization, is used to select the hidden layer structure by assessing the effect of each hidden neuron to the inversion results. Then, the hyperparameter α k , which is based on the generalized mean, is chosen to guide the pruning process according to the prior distribution of the training samples under the small-sample condition. The proposed algorithm is more efficient than other common adaptive regularization methods in geophysics. The inversion of synthetic data and field data suggests that the proposed method suppresses the noise in the neural network training stage and enhances the generalization. The inversion results with the proposed method are better than those of the BPNN, RBFNN, and RRBFNN inversion methods as well as the conventional least squares inversion.

Adaptive Online Sequential ELM for Concept Drift Tackling

PubMed Central

Basaruddin, Chan

2016-01-01

A machine learning method needs to adapt to over time changes in the environment. Such changes are known as concept drift. In this paper, we propose concept drift tackling method as an enhancement of Online Sequential Extreme Learning Machine (OS-ELM) and Constructive Enhancement OS-ELM (CEOS-ELM) by adding adaptive capability for classification and regression problem. The scheme is named as adaptive OS-ELM (AOS-ELM). It is a single classifier scheme that works well to handle real drift, virtual drift, and hybrid drift. The AOS-ELM also works well for sudden drift and recurrent context change type. The scheme is a simple unified method implemented in simple lines of code. We evaluated AOS-ELM on regression and classification problem by using concept drift public data set (SEA and STAGGER) and other public data sets such as MNIST, USPS, and IDS. Experiments show that our method gives higher kappa value compared to the multiclassifier ELM ensemble. Even though AOS-ELM in practice does not need hidden nodes increase, we address some issues related to the increasing of the hidden nodes such as error condition and rank values. We propose taking the rank of the pseudoinverse matrix as an indicator parameter to detect “underfitting” condition. PMID:27594879

Robust Hidden Markov Model based intelligent blood vessel detection of fundus images.

PubMed

Hassan, Mehdi; Amin, Muhammad; Murtza, Iqbal; Khan, Asifullah; Chaudhry, Asmatullah

2017-11-01

In this paper, we consider the challenging problem of detecting retinal vessel networks. Precise detection of retinal vessel networks is vital for accurate eye disease diagnosis. Most of the blood vessel tracking techniques may not properly track vessels in presence of vessels' occlusion. Owing to problem in sensor resolution or acquisition of fundus images, it is possible that some part of vessel may occlude. In this scenario, it becomes a challenging task to accurately trace these vital vessels. For this purpose, we have proposed a new robust and intelligent retinal vessel detection technique on Hidden Markov Model. The proposed model is able to successfully track vessels in the presence of occlusion. The effectiveness of the proposed technique is evaluated on publically available standard DRIVE dataset of the fundus images. The experiments show that the proposed technique not only outperforms the other state of the art methodologies of retinal blood vessels segmentation, but it is also capable of accurate occlusion handling in retinal vessel networks. The proposed technique offers better average classification accuracy, sensitivity, specificity, and area under the curve (AUC) of 95.7%, 81.0%, 97.0%, and 90.0% respectively, which shows the usefulness of the proposed technique. Copyright © 2017 Elsevier B.V. All rights reserved.

Differences in children and adolescents' ability of reporting two CVS-related visual problems.

PubMed

Hu, Liang; Yan, Zheng; Ye, Tiantian; Lu, Fan; Xu, Peng; Chen, Hao

2013-01-01

The present study examined whether children and adolescents can correctly report dry eyes and blurred distance vision, two visual problems associated with computer vision syndrome. Participants are 913 children and adolescents aged 6-17. They were asked to report their visual problems, including dry eyes and blurred distance vision, and received an eye examination, including tear film break-up time (TFBUT) and visual acuity (VA). Inconsistency was found between participants' reports of dry eyes and TFBUT results among all 913 participants as well as for all of four subgroups. In contrast, consistency was found between participants' reports of blurred distance vision and VA results among 873 participants who had never worn glasses as well as for the four subgroups. It was concluded that children and adolescents are unable to report dry eyes correctly; however, they are able to report blurred distance vision correctly. Three practical implications of the findings were discussed. Little is known about children's ability to report their visual problems, an issue critical to diagnosis and treatment of children's computer vision syndrome. This study compared children's self-reports and clinic examination results and found children can correctly report blurred distance vision but not dry eyes.

Cannabis use and schizotypy: the role of social anxiety and other negative affective states.

PubMed

Najolia, Gina M; Buckner, Julia D; Cohen, Alex S

2012-12-30

Emerging research suggests that cannabis use might be related to psychosis onset in people vulnerable to developing schizophrenia-spectrum disorders. Furthermore, individuals with high-positive and disorganized schizotypy traits report more cannabis use and cannabis-related problems than controls. Social anxiety, a frequently co-occurring schizotypal feature, is related to increased cannabis-related problems in the general population. Building on this research, we explored the impact of social anxiety, measured by the Social Interaction Anxiety Scale (SIAS), and depression and trait anxiety reported on the Brief Symptom Inventory (BSI), on the relationship of schizotypy, measured by the Schizotypy Personality Questionnaire-Brief Revised (SPQ-BR), to cannabis use (n=220 schizotypy, 436 controls) and frequent use and cannabis-related problems among users (n=88 schizotypy, 83 controls) in college undergraduates. Among cannabis users, social anxiety moderated the relationships of schizotypy to frequent cannabis use and more cannabis-related problems in the total schizotypy group, and across high-positive, negative, and disorganized schizotypy subgroups. Depression and trait anxiety also moderated the relationship of schizotypy to frequent cannabis use and more cannabis-related problems, but results varied across high-positive, negative, and disorganized schizotypy subgroups. Results suggest therapeutically targeting negative affective states may be useful in psychosocial intervention for cannabis-related problems in schizotypy. Copyright © 2012 Elsevier Ireland Ltd. All rights reserved.

The Physiological Bases of Hidden Noise-Induced Hearing Loss: Protocol for a Functional Neuroimaging Study

PubMed Central

Hall, Deborah A; Guest, Hannah; Prendergast, Garreth; Plack, Christopher J; Francis, Susan T

2018-01-01

Background Rodent studies indicate that noise exposure can cause permanent damage to synapses between inner hair cells and high-threshold auditory nerve fibers, without permanently altering threshold sensitivity. These demonstrations of what is commonly known as hidden hearing loss have been confirmed in several rodent species, but the implications for human hearing are unclear. Objective Our Medical Research Council–funded program aims to address this unanswered question, by investigating functional consequences of the damage to the human peripheral and central auditory nervous system that results from cumulative lifetime noise exposure. Behavioral and neuroimaging techniques are being used in a series of parallel studies aimed at detecting hidden hearing loss in humans. The planned neuroimaging study aims to (1) identify central auditory biomarkers associated with hidden hearing loss; (2) investigate whether there are any additive contributions from tinnitus or diminished sound tolerance, which are often comorbid with hearing problems; and (3) explore the relation between subcortical functional magnetic resonance imaging (fMRI) measures and the auditory brainstem response (ABR). Methods Individuals aged 25 to 40 years with pure tone hearing thresholds ≤20 dB hearing level over the range 500 Hz to 8 kHz and no contraindications for MRI or signs of ear disease will be recruited into the study. Lifetime noise exposure will be estimated using an in-depth structured interview. Auditory responses throughout the central auditory system will be recorded using ABR and fMRI. Analyses will focus predominantly on correlations between lifetime noise exposure and auditory response characteristics. Results This paper reports the study protocol. The funding was awarded in July 2013. Enrollment for the study described in this protocol commenced in February 2017 and was completed in December 2017. Results are expected in 2018. Conclusions This challenging and comprehensive study will have the potential to impact diagnostic procedures for hidden hearing loss, enabling early identification of noise-induced auditory damage via the detection of changes in central auditory processing. Consequently, this will generate the opportunity to give personalized advice regarding provision of ear defense and monitoring of further damage, thus reducing the incidence of noise-induced hearing loss. PMID:29523503

Algorithm 937: MINRES-QLP for Symmetric and Hermitian Linear Equations and Least-Squares Problems.

PubMed

Choi, Sou-Cheng T; Saunders, Michael A

2014-02-01

We describe algorithm MINRES-QLP and its FORTRAN 90 implementation for solving symmetric or Hermitian linear systems or least-squares problems. If the system is singular, MINRES-QLP computes the unique minimum-length solution (also known as the pseudoinverse solution), which generally eludes MINRES. In all cases, it overcomes a potential instability in the original MINRES algorithm. A positive-definite pre-conditioner may be supplied. Our FORTRAN 90 implementation illustrates a design pattern that allows users to make problem data known to the solver but hidden and secure from other program units. In particular, we circumvent the need for reverse communication. Example test programs input and solve real or complex problems specified in Matrix Market format. While we focus here on a FORTRAN 90 implementation, we also provide and maintain MATLAB versions of MINRES and MINRES-QLP.

Intellectual, behavioral, and emotional functioning in children with syndromic craniosynostosis.

PubMed

Maliepaard, Marianne; Mathijssen, Irene M J; Oosterlaan, Jaap; Okkerse, Jolanda M E

2014-06-01

To examine intellectual, behavioral, and emotional functioning of children who have syndromic craniosynostosis and to explore differences between diagnostic subgroups. A national sample of children who have syndromic craniosynostosis participated in this study. Intellectual, behavioral, and emotional outcomes were assessed by using standardized measures: Wechsler Intelligence Scale for Children, Third Edition, Child Behavior Checklist (CBCL)/6-18, Disruptive Behavior Disorder rating scale (DBD), and the National Institute of Mental Health Diagnostic Interview Schedule for Children. We included 82 children (39 boys) aged 6 to 13 years who have syndromic craniosynostosis. Mean Full-Scale IQ (FSIQ) was in the normal range (M = 96.6; SD = 21.6). However, children who have syndromic craniosynostosis had a 1.9 times higher risk for developing intellectual disability (FSIQ < 85) compared with the normative population (P < .001) and had more behavioral and emotional problems compared with the normative population, including higher scores on the CBCL/6-18, DBD Total Problems (P < .001), Internalizing (P < .01), social problems (P < .001), attention problems (P < .001), and the DBD Inattention (P < .001). Children who have Apert syndrome had lower FSIQs (M = 76.7; SD = 13.3) and children who have Muenke syndrome had more social problems (P < .01), attention problems (P < .05), and inattention problems (P < .01) than normative population and with other diagnostic subgroups. Although children who have syndromic craniosynostosis have FSIQs similar to the normative population, they are at increased risk for developing intellectual disability, internalizing, social, and attention problems. Higher levels of behavioral and emotional problems were related to lower levels of intellectual functioning.

Fast determination of structurally cohesive subgroups in large networks

PubMed Central

Sinkovits, Robert S.; Moody, James; Oztan, B. Tolga; White, Douglas R.

2016-01-01

Structurally cohesive subgroups are a powerful and mathematically rigorous way to characterize network robustness. Their strength lies in the ability to detect strong connections among vertices that not only have no neighbors in common, but that may be distantly separated in the graph. Unfortunately, identifying cohesive subgroups is a computationally intensive problem, which has limited empirical assessments of cohesion to relatively small graphs of at most a few thousand vertices. We describe here an approach that exploits the properties of cliques, k-cores and vertex separators to iteratively reduce the complexity of the graph to the point where standard algorithms can be used to complete the analysis. As a proof of principle, we apply our method to the cohesion analysis of a 29,462-vertex biconnected component extracted from a 128,151-vertex co-authorship data set. PMID:28503215

Vertical Mandibular Range of Motion in Anesthetized Dogs and Cats

PubMed Central

Gracis, Margherita; Zini, Eric

2016-01-01

The main movement of the temporomandibular joint of dogs and cats is in vertical dimensions (opening and closing the mouth). An objective evaluation of the vertical mandibular range of motion (vmROM) may favor early diagnosis of a number of conditions affecting the joint mobility. vmROM, corresponding to the maximum interincisal opening, was measured in 260 dogs and 127 cats anesthetized between June 2011 and April 2015 because of oral or maxillofacial problems and procedures. Animals with a known history of or having current diseases considered to hamper mandibular extension were excluded from the study. Dogs were divided into four subgroups, based on body weight: subgroup 1 (≤5.0 kg, 51 dogs), subgroup 2 (5.1–10.0 kg, 56 dogs), subgroup 3 (10.1–25 kg, 66 dogs), and subgroup 4 (>25.1 kg, 87 dogs). The mean vmROM of all dogs was 107 ± 30 mm (median 109, range 40–180); in subgroup 1 was 67 ± 15 mm (median 67, range 40–100), in subgroup 2 was 93 ± 15 mm (median 93, range 53–128), in subgroup 3 was 115 ± 19 mm (median 116, range 59–154), and in subgroup 4 was 134 ± 19 mm (median 135, range 93–180). The mean vmROM of the cats was 62 ± 8 mm (median 63, range 41–84). Correlations between vmROM, age, sex, and body weight were evaluated. In dogs, vmROM did not correlate with age, and in cats a weak positive correlation was found. vmROM and body weight were positively correlated in both populations, except dog subgroup 2. Overall, mean vmROM and body weight were significantly higher in male than in female, both in dogs and in cats. However, vmROM did not differ between sexes in any of the canine subgroups, and only in subgroup 4 male dogs were significantly heavier than females. Evaluation of vmROM should be incorporated into every diagnostic examination as it may be valuable in showing changes over time for every single patient. PMID:27446939

The interaction between gambling activities and modes of access: a comparison of Internet-only, land-based only, and mixed-mode gamblers.

PubMed

Gainsbury, Sally M; Russell, Alex; Blaszczynski, Alex; Hing, Nerilee

2015-02-01

Research suggests that Internet-based gambling includes risk factors that may increase gambling problems. The current study aimed to investigate subgroups of gamblers to identify the potential harms associated with various forms and modes of gambling. An online survey was completed by 4,594 respondents identified as Internet-only (IG), land-based only (LBGs), or mixed-mode (MMG) gamblers based on self-reported gambling behaviour in the last 12months. Results showed significant socio-demographic differences between groups, with the LBGs being the oldest and MMGs the youngest. MMGs engaged in the greatest variety of gambling forms, had the highest average problem gambling severity scores, and were more likely to attribute problems to sports betting than the other groups. IGs were involved in the lowest number of divergent gambling activities, most likely to gamble frequently on sports and races, and attribute problems to these forms. Compared to the other groups, LBs had a higher proportion of problem gamblers than IGs and were most likely to play electronic gaming machines weekly, with this form of gambling contributing to problems at a substantially greater rate. This study confirms the importance of considering gambling involvement across subgroups of Internet or land-based gamblers. There is a need to consider the interaction between forms and modes of gambling to advance our understanding of the potential risk of mode of gambling to contribute to problems. Copyright © 2014 Elsevier Ltd. All rights reserved.

The secret art of managing healthcare expenses: investigating implicit rationing and autonomy in public healthcare systems.

PubMed

Lauridsen, S M R; Norup, M S; Rossel, P J H

2007-12-01

Rationing healthcare is a difficult task, which includes preventing patients from accessing potentially beneficial treatments. Proponents of implicit rationing argue that politicians cannot resist pressure from strong patient groups for treatments and conclude that physicians should ration without informing patients or the public. The authors subdivide this specific programme of implicit rationing, or "hidden rationing", into local hidden rationing, unsophisticated global hidden rationing and sophisticated global hidden rationing. They evaluate the appropriateness of these methods of rationing from the perspectives of individual and political autonomy and conclude that local hidden rationing and unsophisticated global hidden rationing clearly violate patients' individual autonomy, that is, their right to participate in medical decision-making. While sophisticated global hidden rationing avoids this charge, the authors point out that it nonetheless violates the political autonomy of patients, that is, their right to engage in public affairs as citizens. A defence of any of the forms of hidden rationing is therefore considered to be incompatible with a defence of autonomy.

Clinical Holistic Medicine: A Psychological Theory of Dependency to Improve Quality of Life

PubMed Central

Ventegodt, Søren; Morad, Mohammed; Kandel, Isack; Merrick, Joav

2004-01-01

In this paper, we suggest a psychological theory of dependency as an escape from feeling existential suffering and a poor quality of life. The ways in which human beings escape hidden existential pains are multiple. The wide range of dependency states seems to be the most common escape strategy used. If the patient can be guided into the hidden existential pain to feel, understand, and integrate it, we believe that dependency can be cured. The problem is that the patient must be highly motivated, sufficiently resourceful, and supported to want such a treatment that is inherently painful. Often, the family and surrounding world is suffering more than the dependent person himself, because the pattern of behavior the patient is dependent on makes him or her rather insensitive and unable to feel. If the patient is motivated, resourceful, and trusts his physician, recovery from even a severe state of dependency is not out of reach, if the holistic medical tools are applied wisely. The patient must find hidden resources to take action, then in therapy confront and feel old emotional pain, understand the source and inner logic of it, and finally learn to let go of negative attitudes and beliefs. In this way, the person can be healed and released of the emotional suffering and no longer be a slave to the dependency pattern. PMID:15349506

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

Vongehr, Sascha, E-mail: vongehr@usc.edu

There are increasingly suggestions for computer simulations of quantum statistics which try to violate Bell type inequalities via classical, common cause correlations. The Clauser–Horne–Shimony–Holt (CHSH) inequality is very robust. However, we argue that with the Einstein–Podolsky–Rosen setup, the CHSH is inferior to the Bell inequality, although and because the latter must assume anti-correlation of entangled photon singlet states. We simulate how often quantum behavior violates both inequalities, depending on the number of photons. Violating Bell 99% of the time is argued to be an ideal benchmark. We present hidden variables that violate the Bell and CHSH inequalities with 50% probability,more » and ones which violate Bell 85% of the time when missing 13% anti-correlation. We discuss how to present the quantum correlations to a wide audience and conclude that, when defending against claims of hidden classicality, one should demand numerical simulations and insist on anti-correlation and the full amount of Bell violation. -- Highlights: •The widely assumed superiority of the CHSH fails in the EPR problem. •We simulate Bell type inequalities behavior depending on the number of photons. •The core of Bell’s theorem in the EPR setup is introduced in a simple way understandable to a wide audience. •We present hidden variables that violate both inequalities with 50% probability. •Algorithms have been supplied in form of Mathematica programs.« less

Radar HRRP Target Recognition Based on Stacked Autoencoder and Extreme Learning Machine

PubMed Central

Liu, Yongxiang; Huo, Kai; Zhang, Zhongshuai

2018-01-01

A novel radar high-resolution range profile (HRRP) target recognition method based on a stacked autoencoder (SAE) and extreme learning machine (ELM) is presented in this paper. As a key component of deep structure, the SAE does not only learn features by making use of data, it also obtains feature expressions at different levels of data. However, with the deep structure, it is hard to achieve good generalization performance with a fast learning speed. ELM, as a new learning algorithm for single hidden layer feedforward neural networks (SLFNs), has attracted great interest from various fields for its fast learning speed and good generalization performance. However, ELM needs more hidden nodes than conventional tuning-based learning algorithms due to the random set of input weights and hidden biases. In addition, the existing ELM methods cannot utilize the class information of targets well. To solve this problem, a regularized ELM method based on the class information of the target is proposed. In this paper, SAE and the regularized ELM are combined to make full use of their advantages and make up for each of their shortcomings. The effectiveness of the proposed method is demonstrated by experiments with measured radar HRRP data. The experimental results show that the proposed method can achieve good performance in the two aspects of real-time and accuracy, especially when only a few training samples are available. PMID:29320453

Radar HRRP Target Recognition Based on Stacked Autoencoder and Extreme Learning Machine.

PubMed

Zhao, Feixiang; Liu, Yongxiang; Huo, Kai; Zhang, Shuanghui; Zhang, Zhongshuai

2018-01-10

A novel radar high-resolution range profile (HRRP) target recognition method based on a stacked autoencoder (SAE) and extreme learning machine (ELM) is presented in this paper. As a key component of deep structure, the SAE does not only learn features by making use of data, it also obtains feature expressions at different levels of data. However, with the deep structure, it is hard to achieve good generalization performance with a fast learning speed. ELM, as a new learning algorithm for single hidden layer feedforward neural networks (SLFNs), has attracted great interest from various fields for its fast learning speed and good generalization performance. However, ELM needs more hidden nodes than conventional tuning-based learning algorithms due to the random set of input weights and hidden biases. In addition, the existing ELM methods cannot utilize the class information of targets well. To solve this problem, a regularized ELM method based on the class information of the target is proposed. In this paper, SAE and the regularized ELM are combined to make full use of their advantages and make up for each of their shortcomings. The effectiveness of the proposed method is demonstrated by experiments with measured radar HRRP data. The experimental results show that the proposed method can achieve good performance in the two aspects of real-time and accuracy, especially when only a few training samples are available.

The ``Folk Theorem'' on effective field theory: How does it fare in nuclear physics?

NASA Astrophysics Data System (ADS)

Rho, Mannque

2017-10-01

This is a brief history of what I consider as very important, some of which truly seminal, contributions made by young Korean nuclear theorists, mostly graduate students working on PhD thesis in 1990s and early 2000s, to nuclear effective field theory, nowadays heralded as the first-principle approach to nuclear physics. The theoretical framework employed is an effective field theory anchored on a single scale-invariant hidden local symmetric Lagrangian constructed in the spirit of Weinberg's "Folk Theorem" on effective field theory. The problems addressed are the high-precision calculations on the thermal np capture, the solar pp fusion process, the solar hep process — John Bahcall's challenge to nuclear theorists — and the quenching of g A in giant Gamow-Teller resonances and the whopping enhancement of first-forbidden beta transitions relevant in astrophysical processes. Extending adventurously the strategy to a wild uncharted domain in which a systematic implementation of the "theorem" is far from obvious, the same effective Lagrangian is applied to the structure of compact stars. A surprising, unexpected, result on the properties of massive stars, totally different from what has been obtained up to day in the literature, is predicted, such as the precocious onset of conformal sound velocity together with a hint for the possible emergence in dense matter of hidden symmetries such as scale symmetry and hidden local symmetry.

Two fast and accurate heuristic RBF learning rules for data classification.

PubMed

Rouhani, Modjtaba; Javan, Dawood S

2016-03-01

This paper presents new Radial Basis Function (RBF) learning methods for classification problems. The proposed methods use some heuristics to determine the spreads, the centers and the number of hidden neurons of network in such a way that the higher efficiency is achieved by fewer numbers of neurons, while the learning algorithm remains fast and simple. To retain network size limited, neurons are added to network recursively until termination condition is met. Each neuron covers some of train data. The termination condition is to cover all training data or to reach the maximum number of neurons. In each step, the center and spread of the new neuron are selected based on maximization of its coverage. Maximization of coverage of the neurons leads to a network with fewer neurons and indeed lower VC dimension and better generalization property. Using power exponential distribution function as the activation function of hidden neurons, and in the light of new learning approaches, it is proved that all data became linearly separable in the space of hidden layer outputs which implies that there exist linear output layer weights with zero training error. The proposed methods are applied to some well-known datasets and the simulation results, compared with SVM and some other leading RBF learning methods, show their satisfactory and comparable performance. Copyright © 2015 Elsevier Ltd. All rights reserved.

Lessons Learned from Managing a Petabyte

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

Becla, J

2005-01-20

The amount of data collected and stored by the average business doubles each year. Many commercial databases are already approaching hundreds of terabytes, and at this rate, will soon be managing petabytes. More data enables new functionality and capability, but the larger scale reveals new problems and issues hidden in ''smaller'' terascale environments. This paper presents some of these new problems along with implemented solutions in the framework of a petabyte dataset for a large High Energy Physics experiment. Through experience with two persistence technologies, a commercial database and a file-based approach, we expose format-independent concepts and issues prevalent atmore » this new scale of computing.« less

Quantum learning of classical stochastic processes: The completely positive realization problem

NASA Astrophysics Data System (ADS)

Monràs, Alex; Winter, Andreas

2016-01-01

Among several tasks in Machine Learning, a specially important one is the problem of inferring the latent variables of a system and their causal relations with the observed behavior. A paradigmatic instance of this is the task of inferring the hidden Markov model underlying a given stochastic process. This is known as the positive realization problem (PRP), [L. Benvenuti and L. Farina, IEEE Trans. Autom. Control 49(5), 651-664 (2004)] and constitutes a central problem in machine learning. The PRP and its solutions have far-reaching consequences in many areas of systems and control theory, and is nowadays an important piece in the broad field of positive systems theory. We consider the scenario where the latent variables are quantum (i.e., quantum states of a finite-dimensional system) and the system dynamics is constrained only by physical transformations on the quantum system. The observable dynamics is then described by a quantum instrument, and the task is to determine which quantum instrument — if any — yields the process at hand by iterative application. We take as a starting point the theory of quasi-realizations, whence a description of the dynamics of the process is given in terms of linear maps on state vectors and probabilities are given by linear functionals on the state vectors. This description, despite its remarkable resemblance with the hidden Markov model, or the iterated quantum instrument, is however devoid of any stochastic or quantum mechanical interpretation, as said maps fail to satisfy any positivity conditions. The completely positive realization problem then consists in determining whether an equivalent quantum mechanical description of the same process exists. We generalize some key results of stochastic realization theory, and show that the problem has deep connections with operator systems theory, giving possible insight to the lifting problem in quotient operator systems. Our results have potential applications in quantum machine learning, device-independent characterization and reverse-engineering of stochastic processes and quantum processors, and more generally, of dynamical processes with quantum memory [M. Guţă, Phys. Rev. A 83(6), 062324 (2011); M. Guţă and N. Yamamoto, e-print arXiv:1303.3771(2013)].

A theory of cerebellar cortex and adaptive motor control based on two types of universal function approximation capability.

PubMed

Fujita, Masahiko

2016-03-01

Lesions of the cerebellum result in large errors in movements. The cerebellum adaptively controls the strength and timing of motor command signals depending on the internal and external environments of movements. The present theory describes how the cerebellar cortex can control signals for accurate and timed movements. A model network of the cerebellar Golgi and granule cells is shown to be equivalent to a multiple-input (from mossy fibers) hierarchical neural network with a single hidden layer of threshold units (granule cells) that receive a common recurrent inhibition (from a Golgi cell). The weighted sum of the hidden unit signals (Purkinje cell output) is theoretically analyzed regarding the capability of the network to perform two types of universal function approximation. The hidden units begin firing as the excitatory inputs exceed the recurrent inhibition. This simple threshold feature leads to the first approximation theory, and the network final output can be any continuous function of the multiple inputs. When the input is constant, this output becomes stationary. However, when the recurrent unit activity is triggered to decrease or the recurrent inhibition is triggered to increase through a certain mechanism (metabotropic modulation or extrasynaptic spillover), the network can generate any continuous signals for a prolonged period of change in the activity of recurrent signals, as the second approximation theory shows. By incorporating the cerebellar capability of two such types of approximations to a motor system, in which learning proceeds through repeated movement trials with accompanying corrections, accurate and timed responses for reaching the target can be adaptively acquired. Simple models of motor control can solve the motor error vs. sensory error problem, as well as the structural aspects of credit (or error) assignment problem. Two physiological experiments are proposed for examining the delay and trace conditioning of eyelid responses, as well as saccade adaptation, to investigate this novel idea of cerebellar processing. Copyright © 2015 Elsevier Ltd. All rights reserved.

The Hidden Curriculum as Emancipatory and Non-Emancipatory Tools.

ERIC Educational Resources Information Center

Kanpol, Barry

Moral values implied in school practices and policies constitute the "hidden curriculum." Because the hidden curriculum may promote certain moral values to students, teachers are partially responsible for the moral education of students. A component of the hidden curriculum, institutional political resistance, concerns teacher opposition to…

Complex Mental Health Sequelae of Psychological Trauma Among Women in Prenatal Care

PubMed Central

Seng, Julia S.; D’Andrea, Wendy; Ford, Julian D.

2014-01-01

Pregnancy is a critical time to identify and address maternal mental health problems, for the health of both mother and child. Pregnant women with histories of exposure to interpersonal psychological trauma may experience a range of mental health problems including but not limited to posttraumatic stress disorder (PTSD). In a community sample of 1,581 pregnant women, 25% reported symptoms consistent with at least one of six syndromes, including PTSD, major depressive disorder (MDD), generalized anxiety disorder (GAD), or clinically significant dissociation, somatization, or affect dysregulation. Six sub-groups with distinct mental health problem profiles were identified by cluster analysis. Controlling for sociodemographic risk factors, women with histories of interpersonal trauma were over-represented in four sub-groups characterized by: (1) PTSD comorbid with depression (childhood sexual abuse), (2) PTSD comorbid with affect/interpersonal dysregulation (childhood physical or emotional abuse), (3) somatization (adult abuse), and (4) GAD (foster/adoptive placement). Findings suggest risk relationships warranting further study between different types of interpersonal trauma exposure and psychiatric outcomes in pregnant women, including PTSD with two types of comorbidity. PMID:25558308

Apollo 16: Nothing So Hidden

NASA Technical Reports Server (NTRS)

1972-01-01

This film shows the landing and the three lunar traverses in the highland region of the moon, near the crater descartes. It includes an astronaut's eye view from the rover, lunar grand prix, discovery of the house-sized rock, lunar lift-off and eva 173,000 miles above the earth. Microphones and cameras in mission control record the emergency problem solving during the prelanding crisis and the reactions of scientists on earth as the astronauts explore the moon.

Patients with Staged Bilateral Total Joint Arthroplasty in Registries: Immortal Time Bias and Methodological Options.

PubMed

van der Pas, Stéphanie L; Nelissen, Rob G H H; Fiocco, Marta

2017-08-02

In arthroplasty data, patients with staged bilateral total joint arthroplasty (TJA) pose a problem in statistical analysis. Subgroup analysis, in which patients with unilateral and bilateral TJA are studied separately, is sometimes considered an appropriate solution to the problem; we aim to show that this is not true because of immortal time bias. We reviewed patients who underwent staged (at any time) bilateral TJA. The logical fallacy leading to immortal time bias is explained through a simple artificial data example. The cumulative incidences of revision and death are computed by subgroup analysis and by landmark analysis based on hip replacement data from the Dutch Arthroplasty Register and on simulated data sets. For patients who underwent unilateral TJA, subgroup analysis can lead to an overestimate of the cumulative incidence of death and an underestimate of the cumulative incidence of revision. The reverse conclusion holds for patients who underwent staged bilateral TJA. Analysis of these patients can lead to an underestimate of the cumulative incidence of death and an overestimate of the cumulative incidence of revision. Immortal time bias can be prevented by using landmark analysis. When examining arthroplasty registry data, patients who underwent staged bilateral TJA should be analyzed with caution. An appropriate statistical method to address the research question should be selected.

The intersection of interpersonal and self-directed violence among general adult, college student and sexually diverse samples.

PubMed

Cramer, Robert J; Desmarais, Sarah L; Johnson, Kiersten L; Gemberling, Tess M; Nobles, Matt R; Holley, Sarah R; Wright, Susan; Van Dorn, Richard

2017-02-01

Suicide and interpersonal violence (i.e. victimization and perpetration) represent pressing public health problems, and yet remain mostly addressed as separate topics. To identify the (1) frequency and overlap of suicide and interpersonal violence and (2) characteristics differentiating subgroups of violence-related experiences. A health survey was completed by 2,175 respondents comprised of three groups: college students ( n = 702), adult members of a sexuality special interest organization ( n = 816) and a community adult sample ( n = 657). Latent class analysis was used to identify subgroups characterized by violence experiences; logistic regression was used to identify respondent characteristics differentiating subgroups. Overall rates of violence perpetration were low; perpetration, victimization and self-directed violence all varied by sample. Adults with alternative sexual interests reported high rates of victimization and self-directed violence. Analyses indicated two subgroups: (1) victimization + self-directed violence and (2) self-directed violence only. The victimization + self-directed violence subgroup was characterized by older, White, female and sexual orientation minority persons. The self-directed violence subgroup was characterized by younger, non-White, male and straight counterparts engaging with more sexual partners and more frequent drug use. Findings support the Centers for Disease Control and Prevention (CDC) definition of suicide as self-directed violence. Suicide intervention and prevention should further account for the role of violent victimization by focusing on the joint conceptualization of self-directed and interpersonal violence. Additional prevention implications are discussed.

Polsar Land Cover Classification Based on Hidden Polarimetric Features in Rotation Domain and Svm Classifier

NASA Astrophysics Data System (ADS)

Tao, C.-S.; Chen, S.-W.; Li, Y.-Z.; Xiao, S.-P.

2017-09-01

Land cover classification is an important application for polarimetric synthetic aperture radar (PolSAR) data utilization. Rollinvariant polarimetric features such as H / Ani / α / Span are commonly adopted in PolSAR land cover classification. However, target orientation diversity effect makes PolSAR images understanding and interpretation difficult. Only using the roll-invariant polarimetric features may introduce ambiguity in the interpretation of targets' scattering mechanisms and limit the followed classification accuracy. To address this problem, this work firstly focuses on hidden polarimetric feature mining in the rotation domain along the radar line of sight using the recently reported uniform polarimetric matrix rotation theory and the visualization and characterization tool of polarimetric coherence pattern. The former rotates the acquired polarimetric matrix along the radar line of sight and fully describes the rotation characteristics of each entry of the matrix. Sets of new polarimetric features are derived to describe the hidden scattering information of the target in the rotation domain. The latter extends the traditional polarimetric coherence at a given rotation angle to the rotation domain for complete interpretation. A visualization and characterization tool is established to derive new polarimetric features for hidden information exploration. Then, a classification scheme is developed combing both the selected new hidden polarimetric features in rotation domain and the commonly used roll-invariant polarimetric features with a support vector machine (SVM) classifier. Comparison experiments based on AIRSAR and multi-temporal UAVSAR data demonstrate that compared with the conventional classification scheme which only uses the roll-invariant polarimetric features, the proposed classification scheme achieves both higher classification accuracy and better robustness. For AIRSAR data, the overall classification accuracy with the proposed classification scheme is 94.91 %, while that with the conventional classification scheme is 93.70 %. Moreover, for multi-temporal UAVSAR data, the averaged overall classification accuracy with the proposed classification scheme is up to 97.08 %, which is much higher than the 87.79 % from the conventional classification scheme. Furthermore, for multitemporal PolSAR data, the proposed classification scheme can achieve better robustness. The comparison studies also clearly demonstrate that mining and utilization of hidden polarimetric features and information in the rotation domain can gain the added benefits for PolSAR land cover classification and provide a new vision for PolSAR image interpretation and application.

Sleep phenotypes in infants and toddlers with neurogenetic syndromes.

PubMed

Abel, Emily A; Tonnsen, Bridgette L

2017-10-01

Although sleep problems are well characterized in preschool- and school-age children with neurogenetic syndromes, little is known regarding the early emergence of these problems in infancy and toddlerhood. To inform syndrome-specific profiles and targets for intervention, we compared parent-reported sleep problems in infants and toddlers with Angelman syndrome (AS), Williams syndrome (WS), and Prader-Willi syndrome (PWS) with patterns observed among same-aged typically developing (TD) controls. Mothers of 80 children (18 AS, 19 WS, 19 PWS, and 24 TD) completed the Brief Infant Sleep Questionnaire. Primary dependent variables included (1) sleep onset latency, (2) total sleep duration, (3) daytime and nighttime sleep duration, and (4) sleep problem severity, as measured by both maternal impression and National Sleep Foundation guidelines. Sleep problems are relatively common in children with neurogenetic syndromes, with 41% of mothers reporting problematic sleep and 29% of children exhibiting abnormal sleep durations as per national guidelines. Across genetic subgroups, problems are most severe in children with AS and WS, particularly in relation to nighttime sleep duration. Although atypical sleep is characteristically reported in each syndrome later in development, infants and toddlers with PWS exhibited largely typical patterns, potentially indicating delayed onset of sleep problems in concordance with other medical features of PWS. Our findings suggest that sleep problems in neurogenetic syndromes emerge as early as infancy and toddlerhood, with variable profiles across genetic subgroups. This work underscores the importance of early sleep screenings as part of routine medical care of neurosyndromic populations and the need for targeted, syndrome-sensitive treatment. Copyright © 2017 Elsevier B.V. All rights reserved.

Photoacoustic imaging of hidden dental caries by using a fiber-based probing system

NASA Astrophysics Data System (ADS)

Koyama, Takuya; Kakino, Satoko; Matsuura, Yuji

2017-04-01

Photoacoustic method to detect hidden dental caries is proposed. It was found that high frequency ultrasonic waves are generated from hidden carious part when radiating laser light to occlusal surface of model tooth. By making a map of intensity of these high frequency components, photoacoustic images of hidden caries were successfully obtained. A photoacoustic imaging system using a bundle of hollow optical fiber was fabricated for using clinical application, and clear photoacoustic image of hidden caries was also obtained by this system.

--No Title--

Science.gov Websites

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Game-theoretic cooperativity in networks of self-interested units

NASA Astrophysics Data System (ADS)

Barto, Andrew G.

1986-08-01

The behavior of theoretical neural networks is often described in terms of competition and cooperation. I present an approach to network learning that is related to game and team problems in which competition and cooperation have more technical meanings. I briefly describe the application of stochastic learning automata to game and team problems and then present an adaptive element that is a synthesis of aspects of stochastic learning automata and typical neuron-like adaptive elements. These elements act as self-interested agents that work toward improving their performance with respect to their individual preference orderings. Networks of these elements can solve a variety of team decision problems, some of which take the form of layered networks in which the ``hidden units'' become appropriate functional components as they attempt to improve their own payoffs.

Neural architecture design based on extreme learning machine.

PubMed

Bueno-Crespo, Andrés; García-Laencina, Pedro J; Sancho-Gómez, José-Luis

2013-12-01

Selection of the optimal neural architecture to solve a pattern classification problem entails to choose the relevant input units, the number of hidden neurons and its corresponding interconnection weights. This problem has been widely studied in many research works but their solutions usually involve excessive computational cost in most of the problems and they do not provide a unique solution. This paper proposes a new technique to efficiently design the MultiLayer Perceptron (MLP) architecture for classification using the Extreme Learning Machine (ELM) algorithm. The proposed method provides a high generalization capability and a unique solution for the architecture design. Moreover, the selected final network only retains those input connections that are relevant for the classification task. Experimental results show these advantages. Copyright © 2013 Elsevier Ltd. All rights reserved.

Natural hidden antibodies reacting with DNA or cardiolipin bind to thymocytes and evoke their death.

PubMed

Zamulaeva, I A; Lekakh, I V; Kiseleva, V I; Gabai, V L; Saenko, A S; Shevchenko, A S; Poverenny, A M

1997-08-18

Both free and hidden natural antibodies to DNA or cardiolipin were obtained from immunoglobulins of a normal donor. The free antibodies reacting with DNA or cardiolipin were isolated by means of affinity chromatography. Antibodies occurring in an hidden state were disengaged from the depleted immunoglobulins by ion-exchange chromatography and were then affinity-isolated on DNA or cardiolipin sorbents. We used flow cytometry to study the ability of free and hidden antibodies to bind to rat thymocytes. Simultaneously, plasma membrane integrity was tested by propidium iodide (PI) exclusion. The hidden antibodies reacted with 65.2 +/- 10.9% of the thymocytes and caused a fast plasma membrane disruption. Cells (28.7 +/- 7.1%) were stained with PI after incubation with the hidden antibodies for 1 h. The free antibodies bound to a very small fraction of the thymocytes and did not evoke death as compared to control without antibodies. The possible reason for the observed effects is difference in reactivity of the free and hidden antibodies to phospholipids. While free antibodies reacted preferentially with phosphotidylcholine, hidden antibodies reacted with cardiolipin and phosphotidylserine.

Qualitative Treatment-Subgroup Interactions in a Randomized Clinical Trial of Treatments for Adolescents with ADHD: Exploring What Cognitive-Behavioral Treatment Works for Whom

PubMed Central

Geurts, Hilde M.; Prins, Pier J. M.; Van Mechelen, Iven; Van der Oord, Saskia

2016-01-01

Objective This study explored qualitative treatment-subgroup interactions within data of a RCT with two cognitive behavioral treatments (CBT) for adolescents with ADHD: a planning-focused (PML) and a solution-focused CBT (SFT). Qualitative interactions imply that which treatment is best differs across subgroups of patients, and are therefore most relevant for personalized medicine. Methods Adolescents with ADHD (N = 159) received either PML or SFT. Pre-, post- and three-month follow-up data were gathered on parent-rated ADHD symptoms and planning problems. Pretreatment characteristics were explored as potential qualitative moderators of pretest to follow-up treatment effects, using an innovative analyses technique (QUINT; Dusseldorp & Van Mechelen, 2014). In addition, qualitative treatment-subgroup interactions for the therapeutic changes from pre- to posttest and from post- to follow-up test were investigated. Results For the entire time span from pretest to follow-up only a quantitative interaction was found, while from posttest to follow-up qualitative interactions were found: Adolescents with less depressive symptoms but more anxiety symptoms showed more improvement when receiving PML than SFT, while for other adolescents the effects of PML and SFT were comparable. Discussion Whereas subgroups in both treatments followed different trajectories, no subgroup was found for which SFT outperformed PML in terms of the global change in symptoms from pretest to three months after treatment. This implies that, based on this exploratory study, there is no need for personalized treatment allocation with regard to the CBTs under study for adolescents with ADHD. However, for a subgroup with comorbid anxiety symptoms but low depression PML clearly appears the treatment of preference. Trial Registration Nederlands Trial Register NTR2142 PMID:26977602

Food parenting measurement issues: working group consensus report.

PubMed

Hughes, Sheryl O; Frankel, Leslie A; Beltran, Alicia; Hodges, Eric; Hoerr, Sharon; Lumeng, Julie; Tovar, Alison; Kremers, Stef

2013-08-01

Childhood obesity is a growing problem. As more researchers become involved in the study of parenting influences on childhood obesity, there appears to be a lack of agreement regarding the most important parenting constructs of interest, definitions of those constructs, and measurement of those constructs in a consistent manner across studies. This article aims to summarize findings from a working group that convened specifically to discuss measurement issues related to parental influences on childhood obesity. Six subgroups were formed to address key measurement issues. The conceptualization subgroup proposed to define and distinguish constructs of general parenting styles, feeding styles, and food parenting practices with the goal of understanding interrelating levels of parental influence on child eating behaviors. The observational subgroup identified the need to map constructs for use in coding direct observations and create observational measures that can capture the bidirectional effects of parent-child interactions. The self-regulation subgroup proposed an operational definition of child self-regulation of energy intake and suggested future measures of self-regulation across different stages of development. The translational/community involvement subgroup proposed the involvement of community in the development of surveys so that measures adequately reflect cultural understanding and practices of the community. The qualitative methods subgroup proposed qualitative methods as a way to better understand the breadth of food parenting practices and motivations for the use of such practices. The longitudinal subgroup stressed the importance of food parenting measures sensitive to change for use in longitudinal studies. In the creation of new measures, it is important to consider cultural sensitivity and context-specific food parenting domains. Moderating variables such as child temperament and child food preferences should be considered in models.

Food Parenting Measurement Issues: Working Group Consensus Report

PubMed Central

Frankel, Leslie A.; Beltran, Alicia; Hodges, Eric; Hoerr, Sharon; Lumeng, Julie; Tovar, Alison; Kremers, Stef

2013-01-01

Abstract Childhood obesity is a growing problem. As more researchers become involved in the study of parenting influences on childhood obesity, there appears to be a lack of agreement regarding the most important parenting constructs of interest, definitions of those constructs, and measurement of those constructs in a consistent manner across studies. This article aims to summarize findings from a working group that convened specifically to discuss measurement issues related to parental influences on childhood obesity. Six subgroups were formed to address key measurement issues. The conceptualization subgroup proposed to define and distinguish constructs of general parenting styles, feeding styles, and food parenting practices with the goal of understanding interrelating levels of parental influence on child eating behaviors. The observational subgroup identified the need to map constructs for use in coding direct observations and create observational measures that can capture the bidirectional effects of parent–child interactions. The self-regulation subgroup proposed an operational definition of child self-regulation of energy intake and suggested future measures of self-regulation across different stages of development. The translational/community involvement subgroup proposed the involvement of community in the development of surveys so that measures adequately reflect cultural understanding and practices of the community. The qualitative methods subgroup proposed qualitative methods as a way to better understand the breadth of food parenting practices and motivations for the use of such practices. The longitudinal subgroup stressed the importance of food parenting measures sensitive to change for use in longitudinal studies. In the creation of new measures, it is important to consider cultural sensitivity and context-specific food parenting domains. Moderating variables such as child temperament and child food preferences should be considered in models. PMID:23944928

Qualitative Treatment-Subgroup Interactions in a Randomized Clinical Trial of Treatments for Adolescents with ADHD: Exploring What Cognitive-Behavioral Treatment Works for Whom.

PubMed

Boyer, Bianca E; Doove, Lisa L; Geurts, Hilde M; Prins, Pier J M; Van Mechelen, Iven; Van der Oord, Saskia

2016-01-01

This study explored qualitative treatment-subgroup interactions within data of a RCT with two cognitive behavioral treatments (CBT) for adolescents with ADHD: a planning-focused (PML) and a solution-focused CBT (SFT). Qualitative interactions imply that which treatment is best differs across subgroups of patients, and are therefore most relevant for personalized medicine. Adolescents with ADHD (N = 159) received either PML or SFT. Pre-, post- and three-month follow-up data were gathered on parent-rated ADHD symptoms and planning problems. Pretreatment characteristics were explored as potential qualitative moderators of pretest to follow-up treatment effects, using an innovative analyses technique (QUINT; Dusseldorp & Van Mechelen, 2014). In addition, qualitative treatment-subgroup interactions for the therapeutic changes from pre- to posttest and from post- to follow-up test were investigated. For the entire time span from pretest to follow-up only a quantitative interaction was found, while from posttest to follow-up qualitative interactions were found: Adolescents with less depressive symptoms but more anxiety symptoms showed more improvement when receiving PML than SFT, while for other adolescents the effects of PML and SFT were comparable. Whereas subgroups in both treatments followed different trajectories, no subgroup was found for which SFT outperformed PML in terms of the global change in symptoms from pretest to three months after treatment. This implies that, based on this exploratory study, there is no need for personalized treatment allocation with regard to the CBTs under study for adolescents with ADHD. However, for a subgroup with comorbid anxiety symptoms but low depression PML clearly appears the treatment of preference. Nederlands Trial Register NTR2142.

Raising awareness of the hidden curriculum in veterinary medical education: a review and call for research.

PubMed

Whitcomb, Tiffany L

2014-01-01

The hidden curriculum is characterized by information that is tacitly conveyed to and among students about the cultural and moral environment in which they find themselves. Although the hidden curriculum is often defined as a distinct entity, tacit information is conveyed to students throughout all aspects of formal and informal curricula. This unconsciously communicated knowledge has been identified across a wide spectrum of educational environments and is known to have lasting and powerful impacts, both positive and negative. Recently, medical education research on the hidden curriculum of becoming a doctor has come to the forefront as institutions struggle with inconsistencies between formal and hidden curricula that hinder the practice of patient-centered medicine. Similarly, the complex ethical questions that arise during the practice and teaching of veterinary medicine have the potential to cause disagreement between what the institution sets out to teach and what is actually learned. However, the hidden curriculum remains largely unexplored for this field. Because the hidden curriculum is retained effectively by students, elucidating its underlying messages can be a key component of program refinement. A review of recent literature about the hidden curriculum in a variety of fields, including medical education, will be used to explore potential hidden curricula in veterinary medicine and draw attention to the need for further investigation.

Smart aircraft fastener evaluation (SAFE) system: a condition-based corrosion detection system for aging aircraft

NASA Astrophysics Data System (ADS)

Schoess, Jeffrey N.; Seifert, Greg; Paul, Clare A.

1996-05-01

The smart aircraft fastener evaluation (SAFE) system is an advanced structural health monitoring effort to detect and characterize corrosion in hidden and inaccessible locations of aircraft structures. Hidden corrosion is the number one logistics problem for the U.S. Air Force, with an estimated maintenance cost of $700M per year in 1990 dollars. The SAFE system incorporates a solid-state electrochemical microsensor and smart sensor electronics in the body of a Hi-Lok aircraft fastener to process and autonomously report corrosion status to aircraft maintenance personnel. The long-term payoff for using SAFE technology will be in predictive maintenance for aging aircraft and rotorcraft systems, fugitive emissions applications such as control valves, chemical pipeline vessels, and industrial boilers. Predictive maintenance capability, service, and repair will replace the current practice of scheduled maintenance to substantially reduce operational costs. A summary of the SAFE concept, laboratory test results, and future field test plans is presented.

Hamiltonian dynamics of a quantum of space: hidden symmetries and spectrum of the volume operator, and discrete orthogonal polynomials

NASA Astrophysics Data System (ADS)

Aquilanti, Vincenzo; Marinelli, Dimitri; Marzuoli, Annalisa

2013-05-01

The action of the quantum mechanical volume operator, introduced in connection with a symmetric representation of the three-body problem and recently recognized to play a fundamental role in discretized quantum gravity models, can be given as a second-order difference equation which, by a complex phase change, we turn into a discrete Schrödinger-like equation. The introduction of discrete potential-like functions reveals the surprising crucial role here of hidden symmetries, first discovered by Regge for the quantum mechanical 6j symbols; insight is provided into the underlying geometric features. The spectrum and wavefunctions of the volume operator are discussed from the viewpoint of the Hamiltonian evolution of an elementary ‘quantum of space’, and a transparent asymptotic picture of the semiclassical and classical regimes emerges. The definition of coordinates adapted to the Regge symmetry is exploited for the construction of a novel set of discrete orthogonal polynomials, characterizing the oscillatory components of torsion-like modes.

Maximum mutual information estimation of a simplified hidden MRF for offline handwritten Chinese character recognition

NASA Astrophysics Data System (ADS)

Xiong, Yan; Reichenbach, Stephen E.

1999-01-01

Understanding of hand-written Chinese characters is at such a primitive stage that models include some assumptions about hand-written Chinese characters that are simply false. So Maximum Likelihood Estimation (MLE) may not be an optimal method for hand-written Chinese characters recognition. This concern motivates the research effort to consider alternative criteria. Maximum Mutual Information Estimation (MMIE) is an alternative method for parameter estimation that does not derive its rationale from presumed model correctness, but instead examines the pattern-modeling problem in automatic recognition system from an information- theoretic point of view. The objective of MMIE is to find a set of parameters in such that the resultant model allows the system to derive from the observed data as much information as possible about the class. We consider MMIE for recognition of hand-written Chinese characters using on a simplified hidden Markov Random Field. MMIE provides improved performance improvement over MLE in this application.

Utterance independent bimodal emotion recognition in spontaneous communication

NASA Astrophysics Data System (ADS)

Tao, Jianhua; Pan, Shifeng; Yang, Minghao; Li, Ya; Mu, Kaihui; Che, Jianfeng

2011-12-01

Emotion expressions sometimes are mixed with the utterance expression in spontaneous face-to-face communication, which makes difficulties for emotion recognition. This article introduces the methods of reducing the utterance influences in visual parameters for the audio-visual-based emotion recognition. The audio and visual channels are first combined under a Multistream Hidden Markov Model (MHMM). Then, the utterance reduction is finished by finding the residual between the real visual parameters and the outputs of the utterance related visual parameters. This article introduces the Fused Hidden Markov Model Inversion method which is trained in the neutral expressed audio-visual corpus to solve the problem. To reduce the computing complexity the inversion model is further simplified to a Gaussian Mixture Model (GMM) mapping. Compared with traditional bimodal emotion recognition methods (e.g., SVM, CART, Boosting), the utterance reduction method can give better results of emotion recognition. The experiments also show the effectiveness of our emotion recognition system when it was used in a live environment.

Integrating Decision Tree and Hidden Markov Model (HMM) for Subtype Prediction of Human Influenza A Virus

NASA Astrophysics Data System (ADS)

Attaluri, Pavan K.; Chen, Zhengxin; Weerakoon, Aruna M.; Lu, Guoqing

Multiple criteria decision making (MCDM) has significant impact in bioinformatics. In the research reported here, we explore the integration of decision tree (DT) and Hidden Markov Model (HMM) for subtype prediction of human influenza A virus. Infection with influenza viruses continues to be an important public health problem. Viral strains of subtype H3N2 and H1N1 circulates in humans at least twice annually. The subtype detection depends mainly on the antigenic assay, which is time-consuming and not fully accurate. We have developed a Web system for accurate subtype detection of human influenza virus sequences. The preliminary experiment showed that this system is easy-to-use and powerful in identifying human influenza subtypes. Our next step is to examine the informative positions at the protein level and extend its current functionality to detect more subtypes. The web functions can be accessed at http://glee.ist.unomaha.edu/.

Passive acoustic leak detection for sodium cooled fast reactors using hidden Markov models

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

Riber Marklund, A.; Kishore, S.; Prakash, V.

2015-07-01

Acoustic leak detection for steam generators of sodium fast reactors have been an active research topic since the early 1970's and several methods have been tested over the years. Inspired by its success in the field of automatic speech recognition, we here apply hidden Markov models (HMM) in combination with Gaussian mixture models (GMM) to the problem. To achieve this, we propose a new feature calculation scheme, based on the temporal evolution of the power spectral density (PSD) of the signal. Using acoustic signals recorded during steam/water injection experiments done at the Indira Gandhi Centre for Atomic Research (IGCAR), themore » proposed method is tested. We perform parametric studies on the HMM+GMM model size and demonstrate that the proposed method a) performs well without a priori knowledge of injection noise, b) can incorporate several noise models and c) has an output distribution that simplifies false alarm rate control. (authors)« less

Identifying influential user communities on the social network

NASA Astrophysics Data System (ADS)

Hu, Weishu; Gong, Zhiguo; Hou U, Leong; Guo, Jingzhi

2015-10-01

Nowadays social network services have been popularly used in electronic commerce systems. Users on the social network can develop different relationships based on their common interests and activities. In order to promote the business, it is interesting to explore hidden relationships among users developed on the social network. Such knowledge can be used to locate target users for different advertisements and to provide effective product recommendations. In this paper, we define and study a novel community detection problem that is to discover the hidden community structure in large social networks based on their common interests. We observe that the users typically pay more attention to those users who share similar interests, which enable a way to partition the users into different communities according to their common interests. We propose two algorithms to detect influential communities using common interests in large social networks efficiently and effectively. We conduct our experimental evaluation using a data set from Epinions, which demonstrates that our method achieves 4-11.8% accuracy improvement over the state-of-the-art method.

Identification of psychological comorbidity in TMD-patients.

PubMed

Ismail, F; Eisenburger, M; Lange, K; Schneller, T; Schwabe, L; Strempel, J; Stiesch, M

2016-05-01

The aim of the current study was to access the prevalence of depression among patients with Temporomandibular Joint Disorder (TMD) compared to patients with no current TMD. Patients (92) and controls (90) answered questionnaires on subjective pain, severity of chronic pain, jaw disability, emotional well-being and depression, and a clinical examination was performed. Temporomandibular Joint Disorder patients reported higher disability of jaw function, compared to controls (p<0.001). The myoarthopathy subgroup (67.4%) had slightly more jaw disability than the myopathy subgroup (p>0.05). While 51% of TMD patients reported poor emotional well-being, only 7.8% of controls were affected (p<0.001). Clinical symptoms of depression were reported by 16% of TMD patients and not in the controls (p<0.001). Among TMD patients, a higher prevalence of depression was observed in the myopathy subgroup. A regular screening for psychological problems, using standardized questionnaires, should be integrated in clinical examination of TMD patients.

Making better decisions in groups

PubMed Central

Frith, Chris D.

2017-01-01

We review the literature to identify common problems of decision-making in individuals and groups. We are guided by a Bayesian framework to explain the interplay between past experience and new evidence, and the problem of exploring the space of hypotheses about all the possible states that the world could be in and all the possible actions that one could take. There are strong biases, hidden from awareness, that enter into these psychological processes. While biases increase the efficiency of information processing, they often do not lead to the most appropriate action. We highlight the advantages of group decision-making in overcoming biases and searching the hypothesis space for good models of the world and good solutions to problems. Diversity of group members can facilitate these achievements, but diverse groups also face their own problems. We discuss means of managing these pitfalls and make some recommendations on how to make better group decisions. PMID:28878973

Pre-service teachers’ challenges in presenting mathematical problems

NASA Astrophysics Data System (ADS)

Desfitri, R.

2018-01-01

The purpose of this study was to analyzed how pre-service teachers prepare and assigned tasks or assignments in teaching practice situations. This study was also intended to discuss about kind of tasks or assignments they gave to students. Participants of this study were 15 selected pre-service mathematics teachers from mathematics education department who took part on microteaching class as part of teaching preparation program. Based on data obtained, it was occasionally found that there were hidden errors on questions or tasks assigned by pre-service teachers which might lead their students not to be able to reach a logical or correct answer. Although some answers might seem to be true, they were illogical or unfavourable. It is strongly recommended that pre-service teachers be more careful when posing mathematical problems so that students do not misunderstand the problems or the concepts, since both teachers and students were sometimes unaware of errors in problems being worked on.

What if ? On alternative conceptual models and the problem of their implementation

NASA Astrophysics Data System (ADS)

Neuberg, Jurgen

2015-04-01

Seismic and other monitoring techniques rely on a set of conceptual models on the base of which data sets can be interpreted. In order to do this on an operational level in volcano observatories these models need to be tested and ready for an interpretation in a timely manner. Once established, scientists in charge advising stakeholders and decision makers often stick firmly to these models to avoid confusion by giving alternative versions of interpretations to non-experts. This talk gives an overview of widely accepted conceptual models to interpret seismic and deformation data, and highlights in a few case studies some of the arising problems. Aspects covered include knowledge transfer between research institutions and observatories, data sharing, the problem of up-taking advice, and some hidden problems which turn out to be much more critical in assessing volcanic hazard than the actual data interpretation.

Learning and optimization with cascaded VLSI neural network building-block chips

NASA Technical Reports Server (NTRS)

Duong, T.; Eberhardt, S. P.; Tran, M.; Daud, T.; Thakoor, A. P.

1992-01-01

To demonstrate the versatility of the building-block approach, two neural network applications were implemented on cascaded analog VLSI chips. Weights were implemented using 7-b multiplying digital-to-analog converter (MDAC) synapse circuits, with 31 x 32 and 32 x 32 synapses per chip. A novel learning algorithm compatible with analog VLSI was applied to the two-input parity problem. The algorithm combines dynamically evolving architecture with limited gradient-descent backpropagation for efficient and versatile supervised learning. To implement the learning algorithm in hardware, synapse circuits were paralleled for additional quantization levels. The hardware-in-the-loop learning system allocated 2-5 hidden neurons for parity problems. Also, a 7 x 7 assignment problem was mapped onto a cascaded 64-neuron fully connected feedback network. In 100 randomly selected problems, the network found optimal or good solutions in most cases, with settling times in the range of 7-100 microseconds.

Algorithm 937: MINRES-QLP for Symmetric and Hermitian Linear Equations and Least-Squares Problems

PubMed Central

Choi, Sou-Cheng T.; Saunders, Michael A.

2014-01-01

We describe algorithm MINRES-QLP and its FORTRAN 90 implementation for solving symmetric or Hermitian linear systems or least-squares problems. If the system is singular, MINRES-QLP computes the unique minimum-length solution (also known as the pseudoinverse solution), which generally eludes MINRES. In all cases, it overcomes a potential instability in the original MINRES algorithm. A positive-definite pre-conditioner may be supplied. Our FORTRAN 90 implementation illustrates a design pattern that allows users to make problem data known to the solver but hidden and secure from other program units. In particular, we circumvent the need for reverse communication. Example test programs input and solve real or complex problems specified in Matrix Market format. While we focus here on a FORTRAN 90 implementation, we also provide and maintain MATLAB versions of MINRES and MINRES-QLP. PMID:25328255

Heating up the Galaxy with hidden photons

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

Dubovsky, Sergei; Hernández-Chifflet, Guzmán, E-mail: dubovsky@nyu.edu, E-mail: ghc236@nyu.edu

2015-12-01

We elaborate on the dynamics of ionized interstellar medium in the presence of hidden photon dark matter. Our main focus is the ultra-light regime, where the hidden photon mass is smaller than the plasma frequency in the Milky Way. We point out that as a result of the Galactic plasma shielding direct detection of ultra-light photons in this mass range is especially challenging. However, we demonstrate that ultra-light hidden photon dark matter provides a powerful heating source for the ionized interstellar medium. This results in a strong bound on the kinetic mixing between hidden and regular photons all the waymore » down to the hidden photon masses of order 10{sup −20} eV.« less

Heating up the Galaxy with hidden photons

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

Dubovsky, Sergei; Hernández-Chifflet, Guzmán; Instituto de Física, Facultad de Ingeniería, Universidad de la República,Montevideo, 11300

2015-12-29

We elaborate on the dynamics of ionized interstellar medium in the presence of hidden photon dark matter. Our main focus is the ultra-light regime, where the hidden photon mass is smaller than the plasma frequency in the Milky Way. We point out that as a result of the Galactic plasma shielding direct detection of ultra-light photons in this mass range is especially challenging. However, we demonstrate that ultra-light hidden photon dark matter provides a powerful heating source for the ionized interstellar medium. This results in a strong bound on the kinetic mixing between hidden and regular photons all the waymore » down to the hidden photon masses of order 10{sup −20} eV.« less

Disentangling Heterogeneity of Childhood Disruptive Behavior Problems Into Dimensions and Subgroups.

PubMed

Bolhuis, Koen; Lubke, Gitta H; van der Ende, Jan; Bartels, Meike; van Beijsterveldt, Catharina E M; Lichtenstein, Paul; Larsson, Henrik; Jaddoe, Vincent W V; Kushner, Steven A; Verhulst, Frank C; Boomsma, Dorret I; Tiemeier, Henning

2017-08-01

Irritable and oppositional behaviors are increasingly considered as distinct dimensions of oppositional defiant disorder. However, few studies have explored this multidimensionality across the broader spectrum of disruptive behavior problems (DBPs). This study examined the presence of dimensions and distinct subgroups of childhood DBPs, and the cross-sectional and longitudinal associations between these dimensions. Using factor mixture models (FMMs), the presence of dimensions and subgroups of DBPs was assessed in the Generation R Study at ages 6 (n = 6,209) and 10 (n = 4,724) years. Replications were performed in two population-based cohorts (Netherlands Twin Registry, n = 4,402, and Swedish Twin Study of Child and Adolescent Development, n = 1,089) and a clinical sample (n = 1,933). We used cross-lagged modeling in the Generation R Study to assess cross-sectional and longitudinal associations between dimensions. DBPs were assessed using mother-reported responses to the Child Behavior Checklist. Empirically obtained dimensions of DBPs were oppositional behavior (age 6 years), disobedient behavior, rule-breaking behavior (age 10 years), physical aggression, and irritability (both ages). FMMs suggested that one-class solutions had the best model fit for all dimensions in all three population-based cohorts. Similar results were obtained in the clinical sample. All three dimensions, including irritability, predicted subsequent physical aggression (range, 0.08-0.16). This study showed that childhood DBPs should be regarded as a multidimensional phenotype rather than comprising distinct subgroups. Incorporating multidimensionality will improve diagnostic accuracy and refine treatment. Future studies need to address the biological validity of the DBP dimensions observed in this study; herein lies an important opportunity for neuroimaging and genetic measures. Copyright © 2017 American Academy of Child and Adolescent Psychiatry. Published by Elsevier Inc. All rights reserved.

Spyware.

PubMed

Bergren, Martha Dewey

2004-10-01

School nurses access an enormous amount of information through the Internet. Although most avid computer users are savvy to the threat of viruses to the integrity of data, many who surf the Web do not know that their data and the functioning of their computer is at risk to another hidden threat--spyware. This article will describe spyware, why it is a problem, how it is transmitted to a personal or business computer, how to prevent spyware infestation, and how to delete it.

Connectionism and Compositional Semantics

DTIC Science & Technology

1989-05-01

can use their hidden layers to learn difficult discriminations. such as panty or the Penzias two clumps/three clumps problem, where the output is...sauce." For novel sentences that are similar to the training sentences (e.g., train on "the girl hit the boy," test on -the boy hit the girl "), the...overridden by semantic considerations. as in this example from Wendy Lehnert (personal communicanon): (5) John saw the girl with the telescope in a red

Eating disorders: a hidden phenomenon in outpatient mental health?

PubMed

Fursland, Anthea; Watson, Hunna J

2014-05-01

Eating disorders are common but underdiagnosed illnesses. Help-seeking for co-occurring issues, such as anxiety and depression, are common. To identify the prevalence of eating problems, using the SCOFF, and eating disorders when screening positive on the SCOFF (i.e., ≥2), among patients seeking help for anxiety and depression at a community-based mental health service. Patients (N = 260) consecutively referred and assessed for anxiety and depression treatment were administered the SCOFF screening questionnaire and a semi-structured standardized diagnostic interview during routine intake. 18.5% (48/260) scored ≥2 on the SCOFF, indicating eating problems. Of these, 41% (19/48) met criteria for an eating disorder. Thus, overall, 7.3% (19/260) of the sample met criteria for a DSM-IV eating disorder. Those scoring ≥2 on the SCOFF were more likely to: be female (p = 0.001), younger (p = 0.003), and have a history of self-harm (p < 0.001). This study confirms that eating disorders are a hidden phenomenon in general outpatient mental health. By using a standardized diagnostic interview to establish diagnosis rather than self- or staff-report, the study builds on limited previous findings. The naturalistic study setting shows that screening for eating disorders can be easily built into routine intake practice, and successfully identifies treatment need. Copyright © 2013 Wiley Periodicals, Inc.

Improved Leg Tracking Considering Gait Phase and Spline-Based Interpolation during Turning Motion in Walk Tests.

PubMed

Yorozu, Ayanori; Moriguchi, Toshiki; Takahashi, Masaki

2015-09-04

Falling is a common problem in the growing elderly population, and fall-risk assessment systems are needed for community-based fall prevention programs. In particular, the timed up and go test (TUG) is the clinical test most often used to evaluate elderly individual ambulatory ability in many clinical institutions or local communities. This study presents an improved leg tracking method using a laser range sensor (LRS) for a gait measurement system to evaluate the motor function in walk tests, such as the TUG. The system tracks both legs and measures the trajectory of both legs. However, both legs might be close to each other, and one leg might be hidden from the sensor. This is especially the case during the turning motion in the TUG, where the time that a leg is hidden from the LRS is longer than that during straight walking and the moving direction rapidly changes. These situations are likely to lead to false tracking and deteriorate the measurement accuracy of the leg positions. To solve these problems, a novel data association considering gait phase and a Catmull-Rom spline-based interpolation during the occlusion are proposed. From the experimental results with young people, we confirm   that the proposed methods can reduce the chances of false tracking. In addition, we verify the measurement accuracy of the leg trajectory compared to a three-dimensional motion analysis system (VICON).

Modeling volatility using state space models.

PubMed

Timmer, J; Weigend, A S

1997-08-01

In time series problems, noise can be divided into two categories: dynamic noise which drives the process, and observational noise which is added in the measurement process, but does not influence future values of the system. In this framework, we show that empirical volatilities (the squared relative returns of prices) exhibit a significant amount of observational noise. To model and predict their time evolution adequately, we estimate state space models that explicitly include observational noise. We obtain relaxation times for shocks in the logarithm of volatility ranging from three weeks (for foreign exchange) to three to five months (for stock indices). In most cases, a two-dimensional hidden state is required to yield residuals that are consistent with white noise. We compare these results with ordinary autoregressive models (without a hidden state) and find that autoregressive models underestimate the relaxation times by about two orders of magnitude since they do not distinguish between observational and dynamic noise. This new interpretation of the dynamics of volatility in terms of relaxators in a state space model carries over to stochastic volatility models and to GARCH models, and is useful for several problems in finance, including risk management and the pricing of derivative securities. Data sets used: Olsen & Associates high frequency DEM/USD foreign exchange rates (8 years). Nikkei 225 index (40 years). Dow Jones Industrial Average (25 years).

Characterization of skin reactions and pain reported by patients receiving radiation therapy for cancer at different sites.

PubMed

Gewandter, Jennifer S; Walker, Joanna; Heckler, Charles E; Morrow, Gary R; Ryan, Julie L

2013-12-01

Skin reactions and pain are commonly reported side effects of radiation therapy (RT). To characterize RT-induced symptoms according to treatment site subgroups and identify skin symptoms that correlate with pain. A self-report survey-adapted from the MD Anderson Symptom Inventory and the McGill Pain Questionnaire--assessed RT-induced skin problems, pain, and specific skin symptoms. Wilcoxon Sign Ranked tests compared mean severity or pre- and post-RT pain and skin problems within each RT-site subgroup. Multiple linear regression (MLR) investigated associations between skin symptoms and pain. Survey respondents (N = 106) were 58% female and on average 64 years old. RT sites included lung, breast, lower abdomen, head/neck/brain, and upper abdomen. Only patients receiving breast RT reported significant increases in treatment site pain and skin problems (P < or = .007). Patients receiving head/neck/brain RT reported increased skin problems (P < .0009). MLR showed that post-RT skin tenderness and tightness were most strongly associated with post-RT pain (P = .066 and P = .122, respectively). Small sample size, exploratory analyses, and nonvalidated measure. Only patients receiving breast RT reported significant increases in pain and skin problems at the RT site while patients receiving head/neck/brain RT had increased skin problems but not pain. These findings suggest that the severity of skin problems is not the only factor that contributes to pain and that interventions should be tailored to specifically target pain at the RT site, possibly by targeting tenderness and tightness. These findings should be confirmed in a larger sampling of RT patients.

"It's Not Always What It Seems": Exploring the Hidden Curriculum within a Doctoral Program

ERIC Educational Resources Information Center

Foot, Rachel Elizabeth

2017-01-01

The purpose of this qualitative, naturalistic study was to explore the ways in which hidden curriculum might influence doctoral student success. Two questions guided the study: (a) How do doctoral students experience the hidden curriculum? (b) What forms of hidden curricula can be identified in a PhD program? Data were collected from twelve…

The hidden and informal curriculum across the continuum of training: A cross-sectional qualitative study.

PubMed

Doja, Asif; Bould, M Dylan; Clarkin, Chantalle; Eady, Kaylee; Sutherland, Stephanie; Writer, Hilary

2016-04-01

The hidden and informal curricula refer to learning in response to unarticulated processes and constraints, falling outside the formal medical curriculum. The hidden curriculum has been identified as requiring attention across all levels of learning. We sought to assess the knowledge and perceptions of the hidden and informal curricula across the continuum of learning at a single institution. Focus groups were held with undergraduate and postgraduate learners and faculty to explore knowledge and perceptions relating to the hidden and informal curricula. Thematic analysis was conducted both inductively by research team members and deductively using questions structured by the existing literature. Participants highlighted several themes related to the presence of the hidden and informal curricula in medical training and practice, including: the privileging of some specialties over others; the reinforcement of hierarchies within medicine; and a culture of tolerance towards unprofessional behaviors. Participants acknowledged the importance of role modeling in the development of professional identities and discussed the deterioration in idealism that occurs. Common issues pertaining to the hidden curriculum exist across all levels of learners, including faculty. Increased awareness of these issues could allow for the further development of methods to address learning within the hidden curriculum.

The hidden and informal curriculum across the continuum of training: A cross-sectional qualitative study.

PubMed

Doja, Asif; Bould, M Dylan; Clarkin, Chantalle; Eady, Kaylee; Sutherland, Stephanie; Writer, Hilary

2016-01-01

The hidden and informal curricula refer to learning in response to unarticulated processes and constraints, falling outside the formal medical curriculum. The hidden curriculum has been identified as requiring attention across all levels of learning. We sought to assess the knowledge and perceptions of the hidden and informal curricula across the continuum of learning at a single institution. Focus groups were held with undergraduate and postgraduate learners and faculty to explore knowledge and perceptions relating to the hidden and informal curricula. Thematic analysis was conducted both inductively by research team members and deductively using questions structured by the existing literature. Participants highlighted several themes related to the presence of the hidden and informal curricula in medical training and practice, including: the privileging of some specialties over others; the reinforcement of hierarchies within medicine; and a culture of tolerance towards unprofessional behaviors. Participants acknowledged the importance of role modeling in the development of professional identities and discussed the deterioration in idealism that occurs. Common issues pertaining to the hidden curriculum exist across all levels of learners, including faculty. Increased awareness of these issues could allow for the further development of methods to address learning within the hidden curriculum.

Hidden Farmworker Labor Camps in North Carolina: An Indicator of Structural Vulnerability

PubMed Central

Summers, Phillip; Quandt, Sara A.; Talton, Jennifer W.; Galván, Leonardo

2015-01-01

Objectives. We used geographic information systems (GIS) to delineate whether farmworker labor camps were hidden and to determine whether hidden camps differed from visible camps in terms of physical and resident characteristics. Methods. We collected data using observation, interview, and public domain GIS data for 180 farmworker labor camps in east central North Carolina. A hidden camp was defined as one that was at least 0.15 miles from an all-weather road or located behind natural or manufactured objects. Hidden camps were compared with visible camps in terms of physical and resident characteristics. Results. More than one third (37.8%) of the farmworker labor camps were hidden. Hidden camps were significantly larger (42.7% vs 17.0% with 21 or more residents; P ≤ .001; and 29.4% vs 13.5% with 3 or more dwellings; P = .002) and were more likely to include barracks (50% vs 19.6%; P ≤ .001) than were visible camps. Conclusions. Poor housing conditions in farmworker labor camps often go unnoticed because they are hidden in the rural landscape, increasing farmworker vulnerability. Policies that promote greater community engagement with farmworker labor camp residents to reduce structural vulnerability should be considered. PMID:26469658

Sub-grouping patients with non-specific low back pain based on cluster analysis of discriminatory clinical items.

PubMed

Billis, Evdokia; McCarthy, Christopher J; Roberts, Chris; Gliatis, John; Papandreou, Maria; Gioftsos, George; Oldham, Jacqueline A

2013-02-01

To identify potential subgroups amongst patients with non-specific low back pain based on a consensus list of potentially discriminatory examination items. Exploratory study. A convenience sample of 106 patients with non-specific low back pain (43 males, 63 females, mean age 36 years, standard deviation 15.9 years) and 7 physiotherapists. Based on 3 focus groups and a two-round Delphi involving 23 health professionals and a random stratified sample of 150 physiotherapists, respectively, a comprehensive examination list comprising the most "discriminatory" items was compiled. Following reliability analysis, the most reliable clinical items were assessed with a sample of patients with non-specific low back pain. K-means cluster analysis was conducted for 2-, 3- and 4-cluster options to explore for meaningful homogenous subgroups. The most clinically meaningful cluster was a two-subgroup option, comprising a small group (n = 24) with more severe clinical presentation (i.e. more widespread pain, functional and sleeping problems, other symptoms, increased investigations undertaken, more severe clinical signs, etc.) and a larger less dysfunctional group (n = 80). A number of potentially discriminatory clinical items were identified by health professionals and sub-classified, based on a sample of patients with non-specific low back pain, into two subgroups. However, further work is needed to validate this classification process.

The Flynn Effect within Subgroups in the U.S.: Gender, Race, Income, Education, and Urbanization Differences in the NLSY-Children Data.

PubMed

Ang, Siewching; Rodgers, Joseph Lee; Wänström, Linda

2010-07-01

Although the Flynn Effect has been studied widely across cultural, geographic, and intellectual domains, and many explanatory theories have been proposed, little past research attention has been paid to subgroup differences. Rodgers and Wänström (2007) identified an aggregate-level Flynn Effect (FE) at each age between 5 and 13 in the Children of the National Longitudinal Survey of Youth (NLSYC) PIAT-Math data. FE patterns were not obtained for Reading Recognition, Reading Comprehension, or Digit Span, consistent with past FE research suggesting a closer relationship to fluid intelligence measures of problem solving and analytic reasoning than to crystallized measures of verbal comprehension and memory. These prior findings suggest that the NLSYC data can be used as a natural laboratory to study more subtle FE patterns within various demographic subgroups. We test for subgroup Flynn Effect differences by gender, race/ethnicity, maternal education, household income, and urbanization. No subgroups differences emerged for three demographic categories. However, children with more educated (especially college educated) mothers and/or children born into higher income households had an accelerated Flynn effect in their PIAT-M scores compared to cohort peers with lower educated mothers or lower income households. We interpret both the positive and the null findings in relation to previous theoretical explanations.

Basics of identification measurement technology

NASA Astrophysics Data System (ADS)

Klikushin, Yu N.; Kobenko, V. Yu; Stepanov, P. P.

2018-01-01

All available algorithms and suitable for pattern recognition do not give 100% guarantee, therefore there is a field of scientific night activity in this direction, studies are relevant. It is proposed to develop existing technologies for pattern recognition in the form of application of identification measurements. The purpose of the study is to identify the possibility of recognizing images using identification measurement technologies. In solving problems of pattern recognition, neural networks and hidden Markov models are mainly used. A fundamentally new approach to the solution of problems of pattern recognition based on the technology of identification signal measurements (IIS) is proposed. The essence of IIS technology is the quantitative evaluation of the shape of images using special tools and algorithms.

How virtue ethics informs medical professionalism.

PubMed

McCammon, Susan D; Brody, Howard

2012-12-01

We argue that a turn toward virtue ethics as a way of understanding medical professionalism represents both a valuable corrective and a missed opportunity. We look at three ways in which a closer appeal to virtue ethics could help address current problems or issues in professionalism education-first, balancing professionalism training with demands for professional virtues as a prerequisite; second, preventing demands for the demonstrable achievement of competencies from working against ideal professionalism education as lifelong learning; and third, avoiding temptations to dismiss moral distress as a mere "hidden curriculum" problem. As a further demonstration of how best to approach a lifelong practice of medical virtue, we will examine altruism as a mean between the extremes of self-sacrifice and selfishness.

Infrared thermographic detection of buried grave sites

NASA Astrophysics Data System (ADS)

Weil, Gary J.; Graf, Richard J.

1992-04-01

Since time began, people have been born and people have died. For a variety of reasons grave sites have had to be located and investigated. These reasons have included legal, criminal, religious, construction and even simple curiosity problems. Destructive testing methods such as shovels and backhoes, have traditionally been used to determine grave site locations in fields, under pavements, and behind hidden locations. These existing techniques are slow, inconvenient, dirty, destructive, visually obtrusive, irritating to relatives, explosive to the media and expensive. A new, nondestructive, non-contact technique, infrared thermography has been developed to address these problems. This paper will describe how infrared thermography works and will be illustrated by several case histories.

Molecular and phylogenetic characterization of the sieve element occlusion gene family in Fabaceae and non-Fabaceae plants.

PubMed

Rüping, Boris; Ernst, Antonia M; Jekat, Stephan B; Nordzieke, Steffen; Reineke, Anna R; Müller, Boje; Bornberg-Bauer, Erich; Prüfer, Dirk; Noll, Gundula A

2010-10-08

The phloem of dicotyledonous plants contains specialized P-proteins (phloem proteins) that accumulate during sieve element differentiation and remain parietally associated with the cisternae of the endoplasmic reticulum in mature sieve elements. Wounding causes P-protein filaments to accumulate at the sieve plates and block the translocation of photosynthate. Specialized, spindle-shaped P-proteins known as forisomes that undergo reversible calcium-dependent conformational changes have evolved exclusively in the Fabaceae. Recently, the molecular characterization of three genes encoding forisome components in the model legume Medicago truncatula (MtSEO1, MtSEO2 and MtSEO3; SEO = sieve element occlusion) was reported, but little is known about the molecular characteristics of P-proteins in non-Fabaceae. We performed a comprehensive genome-wide comparative analysis by screening the M. truncatula, Glycine max, Arabidopsis thaliana, Vitis vinifera and Solanum phureja genomes, and a Malus domestica EST library for homologs of MtSEO1, MtSEO2 and MtSEO3 and identified numerous novel SEO genes in Fabaceae and even non-Fabaceae plants, which do not possess forisomes. Even in Fabaceae some SEO genes appear to not encode forisome components. All SEO genes have a similar exon-intron structure and are expressed predominantly in the phloem. Phylogenetic analysis revealed the presence of several subgroups with Fabaceae-specific subgroups containing all of the known as well as newly identified forisome component proteins. We constructed Hidden Markov Models that identified three conserved protein domains, which characterize SEO proteins when present in combination. In addition, one common and three subgroup specific protein motifs were found in the amino acid sequences of SEO proteins. SEO genes are organized in genomic clusters and the conserved synteny allowed us to identify several M. truncatula vs G. max orthologs as well as paralogs within the G. max genome. The unexpected occurrence of forisome-like genes in non-Fabaceae plants may indicate that these proteins encode species-specific P-proteins, which is backed up by the phloem-specific expression profiles. The conservation of gene structure, the presence of specific motifs and domains and the genomic synteny argue for a common phylogenetic origin of forisomes and other P-proteins.

A person-centered approach to examining heterogeneity and subgroups among survivors of sexual assault.

PubMed

Masters, N Tatiana; Stappenbeck, Cynthia A; Kaysen, Debra; Kajumulo, Kelly F; Davis, Kelly Cue; George, William H; Norris, Jeanette; Heiman, Julia R

2015-08-01

This study identified subgroups of female sexual assault survivors based on characteristics of their victimization experiences, validated the subgroup structure in a second cohort of women recruited identically to the first, and examined subgroups' differential associations with sexual risk/safety behavior, heavy episodic drinking (HED), psychological distress symptomatology, incarceration, transactional sex, and experiences with controlling and violent partners. The community sample consisted of 667 female survivors of adolescent or adult sexual assault who were 21 to 30 years old (M = 24.78, SD = 2.66). Eligibility criteria included having unprotected sex within the past year, other HIV/STI risk factors, and some experience with HED, but without alcohol problems or dependence. Latent class analyses (LCA) were used to identify subgroups of women with similar victimization experiences. Three groups were identified and validated across 2 cohorts of women using multiple-group LCA: contact or attempted assault (17% of the sample), incapacitated assault (52%), and forceful severe assault (31%). Groups did not differ in their sexual risk/safety behavior. Women in the forceful severe category had higher levels of anxiety, depression, and trauma symptoms; higher proportions of incarceration and transactional sex; and more experiences with controlling and violent partners than did women in the other 2 groups. Women in the forceful severe category also reported a higher frequency of HED than women in the incapacitated category. Different types of assault experiences appear to be differentially associated with negative outcomes. Understanding heterogeneity and subgroups among sexual assault survivors has implications for improving clinical care and contributing to recovery. (c) 2015 APA, all rights reserved).

A Person-Centered Approach to Examining Heterogeneity and Subgroups Among Survivors of Sexual Assault

PubMed Central

Masters, N. Tatiana; Stappenbeck, Cynthia A.; Kaysen, Debra; Kajumulo, Kelly F.; Davis, Kelly Cue; George, William H.; Norris, Jeanette; Heiman, Julia R.

2015-01-01

This study identified subgroups of female sexual assault survivors based on characteristics of their victimization experiences, validated the subgroup structure in a second cohort of women recruited identically to the first, and examined subgroups' differential associations with sexual risk/safety behavior, heavy episodic drinking (HED), psychological distress symptomatology, incarceration, transactional sex, and experiences with controlling and violent partners. The community sample consisted of 667 female survivors of adolescent or adult sexual assault who were 21 to 30 years old (M=24.78, SD=2.66). Eligibility criteria included having unprotected sex within the past year, other HIV/STI risk factors, and some experience with HED, but without alcohol problems or dependence. Latent class analyses (LCA) were used to identify subgroups of women with similar victimization experiences. Three groups were identified and validated across two cohorts of women using multiple-group LCA: Contact or Attempted assault (17% of the sample), Incapacitated assault (52%), and Forceful Severe assault (31%). Groups did not differ in their sexual risk/safety behavior. Women in the Forceful Severe category had higher levels of anxiety, depression, and trauma symptoms, higher proportions of incarceration and transactional sex, and more experiences with controlling and violent partners than did women in the other two groups. Women in the Forceful Severe category also reported a higher frequency of HED than women in the Incapacitated category. Different types of assault experiences appear to be differentially associated with negative outcomes. Understanding heterogeneity and subgroups among sexual assault survivors has implications for improving clinical care and contributing to recovery. PMID:26052619

A hidden curriculum: gambling and problem gambling among high school students in Auckland.

PubMed

Sullivan, Sean

2005-12-01

Participation in gambling by young people aged 13-18 years. During 2001, prior to the passing of legislation to minimise gambling harm, more than 500 students from six high schools completed a survey of their participation in gambling during the previous 12 months, and completed three problem gambling screens. Gambling, including under-age gambling, was a common event. Up to one in five were identified as at risk for problem gambling on at least one screen. Students who were non-European, or were from low socioeconomic areas, were more likely to be at risk for problem gambling. Help for gambling problems was preferred from friends and family rather than others, while inclusion of information in the education curriculum about risk of gambling problems was supported. The survey provided evidence for pre-legislation baseline gambling behaviour, and risk for problem gambling, of students attending high schools in Auckland. Levels of risk for problem gambling paralleled the elevated risk found for youth in many countries. Raising awareness, through a school curriculum, of risk for gambling problems among adolescents may be explored as a strategy to reduce the high levels of risk for gambling problems identified.

Zipf exponent of trajectory distribution in the hidden Markov model

NASA Astrophysics Data System (ADS)

Bochkarev, V. V.; Lerner, E. Yu

2014-03-01

This paper is the first step of generalization of the previously obtained full classification of the asymptotic behavior of the probability for Markov chain trajectories for the case of hidden Markov models. The main goal is to study the power (Zipf) and nonpower asymptotics of the frequency list of trajectories of hidden Markov frequencys and to obtain explicit formulae for the exponent of the power asymptotics. We consider several simple classes of hidden Markov models. We prove that the asymptotics for a hidden Markov model and for the corresponding Markov chain can be essentially different.

Identification of related gene/protein names based on an HMM of name variations.

PubMed

Yeganova, L; Smith, L; Wilbur, W J

2004-04-01

Gene and protein names follow few, if any, true naming conventions and are subject to great variation in different occurrences of the same name. This gives rise to two important problems in natural language processing. First, can one locate the names of genes or proteins in free text, and second, can one determine when two names denote the same gene or protein? The first of these problems is a special case of the problem of named entity recognition, while the second is a special case of the problem of automatic term recognition (ATR). We study the second problem, that of gene or protein name variation. Here we describe a system which, given a query gene or protein name, identifies related gene or protein names in a large list. The system is based on a dynamic programming algorithm for sequence alignment in which the mutation matrix is allowed to vary under the control of a fully trainable hidden Markov model.

Biased Dropout and Crossmap Dropout: Learning towards effective Dropout regularization in convolutional neural network.

PubMed

Poernomo, Alvin; Kang, Dae-Ki

2018-08-01

Training a deep neural network with a large number of parameters often leads to overfitting problem. Recently, Dropout has been introduced as a simple, yet effective regularization approach to combat overfitting in such models. Although Dropout has shown remarkable results on many deep neural network cases, its actual effect on CNN has not been thoroughly explored. Moreover, training a Dropout model will significantly increase the training time as it takes longer time to converge than a non-Dropout model with the same architecture. To deal with these issues, we address Biased Dropout and Crossmap Dropout, two novel approaches of Dropout extension based on the behavior of hidden units in CNN model. Biased Dropout divides the hidden units in a certain layer into two groups based on their magnitude and applies different Dropout rate to each group appropriately. Hidden units with higher activation value, which give more contributions to the network final performance, will be retained by a lower Dropout rate, while units with lower activation value will be exposed to a higher Dropout rate to compensate the previous part. The second approach is Crossmap Dropout, which is an extension of the regular Dropout in convolution layer. Each feature map in a convolution layer has a strong correlation between each other, particularly in every identical pixel location in each feature map. Crossmap Dropout tries to maintain this important correlation yet at the same time break the correlation between each adjacent pixel with respect to all feature maps by applying the same Dropout mask to all feature maps, so that all pixels or units in equivalent positions in each feature map will be either dropped or active during training. Our experiment with various benchmark datasets shows that our approaches provide better generalization than the regular Dropout. Moreover, our Biased Dropout takes faster time to converge during training phase, suggesting that assigning noise appropriately in hidden units can lead to an effective regularization. Copyright © 2018 Elsevier Ltd. All rights reserved.

Dietary hypersensitivity in cats and dogs.

PubMed

Mandigers, Paul; German, Alexander J

2010-10-01

Adverse reactions to food or dietary hypersensitivity are frequently seen problems in companion animal medicine and may be difficult to differentiate from inflammatory bowel disease (IBD). Dietary hypersensitivity can be divided into two subgroups: immunological and nonimmunological problems. Non-immunological problems can be subdivided into food intolerance, food poisoning, and dietary indiscretion. The immunological group can be subdivided into true food allergy (IgE mediated) and anaphylaxis (non-IgE mediated). This article gives an outline of what dietary hypersensitivity is, and more specifically food allergy and how to deal with patients with possible dietary hypersensitivity.

Automated Land Cover Change Detection and Mapping from Hidden Parameter Estimates of Normalized Difference Vegetation Index (NDVI) Time-Series

NASA Astrophysics Data System (ADS)

Chakraborty, S.; Banerjee, A.; Gupta, S. K. S.; Christensen, P. R.; Papandreou-Suppappola, A.

2017-12-01

Multitemporal observations acquired frequently by satellites with short revisit periods such as the Moderate Resolution Imaging Spectroradiometer (MODIS), is an important source for modeling land cover. Due to the inherent seasonality of the land cover, harmonic modeling reveals hidden state parameters characteristic to it, which is used in classifying different land cover types and in detecting changes due to natural or anthropogenic factors. In this work, we use an eight day MODIS composite to create a Normalized Difference Vegetation Index (NDVI) time-series of ten years. Improved hidden parameter estimates of the nonlinear harmonic NDVI model are obtained using the Particle Filter (PF), a sequential Monte Carlo estimator. The nonlinear estimation based on PF is shown to improve parameter estimation for different land cover types compared to existing techniques that use the Extended Kalman Filter (EKF), due to linearization of the harmonic model. As these parameters are representative of a given land cover, its applicability in near real-time detection of land cover change is also studied by formulating a metric that captures parameter deviation due to change. The detection methodology is evaluated by considering change as a rare class problem. This approach is shown to detect change with minimum delay. Additionally, the degree of change within the change perimeter is non-uniform. By clustering the deviation in parameters due to change, this spatial variation in change severity is effectively mapped and validated with high spatial resolution change maps of the given regions.

Fast learning method for convolutional neural networks using extreme learning machine and its application to lane detection.

PubMed

Kim, Jihun; Kim, Jonghong; Jang, Gil-Jin; Lee, Minho

2017-03-01

Deep learning has received significant attention recently as a promising solution to many problems in the area of artificial intelligence. Among several deep learning architectures, convolutional neural networks (CNNs) demonstrate superior performance when compared to other machine learning methods in the applications of object detection and recognition. We use a CNN for image enhancement and the detection of driving lanes on motorways. In general, the process of lane detection consists of edge extraction and line detection. A CNN can be used to enhance the input images before lane detection by excluding noise and obstacles that are irrelevant to the edge detection result. However, training conventional CNNs requires considerable computation and a big dataset. Therefore, we suggest a new learning algorithm for CNNs using an extreme learning machine (ELM). The ELM is a fast learning method used to calculate network weights between output and hidden layers in a single iteration and thus, can dramatically reduce learning time while producing accurate results with minimal training data. A conventional ELM can be applied to networks with a single hidden layer; as such, we propose a stacked ELM architecture in the CNN framework. Further, we modify the backpropagation algorithm to find the targets of hidden layers and effectively learn network weights while maintaining performance. Experimental results confirm that the proposed method is effective in reducing learning time and improving performance. Copyright © 2016 Elsevier Ltd. All rights reserved.

Visual one-shot learning as an 'anti-camouflage device': a novel morphing paradigm.

PubMed

Ishikawa, Tetsuo; Mogi, Ken

2011-09-01

Once people perceive what is in the hidden figure such as Dallenbach's cow and Dalmatian, they seldom seem to come back to the previous state when they were ignorant of the answer. This special type of learning process can be accomplished in a short time, with the effect of learning lasting for a long time (visual one-shot learning). Although it is an intriguing cognitive phenomenon, the lack of the control of difficulty of stimuli presented has been a problem in research. Here we propose a novel paradigm to create new hidden figures systematically by using a morphing technique. Through gradual changes from a blurred and binarized two-tone image to a blurred grayscale image of the original photograph including objects in a natural scene, spontaneous one-shot learning can occur at a certain stage of morphing when a sufficient amount of information is restored to the degraded image. A negative correlation between confidence levels and reaction times is observed, giving support to the fluency theory of one-shot learning. The correlation between confidence ratings and correct recognition rates indicates that participants had an accurate introspective ability (metacognition). The learning effect could be tested later by verifying whether or not the target object was recognized quicker in the second exposure. The present method opens a way for a systematic production of "good" hidden figures, which can be used to demystify the nature of visual one-shot learning.

The Physiological Bases of Hidden Noise-Induced Hearing Loss: Protocol for a Functional Neuroimaging Study.

PubMed

Dewey, Rebecca Susan; Hall, Deborah A; Guest, Hannah; Prendergast, Garreth; Plack, Christopher J; Francis, Susan T

2018-03-09

Rodent studies indicate that noise exposure can cause permanent damage to synapses between inner hair cells and high-threshold auditory nerve fibers, without permanently altering threshold sensitivity. These demonstrations of what is commonly known as hidden hearing loss have been confirmed in several rodent species, but the implications for human hearing are unclear. Our Medical Research Council-funded program aims to address this unanswered question, by investigating functional consequences of the damage to the human peripheral and central auditory nervous system that results from cumulative lifetime noise exposure. Behavioral and neuroimaging techniques are being used in a series of parallel studies aimed at detecting hidden hearing loss in humans. The planned neuroimaging study aims to (1) identify central auditory biomarkers associated with hidden hearing loss; (2) investigate whether there are any additive contributions from tinnitus or diminished sound tolerance, which are often comorbid with hearing problems; and (3) explore the relation between subcortical functional magnetic resonance imaging (fMRI) measures and the auditory brainstem response (ABR). Individuals aged 25 to 40 years with pure tone hearing thresholds ≤20 dB hearing level over the range 500 Hz to 8 kHz and no contraindications for MRI or signs of ear disease will be recruited into the study. Lifetime noise exposure will be estimated using an in-depth structured interview. Auditory responses throughout the central auditory system will be recorded using ABR and fMRI. Analyses will focus predominantly on correlations between lifetime noise exposure and auditory response characteristics. This paper reports the study protocol. The funding was awarded in July 2013. Enrollment for the study described in this protocol commenced in February 2017 and was completed in December 2017. Results are expected in 2018. This challenging and comprehensive study will have the potential to impact diagnostic procedures for hidden hearing loss, enabling early identification of noise-induced auditory damage via the detection of changes in central auditory processing. Consequently, this will generate the opportunity to give personalized advice regarding provision of ear defense and monitoring of further damage, thus reducing the incidence of noise-induced hearing loss. ©Rebecca Susan Dewey, Deborah A Hall, Hannah Guest, Garreth Prendergast, Christopher J Plack, Susan T Francis. Originally published in JMIR Research Protocols (http://www.researchprotocols.org), 09.03.2018.

Internet gamblers: a latent class analysis of their behaviours and health experiences.

PubMed

Lloyd, Joanne; Doll, Helen; Hawton, Keith; Dutton, William H; Geddes, John R; Goodwin, Guy M; Rogers, Robert D

2010-09-01

In order to learn about the behaviours and health experiences of people who gamble on the Internet, we conducted an international online survey with respondents recruited via gambling and gambling-related websites. The mean (SD) age of the 4,125 respondents completing the survey was 35.5 (11.8) years, with 79.1% being male and 68.8% UK residents. Respondents provided demographic details and completed validated psychometric screening instruments for problem gambling, mood disturbances, as well as alcohol and substance misuse, and history of deliberate self harm. We applied latent class analysis to respondents' patterns of regular online gambling activities, and identified subgroups of individuals who used the Internet to gamble in different ways (L (2) = 44.27, bootstrap P = 0.07). We termed the characteristic profiles as 'non-to-minimal gamblers'; 'sports bettors'; 'casino & sports gamblers'; 'lottery players'; and 'multi-activity gamblers'. Furthermore, these subgroups of respondents differed on other demographic and psychological dimensions, with significant inter-cluster differences in proportion of individuals scoring above threshold for problem gambling, mood disorders and substance misuse, and history of deliberate self harm (all Chi (2)s > 23.4, all P-values <0.001). The 'casino & sports' and 'multi-activity-gamblers' clusters had the highest prevalence of mental disorder. Internet gamblers appear to be heterogeneous but composed of several subgroups, differing markedly on both demographic and clinical characteristics.

A composite model for the 750 GeV diphoton excess

DOE PAGES

Harigaya, Keisuke; Nomura, Yasunori

2016-03-14

We study a simple model in which the recently reported 750 GeV diphoton excess arises from a composite pseudo Nambu-Goldstone boson — hidden pion — produced by gluon fusion and decaying into two photons. The model only introduces an extra hidden gauge group at the TeV scale with a vectorlike quark in the bifundamental representation of the hidden and standard model gauge groups. We calculate the masses of all the hidden pions and analyze their experimental signatures and constraints. We find that two colored hidden pions must be near the current experimental limits, and hence are probed in the nearmore » future. We study physics of would-be stable particles — the composite states that do not decay purely by the hidden and standard model gauge dynamics — in detail, including constraints from cosmology. We discuss possible theoretical structures above the TeV scale, e.g. conformal dynamics and supersymmetry, and their phenomenological implications. We also discuss an extension of the minimal model in which there is an extra hidden quark that is singlet under the standard model and has a mass smaller than the hidden dynamical scale. This provides two standard model singlet hidden pions that can both be viewed as diphoton/diboson resonances produced by gluon fusion. We discuss several scenarios in which these (and other) resonances can be used to explain various excesses seen in the LHC data.« less

Radio for hidden-photon dark matter detection

DOE PAGES

Chaudhuri, Saptarshi; Graham, Peter W.; Irwin, Kent; ...

2015-10-08

We propose a resonant electromagnetic detector to search for hidden-photon dark matter over an extensive range of masses. Hidden-photon dark matter can be described as a weakly coupled “hidden electric field,” oscillating at a frequency fixed by the mass, and able to penetrate any shielding. At low frequencies (compared to the inverse size of the shielding), we find that the observable effect of the hidden photon inside any shielding is a real, oscillating magnetic field. We outline experimental setups designed to search for hidden-photon dark matter, using a tunable, resonant LC circuit designed to couple to this magnetic field. Ourmore » “straw man” setups take into consideration resonator design, readout architecture and noise estimates. At high frequencies, there is an upper limit to the useful size of a single resonator set by 1/ν. However, many resonators may be multiplexed within a hidden-photon coherence length to increase the sensitivity in this regime. Hidden-photon dark matter has an enormous range of possible frequencies, but current experiments search only over a few narrow pieces of that range. As a result, we find the potential sensitivity of our proposal is many orders of magnitude beyond current limits over an extensive range of frequencies, from 100 Hz up to 700 GHz and potentially higher.« less

PCSYS: The optimal design integration system picture drawing system with hidden line algorithm capability for aerospace vehicle configurations

NASA Technical Reports Server (NTRS)

Hague, D. S.; Vanderburg, J. D.

1977-01-01

A vehicle geometric definition based upon quadrilateral surface elements to produce realistic pictures of an aerospace vehicle. The PCSYS programs can be used to visually check geometric data input, monitor geometric perturbations, and to visualize the complex spatial inter-relationships between the internal and external vehicle components. PCSYS has two major component programs. The between program, IMAGE, draws a complex aerospace vehicle pictorial representation based on either an approximate but rapid hidden line algorithm or without any hidden line algorithm. The second program, HIDDEN, draws a vehicle representation using an accurate but time consuming hidden line algorithm.

The reported effects of bullying on burn-surviving children.

PubMed

Rimmer, Ruth B; Foster, Kevin N; Bay, Curtis R; Floros, Jim; Rutter, Cindy; Bosch, Jim; Wadsworth, Michelle M; Caruso, Daniel M

2007-01-01

There is a trend of increasing childhood aggression in America, which has been tied to bullying. Although there is growing research concerning bullying in the general pediatric population, there are limited data on bullying and its effects on children with disfigurements and physical limitations. This study was conducted to assess burned children's experience with bullying. A pretest was administered regarding experience with bullying and teasing. A curriculum regarding bullying, which incorporated the Harry Potter and the Sorcerer's Stone movie, was presented. After reviewing bullying depicted in the film and participating in a class regarding bullying, children were invited to complete a survey regarding their experience with bullying. A total of 61% of these children reported being bullied at school; 25% reported experiencing headaches or stomachaches due to bullying, and 12% reported staying home from school. Nearly 25% reported bullying as a big problem. Of those with visible scars (55%), a full 68% reported bullying as a problem, versus 54% with hidden scars (P < .05). However, those with visible scars were no more likely to tell an adult (54%) than those without (56%). Children were much more willing to disclose personal bullying experiences after participating in the class (57%) than before (45%) (P < .01). This study revealed that bullying impacts many burn-injured children and has negative effects on their physical and mental well-being. Many children (with visible or hidden scars) did not seek adult intervention for the problem. Participation in a bullying course appears to give children a forum that increases their willingness to disclose personal bullying experiences and can provide them with prevention information and a safe place to seek help.

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

Farina, Marco; Pappadopulo, Duccio; Ruderman, Joshua T.

A hidden sector with a mass gap undergoes an epoch of cannibalism if number changing interactions are active when the temperature drops below the mass of the lightest hidden particle. During cannibalism, the hidden sector temperature decreases only logarithmically with the scale factor. We consider the possibility that dark matter resides in a hidden sector that underwent cannibalism, and has relic density set by the freeze-out of two-to-two annihilations. We identify three novel phases, depending on the behavior of the hidden sector when dark matter freezes out. During the cannibal phase, dark matter annihilations decouple while the hidden sector ismore » cannibalizing. During the chemical phase, only two-to-two interactions are active and the total number of hidden particles is conserved. During the one way phase, the dark matter annihilation products decay out of equilibrium, suppressing the production of dark matter from inverse annihilations. We map out the distinct phenomenology of each phase, which includes a boosted dark matter annihilation rate, new relativistic degrees of freedom, warm dark matter, and observable distortions to the spectrum of the cosmic microwave background.« less

Phases of cannibal dark matter

NASA Astrophysics Data System (ADS)

Farina, Marco; Pappadopulo, Duccio; Ruderman, Joshua T.; Trevisan, Gabriele

2016-12-01

A hidden sector with a mass gap undergoes an epoch of cannibalism if number changing interactions are active when the temperature drops below the mass of the lightest hidden particle. During cannibalism, the hidden sector temperature decreases only logarithmically with the scale factor. We consider the possibility that dark matter resides in a hidden sector that underwent cannibalism, and has relic density set by the freeze-out of two-to-two annihilations. We identify three novel phases, depending on the behavior of the hidden sector when dark matter freezes out. During the cannibal phase, dark matter annihilations decouple while the hidden sector is cannibalizing. During the chemical phase, only two-to-two interactions are active and the total number of hidden particles is conserved. During the one way phase, the dark matter annihilation products decay out of equilibrium, suppressing the production of dark matter from inverse annihilations. We map out the distinct phenomenology of each phase, which includes a boosted dark matter annihilation rate, new relativistic degrees of freedom, warm dark matter, and observable distortions to the spectrum of the cosmic microwave background.

Phases of cannibal dark matter

DOE PAGES

Farina, Marco; Pappadopulo, Duccio; Ruderman, Joshua T.; ...

2016-12-13

A hidden sector with a mass gap undergoes an epoch of cannibalism if number changing interactions are active when the temperature drops below the mass of the lightest hidden particle. During cannibalism, the hidden sector temperature decreases only logarithmically with the scale factor. We consider the possibility that dark matter resides in a hidden sector that underwent cannibalism, and has relic density set by the freeze-out of two-to-two annihilations. We identify three novel phases, depending on the behavior of the hidden sector when dark matter freezes out. During the cannibal phase, dark matter annihilations decouple while the hidden sector ismore » cannibalizing. During the chemical phase, only two-to-two interactions are active and the total number of hidden particles is conserved. During the one way phase, the dark matter annihilation products decay out of equilibrium, suppressing the production of dark matter from inverse annihilations. We map out the distinct phenomenology of each phase, which includes a boosted dark matter annihilation rate, new relativistic degrees of freedom, warm dark matter, and observable distortions to the spectrum of the cosmic microwave background.« less

Generalization and capacity of extensively large two-layered perceptrons.

PubMed

Rosen-Zvi, Michal; Engel, Andreas; Kanter, Ido

2002-09-01

The generalization ability and storage capacity of a treelike two-layered neural network with a number of hidden units scaling as the input dimension is examined. The mapping from the input to the hidden layer is via Boolean functions; the mapping from the hidden layer to the output is done by a perceptron. The analysis is within the replica framework where an order parameter characterizing the overlap between two networks in the combined space of Boolean functions and hidden-to-output couplings is introduced. The maximal capacity of such networks is found to scale linearly with the logarithm of the number of Boolean functions per hidden unit. The generalization process exhibits a first-order phase transition from poor to perfect learning for the case of discrete hidden-to-output couplings. The critical number of examples per input dimension, alpha(c), at which the transition occurs, again scales linearly with the logarithm of the number of Boolean functions. In the case of continuous hidden-to-output couplings, the generalization error decreases according to the same power law as for the perceptron, with the prefactor being different.

Sound Science: Taking Action with Acoustics

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

Sinha, Dipen

2014-07-16

From tin whistles to sonic booms, sound waves interact with each other and with the medium through which they travel. By observing these interactions, we can identify substances that are hidden in sealed containers and obtain images of buried objects. By manipulating the ability of sound to push matter around, we can create novel structures and unique materials. Join the Lab's own sound hound, Dipen Sinha, as he describes how he uses fundamental research in acoustics for solving problems in industry, security and health.

Sound Science: Taking Action with Acoustics

ScienceCinema

Sinha, Dipen

2018-01-16

From tin whistles to sonic booms, sound waves interact with each other and with the medium through which they travel. By observing these interactions, we can identify substances that are hidden in sealed containers and obtain images of buried objects. By manipulating the ability of sound to push matter around, we can create novel structures and unique materials. Join the Lab's own sound hound, Dipen Sinha, as he describes how he uses fundamental research in acoustics for solving problems in industry, security and health.

Inference of Stochastic Nonlinear Oscillators with Applications to Physiological Problems

NASA Technical Reports Server (NTRS)

Smelyanskiy, Vadim N.; Luchinsky, Dmitry G.

2004-01-01

A new method of inferencing of coupled stochastic nonlinear oscillators is described. The technique does not require extensive global optimization, provides optimal compensation for noise-induced errors and is robust in a broad range of dynamical models. We illustrate the main ideas of the technique by inferencing a model of five globally and locally coupled noisy oscillators. Specific modifications of the technique for inferencing hidden degrees of freedom of coupled nonlinear oscillators is discussed in the context of physiological applications.

Effect of design selection on response surface performance

NASA Technical Reports Server (NTRS)

Carpenter, William C.

1993-01-01

Artificial neural nets and polynomial approximations were used to develop response surfaces for several test problems. Based on the number of functional evaluations required to build the approximations and the number of undetermined parameters associated with the approximations, the performance of the two types of approximations was found to be comparable. A rule of thumb is developed for determining the number of nodes to be used on a hidden layer of an artificial neural net and the number of designs needed to train an approximation is discussed.

Development and application of deep convolutional neural network in target detection

NASA Astrophysics Data System (ADS)

Jiang, Xiaowei; Wang, Chunping; Fu, Qiang

2018-04-01

With the development of big data and algorithms, deep convolution neural networks with more hidden layers have more powerful feature learning and feature expression ability than traditional machine learning methods, making artificial intelligence surpass human level in many fields. This paper first reviews the development and application of deep convolutional neural networks in the field of object detection in recent years, then briefly summarizes and ponders some existing problems in the current research, and the future development of deep convolutional neural network is prospected.

Hidden order in crackling noise during peeling of an adhesive tape.

PubMed

Kumar, Jagadish; Ciccotti, M; Ananthakrishna, G

2008-04-01

We address the longstanding problem of recovering dynamical information from noisy acoustic emission signals arising from peeling of an adhesive tape subject to constant traction velocity. Using the phase space reconstruction procedure we demonstrate the deterministic chaotic dynamics by establishing the existence of correlation dimension as also a positive Lyapunov exponent in a midrange of traction velocities. The results are explained on the basis of the model that also emphasizes the deterministic origin of acoustic emission by clarifying its connection to stick-slip dynamics.

Are the binary typology models of alcoholism valid in polydrug abusers?

PubMed

Pombo, Samuel; da Costa, Nuno F; Figueira, Maria L

2015-01-01

To evaluate the dichotomy of type I/II and type A/B alcoholism typologies in opiate-dependent patients with a comorbid alcohol dependence problem (ODP-AP). The validity assessment process comprised the information regarding the history of alcohol use (internal validity), cognitive-behavioral variables regarding substance use (external validity), and indicators of treatment during 6-month follow-up (predictive validity). ODP-AP subjects classified as type II/B presented an early and much more severe drinking problem and a worse clinical prognosis when considering opiate treatment variables as compared with ODP-AP subjects defined as type I/A. Furthermore, type II/B patients endorse more general positive beliefs and expectancies related to the effect of alcohol and tend to drink heavily across several intra- and interpersonal situations as compared with type I/A patients. These findings confirm two different forms of alcohol dependence, recognized as a low-severity/vulnerability subgroup and a high-severity/vulnerability subgroup, in an opiate-dependent population with a lifetime diagnosis of alcohol dependence.

Biogeography-based particle swarm optimization with fuzzy elitism and its applications to constrained engineering problems

NASA Astrophysics Data System (ADS)

Guo, Weian; Li, Wuzhao; Zhang, Qun; Wang, Lei; Wu, Qidi; Ren, Hongliang

2014-11-01

In evolutionary algorithms, elites are crucial to maintain good features in solutions. However, too many elites can make the evolutionary process stagnate and cannot enhance the performance. This article employs particle swarm optimization (PSO) and biogeography-based optimization (BBO) to propose a hybrid algorithm termed biogeography-based particle swarm optimization (BPSO) which could make a large number of elites effective in searching optima. In this algorithm, the whole population is split into several subgroups; BBO is employed to search within each subgroup and PSO for the global search. Since not all the population is used in PSO, this structure overcomes the premature convergence in the original PSO. Time complexity analysis shows that the novel algorithm does not increase the time consumption. Fourteen numerical benchmarks and four engineering problems with constraints are used to test the BPSO. To better deal with constraints, a fuzzy strategy for the number of elites is investigated. The simulation results validate the feasibility and effectiveness of the proposed algorithm.

Out of Reach, Out of Mind? Infants' Comprehension of References to Hidden Inaccessible Objects.

PubMed

Osina, Maria A; Saylor, Megan M; Ganea, Patricia A

2017-09-01

This study investigated the nature of infants' difficulty understanding references to hidden inaccessible objects. Twelve-month-old infants (N = 32) responded to the mention of objects by looking at, pointing at, or approaching them when the referents were visible or accessible, but not when they were hidden and inaccessible (Experiment I). Twelve-month-olds (N = 16) responded robustly when a container with the hidden referent was moved from a previously inaccessible position to an accessible position before the request, but failed to respond when the reverse occurred (Experiment II). This suggests that infants might be able to track the hidden object's dislocations and update its accessibility as it changes. Knowing the hidden object is currently inaccessible inhibits their responding. Older, 16-month-old (N = 17) infants' performance was not affected by object accessibility. © 2016 The Authors. Child Development © 2016 Society for Research in Child Development, Inc.

Emotional and behavioral problems among adolescent students: the role of immigrant, racial/ethnic congruence and belongingness in schools.

PubMed

Georgiades, Katholiki; Boyle, Michael H; Fife, Kelly A

2013-09-01

As levels of immigration and ethnic diversity continue to rise in most Western societies, the social demography of schools is changing rapidly. Although schools represent a prominent developmental context, relatively little is known about the extent to which the racial/ethnic composition of schools influences mental health outcomes in students. The objective of the present study is to examine the association between immigrant and racial/ethnic congruence in school-the numerical representation of a student's immigrant generational status and race/ethnicity in the student body-and levels of emotional and behavioral problems. This study also examines the extent to which the association between congruence and emotional-behavioral problems differs across racial/ethnic immigrant sub-groups and is accounted for by individual perceptions of school belonging. Data come from the in-school survey of the Longitudinal Study of Adolescent Health (Add Health) conducted in the United States. The sample is nationally representative, and includes 128 schools and 77,150 adolescents in grades 7-12 (50 % female, M age = 14.9 years, SD = 1.78). After controlling for school and family socio-demographic characteristics, immigrant and racial/ethnic congruence in school exhibited a negative association with emotional and behavioral problems for most sub-groups examined. School belonging was associated negatively with emotional and behavioral problems, and partially accounted for the effects linked to congruence in schools. The immigrant and racial/ethnic composition of schools and perceptions of belonging have strong links with emotional and behavioral problems and may represent important targets for intervention.

[A way of helping "Mr. Minotaur" and "Ms. Ariadne" to exit from the multiple morbidity labyrinth: the "master problems"].

PubMed

Turabián, J L; Pérez Franco, B

2016-01-01

Multiple morbidity seems to be "infinite" and so is not easy to make useful decisions. A new concept is introduced: the "master problems", as a qualitative method to facilitate the exit from this maze of multiple morbidity. Metaphors from the art world have been used to teach this concept. These "master problems" generally remain hidden and can only "unravel" between the interstices of multiple morbidity, when the details of the system that defines the problem are explained. A problem with "energy" or a "master problem" is complex, multiple and dramatic or theatrical--everything in the clinical history history make us look into that particular question. It is what gives us a blow to the stomach, which causes our hearts to beat faster, that moves us on many levels, which has a high "density of emotions", human elements, social symbols, and opens solutions in a patient. Copyright © 2015 Sociedad Española de Médicos de Atención Primaria (SEMERGEN). Publicado por Elsevier España, S.L.U. All rights reserved.

Poor Prognosis of Lower Inner Quadrant in Lymph Node-negative Breast Cancer Patients Who Received No Chemotherapy: A Study Based on Nationwide Korean Breast Cancer Registry Database.

PubMed

Hwang, Ki-Tae; Kim, Jongjin; Kim, Eun-Kyu; Jung, Sung Hoo; Sohn, Guiyun; Kim, Seung Il; Jeong, Joon; Lee, Hyouk Jin; Park, Jin Hyun; Oh, Sohee

2017-07-01

We aimed to investigate the prognostic influence of primary tumor site on the survival of patients with breast cancer. Data of 63,388 patients with primary breast cancer from the Korean Breast Cancer Registry were analyzed. Primary tumor sites were classified into 5 groups: upper outer quadrant, lower outer quadrant, upper inner quadrant, lower inner quadrant (LIQ), and central portion. We analyzed overall survival (OS) and breast cancer-specific survival (BCSS) according to primary tumor site. Central portion and LIQ showed lower survival rates regarding both OS and BCSS compared with the other 3 quadrants (all P < .05) and hazard ratios were 1.267 (95% CI, 1.180-1.360, P < .001) and 1.215 (95% CI, 1.097-1.345, P < .001), respectively. Although central portion showed more unfavorable clinicopathologic features, LIQ showed more favorable features than the other 3 quadrants. Primary tumor site was a significant factor in univariate and multivariate analyses for OS and BCSS (all P < .001). For lymph node-negative patients, LIQ showed a worse OS than the other primary tumor sites in the subgroup with no chemotherapy (P < .001), but that effect disappeared in the subgroup with chemotherapy (P = .058). LIQ showed a worse prognosis despite having more favorable clinicopathologic features than other tumor locations and it was more prominent for lymph node-negative patients who received no chemotherapy. The hypothesis of possible hidden internal mammary node metastasis could be suggested to play a key role in LIQ lesions. Copyright © 2017 Elsevier Inc. All rights reserved.

Quantum learning of classical stochastic processes: The completely positive realization problem

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

Monràs, Alex; Centre for Quantum Technologies, National University of Singapore, 3 Science Drive 2, Singapore 117543; Winter, Andreas

2016-01-15

Among several tasks in Machine Learning, a specially important one is the problem of inferring the latent variables of a system and their causal relations with the observed behavior. A paradigmatic instance of this is the task of inferring the hidden Markov model underlying a given stochastic process. This is known as the positive realization problem (PRP), [L. Benvenuti and L. Farina, IEEE Trans. Autom. Control 49(5), 651–664 (2004)] and constitutes a central problem in machine learning. The PRP and its solutions have far-reaching consequences in many areas of systems and control theory, and is nowadays an important piece inmore » the broad field of positive systems theory. We consider the scenario where the latent variables are quantum (i.e., quantum states of a finite-dimensional system) and the system dynamics is constrained only by physical transformations on the quantum system. The observable dynamics is then described by a quantum instrument, and the task is to determine which quantum instrument — if any — yields the process at hand by iterative application. We take as a starting point the theory of quasi-realizations, whence a description of the dynamics of the process is given in terms of linear maps on state vectors and probabilities are given by linear functionals on the state vectors. This description, despite its remarkable resemblance with the hidden Markov model, or the iterated quantum instrument, is however devoid of any stochastic or quantum mechanical interpretation, as said maps fail to satisfy any positivity conditions. The completely positive realization problem then consists in determining whether an equivalent quantum mechanical description of the same process exists. We generalize some key results of stochastic realization theory, and show that the problem has deep connections with operator systems theory, giving possible insight to the lifting problem in quotient operator systems. Our results have potential applications in quantum machine learning, device-independent characterization and reverse-engineering of stochastic processes and quantum processors, and more generally, of dynamical processes with quantum memory [M. Guţă, Phys. Rev. A 83(6), 062324 (2011); M. Guţă and N. Yamamoto, e-print http://arxiv.org/abs/1303.3771 (2013)].« less

Characterization of skin reactions and pain reported by patients receiving radiation therapy for cancer at different sites

PubMed Central

Gewandter, Jennifer S.; Walker, Joanna; Heckler, Charles E.; Morrow, Gary R.; Ryan, Julie L.

2015-01-01

Background Skin reactions and pain are commonly reported side effects of radiation therapy (RT). Objective To characterize RT-induced symptoms according to treatment site subgroups and identify skin symptoms that correlate with pain. Methods A self-report survey, adapted from the MD Anderson Symptom Inventory and the McGill Pain Questionnaire, assessed RT-induced skin problems, pain, and specific skin symptoms. Wilcoxon Sign Ranked tests compared mean severity of pre- and post-RT pain and skin problems within each RT-site subgroup. Multiple linear regression (MLR) investigated associations between skin symptoms and pain. Results Survey respondents (n=106) were 58% female and on average 64 years old. RT sites included lung, breast, lower abdomen, head/neck/brain, and upper abdomen. Only patients receiving breast RT reported significant increases in treatment site pain and skin problems (p≤0.007). Patients receiving head/neck/brain RT reported increased skin problems (p<0.0009). MLR showed that post-RT skin tenderness and tightness were most strongly associated with post-RT pain (p=0.066 and p=0.122, respectively). Limitations Small sample size, exploratory analyses, and non-validated measure. Conclusions Only patients receiving breast RT reported significant increases in pain and skin problems at the RT site, while patients receiving head/neck/brain RT had increased skin problems, but not pain. These findings suggest that the severity of skin problems is not the only factor that contributes to pain, and interventions should be tailored to specifically target pain at the RT site, possibly by targeting tenderness and tightness. These findings should be confirmed in a larger sampling of RT patients. PMID:24645338

Learning and inference in a nonequilibrium Ising model with hidden nodes.

PubMed

Dunn, Benjamin; Roudi, Yasser

2013-02-01

We study inference and reconstruction of couplings in a partially observed kinetic Ising model. With hidden spins, calculating the likelihood of a sequence of observed spin configurations requires performing a trace over the configurations of the hidden ones. This, as we show, can be represented as a path integral. Using this representation, we demonstrate that systematic approximate inference and learning rules can be derived using dynamical mean-field theory. Although naive mean-field theory leads to an unstable learning rule, taking into account Gaussian corrections allows learning the couplings involving hidden nodes. It also improves learning of the couplings between the observed nodes compared to when hidden nodes are ignored.

Radiographic hand osteoarthritis: patterns and associations with hand pain and function in a community-dwelling sample.

PubMed

Marshall, M; van der Windt, D; Nicholls, E; Myers, H; Hay, E; Dziedzic, K

2009-11-01

Patterns of radiographic osteoarthritis (ROA) of the hand are often examined by row, with the four joints of the thumb studied inconsistently. The objectives of this study were to determine relationships of ROA at different hand joints, use the findings to define radiographic sub-groups and investigate their associations with pain and function. Sixteen joints in each hand were scored for the presence of ROA in a community-dwelling cohort of adults, 50-years-and-over, with self-reported hand pain or problems. Principal components analysis (PCA) with varimax rotation was used to study patterns of ROA in the hand joints and identify distinct sub-groups. Differences in pain and function between these sub-groups were assessed using Australian/Canadian Osteoarthritis Index (AUSCAN), Grip Ability Test (GAT) and grip and pinch strength. PCA was undertaken on data from 592 participants and identified four components: distal interphalangeal joints (DIPs), proximal interphalangeal joints (PIPs), metacarpophalangeal joints (MCPs), thumb joints. However, the left thumb interphalangeal (IP) joint cross-loaded with the PIP and thumb groups. On this basis, participants were categorised into four radiographic sub-groups: no osteoarthritis (OA), finger only OA, thumb only OA and combined thumb and finger OA. Statistically significant differences were found between the sub-groups for AUSCAN function, and in women alone for grip and pinch strength. Participants with combined thumb and finger OA had the worst scores. Individual thumb joints can be clustered together as a joint group in ROA. Four radiographic sub-groups of hand OA can be distinguished. Pain and functional difficulties were highest in participants with both thumb and finger OA.

A Computer-Aided Instruction Program for Teaching the TOPS20-MM Facility on the DDN (Defense Data Network)

DTIC Science & Technology

1988-06-01

Continue on reverse if necessary and identify by block number) FIELD GROUP SUB-GROUP Computer Assisted Instruction; Artificial Intelligence 194...while he/she tries to perform given tasks. Means-ends analysis, a classic technique for solving search problems in Artificial Intelligence, has been...he/she tries to perform given tasks. Means-ends analysis, a classic technique for solving search problems in Artificial Intelligence, has been used

Controller-reported performance defects in the air traffic control radar beacon system (1971 survey)

DOT National Transportation Integrated Search

1973-03-01

This report analyzes the returns from a recent ATC performance survey initiated by the Beacon System Interference Problem Subgroup. The survey began on the 27 November 1971 and lasted for two weeks. Participatione was limited to 37 facilities with pr...

Bench-to-bedside review: Avoiding pitfalls in critical care meta-analysis – funnel plots, risk estimates, types of heterogeneity, baseline risk and the ecologic fallacy

PubMed Central

Reade, Michael C; Delaney, Anthony; Bailey, Michael J; Angus, Derek C

2008-01-01

Meta-analysis can be a powerful tool for demonstrating the applicability of a concept beyond the context of individual clinical trials and observational studies, including exploration of effects across different subgroups. Meta-analysis avoids Simpson's paradox, in which a consistent effect in constituent trials is reversed when results are simply pooled. Meta-analysis in critical care medicine is made more complicated, however, by the heterogeneous nature of critically ill patients and the contexts within which they are treated. Failure to properly adjust for this heterogeneity risks missing important subgroup effects in, for example, the interaction of treatment with varying levels of baseline risk. When subgroups are defined by characteristics that vary within constituent trials (such as age) rather than features constant within each trial (such as drug dose), there is the additional risk of incorrect conclusions due to the ecological fallacy. The present review explains these problems and the strategies by which they are overcome. PMID:18671838

Differentiating subgroups of children with special health care needs by health status and complexity of health care needs.

PubMed

Bramlett, Matthew D; Read, Debra; Bethell, Christina; Blumberg, Stephen J

2009-03-01

Our objective is to use the Children with Special Health Care Needs (CSHCN) Screener to identify subgroups of CSHCN differentiated by health status and complexity of need. Data are from the National Survey of Children with Special Health Care Needs, 2001 and the National Survey of Children's Health, 2003 (conducted by the Maternal and Child Health Bureau and the National Center for Health Statistics); and the 2001 and 2002 Medical Expenditure Panel Survey, conducted by the Agency for Healthcare Research and Quality. A broad array of variables measuring health status, complexity of need, and related issues are examined by subgroupings of CSHCN. Relative to other CSHCN, CSHCN with functional limitations or who qualify on more CSHCN Screener items have poorer health status and more complex health care needs. They more often experience a variety of health issues; their insurance is more often inadequate; the impact of their conditions on their families is higher; and their medical costs are higher. In the absence of information on specific conditions, health status, or complexity of need, the CSHCN Screener alone can be used to create useful analytic subgroups that differ on these dimensions. The proposed subgroups, based on the type or number of CSHCN screening criteria, differentiate CSHCN by health status and complexity of health care needs, and also show differences in the impact of their conditions on their families, costs of their medical care, and prevalence of various health problems.

Behavioral approach and avoidance in schizophrenia: an evaluation of motivational profiles.

PubMed

Felice Reddy, L; Green, Michael F; Rizzo, Shemra; Sugar, Catherine A; Blanchard, Jack J; Gur, Raquel E; Kring, Ann M; Horan, William P

2014-10-01

Schizophrenia is associated with motivational deficits that interfere with a wide range of goal directed activities. Despite their clinical importance, our current understanding of these motivational impairments is limited. Furthermore, different types of motivational problems are commonly seen among individuals within the broad diagnosis of schizophrenia. The goal of the current study was to examine whether clinically meaningful subgroups could be identified based on approach and avoidance motivational tendencies. We measured these tendencies in 151 individuals with schizophrenia. Although prior studies demonstrate elevated BIS sensitivity in schizophrenia at the overall group level, none have explored various combinations of BIS/BAS sensitivities within this disorder. Cluster analyses yielded five subgroups with different combinations of low, moderate, or high BIS and BAS. The subgroups had interpretable differences in clinically rated negative symptoms and self-reported anhedonia/socio-emotional attitudes, which were not detectable with the more commonly used linear BIS/BAS scores. Two of the subgroups had significantly elevated negative symptoms but different approach/avoidance profiles: one was characterized by markedly low BIS, low BAS and an overall lack of social approach motivation; the other had markedly high BIS but moderate BAS and elevated social avoidance motivation. The two subgroups with relatively good clinical functioning showed patterns of BAS greater than BIS. Our findings indicate that there are distinct motivational pathways that can lead to asociality in schizophrenia and highlight the value of considering profiles based on combined patterns of BIS and BAS in schizophrenia. Published by Elsevier B.V.

Low home ventilation rate in combination with moldy odor from the building structure increase the risk for allergic symptoms in children.

PubMed

Hägerhed-Engman, L; Sigsgaard, T; Samuelson, I; Sundell, J; Janson, S; Bornehag, C-G

2009-06-01

There are consistent findings on associations between asthma and allergy symptoms and residential mold and moisture. However, definitions of 'dampness' in studies are diverse because of differences in climate and building construction. Few studies have estimated mold problems inside the building structure by odor assessments. In a nested case-control study of 400 Swedish children, observations and measurements were performed in their homes by inspectors, and the children were examined by physicians for diagnoses of asthma, eczema, and rhinitis. In conclusion, we found an association between moldy odor along the skirting board and allergic symptoms among children, mainly rhinitis. No associations with any of the allergic symptoms were found for discoloured stains, 'floor dampness' or a general mold odor in the room. A moldy odor along the skirting board can be a proxy for hidden moisture problem inside the outer wall construction or in the foundation construction. There are indications that such dampness problems increase the risk for sensitization but the interpretation of data in respect of sensitization is difficult as about 80% of the children with rhinitis were sensitized. Furthermore, low ventilation rate in combination with moldy odor along the skirting board further increased the risk for three out of four studied outcomes, indicating that the ventilation rate is an effect modifier for indoor pollutants. This study showed that mold odor at the skirting board level is strongly associated with allergic symptoms among children. Such odor at that specific place can be seen as a proxy for some kind of hidden moisture or mold problem in the building structure, such as the foundation or wooden ground beam. In houses with odor along the skirting board, dismantling of the structure is required for an investigation of possible moisture damage, measurements, and choice of actions. In homes with low ventilation in combination with mold odor along the skirting board, there was even a higher risk of health effects. This emphasizes the need for the appropriate remediation as this is an ever increasing problem in poorly ventilated houses that are damp.

Life imitating art: depictions of the hidden curriculum in medical television programs.

PubMed

Stanek, Agatha; Clarkin, Chantalle; Bould, M Dylan; Writer, Hilary; Doja, Asif

2015-09-26

The hidden curriculum represents influences occurring within the culture of medicine that indirectly alter medical professionals' interactions, beliefs and clinical practices throughout their training. One approach to increase medical student awareness of the hidden curriculum is to provide them with readily available examples of how it is enacted in medicine; as such the purpose of this study was to examine depictions of the hidden curriculum in popular medical television programs. One full season of ER, Grey's Anatomy and Scrubs were selected for review. A summative content analysis was performed to ascertain the presence of depictions of the hidden curriculum, as well as to record the type, frequency and quality of examples. A second reviewer also viewed a random selection of episodes from each series to establish coding reliability. The most prevalent themes across all television programs were: the hierarchical nature of medicine; challenges during transitional stages in medicine; the importance of role modeling; patient dehumanization; faking or overstating one's capabilities; unprofessionalism; the loss of idealism; and difficulties with work-life balance. The hidden curriculum is frequently depicted in popular medical television shows. These examples of the hidden curriculum could serve as a valuable teaching resource in undergraduate medical programs.

Uncovering hidden nodes in complex networks in the presence of noise

PubMed Central

Su, Ri-Qi; Lai, Ying-Cheng; Wang, Xiao; Do, Younghae

2014-01-01

Ascertaining the existence of hidden objects in a complex system, objects that cannot be observed from the external world, not only is curiosity-driven but also has significant practical applications. Generally, uncovering a hidden node in a complex network requires successful identification of its neighboring nodes, but a challenge is to differentiate its effects from those of noise. We develop a completely data-driven, compressive-sensing based method to address this issue by utilizing complex weighted networks with continuous-time oscillatory or discrete-time evolutionary-game dynamics. For any node, compressive sensing enables accurate reconstruction of the dynamical equations and coupling functions, provided that time series from this node and all its neighbors are available. For a neighboring node of the hidden node, this condition cannot be met, resulting in abnormally large prediction errors that, counterintuitively, can be used to infer the existence of the hidden node. Based on the principle of differential signal, we demonstrate that, when strong noise is present, insofar as at least two neighboring nodes of the hidden node are subject to weak background noise only, unequivocal identification of the hidden node can be achieved. PMID:24487720

On Parametrization of the Linear GL(4,C) and Unitary SU(4) Groups in Terms of Dirac Matrices

NASA Astrophysics Data System (ADS)

Red'Kov, Victor M.; Bogush, Andrei A.; Tokarevskaya, Natalia G.

2008-02-01

Parametrization of 4 × 4-matrices G of the complex linear group GL(4,C) in terms of four complex 4-vector parameters (k,m,n,l) is investigated. Additional restrictions separating some subgroups of GL(4,C) are given explicitly. In the given parametrization, the problem of inverting any 4 × 4 matrix G is solved. Expression for determinant of any matrix G is found: det G = F(k,m,n,l). Unitarity conditions G+ = G-1 have been formulated in the form of non-linear cubic algebraic equations including complex conjugation. Several simplest solutions of these unitarity equations have been found: three 2-parametric subgroups G1, G2, G3 - each of subgroups consists of two commuting Abelian unitary groups; 4-parametric unitary subgroup consis! ting of a product of a 3-parametric group isomorphic SU(2) and 1-parametric Abelian group. The Dirac basis of generators Λk, being of Gell-Mann type, substantially differs from the basis λi used in the literature on SU(4) group, formulas relating them are found - they permit to separate SU(3) subgroup in SU(4). Special way to list 15 Dirac generators of GL(4,C) can be used {Λk} = {μiÅνjÅ(μiVνj = KÅL ÅM )}, which permit to factorize SU(4) transformations according to S = eiaμ eibνeikKeilLeimM, where two first factors commute with each other and are isomorphic to SU(2) group, the three last ones are 3-parametric groups, each of them consisting of three Abelian commuting unitary subgroups. Besides, the structure of fifteen Dirac matrices Λk permits to separate twenty 3-parametric subgroups in SU(4) isomorphic to SU(2); those subgroups might be used as bigger elementary blocks in constructing of a general transformation SU(4). It is shown how one can specify the present approach for the pseudounitary group SU(2,2) and SU(3,1).

Nurse faculty experiences in problem-based learning: an interpretive phenomenologic analysis.

PubMed

Paige, Jane B; Smith, Regina O

2013-01-01

This study explored the nurse faculty experience of participating in a problem-based learning (PBL) faculty development program. Utilizing PBL as a pedagogical method requires a paradigm shift in the way faculty think about teaching, learning, and the teacher-student relationship. An interpretive phenomenological analysis approach was used to explore the faculty experience in a PBL development program. Four themes emerged: change in perception of the teacher-student relationship, struggle in letting go, uncertainty, and valuing PBL as a developmental process. Epistemic doubt happens when action and intent toward the PBL teaching perspective do not match underlying beliefs. Findings from this study call for ongoing administrative support for education on PBL while faculty take time to uncover hidden epistemological beliefs.

Solving the quantum many-body problem with artificial neural networks

NASA Astrophysics Data System (ADS)

Carleo, Giuseppe; Troyer, Matthias

2017-02-01

The challenge posed by the many-body problem in quantum physics originates from the difficulty of describing the nontrivial correlations encoded in the exponential complexity of the many-body wave function. Here we demonstrate that systematic machine learning of the wave function can reduce this complexity to a tractable computational form for some notable cases of physical interest. We introduce a variational representation of quantum states based on artificial neural networks with a variable number of hidden neurons. A reinforcement-learning scheme we demonstrate is capable of both finding the ground state and describing the unitary time evolution of complex interacting quantum systems. Our approach achieves high accuracy in describing prototypical interacting spins models in one and two dimensions.

On integrability of the Killing equation

NASA Astrophysics Data System (ADS)

Houri, Tsuyoshi; Tomoda, Kentaro; Yasui, Yukinori

2018-04-01

Killing tensor fields have been thought of as describing the hidden symmetry of space(-time) since they are in one-to-one correspondence with polynomial first integrals of geodesic equations. Since many problems in classical mechanics can be formulated as geodesic problems in curved space and spacetime, solving the defining equation for Killing tensor fields (the Killing equation) is a powerful way to integrate equations of motion. Thus it has been desirable to formulate the integrability conditions of the Killing equation, which serve to determine the number of linearly independent solutions and also to restrict the possible forms of solutions tightly. In this paper, we show the prolongation for the Killing equation in a manner that uses Young symmetrizers. Using the prolonged equations, we provide the integrability conditions explicitly.

Mathematical characterization of mechanical behavior of porous frictional granular media

NASA Technical Reports Server (NTRS)

Chung, T. J.; Lee, J. K.

1972-01-01

A new definition of loading and unloading along the yield surface of Roscoe and Burland is introduced. This is achieved by noting that the strain-hardening parameter in the plastic potential function is deduced from the yield locus equation of Roscoe and Burland. The analytical results are compared with the experimental results for plate-bearing and cone-penetrometer problems and close agreements are demonstrated. The wheel-soil interaction is studied under dynamic loading. The rate-dependent plasticity or viscoelastoplastic behavior is considered. This is accomplished by the internal (hidden) variables associated with time-dependent viscous properties directly superimposed with inelastic behavior governed by the yield criteria of Roscoe and Burland. Effects of inertia and energy dissipation are properly accounted for. Example problems are presented.

Domestic horses send signals to humans when they face with an unsolvable task.

PubMed

Ringhofer, Monamie; Yamamoto, Shinya

2017-05-01

Some domestic animals are thought to be skilled at social communication with humans due to the process of domestication. Horses, being in close relationship with humans, similar to dogs, might be skilled at communication with humans. Previous studies have indicated that they are sensitive to bodily signals and the attentional state of humans; however, there are few studies that investigate communication with humans and responses to the knowledge state of humans. Our first question was whether and how horses send signals to their potentially helpful but ignorant caretakers in a problem-solving situation where a food item was hidden in a bucket that was accessible only to the caretakers. We then examined whether horses alter their behaviours on the basis of the caretakers' knowledge of where the food was hidden. We found that horses communicated to their caretakers using visual and tactile signals. The signalling behaviour of the horses significantly increased in conditions where the caretakers had not seen the hiding of the food. These results suggest that horses alter their communicative behaviour towards humans in accordance with humans' knowledge state.

Variables in psychology: a critique of quantitative psychology.

PubMed

Toomela, Aaro

2008-09-01

Mind is hidden from direct observation; it can be studied only by observing behavior. Variables encode information about behaviors. There is no one-to-one correspondence between behaviors and mental events underlying the behaviors, however. In order to understand mind it would be necessary to understand exactly what information is represented in variables. This aim cannot be reached after variables are already encoded. Therefore, statistical data analysis can be very misleading in studies aimed at understanding mind that underlies behavior. In this article different kinds of information that can be represented in variables are described. It is shown how informational ambiguity of variables leads to problems of theoretically meaningful interpretation of the results of statistical data analysis procedures in terms of hidden mental processes. Reasons are provided why presence of dependence between variables does not imply causal relationship between events represented by variables and absence of dependence between variables cannot rule out the causal dependence of events represented by variables. It is concluded that variable-psychology has a very limited range of application for the development of a theory of mind-psychology.

Feature to prototype transition in neural networks

NASA Astrophysics Data System (ADS)

Krotov, Dmitry; Hopfield, John

Models of associative memory with higher order (higher than quadratic) interactions, and their relationship to neural networks used in deep learning are discussed. Associative memory is conventionally described by recurrent neural networks with dynamical convergence to stable points. Deep learning typically uses feedforward neural nets without dynamics. However, a simple duality relates these two different views when applied to problems of pattern classification. From the perspective of associative memory such models deserve attention because they make it possible to store a much larger number of memories, compared to the quadratic case. In the dual description, these models correspond to feedforward neural networks with one hidden layer and unusual activation functions transmitting the activities of the visible neurons to the hidden layer. These activation functions are rectified polynomials of a higher degree rather than the rectified linear functions used in deep learning. The network learns representations of the data in terms of features for rectified linear functions, but as the power in the activation function is increased there is a gradual shift to a prototype-based representation, the two extreme regimes of pattern recognition known in cognitive psychology. Simons Center for Systems Biology.

Speakable and Unspeakable in Quantum Mechanics

NASA Astrophysics Data System (ADS)

Bell, J. S.; Aspect, Introduction by Alain

2004-06-01

List of papers on quantum philosophy by J. S. Bell; Preface; Acknowledgements; Introduction by Alain Aspect; 1. On the problem of hidden variables in quantum mechanics; 2. On the Einstein-Rosen-Podolsky paradox; 3. The moral aspects of quantum mechanics; 4. Introduction to the hidden-variable question; 5. Subject and object; 6. On wave packet reduction in the Coleman-Hepp model; 7. The theory of local beables; 8. Locality in quantum mechanics: reply to critics; 9. How to teach special relativity; 10. Einstein-Podolsky-Rosen experiments; 11. The measurement theory of Everett and de Broglie's pilot wave; 12. Free variables and local causality; 13. Atomic-cascade photons and quantum-mechanical nonlocality; 14. de Broglie-Bohm delayed choice double-slit experiments and density matrix; 15. Quantum mechanics for cosmologists; 16. Bertlmann's socks and the nature of reality; 17. On the impossible pilot wave; 18. Speakable and unspeakable in quantum mechanics; 19. Beables for quantum field theory; 20. Six possible worlds of quantum mechanics; 21. EPR correlations and EPR distributions; 22. Are there quantum jumps?; 23. Against 'measurement'; 24. La Nouvelle cuisine.

Short-term prediction of chaotic time series by using RBF network with regression weights.

PubMed

Rojas, I; Gonzalez, J; Cañas, A; Diaz, A F; Rojas, F J; Rodriguez, M

2000-10-01

We propose a framework for constructing and training a radial basis function (RBF) neural network. The structure of the gaussian functions is modified using a pseudo-gaussian function (PG) in which two scaling parameters sigma are introduced, which eliminates the symmetry restriction and provides the neurons in the hidden layer with greater flexibility with respect to function approximation. We propose a modified PG-BF (pseudo-gaussian basis function) network in which the regression weights are used to replace the constant weights in the output layer. For this purpose, a sequential learning algorithm is presented to adapt the structure of the network, in which it is possible to create a new hidden unit and also to detect and remove inactive units. A salient feature of the network systems is that the method used for calculating the overall output is the weighted average of the output associated with each receptive field. The superior performance of the proposed PG-BF system over the standard RBF are illustrated using the problem of short-term prediction of chaotic time series.

A new learning paradigm: learning using privileged information.

PubMed

Vapnik, Vladimir; Vashist, Akshay

2009-01-01

In the Afterword to the second edition of the book "Estimation of Dependences Based on Empirical Data" by V. Vapnik, an advanced learning paradigm called Learning Using Hidden Information (LUHI) was introduced. This Afterword also suggested an extension of the SVM method (the so called SVM(gamma)+ method) to implement algorithms which address the LUHI paradigm (Vapnik, 1982-2006, Sections 2.4.2 and 2.5.3 of the Afterword). See also (Vapnik, Vashist, & Pavlovitch, 2008, 2009) for further development of the algorithms. In contrast to the existing machine learning paradigm where a teacher does not play an important role, the advanced learning paradigm considers some elements of human teaching. In the new paradigm along with examples, a teacher can provide students with hidden information that exists in explanations, comments, comparisons, and so on. This paper discusses details of the new paradigm and corresponding algorithms, introduces some new algorithms, considers several specific forms of privileged information, demonstrates superiority of the new learning paradigm over the classical learning paradigm when solving practical problems, and discusses general questions related to the new ideas.

Biological energy sources: the surface energy and the physical chemistry of water. Examples from studies on muscle contraction.

PubMed

Widdas, W F; Baker, G F

2004-01-01

The physical chemistry of water at nanometre dimensions was used to explain the conformational changes and water breaking properties of the glucose transporter protein (GLUTI) in human erythrocytes more than ten years ago. The energy for this hidden work arises from cycles of evaporation and condensation of water within the cells but was several times larger than resting metabolism. Physical chemical principles can quantify the hidden work done and demonstrate that a significant source of energy is available, which is free of the metabolic energy derived from the hydrolysis of ATP. Therefore, a more widespread biological use of this "free" energy source was probable and a working hypothesis, which applied this energy to supplement the work derived from ATP hydrolysis in muscle, was proposed. The scheme gives a complete explanation for the unexpected and novel findings in skeletal muscle reported from Italy. The problem of using two energy sources and the novel properties of water at nanometer dimensions as they would apply in muscle are briefly discussed but they merit further interdisciplinary studies.

Online Sequential Projection Vector Machine with Adaptive Data Mean Update

PubMed Central

Chen, Lin; Jia, Ji-Ting; Zhang, Qiong; Deng, Wan-Yu; Wei, Wei

2016-01-01

We propose a simple online learning algorithm especial for high-dimensional data. The algorithm is referred to as online sequential projection vector machine (OSPVM) which derives from projection vector machine and can learn from data in one-by-one or chunk-by-chunk mode. In OSPVM, data centering, dimension reduction, and neural network training are integrated seamlessly. In particular, the model parameters including (1) the projection vectors for dimension reduction, (2) the input weights, biases, and output weights, and (3) the number of hidden nodes can be updated simultaneously. Moreover, only one parameter, the number of hidden nodes, needs to be determined manually, and this makes it easy for use in real applications. Performance comparison was made on various high-dimensional classification problems for OSPVM against other fast online algorithms including budgeted stochastic gradient descent (BSGD) approach, adaptive multihyperplane machine (AMM), primal estimated subgradient solver (Pegasos), online sequential extreme learning machine (OSELM), and SVD + OSELM (feature selection based on SVD is performed before OSELM). The results obtained demonstrated the superior generalization performance and efficiency of the OSPVM. PMID:27143958

Forecasting daily streamflow using online sequential extreme learning machines

NASA Astrophysics Data System (ADS)

Lima, Aranildo R.; Cannon, Alex J.; Hsieh, William W.

2016-06-01

While nonlinear machine methods have been widely used in environmental forecasting, in situations where new data arrive continually, the need to make frequent model updates can become cumbersome and computationally costly. To alleviate this problem, an online sequential learning algorithm for single hidden layer feedforward neural networks - the online sequential extreme learning machine (OSELM) - is automatically updated inexpensively as new data arrive (and the new data can then be discarded). OSELM was applied to forecast daily streamflow at two small watersheds in British Columbia, Canada, at lead times of 1-3 days. Predictors used were weather forecast data generated by the NOAA Global Ensemble Forecasting System (GEFS), and local hydro-meteorological observations. OSELM forecasts were tested with daily, monthly or yearly model updates. More frequent updating gave smaller forecast errors, including errors for data above the 90th percentile. Larger datasets used in the initial training of OSELM helped to find better parameters (number of hidden nodes) for the model, yielding better predictions. With the online sequential multiple linear regression (OSMLR) as benchmark, we concluded that OSELM is an attractive approach as it easily outperformed OSMLR in forecast accuracy.

A substantial amount of hidden magnetic energy in the quiet Sun.

PubMed

Bueno, J Trujillo; Shchukina, N; Ramos, A Asensio

2004-07-15

Deciphering and understanding the small-scale magnetic activity of the quiet solar photosphere should help to solve many of the key problems of solar and stellar physics, such as the magnetic coupling to the outer atmosphere and the coronal heating. At present, we can see only approximately 1 per cent of the complex magnetism of the quiet Sun, which highlights the need to develop a reliable way to investigate the remaining 99 per cent. Here we report three-dimensional radiative transfer modelling of scattering polarization in atomic and molecular lines that indicates the presence of hidden, mixed-polarity fields on subresolution scales. Combining this modelling with recent observational data, we find a ubiquitous tangled magnetic field with an average strength of approximately 130 G, which is much stronger in the intergranular regions of solar surface convection than in the granular regions. So the average magnetic energy density in the quiet solar photosphere is at least two orders of magnitude greater than that derived from simplistic one-dimensional investigations, and sufficient to balance radiative energy losses from the solar chromosphere.

Variance Estimation, Design Effects, and Sample Size Calculations for Respondent-Driven Sampling

PubMed Central

2006-01-01

Hidden populations, such as injection drug users and sex workers, are central to a number of public health problems. However, because of the nature of these groups, it is difficult to collect accurate information about them, and this difficulty complicates disease prevention efforts. A recently developed statistical approach called respondent-driven sampling improves our ability to study hidden populations by allowing researchers to make unbiased estimates of the prevalence of certain traits in these populations. Yet, not enough is known about the sample-to-sample variability of these prevalence estimates. In this paper, we present a bootstrap method for constructing confidence intervals around respondent-driven sampling estimates and demonstrate in simulations that it outperforms the naive method currently in use. We also use simulations and real data to estimate the design effects for respondent-driven sampling in a number of situations. We conclude with practical advice about the power calculations that are needed to determine the appropriate sample size for a study using respondent-driven sampling. In general, we recommend a sample size twice as large as would be needed under simple random sampling. PMID:16937083

Online Sequential Projection Vector Machine with Adaptive Data Mean Update.

PubMed

Chen, Lin; Jia, Ji-Ting; Zhang, Qiong; Deng, Wan-Yu; Wei, Wei

2016-01-01

We propose a simple online learning algorithm especial for high-dimensional data. The algorithm is referred to as online sequential projection vector machine (OSPVM) which derives from projection vector machine and can learn from data in one-by-one or chunk-by-chunk mode. In OSPVM, data centering, dimension reduction, and neural network training are integrated seamlessly. In particular, the model parameters including (1) the projection vectors for dimension reduction, (2) the input weights, biases, and output weights, and (3) the number of hidden nodes can be updated simultaneously. Moreover, only one parameter, the number of hidden nodes, needs to be determined manually, and this makes it easy for use in real applications. Performance comparison was made on various high-dimensional classification problems for OSPVM against other fast online algorithms including budgeted stochastic gradient descent (BSGD) approach, adaptive multihyperplane machine (AMM), primal estimated subgradient solver (Pegasos), online sequential extreme learning machine (OSELM), and SVD + OSELM (feature selection based on SVD is performed before OSELM). The results obtained demonstrated the superior generalization performance and efficiency of the OSPVM.

The Politics of the Hidden Curriculum

ERIC Educational Resources Information Center

Giroux, Henry A.

1977-01-01

Schools teach much more than the traditional curriculum. They also teach a "hidden curriculum"--those unstated norms, values, and beliefs promoting hierarchic and authoritarian social relations that are transmitted to students through the underlying educational structure. Discusses the effects of the "hidden curriculum" on the…

Birefringence and hidden photons

NASA Astrophysics Data System (ADS)

Arza, Ariel; Gamboa, J.

2018-05-01

We study a model where photons interact with hidden photons and millicharged particles through a kinetic mixing term. Particularly, we focus on vacuum birefringence effects and we find a bound for the millicharged parameter assuming that hidden photons are a piece of the local dark matter density.

Hidden vorticity in binary Bose-Einstein condensates

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

Brtka, Marijana; Gammal, Arnaldo; Malomed, Boris A.

We consider a binary Bose-Einstein condensate (BEC) described by a system of two-dimensional (2D) Gross-Pitaevskii equations with the harmonic-oscillator trapping potential. The intraspecies interactions are attractive, while the interaction between the species may have either sign. The same model applies to the copropagation of bimodal beams in photonic-crystal fibers. We consider a family of trapped hidden-vorticity (HV) modes in the form of bound states of two components with opposite vorticities S{sub 1,2}={+-}1, the total angular momentum being zero. A challenging problem is the stability of the HV modes. By means of a linear-stability analysis and direct simulations, stability domains aremore » identified in a relevant parameter plane. In direct simulations, stable HV modes feature robustness against large perturbations, while unstable ones split into fragments whose number is identical to the azimuthal index of the fastest growing perturbation eigenmode. Conditions allowing for the creation of the HV modes in the experiment are discussed too. For comparison, a similar but simpler problem is studied in an analytical form, viz., the modulational instability of an HV state in a one-dimensional (1D) system with periodic boundary conditions (this system models a counterflow in a binary BEC mixture loaded into a toroidal trap or a bimodal optical beam coupled into a cylindrical shell). We demonstrate that the stabilization of the 1D HV modes is impossible, which stresses the significance of the stabilization of the HV modes in the 2D setting.« less

Implications of the measured angular anisotropy at the hidden order transition of URu2Si2

NASA Astrophysics Data System (ADS)

Chandra, P.; Coleman, P.; Flint, R.; Trinh, J.; Ramirez, A. P.

2018-05-01

The heavy fermion compound URu2Si2 continues to attract great interest due to the long-unidentified nature of the hidden order that develops below 17.5 K. Here we discuss the implications of an angular survey of the linear and nonlinear susceptibility of URu2Si2 in the vicinity of the hidden order transition [1]. While the anisotropic nature of spin fluctuations and low-temperature quasiparticles was previously established, our recent results suggest that the order parameter itself has intrinsic Ising anisotropy, and that moreover this anisotropy extends far above the hidden order transition. Consistency checks and subsequent questions for future experimental and theoretical studies of hidden order are discussed.

Optimal satisfaction degree in energy harvesting cognitive radio networks

NASA Astrophysics Data System (ADS)

Li, Zan; Liu, Bo-Yang; Si, Jiang-Bo; Zhou, Fu-Hui

2015-12-01

A cognitive radio (CR) network with energy harvesting (EH) is considered to improve both spectrum efficiency and energy efficiency. A hidden Markov model (HMM) is used to characterize the imperfect spectrum sensing process. In order to maximize the whole satisfaction degree (WSD) of the cognitive radio network, a tradeoff between the average throughput of the secondary user (SU) and the interference to the primary user (PU) is analyzed. We formulate the satisfaction degree optimization problem as a mixed integer nonlinear programming (MINLP) problem. The satisfaction degree optimization problem is solved by using differential evolution (DE) algorithm. The proposed optimization problem allows the network to adaptively achieve the optimal solution based on its required quality of service (Qos). Numerical results are given to verify our analysis. Project supported by the National Natural Science Foundation of China (Grant No. 61301179), the Doctorial Programs Foundation of the Ministry of Education of China (Grant No. 20110203110011), and the 111 Project (Grant No. B08038).

Securing the User's Work Environment

NASA Technical Reports Server (NTRS)

Cardo, Nicholas P.

2004-01-01

High performance computing at the Numerical Aerospace Simulation Facility at NASA Ames Research Center includes C90's, J90's and Origin 2000's. Not only is it necessary to protect these systems from outside attacks, but also to provide a safe working environment on the systems. With the right tools, security anomalies in the user s work environment can be deleted and corrected. Validating proper ownership of files against user s permissions, will reduce the risk of inadvertent data compromise. The detection of extraneous directories and files hidden amongst user home directories is important for identifying potential compromises. The first runs of these utilities detected over 350,000 files with problems. With periodic scans, automated correction of problems takes only minutes. Tools for detecting these types of problems as well as their development techniques will be discussed with emphasis on consistency, portability and efficiency for both UNICOS and IRIX.

Health impacts and research ethics in female trafficking.

PubMed

Dhital, S R; Aro, R A; Sapkota, K

2011-04-01

Female trafficking is a social and public health problem, associated with physical and sexual abuse, psychological trauma, injuries from violence, sexually transmitted infections, adverse reproductive outcomes and substance misuse. It faces several challenges ranging from the hidden nature of the problem to ethical and human rights issues. The objectives of this paper are to analyze health impact of trafficking; ethical and research issues and anti-trafficking strategies in the Nepalese context. We collected published and unpublished data assessing the public health, ethical burden and research needs from different sources. Trafficked female involved in sex-industry that face grave situation as depicted and it might a reservoir of sexually transmitted diseases. Ethical issues related to survey of assessing the burden are difficult to carry out. The best ways to prevent and control these problems are to enhance anti- trafficking laws and raise awareness, empower and mobilize females and establish organizational capacity.

Rethinking Suspensions

ERIC Educational Resources Information Center

Stetson, Frank H.; Collins, Betty J.

2010-01-01

The overrepresentation of the Black and Hispanic subgroups in suspension data is a national problem and a troubling issue for schools and school systems across the United States. In Maryland, an analysis of student suspensions by school districts for the 2006-2007 school year revealed disproportionality issues. In 23 of the 24 jurisdictions,…

Personality Profiles of Intimate Partner Violence Offenders with and without PTSD

ERIC Educational Resources Information Center

Hoyt, Tim; Wray, Alisha M.; Wiggins, Kathryn T.; Gerstle, Melissa; Maclean, Peggy C.

2012-01-01

Intimate partner violence (IPV) is a serious forensic and clinical problem throughout the United States. Research aimed at defining and differentiating subgroups of IPV offenders using standardized personality instruments may eventually help with matching treatments to specific individuals to reduce recidivism. The current study used a convenience…

Behaviour Profile of Hungarian Adolescent Outpatients with a Dual Diagnosis

ERIC Educational Resources Information Center

Dinya, Elek; Csorba, Janos; Suli, Agota; Grosz, Zsofia

2012-01-01

The behaviour dimensions of 244 Hungarian adolescent psychiatric outpatients with a dual diagnosis (intellectual disability and psychiatric diagnosis) were examined by means of the adapted version of the Behaviour Problem Inventory (BPI, Rojahn, Matson, Lott, Esbensen, & Smalls, 2001). Four IQ subgroups were created: borderline, mild, moderate…

Hidden attractors in dynamical systems

NASA Astrophysics Data System (ADS)

Dudkowski, Dawid; Jafari, Sajad; Kapitaniak, Tomasz; Kuznetsov, Nikolay V.; Leonov, Gennady A.; Prasad, Awadhesh

2016-06-01

Complex dynamical systems, ranging from the climate, ecosystems to financial markets and engineering applications typically have many coexisting attractors. This property of the system is called multistability. The final state, i.e., the attractor on which the multistable system evolves strongly depends on the initial conditions. Additionally, such systems are very sensitive towards noise and system parameters so a sudden shift to a contrasting regime may occur. To understand the dynamics of these systems one has to identify all possible attractors and their basins of attraction. Recently, it has been shown that multistability is connected with the occurrence of unpredictable attractors which have been called hidden attractors. The basins of attraction of the hidden attractors do not touch unstable fixed points (if exists) and are located far away from such points. Numerical localization of the hidden attractors is not straightforward since there are no transient processes leading to them from the neighborhoods of unstable fixed points and one has to use the special analytical-numerical procedures. From the viewpoint of applications, the identification of hidden attractors is the major issue. The knowledge about the emergence and properties of hidden attractors can increase the likelihood that the system will remain on the most desirable attractor and reduce the risk of the sudden jump to undesired behavior. We review the most representative examples of hidden attractors, discuss their theoretical properties and experimental observations. We also describe numerical methods which allow identification of the hidden attractors.

Influence of aging on the activity of mice Sca-1+CD31- cardiac stem cells.

PubMed

Wu, Qiong; Zhan, Jinxi; Pu, Shiming; Qin, Liu; Li, Yun; Zhou, Zuping

2017-01-03

Therapeutic application of cardiac resident stem/progenitor cells (CSC/CPCs) is limited due to decline of their regenerative potential with donor age. A variety of studies have shown that the cardiac aging was the problem of the stem cells, but little is known about the impact of age on the subgroups CSC/CPCs, the relationship between subgroups CSC/CPCs ageing and age-related dysfunction. Here, we studied Sca-1+CD31- subgroups of CSCs from younger(2~3months) and older(22~24months) age mice, biological differentiation was realized using specific mediums for 14 days to induce cardiomyocyte, smooth muscle cells or endothelial cells and immunostain analysis of differentiated cell resulting were done. Proliferation and cell cycle were measured by flow cytometry assay, then used microarray to dissect variability from younger and older mice. Although the number of CSCs was higher in older mice, the advanced age significantly reduced the differentiation ability into cardiac cell lineages and the proliferation ability. Transcriptional changes in Sca-1+CD31- subgroups of CSCs during aging are related to Vitamin B6 metabolism, circadian rhythm, Tyrosine metabolism, Complement and coagulation cascades. Taking together these results indicate that Cardiac resident stem/progenitor cells have significant differences in their proliferative, pluripotency and gene profiles and those differences are age depending.

Fatigue is correlated with disease activity but not with the type of organ involvement in Behçet's syndrome: a comparative clinical survey.

PubMed

Buyuktas, Deram; Hatemi, Gulen; Yuksel-Findikoglu, Sukran; Ugurlu, Serdal; Yazici, Hasan; Yurdakul, Sebahattin

2015-01-01

Fatigue is an important problem in inflammatory diseases and affects the quality of life (QoL). We aimed to evaluate the severity and impact of fatigue in Behçet's syndrome (BS) and to determine its association with type of organ involvement and gender. One hundred and fifty-two BS, 51 rheumatoid arthritis (RA), 51 systemic lupus erythematosus (SLE), 51 ankylosing spondylitis (AS) patients and 65 healthy controls were evaluated by the fatigue severity scale, fatigue impact scale, fibromyalgia impact questionnaire (FIQ), RAPID3, SF-36 and Behçet's syndrome activity scale (the latter only in BS patients). We also analysed subgroups of BS patients with predominantly eye, vascular, joint and mucocutaneous involvement and did an additional gender analysis. Fatigue severity and fatigue impact scores were similar among BS, RA, SLE and AS patients and significantly higher than that in healthy controls (F4df=8.51; p<0.001 and F4df=8.67; p<0.001, respectively). The fatigue severity and fatigue impact scores were similarly high in BS subgroups with different types of organ involvement, and in both genders. Fatigue is an important problem in BS, as it is in other inflammatory conditions. It is similarly severe in subgroups of patients with eye, vascular, joint and mucocutaneous involvement and in either gender. Fatigue is a candidate outcome measure for clinical trials, to assess the life impact of Behçet's syndrome.

The Riccati equation, imprimitive actions and symplectic forms. [with application to decentralized optimal control problem

NASA Technical Reports Server (NTRS)

Garzia, M. R.; Loparo, K. A.; Martin, C. F.

1982-01-01

This paper looks at the structure of the solution of a matrix Riccati differential equation under a predefined group of transformations. The group of transformations used is an expanded form of the feedback group. It is shown that this group of transformations is a subgroup of the symplectic group. The orbits of the Riccati differential equation under the action of this group are studied and it is seen how these techniques apply to a decentralized optimal control problem.

The Hidden Curriculum in Distance Education: An Updated View.

ERIC Educational Resources Information Center

Anderson, Terry

2001-01-01

Addressing recent criticism of distance education, explores the distinctive hidden curriculum (supposed "real" agenda) of distance education, focusing on both its positive and negative expressions. Also offers an updated view of the hidden curriculum of traditional, campus-based education, grounded in an emerging worldwide context of broadening…

77 FR 8253 - Notice of Proposed Settlement Agreement and Opportunity for Public Comment: Hidden Lane Landfill...

Federal Register 2010, 2011, 2012, 2013, 2014

2012-02-14

... ENVIRONMENTAL PROTECTION AGENCY [FRL-9631-3] Notice of Proposed Settlement Agreement and Opportunity for Public Comment: Hidden Lane Landfill Superfund Site ACTION: Notice. SUMMARY: In accordance... (``DOJ'') on behalf of EPA, in connection with the Hidden Lane Landfill Superfund Site, Sterling, Loudoun...

Hidden Curriculum as One of Current Issue of Curriculum

ERIC Educational Resources Information Center

Alsubaie, Merfat Ayesh

2015-01-01

There are several issues in the education system, especially in the curriculum field that affect education. Hidden curriculum is one of current controversial curriculum issues. Many hidden curricular issues are the result of assumptions and expectations that are not formally communicated, established, or conveyed within the learning environment.…

Hidden Variable Theories and Quantum Nonlocality

ERIC Educational Resources Information Center

Boozer, A. D.

2009-01-01

We clarify the meaning of Bell's theorem and its implications for the construction of hidden variable theories by considering an example system consisting of two entangled spin-1/2 particles. Using this example, we present a simplified version of Bell's theorem and describe several hidden variable theories that agree with the predictions of…

Building Simple Hidden Markov Models. Classroom Notes

ERIC Educational Resources Information Center

Ching, Wai-Ki; Ng, Michael K.

2004-01-01

Hidden Markov models (HMMs) are widely used in bioinformatics, speech recognition and many other areas. This note presents HMMs via the framework of classical Markov chain models. A simple example is given to illustrate the model. An estimation method for the transition probabilities of the hidden states is also discussed.

Seuss's Butter Battle Book: Is There Hidden Harm?

ERIC Educational Resources Information Center

Van Cleaf, David W.; Martin, Rita J.

1986-01-01

Examines whether elementary school children relate to the "harmful hidden message" about nuclear war in Dr. Seuss's THE BUTTER BATTLE BOOK. After ascertaining the children's cognitive level, they participated in activities to find hidden meanings in stories, including Seuss's book. Students failed to identify the nuclear war message in…

Comment on 'All quantum observables in a hidden-variable model must commute simultaneously'

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

Nagata, Koji

Malley discussed [Phys. Rev. A 69, 022118 (2004)] that all quantum observables in a hidden-variable model for quantum events must commute simultaneously. In this comment, we discuss that Malley's theorem is indeed valid for the hidden-variable theoretical assumptions, which were introduced by Kochen and Specker. However, we give an example that the local hidden-variable (LHV) model for quantum events preserves noncommutativity of quantum observables. It turns out that Malley's theorem is not related to the LHV model for quantum events, in general.

Individual differences in children's understanding of inversion and arithmetical skill.

PubMed

Gilmore, Camilla K; Bryant, Peter

2006-06-01

Background and aims. In order to develop arithmetic expertise, children must understand arithmetic principles, such as the inverse relationship between addition and subtraction, in addition to learning calculation skills. We report two experiments that investigate children's understanding of the principle of inversion and the relationship between their conceptual understanding and arithmetical skills. A group of 127 children from primary schools took part in the study. The children were from 2 age groups (6-7 and 8-9 years). Children's accuracy on inverse and control problems in a variety of presentation formats and in canonical and non-canonical forms was measured. Tests of general arithmetic ability were also administered. Children consistently performed better on inverse than control problems, which indicates that they could make use of the inverse principle. Presentation format affected performance: picture presentation allowed children to apply their conceptual understanding flexibly regardless of the problem type, while word problems restricted their ability to use their conceptual knowledge. Cluster analyses revealed three subgroups with different profiles of conceptual understanding and arithmetical skill. Children in the 'high ability' and 'low ability' groups showed conceptual understanding that was in-line with their arithmetical skill, whilst a 3rd group of children had more advanced conceptual understanding than arithmetical skill. The three subgroups may represent different points along a single developmental path or distinct developmental paths. The discovery of the existence of the three groups has important consequences for education. It demonstrates the importance of considering the pattern of individual children's conceptual understanding and problem-solving skills.

Assessment of the Short-Term Effectiveness of Kinesiotaping and Trigger Points Release Used in Functional Disorders of the Masticatory Muscles

PubMed Central

Lietz-Kijak, Danuta; Kopacz, Łukasz; Grzegocka, Marta

2018-01-01

Chronic face pain syndrome is a diagnostic and therapeutic problem for many specialists, and this proves the interdisciplinary and complex nature of this ailment. Physiotherapy is of particular importance in the treatment of pain syndrome in the course of temporomandibular joint functional disorders. In patients with long-term dysfunction of masticatory muscles, the palpation examination can localize trigger points, that is, thickening in the form of nodules in the size of rice grains or peas. Latent trigger points located in the muscles can interfere with muscular movement patterns, cause cramps, and reduce muscle strength. Because hidden trigger points can spontaneously activate, they should be found and released to prevent further escalation of the discomfort. Kinesiotaping (KT) is considered as an intervention that can be used to release latent myofascial trigger points. It is a method that involves applying specific tapes to the patient's skin in order to take advantage of the natural self-healing processes of the body. The aim of the study was to evaluate the effect of the kinesiotaping method and trigger points inactivation on the nonpharmacological elimination of pain in patients with temporomandibular disorders. The study was conducted in 60 patients (18 to 35 years old). The subjects were randomly divided into two subgroups of 30 people each. Group KT (15 women and 15 men) were subjected to active kinesiotaping application. Group TrP, composed of 16 women and 14 men, was subjected to physiotherapy with the release of trigger points by the ischemic compression method. The results show that the KT method and TrP inactivation brought significant therapeutic analgesic effects in the course of pain-related functional disorders of the muscles of mastication. The more beneficial outcomes of the therapy were observed after using the KT method, which increased the analgesic effect in dysfunctional patients. PMID:29861804

Approaches to Recruiting 'Hard-To-Reach' Populations into Re-search: A Review of the Literature.

PubMed

Shaghaghi, Abdolreza; Bhopal, Raj S; Sheikh, Aziz

2011-01-01

'Hard-to-reach' is a term used to describe those sub-groups of the population that may be difficult to reach or involve in research or public health programmes. Application of a single term to call these sub-sections of populations implies a homogeneity within distinct groups, which does not necessarily exist. Different sampling techniques were introduced so far to recruit hard-to-reach populations. In this article, we have reviewed a range of ap-proaches that have been used to widen participation in studies. We performed a Pubmed and Google search for relevant English language articles using the keywords and phrases: (hard-to-reach AND population* OR sampl*), (hidden AND population* OR sample*) and ("hard to reach" AND population* OR sample*) and a consul-tation of the retrieved articles' bibliographies to extract empirical evidence from publications that discussed or examined the use of sampling techniques to recruit hidden or hard-to-reach populations in health studies. Reviewing the literature has identified a range of techniques to recruit hard-to-reach populations, including snowball sampling, respondent-driven sampling (RDS), indigenous field worker sampling (IFWS), facility-based sampling (FBS), targeted sampling (TS), time-location (space) sampling (TLS), conventional cluster sampling (CCS) and capture re-capture sampling (CR). The degree of compliance with a study by a certain 'hard-to-reach' group de-pends on the characteristics of that group, recruitment technique used and the subject of inter-est. Irrespective of potential advantages or limitations of the recruitment techniques reviewed, their successful use depends mainly upon our knowledge about specific characteristics of the target populations. Thus in line with attempts to expand the current boundaries of our know-ledge about recruitment techniques in health studies and their applications in varying situa-tions, we should also focus on possibly all contributing factors which may have an impact on participation rate within a defined population group.

Surgical management of cutaneous infection caused by atypical mycobacteria after penetrating injury: the hidden dangers of horticulture.

PubMed

Holland, J; Smith, C; Childs, P A; Holland, A J

1997-02-01

We identified two patients in a 12-month period who presented with cutaneous infection and secondary lymph node involvement from atypical mycobacterial infection after minor gardening injuries. One patient had a coinfection with Nocardia asteroides. Both patients required multiple surgical interventions, despite appropriate antibiotic therapy, before resolution of the disease. The course of the infection was characterized by chronic relapses with complete healing at 12 to 18 months after the original injury. The identification and management of this clinical problem are reviewed.

A comparison of polynomial approximations and artificial neural nets as response surfaces

NASA Technical Reports Server (NTRS)

Carpenter, William C.; Barthelemy, Jean-Francois M.

1992-01-01

Artificial neural nets and polynomial approximations were used to develop response surfaces for several test problems. Based on the number of functional evaluations required to build the approximations and the number of undetermined parameters associated with the approximations, the performance of the two types of approximations was found to be comparable. A rule of thumb is developed for determining the number of nodes to be used on a hidden layer of an artificial neural net, and the number of designs needed to train an approximation is discussed.

Protecting the axion with local baryon number

NASA Astrophysics Data System (ADS)

Duerr, Michael; Schmidt-Hoberg, Kai; Unwin, James

2018-05-01

The Peccei-Quinn (PQ) solution to the Strong CP Problem is expected to fail unless the global symmetry U(1)PQ is protected from Planck-scale operators up to high mass dimension. Suitable protection can be achieved if the PQ symmetry is an automatic consequence of some gauge symmetry. We highlight that if baryon number is promoted to a gauge symmetry, the exotic fermions needed for anomaly cancellation can elegantly provide an implementation of the Kim-Shifman-Vainshtein-Zakharov 'hidden axion' mechanism with a PQ symmetry protected from Planck-scale physics.

What Is Going on Inside the Arrows? Discovering the Hidden Springs in Causal Models

PubMed Central

Murray-Watters, Alexander; Glymour, Clark

2016-01-01

Using Gebharter's (2014) representation, we consider aspects of the problem of discovering the structure of unmeasured sub-mechanisms when the variables in those sub-mechanisms have not been measured. Exploiting an early insight of Sober's (1998), we provide a correct algorithm for identifying latent, endogenous structure—sub-mechanisms—for a restricted class of structures. The algorithm can be merged with other methods for discovering causal relations among unmeasured variables, and feedback relations between measured variables and unobserved causes can sometimes be learned. PMID:27313331

Increased taxon sampling reveals thousands of hidden orthologs in flatworms

PubMed Central

2017-01-01

Gains and losses shape the gene complement of animal lineages and are a fundamental aspect of genomic evolution. Acquiring a comprehensive view of the evolution of gene repertoires is limited by the intrinsic limitations of common sequence similarity searches and available databases. Thus, a subset of the gene complement of an organism consists of hidden orthologs, i.e., those with no apparent homology to sequenced animal lineages—mistakenly considered new genes—but actually representing rapidly evolving orthologs or undetected paralogs. Here, we describe Leapfrog, a simple automated BLAST pipeline that leverages increased taxon sampling to overcome long evolutionary distances and identify putative hidden orthologs in large transcriptomic databases by transitive homology. As a case study, we used 35 transcriptomes of 29 flatworm lineages to recover 3427 putative hidden orthologs, some unidentified by OrthoFinder and HaMStR, two common orthogroup inference algorithms. Unexpectedly, we do not observe a correlation between the number of putative hidden orthologs in a lineage and its “average” evolutionary rate. Hidden orthologs do not show unusual sequence composition biases that might account for systematic errors in sequence similarity searches. Instead, gene duplication with divergence of one paralog and weak positive selection appear to underlie hidden orthology in Platyhelminthes. By using Leapfrog, we identify key centrosome-related genes and homeodomain classes previously reported as absent in free-living flatworms, e.g., planarians. Altogether, our findings demonstrate that hidden orthologs comprise a significant proportion of the gene repertoire in flatworms, qualifying the impact of gene losses and gains in gene complement evolution. PMID:28400424

A Rose By Other Names: Some General Musings on Lawrence and Colleagues' Hidden Curriculum Scoping Review.

PubMed

Hafferty, Frederic W; Martimianakis, Maria Athina

2017-11-07

In this Commentary, the authors explore the scoping review by Lawrence and colleagues by challenging their conclusion that with over 25 years' worth of "ambiguous and seemingly ubiquitous use" of the hidden curriculum construct in health professions education scholarship, it is time to either move to a more uniform definitional foundation or abandon the term altogether. The commentary authors counter these remedial propositions by foregrounding the importance of theoretical diversity and the conceptual richness afforded when the hidden curriculum construct is used as an entry point for studying the interstitial space between the formal and a range of other-than-formal domains of learning. Further, they document how tightly-delimited scoping strategies fail to capture the wealth of educational scholarship that operates within a hidden curriculum framework, including "hidden" hidden curriculum articles, studies that employ alternative constructs, and investigations that target important tacit socio-cultural influences on learners and faculty without formally deploying the term. They offer examples of how the hidden curriculum construct, while undergoing significant transformation in its application within the field of health professions education, has created the conceptual foundation for the application of a number of critical perspectives that make visible the field's political investments in particular forms of knowing and associated practices. Finally, the commentary authors invite readers to consider the methodological promise afforded by conceptual heterogeneity, particularly strands of scholarship that resituate the hidden curriculum concept within the magically expansive dance of social relationships, social learning, and social life that form the learning environments of health professions education.

FIMP dark matter freeze-in gauge mediation and hidden sector

NASA Astrophysics Data System (ADS)

Tsao, Kuo-Hsing

2018-07-01

We explore the dark matter freeze-in mechanism within the gauge mediation framework, which involves a hidden feebly interacting massive particle (FIMP) coupling feebly with the messenger fields while the messengers are still in the thermal bath. The FIMP is the fermionic component of the pseudo-moduli in a generic metastable supersymmetry (SUSY) breaking model and resides in the hidden sector. The relic abundance and the mass of the FIMP are determined by the SUSY breaking scale and the feeble coupling. The gravitino, which is the canonical dark matter candidate in the gauge mediation framework, contributes to the dark matter relic abundance along with the freeze-in of the FIMP. The hidden sector thus becomes two-component with both the FIMP and gravitino lodging in the SUSY breaking hidden sector. We point out that the ratio between the FIMP and the gravitino is determined by how SUSY breaking is communicated to the messengers. In particular when the FIMP dominates the hidden sector, the gravitino becomes the minor contributor in the hidden sector. Meanwhile, the neutralino is assumed to be both the weakly interacting massive particle dark matter candidate in the freeze-out mechanism and the lightest observable SUSY particle. We further find out the neutralino has the sub-leading contribution to the current dark matter relic density in the parameter space of our freeze-in gauge mediation model. Our result links the SUSY breaking scale in the gauge mediation framework with the FIMP freeze-in production rate leading to a natural and predicting scenario for the studies of the dark matter in the hidden sector.

What Should We Do With a Hidden Curriculum When We Fine One?

ERIC Educational Resources Information Center

Martin, Jane R.

1976-01-01

A hidden curriculum consists of those learning states of a setting that are either unintended or intended but not openly acknowledged to the learners in the setting unless the learners are aware of them. Consciousness-raising may be the best weapon of individuals who are subject to hidden curricula. (Author/MLF)

Manifestations of Hidden Curriculum in a Community College Online Opticianry Program: An Ecological Approach

ERIC Educational Resources Information Center

Hubbard, Barry

2010-01-01

Understanding the influential factors at work within an online learning environment is a growing area of interest. Hidden or implicit expectations, skill sets, knowledge, and social process can help or hinder student achievement, belief systems, and persistence. This qualitative study investigated how hidden curricular issues transpired in an…

The Hidden Reason Behind Children's Misbehavior.

ERIC Educational Resources Information Center

Nystul, Michael S.

1986-01-01

Discusses hidden reason theory based on the assumptions that: (1) the nature of people is positive; (2) a child's most basic psychological need is involvement; and (3) a child has four possible choices in life (good somebody, good nobody, bad somebody, or severely mentally ill.) A three step approach for implementing hidden reason theory is…

Student Teaching: A Hidden Wholeness

ERIC Educational Resources Information Center

Bowman, Richard F.

2007-01-01

Productive student teachers lead learning by emergently sensing and honoring the hidden wholeness of life in classrooms. That hidden wholeness mirrors seven contextual concerns which learners reflect upon in the everydayness of classroom life: What are we going to do in class today? What am I going to have to do in class? What counts in today's…

Environmental Assessment for the Expansion of Permitted Land and Operations at the 9940 Complex and Thunder Range at Sandia National Laboratories/New Mexico

DTIC Science & Technology

2008-03-01

vivipara Hidden flower Cryptantha crassisepala Hidden flower Cryptantha fulvocanescens James’s hidden flower Cryptantha jamesii Buffalo gourd...pumila Bigbract verbena ta Verbena bractea Banana yucca ta Yucca bacca Soapweed yucca Yucca glauca Rocky Mountain zinnia Zinnia grandiflora A-9

Driving style recognition method using braking characteristics based on hidden Markov model

PubMed Central

Wu, Chaozhong; Lyu, Nengchao; Huang, Zhen

2017-01-01

Since the advantage of hidden Markov model in dealing with time series data and for the sake of identifying driving style, three driving style (aggressive, moderate and mild) are modeled reasonably through hidden Markov model based on driver braking characteristics to achieve efficient driving style. Firstly, braking impulse and the maximum braking unit area of vacuum booster within a certain time are collected from braking operation, and then general braking and emergency braking characteristics are extracted to code the braking characteristics. Secondly, the braking behavior observation sequence is used to describe the initial parameters of hidden Markov model, and the generation of the hidden Markov model for differentiating and an observation sequence which is trained and judged by the driving style is introduced. Thirdly, the maximum likelihood logarithm could be implied from the observable parameters. The recognition accuracy of algorithm is verified through experiments and two common pattern recognition algorithms. The results showed that the driving style discrimination based on hidden Markov model algorithm could realize effective discriminant of driving style. PMID:28837580

A possible loophole in the theorem of Bell.

PubMed

Hess, K; Philipp, W

2001-12-04

The celebrated inequalities of Bell are based on the assumption that local hidden parameters exist. When combined with conflicting experimental results, these inequalities appear to prove that local hidden parameters cannot exist. This contradiction suggests to many that only instantaneous action at a distance can explain the Einstein, Podolsky, and Rosen type of experiments. We show that, in addition to the assumption that hidden parameters exist, Bell tacitly makes a variety of other assumptions that contribute to his being able to obtain the desired contradiction. For instance, Bell assumes that the hidden parameters do not depend on time and are governed by a single probability measure independent of the analyzer settings. We argue that the exclusion of time has neither a physical nor a mathematical basis but is based on Bell's translation of the concept of Einstein locality into the language of probability theory. Our additional set of local hidden variables includes time-like correlated parameters and a generalized probability density. We prove that our extended space of local hidden variables does not permit Bell-type proofs to go forward.

Photoacoustic imaging of hidden dental caries by using a bundle of hollow optical fibers

NASA Astrophysics Data System (ADS)

Koyama, Takuya; Kakino, Satoko; Matsuura, Yuji

2018-02-01

Photoacoustic imaging system using a bundle of hollow-optical fibers to detect hidden dental caries is proposed. Firstly, we fabricated a hidden caries model with a brown pigment simulating a common color of caries lesion. It was found that high frequency ultrasonic waves are generated from hidden carious part when radiating Nd:YAG laser light with a 532 nm wavelength to occlusal surface of model tooth. We calculated by Fourier transform and found that the waveform from the carious part provides frequency components of approximately from 0.5 to 1.2 MHz. Then a photoacoustic imaging system using a bundle of hollow optical fiber was fabricated for clinical applications. From intensity map of frequency components in 0.5-1.2 MHz, photoacoustic images of hidden caries in the simulated samples were successfully obtained.

On the LHC sensitivity for non-thermalised hidden sectors

NASA Astrophysics Data System (ADS)

Kahlhoefer, Felix

2018-04-01

We show under rather general assumptions that hidden sectors that never reach thermal equilibrium in the early Universe are also inaccessible for the LHC. In other words, any particle that can be produced at the LHC must either have been in thermal equilibrium with the Standard Model at some point or must be produced via the decays of another hidden sector particle that has been in thermal equilibrium. To reach this conclusion, we parametrise the cross section connecting the Standard Model to the hidden sector in a very general way and use methods from linear programming to calculate the largest possible number of LHC events compatible with the requirement of non-thermalisation. We find that even the HL-LHC cannot possibly produce more than a few events with energy above 10 GeV involving states from a non-thermalised hidden sector.

Optimization of Artificial Neural Network using Evolutionary Programming for Prediction of Cascading Collapse Occurrence due to the Hidden Failure Effect

NASA Astrophysics Data System (ADS)

Idris, N. H.; Salim, N. A.; Othman, M. M.; Yasin, Z. M.

2018-03-01

This paper presents the Evolutionary Programming (EP) which proposed to optimize the training parameters for Artificial Neural Network (ANN) in predicting cascading collapse occurrence due to the effect of protection system hidden failure. The data has been collected from the probability of hidden failure model simulation from the historical data. The training parameters of multilayer-feedforward with backpropagation has been optimized with objective function to minimize the Mean Square Error (MSE). The optimal training parameters consists of the momentum rate, learning rate and number of neurons in first hidden layer and second hidden layer is selected in EP-ANN. The IEEE 14 bus system has been tested as a case study to validate the propose technique. The results show the reliable prediction of performance validated through MSE and Correlation Coefficient (R).

Peer Victimization, Aggression, and Their Co-Occurrence in Middle School: Pathways to Adjustment Problems

ERIC Educational Resources Information Center

Graham, Sandra; Bellmore, Amy D.; Mize, Jennifer

2006-01-01

An ethnically diverse sample of 6th-grade students completed peer nomination procedures that were used to create subgroups of students with reputations as victims, aggressors, aggressive victims, and socially adjusted (neither aggressive nor victimized). Self-report data on psychological adjustment, attributions for peer harassment, and perceived…

Dating Violence, Bullying, and Sexual Harassment: Longitudinal Profiles and Transitions over Time

ERIC Educational Resources Information Center

Miller, Shari; Williams, Jason; Cutbush, Stacey; Gibbs, Deborah; Clinton-Sherrod, Monique; Jones, Sarah

2013-01-01

Although there is growing recognition of the problem of dating violence, little is known about how it unfolds among young adolescents who are just beginning to date. This study examined classes (subgroups) and transitions between classes over three time points based on dating violence, bullying, and sexual harassment perpetration and victimization…

Identifying Predictors of Negative Psychological Reactions to Stalking Victimization

ERIC Educational Resources Information Center

Johnson, Matthew C.; Kercher, Glen A.

2009-01-01

Victims of stalking often experience a number of negative psychological problems including such things as fear, symptoms of depression, and anger. However, research on factors that lead to these outcomes is limited. The goal of this study was to first identify distinct subgroups of stalking victims based on measures of psychological problems…

Subtypes of Attachment Security in School-Age Children with Learning Disabilities

ERIC Educational Resources Information Center

Al-Yagon, Michal

2012-01-01

This study explored children's secure attachment with both parents versus one parent, as well as the unique role of children's patterns of close relationships with father and mother, for a deeper understanding of maladjustment problems among children with learning disabilities (LD). Specifically, this study identified subgroups of children with…

Substance Use Among Migrant and Seasonal Farmworkers in Central Florida.

ERIC Educational Resources Information Center

Arnow, Beth

A study of alcohol and drug use among migrant and seasonal farmworkers in Orange and Lake counties (Central Florida) was conducted in 1978 to determine substance abuse among migrant and seasonal farmworkers, the subgroups with substance abuse problems, the farmworkers' knowledge of and attitudes toward alcohol and drug treatment programs, and the…

Cognitive Profiles of Finnish Preschool Children with Expressive and Receptive Language Impairment

ERIC Educational Resources Information Center

Saar, Virpi; Levänen, Sari; Komulainen, Erkki

2018-01-01

Purpose: The aim of this study was to compare the verbal and nonverbal cognitive profiles of children with specific language impairment (SLI) with problems predominantly in expressive (SLI-E) or receptive (SLI-R) language skills. These diagnostic subgroups have not been compared before in psychological studies. Method: Participants were…

Hawaii Opinion Poll on Public Education (HOPE), 1998.

ERIC Educational Resources Information Center

Hawaii State Dept. of Education, Honolulu. Office of Accountability and School Instructional Support.

The 1998 Hawaii Opinion Poll on Public Education is the fifth to report the public's perceptions of public schools. Three questions included in every report since 1990 ask respondents to grade Hawaii's public schools, whether schools are improving or deteriorating, and to identify the school system's biggest problems. Responses of two subgroups,…

Factor Covariance Analysis in Subgroups.

ERIC Educational Resources Information Center

Pennell, Roger

The problem considered is that of an investigator sampling two or more correlation matrices and desiring to fit a model where a factor pattern matrix is assumed to be identical across samples and we need to estimate only the factor covariance matrix and the unique variance for each sample. A flexible, least squares solution is worked out and…

Predictors of Asian American Adolescents' Suicide Attempts: A Latent Class Regression Analysis

ERIC Educational Resources Information Center

Wong, Y. Joel; Maffini, Cara S.

2011-01-01

Although suicide-related outcomes among Asian American adolescents are a serious public health problem in the United States, research in this area has been relatively sparse. To address this gap in the empirical literature, this study examined subgroups of Asian American adolescents for whom family, school, and peer relationships exerted…

Hidden charged dark matter and chiral dark radiation

NASA Astrophysics Data System (ADS)

Ko, P.; Nagata, Natsumi; Tang, Yong

2017-10-01

In the light of recent possible tensions in the Hubble constant H0 and the structure growth rate σ8 between the Planck and other measurements, we investigate a hidden-charged dark matter (DM) model where DM interacts with hidden chiral fermions, which are charged under the hidden SU(N) and U(1) gauge interactions. The symmetries in this model assure these fermions to be massless. The DM in this model, which is a Dirac fermion and singlet under the hidden SU(N), is also assumed to be charged under the U(1) gauge symmetry, through which it can interact with the chiral fermions. Below the confinement scale of SU(N), the hidden quark condensate spontaneously breaks the U(1) gauge symmetry such that there remains a discrete symmetry, which accounts for the stability of DM. This condensate also breaks a flavor symmetry in this model and Nambu-Goldstone bosons associated with this flavor symmetry appear below the confinement scale. The hidden U(1) gauge boson and hidden quarks/Nambu-Goldstone bosons are components of dark radiation (DR) above/below the confinement scale. These light fields increase the effective number of neutrinos by δNeff ≃ 0.59 above the confinement scale for N = 2, resolving the tension in the measurements of the Hubble constant by Planck and Hubble Space Telescope if the confinement scale is ≲1 eV. DM and DR continuously scatter with each other via the hidden U(1) gauge interaction, which suppresses the matter power spectrum and results in a smaller structure growth rate. The DM sector couples to the Standard Model sector through the exchange of a real singlet scalar mixing with the Higgs boson, which makes it possible to probe our model in DM direct detection experiments. Variants of this model are also discussed, which may offer alternative ways to investigate this scenario.

DNA Microarray Data Analysis: A Novel Biclustering Algorithm Approach

NASA Astrophysics Data System (ADS)

Tchagang, Alain B.; Tewfik, Ahmed H.

2006-12-01

Biclustering algorithms refer to a distinct class of clustering algorithms that perform simultaneous row-column clustering. Biclustering problems arise in DNA microarray data analysis, collaborative filtering, market research, information retrieval, text mining, electoral trends, exchange analysis, and so forth. When dealing with DNA microarray experimental data for example, the goal of biclustering algorithms is to find submatrices, that is, subgroups of genes and subgroups of conditions, where the genes exhibit highly correlated activities for every condition. In this study, we develop novel biclustering algorithms using basic linear algebra and arithmetic tools. The proposed biclustering algorithms can be used to search for all biclusters with constant values, biclusters with constant values on rows, biclusters with constant values on columns, and biclusters with coherent values from a set of data in a timely manner and without solving any optimization problem. We also show how one of the proposed biclustering algorithms can be adapted to identify biclusters with coherent evolution. The algorithms developed in this study discover all valid biclusters of each type, while almost all previous biclustering approaches will miss some.

Using an innovative multiple regression procedure in a cancer population (Part II): fever, depressive affect, and mobility problems clarify an influential symptom pair (pain-fatigue/weakness) and cluster (pain-fatigue/weakness-sleep problems).

PubMed

Francoeur, Richard B

2015-01-01

Most patients with advanced cancer experience symptom pairs or clusters among pain, fatigue, and insomnia. However, only combinations where symptoms are mutually influential hold potential for identifying patient subgroups at greater risk, and in some contexts, interventions with "cross-over" (multisymptom) effects. Improved methods to detect and interpret interactions among symptoms, signs, or biomarkers are needed to reveal these influential pairs and clusters. I recently created sequential residual centering (SRC) to reduce multicollinearity in moderated regression, which enhances sensitivity to detect these interactions. I applied SRC to moderated regressions of single-item symptoms that interact to predict outcomes from 268 palliative radiation outpatients. I investigated: 1) the hypothesis that the interaction, pain × fatigue/weakness × sleep problems, predicts depressive affect only when fever presents, and 2) an exploratory analysis, when fever is absent, that the interaction, pain × fatigue/weakness × sleep problems × depressive affect, predicts mobility problems. In the fever context, three-way interactions (and derivative terms) of the four symptoms (pain, fatigue/weakness, fever, sleep problems) are tested individually and simultaneously; in the non-fever context, a single four-way interaction (and derivative terms) is tested. Fever interacts separately with fatigue/weakness and sleep problems; these comoderators each magnify the pain-depressive affect relationship along the upper or full range of pain values. In non-fever contexts, fatigue/weakness, sleep problems, and depressive affect comagnify the relationship between pain and mobility problems. Different mechanisms contribute to the pain × fatigue/weakness × sleep problems interaction, but all depend on the presence of fever, a sign/biomarker/symptom of proinflammatory sickness behavior. In non-fever contexts, depressive affect is no longer an outcome representing malaise from the physical symptoms of sickness, but becomes a fourth symptom of the interaction. In outpatient subgroups at heightened risk, single interventions could potentially relieve multiple symptoms when fever accompanies sickness malaise and in non-fever contexts with mobility problems. SRC strengthens insights into symptom pairs/clusters.

Global SO(3) x SO(3) x U(1) symmetry of the Hubbard model on bipartite lattices

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

Carmelo, J.M.P., E-mail: carmelo@fisica.uminho.p; Ostlund, Stellan; Sampaio, M.J.

2010-08-15

In this paper the global symmetry of the Hubbard model on a bipartite lattice is found to be larger than SO(4). The model is one of the most studied many-particle quantum problems, yet except in one dimension it has no exact solution, so that there remain many open questions about its properties. Symmetry plays an important role in physics and often can be used to extract useful information on unsolved non-perturbative quantum problems. Specifically, here it is found that for on-site interaction U {ne} 0 the local SU(2) x SU(2) x U(1) gauge symmetry of the Hubbard model on amore » bipartite lattice with N{sub a}{sup D} sites and vanishing transfer integral t = 0 can be lifted to a global [SU(2) x SU(2) x U(1)]/Z{sub 2}{sup 2} = SO(3) x SO(3) x U(1) symmetry in the presence of the kinetic-energy hopping term of the Hamiltonian with t > 0. (Examples of a bipartite lattice are the D-dimensional cubic lattices of lattice constant a and edge length L = N{sub a}a for which D = 1, 2, 3,... in the number N{sub a}{sup D} of sites.) The generator of the new found hidden independent charge global U(1) symmetry, which is not related to the ordinary U(1) gauge subgroup of electromagnetism, is one half the rotated-electron number of singly occupied sites operator. Although addition of chemical-potential and magnetic-field operator terms to the model Hamiltonian lowers its symmetry, such terms commute with it. Therefore, its 4{sup N}{sub a}{sup D} energy eigenstates refer to representations of the new found global [SU(2) x SU(2) x U(1)]/Z{sub 2}{sup 2} = SO(3) x SO(3) x U(1) symmetry. Consistently, we find that for the Hubbard model on a bipartite lattice the number of independent representations of the group SO(3) x SO(3) x U(1) equals the Hilbert-space dimension 4{sup N}{sub a}{sup D}. It is confirmed elsewhere that the new found symmetry has important physical consequences.« less

TRIZ: A Bridge Between Applied and Industrial Physics

NASA Astrophysics Data System (ADS)

Savransky, Semyon

1997-03-01

TRIZ provides a methodology for creative engineering design. TRIZ was founded by Genrich S. Altshuller in Russia, whose with co-workers analyses about 1,500,000 worldwide patents. The major TRIZ principles are [1,2]: 1. All engineering systems have uniform evolution. Many other systems (economic, educational, etc.) have the same evolution trends. 2. Any inventive problem represents a conflict between new requirements and old system. TRIZ comprises various systematically techniques to find an quasi-ideal answer to the inventive problem through solve the conflict based on the knowledge of a system evolution. Usually the hidden root of technical problem is physical contradictions that is possible to resolve using the lists of effects. TRIZ experts use a knowledge base of applied physics to provide solutions of industrial problems . Many companies around the world cite a phenomenal increase in the producti-vity and quality of solutions to tough engineering problems through the use of TRIZ. [1]. G. S. Altshuller, B.L. Zlotin, A.V. Zusman and V.I. Filatov, The new ideas search: From intuition to technology. (in Russian) Kishinev, 1989, 381p. [2]. S.D. Savransky, and C. Stephan, TRIZ: Methodology of Inventive Problem Solving. The Indust-rial Physicist (December 1996).

Constructive autoassociative neural network for facial recognition.

PubMed

Fernandes, Bruno J T; Cavalcanti, George D C; Ren, Tsang I

2014-01-01

Autoassociative artificial neural networks have been used in many different computer vision applications. However, it is difficult to define the most suitable neural network architecture because this definition is based on previous knowledge and depends on the problem domain. To address this problem, we propose a constructive autoassociative neural network called CANet (Constructive Autoassociative Neural Network). CANet integrates the concepts of receptive fields and autoassociative memory in a dynamic architecture that changes the configuration of the receptive fields by adding new neurons in the hidden layer, while a pruning algorithm removes neurons from the output layer. Neurons in the CANet output layer present lateral inhibitory connections that improve the recognition rate. Experiments in face recognition and facial expression recognition show that the CANet outperforms other methods presented in the literature.