EPR and Bell's theorem: A critical review

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

Stapp, H.P.

1991-01-01

The argument of Einstein, Podolsky, and Rosen is reviewed with attention to logical structure and character of assumptions. Bohr's reply is discussed. Bell's contribution is formulated without use of hidden variables, and efforts to equate hidden variables to realism are critically examined. An alternative derivation of nonlocality that makes no use of hidden variables, microrealism, counterfactual definiteness, or any other assumption alien to orthodox quantum thinking is described in detail, with particular attention to the quartet or broken-square question.

Experimental test of state-independent quantum contextuality of an indivisible quantum system

NASA Astrophysics Data System (ADS)

Li, Meng; Huang, Yun-Feng; Cao, Dong-Yang; Zhang, Chao; Zhang, Yong-Sheng; Liu, Bi-Heng; Li, Chuan-Feng; Guo, Guang-Can

2014-05-01

Since the quantum mechanics was born, quantum mechanics was argued among scientists because the differences between quantum mechanics and the classical physics. Because of this, some people give hidden variable theory. One of the hidden variable theory is non-contextual hidden variable theory, and KS inequalities are famous in non-contextual hidden variable theory. But the original KS inequalities have 117 directions to measure, so it is almost impossible to test the KS inequalities in experiment. However bout two years ago, Sixia Yu and C.H. Oh point out that for a single qutrit, we only need to measure 13 directions, then we can test the KS inequalities. This makes it possible to test the KS inequalities in experiment. We use the polarization and the path of single photon to construct a qutrit, and we use the half-wave plates, the beam displacers and polar beam splitters to prepare the quantum state and finish the measurement. And the result prove that quantum mechanics is right and non-contextual hidden variable theory is wrong.

Effect of proton-conduction in electrolyte on electric efficiency of multi-stage solid oxide fuel cells

PubMed Central

Matsuzaki, Yoshio; Tachikawa, Yuya; Somekawa, Takaaki; Hatae, Toru; Matsumoto, Hiroshige; Taniguchi, Shunsuke; Sasaki, Kazunari

2015-01-01

Solid oxide fuel cells (SOFCs) are promising electrochemical devices that enable the highest fuel-to-electricity conversion efficiencies under high operating temperatures. The concept of multi-stage electrochemical oxidation using SOFCs has been proposed and studied over the past several decades for further improving the electrical efficiency. However, the improvement is limited by fuel dilution downstream of the fuel flow. Therefore, evolved technologies are required to achieve considerably higher electrical efficiencies. Here we present an innovative concept for a critically-high fuel-to-electricity conversion efficiency of up to 85% based on the lower heating value (LHV), in which a high-temperature multi-stage electrochemical oxidation is combined with a proton-conducting solid electrolyte. Switching a solid electrolyte material from a conventional oxide-ion conducting material to a proton-conducting material under the high-temperature multi-stage electrochemical oxidation mechanism has proven to be highly advantageous for the electrical efficiency. The DC efficiency of 85% (LHV) corresponds to a net AC efficiency of approximately 76% (LHV), where the net AC efficiency refers to the transmission-end AC efficiency. This evolved concept will yield a considerably higher efficiency with a much smaller generation capacity than the state-of-the-art several tens-of-MW-class most advanced combined cycle (MACC). PMID:26218470

Effect of proton-conduction in electrolyte on electric efficiency of multi-stage solid oxide fuel cells.

PubMed

Matsuzaki, Yoshio; Tachikawa, Yuya; Somekawa, Takaaki; Hatae, Toru; Matsumoto, Hiroshige; Taniguchi, Shunsuke; Sasaki, Kazunari

2015-07-28

Solid oxide fuel cells (SOFCs) are promising electrochemical devices that enable the highest fuel-to-electricity conversion efficiencies under high operating temperatures. The concept of multi-stage electrochemical oxidation using SOFCs has been proposed and studied over the past several decades for further improving the electrical efficiency. However, the improvement is limited by fuel dilution downstream of the fuel flow. Therefore, evolved technologies are required to achieve considerably higher electrical efficiencies. Here we present an innovative concept for a critically-high fuel-to-electricity conversion efficiency of up to 85% based on the lower heating value (LHV), in which a high-temperature multi-stage electrochemical oxidation is combined with a proton-conducting solid electrolyte. Switching a solid electrolyte material from a conventional oxide-ion conducting material to a proton-conducting material under the high-temperature multi-stage electrochemical oxidation mechanism has proven to be highly advantageous for the electrical efficiency. The DC efficiency of 85% (LHV) corresponds to a net AC efficiency of approximately 76% (LHV), where the net AC efficiency refers to the transmission-end AC efficiency. This evolved concept will yield a considerably higher efficiency with a much smaller generation capacity than the state-of-the-art several tens-of-MW-class most advanced combined cycle (MACC).

p-adic stochastic hidden variable model

NASA Astrophysics Data System (ADS)

Khrennikov, Andrew

1998-03-01

We propose stochastic hidden variables model in which hidden variables have a p-adic probability distribution ρ(λ) and at the same time conditional probabilistic distributions P(U,λ), U=A,A',B,B', are ordinary probabilities defined on the basis of the Kolmogorov measure-theoretical axiomatics. A frequency definition of p-adic probability is quite similar to the ordinary frequency definition of probability. p-adic frequency probability is defined as the limit of relative frequencies νn but in the p-adic metric. We study a model with p-adic stochastics on the level of the hidden variables description. But, of course, responses of macroapparatuses have to be described by ordinary stochastics. Thus our model describes a mixture of p-adic stochastics of the microworld and ordinary stochastics of macroapparatuses. In this model probabilities for physical observables are the ordinary probabilities. At the same time Bell's inequality is violated.

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.

Von Neumann's impossibility proof: Mathematics in the service of rhetorics

NASA Astrophysics Data System (ADS)

Dieks, Dennis

2017-11-01

According to what has become a standard history of quantum mechanics, in 1932 von Neumann persuaded the physics community that hidden variables are impossible as a matter of principle, after which leading proponents of the Copenhagen interpretation put the situation to good use by arguing that the completeness of quantum mechanics was undeniable. This state of affairs lasted, so the story continues, until Bell in 1966 exposed von Neumann's proof as obviously wrong. The realization that von Neumann's proof was fallacious then rehabilitated hidden variables and made serious foundational research possible again. It is often added in recent accounts that von Neumann's error had been spotted almost immediately by Grete Hermann, but that her discovery was of no effect due to the dominant Copenhagen Zeitgeist. We shall attempt to tell a story that is more historically accurate and less ideologically charged. Most importantly, von Neumann never claimed to have shown the impossibility of hidden variables tout court, but argued that hidden-variable theories must possess a structure that deviates fundamentally from that of quantum mechanics. Both Hermann and Bell appear to have missed this point; moreover, both raised unjustified technical objections to the proof. Von Neumann's argument was basically that hidden-variables schemes must violate the ;quantum principle; that physical quantities are to be represented by operators in a Hilbert space. As a consequence, hidden-variables schemes, though possible in principle, necessarily exhibit a certain kind of contextuality. As we shall illustrate, early reactions to Bohm's theory are in agreement with this account. Leading physicists pointed out that Bohm's theory has the strange feature that pre-existing particle properties do not generally reveal themselves in measurements, in accordance with von Neumann's result. They did not conclude that the ;impossible was done; and that von Neumann had been shown wrong.

Heisenberg (and Schrödinger, and Pauli) on hidden variables

NASA Astrophysics Data System (ADS)

Bacciagaluppi, Guido; Crull, Elise

In this paper, we discuss various aspects of Heisenberg's thought on hidden variables in the period 1927-1935. We also compare Heisenberg's approach to others current at the time, specifically that embodied by von Neumann's impossibility proof, but also views expressed mainly in correspondence by Pauli and by Schrödinger. We shall base ourselves mostly on published and unpublished materials that are known but little-studied, among others Heisenberg's own draft response to the EPR paper. Our aim will be not only to clarify Heisenberg's thought on the hidden-variables question, but in part also to clarify how this question was understood more generally at the time.

Computational study of peptide permeation through membrane: searching for hidden slow variables

NASA Astrophysics Data System (ADS)

Cardenas, Alfredo E.; Elber, Ron

2013-12-01

Atomically detailed molecular dynamics trajectories in conjunction with Milestoning are used to analyse the different contributions of coarse variables to the permeation process of a small peptide (N-acetyl-l-tryptophanamide, NATA) through a 1,2-dioleoyl-sn-glycero-3-phosphocholine membrane. The peptide reverses its overall orientation as it permeates through the biological bilayer. The large change in orientation is investigated explicitly but is shown to impact the free energy landscape and permeation time only moderately. Nevertheless, a significant difference in permeation properties of the two halves of the membrane suggests the presence of other hidden slow variables. We speculate, based on calculation of the potential of mean force, that a conformational transition of NATA makes significant contribution to these differences. Other candidates for hidden slow variables may include water permeation and collective motions of phospholipids.

Microplastics co-gasification with biomass: Modelling syngas characteristics at low temperatures

NASA Astrophysics Data System (ADS)

Ramos, Ana; Tavares, Raquel; Rouboa, Abel

2018-05-01

To assess the syngas produced through the gasification of microplastics at low temperatures, distinct blends of polyethylene terephthalate (PET) with biomass (vine pruning) were modelled using Aspen Plus. Critical gasification parameters such as co-fuel mixture, temperature and hydrogen production were evaluated, under two different gasifier agents (air and O2). Results have shown that higher PET ratios and higher temperatures (< 1200 °C) lead to enhanced hydrogen yields, for both atmospheres. The calorific content was also seen to increase with growing temperatures, superior LHV being achieved for the mixture with less microplastics fraction (9.2 MJ/Nm3) for both air and O2 environments. A final high-quality syngas was achieved, the dominant requirement determining which parameter to optimize: on one hand, higher H2 contents were seen for the blend with higher microplastic fraction, and on the other higher LHV was achieved for the equimolar mixture.

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.

Communication cost of simulating Bell correlations.

PubMed

Toner, B F; Bacon, D

2003-10-31

What classical resources are required to simulate quantum correlations? For the simplest and most important case of local projective measurements on an entangled Bell pair state, we show that exact simulation is possible using local hidden variables augmented by just one bit of classical communication. Certain quantum teleportation experiments, which teleport a single qubit, therefore admit a local hidden variables model.

A Proposal for Testing Local Realism Without Using Assumptions Related to Hidden Variable States

NASA Technical Reports Server (NTRS)

Ryff, Luiz Carlos

1996-01-01

A feasible experiment is discussed which allows us to prove a Bell's theorem for two particles without using an inequality. The experiment could be used to test local realism against quantum mechanics without the introduction of additional assumptions related to hidden variables states. Only assumptions based on direct experimental observation are needed.

All quantum observables in a hidden-variable model must commute simultaneously

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

Malley, James D.

Under a standard set of assumptions for a hidden-variable model for quantum events we show that all observables must commute simultaneously. This seems to be an ultimate statement about the inapplicability of the usual hidden-variable model for quantum events. And, despite Bell's complaint that a key condition of von Neumann's was quite unrealistic, we show that these conditions, under which von Neumann produced the first no-go proof, are entirely equivalent to those introduced by Bell and Kochen and Specker. As these conditions are also equivalent to those under which the Bell-Clauster-Horne inequalities are derived, we see that the experimental violationsmore » of the inequalities demonstrate only that quantum observables do not commute.« less

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

Miller, D. J.

It is shown that a weak measurement of a quantum system produces a new state of the quantum system which depends on the prior state, as well as the (uncontrollable) measured position of the pointer variable of the weak-measurement apparatus. The result imposes a constraint on hidden-variable theories which assign a different state to a quantum system than standard quantum mechanics. The constraint means that a crypto-nonlocal hidden-variable theory can be ruled out in a more direct way than previously done.

State-dependent rotations of spins by weak measurements

NASA Astrophysics Data System (ADS)

Miller, D. J.

2011-03-01

It is shown that a weak measurement of a quantum system produces a new state of the quantum system which depends on the prior state, as well as the (uncontrollable) measured position of the pointer variable of the weak-measurement apparatus. The result imposes a constraint on hidden-variable theories which assign a different state to a quantum system than standard quantum mechanics. The constraint means that a crypto-nonlocal hidden-variable theory can be ruled out in a more direct way than previously done.

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

Hardy's argument and successive spin-s measurements

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

Ahanj, Ali

2010-07-15

We consider a hidden-variable theoretic description of successive measurements of noncommuting spin observables on an input spin-s state. In this scenario, the hidden-variable theory leads to a Hardy-type argument that quantum predictions violate it. We show that the maximum probability of success of Hardy's argument in quantum theory is ((1/2)){sup 4s}, which is more than in the spatial case.

Improvement of Early Antenatal Care Initiation: The Effects of Training Local Health Volunteers in the Community.

PubMed

Liabsuetrakul, Tippawan; Oumudee, Nurlisa; Armeeroh, Masuenah; Nima, Niamina; Duerahing, Nurosanah

2018-01-01

Although antenatal care (ANC) coverage has been increasing in low- and middle-income countries, the adherence to the ANC initiation standards at gestational age <12 weeks was inadequate including Thailand. The study aimed to improve the rate of early ANC initiation by training the existing local health volunteers (LHVs) in 3 southernmost provinces of Thailand. A clustered nonrandomized intervention study was conducted from November 2012 to February 2014. One district of each province was selected to be the study intervention districts for that province. A total of 124 LHVs in the intervention districts participated in the knowledge-counseling intervention. It was organized as half-day workshop using 2 training modules each comprising a 30-minute lecture followed by counseling practice in pairs for 1 hour. Outcome was the rate of early ANC initiation among women giving birth, and its association with intervention, meeting an LHV, and months after training was analyzed. Of 6677 women, 3178 and 3499 women were in the control and intervention groups, respectively. Rates of early ANC were significantly improved after the intervention (adjusted odds ratio [OR]: 1.29, 95% confidence interval [CI]: 1.17-1.43, P < .001) and meeting an LHV (adjusted OR: 2.06, 95% CI: 1.86-2.29, P < .001), but lower at 6 months after training (adjusted OR: 0.76, 95% CI: 0.60-0.96, P = .002). Almost all women (99.7%) in the intervention group who met an LHV reported that they were encouraged to attend early ANC. Training LHVs in communities by knowledge-counseling intervention significantly improved early ANC initiation, but the magnitude of change was still limited.

Improvement of Early Antenatal Care Initiation

PubMed Central

Oumudee, Nurlisa; Armeeroh, Masuenah; Nima, Niamina; Duerahing, Nurosanah

2018-01-01

Background: Although antenatal care (ANC) coverage has been increasing in low- and middle-income countries, the adherence to the ANC initiation standards at gestational age <12 weeks was inadequate including Thailand. The study aimed to improve the rate of early ANC initiation by training the existing local health volunteers (LHVs) in 3 southernmost provinces of Thailand. Methods: A clustered nonrandomized intervention study was conducted from November 2012 to February 2014. One district of each province was selected to be the study intervention districts for that province. A total of 124 LHVs in the intervention districts participated in the knowledge–counseling intervention. It was organized as half-day workshop using 2 training modules each comprising a 30-minute lecture followed by counseling practice in pairs for 1 hour. Outcome was the rate of early ANC initiation among women giving birth, and its association with intervention, meeting an LHV, and months after training was analyzed. Results: Of 6677 women, 3178 and 3499 women were in the control and intervention groups, respectively. Rates of early ANC were significantly improved after the intervention (adjusted odds ratio [OR]: 1.29, 95% confidence interval [CI]: 1.17-1.43, P < .001) and meeting an LHV (adjusted OR: 2.06, 95% CI: 1.86-2.29, P < .001), but lower at 6 months after training (adjusted OR: 0.76, 95% CI: 0.60-0.96, P = .002). Almost all women (99.7%) in the intervention group who met an LHV reported that they were encouraged to attend early ANC. Conclusion: Training LHVs in communities by knowledge–counseling intervention significantly improved early ANC initiation, but the magnitude of change was still limited. PMID:29657959

Hidden Statistics of Schroedinger Equation

NASA Technical Reports Server (NTRS)

Zak, Michail

2011-01-01

Work was carried out in determination of the mathematical origin of randomness in quantum mechanics and creating a hidden statistics of Schr dinger equation; i.e., to expose the transitional stochastic process as a "bridge" to the quantum world. The governing equations of hidden statistics would preserve such properties of quantum physics as superposition, entanglement, and direct-product decomposability while allowing one to measure its state variables using classical methods.

Central Compact Objects in Kes 79 and RCW 103 as `Hidden' Magnetars with Crustal Activity

NASA Astrophysics Data System (ADS)

Popov, S. B.; Kaurov, A. A.; Kaminker, A. D.

2015-05-01

We propose that observations of `hidden' magnetars in central compact objects can be used to probe crustal activity of neutron stars with large internal magnetic fields. Estimates based on calculations by Perna & Pons, Pons & Rea and Kaminker et al. suggest that central compact objects, which are proposed to be `hidden' magnetars, must demonstrate flux variations on the time scale of months-years. However, the most prominent candidate for the `hidden' magnetars - CXO J1852.6+0040 in Kes 79 - shows constant (within error bars) flux. This can be interpreted by lower variable crustal activity than in typical magnetars. Alternatively, CXO J1852.6+0040 can be in a high state of variable activity during the whole period of observations. Then we consider the source 1E161348 - 5055 in RCW103 as another candidate. Employing a simple 2D-modelling we argue that properties of the source can be explained by the crustal activity of the magnetar type. Thus, this object may be supplemented for the three known candidates for the `hidden' magnetars among central compact objects discussed in literature.

A Bell-type theorem without hidden variables

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

Stapp, Henry P.

2003-09-12

It is shown that no theory that satisfies certain premises can exclude faster-than-light influences. The premises include neither the existence of hidden variables nor counterfactual definiteness, nor any premise that effectively entails the general existence of outcomes of unperformed local measurements. All the premises are compatible with Copenhagen philosophy and the principles and predictions of relativistic quantum field theory. The present proof is contrasted with an earlier one with the same objective.

Violation of Leggett-type inequalities in the spin-orbit degrees of freedom of a single photon

NASA Astrophysics Data System (ADS)

Cardano, Filippo; Karimi, Ebrahim; Marrucci, Lorenzo; de Lisio, Corrado; Santamato, Enrico

2013-09-01

We report the experimental violation of Leggett-type inequalities for a hybrid entangled state of spin and orbital angular momentum of a single photon. These inequalities give a physical criterion to verify the possible validity of a class of hidden-variable theories, originally named “crypto nonlocal,” that are not excluded by the violation of Bell-type inequalities. In our case, the tested theories assume the existence of hidden variables associated with independent degrees of freedom of the same particle, while admitting the possibility of an influence between the two measurements, i.e., the so-called contextuality of observables. We observe a violation of the Leggett inequalities for a range of experimental inputs, with a maximum violation of seven standard deviations, thus ruling out this class of hidden-variable models with a high level of confidence.

Modeling the energy content of combustible ship-scrapping waste at Alang-Sosiya, India, using multiple regression analysis.

PubMed

Reddy, M Srinivasa; Basha, Shaik; Joshi, H V; Sravan Kumar, V G; Jha, B; Ghosh, P K

2005-01-01

Alang-Sosiya is the largest ship-scrapping yard in the world, established in 1982. Every year an average of 171 ships having a mean weight of 2.10 x 10(6)(+/-7.82 x 10(5)) of light dead weight tonnage (LDT) being scrapped. Apart from scrapped metals, this yard generates a massive amount of combustible solid waste in the form of waste wood, plastic, insulation material, paper, glass wool, thermocol pieces (polyurethane foam material), sponge, oiled rope, cotton waste, rubber, etc. In this study multiple regression analysis was used to develop predictive models for energy content of combustible ship-scrapping solid wastes. The scope of work comprised qualitative and quantitative estimation of solid waste samples and performing a sequential selection procedure for isolating variables. Three regression models were developed to correlate the energy content (net calorific values (LHV)) with variables derived from material composition, proximate and ultimate analyses. The performance of these models for this particular waste complies well with the equations developed by other researchers (Dulong, Steuer, Scheurer-Kestner and Bento's) for estimating energy content of municipal solid waste.

Context-invariant quasi hidden variable (qHV) modelling of all joint von Neumann measurements for an arbitrary Hilbert space

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

Loubenets, Elena R.

We prove the existence for each Hilbert space of the two new quasi hidden variable (qHV) models, statistically noncontextual and context-invariant, reproducing all the von Neumann joint probabilities via non-negative values of real-valued measures and all the quantum product expectations—via the qHV (classical-like) average of the product of the corresponding random variables. In a context-invariant model, a quantum observable X can be represented by a variety of random variables satisfying the functional condition required in quantum foundations but each of these random variables equivalently models X under all joint von Neumann measurements, regardless of their contexts. The proved existence ofmore » this model negates the general opinion that, in terms of random variables, the Hilbert space description of all the joint von Neumann measurements for dimH≥3 can be reproduced only contextually. The existence of a statistically noncontextual qHV model, in particular, implies that every N-partite quantum state admits a local quasi hidden variable model introduced in Loubenets [J. Math. Phys. 53, 022201 (2012)]. The new results of the present paper point also to the generality of the quasi-classical probability model proposed in Loubenets [J. Phys. A: Math. Theor. 45, 185306 (2012)].« less

A Top-down versus a Bottom-up Hidden-variables Description of the Stern-Gerlach Experiment

NASA Astrophysics Data System (ADS)

Arsenijević, M.; Jeknić-Dugić, J.; Dugić, M.

We employ the Stern-Gerlach experiment to highlight the basics of a minimalist, non-interpretational top-down approach to quantum foundations. Certain benefits of the "quantum structural studies" (QSS) highlightedhere are detected and discussed. While the top-down approach can be described without making any reference to the fundamental structure of a closed system, the hidden variables (HV) theory á la Bohm proves to be more subtle than it is typically regarded.

Bayesian Inference and Online Learning in Poisson Neuronal Networks.

PubMed

Huang, Yanping; Rao, Rajesh P N

2016-08-01

Motivated by the growing evidence for Bayesian computation in the brain, we show how a two-layer recurrent network of Poisson neurons can perform both approximate Bayesian inference and learning for any hidden Markov model. The lower-layer sensory neurons receive noisy measurements of hidden world states. The higher-layer neurons infer a posterior distribution over world states via Bayesian inference from inputs generated by sensory neurons. We demonstrate how such a neuronal network with synaptic plasticity can implement a form of Bayesian inference similar to Monte Carlo methods such as particle filtering. Each spike in a higher-layer neuron represents a sample of a particular hidden world state. The spiking activity across the neural population approximates the posterior distribution over hidden states. In this model, variability in spiking is regarded not as a nuisance but as an integral feature that provides the variability necessary for sampling during inference. We demonstrate how the network can learn the likelihood model, as well as the transition probabilities underlying the dynamics, using a Hebbian learning rule. We present results illustrating the ability of the network to perform inference and learning for arbitrary hidden Markov models.

Use of Partial Least Squares improves the efficacy of removing unwanted variability in differential expression analyses based on RNA-Seq data.

PubMed

Chakraborty, Sutirtha

2018-05-26

RNA-Seq technology has revolutionized the face of gene expression profiling by generating read count data measuring the transcript abundances for each queried gene on multiple experimental subjects. But on the downside, the underlying technical artefacts and hidden biological profiles of the samples generate a wide variety of latent effects that may potentially distort the actual transcript/gene expression signals. Standard normalization techniques fail to correct for these hidden variables and lead to flawed downstream analyses. In this work I demonstrate the use of Partial Least Squares (built as an R package 'SVAPLSseq') to correct for the traces of extraneous variability in RNA-Seq data. A novel and thorough comparative analysis of the PLS based method is presented along with some of the other popularly used approaches for latent variable correction in RNA-Seq. Overall, the method is found to achieve a substantially improved estimation of the hidden effect signatures in the RNA-Seq transcriptome expression landscape compared to other available techniques. Copyright © 2017. Published by Elsevier Inc.

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.

Pyrolysis of automotive shredder residue in a bench scale rotary kiln.

PubMed

Notarnicola, Michele; Cornacchia, Giacinto; De Gisi, Sabino; Di Canio, Francesco; Freda, Cesare; Garzone, Pietro; Martino, Maria; Valerio, Vito; Villone, Antonio

2017-07-01

Automotive shredder residue (ASR) can create difficulties when managing, with its production increasing. It is made of different type of plastics, foams, elastomers, wood, glasses and textiles. For this reason, it is complicated to dispose of in a cost effective way, while also respecting the stringent environmental restrictions. Among thermal treatments, pyrolysis seems to offer an environmentally attractive method for the treatment of ASR; it also allows for the recovery of valuable secondary materials/fuels such as pyrolysis oils, chars, and gas. While, there is a great deal of significant research on ASR pyrolysis, the literature on higher scale pyrolysis experiments is limited. To improve current literature, the aim of the study was to investigate the pyrolysis of ASR in a bench scale rotary kiln. The Italian ASR was separated by dry-sieving into two particle size fractions: d<30mm and d>30mm. Both the streams were grounded, pelletized and then pyrolyzed in a continuous bench scale rotary kiln at 450, 550 and 650°C. The mass flow rate of the ASR pellets was 200-350g/h and each test ran for about 4-5h. The produced char, pyrolysis oil and syngas were quantified to determine product distribution. They were thoroughly analyzed with regard to their chemical and physical properties. The results show how higher temperatures increase the pyrolysis gas yield (44wt% at 650°C) as well as its heating value. The low heating value (LHV) of syngas ranges between 18 and 26MJ/Nm 3 dry. The highest pyrolysis oil yield (33wt.%) was observed at 550°C and its LHV ranges between 12.5 and 14.5MJ/kg. Furthermore, only two out of the six produced chars respect the LHV limit set by the Italian environmental regulations for landfilling. The obtained results in terms of product distribution and their chemical-physical analyses provide useful information for plant scale-up. Copyright © 2017 Elsevier Ltd. All rights reserved.

Deep Restricted Kernel Machines Using Conjugate Feature Duality.

PubMed

Suykens, Johan A K

2017-08-01

The aim of this letter is to propose a theory of deep restricted kernel machines offering new foundations for deep learning with kernel machines. From the viewpoint of deep learning, it is partially related to restricted Boltzmann machines, which are characterized by visible and hidden units in a bipartite graph without hidden-to-hidden connections and deep learning extensions as deep belief networks and deep Boltzmann machines. From the viewpoint of kernel machines, it includes least squares support vector machines for classification and regression, kernel principal component analysis (PCA), matrix singular value decomposition, and Parzen-type models. A key element is to first characterize these kernel machines in terms of so-called conjugate feature duality, yielding a representation with visible and hidden units. It is shown how this is related to the energy form in restricted Boltzmann machines, with continuous variables in a nonprobabilistic setting. In this new framework of so-called restricted kernel machine (RKM) representations, the dual variables correspond to hidden features. Deep RKM are obtained by coupling the RKMs. The method is illustrated for deep RKM, consisting of three levels with a least squares support vector machine regression level and two kernel PCA levels. In its primal form also deep feedforward neural networks can be trained within this framework.

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.

Local hidden-variable model for a recent experimental test of quantum nonlocality and local contextuality

NASA Astrophysics Data System (ADS)

La Cour, Brian R.

2017-07-01

An experiment has recently been performed to demonstrate quantum nonlocality by establishing contextuality in one of a pair of photons encoding four qubits; however, low detection efficiencies and use of the fair-sampling hypothesis leave these results open to possible criticism due to the detection loophole. In this Letter, a physically motivated local hidden-variable model is considered as a possible mechanism for explaining the experimentally observed results. The model, though not intrinsically contextual, acquires this quality upon post-selection of coincident detections.

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.

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.

From Wang-Chen System with Only One Stable Equilibrium to a New Chaotic System Without Equilibrium

NASA Astrophysics Data System (ADS)

Pham, Viet-Thanh; Wang, Xiong; Jafari, Sajad; Volos, Christos; Kapitaniak, Tomasz

2017-06-01

Wang-Chen system with only one stable equilibrium as well as the coexistence of hidden attractors has attracted increasing interest due to its striking features. In this work, the effect of state feedback on Wang-Chen system is investigated by introducing a further state variable. It is worth noting that a new chaotic system without equilibrium is obtained. We believe that the system is an interesting example to illustrate the conversion of hidden attractors with one stable equilibrium to hidden attractors without equilibrium.

High pressure air compressor valve fault diagnosis using feedforward neural networks

NASA Astrophysics Data System (ADS)

James Li, C.; Yu, Xueli

1995-09-01

Feedforward neural networks (FNNs) are developed and implemented to classify a four-stage high pressure air compressor into one of the following conditions: baseline, suction or exhaust valve faults. These FNNs are used for the compressor's automatic condition monitoring and fault diagnosis. Measurements of 39 variables are obtained under different baseline conditions and third-stage suction and exhaust valve faults. These variables include pressures and temperatures at all stages, voltage between phase aand phase b, voltage between phase band phase c, total three-phase real power, cooling water flow rate, etc. To reduce the number of variables, the amount of their discriminatory information is quantified by scattering matrices to identify statistical significant ones. Measurements of the selected variables are then used by a fully automatic structural and weight learning algorithm to construct three-layer FNNs to classify the compressor's condition. This learning algorithm requires neither guesses of initial weight values nor number of neurons in the hidden layer of an FNN. It takes an incremental approach in which a hidden neuron is trained by exemplars and then augmented to the existing network. These exemplars are then made orthogonal to the newly identified hidden neuron. They are subsequently used for the training of the next hidden neuron. The betterment continues until a desired accuracy is reached. After the neural networks are established, novel measurements from various conditions that haven't been previously seen by the FNNs are then used to evaluate their ability in fault diagnosis. The trained neural networks provide very accurate diagnosis for suction and discharge valve defects.

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.

Subtleties of Hidden Quantifiers in Implication

ERIC Educational Resources Information Center

Shipman, Barbara A.

2016-01-01

Mathematical conjectures and theorems are most often of the form P(x) ? Q(x), meaning ?x,P(x) ? Q(x). The hidden quantifier ?x is crucial in understanding the implication as a statement with a truth value. Here P(x) and Q(x) alone are only predicates, without truth values, since they contain unquantified variables. But standard textbook…

Algorithmic information theory and the hidden variable question

NASA Technical Reports Server (NTRS)

Fuchs, Christopher

1992-01-01

The admissibility of certain nonlocal hidden-variable theories are explained via information theory. Consider a pair of Stern-Gerlach devices with fixed nonparallel orientations that periodically perform spin measurements on identically prepared pairs of electrons in the singlet spin state. Suppose the outcomes are recorded as binary strings l and r (with l sub n and r sub n denoting their n-length prefixes). The hidden-variable theories considered here require that there exists a recursive function which may be used to transform l sub n into r sub n for any n. This note demonstrates that such a theory cannot reproduce all the statistical predictions of quantum mechanics. Specifically, consider an ensemble of outcome pairs (l,r). From the associated probability measure, the Shannon entropies H sub n and H bar sub n for strings l sub n and pairs (l sub n, r sub n) may be formed. It is shown that such a theory requires that the absolute value of H bar sub n - H sub n be bounded - contrasting the quantum mechanical prediction that it grow with n.

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

Hoban, Matty J.; Department of Computer Science, University of Oxford, Wolfson Building, Parks Road, Oxford OX1 3QD; Wallman, Joel J.

We consider general settings of Bell inequality experiments with many parties, where each party chooses from a finite number of measurement settings each with a finite number of outcomes. We investigate the constraints that Bell inequalities place upon the correlations possible in local hidden variable theories using a geometrical picture of correlations. We show that local hidden variable theories can be characterized in terms of limited computational expressiveness, which allows us to characterize families of Bell inequalities. The limited computational expressiveness for many settings (each with many outcomes) generalizes previous results about the many-party situation each with a choice ofmore » two possible measurements (each with two outcomes). Using this computational picture we present generalizations of the Popescu-Rohrlich nonlocal box for many parties and nonbinary inputs and outputs at each site. Finally, we comment on the effect of preprocessing on measurement data in our generalized setting and show that it becomes problematic outside of the binary setting, in that it allows local hidden variable theories to simulate maximally nonlocal correlations such as those of these generalized Popescu-Rohrlich nonlocal boxes.« less

Determinism, independence, and objectivity are incompatible.

PubMed

Ionicioiu, Radu; Mann, Robert B; Terno, Daniel R

2015-02-13

Hidden-variable models aim to reproduce the results of quantum theory and to satisfy our classical intuition. Their refutation is usually based on deriving predictions that are different from those of quantum mechanics. Here instead we study the mutual compatibility of apparently reasonable classical assumptions. We analyze a version of the delayed-choice experiment which ostensibly combines determinism, independence of hidden variables on the conducted experiments, and wave-particle objectivity (the assertion that quantum systems are, at any moment, either particles or waves, but not both). These three ideas are incompatible with any theory, not only with quantum mechanics.

Characterization of Korean solid recovered fuels (SRFs): an analysis and comparison of SRFs.

PubMed

Choi, Yeon-Seok; Han, Soyoung; Choi, Hang-Seok; Kim, Seock-Joon

2012-04-01

To date, Korea has used four species of solid recovered fuels (SRFs) which have been certified by the Environmental Ministry of Korea: refuse-derived fuel (RDF), refused plastic fuel (RPF), tyre-derived fuel (TDF), and wood chip fuel (WCF). These fuels have been used in many industrial boilers. In this study, seven regulatory properties associated with each of the four species: particle size, moisture and ash content, lower heating value (LHV), total chlorine, sulfur, and heavy metals content (Pb, As, Cd, Hg, Cr) were analysed. These properties are the main regulation criteria for the usage and transfer of SRFs in Korea. Different properties of each SRF were identified on the basis of data collected over the last 3 years in Korea, and the manufacturing process problem associated with the production of SRFs were considered. It was found that the high moisture content of SRFs (especially WCF) could directly lead to the low LHV of SRFs and that the poor screening and sorting of raw materials could cause defective SRF products with high ash or chlorine contents. The information obtained from this study could contribute to the manufacturing of SRF with good quality.

Predicting the ultimate potential of natural gas SOFC power cycles with CO2 capture - Part A: Methodology and reference cases

NASA Astrophysics Data System (ADS)

Campanari, Stefano; Mastropasqua, Luca; Gazzani, Matteo; Chiesa, Paolo; Romano, Matteo C.

2016-08-01

Driven by the search for the highest theoretical efficiency, in the latest years several studies investigated the integration of high temperature fuel cells in natural gas fired power plants, where fuel cells are integrated with simple or modified Brayton cycles and/or with additional bottoming cycles, and CO2 can be separated via chemical or physical separation, oxy-combustion and cryogenic methods. Focusing on Solid Oxide Fuel Cells (SOFC) and following a comprehensive review and analysis of possible plant configurations, this work investigates their theoretical potential efficiency and proposes two ultra-high efficiency plant configurations based on advanced intermediate-temperature SOFCs integrated with a steam turbine or gas turbine cycle. The SOFC works at atmospheric or pressurized conditions and the resulting power plant exceeds 78% LHV efficiency without CO2 capture (as discussed in part A of the work) and 70% LHV efficiency with substantial CO2 capture (part B). The power plants are simulated at the 100 MW scale with a complete set of realistic assumptions about fuel cell (FC) performance, plant components and auxiliaries, presenting detailed energy and material balances together with a second law analysis.

Hidden symmetry in the confined hydrogen atom problem

NASA Astrophysics Data System (ADS)

Pupyshev, Vladimir I.; Scherbinin, Andrei V.

2002-07-01

The classical counterpart of the well-known quantum mechanical model of a spherically confined hydrogen atom is examined in terms of the Lenz vector, a dynamic variable featuring the conventional Kepler problem. It is shown that a conditional conservation law associated with the Lenz vector is true, in fair agreement with the corresponding quantum problem previously found to exhibit a hidden symmetry as well.

Inference for dynamics of continuous variables: the extended Plefka expansion with hidden nodes

NASA Astrophysics Data System (ADS)

Bravi, B.; Sollich, P.

2017-06-01

We consider the problem of a subnetwork of observed nodes embedded into a larger bulk of unknown (i.e. hidden) nodes, where the aim is to infer these hidden states given information about the subnetwork dynamics. The biochemical networks underlying many cellular and metabolic processes are important realizations of such a scenario as typically one is interested in reconstructing the time evolution of unobserved chemical concentrations starting from the experimentally more accessible ones. We present an application to this problem of a novel dynamical mean field approximation, the extended Plefka expansion, which is based on a path integral description of the stochastic dynamics. As a paradigmatic model we study the stochastic linear dynamics of continuous degrees of freedom interacting via random Gaussian couplings. The resulting joint distribution is known to be Gaussian and this allows us to fully characterize the posterior statistics of the hidden nodes. In particular the equal-time hidden-to-hidden variance—conditioned on observations—gives the expected error at each node when the hidden time courses are predicted based on the observations. We assess the accuracy of the extended Plefka expansion in predicting these single node variances as well as error correlations over time, focussing on the role of the system size and the number of observed nodes.

Variable complexity online sequential extreme learning machine, with applications to streamflow prediction

NASA Astrophysics Data System (ADS)

Lima, Aranildo R.; Hsieh, William W.; Cannon, Alex J.

2017-12-01

In situations where new data arrive continually, online learning algorithms are computationally much less costly than batch learning ones in maintaining the model up-to-date. The extreme learning machine (ELM), a single hidden layer artificial neural network with random weights in the hidden layer, is solved by linear least squares, and has an online learning version, the online sequential ELM (OSELM). As more data become available during online learning, information on the longer time scale becomes available, so ideally the model complexity should be allowed to change, but the number of hidden nodes (HN) remains fixed in OSELM. A variable complexity VC-OSELM algorithm is proposed to dynamically add or remove HN in the OSELM, allowing the model complexity to vary automatically as online learning proceeds. The performance of VC-OSELM was compared with OSELM in daily streamflow predictions at two hydrological stations in British Columbia, Canada, with VC-OSELM significantly outperforming OSELM in mean absolute error, root mean squared error and Nash-Sutcliffe efficiency at both stations.

Free energy and hidden barriers of the β-sheet structure of prion protein.

PubMed

Paz, S Alexis; Abrams, Cameron F

2015-10-13

On-the-fly free-energy parametrization is a new collective variable biasing approach akin to metadynamics with one important distinction: rather than acquiring an accelerated distribution via a history-dependent bias potential, sampling on this distribution is achieved from the beginning of the simulation using temperature-accelerated molecular dynamics. In the present work, we compare the performance of both approaches to compute the free-energy profile along a scalar collective variable measuring the H-bond registry of the β-sheet structure of the mouse Prion protein. Both methods agree on the location of the free-energy minimum, but free-energy profiles from well-tempered metadynamics are subject to a much higher degree of statistical noise due to hidden barriers. The sensitivity of metadynamics to hidden barriers is shown to be a consequence of the history dependence of the bias potential, and we detail the nature of these barriers for the prion β-sheet. In contrast, on-the-fly parametrization is much less sensitive to these barriers and thus displays improved convergence behavior relative to that of metadynamics. While hidden barriers are a frequent and central issue in free-energy methods, on-the-fly free-energy parametrization appears to be a robust and preferable method to confront this issue.

Heat Exchanger Design and Testing for a 6-Inch Rotating Detonation Engine

DTIC Science & Technology

2013-03-01

Engine Research Facility HHV Higher heating value LHV Lower heating value PDE Pulsed detonation engine RDE Rotating detonation engine RTD...the combustion community are pulse detonation engines ( PDEs ) and rotating detonation engines (RDEs). 1.1 Differences between Pulsed and Rotating ...steadier than that of a PDE (2, 3). (2) (3) Figure 1. Unrolled rotating detonation wave from high-speed video (4) Another difference that

Impact Testing of the H1224A Shipping/Storage Container

DTIC Science & Technology

1994-05-01

may not provide significant ener- gy absorption for the re - entry vehicle midsection but can provide some confinement of potentially damaged...Horizontal Low-Velocity impact test LHV Longitudinal High-Velocity impact test HHV Horizontal High-Velocity impact test RV Re - entry Vehicle midsection mass...Also, integration of these pulses showed that only a much shorter dura- tion pulse was necessary to slow the re - entry vehicle midsection velocity

Soil Moisture Limitations on Monitoring Boreal Forest Regrowth Using Spaceborne L-Band SAR Data

NASA Technical Reports Server (NTRS)

Kasischke, Eric S.; Tanase, Mihai A.; Bourgeau-Chavez, Laura L.; Borr, Matthew

2011-01-01

A study was carried out to investigate the utility of L-band SAR data for estimating aboveground biomass in sites with low levels of vegetation regrowth. Data to estimate biomass were collected from 59 sites located in fire-disturbed black spruce forests in interior Alaska. PALSAR L-band data (HH and HV polarizations) collected on two dates in the summer/fall of 2007 and one date in the summer of 2009 were used. Significant linear correlations were found between the log of aboveground biomass (range of 0.02 to 22.2 t ha-1) and (L-HH) and (L-HV) for the data collected on each of the three dates, with the highest correlation found using the LHV data collected when soil moisture was highest. Soil moisture, however, did change the correlations between L-band and aboveground biomass, and the analyses suggest that the influence of soil moisture is biomass dependent. The results indicate that to use L-band SAR data for mapping aboveground biomass and monitoring forest regrowth will require development of approaches to account for the influence that variations in soil moisture have on L-band microwave backscatter, which can be particularly strong when low levels of aboveground biomass occur

Life cycle carbon footprint of shale gas: review of evidence and implications.

PubMed

Weber, Christopher L; Clavin, Christopher

2012-06-05

The recent increase in the production of natural gas from shale deposits has significantly changed energy outlooks in both the US and world. Shale gas may have important climate benefits if it displaces more carbon-intensive oil or coal, but recent attention has discussed the potential for upstream methane emissions to counteract this reduced combustion greenhouse gas emissions. We examine six recent studies to produce a Monte Carlo uncertainty analysis of the carbon footprint of both shale and conventional natural gas production. The results show that the most likely upstream carbon footprints of these types of natural gas production are largely similar, with overlapping 95% uncertainty ranges of 11.0-21.0 g CO(2)e/MJ(LHV) for shale gas and 12.4-19.5 g CO(2)e/MJ(LHV) for conventional gas. However, because this upstream footprint represents less than 25% of the total carbon footprint of gas, the efficiency of producing heat, electricity, transportation services, or other function is of equal or greater importance when identifying emission reduction opportunities. Better data are needed to reduce the uncertainty in natural gas's carbon footprint, but understanding system-level climate impacts of shale gas, through shifts in national and global energy markets, may be more important and requires more detailed energy and economic systems assessments.

Coal-to-methanol: an engineering evaluation of Texaco gasification and ICI methanol-synthesis route. Final report

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

Buckingham, P.A.; Cobb, D.D.; Leavitt, A.A.

1981-08-01

This report presents the results of a technical and economic evaluation of producing methanol from bituminous coal using Texaco coal gasification and ICI methanol synthesis. The scope of work included the development of an overall configuration for a large plant comprising coal preparation, air separation, coal gasification, shift conversion, COS hydrolysis, acid gas removal, methanol synthesis, methanol refining, and all required utility systems and off-site facilities. Design data were received from both Texaco and ICI while a design and cost estimate were received from Lotepro covering the Rectisol acid gas removal unit. The plant processes 14,448 tons per day (drymore » basis) of Illinois No. 6 bituminous coal and produces 10,927 tons per day of fuel-grade methanol. An overall thermal efficiency of 57.86 percent was calculated on an HHV basis and 52.64 percent based on LHV. Total plant investment at an Illinois plant site was estimated to be $1159 million dollars in terms of 1979 investment. Using EPRI's economic premises, the first-year product costs were calculated to $4.74 per million Btu (HHV) which is equivalent to $30.3 cents per gallon and $5.37 per million Btu (LHV).« less

Pitowsky's Kolmogorovian Models and Super-determinism.

PubMed

Kellner, Jakob

2017-01-01

In an attempt to demonstrate that local hidden variables are mathematically possible, Pitowsky constructed "spin-[Formula: see text] functions" and later "Kolmogorovian models", which employs a nonstandard notion of probability. We describe Pitowsky's analysis and argue (with the benefit of hindsight) that his notion of hidden variables is in fact just super-determinism (and accordingly physically not relevant). Pitowsky's first construction uses the Continuum Hypothesis. Farah and Magidor took this as an indication that at some stage physics might give arguments for or against adopting specific new axioms of set theory. We would rather argue that it supports the opposing view, i.e., the widespread intuition "if you need a non-measurable function, it is physically irrelevant".

Sharp Contradiction for Local-Hidden-State Model in Quantum Steering.

PubMed

Chen, Jing-Ling; Su, Hong-Yi; Xu, Zhen-Peng; Pati, Arun Kumar

2016-08-26

In quantum theory, no-go theorems are important as they rule out the existence of a particular physical model under consideration. For instance, the Greenberger-Horne-Zeilinger (GHZ) theorem serves as a no-go theorem for the nonexistence of local hidden variable models by presenting a full contradiction for the multipartite GHZ states. However, the elegant GHZ argument for Bell's nonlocality does not go through for bipartite Einstein-Podolsky-Rosen (EPR) state. Recent study on quantum nonlocality has shown that the more precise description of EPR's original scenario is "steering", i.e., the nonexistence of local hidden state models. Here, we present a simple GHZ-like contradiction for any bipartite pure entangled state, thus proving a no-go theorem for the nonexistence of local hidden state models in the EPR paradox. This also indicates that the very simple steering paradox presented here is indeed the closest form to the original spirit of the EPR paradox.

Discovering Hidden Controlling Parameters using Data Analytics and Dimensional Analysis

NASA Astrophysics Data System (ADS)

Del Rosario, Zachary; Lee, Minyong; Iaccarino, Gianluca

2017-11-01

Dimensional Analysis is a powerful tool, one which takes a priori information and produces important simplifications. However, if this a priori information - the list of relevant parameters - is missing a relevant quantity, then the conclusions from Dimensional Analysis will be incorrect. In this work, we present novel conclusions in Dimensional Analysis, which provide a means to detect this failure mode of missing or hidden parameters. These results are based on a restated form of the Buckingham Pi theorem that reveals a ridge function structure underlying all dimensionless physical laws. We leverage this structure by constructing a hypothesis test based on sufficient dimension reduction, allowing for an experimental data-driven detection of hidden parameters. Both theory and examples will be presented, using classical turbulent pipe flow as the working example. Keywords: experimental techniques, dimensional analysis, lurking variables, hidden parameters, buckingham pi, data analysis. First author supported by the NSF GRFP under Grant Number DGE-114747.

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.

Applying Data Mining Techniques to Extract Hidden Patterns about Breast Cancer Survival in an Iranian Cohort Study.

PubMed

Khalkhali, Hamid Reza; Lotfnezhad Afshar, Hadi; Esnaashari, Omid; Jabbari, Nasrollah

2016-01-01

Breast cancer survival has been analyzed by many standard data mining algorithms. A group of these algorithms belonged to the decision tree category. Ability of the decision tree algorithms in terms of visualizing and formulating of hidden patterns among study variables were main reasons to apply an algorithm from the decision tree category in the current study that has not studied already. The classification and regression trees (CART) was applied to a breast cancer database contained information on 569 patients in 2007-2010. The measurement of Gini impurity used for categorical target variables was utilized. The classification error that is a function of tree size was measured by 10-fold cross-validation experiments. The performance of created model was evaluated by the criteria as accuracy, sensitivity and specificity. The CART model produced a decision tree with 17 nodes, 9 of which were associated with a set of rules. The rules were meaningful clinically. They showed in the if-then format that Stage was the most important variable for predicting breast cancer survival. The scores of accuracy, sensitivity and specificity were: 80.3%, 93.5% and 53%, respectively. The current study model as the first one created by the CART was able to extract useful hidden rules from a relatively small size dataset.

Test and Evaluation of the Heat Recovery Incinerator System at Naval Station, Mayport, Florida.

DTIC Science & Technology

1981-05-01

co m m~~C 0 -4 𔃺V 0.4 𔃺 Cl .4* C 0% ’ 039 TABLE 4-4. HEATING VALUES AND MOISTURE CONTENT OF DECEMBER REFUSE HHV LHV Moisture Basis (Btu/lb) (Btu/lb...36 Solid waste characteristics ..... ......... 36 Auxiliary fuel characteristics. ..... ....... 36 Ash characteristics ...... ............ 38 Bottom...49 4-15 Average Fuel and Flue Gas Analysis .. ........... ... 49 4-16 Air and Fuel Inputs ...... ................... ... 50 4

Hidden Markov models incorporating fuzzy measures and integrals for protein sequence identification and alignment.

PubMed

Bidargaddi, Niranjan P; Chetty, Madhu; Kamruzzaman, Joarder

2008-06-01

Profile hidden Markov models (HMMs) based on classical HMMs have been widely applied for protein sequence identification. The formulation of the forward and backward variables in profile HMMs is made under statistical independence assumption of the probability theory. We propose a fuzzy profile HMM to overcome the limitations of that assumption and to achieve an improved alignment for protein sequences belonging to a given family. The proposed model fuzzifies the forward and backward variables by incorporating Sugeno fuzzy measures and Choquet integrals, thus further extends the generalized HMM. Based on the fuzzified forward and backward variables, we propose a fuzzy Baum-Welch parameter estimation algorithm for profiles. The strong correlations and the sequence preference involved in the protein structures make this fuzzy architecture based model as a suitable candidate for building profiles of a given family, since the fuzzy set can handle uncertainties better than classical methods.

A Geometrical Approach to Bell's Theorem

NASA Technical Reports Server (NTRS)

Rubincam, David Parry

2000-01-01

Bell's theorem can be proved through simple geometrical reasoning, without the need for the Psi function, probability distributions, or calculus. The proof is based on N. David Mermin's explication of the Einstein-Podolsky-Rosen-Bohm experiment, which involves Stern-Gerlach detectors which flash red or green lights when detecting spin-up or spin-down. The statistics of local hidden variable theories for this experiment can be arranged in colored strips from which simple inequalities can be deduced. These inequalities lead to a demonstration of Bell's theorem. Moreover, all local hidden variable theories can be graphed in such a way as to enclose their statistics in a pyramid, with the quantum-mechanical result lying a finite distance beneath the base of the pyramid.

Optimal design of solid oxide fuel cell, ammonia-water single effect absorption cycle and Rankine steam cycle hybrid system

NASA Astrophysics Data System (ADS)

Mehrpooya, Mehdi; Dehghani, Hossein; Ali Moosavian, S. M.

2016-02-01

A combined system containing solid oxide fuel cell-gas turbine power plant, Rankine steam cycle and ammonia-water absorption refrigeration system is introduced and analyzed. In this process, power, heat and cooling are produced. Energy and exergy analyses along with the economic factors are used to distinguish optimum operating point of the system. The developed electrochemical model of the fuel cell is validated with experimental results. Thermodynamic package and main parameters of the absorption refrigeration system are validated. The power output of the system is 500 kW. An optimization problem is defined in order to finding the optimal operating point. Decision variables are current density, temperature of the exhaust gases from the boiler, steam turbine pressure (high and medium), generator temperature and consumed cooling water. Results indicate that electrical efficiency of the combined system is 62.4% (LHV). Produced refrigeration (at -10 °C) and heat recovery are 101 kW and 22.1 kW respectively. Investment cost for the combined system (without absorption cycle) is about 2917 kW-1.

A Finite Element Analysis of a Class of Problems in Elasto-Plasticity with Hidden Variables.

DTIC Science & Technology

1985-09-01

RD-R761 642 A FINITE ELEMENT ANALYSIS OF A CLASS OF PROBLEMS IN 1/2 ELASTO-PLASTICITY MIlT (U) TEXAS INST FOR COMPUTATIONAL MECHANICS AUSTIN J T ODEN...end Subtitle) S. TYPE OF REPORT & PERIOD COVERED A FINITE ELEMENT ANALYSIS OF A CLASS OF PROBLEMS Final Report IN ELASTO-PLASTICITY WITH HIDDEN...aieeoc ede It neceeeary nd Identify by block number) ;"Elastoplasticity, finite deformations; non-convex analysis ; finite element methods, metal forming

Relations between Representational Consistency, Conceptual Understanding of the Force Concept, and Scientific Reasoning

ERIC Educational Resources Information Center

Nieminen, Pasi; Savinainen, Antti; Viiri, Jouni

2012-01-01

Previous physics education research has raised the question of "hidden variables" behind students' success in learning certain concepts. In the context of the force concept, it has been suggested that students' reasoning ability is one such variable. Strong positive correlations between students' preinstruction scores for reasoning…

Ramgen Power Systems-Supersonic Component Technology for Military Engine Applications

DTIC Science & Technology

2006-11-01

turbine efficiency power (kW) LHV efficiency HHV efficiency notes **Current Design Point 0.45 1700 1013 84.4% 220.1 35.4% 31.8% - Rampressor...tor (such as a standalone power-only mode device), or to a fuel cell in a hybrid configuration. This paper presents the development of the RPS gas...turbine technology and potential applications to the two specific engine cycle configurations, i.e., an indirect fuel cell / RPS turbine hybrid-cycle

Non-contrast-enhanced MR portography and hepatic venography with time-spatial labeling inversion pulses: comparison of imaging with the short tau inversion recovery method and the chemical shift selective method.

PubMed

Shimizu, Hironori; Isoda, Hiroyoshi; Ohno, Tsuyoshi; Yamashita, Rikiya; Kawahara, Seiya; Furuta, Akihiro; Fujimoto, Koji; Kido, Aki; Kusahara, Hiroshi; Togashi, Kaori

2015-01-01

To compare and evaluate images of non-contrast enhanced magnetic resonance (MR) portography and hepatic venography acquired with two different fat suppression methods, the chemical shift selective (CHESS) method and short tau inversion recovery (STIR) method. Twenty-two healthy volunteers were examined using respiratory-triggered three-dimensional true steady-state free-precession with two time-spatial labeling inversion pulses. The CHESS or STIR methods were used for fat suppression. The relative signal-to-noise ratio and contrast-to-noise ratio (CNR) were quantified, and the quality of visualization was scored. Image acquisition was successfully conducted in all volunteers. The STIR method significantly improved the CNRs of MR portography and hepatic venography. The image quality scores of main portal vein and right portal vein were higher with the STIR method, but there were no significant differences. The image quality scores of right hepatic vein, middle hepatic vein, and left hepatic vein (LHV) were all higher, and the visualization of LHV was significantly better (p<0.05). The STIR method contributes to further suppression of the background signal and improves visualization of the portal and hepatic veins. The results support using non-contrast-enhanced MR portography and hepatic venography in clinical practice. Copyright © 2014 Elsevier Inc. All rights reserved.

Refuse Derived Fuel (RDF) production and gasification in a pilot plant integrated with an Otto cycle ICE through Aspen plus™ modelling: Thermodynamic and economic viability.

PubMed

Násner, Albany Milena Lozano; Lora, Electo Eduardo Silva; Palacio, José Carlos Escobar; Rocha, Mateus Henrique; Restrepo, Julian Camilo; Venturini, Osvaldo José; Ratner, Albert

2017-11-01

This work deals with the development of a Refuse Derived Fuel (RDF) gasification pilot plant using air as a gasification agent. A downdraft fixed bed reactor is integrated with an Otto cycle Internal Combustion Engine (ICE). Modelling was carried out using the Aspen Plus™ software to predict the ideal operational conditions for maximum efficiency. Thermodynamics package used in the simulation comprised the Non-Random Two-Liquid (NRTL) model and the Hayden-O'Connell (HOC) equation of state. As expected, the results indicated that the Equivalence Ratio (ER) has a direct influence over the gasification temperature and the composition of the Raw Produced Gas (RPG), and effects of ER over the Lower Heating Value (LHV) and Cold Gasification Efficiency (CGE) of the RPG are also discussed. A maximum CGE efficiency of 57-60% was reached for ER values between 0.25 and 0.3, also an average reactor temperature values in the range of 680-700°C, with a peak LHV of 5.8MJ/Nm 3 . RPG was burned in an ICE, reaching an electrical power of 50kW el . The economic assessment of the pilot plant implementation was also performed, showing the project is feasible, with power above 120kW el with an initial investment of approximately US$ 300,000. Copyright © 2017 Elsevier Ltd. All rights reserved.

Development of a soldier-portable fuel cell power system. Part I: A bread-board methanol fuel processor

NASA Astrophysics Data System (ADS)

Palo, Daniel R.; Holladay, Jamie D.; Rozmiarek, Robert T.; Guzman-Leong, Consuelo E.; Wang, Yong; Hu, Jianli; Chin, Ya-Huei; Dagle, Robert A.; Baker, Eddie G.

A 15-W e portable power system is being developed for the US Army that consists of a hydrogen-generating fuel reformer coupled to a proton-exchange membrane fuel cell. In the first phase of this project, a methanol steam reformer system was developed and demonstrated. The reformer system included a combustor, two vaporizers, and a steam reforming reactor. The device was demonstrated as a thermally independent unit over the range of 14-80 W t output. Assuming a 14-day mission life and an ultimate 1-kg fuel processor/fuel cell assembly, a base case was chosen to illustrate the expected system performance. Operating at 13 W e, the system yielded a fuel processor efficiency of 45% (LHV of H 2 out/LHV of fuel in) and an estimated net efficiency of 22% (assuming a fuel cell efficiency of 48%). The resulting energy density of 720 Wh/kg is several times the energy density of the best lithium-ion batteries. Some immediate areas of improvement in thermal management also have been identified, and an integrated fuel processor is under development. The final system will be a hybrid, containing a fuel reformer, a fuel cell, and a rechargeable battery. The battery will provide power for start-up and added capacity for times of peak power demand.

Development of a Soldier-Portable Fuel Cell Power System, Part I: A Bread-Board Methanol Fuel Processor

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

Palo, Daniel R.; Holladay, Jamelyn D.; Rozmiarek, Robert T.

A 15-We portable power system is being developed for the US Army, comprised of a hydrogen-generating fuel reformer coupled to a hydrogen-converting fuel cell. As a first phase of this project, a methanol steam reformer system was developed and demonstrated. The reformer system included a combustor, two vaporizers, and a steam-reforming reactor. The device was demonstrated as a thermally independent unit over the range of 14 to 80 Wt output. Assuming a 14-day mission life and an ultimate 1-kg fuel processor/fuel cell assembly, a base case was chosen to illustrate the expected system performance. Operating at 13 We, the systemmore » yielded a fuel processor efficiency of 45% (LHV of H2 out/LHV of fuel in) and an estimated net efficiency of 22% (assuming a fuel cell efficiency of 48%). The resulting energy density of 720 W-hr/kg is several times the energy density of the best lithium-ion batteries. Some immediate areas of improvement in thermal management also have been identified and an integrated fuel processor is under development. The final system will be a hybrid, containing a fuel reformer, fuel cell, and rechargeable battery. The battery will provide power for startup and added capacity for times of peak power demand.« less

Sharp Contradiction for Local-Hidden-State Model in Quantum Steering

PubMed Central

Chen, Jing-Ling; Su, Hong-Yi; Xu, Zhen-Peng; Pati, Arun Kumar

2016-01-01

In quantum theory, no-go theorems are important as they rule out the existence of a particular physical model under consideration. For instance, the Greenberger-Horne-Zeilinger (GHZ) theorem serves as a no-go theorem for the nonexistence of local hidden variable models by presenting a full contradiction for the multipartite GHZ states. However, the elegant GHZ argument for Bell’s nonlocality does not go through for bipartite Einstein-Podolsky-Rosen (EPR) state. Recent study on quantum nonlocality has shown that the more precise description of EPR’s original scenario is “steering”, i.e., the nonexistence of local hidden state models. Here, we present a simple GHZ-like contradiction for any bipartite pure entangled state, thus proving a no-go theorem for the nonexistence of local hidden state models in the EPR paradox. This also indicates that the very simple steering paradox presented here is indeed the closest form to the original spirit of the EPR paradox. PMID:27562658

Sharp Contradiction for Local-Hidden-State Model in Quantum Steering

NASA Astrophysics Data System (ADS)

Chen, Jing-Ling; Su, Hong-Yi; Xu, Zhen-Peng; Pati, Arun Kumar

2016-08-01

In quantum theory, no-go theorems are important as they rule out the existence of a particular physical model under consideration. For instance, the Greenberger-Horne-Zeilinger (GHZ) theorem serves as a no-go theorem for the nonexistence of local hidden variable models by presenting a full contradiction for the multipartite GHZ states. However, the elegant GHZ argument for Bell’s nonlocality does not go through for bipartite Einstein-Podolsky-Rosen (EPR) state. Recent study on quantum nonlocality has shown that the more precise description of EPR’s original scenario is “steering”, i.e., the nonexistence of local hidden state models. Here, we present a simple GHZ-like contradiction for any bipartite pure entangled state, thus proving a no-go theorem for the nonexistence of local hidden state models in the EPR paradox. This also indicates that the very simple steering paradox presented here is indeed the closest form to the original spirit of the EPR paradox.

Construction of state-independent proofs for quantum contextuality

NASA Astrophysics Data System (ADS)

Tang, Weidong; Yu, Sixia

2017-12-01

Since the enlightening proofs of quantum contextuality first established by Kochen and Specker, and also by Bell, various simplified proofs have been constructed to exclude the noncontextual hidden variable theory of our nature at the microscopic scale. The conflict between the noncontextual hidden variable theory and quantum mechanics is commonly revealed by Kochen-Specker sets of yes-no tests, represented by projectors (or rays), via either logical contradictions or noncontextuality inequalities in a state-(in)dependent manner. Here we propose a systematic and programmable construction of a state-independent proof from a given set of nonspecific rays in C3 according to their Gram matrix. This approach brings us a greater convenience in the experimental arrangements. Besides, our proofs in C3 can also be generalized to any higher-dimensional systems by a recursive method.

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.

Experimental demonstration of nonbilocal quantum correlations.

PubMed

Saunders, Dylan J; Bennet, Adam J; Branciard, Cyril; Pryde, Geoff J

2017-04-01

Quantum mechanics admits correlations that cannot be explained by local realistic models. The most studied models are the standard local hidden variable models, which satisfy the well-known Bell inequalities. To date, most works have focused on bipartite entangled systems. We consider correlations between three parties connected via two independent entangled states. We investigate the new type of so-called "bilocal" models, which correspondingly involve two independent hidden variables. These models describe scenarios that naturally arise in quantum networks, where several independent entanglement sources are used. Using photonic qubits, we build such a linear three-node quantum network and demonstrate nonbilocal correlations by violating a Bell-like inequality tailored for bilocal models. Furthermore, we show that the demonstration of nonbilocality is more noise-tolerant than that of standard Bell nonlocality in our three-party quantum network.

Characterization of High Damping Fe-Cr-Mo and Fe-Cr-Al Alloys for Naval Ships Application.

DTIC Science & Technology

1988-03-01

austenitic , and martensitic. The high damping Fe-Cr-based alloys are closely related to ferritic stainless steels . Ferritic stainless steel consists of an Fe...cm reveme it Prectiaq #no ’uenf r oy o.o(a tflrowf U S9GO..P Damping; Ship Silencing; Ferritic Stainless Steels ; Ti-Ni 7 LhV I,. Cintunue on roere .r...decreased. E. METALLURGY OF THE IRON-CHROMIUM ALLOY SYSTEM 1. Physical Properties Stainless steels are divided into three main classes: ferritic

EMG-based speech recognition using hidden markov models with global control variables.

PubMed

Lee, Ki-Seung

2008-03-01

It is well known that a strong relationship exists between human voices and the movement of articulatory facial muscles. In this paper, we utilize this knowledge to implement an automatic speech recognition scheme which uses solely surface electromyogram (EMG) signals. The sequence of EMG signals for each word is modelled by a hidden Markov model (HMM) framework. The main objective of the work involves building a model for state observation density when multichannel observation sequences are given. The proposed model reflects the dependencies between each of the EMG signals, which are described by introducing a global control variable. We also develop an efficient model training method, based on a maximum likelihood criterion. In a preliminary study, 60 isolated words were used as recognition variables. EMG signals were acquired from three articulatory facial muscles. The findings indicate that such a system may have the capacity to recognize speech signals with an accuracy of up to 87.07%, which is superior to the independent probabilistic model.

Multivariate generalized hidden Markov regression models with random covariates: Physical exercise in an elderly population.

PubMed

Punzo, Antonio; Ingrassia, Salvatore; Maruotti, Antonello

2018-04-22

A time-varying latent variable model is proposed to jointly analyze multivariate mixed-support longitudinal data. The proposal can be viewed as an extension of hidden Markov regression models with fixed covariates (HMRMFCs), which is the state of the art for modelling longitudinal data, with a special focus on the underlying clustering structure. HMRMFCs are inadequate for applications in which a clustering structure can be identified in the distribution of the covariates, as the clustering is independent from the covariates distribution. Here, hidden Markov regression models with random covariates are introduced by explicitly specifying state-specific distributions for the covariates, with the aim of improving the recovering of the clusters in the data with respect to a fixed covariates paradigm. The hidden Markov regression models with random covariates class is defined focusing on the exponential family, in a generalized linear model framework. Model identifiability conditions are sketched, an expectation-maximization algorithm is outlined for parameter estimation, and various implementation and operational issues are discussed. Properties of the estimators of the regression coefficients, as well as of the hidden path parameters, are evaluated through simulation experiments and compared with those of HMRMFCs. The method is applied to physical activity data. Copyright © 2018 John Wiley & Sons, Ltd.

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.

Hidden negative linear compressibility in lithium l-tartrate.

PubMed

Yeung, Hamish H-M; Kilmurray, Rebecca; Hobday, Claire L; McKellar, Scott C; Cheetham, Anthony K; Allan, David R; Moggach, Stephen A

2017-02-01

By decoupling the mechanical behaviour of building units for the first time in a wine-rack framework containing two different strut types, we show that lithium l-tartrate exhibits NLC with a maximum value, K max = -21 TPa -1 , and an overall NLC capacity, χ NLC = 5.1%, that are comparable to the most exceptional materials to date. Furthermore, the contributions from molecular strut compression and angle opening interplay to give rise to so-called "hidden" negative linear compressibility, in which NLC is absent at ambient pressure, switched on at 2 GPa and sustained up to the limit of our experiment, 5.5 GPa. Analysis of the changes in crystal structure using variable-pressure synchrotron X-ray diffraction reveals new chemical and geometrical design rules to assist the discovery of other materials with exciting hidden anomalous mechanical properties.

Final Technical Report for Collaborative Research: Regional climate-change projections through next-generation empirical and dynamical models, DE-FG02-07ER64429

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

Smyth, Padhraic

2013-07-22

This is the final report for a DOE-funded research project describing the outcome of research on non-homogeneous hidden Markov models (NHMMs) and coupled ocean-atmosphere (O-A) intermediate-complexity models (ICMs) to identify the potentially predictable modes of climate variability, and to investigate their impacts on the regional-scale. The main results consist of extensive development of the hidden Markov models for rainfall simulation and downscaling specifically within the non-stationary climate change context together with the development of parallelized software; application of NHMMs to downscaling of rainfall projections over India; identification and analysis of decadal climate signals in data and models; and, studies ofmore » climate variability in terms of the dynamics of atmospheric flow regimes.« less

Kochen-Specker theorem studied with neutron interferometer.

PubMed

Hasegawa, Yuji; Durstberger-Rennhofer, Katharina; Sponar, Stephan; Rauch, Helmut

2011-04-01

The Kochen-Specker theorem shows the incompatibility of noncontextual hidden variable theories with quantum mechanics. Quantum contextuality is a more general concept than quantum non-locality which is quite well tested in experiments using Bell inequalities. Within neutron interferometry we performed an experimental test of the Kochen-Specker theorem with an inequality, which identifies quantum contextuality, by using spin-path entanglement of single neutrons. Here entanglement is achieved not between different particles, but between degrees of freedom of a single neutron, i.e., between spin and path degree of freedom. Appropriate combinations of the spin analysis and the position of the phase shifter allow an experimental verification of the violation of an inequality derived from the Kochen-Specker theorem. The observed violation 2.291±0.008≰1 clearly shows that quantum mechanical predictions cannot be reproduced by noncontextual hidden variable theories.

General Method for Constructing Local Hidden Variable Models for Entangled Quantum States

NASA Astrophysics Data System (ADS)

Cavalcanti, D.; Guerini, L.; Rabelo, R.; Skrzypczyk, P.

2016-11-01

Entanglement allows for the nonlocality of quantum theory, which is the resource behind device-independent quantum information protocols. However, not all entangled quantum states display nonlocality. A central question is to determine the precise relation between entanglement and nonlocality. Here we present the first general test to decide whether a quantum state is local, and show that the test can be implemented by semidefinite programing. This method can be applied to any given state and for the construction of new examples of states with local hidden variable models for both projective and general measurements. As applications, we provide a lower-bound estimate of the fraction of two-qubit local entangled states and present new explicit examples of such states, including those that arise from physical noise models, Bell-diagonal states, and noisy Greenberger-Horne-Zeilinger and W states.

Experimental demonstration of nonbilocal quantum correlations

PubMed Central

Saunders, Dylan J.; Bennet, Adam J.; Branciard, Cyril; Pryde, Geoff J.

2017-01-01

Quantum mechanics admits correlations that cannot be explained by local realistic models. The most studied models are the standard local hidden variable models, which satisfy the well-known Bell inequalities. To date, most works have focused on bipartite entangled systems. We consider correlations between three parties connected via two independent entangled states. We investigate the new type of so-called “bilocal” models, which correspondingly involve two independent hidden variables. These models describe scenarios that naturally arise in quantum networks, where several independent entanglement sources are used. Using photonic qubits, we build such a linear three-node quantum network and demonstrate nonbilocal correlations by violating a Bell-like inequality tailored for bilocal models. Furthermore, we show that the demonstration of nonbilocality is more noise-tolerant than that of standard Bell nonlocality in our three-party quantum network. PMID:28508045

Studies of regional-scale climate variability and change. Hidden Markov models and coupled ocean-atmosphere modes

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

Ghil, M.; Kravtsov, S.; Robertson, A. W.

2008-10-14

This project was a continuation of previous work under DOE CCPP funding, in which we had developed a twin approach of probabilistic network (PN) models (sometimes called dynamic Bayesian networks) and intermediate-complexity coupled ocean-atmosphere models (ICMs) to identify the predictable modes of climate variability and to investigate their impacts on the regional scale. We had developed a family of PNs (similar to Hidden Markov Models) to simulate historical records of daily rainfall, and used them to downscale GCM seasonal predictions. Using an idealized atmospheric model, we had established a novel mechanism through which ocean-induced sea-surface temperature (SST) anomalies might influencemore » large-scale atmospheric circulation patterns on interannual and longer time scales; we had found similar patterns in a hybrid coupled ocean-atmosphere-sea-ice model. The goal of the this continuation project was to build on these ICM results and PN model development to address prediction of rainfall and temperature statistics at the local scale, associated with global climate variability and change, and to investigate the impact of the latter on coupled ocean-atmosphere modes. Our main results from the grant consist of extensive further development of the hidden Markov models for rainfall simulation and downscaling together with the development of associated software; new intermediate coupled models; a new methodology of inverse modeling for linking ICMs with observations and GCM results; and, observational studies of decadal and multi-decadal natural climate results, informed by ICM results.« less

Hydro, wind and solar power as a base for a 100% renewable energy supply for South and Central America.

PubMed

Barbosa, Larissa de Souza Noel Simas; Bogdanov, Dmitrii; Vainikka, Pasi; Breyer, Christian

2017-01-01

Power systems for South and Central America based on 100% renewable energy (RE) in the year 2030 were calculated for the first time using an hourly resolved energy model. The region was subdivided into 15 sub-regions. Four different scenarios were considered: three according to different high voltage direct current (HVDC) transmission grid development levels (region, country, area-wide) and one integrated scenario that considers water desalination and industrial gas demand supplied by synthetic natural gas via power-to-gas (PtG). RE is not only able to cover 1813 TWh of estimated electricity demand of the area in 2030 but also able to generate the electricity needed to fulfil 3.9 billion m3 of water desalination and 640 TWhLHV of synthetic natural gas demand. Existing hydro dams can be used as virtual batteries for solar and wind electricity storage, diminishing the role of storage technologies. The results for total levelized cost of electricity (LCOE) are decreased from 62 €/MWh for a highly decentralized to 56 €/MWh for a highly centralized grid scenario (currency value of the year 2015). For the integrated scenario, the levelized cost of gas (LCOG) and the levelized cost of water (LCOW) are 95 €/MWhLHV and 0.91 €/m3, respectively. A reduction of 8% in total cost and 5% in electricity generation was achieved when integrating desalination and power-to-gas into the system.

Hydro, wind and solar power as a base for a 100% renewable energy supply for South and Central America

PubMed Central

Barbosa, Larissa de Souza Noel Simas; Bogdanov, Dmitrii; Vainikka, Pasi; Breyer, Christian

2017-01-01

Power systems for South and Central America based on 100% renewable energy (RE) in the year 2030 were calculated for the first time using an hourly resolved energy model. The region was subdivided into 15 sub-regions. Four different scenarios were considered: three according to different high voltage direct current (HVDC) transmission grid development levels (region, country, area-wide) and one integrated scenario that considers water desalination and industrial gas demand supplied by synthetic natural gas via power-to-gas (PtG). RE is not only able to cover 1813 TWh of estimated electricity demand of the area in 2030 but also able to generate the electricity needed to fulfil 3.9 billion m3 of water desalination and 640 TWhLHV of synthetic natural gas demand. Existing hydro dams can be used as virtual batteries for solar and wind electricity storage, diminishing the role of storage technologies. The results for total levelized cost of electricity (LCOE) are decreased from 62 €/MWh for a highly decentralized to 56 €/MWh for a highly centralized grid scenario (currency value of the year 2015). For the integrated scenario, the levelized cost of gas (LCOG) and the levelized cost of water (LCOW) are 95 €/MWhLHV and 0.91 €/m3, respectively. A reduction of 8% in total cost and 5% in electricity generation was achieved when integrating desalination and power-to-gas into the system. PMID:28329023

Violation of Bell's Inequality Using Continuous Variable Measurements

NASA Astrophysics Data System (ADS)

Thearle, Oliver; Janousek, Jiri; Armstrong, Seiji; Hosseini, Sara; Schünemann Mraz, Melanie; Assad, Syed; Symul, Thomas; James, Matthew R.; Huntington, Elanor; Ralph, Timothy C.; Lam, Ping Koy

2018-01-01

A Bell inequality is a fundamental test to rule out local hidden variable model descriptions of correlations between two physically separated systems. There have been a number of experiments in which a Bell inequality has been violated using discrete-variable systems. We demonstrate a violation of Bell's inequality using continuous variable quadrature measurements. By creating a four-mode entangled state with homodyne detection, we recorded a clear violation with a Bell value of B =2.31 ±0.02 . This opens new possibilities for using continuous variable states for device independent quantum protocols.

Daily Rainfall Simulation Using Climate Variables and Nonhomogeneous Hidden Markov Model

NASA Astrophysics Data System (ADS)

Jung, J.; Kim, H. S.; Joo, H. J.; Han, D.

2017-12-01

Markov chain is an easy method to handle when we compare it with other ones for the rainfall simulation. However, it also has limitations in reflecting seasonal variability of rainfall or change on rainfall patterns caused by climate change. This study applied a Nonhomogeneous Hidden Markov Model(NHMM) to consider these problems. The NHMM compared with a Hidden Markov Model(HMM) for the evaluation of a goodness of the model. First, we chose Gum river basin in Korea to apply the models and collected daily rainfall data from the stations. Also, the climate variables of geopotential height, temperature, zonal wind, and meridional wind date were collected from NCEP/NCAR reanalysis data to consider external factors affecting the rainfall event. We conducted a correlation analysis between rainfall and climate variables then developed a linear regression equation using the climate variables which have high correlation with rainfall. The monthly rainfall was obtained by the regression equation and it became input data of NHMM. Finally, the daily rainfall by NHMM was simulated and we evaluated the goodness of fit and prediction capability of NHMM by comparing with those of HMM. As a result of simulation by HMM, the correlation coefficient and root mean square error of daily/monthly rainfall were 0.2076 and 10.8243/131.1304mm each. In case of NHMM, the correlation coefficient and root mean square error of daily/monthly rainfall were 0.6652 and 10.5112/100.9865mm each. We could verify that the error of daily and monthly rainfall simulated by NHMM was improved by 2.89% and 22.99% compared with HMM. Therefore, it is expected that the results of the study could provide more accurate data for hydrologic analysis. Acknowledgements This research was supported by Basic Science Research Program through the National Research Foundation of Korea(NRF) funded by the Ministry of Science, ICT & Future Planning(2017R1A2B3005695)

Dynamic Latent Trait Models with Mixed Hidden Markov Structure for Mixed Longitudinal Outcomes.

PubMed

Zhang, Yue; Berhane, Kiros

2016-01-01

We propose a general Bayesian joint modeling approach to model mixed longitudinal outcomes from the exponential family for taking into account any differential misclassification that may exist among categorical outcomes. Under this framework, outcomes observed without measurement error are related to latent trait variables through generalized linear mixed effect models. The misclassified outcomes are related to the latent class variables, which represent unobserved real states, using mixed hidden Markov models (MHMM). In addition to enabling the estimation of parameters in prevalence, transition and misclassification probabilities, MHMMs capture cluster level heterogeneity. A transition modeling structure allows the latent trait and latent class variables to depend on observed predictors at the same time period and also on latent trait and latent class variables at previous time periods for each individual. Simulation studies are conducted to make comparisons with traditional models in order to illustrate the gains from the proposed approach. The new approach is applied to data from the Southern California Children Health Study (CHS) to jointly model questionnaire based asthma state and multiple lung function measurements in order to gain better insight about the underlying biological mechanism that governs the inter-relationship between asthma state and lung function development.

Several foundational and information theoretic implications of Bell’s theorem

NASA Astrophysics Data System (ADS)

Kar, Guruprasad; Banik, Manik

2016-08-01

In 1935, Albert Einstein and two colleagues, Boris Podolsky and Nathan Rosen (EPR) developed a thought experiment to demonstrate what they felt was a lack of completeness in quantum mechanics (QM). EPR also postulated the existence of more fundamental theory where physical reality of any system would be completely described by the variables/states of that fundamental theory. This variable is commonly called hidden variable and the theory is called hidden variable theory (HVT). In 1964, John Bell proposed an empirically verifiable criterion to test for the existence of these HVTs. He derived an inequality, which must be satisfied by any theory that fulfill the conditions of locality and reality. He also showed that QM, as it violates this inequality, is incompatible with any local-realistic theory. Later it has been shown that Bell’s inequality (BI) can be derived from different set of assumptions and it also find applications in useful information theoretic protocols. In this review, we will discuss various foundational as well as information theoretic implications of BI. We will also discuss about some restricted nonlocal feature of quantum nonlocality and elaborate the role of Uncertainty principle and Complementarity principle in explaining this feature.

EPR Steering inequalities with Communication Assistance

PubMed Central

Nagy, Sándor; Vértesi, Tamás

2016-01-01

In this paper, we investigate the communication cost of reproducing Einstein-Podolsky-Rosen (EPR) steering correlations arising from bipartite quantum systems. We characterize the set of bipartite quantum states which admits a local hidden state model augmented with c bits of classical communication from an untrusted party (Alice) to a trusted party (Bob). In case of one bit of information (c = 1), we show that this set has a nontrivial intersection with the sets admitting a local hidden state and a local hidden variables model for projective measurements. On the other hand, we find that an infinite amount of classical communication is required from an untrusted Alice to a trusted Bob to simulate the EPR steering correlations produced by a two-qubit maximally entangled state. It is conjectured that a state-of-the-art quantum experiment would be able to falsify two bits of communication this way. PMID:26880376

Epistemic View of Quantum States and Communication Complexity of Quantum Channels

NASA Astrophysics Data System (ADS)

Montina, Alberto

2012-09-01

The communication complexity of a quantum channel is the minimal amount of classical communication required for classically simulating a process of state preparation, transmission through the channel and subsequent measurement. It establishes a limit on the power of quantum communication in terms of classical resources. We show that classical simulations employing a finite amount of communication can be derived from a special class of hidden variable theories where quantum states represent statistical knowledge about the classical state and not an element of reality. This special class has attracted strong interest very recently. The communication cost of each derived simulation is given by the mutual information between the quantum state and the classical state of the parent hidden variable theory. Finally, we find that the communication complexity for single qubits is smaller than 1.28 bits. The previous known upper bound was 1.85 bits.

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.

The missing history of Bohm's hidden variables theory: The Ninth Symposium of the Colston Research Society, Bristol, 1957

NASA Astrophysics Data System (ADS)

Kožnjak, Boris

2018-05-01

In this paper, I analyze the historical context, scientific and philosophical content, and the implications of the thus far historically largely neglected Ninth Symposium of the Colston Research Society held in Bristol at the beginning of April 1957, the first major international event after World War II gathering eminent physicists and philosophers to discuss the foundational questions of quantum mechanics, in respect to the early reception of the causal quantum theory program mapped and defended by David Bohm during the five years preceding the Symposium. As will be demonstrated, contrary to the almost unanimously negative and even hostile reception of Bohm's ideas on hidden variables in the early 1950s, in the close aftermath of the 1957 Colston Research Symposium Bohm's ideas received a more open-minded and ideologically relaxed critical rehabilitation, in which the Symposium itself played a vital and essential part.

Comparison of neurofuzzy logic and decision trees in discovering knowledge from experimental data of an immediate release tablet formulation.

PubMed

Shao, Q; Rowe, R C; York, P

2007-06-01

Understanding of the cause-effect relationships between formulation ingredients, process conditions and product properties is essential for developing a quality product. However, the formulation knowledge is often hidden in experimental data and not easily interpretable. This study compares neurofuzzy logic and decision tree approaches in discovering hidden knowledge from an immediate release tablet formulation database relating formulation ingredients (silica aerogel, magnesium stearate, microcrystalline cellulose and sodium carboxymethylcellulose) and process variables (dwell time and compression force) to tablet properties (tensile strength, disintegration time, friability, capping and drug dissolution at various time intervals). Both approaches successfully generated useful knowledge in the form of either "if then" rules or decision trees. Although different strategies are employed by the two approaches in generating rules/trees, similar knowledge was discovered in most cases. However, as decision trees are not able to deal with continuous dependent variables, data discretisation procedures are generally required.

Computational analysis of cell-to-cell heterogeneity in single-cell RNA-sequencing data reveals hidden subpopulations of cells.

PubMed

Buettner, Florian; Natarajan, Kedar N; Casale, F Paolo; Proserpio, Valentina; Scialdone, Antonio; Theis, Fabian J; Teichmann, Sarah A; Marioni, John C; Stegle, Oliver

2015-02-01

Recent technical developments have enabled the transcriptomes of hundreds of cells to be assayed in an unbiased manner, opening up the possibility that new subpopulations of cells can be found. However, the effects of potential confounding factors, such as the cell cycle, on the heterogeneity of gene expression and therefore on the ability to robustly identify subpopulations remain unclear. We present and validate a computational approach that uses latent variable models to account for such hidden factors. We show that our single-cell latent variable model (scLVM) allows the identification of otherwise undetectable subpopulations of cells that correspond to different stages during the differentiation of naive T cells into T helper 2 cells. Our approach can be used not only to identify cellular subpopulations but also to tease apart different sources of gene expression heterogeneity in single-cell transcriptomes.

Is wave-particle objectivity compatible with determinism and locality?

PubMed

Ionicioiu, Radu; Jennewein, Thomas; Mann, Robert B; Terno, Daniel R

2014-09-26

Wave-particle duality, superposition and entanglement are among the most counterintuitive features of quantum theory. Their clash with our classical expectations motivated hidden-variable (HV) theories. With the emergence of quantum technologies, we can test experimentally the predictions of quantum theory versus HV theories and put strong restrictions on their key assumptions. Here, we study an entanglement-assisted version of the quantum delayed-choice experiment and show that the extension of HV to the controlling devices only exacerbates the contradiction. We compare HV theories that satisfy the conditions of objectivity (a property of photons being either particles or waves, but not both), determinism and local independence of hidden variables with quantum mechanics. Any two of the above conditions are compatible with it. The conflict becomes manifest when all three conditions are imposed and persists for any non-zero value of entanglement. We propose an experiment to test our conclusions.

Is wave–particle objectivity compatible with determinism and locality?

PubMed Central

Ionicioiu, Radu; Jennewein, Thomas; Mann, Robert B.; Terno, Daniel R.

2014-01-01

Wave–particle duality, superposition and entanglement are among the most counterintuitive features of quantum theory. Their clash with our classical expectations motivated hidden-variable (HV) theories. With the emergence of quantum technologies, we can test experimentally the predictions of quantum theory versus HV theories and put strong restrictions on their key assumptions. Here, we study an entanglement-assisted version of the quantum delayed-choice experiment and show that the extension of HV to the controlling devices only exacerbates the contradiction. We compare HV theories that satisfy the conditions of objectivity (a property of photons being either particles or waves, but not both), determinism and local independence of hidden variables with quantum mechanics. Any two of the above conditions are compatible with it. The conflict becomes manifest when all three conditions are imposed and persists for any non-zero value of entanglement. We propose an experiment to test our conclusions. PMID:25256419

Estimating Density and Temperature Dependence of Juvenile Vital Rates Using a Hidden Markov Model

PubMed Central

McElderry, Robert M.

2017-01-01

Organisms in the wild have cryptic life stages that are sensitive to changing environmental conditions and can be difficult to survey. In this study, I used mark-recapture methods to repeatedly survey Anaea aidea (Nymphalidae) caterpillars in nature, then modeled caterpillar demography as a hidden Markov process to assess if temporal variability in temperature and density influence the survival and growth of A. aidea over time. Individual encounter histories result from the joint likelihood of being alive and observed in a particular stage, and I have included hidden states by separating demography and observations into parallel and independent processes. I constructed a demographic matrix containing the probabilities of all possible fates for each stage, including hidden states, e.g., eggs and pupae. I observed both dead and live caterpillars with high probability. Peak caterpillar abundance attracted multiple predators, and survival of fifth instars declined as per capita predation rate increased through spring. A time lag between predator and prey abundance was likely the cause of improved fifth instar survival estimated at high density. Growth rates showed an increase with temperature, but the preferred model did not include temperature. This work illustrates how state-space models can include unobservable stages and hidden state processes to evaluate how environmental factors influence vital rates of cryptic life stages in the wild. PMID:28505138

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.

Use of Machine Learning Techniques for Identification of Robust Teleconnections to East African Rainfall Variability

NASA Technical Reports Server (NTRS)

Roberts, J. Brent; Robertson, F. R.; Funk, C.

2014-01-01

Hidden Markov models can be used to investigate structure of subseasonal variability. East African short rain variability has connections to large-scale tropical variability. MJO - Intraseasonal variations connected with appearance of "wet" and "dry" states. ENSO/IOZM SST and circulation anomalies are apparent during years of anomalous residence time in the subseasonal "wet" state. Similar results found in previous studies, but we can interpret this with respect to variations of subseasonal wet and dry modes. Reveal underlying connections between MJO/IOZM/ENSO with respect to East African rainfall.

Assessing the effect of quantitative and qualitative predictors on gastric cancer individuals survival using hierarchical artificial neural network models.

PubMed

Amiri, Zohreh; Mohammad, Kazem; Mahmoudi, Mahmood; Parsaeian, Mahbubeh; Zeraati, Hojjat

2013-01-01

There are numerous unanswered questions in the application of artificial neural network models for analysis of survival data. In most studies, independent variables have been studied as qualitative dichotomous variables, and results of using discrete and continuous quantitative, ordinal, or multinomial categorical predictive variables in these models are not well understood in comparison to conventional models. This study was designed and conducted to examine the application of these models in order to determine the survival of gastric cancer patients, in comparison to the Cox proportional hazards model. We studied the postoperative survival of 330 gastric cancer patients who suffered surgery at a surgical unit of the Iran Cancer Institute over a five-year period. Covariates of age, gender, history of substance abuse, cancer site, type of pathology, presence of metastasis, stage, and number of complementary treatments were entered in the models, and survival probabilities were calculated at 6, 12, 18, 24, 36, 48, and 60 months using the Cox proportional hazards and neural network models. We estimated coefficients of the Cox model and the weights in the neural network (with 3, 5, and 7 nodes in the hidden layer) in the training group, and used them to derive predictions in the study group. Predictions with these two methods were compared with those of the Kaplan-Meier product limit estimator as the gold standard. Comparisons were performed with the Friedman and Kruskal-Wallis tests. Survival probabilities at different times were determined using the Cox proportional hazards and a neural network with three nodes in the hidden layer; the ratios of standard errors with these two methods to the Kaplan-Meier method were 1.1593 and 1.0071, respectively, revealed a significant difference between Cox and Kaplan-Meier (P < 0.05) and no significant difference between Cox and the neural network, and the neural network and the standard (Kaplan-Meier), as well as better accuracy for the neural network (with 3 nodes in the hidden layer). Probabilities of survival were calculated using three neural network models with 3, 5, and 7 nodes in the hidden layer, and it has been observed that none of the predictions was significantly different from results with the Kaplan-Meier method and they appeared more comparable towards the last months (fifth year). However, we observed better accuracy using the neural network with 5 nodes in the hidden layer. Using the Cox proportional hazards and a neural network with 3 nodes in the hidden layer, we found enhanced accuracy with the neural network model. Neural networks can provide more accurate predictions for survival probabilities compared to the Cox proportional hazards mode, especially now that advances in computer sciences have eliminated limitations associated with complex computations. It is not recommended in order to adding too many hidden layer nodes because sample size related effects can reduce the accuracy. We recommend increasing the number of nodes to a point that increased accuracy continues (decrease in mean standard error), however increasing nodes should cease when a change in this trend is observed.

Optimizing Experimental Designs: Finding Hidden Treasure.

USDA-ARS?s Scientific Manuscript database

Classical experimental design theory, the predominant treatment in most textbooks, promotes the use of blocking designs for control of spatial variability in field studies and other situations in which there is significant variation among heterogeneity among experimental units. Many blocking design...

Bio-drying and size sorting of municipal solid waste with high water content for improving energy recovery.

PubMed

Shao, Li-Ming; Ma, Zhong-He; Zhang, Hua; Zhang, Dong-Qing; He, Pin-Jing

2010-07-01

Bio-drying can enhance the sortability and heating value of municipal solid waste (MSW), consequently improving energy recovery. Bio-drying followed by size sorting was adopted for MSW with high water content to improve its combustibility and reduce potential environmental pollution during the follow-up incineration. The effects of bio-drying and waste particle size on heating values, acid gas and heavy metal emission potential were investigated. The results show that, the water content of MSW decreased from 73.0% to 48.3% after bio-drying, whereas its lower heating value (LHV) increased by 157%. The heavy metal concentrations increased by around 60% due to the loss of dry materials mainly resulting from biodegradation of food residues. The bio-dried waste fractions with particle size higher than 45 mm were mainly composed of plastics and papers, and were preferable for the production of refuse derived fuel (RDF) in view of higher LHV as well as lower heavy metal concentration and emission. However, due to the higher chlorine content and HCl emission potential, attention should be paid to acid gas and dioxin pollution control. Although LHVs of the waste fractions with size <45 mm increased by around 2x after bio-drying, they were still below the quality standards for RDF and much higher heavy metal pollution potential was observed. Different incineration strategies could be adopted for different particle size fractions of MSW, regarding to their combustibility and pollution property. Copyright (c) 2010 Elsevier Ltd. All rights reserved.

What is the Effect of Interannual Hydroclimatic Variability on Water Supply Reservoir Operations?

NASA Astrophysics Data System (ADS)

Galelli, S.; Turner, S. W. D.

2015-12-01

Rather than deriving from a single distribution and uniform persistence structure, hydroclimatic data exhibit significant trends and shifts in their mean, variance, and lagged correlation through time. Consequentially, observed and reconstructed streamflow records are often characterized by features of interannual variability, including long-term persistence and prolonged droughts. This study examines the effect of these features on the operating performance of water supply reservoirs. We develop a Stochastic Dynamic Programming (SDP) model that can incorporate a regime-shifting climate variable. We then compare the performance of operating policies—designed with and without climate variable—to quantify the contribution of interannual variability to standard policy sub-optimality. The approach uses a discrete-time Markov chain to partition the reservoir inflow time series into small number of 'hidden' climate states. Each state defines a distinct set of inflow transition probability matrices, which are used by the SDP model to condition the release decisions on the reservoir storage, current-period inflow and hidden climate state. The experimental analysis is carried out on 99 hypothetical water supply reservoirs fed from pristine catchments in Australia—all impacted by the Millennium drought. Results show that interannual hydroclimatic variability is a major cause of sub-optimal hedging decisions. The practical import is that conventional optimization methods may misguide operators, particularly in regions susceptible to multi-year droughts.

Fast and robust group-wise eQTL mapping using sparse graphical models.

PubMed

Cheng, Wei; Shi, Yu; Zhang, Xiang; Wang, Wei

2015-01-16

Genome-wide expression quantitative trait loci (eQTL) studies have emerged as a powerful tool to understand the genetic basis of gene expression and complex traits. The traditional eQTL methods focus on testing the associations between individual single-nucleotide polymorphisms (SNPs) and gene expression traits. A major drawback of this approach is that it cannot model the joint effect of a set of SNPs on a set of genes, which may correspond to hidden biological pathways. We introduce a new approach to identify novel group-wise associations between sets of SNPs and sets of genes. Such associations are captured by hidden variables connecting SNPs and genes. Our model is a linear-Gaussian model and uses two types of hidden variables. One captures the set associations between SNPs and genes, and the other captures confounders. We develop an efficient optimization procedure which makes this approach suitable for large scale studies. Extensive experimental evaluations on both simulated and real datasets demonstrate that the proposed methods can effectively capture both individual and group-wise signals that cannot be identified by the state-of-the-art eQTL mapping methods. Considering group-wise associations significantly improves the accuracy of eQTL mapping, and the successful multi-layer regression model opens a new approach to understand how multiple SNPs interact with each other to jointly affect the expression level of a group of genes.

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

A Hidden Markov Model for Analysis of Frontline Veterinary Data for Emerging Zoonotic Disease Surveillance

PubMed Central

Robertson, Colin; Sawford, Kate; Gunawardana, Walimunige S. N.; Nelson, Trisalyn A.; Nathoo, Farouk; Stephen, Craig

2011-01-01

Surveillance systems tracking health patterns in animals have potential for early warning of infectious disease in humans, yet there are many challenges that remain before this can be realized. Specifically, there remains the challenge of detecting early warning signals for diseases that are not known or are not part of routine surveillance for named diseases. This paper reports on the development of a hidden Markov model for analysis of frontline veterinary sentinel surveillance data from Sri Lanka. Field veterinarians collected data on syndromes and diagnoses using mobile phones. A model for submission patterns accounts for both sentinel-related and disease-related variability. Models for commonly reported cattle diagnoses were estimated separately. Region-specific weekly average prevalence was estimated for each diagnoses and partitioned into normal and abnormal periods. Visualization of state probabilities was used to indicate areas and times of unusual disease prevalence. The analysis suggests that hidden Markov modelling is a useful approach for surveillance datasets from novel populations and/or having little historical baselines. PMID:21949763

Test Report for NG Sensors GTX-1000

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

Manginell, Ronald P.

2014-12-01

This report describes initial testing of the NG Sensor GTX-1000 natural gas monitoring system. This testing showed that the retention time, peak area stability and heating value repeatability of the GTX-1000 were promising for natural gas measurements in the field or at the well head. The repeatability can be less than 0.25% for LHV and HHV for the Airgas standard tested in this report, which is very promising for a first generation prototype. Ultimately this system should be capable of 0.1% repeatability in heating value at significant size and power reductions compared with competing systems.

Single photon and nonlocality

NASA Astrophysics Data System (ADS)

Drezet, Aurelien

2007-03-01

In a paper by Home and Agarwal [1], it is claimed that quantum nonlocality can be revealed in a simple interferometry experiment using only single particles. A critical analysis of the concept of hidden variable used by the authors of [1] shows that the reasoning is not correct.

Violation of a Bell-like inequality in single-neutron interferometry.

PubMed

Hasegawa, Yuji; Loidl, Rudolf; Badurek, Gerald; Baron, Matthias; Rauch, Helmut

2003-09-04

Non-local correlations between spatially separated systems have been extensively discussed in the context of the Einstein, Podolsky and Rosen (EPR) paradox and Bell's inequalities. Many proposals and experiments designed to test hidden variable theories and the violation of Bell's inequalities have been reported; usually, these involve correlated photons, although recently an experiment was performed with (9)Be(+) ions. Nevertheless, it is of considerable interest to show that such correlations (arising from quantum mechanical entanglement) are not simply a peculiarity of photons. Here we measure correlations between two degrees of freedom (comprising spatial and spin components) of single neutrons; this removes the need for a source of entangled neutron pairs, which would present a considerable technical challenge. A Bell-like inequality is introduced to clarify the correlations that can arise between observables of otherwise independent degrees of freedom. We demonstrate the violation of this Bell-like inequality: our measured value is 2.051 +/- 0.019, clearly above the value of 2 predicted by classical hidden variable theories.

Modeling T-cell activation using gene expression profiling and state-space models.

PubMed

Rangel, Claudia; Angus, John; Ghahramani, Zoubin; Lioumi, Maria; Sotheran, Elizabeth; Gaiba, Alessia; Wild, David L; Falciani, Francesco

2004-06-12

We have used state-space models to reverse engineer transcriptional networks from highly replicated gene expression profiling time series data obtained from a well-established model of T-cell activation. State space models are a class of dynamic Bayesian networks that assume that the observed measurements depend on some hidden state variables that evolve according to Markovian dynamics. These hidden variables can capture effects that cannot be measured in a gene expression profiling experiment, e.g. genes that have not been included in the microarray, levels of regulatory proteins, the effects of messenger RNA and protein degradation, etc. Bootstrap confidence intervals are developed for parameters representing 'gene-gene' interactions over time. Our models represent the dynamics of T-cell activation and provide a methodology for the development of rational and experimentally testable hypotheses. Supplementary data and Matlab computer source code will be made available on the web at the URL given below. http://public.kgi.edu/~wild/LDS/index.htm

Best Hiding Capacity Scheme for Variable Length Messages Using Particle Swarm Optimization

NASA Astrophysics Data System (ADS)

Bajaj, Ruchika; Bedi, Punam; Pal, S. K.

Steganography is an art of hiding information in such a way that prevents the detection of hidden messages. Besides security of data, the quantity of data that can be hidden in a single cover medium, is also very important. We present a secure data hiding scheme with high embedding capacity for messages of variable length based on Particle Swarm Optimization. This technique gives the best pixel positions in the cover image, which can be used to hide the secret data. In the proposed scheme, k bits of the secret message are substituted into k least significant bits of the image pixel, where k varies from 1 to 4 depending on the message length. The proposed scheme is tested and results compared with simple LSB substitution, uniform 4-bit LSB hiding (with PSO) for the test images Nature, Baboon, Lena and Kitty. The experimental study confirms that the proposed method achieves high data hiding capacity and maintains imperceptibility and minimizes the distortion between the cover image and the obtained stego image.

The Misapplication of Probability Theory in Quantum Mechanics

NASA Astrophysics Data System (ADS)

Racicot, Ronald

2014-03-01

This article is a revision of two papers submitted to the APS in the past two and a half years. In these papers, arguments and proofs are summarized for the following: (1) The wrong conclusion by EPR that Quantum Mechanics is incomplete, perhaps requiring the addition of ``hidden variables'' for completion. Theorems that assume such ``hidden variables,'' such as Bell's theorem, are also wrong. (2) Quantum entanglement is not a realizable physical phenomenon and is based entirely on assuming a probability superposition model for quantum spin. Such a model directly violates conservation of angular momentum. (3) Simultaneous multiple-paths followed by a quantum particle traveling through space also cannot possibly exist. Besides violating Noether's theorem, the multiple-paths theory is based solely on probability calculations. Probability calculations by themselves cannot possibly represent simultaneous physically real events. None of the reviews of the submitted papers actually refuted the arguments and evidence that was presented. These analyses should therefore be carefully evaluated since the conclusions reached have such important impact in quantum mechanics and quantum information theory.

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

Temporal framing and the hidden-zero effect: rate-dependent outcomes on delay discounting.

PubMed

Naudé, Gideon P; Kaplan, Brent A; Reed, Derek D; Henley, Amy J; DiGennaro Reed, Florence D

2018-05-01

Recent research suggests that presenting time intervals as units (e.g., days) or as specific dates, can modulate the degree to which humans discount delayed outcomes. Another framing effect involves explicitly stating that choosing a smaller-sooner reward is mutually exclusive to receiving a larger-later reward, thus presenting choices as an extended sequence. In Experiment 1, participants (N = 201) recruited from Amazon Mechanical Turk completed the Monetary Choice Questionnaire in a 2 (delay framing) by 2 (zero framing) design. Regression suggested a main effect of delay, but not zero, framing after accounting for other demographic variables and manipulations. We observed a rate-dependent effect for the date-framing group, such that those with initially steep discounting exhibited greater sensitivity to the manipulation than those with initially shallow discounting. Subsequent analyses suggest these effects cannot be explained by regression to the mean. Experiment 2 addressed the possibility that the null effect of zero framing was due to within-subject exposure to the hidden- and explicit-zero conditions. A new Amazon Mechanical Turk sample completed the Monetary Choice Questionnaire in either hidden- or explicit-zero formats. Analyses revealed a main effect of reward magnitude, but not zero framing, suggesting potential limitations to the generality of the hidden-zero effect. © 2018 Society for the Experimental Analysis of Behavior.

Accurate permittivity measurements for microwave imaging via ultra-wideband removal of spurious reflectors.

PubMed

Pelletier, Mathew G; Viera, Joseph A; Wanjura, John; Holt, Greg

2010-01-01

The use of microwave imaging is becoming more prevalent for detection of interior hidden defects in manufactured and packaged materials. In applications for detection of hidden moisture, microwave tomography can be used to image the material and then perform an inverse calculation to derive an estimate of the variability of the hidden material, such internal moisture, thereby alerting personnel to damaging levels of the hidden moisture before material degradation occurs. One impediment to this type of imaging occurs with nearby objects create strong reflections that create destructive and constructive interference, at the receiver, as the material is conveyed past the imaging antenna array. In an effort to remove the influence of the reflectors, such as metal bale ties, research was conducted to develop an algorithm for removal of the influence of the local proximity reflectors from the microwave images. This research effort produced a technique, based upon the use of ultra-wideband signals, for the removal of spurious reflections created by local proximity reflectors. This improvement enables accurate microwave measurements of moisture in such products as cotton bales, as well as other physical properties such as density or material composition. The proposed algorithm was shown to reduce errors by a 4:1 ratio and is an enabling technology for imaging applications in the presence of metal bale ties.

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

Large size biogas-fed Solid Oxide Fuel Cell power plants with carbon dioxide management: Technical and economic optimization

NASA Astrophysics Data System (ADS)

Curletti, F.; Gandiglio, M.; Lanzini, A.; Santarelli, M.; Maréchal, F.

2015-10-01

This article investigates the techno-economic performance of large integrated biogas Solid Oxide Fuel Cell (SOFC) power plants. Both atmospheric and pressurized operation is analysed with CO2 vented or captured. The SOFC module produces a constant electrical power of 1 MWe. Sensitivity analysis and multi-objective optimization are the mathematical tools used to investigate the effects of Fuel Utilization (FU), SOFC operating temperature and pressure on the plant energy and economic performances. FU is the design variable that most affects the plant performance. Pressurized SOFC with hybridization with a gas turbine provides a notable boost in electrical efficiency. For most of the proposed plant configurations, the electrical efficiency ranges in the interval 50-62% (LHV biogas) when a trade-off of between energy and economic performances is applied based on Pareto charts obtained from multi-objective plant optimization. The hybrid SOFC is potentially able to reach an efficiency above 70% when FU is 90%. Carbon capture entails a penalty of more 10 percentage points in pressurized configurations mainly due to the extra energy burdens of captured CO2 pressurization and oxygen production and for the separate and different handling of the anode and cathode exhausts and power recovery from them.

A novel framework to simulating non-stationary, non-linear, non-Normal hydrological time series using Markov Switching Autoregressive Models

NASA Astrophysics Data System (ADS)

Birkel, C.; Paroli, R.; Spezia, L.; Tetzlaff, D.; Soulsby, C.

2012-12-01

In this paper we present a novel model framework using the class of Markov Switching Autoregressive Models (MSARMs) to examine catchments as complex stochastic systems that exhibit non-stationary, non-linear and non-Normal rainfall-runoff and solute dynamics. Hereby, MSARMs are pairs of stochastic processes, one observed and one unobserved, or hidden. We model the unobserved process as a finite state Markov chain and assume that the observed process, given the hidden Markov chain, is conditionally autoregressive, which means that the current observation depends on its recent past (system memory). The model is fully embedded in a Bayesian analysis based on Markov Chain Monte Carlo (MCMC) algorithms for model selection and uncertainty assessment. Hereby, the autoregressive order and the dimension of the hidden Markov chain state-space are essentially self-selected. The hidden states of the Markov chain represent unobserved levels of variability in the observed process that may result from complex interactions of hydroclimatic variability on the one hand and catchment characteristics affecting water and solute storage on the other. To deal with non-stationarity, additional meteorological and hydrological time series along with a periodic component can be included in the MSARMs as covariates. This extension allows identification of potential underlying drivers of temporal rainfall-runoff and solute dynamics. We applied the MSAR model framework to streamflow and conservative tracer (deuterium and oxygen-18) time series from an intensively monitored 2.3 km2 experimental catchment in eastern Scotland. Statistical time series analysis, in the form of MSARMs, suggested that the streamflow and isotope tracer time series are not controlled by simple linear rules. MSARMs showed that the dependence of current observations on past inputs observed by transport models often in form of the long-tailing of travel time and residence time distributions can be efficiently explained by non-stationarity either of the system input (climatic variability) and/or the complexity of catchment storage characteristics. The statistical model is also capable of reproducing short (event) and longer-term (inter-event) and wet and dry dynamical "hydrological states". These reflect the non-linear transport mechanisms of flow pathways induced by transient climatic and hydrological variables and modified by catchment characteristics. We conclude that MSARMs are a powerful tool to analyze the temporal dynamics of hydrological data, allowing for explicit integration of non-stationary, non-linear and non-Normal characteristics.

Optimization of artificial neural network models through genetic algorithms for surface ozone concentration forecasting.

PubMed

Pires, J C M; Gonçalves, B; Azevedo, F G; Carneiro, A P; Rego, N; Assembleia, A J B; Lima, J F B; Silva, P A; Alves, C; Martins, F G

2012-09-01

This study proposes three methodologies to define artificial neural network models through genetic algorithms (GAs) to predict the next-day hourly average surface ozone (O(3)) concentrations. GAs were applied to define the activation function in hidden layer and the number of hidden neurons. Two of the methodologies define threshold models, which assume that the behaviour of the dependent variable (O(3) concentrations) changes when it enters in a different regime (two and four regimes were considered in this study). The change from one regime to another depends on a specific value (threshold value) of an explanatory variable (threshold variable), which is also defined by GAs. The predictor variables were the hourly average concentrations of carbon monoxide (CO), nitrogen oxide, nitrogen dioxide (NO(2)), and O(3) (recorded in the previous day at an urban site with traffic influence) and also meteorological data (hourly averages of temperature, solar radiation, relative humidity and wind speed). The study was performed for the period from May to August 2004. Several models were achieved and only the best model of each methodology was analysed. In threshold models, the variables selected by GAs to define the O(3) regimes were temperature, CO and NO(2) concentrations, due to their importance in O(3) chemistry in an urban atmosphere. In the prediction of O(3) concentrations, the threshold model that considers two regimes was the one that fitted the data most efficiently.

Investigating Dueling Scenarios in NGC 7582 with Broadband X-ray Spectroscopy

NASA Astrophysics Data System (ADS)

Rivers, E.

2015-09-01

NGC 7582 is a well-studied X-ray bright Seyfert 2 with moderately heavy (NH = 10^{23} - 10^{24} cm^{-2}), highly variable absorption and unusually strong reflection spectral features. The spectral shape changed around the year 2000, dropping in observed flux and becoming much more highly absorbed. Two scenarios have been put forth to explain this spectral change: 1) the source "shut off" around this time, decreasing in intrinsic luminosity, with a delayed decrease in reflection features due to the light crossing time of the Compton-thick material or 2) the source is a "hidden nucleus" which has recently become more heavily obscured, with only a portion of the power law continuum leaking through. NuSTAR observed NGC 7582 twice in 2012 two weeks apart in order to quantify the reflection using high-quality data above 10 keV. We analyze both NuSTAR observations placing them in the context of historical X-ray, infrared and optical observations, including re-analysis of RXTE data from 2003-2005. We find that the most plausible scenario is that NGC 7582 has a hidden nucleus which has recently become more heavily absorbed by a patchy torus with a covering fraction of 80-90% and a column density of 3.6 x 10^{24} cm^{-2}. We find the need for an additional highly variable full-covering absorber with NH= 4-6 x 10^{23} cm^{-2}, possibly associated with a hidden broad line region or a dust lane in the host galaxy.

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

Khrennikov, Andrei

We present fundamentals of a prequantum model with hidden variables of the classical field type. In some sense this is the comeback of classical wave mechanics. Our approach also can be considered as incorporation of quantum mechanics into classical signal theory. All quantum averages (including correlations of entangled systems) can be represented as classical signal averages and correlations.

Object Boundaries Influence Toddlers' Performance in a Search Task

ERIC Educational Resources Information Center

Shutts, Kristin; Keen, Rachel; Spelke, Elizabeth S.

2006-01-01

Previous research has shown that young children have difficulty searching for a hidden object whose location depends on the position of a partly visible physical barrier. Across four experiments, we tested whether children's search errors are affected by two variables that influence adults' object-directed attention: object boundaries and…

Combustion characteristics of an SI engine fueled with biogas fuel

NASA Astrophysics Data System (ADS)

Chen, Lei; Long, Wuqiang; Song, Peng

2017-04-01

An experimental research of the effect of H2 substitution and CO2 dilution on CH4 combustion has been carried out on a spark ignition engine. The results show that H2 addition could improve BMEP, thermal efficiency, CO and THC emissions. NOX emissions increased for higher low heating value (LHV) of H2 than CH4. CO2 dilution could effective reduce NOX emission of H2-CH4 combustion. Although engine performance, thermal efficiency and exhaust get unacceptable under high fuel dilution ratio (F.D.R.) conditions, it could be solved by decreasing F.D.R. and/or increasing hydrogen substitution ratio (H.S.R.).

Performance of a Small Internal Combustion Engine Using N-Heptane and Iso-Octane

DTIC Science & Technology

2010-03-01

evaluate the ON effects on a FUJI BF34-EI, small 4-stroke spark ignition engine as preliminary steps to using a military grade JP-8 jet turbine fuel ...K) Pcrit (MPa) HHV (kJ/kg) LHV (kJ/kg) n-Heptane C7H16 100.20 371.60 537.70 2.62 48,456 44,926 i-Octane C8H18 114.22 398.40 567.50 2.40 48,275 44,791...meter the fuel . The carburetor is equipped with both a high speed and low speed fuel jet . It is unknown what engine speed it switches from one to

GT200 getting better than 34% efficiency

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

Farmer, R.

1980-01-01

Design features are described for the GT200, a 50-Hz machine blend of high temperature advanced aircraft rotating components and heavy frame industrial gas turbine structure. It includes a twin spool as generator with a two-stage power turbine giving nominal performance of 85,000 kW ISO peak output with a 10,120 Btu per kW-h heat rate on LHV distillate. It is desgined for base, intermediate, or peak load operation simple or combined cycle. Stal-Laval in Sweden developed it and sold the first unit to the Swedish State Power Board in July 1977. The unit was installed at the Stallbocka Station.

Accurate Permittivity Measurements for Microwave Imaging via Ultra-Wideband Removal of Spurious Reflectors

PubMed Central

Pelletier, Mathew G.; Viera, Joseph A.; Wanjura, John; Holt, Greg

2010-01-01

The use of microwave imaging is becoming more prevalent for detection of interior hidden defects in manufactured and packaged materials. In applications for detection of hidden moisture, microwave tomography can be used to image the material and then perform an inverse calculation to derive an estimate of the variability of the hidden material, such internal moisture, thereby alerting personnel to damaging levels of the hidden moisture before material degradation occurs. One impediment to this type of imaging occurs with nearby objects create strong reflections that create destructive and constructive interference, at the receiver, as the material is conveyed past the imaging antenna array. In an effort to remove the influence of the reflectors, such as metal bale ties, research was conducted to develop an algorithm for removal of the influence of the local proximity reflectors from the microwave images. This research effort produced a technique, based upon the use of ultra-wideband signals, for the removal of spurious reflections created by local proximity reflectors. This improvement enables accurate microwave measurements of moisture in such products as cotton bales, as well as other physical properties such as density or material composition. The proposed algorithm was shown to reduce errors by a 4:1 ratio and is an enabling technology for imaging applications in the presence of metal bale ties. PMID:22163668

Exploring the Unknown: Detection of Fast Variability of Starlight (Abstract)

NASA Astrophysics Data System (ADS)

Stanton, R. H.

2017-12-01

(Abstract only) In previous papers the author described a photometer designed for observing high-speed events such as lunar and asteroid occultations, and for searching for new varieties of fast stellar variability. A significant challenge presented by such a system is how one deals with the large quantity of data generated in order to process it efficiently and reveal any hidden information that might be present. This paper surveys some of the techniques used to achieve this goal.

Exploring the Hard and Soft X-ray Emission of Magnetic Cataclysmic Variables

NASA Astrophysics Data System (ADS)

de Martino, D.; Anzolin, G.; Bonnet-Bidaud, J.-M.; Falanga, M.; Matt, G.; Mouchet, M.; Mukai, K.; Masetti, N.

2009-05-01

A non-negligible fraction of galactic hard (>20 keV) X-ray sources were identified as CVs of the magnetic Intermediate Polar type in INTEGRAL, SWIFT and RXTE surveys, that suggests a still hidden but potentially important population of faint hard X-ray sources. Simbol-X has the unique potential to simultaneously characterize their variable and complex soft and hard X-ray emission thus allowing to understand their putative role in galactic populations of X-ray sources.

Investigation of an HMM/ANN hybrid structure in pattern recognition application using cepstral analysis of dysarthric (distorted) speech signals.

PubMed

Polur, Prasad D; Miller, Gerald E

2006-10-01

Computer speech recognition of individuals with dysarthria, such as cerebral palsy patients requires a robust technique that can handle conditions of very high variability and limited training data. In this study, application of a 10 state ergodic hidden Markov model (HMM)/artificial neural network (ANN) hybrid structure for a dysarthric speech (isolated word) recognition system, intended to act as an assistive tool, was investigated. A small size vocabulary spoken by three cerebral palsy subjects was chosen. The effect of such a structure on the recognition rate of the system was investigated by comparing it with an ergodic hidden Markov model as a control tool. This was done in order to determine if this modified technique contributed to enhanced recognition of dysarthric speech. The speech was sampled at 11 kHz. Mel frequency cepstral coefficients were extracted from them using 15 ms frames and served as training input to the hybrid model setup. The subsequent results demonstrated that the hybrid model structure was quite robust in its ability to handle the large variability and non-conformity of dysarthric speech. The level of variability in input dysarthric speech patterns sometimes limits the reliability of the system. However, its application as a rehabilitation/control tool to assist dysarthric motor impaired individuals holds sufficient promise.

Dynamic Alignment Models for Neural Coding

PubMed Central

Kollmorgen, Sepp; Hahnloser, Richard H. R.

2014-01-01

Recently, there have been remarkable advances in modeling the relationships between the sensory environment, neuronal responses, and behavior. However, most models cannot encompass variable stimulus-response relationships such as varying response latencies and state or context dependence of the neural code. Here, we consider response modeling as a dynamic alignment problem and model stimulus and response jointly by a mixed pair hidden Markov model (MPH). In MPHs, multiple stimulus-response relationships (e.g., receptive fields) are represented by different states or groups of states in a Markov chain. Each stimulus-response relationship features temporal flexibility, allowing modeling of variable response latencies, including noisy ones. We derive algorithms for learning of MPH parameters and for inference of spike response probabilities. We show that some linear-nonlinear Poisson cascade (LNP) models are a special case of MPHs. We demonstrate the efficiency and usefulness of MPHs in simulations of both jittered and switching spike responses to white noise and natural stimuli. Furthermore, we apply MPHs to extracellular single and multi-unit data recorded in cortical brain areas of singing birds to showcase a novel method for estimating response lag distributions. MPHs allow simultaneous estimation of receptive fields, latency statistics, and hidden state dynamics and so can help to uncover complex stimulus response relationships that are subject to variable timing and involve diverse neural codes. PMID:24625448

Efficiently Exploring Multilevel Data with Recursive Partitioning

ERIC Educational Resources Information Center

Martin, Daniel P.; von Oertzen, Timo; Rimm-Kaufman, Sara E.

2015-01-01

There is an increasing number of datasets with many participants, variables, or both, in education and other fields that often deal with large, multilevel data structures. Once initial confirmatory hypotheses are exhausted, it can be difficult to determine how best to explore the dataset to discover hidden relationships that could help to inform…

Quasi-Bell inequalities from symmetrized products of noncommuting qubit observables

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

Gamel, Omar E.; Fleming, Graham R.

Noncommuting observables cannot be simultaneously measured; however, under local hidden variable models, they must simultaneously hold premeasurement values, implying the existence of a joint probability distribution. We study the joint distributions of noncommuting observables on qubits, with possible criteria of positivity and the Fréchet bounds limiting the joint probabilities, concluding that the latter may be negative. We use symmetrization, justified heuristically and then more carefully via the Moyal characteristic function, to find the quantum operator corresponding to the product of noncommuting observables. This is then used to construct Quasi-Bell inequalities, Bell inequalities containing products of noncommuting observables, on two qubits.more » These inequalities place limits on the local hidden variable models that define joint probabilities for noncommuting observables. We also found that the Quasi-Bell inequalities have a quantum to classical violation as high as 3/2 on two qubit, higher than conventional Bell inequalities. Our result demonstrates the theoretical importance of noncommutativity in the nonlocality of quantum mechanics and provides an insightful generalization of Bell inequalities.« less

Improving Forecasts Through Realistic Uncertainty Estimates: A Novel Data Driven Method for Model Uncertainty Quantification in Data Assimilation

NASA Astrophysics Data System (ADS)

Pathiraja, S. D.; Moradkhani, H.; Marshall, L. A.; Sharma, A.; Geenens, G.

2016-12-01

Effective combination of model simulations and observations through Data Assimilation (DA) depends heavily on uncertainty characterisation. Many traditional methods for quantifying model uncertainty in DA require some level of subjectivity (by way of tuning parameters or by assuming Gaussian statistics). Furthermore, the focus is typically on only estimating the first and second moments. We propose a data-driven methodology to estimate the full distributional form of model uncertainty, i.e. the transition density p(xt|xt-1). All sources of uncertainty associated with the model simulations are considered collectively, without needing to devise stochastic perturbations for individual components (such as model input, parameter and structural uncertainty). A training period is used to derive the distribution of errors in observed variables conditioned on hidden states. Errors in hidden states are estimated from the conditional distribution of observed variables using non-linear optimization. The theory behind the framework and case study applications are discussed in detail. Results demonstrate improved predictions and more realistic uncertainty bounds compared to a standard perturbation approach.

Steering, or maybe why Einstein did not go all the way to Bellʼs argument

NASA Astrophysics Data System (ADS)

Werner, R. F.

2014-10-01

It is shown that a main source of conflict between Einstein and the mainstream quantum physicists was his insistence that wave functions, like classical probability distributions, do not refer to individual particles and, in particular, do not describe individual systems completely. The EPR paper was written to argue for this position. By aiming at showing that wave functions are unsuitable as local hidden variables, the authors failed to see that a slight extension could have ruled out such local hidden variables in general. As background for this analysis of the EPR argument the notion of steering is described, and a version of the Bell argument is proved which emphasizes non-local signalling aspects. Finally, some background is given concerning a well-known paper by the present author, which is celebrating 25 years this year, and in which the first non-steering models were constructed. This article is part of a special issue of Journal of Physics A: Mathematical and Theoretical devoted to ‘50 years of Bell’s theorem’.

Quasi-Bell inequalities from symmetrized products of noncommuting qubit observables

DOE PAGES

Gamel, Omar E.; Fleming, Graham R.

2017-05-01

Noncommuting observables cannot be simultaneously measured; however, under local hidden variable models, they must simultaneously hold premeasurement values, implying the existence of a joint probability distribution. We study the joint distributions of noncommuting observables on qubits, with possible criteria of positivity and the Fréchet bounds limiting the joint probabilities, concluding that the latter may be negative. We use symmetrization, justified heuristically and then more carefully via the Moyal characteristic function, to find the quantum operator corresponding to the product of noncommuting observables. This is then used to construct Quasi-Bell inequalities, Bell inequalities containing products of noncommuting observables, on two qubits.more » These inequalities place limits on the local hidden variable models that define joint probabilities for noncommuting observables. We also found that the Quasi-Bell inequalities have a quantum to classical violation as high as 3/2 on two qubit, higher than conventional Bell inequalities. Our result demonstrates the theoretical importance of noncommutativity in the nonlocality of quantum mechanics and provides an insightful generalization of Bell inequalities.« less

A hidden variable in shear transformation zone volume versus Poisson's ratio relation in metallic glasses

NASA Astrophysics Data System (ADS)

Kim, S. Y.; Oh, H. S.; Park, E. S.

2017-10-01

Herein, we elucidate a hidden variable in a shear transformation zone (STZ) volume (Ω) versus Poisson's ratio (ν) relation and clarify the correlation between STZ characteristics and the plasticity of metallic glasses (MGs). On the basis of cooperative shear model and atomic stress theories, we carefully formulate Ω as a function of molar volume (Vm) and ν. The twofold trend in Ω and ν is attributed to a relatively large variation of Vm as compared to that of ν as well as an inverse relation between Vm and ν. Indeed, the derived equation reveals that the number of atoms in an STZ instead of Ω is a microstructural characteristic which has a close relationship with plasticity since it reflects the preference of atomistic behaviors between cooperative shearing and the generation of volume strain fluctuation under stress. The results would deepen our understanding of the correlation between microscopic behaviors (STZ activation) and macroscopic properties (plasticity) in MGs and enable a quantitative approach in associating various STZ-related macroscopic behaviors with intrinsic properties of MGs.

From the Kochen-Specker theorem to noncontextuality inequalities without assuming determinism.

PubMed

Kunjwal, Ravi; Spekkens, Robert W

2015-09-11

The Kochen-Specker theorem demonstrates that it is not possible to reproduce the predictions of quantum theory in terms of a hidden variable model where the hidden variables assign a value to every projector deterministically and noncontextually. A noncontextual value assignment to a projector is one that does not depend on which other projectors-the context-are measured together with it. Using a generalization of the notion of noncontextuality that applies to both measurements and preparations, we propose a scheme for deriving inequalities that test whether a given set of experimental statistics is consistent with a noncontextual model. Unlike previous inequalities inspired by the Kochen-Specker theorem, we do not assume that the value assignments are deterministic and therefore in the face of a violation of our inequality, the possibility of salvaging noncontextuality by abandoning determinism is no longer an option. Our approach is operational in the sense that it does not presume quantum theory: a violation of our inequality implies the impossibility of a noncontextual model for any operational theory that can account for the experimental observations, including any successor to quantum theory.

Quantum Locality?

NASA Astrophysics Data System (ADS)

Stapp, Henry P.

2012-05-01

Robert Griffiths has recently addressed, within the framework of a `consistent quantum theory' that he has developed, the issue of whether, as is often claimed, quantum mechanics entails a need for faster-than-light transfers of information over long distances. He argues that the putative proofs of this property that involve hidden variables include in their premises some essentially classical-physics-type assumptions that are not entailed by the precepts of quantum mechanics. Thus whatever is proved is not a feature of quantum mechanics, but is a property of a theory that tries to combine quantum theory with quasi-classical features that go beyond what is entailed by quantum theory itself. One cannot logically prove properties of a system by establishing, instead, properties of a system modified by adding properties alien to the original system. Hence Griffiths' rejection of hidden-variable-based proofs is logically warranted. Griffiths mentions the existence of a certain alternative proof that does not involve hidden variables, and that uses only macroscopically described observable properties. He notes that he had examined in his book proofs of this general kind, and concluded that they provide no evidence for nonlocal influences. But he did not examine the particular proof that he cites. An examination of that particular proof by the method specified by his `consistent quantum theory' shows that the cited proof is valid within that restrictive version of quantum theory. An added section responds to Griffiths' reply, which cites general possibilities of ambiguities that might make what is to be proved ill-defined, and hence render the pertinent `consistent framework' ill defined. But the vagaries that he cites do not upset the proof in question, which, both by its physical formulation and by explicit identification, specify the framework to be used. Griffiths confirms the validity of the proof insofar as that pertinent framework is used. The section also shows, in response to Griffiths' challenge, why a putative proof of locality that he has described is flawed.

Estimation of Hidden State Variables of the Intracranial System Using Constrained Nonlinear Kalman Filters

PubMed Central

Nenov, Valeriy; Bergsneider, Marvin; Glenn, Thomas C.; Vespa, Paul; Martin, Neil

2007-01-01

Impeded by the rigid skull, assessment of physiological variables of the intracranial system is difficult. A hidden state estimation approach is used in the present work to facilitate the estimation of unobserved variables from available clinical measurements including intracranial pressure (ICP) and cerebral blood flow velocity (CBFV). The estimation algorithm is based on a modified nonlinear intracranial mathematical model, whose parameters are first identified in an offline stage using a nonlinear optimization paradigm. Following the offline stage, an online filtering process is performed using a nonlinear Kalman filter (KF)-like state estimator that is equipped with a new way of deriving the Kalman gain satisfying the physiological constraints on the state variables. The proposed method is then validated by comparing different state estimation methods and input/output (I/O) configurations using simulated data. It is also applied to a set of CBFV, ICP and arterial blood pressure (ABP) signal segments from brain injury patients. The results indicated that the proposed constrained nonlinear KF achieved the best performance among the evaluated state estimators and that the state estimator combined with the I/O configuration that has ICP as the measured output can potentially be used to estimate CBFV continuously. Finally, the state estimator combined with the I/O configuration that has both ICP and CBFV as outputs can potentially estimate the lumped cerebral arterial radii, which are not measurable in a typical clinical environment. PMID:17281533

Python Environment for Bayesian Learning: Inferring the Structure of Bayesian Networks from Knowledge and Data

PubMed Central

Shah, Abhik; Woolf, Peter

2009-01-01

Summary In this paper, we introduce pebl, a Python library and application for learning Bayesian network structure from data and prior knowledge that provides features unmatched by alternative software packages: the ability to use interventional data, flexible specification of structural priors, modeling with hidden variables and exploitation of parallel processing. PMID:20161541

Linking Costs and Postsecondary Degrees: Key Issues for Policymakers. Working Paper 2011-03

ERIC Educational Resources Information Center

Johnson, Nate

2011-01-01

In this paper the author offers practical advice for decision-makers who are struggling to rein in college costs while improving productivity. He provides a step-by-step guide to different approaches for calculating costs, highlights the tremendous variability in cost across programs within institutions, and documents some of the "hidden costs" of…

The Hidden Factor in Early Field Experience: Teachers' Perception of the Quality of Life at Work.

ERIC Educational Resources Information Center

Divins, Barbara; And Others

This project identified work environment factors in eight schools where a teacher preparation program placed early field experience students and where the university students reported experiencing positive field placements. The purpose was to determine the impact of certain variables on teachers' perception of the quality of their own professional…

Memory and foraging theory: Chimpanzee utilization of optimality heuristics in the rank-order recovery of hidden foods

PubMed Central

Sayers, Ken; Menzel, Charles R.

2012-01-01

Many models from foraging theory and movement ecology assume that resources are encountered randomly. If food locations, types and values are retained in memory, however, search time could be significantly reduced, with concurrent effects on biological fitness. Despite this, little is known about what specific characteristics of foods, particularly those relevant to profitability, nonhuman animals can remember. Building upon previous observations, we hypothesized that chimpanzees (Pan troglodytes), after observing foods being hidden in a large wooded test area they could not enter, and after long delays, would direct (through gesture and vocalization) experimentally naïve humans to the reward locations in an order that could be predicted beforehand by the spatial and physical characteristics of those items. In the main experiment, various quantities of almonds, both in and out of shells and sealed in transparent bags, were hidden in the test area. The chimpanzees later directed searchers to those items in a nonrandom order related to quantity, shell presence/absence, and the distance they were hidden from the subject. The recovery sequences were closely related to the actual e/h profitability of the foods. Predicted recovery orders, based on the energetic value of almonds and independently-measured, individual-specific expected pursuit and processing times, were closely related to observed recovery orders. We argue that the information nonhuman animals possess regarding their environment can be extensive, and that further comparative study is vital for incorporating realistic cognitive variables into models of foraging and movement. PMID:23226837

Parsing Social Network Survey Data from Hidden Populations Using Stochastic Context-Free Grammars

PubMed Central

Poon, Art F. Y.; Brouwer, Kimberly C.; Strathdee, Steffanie A.; Firestone-Cruz, Michelle; Lozada, Remedios M.; Kosakovsky Pond, Sergei L.; Heckathorn, Douglas D.; Frost, Simon D. W.

2009-01-01

Background Human populations are structured by social networks, in which individuals tend to form relationships based on shared attributes. Certain attributes that are ambiguous, stigmatized or illegal can create a ÔhiddenÕ population, so-called because its members are difficult to identify. Many hidden populations are also at an elevated risk of exposure to infectious diseases. Consequently, public health agencies are presently adopting modern survey techniques that traverse social networks in hidden populations by soliciting individuals to recruit their peers, e.g., respondent-driven sampling (RDS). The concomitant accumulation of network-based epidemiological data, however, is rapidly outpacing the development of computational methods for analysis. Moreover, current analytical models rely on unrealistic assumptions, e.g., that the traversal of social networks can be modeled by a Markov chain rather than a branching process. Methodology/Principal Findings Here, we develop a new methodology based on stochastic context-free grammars (SCFGs), which are well-suited to modeling tree-like structure of the RDS recruitment process. We apply this methodology to an RDS case study of injection drug users (IDUs) in Tijuana, México, a hidden population at high risk of blood-borne and sexually-transmitted infections (i.e., HIV, hepatitis C virus, syphilis). Survey data were encoded as text strings that were parsed using our custom implementation of the inside-outside algorithm in a publicly-available software package (HyPhy), which uses either expectation maximization or direct optimization methods and permits constraints on model parameters for hypothesis testing. We identified significant latent variability in the recruitment process that violates assumptions of Markov chain-based methods for RDS analysis: firstly, IDUs tended to emulate the recruitment behavior of their own recruiter; and secondly, the recruitment of like peers (homophily) was dependent on the number of recruits. Conclusions SCFGs provide a rich probabilistic language that can articulate complex latent structure in survey data derived from the traversal of social networks. Such structure that has no representation in Markov chain-based models can interfere with the estimation of the composition of hidden populations if left unaccounted for, raising critical implications for the prevention and control of infectious disease epidemics. PMID:19738904

Extracting Leading Nonlinear Modes of Changing Climate From Global SST Time Series

NASA Astrophysics Data System (ADS)

Mukhin, D.; Gavrilov, A.; Loskutov, E. M.; Feigin, A. M.; Kurths, J.

2017-12-01

Data-driven modeling of climate requires adequate principal variables extracted from observed high-dimensional data. For constructing such variables it is needed to find spatial-temporal patterns explaining a substantial part of the variability and comprising all dynamically related time series from the data. The difficulties of this task rise from the nonlinearity and non-stationarity of the climate dynamical system. The nonlinearity leads to insufficiency of linear methods of data decomposition for separating different processes entangled in the observed time series. On the other hand, various forcings, both anthropogenic and natural, make the dynamics non-stationary, and we should be able to describe the response of the system to such forcings in order to separate the modes explaining the internal variability. The method we present is aimed to overcome both these problems. The method is based on the Nonlinear Dynamical Mode (NDM) decomposition [1,2], but takes into account external forcing signals. An each mode depends on hidden, unknown a priori, time series which, together with external forcing time series, are mapped onto data space. Finding both the hidden signals and the mapping allows us to study the evolution of the modes' structure in changing external conditions and to compare the roles of the internal variability and forcing in the observed behavior. The method is used for extracting of the principal modes of SST variability on inter-annual and multidecadal time scales accounting the external forcings such as CO2, variations of the solar activity and volcanic activity. The structure of the revealed teleconnection patterns as well as their forecast under different CO2 emission scenarios are discussed.[1] Mukhin, D., Gavrilov, A., Feigin, A., Loskutov, E., & Kurths, J. (2015). Principal nonlinear dynamical modes of climate variability. Scientific Reports, 5, 15510. [2] Gavrilov, A., Mukhin, D., Loskutov, E., Volodin, E., Feigin, A., & Kurths, J. (2016). Method for reconstructing nonlinear modes with adaptive structure from multidimensional data. Chaos: An Interdisciplinary Journal of Nonlinear Science, 26(12), 123101.

Religious Beliefs: A Hidden Variable in the Performance of Science Teachers in the Classroom

ERIC Educational Resources Information Center

Mansour, Nasser

2008-01-01

This article focuses on some of the challenges of teaching science in a culture where science and religion sometimes appear to be or are set at odds with each other. Apparent conflicts between scholarly claims and religious claims are not limited to science, however--they occur in almost every subject. Many topics included in science education are…

Non-local boxes and their implementation in Minecraft

NASA Astrophysics Data System (ADS)

Simnacher, Timo Yannick

PR-boxes are binary devices connecting two remote parties satisfying x AND y = a + b mod 2, where x and y denote the binary inputs and a and b are the respective outcomes without signaling. These devices are named after their inventors Sandu Popescu and Daniel Rohrlich and saturate the Clauser-Horne-Shimony-Holt (CHSH) inequality. This Bell-like inequality bounds the correlation that can exist between two remote, non-signaling, classical systems described by local hidden variable theories. Experiments have now convincingly shown that quantum entanglement cannot be explained by local hidden variable theories. Furthermore, the CHSH inequality provides a method to distinguish quantum systems from super-quantum correlations. The correlation between the outputs of the PR-box goes beyond any quantum entanglement. Though PR-boxes would have impressive consequences, as far as we know they are not physically realizable. However, by introducing PR-boxes to Minecraft as part of the redstone system, which simulates the electrical components for binary computing, we can experience the consequences of super-quantum correlations. For instance, Wim van Dam proved that two parties can use a sufficient number of PR-boxes to compute any Boolean function f(x,y) with only one bit of communication.

Estimating the periodic components of a biomedical signal through inverse problem modelling and Bayesian inference with sparsity enforcing prior

NASA Astrophysics Data System (ADS)

Dumitru, Mircea; Djafari, Ali-Mohammad

2015-01-01

The recent developments in chronobiology need a periodic components variation analysis for the signals expressing the biological rhythms. A precise estimation of the periodic components vector is required. The classical approaches, based on FFT methods, are inefficient considering the particularities of the data (short length). In this paper we propose a new method, using the sparsity prior information (reduced number of non-zero values components). The considered law is the Student-t distribution, viewed as a marginal distribution of a Infinite Gaussian Scale Mixture (IGSM) defined via a hidden variable representing the inverse variances and modelled as a Gamma Distribution. The hyperparameters are modelled using the conjugate priors, i.e. using Inverse Gamma Distributions. The expression of the joint posterior law of the unknown periodic components vector, hidden variables and hyperparameters is obtained and then the unknowns are estimated via Joint Maximum A Posteriori (JMAP) and Posterior Mean (PM). For the PM estimator, the expression of the posterior law is approximated by a separable one, via the Bayesian Variational Approximation (BVA), using the Kullback-Leibler (KL) divergence. Finally we show the results on synthetic data in cancer treatment applications.

Inference for finite-sample trajectories in dynamic multi-state site-occupancy models using hidden Markov model smoothing

USGS Publications Warehouse

Fiske, Ian J.; Royle, J. Andrew; Gross, Kevin

2014-01-01

Ecologists and wildlife biologists increasingly use latent variable models to study patterns of species occurrence when detection is imperfect. These models have recently been generalized to accommodate both a more expansive description of state than simple presence or absence, and Markovian dynamics in the latent state over successive sampling seasons. In this paper, we write these multi-season, multi-state models as hidden Markov models to find both maximum likelihood estimates of model parameters and finite-sample estimators of the trajectory of the latent state over time. These estimators are especially useful for characterizing population trends in species of conservation concern. We also develop parametric bootstrap procedures that allow formal inference about latent trend. We examine model behavior through simulation, and we apply the model to data from the North American Amphibian Monitoring Program.

Analysis of complex neural circuits with nonlinear multidimensional hidden state models

PubMed Central

Friedman, Alexander; Slocum, Joshua F.; Tyulmankov, Danil; Gibb, Leif G.; Altshuler, Alex; Ruangwises, Suthee; Shi, Qinru; Toro Arana, Sebastian E.; Beck, Dirk W.; Sholes, Jacquelyn E. C.; Graybiel, Ann M.

2016-01-01

A universal need in understanding complex networks is the identification of individual information channels and their mutual interactions under different conditions. In neuroscience, our premier example, networks made up of billions of nodes dynamically interact to bring about thought and action. Granger causality is a powerful tool for identifying linear interactions, but handling nonlinear interactions remains an unmet challenge. We present a nonlinear multidimensional hidden state (NMHS) approach that achieves interaction strength analysis and decoding of networks with nonlinear interactions by including latent state variables for each node in the network. We compare NMHS to Granger causality in analyzing neural circuit recordings and simulations, improvised music, and sociodemographic data. We conclude that NMHS significantly extends the scope of analyses of multidimensional, nonlinear networks, notably in coping with the complexity of the brain. PMID:27222584

Mathematical and physical meaning of the Bell inequalities

NASA Astrophysics Data System (ADS)

Santos, Emilio

2016-09-01

It is shown that the Bell inequalities are closely related to the triangle inequalities involving distance functions amongst pairs of random variables with values \\{0,1\\}. A hidden variables model may be defined as a mapping between a set of quantum projection operators and a set of random variables. The model is noncontextual if there is a joint probability distribution. The Bell inequalities are necessary conditions for its existence. The inequalities are most relevant when measurements are performed at space-like separation, thus showing a conflict between quantum mechanics and local realism (Bell's theorem). The relations of the Bell inequalities with contextuality, the Kochen-Specker theorem, and quantum entanglement are briefly discussed.

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.

Optimization of neural network architecture for classification of radar jamming FM signals

NASA Astrophysics Data System (ADS)

Soto, Alberto; Mendoza, Ariadna; Flores, Benjamin C.

2017-05-01

The purpose of this study is to investigate several artificial Neural Network (NN) architectures in order to design a cognitive radar system capable of optimally distinguishing linear Frequency-Modulated (FM) signals from bandlimited Additive White Gaussian Noise (AWGN). The goal is to create a theoretical framework to determine an optimal NN architecture to achieve a Probability of Detection (PD) of 95% or higher and a Probability of False Alarm (PFA) of 1.5% or lower at 5 dB Signal to Noise Ratio (SNR). Literature research reveals that the frequency-domain power spectral densities characterize a signal more efficiently than its time-domain counterparts. Therefore, the input data is preprocessed by calculating the magnitude square of the Discrete Fourier Transform of the digitally sampled bandlimited AWGN and linear FM signals to populate a matrix containing N number of samples and M number of spectra. This matrix is used as input for the NN, and the spectra are divided as follows: 70% for training, 15% for validation, and 15% for testing. The study begins by experimentally deducing the optimal number of hidden neurons (1-40 neurons), then the optimal number of hidden layers (1-5 layers), and lastly, the most efficient learning algorithm. The training algorithms examined are: Resilient Backpropagation, Scaled Conjugate Gradient, Conjugate Gradient with Powell/Beale Restarts, Polak-Ribiére Conjugate Gradient, and Variable Learning Rate Backpropagation. We determine that an architecture with ten hidden neurons (or higher), one hidden layer, and a Scaled Conjugate Gradient for training algorithm encapsulates an optimal architecture for our application.

Nonrecurrence and Bell-like inequalities

NASA Astrophysics Data System (ADS)

Danforth, Douglas G.

2017-12-01

The general class, Λ, of Bell hidden variables is composed of two subclasses ΛR and ΛN such that ΛR⋃ΛN = Λ and ΛR∩ ΛN = {}. The class ΛN is very large and contains random variables whose domain is the continuum, the reals. There are an uncountable infinite number of reals. Every instance of a real random variable is unique. The probability of two instances being equal is zero, exactly zero. ΛN induces sample independence. All correlations are context dependent but not in the usual sense. There is no "spooky action at a distance". Random variables, belonging to ΛN, are independent from one experiment to the next. The existence of the class ΛN makes it impossible to derive any of the standard Bell inequalities used to define quantum entanglement.

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

Cabello, Adan

We introduce two two-player quantum pseudotelepathy games based on two recently proposed all-versus-nothing (AVN) proofs of Bell's theorem [A. Cabello, Phys. Rev. Lett. 95, 210401 (2005); Phys. Rev. A 72, 050101(R) (2005)]. These games prove that Broadbent and Methot's claim that these AVN proofs do not rule out local-hidden-variable theories in which it is possible to exchange unlimited information inside the same light cone (quant-ph/0511047) is incorrect.

Multi-Observation Continuous Density Hidden Markov Models for Anomaly Detection in Full Motion Video

DTIC Science & Technology

2012-06-01

response profiles . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 47 3.5 Method for measuring angular movement versus average direction...of movement 49 3.6 Method for calculating Angular Deviation, Θ . . . . . . . . . . . . . . . . . . 50 4.1 HMM produced by K Means Learning for agent H... Angular Deviation. A random variable, the difference in heading (in degrees) from the overall direction of movement over the sequence • S : Speed. A

Repositioned Lives: Language, Ethnicity, and Narrative Identity among Chinese-Vietnamese Community College Students in Los Angeles' San Gabriel Valley.

ERIC Educational Resources Information Center

Frank, Russell Alan

Chinese speakers from Vietnam are a distinctive but hidden ethnolinguistic minority group in the San Gabriel Valley region of Los Angeles. Many variables present barriers to their full participation in society from both the values and norms of dominant American society and non-Chinese co-nationals from Vietnam as well as higher status co-ethnics…

Reply to ''Comment on 'Mutually unbiased bases, orthogonal Latin squares, and hidden-variable models'''

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

Paterek, Tomasz; Dakic, Borivoje; Brukner, Caslav

In this Reply to the preceding Comment by Hall and Rao [Phys. Rev. A 83, 036101 (2011)], we motivate terminology of our original paper and point out that further research is needed in order to (dis)prove the claimed link between every orthogonal Latin square of order being a power of a prime and a mutually unbiased basis.

Nonassociativity, supersymmetry, and hidden variables

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

Dzhunushaliev, Vladimir

2008-04-15

It is shown that the supersymmetric quantum mechanics has an octonionic generalization. The generalization is based on the inclusion of quaternions into octonions. The elements from the coset octonions/quaternions are unobservables because they cannot be considered as quantum operators as a consequence of their nonassociative properties. The idea that the octonionic generalization of the supersymmetric quantum mechanics describes an observable particle formed with unobservable ''particles'' is presented.

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

Quantum Locality?

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

Stapp, Henry

Robert Griffiths has recently addressed, within the framework of a ‘consistent quantum theory’ (CQT) that he has developed, the issue of whether, as is often claimed, quantum mechanics entails a need for faster-than-light transfers of information over long distances. He argues, on the basis of his examination of certain arguments that claim to demonstrate the existence of such nonlocal influences, that such influences do not exist. However, his examination was restricted mainly to hidden-variable-based arguments that include in their premises some essentially classical-physics-type assumptions that are fundamentally incompatible with the precepts of quantum physics. One cannot logically prove properties ofmore » a system by attributing to the system properties alien to that system. Hence Griffiths’ rejection of hidden-variable-based proofs is logically warranted. Griffiths mentions the existence of a certain alternative proof that does not involve hidden variables, and that uses only macroscopically described observable properties. He notes that he had examined in his book proofs of this general kind, and concluded that they provide no evidence for nonlocal influences. But he did not examine the particular proof that he cites. An examination of that particular proof by the method specified by his ‘consistent quantum theory’ shows that the cited proof is valid within that restrictive framework. This necessary existence, within the ‘consistent’ framework, of long range essentially instantaneous influences refutes the claim made by Griffiths that his ‘consistent’ framework is superior to the orthodox quantum theory of von Neumann because it does not entail instantaneous influences. An added section responds to Griffiths’ reply, which cites a litany of ambiguities that seem to restrict, devastatingly, the scope of his CQT formalism, apparently to buttress his claim that my use of that formalism to validate the nonlocality theorem is flawed. But the vagaries that he cites do not upset the proof in question. It is show here in detail why the precise statement of this theorem justifies the specified application of CQT. It is also shown, in response to his challenge, why a putative proof of locality that he has proposed is not valid.« less

A Bayesian approach to estimating hidden variables as well as missing and wrong molecular interactions in ordinary differential equation-based mathematical models.

PubMed

Engelhardt, Benjamin; Kschischo, Maik; Fröhlich, Holger

2017-06-01

Ordinary differential equations (ODEs) are a popular approach to quantitatively model molecular networks based on biological knowledge. However, such knowledge is typically restricted. Wrongly modelled biological mechanisms as well as relevant external influence factors that are not included into the model are likely to manifest in major discrepancies between model predictions and experimental data. Finding the exact reasons for such observed discrepancies can be quite challenging in practice. In order to address this issue, we suggest a Bayesian approach to estimate hidden influences in ODE-based models. The method can distinguish between exogenous and endogenous hidden influences. Thus, we can detect wrongly specified as well as missed molecular interactions in the model. We demonstrate the performance of our Bayesian dynamic elastic-net with several ordinary differential equation models from the literature, such as human JAK-STAT signalling, information processing at the erythropoietin receptor, isomerization of liquid α -Pinene, G protein cycling in yeast and UV-B triggered signalling in plants. Moreover, we investigate a set of commonly known network motifs and a gene-regulatory network. Altogether our method supports the modeller in an algorithmic manner to identify possible sources of errors in ODE-based models on the basis of experimental data. © 2017 The Author(s).

Implementation of neural network for color properties of polycarbonates

NASA Astrophysics Data System (ADS)

Saeed, U.; Ahmad, S.; Alsadi, J.; Ross, D.; Rizvi, G.

2014-05-01

In present paper, the applicability of artificial neural networks (ANN) is investigated for color properties of plastics. The neural networks toolbox of Matlab 6.5 is used to develop and test the ANN model on a personal computer. An optimal design is completed for 10, 12, 14,16,18 & 20 hidden neurons on single hidden layer with five different algorithms: batch gradient descent (GD), batch variable learning rate (GDX), resilient back-propagation (RP), scaled conjugate gradient (SCG), levenberg-marquardt (LM) in the feed forward back-propagation neural network model. The training data for ANN is obtained from experimental measurements. There were twenty two inputs including resins, additives & pigments while three tristimulus color values L*, a* and b* were used as output layer. Statistical analysis in terms of Root-Mean-Squared (RMS), absolute fraction of variance (R squared), as well as mean square error is used to investigate the performance of ANN. LM algorithm with fourteen neurons on hidden layer in Feed Forward Back-Propagation of ANN model has shown best result in the present study. The degree of accuracy of the ANN model in reduction of errors is proven acceptable in all statistical analysis and shown in results. However, it was concluded that ANN provides a feasible method in error reduction in specific color tristimulus values.

Life-cycle modification in open oceans accounts for genome variability in a cosmopolitan phytoplankton.

PubMed

von Dassow, Peter; John, Uwe; Ogata, Hiroyuki; Probert, Ian; Bendif, El Mahdi; Kegel, Jessica U; Audic, Stéphane; Wincker, Patrick; Da Silva, Corinne; Claverie, Jean-Michel; Doney, Scott; Glover, David M; Flores, Daniella Mella; Herrera, Yeritza; Lescot, Magali; Garet-Delmas, Marie-José; de Vargas, Colomban

2015-06-01

Emiliania huxleyi is the most abundant calcifying plankton in modern oceans with substantial intraspecific genome variability and a biphasic life cycle involving sexual alternation between calcified 2N and flagellated 1N cells. We show that high genome content variability in Emiliania relates to erosion of 1N-specific genes and loss of the ability to form flagellated cells. Analysis of 185 E. huxleyi strains isolated from world oceans suggests that loss of flagella occurred independently in lineages inhabiting oligotrophic open oceans over short evolutionary timescales. This environmentally linked physiogenomic change suggests life cycling is not advantageous in very large/diluted populations experiencing low biotic pressure and low ecological variability. Gene loss did not appear to reflect pressure for genome streamlining in oligotrophic oceans as previously observed in picoplankton. Life-cycle modifications might be common in plankton and cause major functional variability to be hidden from traditional taxonomic or molecular markers.

Foundational Forces & Hidden Variables in Technology Commercialization

NASA Astrophysics Data System (ADS)

Barnett, Brandon

2011-03-01

The science of physics seems vastly different from the process of technology commercialization. Physics strives to understand our world through the experimental deduction of immutable laws and dependent variables and the resulting macro-scale phenomenon. In comparison, the~goal of business is to make a profit by addressing the needs, preferences, and whims of individuals in a market. It may seem that this environment is too dynamic to identify all the hidden variables and deduct the foundational forces that impact a business's ability to commercialize innovative technologies. One example of a business ``force'' is found in the semiconductor industry. In 1965, Intel co-founder Gordon Moore predicted that the number of transistors incorporated in a chip will approximately double every 24 months. Known as Moore's Law, this prediction has become the guiding principle for the semiconductor industry for the last 40 years. Of course, Moore's Law is not really a law of nature; rather it is the result of efforts by Intel and the entire semiconductor industry. A closer examination suggests that there are foundational principles of business that underlie the macro-scale phenomenon of Moore's Law. Principles of profitability, incentive, and strategic alignment have resulted in a coordinated influx of resources that has driven technologies to market, increasing the profitability of the semiconductor industry and optimizing the fitness of its participants. New innovations in technology are subject to these same principles. So, in addition to traditional market forces, these often unrecognized forces and variables create challenges for new technology commercialization. In this talk, I will draw from ethnographic research, complex adaptive theory, and industry data to suggest a framework with which to think about new technology commercialization. Intel's bio-silicon initiative provides a case study.

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

Lessons from conducting trans-national Internet-mediated participatory research with hidden populations of cannabis cultivators.

PubMed

Barratt, Monica J; Potter, Gary R; Wouters, Marije; Wilkins, Chris; Werse, Bernd; Perälä, Jussi; Pedersen, Michael Mulbjerg; Nguyen, Holly; Malm, Aili; Lenton, Simon; Korf, Dirk; Klein, Axel; Heyde, Julie; Hakkarainen, Pekka; Frank, Vibeke Asmussen; Decorte, Tom; Bouchard, Martin; Blok, Thomas

2015-03-01

Internet-mediated research methods are increasingly used to access hidden populations. The International Cannabis Cultivation Questionnaire (ICCQ) is an online survey designed to facilitate international comparisons into the relatively under-researched but increasingly significant phenomenon of domestic cannabis cultivation. The Global Cannabis Cultivation Research Consortium has used the ICCQ to survey over 6000 cannabis cultivators across 11 countries. In this paper, we describe and reflect upon our methodological approach, focusing on the digital and traditional recruitment methods used to access this hidden population and the challenges of working across multiple countries, cultures and languages. Descriptive statistics showing eligibility and completion rates and recruitment source by country of residence. Over three quarters of eligible respondents who were presented with the survey were included in the final sample of n=6528. English-speaking countries expended more effort to recruit participants than non-English-speaking countries. The most effective recruitment modes were cannabis websites/groups (33%), Facebook (14%) and news articles (11%). While respondents recruited through news articles were older, growing practice variables were strikingly similar between these main recruitment modes. Through this process, we learnt that there are trade-offs between hosting multiple surveys in each country vs. using one integrated database. We also found that although perceived anonymity is routinely assumed to be a benefit of using digital research methodologies, there are significant limits to research participant anonymity in the current era of mass digital surveillance, especially when the target group is particularly concerned about evading law enforcement. Finally, we list a number of specific recommendations for future researchers utilising Internet-mediated approaches to researching hidden populations. Copyright © 2014 Elsevier B.V. All rights reserved.

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.

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.

Development of Residential SOFC Cogeneration System

NASA Astrophysics Data System (ADS)

Ono, Takashi; Miyachi, Itaru; Suzuki, Minoru; Higaki, Katsuki

2011-06-01

Since 2001 Kyocera has been developing 1kW class Solid Oxide Fuel Cell (SOFC) for power generation system. We have developed a cell, stack, module and system. Since 2004, Kyocera and Osaka Gas Co., Ltd. have been developed SOFC residential co-generation system. From 2007, we took part in the "Demonstrative Research on Solid Oxide Fuel Cells" Project conducted by New Energy Foundation (NEF). Total 57 units of 0.7kW class SOFC cogeneration systems had been installed at residential houses. In spite of residential small power demand, the actual electric efficiency was about 40%(netAC,LHV), and high CO2 reduction performance was achieved by these systems. Hereafter, new joint development, Osaka Gas, Toyota Motors, Kyocera and Aisin Seiki, aims early commercialization of residential SOFC CHP system.

Electrical Stimulation of the Midbrain to Promote Recovery from Traumatic Forebrain Injury

DTIC Science & Technology

2009-04-01

the beneficial trophic effects . The cylinder test, taken to indicate somatosensory function, gave highly variable results. We were unable to see a...learning in a hidden-platform water maze test was speeded by both dorsal and median raphe stimulation. Rearing movements in a transparent cylinder ...sensorimotor performance) were normalized by the median but not the dorsal raphe. One adverse effect was seen: the dorsal but not the median raphe reduced

Regime Behavior in Paleo-Reconstructed Streamflow: Attributions to Atmospheric Dynamics, Synoptic Circulation and Large-Scale Climate Teleconnection Patterns

NASA Astrophysics Data System (ADS)

Ravindranath, A.; Devineni, N.

2017-12-01

Studies have shown that streamflow behavior and dynamics have a significant link with climate and climate variability. Patterns of persistent regime behavior from extended streamflow records in many watersheds justify investigating large-scale climate mechanisms as potential drivers of hydrologic regime behavior and streamflow variability. Understanding such streamflow-climate relationships is crucial to forecasting/simulation systems and the planning and management of water resources. In this study, hidden Markov models are used with reconstructed streamflow to detect regime-like behaviors - the hidden states - and state transition phenomena. Individual extreme events and their spatial variability across the basin are then verified with the identified states. Wavelet analysis is performed to examine the signals over time in the streamflow records. Joint analyses of the climatic data in the 20th century and the identified states are undertaken to better understand the hydroclimatic connections within the basin as well as important teleconnections that influence water supply. Compositing techniques are used to identify atmospheric circulation patterns associated with identified states of streamflow. The grouping of such synoptic patterns and their frequency are then examined. Sliding time-window correlation analysis and cross-wavelet spectral analysis are performed to establish the synchronicity of basin flows to the identified synoptic and teleconnection patterns. The Missouri River Basin (MRB) is examined in this study, both as a means of better understanding the synoptic climate controls in this important watershed and as a case study for the techniques developed here. Initial wavelet analyses of reconstructed streamflow at major gauges in the MRB show multidecadal cycles in regime behavior.

Measuring the health effects of gender.

PubMed

Phillips, S P

2008-04-01

The health effects of gender are mediated via group-level constraints of sex roles and norms, discrimination and marginalisation of individuals, and internalisation of the stresses of role discordance. Although gender is frequently a lens through which data are interpreted there are few composite measures that insert gender as an independent variable into research design. Instead, sex disaggregation of data is often conflated with gender, identifying statistically significant but sometimes clinically insignificant sex differences. To directly assess the impact of gender on wellbeing requires development of group and individual-level derived variables. At the ecological level such a summative variable could be composed of a selection of group-level measures of equality between sexes. This gender index could be used in ecological and individual-level studies of health outcomes. A quantitative indicator of gender role acceptance and of the personal effects of gender inequities could insert the often hidden variable of gender into individual-level clinical research.

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.

Hidden Attractors in Dynamical Systems. From Hidden Oscillations in Hilbert-Kolmogorov Aizerman, and Kalman Problems to Hidden Chaotic Attractor in Chua Circuits

NASA Astrophysics Data System (ADS)

Leonov, G. A.; Kuznetsov, N. V.

From a computational point of view, in nonlinear dynamical systems, attractors can be regarded as self-excited and hidden attractors. Self-excited attractors can be localized numerically by a standard computational procedure, in which after a transient process a trajectory, starting from a point of unstable manifold in a neighborhood of equilibrium, reaches a state of oscillation, therefore one can easily identify it. In contrast, for a hidden attractor, a basin of attraction does not intersect with small neighborhoods of equilibria. While classical attractors are self-excited, attractors can therefore be obtained numerically by the standard computational procedure. For localization of hidden attractors it is necessary to develop special procedures, since there are no similar transient processes leading to such attractors. At first, the problem of investigating hidden oscillations arose in the second part of Hilbert's 16th problem (1900). The first nontrivial results were obtained in Bautin's works, which were devoted to constructing nested limit cycles in quadratic systems, that showed the necessity of studying hidden oscillations for solving this problem. Later, the problem of analyzing hidden oscillations arose from engineering problems in automatic control. In the 50-60s of the last century, the investigations of widely known Markus-Yamabe's, Aizerman's, and Kalman's conjectures on absolute stability have led to the finding of hidden oscillations in automatic control systems with a unique stable stationary point. In 1961, Gubar revealed a gap in Kapranov's work on phase locked-loops (PLL) and showed the possibility of the existence of hidden oscillations in PLL. At the end of the last century, the difficulties in analyzing hidden oscillations arose in simulations of drilling systems and aircraft's control systems (anti-windup) which caused crashes. Further investigations on hidden oscillations were greatly encouraged by the present authors' discovery, in 2010 (for the first time), of chaotic hidden attractor in Chua's circuit. This survey is dedicated to efficient analytical-numerical methods for the study of hidden oscillations. Here, an attempt is made to reflect the current trends in the synthesis of analytical and numerical methods.

Thermodynamic Modeling and Dispatch of Distributed Energy Technologies including Fuel Cell -- Gas Turbine Hybrids

NASA Astrophysics Data System (ADS)

McLarty, Dustin Fogle

Distributed energy systems are a promising means by which to reduce both emissions and costs. Continuous generators must be responsive and highly efficiency to support building dynamics and intermittent on-site renewable power. Fuel cell -- gas turbine hybrids (FC/GT) are fuel-flexible generators capable of ultra-high efficiency, ultra-low emissions, and rapid power response. This work undertakes a detailed study of the electrochemistry, chemistry and mechanical dynamics governing the complex interaction between the individual systems in such a highly coupled hybrid arrangement. The mechanisms leading to the compressor stall/surge phenomena are studied for the increased risk posed to particular hybrid configurations. A novel fuel cell modeling method introduced captures various spatial resolutions, flow geometries, stack configurations and novel heat transfer pathways. Several promising hybrid configurations are analyzed throughout the work and a sensitivity analysis of seven design parameters is conducted. A simple estimating method is introduced for the combined system efficiency of a fuel cell and a turbine using component performance specifications. Existing solid oxide fuel cell technology is capable of hybrid efficiencies greater than 75% (LHV) operating on natural gas, and existing molten carbonate systems greater than 70% (LHV). A dynamic model is calibrated to accurately capture the physical coupling of a FC/GT demonstrator tested at UC Irvine. The 2900 hour experiment highlighted the sensitivity to small perturbations and a need for additional control development. Further sensitivity studies outlined the responsiveness and limits of different control approaches. The capability for substantial turn-down and load following through speed control and flow bypass with minimal impact on internal fuel cell thermal distribution is particularly promising to meet local demands or provide dispatchable support for renewable power. Advanced control and dispatch heuristics are discussed using a case study of the UCI central plant. Thermal energy storage introduces a time horizon into the dispatch optimization which requires novel solution strategies. Highly efficient and responsive generators are required to meet the increasingly dynamic loads of today's efficient buildings and intermittent local renewable wind and solar power. Fuel cell gas turbine hybrids will play an integral role in the complex and ever-changing solution to local electricity production.

iHeartLift: a closed loop system with bio-feedback that uses music tempo variability to improve heart rate variability.

PubMed

Ho, Thomas C T; Chen, Xiang

2011-01-01

"Musica delenit bestiam feram" translates into "Music soothes the savage beast". There is a hidden truth in this ancient quip passed down from generations. Besides soothing the heart, it also incites the heart to a healthier level of heart rate variability (HRV). In this paper, an approach to use and test music and biofeedback to increase the heart rate variability for people facing daily stress is discussed. By determining the music tempo variability (MTV) of a piece of music and current heart rate variability, iHeartLift is able to compare the 2 trends and locate a musical piece that is suited to increase the user's heart rate variability to a healthier level. With biofeedback, the 2 trends are continuously compared in real-time and the musical piece is changed in accordance with the current comparisons. A study was conducted and it was generally found that HRV can be uplifted by music regardless of language and meaning of musical lyrics but with limitations to musical genre.

Variability in the combustion-derived fraction of urban humidity in Salt Lake City winter estimated from stable water vapor isotopes and its relationship to atmospheric stability and inversion structure

NASA Astrophysics Data System (ADS)

Fiorella, R.; Bares, R.; Lin, J. C.; Strong, C.; Bowen, G. J.

2017-12-01

Water released from the combustion of fossil fuels, while a negligible part of the global hydrological cycle, may be a significant contributor to urban humidity as fossil fuel emissions are strongly concentrated in space and time. The fraction of urban humidity comprised of combustion-derived vapor (CDV) cannot be observed through humidity measurements alone. However, the distinct stable isotopic composition of CDV, which arises from the reaction of 18O-enriched atmospheric O2 with 2H-depleted organic molecules, represents a promising method to apportion observed humidity between CDV and advected vapor. We apply stable water vapor isotopes to investigate variability in CDV amount and its relationship to atmospheric conditions in Salt Lake City, Utah. The Salt Lake Valley experiences several periods of atmospheric stratification during winter known as cold air pools, during which concentrations of CDV and pollutants can be markedly elevated due to reduced atmospheric mixing. Therefore, the SLV during winter is an ideal place to investigate variability in CDV fraction across a spectrum of boundary layer conditions, ranging from well-mixed to very stable. We present water vapor isotope data from four winters (2013-2017) from the top of a 30 m building on the University of Utah (U of U) Campus. Additionally, we present water vapor isotope data from the summit of Hidden Peak from the 2016-2017 winter, 25 km SE and 2000 m above the U of U site. The Hidden Peak site is consistently above the cold air pool emplaced in the SLV during stable events. We find the expression of the CDV signal in the valley is related to the atmospheric structure of the cold air pools in the SLV, and that the fraction of CDV inferred in the valley is likely related to the mixing height within the cold air pool. Furthermore, we find that patterns between the Hidden Peak and U of U sites during inversion events may record the large-scale atmospheric dynamics promoting emplacement of the cold air pool in the SLV. Further refinements of CDV estimation through stable isotope methods will bring improved mechanistic understanding of the role of CDV in the urban hydrological cycle and improve model simulations of urban environments.

Functional Neuronal Processing of Human Body Odors

PubMed Central

Lundström, Johan N.; Olsson, Mats J.

2013-01-01

Body odors carry informational cues of great importance for individuals across a wide range of species, and signals hidden within the body odor cocktail are known to regulate several key behaviors in animals. For a long time, the notion that humans may be among these species has been dismissed. We now know, however, that each human has a unique odor signature that carries information related to his or her genetic makeup, as well as information about personal environmental variables, such as diet and hygiene. Although a substantial number of studies have investigated the behavioral effects of body odors, only a handful have studied central processing. Recent studies have, however, demonstrated that the human brain responds to fear signals hidden within the body odor cocktail, is able to extract kin specific signals, and processes body odors differently than other perceptually similar odors. In this chapter, we provide an overview of the current knowledge of how the human brain processes body odors and the potential importance these signals have for us in everyday life. PMID:20831940

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

Hidden Markov Model-Based CNV Detection Algorithms for Illumina Genotyping Microarrays.

PubMed

Seiser, Eric L; Innocenti, Federico

2014-01-01

Somatic alterations in DNA copy number have been well studied in numerous malignancies, yet the role of germline DNA copy number variation in cancer is still emerging. Genotyping microarrays generate allele-specific signal intensities to determine genotype, but may also be used to infer DNA copy number using additional computational approaches. Numerous tools have been developed to analyze Illumina genotype microarray data for copy number variant (CNV) discovery, although commonly utilized algorithms freely available to the public employ approaches based upon the use of hidden Markov models (HMMs). QuantiSNP, PennCNV, and GenoCN utilize HMMs with six copy number states but vary in how transition and emission probabilities are calculated. Performance of these CNV detection algorithms has been shown to be variable between both genotyping platforms and data sets, although HMM approaches generally outperform other current methods. Low sensitivity is prevalent with HMM-based algorithms, suggesting the need for continued improvement in CNV detection methodologies.

Cross-modal learning to rank via latent joint representation.

PubMed

Wu, Fei; Jiang, Xinyang; Li, Xi; Tang, Siliang; Lu, Weiming; Zhang, Zhongfei; Zhuang, Yueting

2015-05-01

Cross-modal ranking is a research topic that is imperative to many applications involving multimodal data. Discovering a joint representation for multimodal data and learning a ranking function are essential in order to boost the cross-media retrieval (i.e., image-query-text or text-query-image). In this paper, we propose an approach to discover the latent joint representation of pairs of multimodal data (e.g., pairs of an image query and a text document) via a conditional random field and structural learning in a listwise ranking manner. We call this approach cross-modal learning to rank via latent joint representation (CML²R). In CML²R, the correlations between multimodal data are captured in terms of their sharing hidden variables (e.g., topics), and a hidden-topic-driven discriminative ranking function is learned in a listwise ranking manner. The experiments show that the proposed approach achieves a good performance in cross-media retrieval and meanwhile has the capability to learn the discriminative representation of multimodal data.

Quantum Computing since Democritus

NASA Astrophysics Data System (ADS)

Aaronson, Scott

2013-03-01

1. Atoms and the void; 2. Sets; 3. Gödel, Turing, and friends; 4. Minds and machines; 5. Paleocomplexity; 6. P, NP, and friends; 7. Randomness; 8. Crypto; 9. Quantum; 10. Quantum computing; 11. Penrose; 12. Decoherence and hidden variables; 13. Proofs; 14. How big are quantum states?; 15. Skepticism of quantum computing; 16. Learning; 17. Interactive proofs and more; 18. Fun with the Anthropic Principle; 19. Free will; 20. Time travel; 21. Cosmology and complexity; 22. Ask me anything.

A Viable Paradigm for Quantum Reality

NASA Astrophysics Data System (ADS)

Srivastava, Jagdish

2010-10-01

After a brief discussion of the EPR paradox, Bell's inequality, and Aspect's experiment, arguments will be presented in favor of the following statements: ``As it stands, Quantum mechanics is incomplete. There is further hidden structure, which would involve variables. No influence can move faster than light. The wave function is one whole thing and any change in its structure instantly influences its outcomes. Bell's theorem has not been applied correctly. There is a better paradigm.'' The said paradigm will be presented.

On the CHSH Form of Bell's Inequalities

NASA Astrophysics Data System (ADS)

Lambare, Justo Pastor

2017-03-01

A common mistake present in the derivation of the usually known as the CHSH form of Bell's inequalities is pointed out. References and comments to the correct approach are given. This error does not alter the final result and only affects the logical consistency of the derivation, but since it seems to be a widespread misconception regarding the roll and interpretation of the of use of hidden variables in Bell's theorem it is considered to be of general interest.

Inference for the Bivariate and Multivariate Hidden Truncated Pareto(type II) and Pareto(type IV) Distribution and Some Measures of Divergence Related to Incompatibility of Probability Distribution

ERIC Educational Resources Information Center

Ghosh, Indranil

2011-01-01

Consider a discrete bivariate random variable (X, Y) with possible values x[subscript 1], x[subscript 2],..., x[subscript I] for X and y[subscript 1], y[subscript 2],..., y[subscript J] for Y. Further suppose that the corresponding families of conditional distributions, for X given values of Y and of Y for given values of X are available. We…

Discriminative latent models for recognizing contextual group activities.

PubMed

Lan, Tian; Wang, Yang; Yang, Weilong; Robinovitch, Stephen N; Mori, Greg

2012-08-01

In this paper, we go beyond recognizing the actions of individuals and focus on group activities. This is motivated from the observation that human actions are rarely performed in isolation; the contextual information of what other people in the scene are doing provides a useful cue for understanding high-level activities. We propose a novel framework for recognizing group activities which jointly captures the group activity, the individual person actions, and the interactions among them. Two types of contextual information, group-person interaction and person-person interaction, are explored in a latent variable framework. In particular, we propose three different approaches to model the person-person interaction. One approach is to explore the structures of person-person interaction. Differently from most of the previous latent structured models, which assume a predefined structure for the hidden layer, e.g., a tree structure, we treat the structure of the hidden layer as a latent variable and implicitly infer it during learning and inference. The second approach explores person-person interaction in the feature level. We introduce a new feature representation called the action context (AC) descriptor. The AC descriptor encodes information about not only the action of an individual person in the video, but also the behavior of other people nearby. The third approach combines the above two. Our experimental results demonstrate the benefit of using contextual information for disambiguating group activities.

Discriminative Latent Models for Recognizing Contextual Group Activities

PubMed Central

Lan, Tian; Wang, Yang; Yang, Weilong; Robinovitch, Stephen N.; Mori, Greg

2012-01-01

In this paper, we go beyond recognizing the actions of individuals and focus on group activities. This is motivated from the observation that human actions are rarely performed in isolation; the contextual information of what other people in the scene are doing provides a useful cue for understanding high-level activities. We propose a novel framework for recognizing group activities which jointly captures the group activity, the individual person actions, and the interactions among them. Two types of contextual information, group-person interaction and person-person interaction, are explored in a latent variable framework. In particular, we propose three different approaches to model the person-person interaction. One approach is to explore the structures of person-person interaction. Differently from most of the previous latent structured models, which assume a predefined structure for the hidden layer, e.g., a tree structure, we treat the structure of the hidden layer as a latent variable and implicitly infer it during learning and inference. The second approach explores person-person interaction in the feature level. We introduce a new feature representation called the action context (AC) descriptor. The AC descriptor encodes information about not only the action of an individual person in the video, but also the behavior of other people nearby. The third approach combines the above two. Our experimental results demonstrate the benefit of using contextual information for disambiguating group activities. PMID:22144516

Experimental non-classicality of an indivisible quantum system.

PubMed

Lapkiewicz, Radek; Li, Peizhe; Schaeff, Christoph; Langford, Nathan K; Ramelow, Sven; Wieśniak, Marcin; Zeilinger, Anton

2011-06-22

In contrast to classical physics, quantum theory demands that not all properties can be simultaneously well defined; the Heisenberg uncertainty principle is a manifestation of this fact. Alternatives have been explored--notably theories relying on joint probability distributions or non-contextual hidden-variable models, in which the properties of a system are defined independently of their own measurement and any other measurements that are made. Various deep theoretical results imply that such theories are in conflict with quantum mechanics. Simpler cases demonstrating this conflict have been found and tested experimentally with pairs of quantum bits (qubits). Recently, an inequality satisfied by non-contextual hidden-variable models and violated by quantum mechanics for all states of two qubits was introduced and tested experimentally. A single three-state system (a qutrit) is the simplest system in which such a contradiction is possible; moreover, the contradiction cannot result from entanglement between subsystems, because such a three-state system is indivisible. Here we report an experiment with single photonic qutrits which provides evidence that no joint probability distribution describing the outcomes of all possible measurements--and, therefore, no non-contextual theory--can exist. Specifically, we observe a violation of the Bell-type inequality found by Klyachko, Can, Binicioğlu and Shumovsky. Our results illustrate a deep incompatibility between quantum mechanics and classical physics that cannot in any way result from entanglement.

Supervised artificial neural network-based method for conversion of solar radiation data (case study: Algeria)

NASA Astrophysics Data System (ADS)

Laidi, Maamar; Hanini, Salah; Rezrazi, Ahmed; Yaiche, Mohamed Redha; El Hadj, Abdallah Abdallah; Chellali, Farouk

2017-04-01

In this study, a backpropagation artificial neural network (BP-ANN) model is used as an alternative approach to predict solar radiation on tilted surfaces (SRT) using a number of variables involved in physical process. These variables are namely the latitude of the site, mean temperature and relative humidity, Linke turbidity factor and Angstrom coefficient, extraterrestrial solar radiation, solar radiation data measured on horizontal surfaces (SRH), and solar zenith angle. Experimental solar radiation data from 13 stations spread all over Algeria around the year (2004) were used for training/validation and testing the artificial neural networks (ANNs), and one station was used to make the interpolation of the designed ANN. The ANN model was trained, validated, and tested using 60, 20, and 20 % of all data, respectively. The configuration 8-35-1 (8 inputs, 35 hidden, and 1 output neurons) presented an excellent agreement between the prediction and the experimental data during the test stage with determination coefficient of 0.99 and root meat squared error of 5.75 Wh/m2, considering a three-layer feedforward backpropagation neural network with Levenberg-Marquardt training algorithm, a hyperbolic tangent sigmoid and linear transfer function at the hidden and the output layer, respectively. This novel model could be used by researchers or scientists to design high-efficiency solar devices that are usually tilted at an optimum angle to increase the solar incident on the surface.

Searching for Extragalactic Sources in the VISTA Variables in the Vía Láctea Survey

NASA Astrophysics Data System (ADS)

Baravalle, Laura D.; Alonso, M. Victoria; Nilo Castellón, José Luis; Beamín, Juan Carlos; Minniti, Dante

2018-01-01

We search for extragalactic sources in the VISTA Variables in the Vía Láctea survey that are hidden by the Galaxy. Herein, we describe our photometric procedure to find and characterize extragalactic objects using a combination of SExtractor and PSFEx. It was applied in two tiles of the survey: d010 and d115, without previous extragalactic IR detections, in order to obtain photometric parameters of the detected sources. The adopted criteria to define extragalactic candidates include CLASSSTAR< 0.3; 1.0 < R1/2< 5.0 arcsec; 2.1 < C < 5 and Φ > 0.002 and the colors: 0.5 < (J–K s ) < 2.0 mag; 0.0 < (J–H) < 1.0 mag; 0.0 < (H–K s ) < 2.0 mag and (J–H) + 0.9 (H–K s ) > 0.44 mag. We detected 345 and 185 extragalactic candidates in the d010 and d115 tiles, respectively. All of them were visually inspected and confirmed to be galaxies. In general, they are small and more circular objects, due to the near-IR sensitivity to select more compact objects with higher surface brightness. The procedure will be used to identify extragalactic objects in other tiles of the VVV disk, which will allow us to study the distribution of galaxies and filaments hidden by the Milky Way.

Sparse covariance estimation in heterogeneous samples*

PubMed Central

Rodríguez, Abel; Lenkoski, Alex; Dobra, Adrian

2015-01-01

Standard Gaussian graphical models implicitly assume that the conditional independence among variables is common to all observations in the sample. However, in practice, observations are usually collected from heterogeneous populations where such an assumption is not satisfied, leading in turn to nonlinear relationships among variables. To address such situations we explore mixtures of Gaussian graphical models; in particular, we consider both infinite mixtures and infinite hidden Markov models where the emission distributions correspond to Gaussian graphical models. Such models allow us to divide a heterogeneous population into homogenous groups, with each cluster having its own conditional independence structure. As an illustration, we study the trends in foreign exchange rate fluctuations in the pre-Euro era. PMID:26925189

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.

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…

Detecting faked continuous-variable entanglement using one-sided device-independent entanglement witnesses

NASA Astrophysics Data System (ADS)

Opanchuk, B.; Arnaud, L.; Reid, M. D.

2014-06-01

We demonstrate the principle of one-sided device-independent continuous-variable (CV) quantum information. In situations of no trust, we show by enactment how the use of standard CV entanglement criteria can mislead Charlie into thinking that Alice and Bob share entanglement, when the data are actually generated classically using a local-hidden-variable theory based on the Wigner function. We distinguish between criteria that demonstrate CV entanglement, and criteria that demonstrate the CV Einstein-Podolsky-Rosen (EPR) steering paradox. We show that the latter, but not the former, are necessarily one-sided device-independent entanglement witnesses, and can be used by Charlie to signify genuine EPR entanglement, if he trusts only Alice. A monogamy result for the EPR steering paradox confirms the security of the shared amplitude values in that case.

Entanglement and nonlocality in multi-particle systems

NASA Astrophysics Data System (ADS)

Reid, Margaret D.; He, Qiong-Yi; Drummond, Peter D.

2012-02-01

Entanglement, the Einstein-Podolsky-Rosen (EPR) paradox and Bell's failure of local-hiddenvariable (LHV) theories are three historically famous forms of "quantum nonlocality". We give experimental criteria for these three forms of nonlocality in multi-particle systems, with the aim of better understanding the transition from microscopic to macroscopic nonlocality. We examine the nonlocality of N separated spin J systems. First, we obtain multipartite Bell inequalities that address the correlation between spin values measured at each site, and then we review spin squeezing inequalities that address the degree of reduction in the variance of collective spins. The latter have been particularly useful as a tool for investigating entanglement in Bose-Einstein condensates (BEC). We present solutions for two topical quantum states: multi-qubit Greenberger-Horne-Zeilinger (GHZ) states, and the ground state of a two-well BEC.

Advanced energy system program

NASA Astrophysics Data System (ADS)

Trester, K.

1987-06-01

The ogjectives are to design, develop, and demonstrate a natural-gas-fueled, highly recuperated, 50 kw Brayton-cycle cogeneration system for commercial, institutional, and multifamily residential applications. Recent marketing studies have shown that the Advanced Energy System (AES), with its many cost-effective features, has the potential to offer significant reductions in annual electrical and thermal energy costs to the consumer. Specific advantates of the system that result in low cost ownership are high electrical efficiency (34 percent, LHV), low maintenance, high reliability and long life (20 years). Significant technical features include: an integral turbogenerator with shaft-speed permanent magnet generator; a rotating assembly supported by compliant foil air bearings; a formed-tubesheet plate/fin recuperator with 91 percent effectiveness; and a bi-directional power conditioner to ultilize the generator for system startup. The planned introduction of catalytic combustion will further enhance the economic and ecological attractiveness.

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.

An hourly variation in zoo visitor interest: measurement and significance for animal welfare research.

PubMed

Davey, Gareth

2006-01-01

A methodological difficulty facing welfare research on nonhuman animals in the zoo is the large number of uncontrolled variables due to variation within and between study sites. Zoo visitors act as uncontrolled variables, with number, density, size, and behavior constantly changing. This is worrisome because previous research linked visitor variables to animal behavioral changes indicative of stress. There are implications for research design: Studies not accounting for visitors' effect on animal welfare risk confounding (visitor) variables distorting their findings. Zoos need methods to measure and minimize effects of visitor behavior and to ensure that there are no hidden variables in research models. This article identifies a previously unreported variable--hourly variation (decrease) in visitor interest--that may impinge on animal welfare and validates a methodology for measuring it. That visitor interest wanes across the course of the day has important implications for animal welfare management; visitor effects on animal welfare are likely to occur, or intensify, during the morning or in earlier visits when visitor interest is greatest. This article discusses this issue and possible solutions to reduce visitor effects on animal well-being.

Neural Network Burst Pressure Prediction in Graphite/Epoxy Pressure Vessels from Acoustic Emission Amplitude Data

NASA Technical Reports Server (NTRS)

Hill, Eric v. K.; Walker, James L., II; Rowell, Ginger H.

1995-01-01

Acoustic emission (AE) data were taken during hydroproof for three sets of ASTM standard 5.75 inch diameter filament wound graphite/epoxy bottles. All three sets of bottles had the same design and were wound from the same graphite fiber; the only difference was in the epoxies used. Two of the epoxies had similar mechanical properties, and because the acoustic properties of materials are a function of their stiffnesses, it was thought that the AE data from the two sets might also be similar; however, this was not the case. Therefore, the three resin types were categorized using dummy variables, which allowed the prediction of burst pressures all three sets of bottles using a single neural network. Three bottles from each set were used to train the network. The resin category, the AE amplitude distribution data taken up to 25 % of the expected burst pressure, and the actual burst pressures were used as inputs. Architecturally, the network consisted of a forty-three neuron input layer (a single categorical variable defining the resin type plus forty-two continuous variables for the AE amplitude frequencies), a fifteen neuron hidden layer for mapping, and a single output neuron for burst pressure prediction. The network trained on all three bottle sets was able to predict burst pressures in the remaining bottles with a worst case error of + 6.59%, slightly greater than the desired goal of + 5%. This larger than desired error was due to poor resolution in the amplitude data for the third bottle set. When the third set of bottles was eliminated from consideration, only four hidden layer neurons were necessary to generate a worst case prediction error of - 3.43%, well within the desired goal.

--No Title--

Science.gov Websites

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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.

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.

Anomalous neural circuit function in schizophrenia during a virtual Morris water task.

PubMed

Folley, Bradley S; Astur, Robert; Jagannathan, Kanchana; Calhoun, Vince D; Pearlson, Godfrey D

2010-02-15

Previous studies have reported learning and navigation impairments in schizophrenia patients during virtual reality allocentric learning tasks. The neural bases of these deficits have not been explored using functional MRI despite well-explored anatomic characterization of these paradigms in non-human animals. Our objective was to characterize the differential distributed neural circuits involved in virtual Morris water task performance using independent component analysis (ICA) in schizophrenia patients and controls. Additionally, we present behavioral data in order to derive relationships between brain function and performance, and we have included a general linear model-based analysis in order to exemplify the incremental and differential results afforded by ICA. Thirty-four individuals with schizophrenia and twenty-eight healthy controls underwent fMRI scanning during a block design virtual Morris water task using hidden and visible platform conditions. Independent components analysis was used to deconstruct neural contributions to hidden and visible platform conditions for patients and controls. We also examined performance variables, voxel-based morphometry and hippocampal subparcellation, and regional BOLD signal variation. Independent component analysis identified five neural circuits. Mesial temporal lobe regions, including the hippocampus, were consistently task-related across conditions and groups. Frontal, striatal, and parietal circuits were recruited preferentially during the visible condition for patients, while frontal and temporal lobe regions were more saliently recruited by controls during the hidden platform condition. Gray matter concentrations and BOLD signal in hippocampal subregions were associated with task performance in controls but not patients. Patients exhibited impaired performance on the hidden and visible conditions of the task, related to negative symptom severity. While controls showed coupling between neural circuits, regional neuroanatomy, and behavior, patients activated different task-related neural circuits, not associated with appropriate regional neuroanatomy. GLM analysis elucidated several comparable regions, with the exception of the hippocampus. Inefficient allocentric learning and memory in patients may be related to an inability to recruit appropriate task-dependent neural circuits. Copyright 2009 Elsevier Inc. All rights reserved.

Geophysical Investigations at Hidden Dam, Raymond, California Flow Simulations

USGS Publications Warehouse

Minsley, Burke J.; Ikard, Scott

2010-01-01

Numerical flow modeling and analysis of observation-well data at Hidden Dam are carried out to supplement recent geophysical field investigations at the site (Minsley and others, 2010). This work also is complementary to earlier seepage-related studies at Hidden Dam documented by Cedergren (1980a, b). Known seepage areas on the northwest right abutment area of the downstream side of the dam was documented by Cedergren (1980a, b). Subsequent to the 1980 seepage study, a drainage blanket with a sub-drain system was installed to mitigate downstream seepage. Flow net analysis provided by Cedergren (1980a, b) suggests that the primary seepage mechanism involves flow through the dam foundation due to normal reservoir pool elevations, which results in upflow that intersects the ground surface in several areas on the downstream side of the dam. In addition to the reservoir pool elevations and downstream surface topography, flow is also controlled by the existing foundation geology as well as the presence or absence of a horizontal drain in the downstream portion of the dam. The current modeling study is aimed at quantifying how variability in dam and foundation hydrologic properties influences seepage as a function of reservoir stage. Flow modeling is implemented using the COMSOL Multiphysics software package, which solves the partially saturated flow equations in a two-dimensional (2D) cross-section of Hidden Dam that also incorporates true downstream topography. Use of the COMSOL software package provides a more quantitative approach than the flow net analysis by Cedergren (1980a, b), and allows for rapid evaluation of the influence of various parameters such as reservoir level, dam structure and geometry, and hydrogeologic properties of the dam and foundation materials. Historical observation-well data are used to help validate the flow simulations by comparing observed and predicted water levels for a range of reservoir elevations. The flow models are guided by, and discussed in the context of, the geophysical work (Minsley and others, 2010) where appropriate.

Two-player quantum pseudotelepathy based on recent all-versus-nothing violations of local realism

NASA Astrophysics Data System (ADS)

Cabello, Adán

2006-02-01

We introduce two two-player quantum pseudotelepathy games based on two recently proposed all-versus-nothing (AVN) proofs of Bell’s theorem [A. Cabello, Phys. Rev. Lett. 95, 210401 (2005); Phys. Rev. A 72, 050101(R) (2005)]. These games prove that Broadbent and Méthot’s claim that these AVN proofs do not rule out local-hidden-variable theories in which it is possible to exchange unlimited information inside the same light cone (quant-ph/0511047) is incorrect.

Prognosis of Electrical Faults in Permanent Magnet AC Machines using the Hidden Markov Model

DTIC Science & Technology

2010-11-10

time resolution and high frequency resolution Tiling is variable Wigner Ville Distribution Defined as W (t, ω) = ∫ s(t + τ 2 )s∗(t − τ 2 )e−jωτdτ...smoothed version of the Wigner distribution Amount of smoothing is controlled by σ Smoothing comes with a tradeoff of reduced resolution UNCLAS: Dist A...the Wigner or Choi-Williams distributions Although for Wigner and Choi-Williams distributions the probabilities are close for the early fault

Extracting volatility signal using maximum a posteriori estimation

NASA Astrophysics Data System (ADS)

Neto, David

2016-11-01

This paper outlines a methodology to estimate a denoised volatility signal for foreign exchange rates using a hidden Markov model (HMM). For this purpose a maximum a posteriori (MAP) estimation is performed. A double exponential prior is used for the state variable (the log-volatility) in order to allow sharp jumps in realizations and then log-returns marginal distributions with heavy tails. We consider two routes to choose the regularization and we compare our MAP estimate to realized volatility measure for three exchange rates.

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

"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

Evaluating disease management programme effectiveness: an introduction to instrumental variables.

PubMed

Linden, Ariel; Adams, John L

2006-04-01

This paper introduces the concept of instrumental variables (IVs) as a means of providing an unbiased estimate of treatment effects in evaluating disease management (DM) programme effectiveness. Model development is described using zip codes as the IV. Three diabetes DM outcomes were evaluated: annual diabetes costs, emergency department (ED) visits and hospital days. Both ordinary least squares (OLS) and IV estimates showed a significant treatment effect for diabetes costs (P = 0.011) but neither model produced a significant treatment effect for ED visits. However, the IV estimate showed a significant treatment effect for hospital days (P = 0.006) whereas the OLS model did not. These results illustrate the utility of IV estimation when the OLS model is sensitive to the confounding effect of hidden bias.

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.

Characterization of computer network events through simultaneous feature selection and clustering of intrusion alerts

NASA Astrophysics Data System (ADS)

Chen, Siyue; Leung, Henry; Dondo, Maxwell

2014-05-01

As computer network security threats increase, many organizations implement multiple Network Intrusion Detection Systems (NIDS) to maximize the likelihood of intrusion detection and provide a comprehensive understanding of intrusion activities. However, NIDS trigger a massive number of alerts on a daily basis. This can be overwhelming for computer network security analysts since it is a slow and tedious process to manually analyse each alert produced. Thus, automated and intelligent clustering of alerts is important to reveal the structural correlation of events by grouping alerts with common features. As the nature of computer network attacks, and therefore alerts, is not known in advance, unsupervised alert clustering is a promising approach to achieve this goal. We propose a joint optimization technique for feature selection and clustering to aggregate similar alerts and to reduce the number of alerts that analysts have to handle individually. More precisely, each identified feature is assigned a binary value, which reflects the feature's saliency. This value is treated as a hidden variable and incorporated into a likelihood function for clustering. Since computing the optimal solution of the likelihood function directly is analytically intractable, we use the Expectation-Maximisation (EM) algorithm to iteratively update the hidden variable and use it to maximize the expected likelihood. Our empirical results, using a labelled Defense Advanced Research Projects Agency (DARPA) 2000 reference dataset, show that the proposed method gives better results than the EM clustering without feature selection in terms of the clustering accuracy.

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.

Application of biomass pyrolytic polygeneration technology using retort reactors.

PubMed

Yang, Haiping; Liu, Biao; Chen, Yingquan; Chen, Wei; Yang, Qing; Chen, Hanping

2016-01-01

To introduce application status and illustrate the good utilisation potential of biomass pyrolytic polygeneration using retort reactors, the properties of major products and the economic viability of commercial factories were investigated. The capacity of one factory was about 3000t of biomass per year, which was converted into 1000t of charcoal, 950,000Nm(3) of biogas, 270t of woody tar, and 950t of woody vinegar. Charcoal and fuel gas had LHV of 31MJ/kg and 12MJ/m(3), respectively, indicating their potential for use as commercial fuels. The woody tar was rich in phenols, while woody vinegar contained large quantities of water and acetic acid. The economic analysis showed that the factory using this technology could be profitable, and the initial investment could be recouped over the factory lifetime. This technology offered a promising means of converting abundant agricultural biomass into high-value products. Copyright © 2015 Elsevier Ltd. All rights reserved.

Lassa fever or lassa hemorrhagic fever risk to humans from rodent-borne zoonoses.

PubMed

El-Bahnasawy, Mamdouh M; Megahed, Laila Abdel-Mawla; Abdalla Saleh, Hala Ahmed; Morsy, Tosson A

2015-04-01

Viral hemorrhagic fevers (VHFs) typically manifest as rapidly progressing acute febrile syndromes with profound hemorrhagic manifestations and very high fatality rates. Lassa fever, an acute hemorrhagic fever characterized by fever, muscle aches, sore throat, nausea, vomiting, diarrhea and chest and abdominal pain. Rodents are important reservoirs of rodent-borne zoonosis worldwide. Transmission rodents to humans occur by aerosol spread, either from the genus Mastomys rodents' excreta (multimammate rat) or through the close contact with infected patients (nosocomial infection). Other rodents of the genera Rattus, Mus, Lemniscomys, and Praomys are incriminated rodents hosts. Now one may ask do the rodents' ectoparasites play a role in Lassa virus zoonotic transmission. This paper summarized the update knowledge on LHV; hopping it might be useful to the clinicians, nursing staff, laboratories' personals as well as those concerned zoonoses from rodents and rodent control.

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

Functional neuronal processing of human body odors.

PubMed

Lundström, Johan N; Olsson, Mats J

2010-01-01

Body odors carry informational cues of great importance for individuals across a wide range of species, and signals hidden within the body odor cocktail are known to regulate several key behaviors in animals. For a long time, the notion that humans may be among these species has been dismissed. We now know, however, that each human has a unique odor signature that carries information related to his or her genetic makeup, as well as information about personal environmental variables, such as diet and hygiene. Although a substantial number of studies have investigated the behavioral effects of body odors, only a handful have studied central processing. Recent studies have, however, demonstrated that the human brain responds to fear signals hidden within the body odor cocktail, is able to extract kin specific signals, and processes body odors differently than other perceptually similar odors. In this chapter, we provide an overview of the current knowledge of how the human brain processes body odors and the potential importance these signals have for us in everyday life. Copyright © 2010 Elsevier Inc. All rights reserved.

Hidden complexity of free energy surfaces for peptide (protein) folding.

PubMed

Krivov, Sergei V; Karplus, Martin

2004-10-12

An understanding of the thermodynamics and kinetics of protein folding requires a knowledge of the free energy surface governing the motion of the polypeptide chain. Because of the many degrees of freedom involved, surfaces projected on only one or two progress variables are generally used in descriptions of the folding reaction. Such projections result in relatively smooth surfaces, but they could mask the complexity of the unprojected surface. Here we introduce an approach to determine the actual (unprojected) free energy surface and apply it to the second beta-hairpin of protein G, which has been used as a model system for protein folding. The surface is represented by a disconnectivity graph calculated from a long equilibrium folding-unfolding trajectory. The denatured state is found to have multiple low free energy basins. Nevertheless, the peptide shows exponential kinetics in folding to the native basin. Projected surfaces obtained from the present analysis have a simple form in agreement with other studies of the beta-hairpin. The hidden complexity found for the beta-hairpin surface suggests that the standard funnel picture of protein folding should be revisited.

Modeling Protein Expression and Protein Signaling Pathways

PubMed Central

Telesca, Donatello; Müller, Peter; Kornblau, Steven M.; Suchard, Marc A.; Ji, Yuan

2015-01-01

High-throughput functional proteomic technologies provide a way to quantify the expression of proteins of interest. Statistical inference centers on identifying the activation state of proteins and their patterns of molecular interaction formalized as dependence structure. Inference on dependence structure is particularly important when proteins are selected because they are part of a common molecular pathway. In that case, inference on dependence structure reveals properties of the underlying pathway. We propose a probability model that represents molecular interactions at the level of hidden binary latent variables that can be interpreted as indicators for active versus inactive states of the proteins. The proposed approach exploits available expert knowledge about the target pathway to define an informative prior on the hidden conditional dependence structure. An important feature of this prior is that it provides an instrument to explicitly anchor the model space to a set of interactions of interest, favoring a local search approach to model determination. We apply our model to reverse-phase protein array data from a study on acute myeloid leukemia. Our inference identifies relevant subpathways in relation to the unfolding of the biological process under study. PMID:26246646

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

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.

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.

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.

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.

On the genre-fication of music: a percolation approach

NASA Astrophysics Data System (ADS)

Lambiotte, R.; Ausloos, M.

2006-03-01

We analyze web-downloaded data on people sharing their music library. By attributing to each music group usual music genres (Rock, Pop ...), and analysing correlations between music groups of different genres with percolation-idea based methods, we probe the reality of these subdivisions and construct a music genre cartography, with a tree representation. We also discuss an alternative objective way to classify music, that is based on the complex structure of the groups audience. Finally, a link is drawn with the theory of hidden variables in complex networks.

Foot anthropometry and morphology phenomena.

PubMed

Agić, Ante; Nikolić, Vasilije; Mijović, Budimir

2006-12-01

Foot structure description is important for many reasons. The foot anthropometric morphology phenomena are analyzed together with hidden biomechanical functionality in order to fully characterize foot structure and function. For younger Croatian population the scatter data of the individual foot variables were interpolated by multivariate statistics. Foot structure descriptors are influenced by many factors, as a style of life, race, climate, and things of the great importance in human society. Dominant descriptors are determined by principal component analysis. Some practical recommendation and conclusion for medical, sportswear and footwear practice are highlighted.

Quantum States and Generalized Observables: A Simple Proof of Gleason's Theorem

NASA Astrophysics Data System (ADS)

Busch, P.

2003-09-01

A quantum state can be understood in a loose sense as a map that assigns a value to every observable. Formalizing this characterization of states in terms of generalized probability distributions on the set of effects, we obtain a simple proof of the result, analogous to Gleason’s theorem, that any quantum state is given by a density operator. As a corollary we obtain a vonNeumann type argument against noncontextual hidden variables. It follows that on an individual interpretation of quantum mechanics the values of effects are appropriately understood as propensities.

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

Krtous, Pavel; Frolov, Valeri P.; Kubiznak, David

We prove that the most general solution of the Einstein equations with the cosmological constant which admits a principal conformal Killing-Yano tensor is the Kerr-NUT-(A)dS metric. Even when the Einstein equations are not imposed, any spacetime admitting such hidden symmetry can be written in a canonical form which guarantees the following properties: it is of the Petrov type D, it allows the separation of variables for the Hamilton-Jacobi, Klein-Gordon, and Dirac equations, the geodesic motion in such a spacetime is completely integrable. These results naturally generalize the results obtained earlier in four dimensions.

Equivalence between contextuality and negativity of the Wigner function for qudits

NASA Astrophysics Data System (ADS)

Delfosse, Nicolas; Okay, Cihan; Bermejo-Vega, Juan; Browne, Dan E.; Raussendorf, Robert

2017-12-01

Understanding what distinguishes quantum mechanics from classical mechanics is crucial for quantum information processing applications. In this work, we consider two notions of non-classicality for quantum systems, negativity of the Wigner function and contextuality for Pauli measurements. We prove that these two notions are equivalent for multi-qudit systems with odd local dimension. For a single qudit, the equivalence breaks down. We show that there exist single qudit states that admit a non-contextual hidden variable model description and whose Wigner functions are negative.

Space Radar Image of the Lost City of Ubar

NASA Image and Video Library

1999-01-27

This is a radar image of the region around the site of the lost city of Ubar in southern Oman, on the Arabian Peninsula. The ancient city was discovered in 1992 with the aid of remote sensing data. Archeologists believe Ubar existed from about 2800 B.C. to about 300 A.D. and was a remote desert outpost where caravans were assembled for the transport of frankincense across the desert. This image was acquired on orbit 65 of space shuttle Endeavour on April 13, 1994 by the Spaceborne Imaging Radar C/X-Band Synthetic Aperture Radar (SIR-C/X-SAR). The SIR-C image shown is centered at 18.4 degrees north latitude and 53.6 degrees east longitude. The image covers an area about 50 by 100 kilometers (31 miles by 62 miles). The image is constructed from three of the available SIR-C channels and displays L-band, HH (horizontal transmit and receive) data as red, C-band HH as blue, and L-band HV (horizontal transmit, vertical receive) as green. The prominent magenta colored area is a region of large sand dunes, which are bright reflectors at both L-and C-band. The prominent green areas (L-HV) are rough limestone rocks, which form a rocky desert floor. A major wadi, or dry stream bed, runs across the middle of the image and is shown largely in white due to strong radar scattering in all channels displayed (L and C HH, L-HV). The actual site of the fortress of the lost city of Ubar, currently under excavation, is near the Wadi close to the center of the image. The fortress is too small to be detected in this image. However, tracks leading to the site, and surrounding tracks, appear as prominent, but diffuse, reddish streaks. These tracks have been used in modern times, but field investigations show many of these tracks were in use in ancient times as well. Mapping of these tracks on regional remote sensing images was a key to recognizing the site as Ubar in 1992. This image, and ongoing field investigations, will help shed light on a little known early civilization. http://photojournal.jpl.nasa.gov/catalog/PIA01721

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

Modeling the contributions of global air temperature, synoptic-scale phenomena and soil moisture to near-surface static energy variability using artificial neural networks

NASA Astrophysics Data System (ADS)

Pryor, Sara C.; Sullivan, Ryan C.; Schoof, Justin T.

2017-12-01

The static energy content of the atmosphere is increasing on a global scale, but exhibits important subglobal and subregional scales of variability and is a useful parameter for integrating the net effect of changes in the partitioning of energy at the surface and for improving understanding of the causes of so-called warming holes (i.e., locations with decreasing daily maximum air temperatures (T) or increasing trends of lower magnitude than the global mean). Further, measures of the static energy content (herein the equivalent potential temperature, θe) are more strongly linked to excess human mortality and morbidity than air temperature alone, and have great relevance in understanding causes of past heat-related excess mortality and making projections of possible future events that are likely to be associated with negative human health and economic consequences. New nonlinear statistical models for summertime daily maximum and minimum θe are developed and used to advance understanding of drivers of historical change and variability over the eastern USA. The predictor variables are an index of the daily global mean temperature, daily indices of the synoptic-scale meteorology derived from T and specific humidity (Q) at 850 and 500 hPa geopotential heights (Z), and spatiotemporally averaged soil moisture (SM). SM is particularly important in determining the magnitude of θe over regions that have previously been identified as exhibiting warming holes, confirming the key importance of SM in dictating the partitioning of net radiation into sensible and latent heat and dictating trends in near-surface T and θe. Consistent with our a priori expectations, models built using artificial neural networks (ANNs) out-perform linear models that do not permit interaction of the predictor variables (global T, synoptic-scale meteorological conditions and SM). This is particularly marked in regions with high variability in minimum and maximum θe, where more complex models built using ANN with multiple hidden layers are better able to capture the day-to-day variability in θe and the occurrence of extreme maximum θe. Over the entire domain, the ANN with three hidden layers exhibits high accuracy in predicting maximum θe > 347 K. The median hit rate for maximum θe > 347 K is > 0.60, while the median false alarm rate is ≈ 0.08.

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.

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.

A Self-Organizing Incremental Spatiotemporal Associative Memory Networks Model for Problems with Hidden State

PubMed Central

2016-01-01

Identifying the hidden state is important for solving problems with hidden state. We prove any deterministic partially observable Markov decision processes (POMDP) can be represented by a minimal, looping hidden state transition model and propose a heuristic state transition model constructing algorithm. A new spatiotemporal associative memory network (STAMN) is proposed to realize the minimal, looping hidden state transition model. STAMN utilizes the neuroactivity decay to realize the short-term memory, connection weights between different nodes to represent long-term memory, presynaptic potentials, and synchronized activation mechanism to complete identifying and recalling simultaneously. Finally, we give the empirical illustrations of the STAMN and compare the performance of the STAMN model with that of other methods. PMID:27891146

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.

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.

Final Technical Report for "Collaborative Research: Regional climate-change projections through next-generation empirical and dynamical models"

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

Robertson, A.W.; Ghil, M.; Kravtsov, K.

2011-04-08

This project was a continuation of previous work under DOE CCPP funding in which we developed a twin approach of non-homogeneous hidden Markov models (NHMMs) and coupled ocean-atmosphere (O-A) intermediate-complexity models (ICMs) to identify the potentially predictable modes of climate variability, and to investigate their impacts on the regional-scale. We have developed a family of latent-variable NHMMs to simulate historical records of daily rainfall, and used them to downscale seasonal predictions. We have also developed empirical mode reduction (EMR) models for gaining insight into the underlying dynamics in observational data and general circulation model (GCM) simulations. Using coupled O-A ICMs,more » we have identified a new mechanism of interdecadal climate variability, involving the midlatitude oceans mesoscale eddy field and nonlinear, persistent atmospheric response to the oceanic anomalies. A related decadal mode is also identified, associated with the oceans thermohaline circulation. The goal of the continuation was to build on these ICM results and NHMM/EMR model developments and software to strengthen two key pillars of support for the development and application of climate models for climate change projections on time scales of decades to centuries, namely: (a) dynamical and theoretical understanding of decadal-to-interdecadal oscillations and their predictability; and (b) an interface from climate models to applications, in order to inform societal adaptation strategies to climate change at the regional scale, including model calibration, correction, downscaling and, most importantly, assessment and interpretation of spread and uncertainties in multi-model ensembles. Our main results from the grant consist of extensive further development of the hidden Markov models for rainfall simulation and downscaling specifically within the non-stationary climate change context together with the development of parallelized software; application of NHMMs to downscaling of rainfall projections over India; identification and analysis of decadal climate signals in data and models; and, studies of climate variability in terms of the dynamics of atmospheric flow regimes. Each of these project components is elaborated on below, followed by a list of publications resulting from the grant.« less

Final Technical Report for "Collaborative Research. Regional climate-change projections through next-generation empirical and dynamical models"

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

Kravtsov, S.; Robertson, Andrew W.; Ghil, Michael

2011-04-08

This project was a continuation of previous work under DOE CCPP funding in which we developed a twin approach of non-homogeneous hidden Markov models (NHMMs) and coupled ocean-atmosphere (O-A) intermediate-complexity models (ICMs) to identify the potentially predictable modes of climate variability, and to investigate their impacts on the regional-scale. We have developed a family of latent-variable NHMMs to simulate historical records of daily rainfall, and used them to downscale seasonal predictions. We have also developed empirical mode reduction (EMR) models for gaining insight into the underlying dynamics in observational data and general circulation model (GCM) simulations. Using coupled O-A ICMs,more » we have identified a new mechanism of interdecadal climate variability, involving the midlatitude oceans mesoscale eddy field and nonlinear, persistent atmospheric response to the oceanic anomalies. A related decadal mode is also identified, associated with the oceans thermohaline circulation. The goal of the continuation was to build on these ICM results and NHMM/EMR model developments and software to strengthen two key pillars of support for the development and application of climate models for climate change projections on time scales of decades to centuries, namely: (a) dynamical and theoretical understanding of decadal-to-interdecadal oscillations and their predictability; and (b) an interface from climate models to applications, in order to inform societal adaptation strategies to climate change at the regional scale, including model calibration, correction, downscaling and, most importantly, assessment and interpretation of spread and uncertainties in multi-model ensembles. Our main results from the grant consist of extensive further development of the hidden Markov models for rainfall simulation and downscaling specifically within the non-stationary climate change context together with the development of parallelized software; application of NHMMs to downscaling of rainfall projections over India; identification and analysis of decadal climate signals in data and models; and, studies of climate variability in terms of the dynamics of atmospheric flow regimes. Each of these project components is elaborated on below, followed by a list of publications resulting from the grant.« less

A multiple-alignment based primer design algorithm for genetically highly variable DNA targets

PubMed Central

2013-01-01

Background Primer design for highly variable DNA sequences is difficult, and experimental success requires attention to many interacting constraints. The advent of next-generation sequencing methods allows the investigation of rare variants otherwise hidden deep in large populations, but requires attention to population diversity and primer localization in relatively conserved regions, in addition to recognized constraints typically considered in primer design. Results Design constraints include degenerate sites to maximize population coverage, matching of melting temperatures, optimizing de novo sequence length, finding optimal bio-barcodes to allow efficient downstream analyses, and minimizing risk of dimerization. To facilitate primer design addressing these and other constraints, we created a novel computer program (PrimerDesign) that automates this complex procedure. We show its powers and limitations and give examples of successful designs for the analysis of HIV-1 populations. Conclusions PrimerDesign is useful for researchers who want to design DNA primers and probes for analyzing highly variable DNA populations. It can be used to design primers for PCR, RT-PCR, Sanger sequencing, next-generation sequencing, and other experimental protocols targeting highly variable DNA samples. PMID:23965160

A constraint-based evolutionary learning approach to the expectation maximization for optimal estimation of the hidden Markov model for speech signal modeling.

PubMed

Huda, Shamsul; Yearwood, John; Togneri, Roberto

2009-02-01

This paper attempts to overcome the tendency of the expectation-maximization (EM) algorithm to locate a local rather than global maximum when applied to estimate the hidden Markov model (HMM) parameters in speech signal modeling. We propose a hybrid algorithm for estimation of the HMM in automatic speech recognition (ASR) using a constraint-based evolutionary algorithm (EA) and EM, the CEL-EM. The novelty of our hybrid algorithm (CEL-EM) is that it is applicable for estimation of the constraint-based models with many constraints and large numbers of parameters (which use EM) like HMM. Two constraint-based versions of the CEL-EM with different fusion strategies have been proposed using a constraint-based EA and the EM for better estimation of HMM in ASR. The first one uses a traditional constraint-handling mechanism of EA. The other version transforms a constrained optimization problem into an unconstrained problem using Lagrange multipliers. Fusion strategies for the CEL-EM use a staged-fusion approach where EM has been plugged with the EA periodically after the execution of EA for a specific period of time to maintain the global sampling capabilities of EA in the hybrid algorithm. A variable initialization approach (VIA) has been proposed using a variable segmentation to provide a better initialization for EA in the CEL-EM. Experimental results on the TIMIT speech corpus show that CEL-EM obtains higher recognition accuracies than the traditional EM algorithm as well as a top-standard EM (VIA-EM, constructed by applying the VIA to EM).

Data-Driven Model Uncertainty Estimation in Hydrologic Data Assimilation

NASA Astrophysics Data System (ADS)

Pathiraja, S.; Moradkhani, H.; Marshall, L.; Sharma, A.; Geenens, G.

2018-02-01

The increasing availability of earth observations necessitates mathematical methods to optimally combine such data with hydrologic models. Several algorithms exist for such purposes, under the umbrella of data assimilation (DA). However, DA methods are often applied in a suboptimal fashion for complex real-world problems, due largely to several practical implementation issues. One such issue is error characterization, which is known to be critical for a successful assimilation. Mischaracterized errors lead to suboptimal forecasts, and in the worst case, to degraded estimates even compared to the no assimilation case. Model uncertainty characterization has received little attention relative to other aspects of DA science. Traditional methods rely on subjective, ad hoc tuning factors or parametric distribution assumptions that may not always be applicable. We propose a novel data-driven approach (named SDMU) to model uncertainty characterization for DA studies where (1) the system states are partially observed and (2) minimal prior knowledge of the model error processes is available, except that the errors display state dependence. It includes an approach for estimating the uncertainty in hidden model states, with the end goal of improving predictions of observed variables. The SDMU is therefore suited to DA studies where the observed variables are of primary interest. Its efficacy is demonstrated through a synthetic case study with low-dimensional chaotic dynamics and a real hydrologic experiment for one-day-ahead streamflow forecasting. In both experiments, the proposed method leads to substantial improvements in the hidden states and observed system outputs over a standard method involving perturbation with Gaussian noise.

Preserving entanglement during weak measurement demonstrated with a violation of the Bell-Leggett-Garg inequality

NASA Astrophysics Data System (ADS)

White, Theodore C.

Quantum mechanics makes many predictions, such as superposition, projective measurement, and entanglement, which defy classical intuition. For many years it remained unclear if these predictions were real physical phenomena, or the result of an incomplete understanding of hidden classical variables. For quantum entanglement, the Bell inequality provided the first experimental bound on such hidden variable theories by considering correlated measurements between spatially separated photons. Following a similar logic, the Leggett-Garg inequality provides an experimental test of projective measurement by correlating sequential measurements of the same object. More recently, these inequalities have become important benchmarks for the "quantumness'' of novel systems, measurement techniques, or methods of generating entanglement. In this work we describe a continuous and controlled exchange of extracted state information and two-qubit entanglement collapse, demonstrated using the hybrid Bell-Leggett-Garg inequality. This effect is quantified by correlating weak measurement results with subsequent projective readout to collect all the statistics of a Bell inequality experiment in a single quantum circuit. This result was made possible by technological advances in superconducting quantum processors which allow precise control and measurement in multi-qubit systems. Additionally we discuss the central role of superconducting Josephson parametric amplifiers, which are a requirement for high fidelity single shot qubit readout. We demonstrate the ability to measure average Bell state information with minimal entanglement collapse, by violating this hybrid Bell-Leggett-Garg inequality at the weakest measurement strengths. This result indicates that it is possible to learn about the dynamics of large entangled systems without significantly affecting their evolution.

Adaptive sampling in behavioral surveys.

PubMed

Thompson, S K

1997-01-01

Studies of populations such as drug users encounter difficulties because the members of the populations are rare, hidden, or hard to reach. Conventionally designed large-scale surveys detect relatively few members of the populations so that estimates of population characteristics have high uncertainty. Ethnographic studies, on the other hand, reach suitable numbers of individuals only through the use of link-tracing, chain referral, or snowball sampling procedures that often leave the investigators unable to make inferences from their sample to the hidden population as a whole. In adaptive sampling, the procedure for selecting people or other units to be in the sample depends on variables of interest observed during the survey, so the design adapts to the population as encountered. For example, when self-reported drug use is found among members of the sample, sampling effort may be increased in nearby areas. Types of adaptive sampling designs include ordinary sequential sampling, adaptive allocation in stratified sampling, adaptive cluster sampling, and optimal model-based designs. Graph sampling refers to situations with nodes (for example, people) connected by edges (such as social links or geographic proximity). An initial sample of nodes or edges is selected and edges are subsequently followed to bring other nodes into the sample. Graph sampling designs include network sampling, snowball sampling, link-tracing, chain referral, and adaptive cluster sampling. A graph sampling design is adaptive if the decision to include linked nodes depends on variables of interest observed on nodes already in the sample. Adjustment methods for nonsampling errors such as imperfect detection of drug users in the sample apply to adaptive as well as conventional designs.

Hybrid approach combining chemometrics and likelihood ratio framework for reporting the evidential value of spectra.

PubMed

Martyna, Agnieszka; Zadora, Grzegorz; Neocleous, Tereza; Michalska, Aleksandra; Dean, Nema

2016-08-10

Many chemometric tools are invaluable and have proven effective in data mining and substantial dimensionality reduction of highly multivariate data. This becomes vital for interpreting various physicochemical data due to rapid development of advanced analytical techniques, delivering much information in a single measurement run. This concerns especially spectra, which are frequently used as the subject of comparative analysis in e.g. forensic sciences. In the presented study the microtraces collected from the scenarios of hit-and-run accidents were analysed. Plastic containers and automotive plastics (e.g. bumpers, headlamp lenses) were subjected to Fourier transform infrared spectrometry and car paints were analysed using Raman spectroscopy. In the forensic context analytical results must be interpreted and reported according to the standards of the interpretation schemes acknowledged in forensic sciences using the likelihood ratio approach. However, for proper construction of LR models for highly multivariate data, such as spectra, chemometric tools must be employed for substantial data compression. Conversion from classical feature representation to distance representation was proposed for revealing hidden data peculiarities and linear discriminant analysis was further applied for minimising the within-sample variability while maximising the between-sample variability. Both techniques enabled substantial reduction of data dimensionality. Univariate and multivariate likelihood ratio models were proposed for such data. It was shown that the combination of chemometric tools and the likelihood ratio approach is capable of solving the comparison problem of highly multivariate and correlated data after proper extraction of the most relevant features and variance information hidden in the data structure. Copyright © 2016 Elsevier B.V. All rights reserved.

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.…

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…

Is reducing variability of blood glucose the real but hidden target of intensive insulin therapy?

PubMed

Egi, Moritoki; Bellomo, Rinaldo; Reade, Michael C

2009-01-01

Since the first report that intensive insulin therapy reduced mortality in selected surgical critically ill patients, lowering of blood glucose levels has been recommended as a means of improving patient outcomes. In this initial Leuven trial, blood glucose control by protocol using insulin was applied to 98.7% of patients in the intensive group but to only 39.2% (P < 0.0001) of patients in the control group. If appropriately applied, such protocols should decrease both the mean blood glucose concentration and its variability (variation of blood glucose concentration). Thus, it is logically possible that the benefit of intensive insulin therapy in the first Leuven trial was due to a decrease in mean glucose levels, a decrease in their variability, or both. Several recent studies have confirmed significant associations between variability of blood glucose levels and patient outcomes. Decreasing the variability of blood glucose levels might be an important dimension of glucose management, a possible mechanism by which an intensive insulin protocol exerts its putative beneficial effects, and an important goal of glucose management in the intensive care unit. Clinicians need to be aware of this controversy when considering the application of intensive insulin therapy and interpreting future trials.

SU-E-T-206: Improving Radiotherapy Toxicity Based On Artificial Neural Network (ANN) for Head and Neck Cancer Patients

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

Cho, Daniel D; Wernicke, A Gabriella; Nori, Dattatreyudu

Purpose/Objective(s): The aim of this study is to build the estimator of toxicity using artificial neural network (ANN) for head and neck cancer patients Materials/Methods: An ANN can combine variables into a predictive model during training and considered all possible correlations of variables. We constructed an ANN based on the data from 73 patients with advanced H and N cancer treated with external beam radiotherapy and/or chemotherapy at our institution. For the toxicity estimator we defined input data including age, sex, site, stage, pathology, status of chemo, technique of external beam radiation therapy (EBRT), length of treatment, dose of EBRT,more » status of post operation, length of follow-up, the status of local recurrences and distant metastasis. These data were digitized based on the significance and fed to the ANN as input nodes. We used 20 hidden nodes (for the 13 input nodes) to take care of the correlations of input nodes. For training ANN, we divided data into three subsets such as training set, validation set and test set. Finally, we built the estimator for the toxicity from ANN output. Results: We used 13 input variables including the status of local recurrences and distant metastasis and 20 hidden nodes for correlations. 59 patients for training set, 7 patients for validation set and 7 patients for test set and fed the inputs to Matlab neural network fitting tool. We trained the data within 15% of errors of outcome. In the end we have the toxicity estimation with 74% of accuracy. Conclusion: We proved in principle that ANN can be a very useful tool for predicting the RT outcomes for high risk H and N patients. Currently we are improving the results using cross validation.« less

Prediction of municipal solid waste generation using nonlinear autoregressive network.

PubMed

Younes, Mohammad K; Nopiah, Z M; Basri, N E Ahmad; Basri, H; Abushammala, Mohammed F M; Maulud, K N A

2015-12-01

Most of the developing countries have solid waste management problems. Solid waste strategic planning requires accurate prediction of the quality and quantity of the generated waste. In developing countries, such as Malaysia, the solid waste generation rate is increasing rapidly, due to population growth and new consumption trends that characterize society. This paper proposes an artificial neural network (ANN) approach using feedforward nonlinear autoregressive network with exogenous inputs (NARX) to predict annual solid waste generation in relation to demographic and economic variables like population number, gross domestic product, electricity demand per capita and employment and unemployment numbers. In addition, variable selection procedures are also developed to select a significant explanatory variable. The model evaluation was performed using coefficient of determination (R(2)) and mean square error (MSE). The optimum model that produced the lowest testing MSE (2.46) and the highest R(2) (0.97) had three inputs (gross domestic product, population and employment), eight neurons and one lag in the hidden layer, and used Fletcher-Powell's conjugate gradient as the training algorithm.

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.

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.

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

Hidden Agendas in Marriage: Affective and Longitudinal Dimensions.

ERIC Educational Resources Information Center

Krokoff, Lowell J.

1990-01-01

Examines how couples' discussions of troublesome problems reveal hidden agendas (issues not directly discussed or explored). Finds disgust and contempt are at the core of both love and respect agendas for husbands and wives. Finds that wives' more than husbands' hidden agendas are directly predictive of how negatively they argue at home. (SR)

Hidden Connections between Regression Models of Strain-Gage Balance Calibration Data

NASA Technical Reports Server (NTRS)

Ulbrich, Norbert

2013-01-01

Hidden connections between regression models of wind tunnel strain-gage balance calibration data are investigated. These connections become visible whenever balance calibration data is supplied in its design format and both the Iterative and Non-Iterative Method are used to process the data. First, it is shown how the regression coefficients of the fitted balance loads of a force balance can be approximated by using the corresponding regression coefficients of the fitted strain-gage outputs. Then, data from the manual calibration of the Ames MK40 six-component force balance is chosen to illustrate how estimates of the regression coefficients of the fitted balance loads can be obtained from the regression coefficients of the fitted strain-gage outputs. The study illustrates that load predictions obtained by applying the Iterative or the Non-Iterative Method originate from two related regression solutions of the balance calibration data as long as balance loads are given in the design format of the balance, gage outputs behave highly linear, strict statistical quality metrics are used to assess regression models of the data, and regression model term combinations of the fitted loads and gage outputs can be obtained by a simple variable exchange.

Reciprocal Markov Modeling of Feedback Mechanisms Between Emotion and Dietary Choice Using Experience-Sampling Data.

PubMed

Lu, Ji; Pan, Junhao; Zhang, Qiang; Dubé, Laurette; Ip, Edward H

2015-01-01

With intensively collected longitudinal data, recent advances in the experience-sampling method (ESM) benefit social science empirical research, but also pose important methodological challenges. As traditional statistical models are not generally well equipped to analyze a system of variables that contain feedback loops, this paper proposes the utility of an extended hidden Markov model to model reciprocal the relationship between momentary emotion and eating behavior. This paper revisited an ESM data set (Lu, Huet, & Dube, 2011) that observed 160 participants' food consumption and momentary emotions 6 times per day in 10 days. Focusing on the analyses on feedback loop between mood and meal-healthiness decision, the proposed reciprocal Markov model (RMM) can accommodate both hidden ("general" emotional states: positive vs. negative state) and observed states (meal: healthier, same or less healthy than usual) without presuming independence between observations and smooth trajectories of mood or behavior changes. The results of RMM analyses illustrated the reciprocal chains of meal consumption and mood as well as the effect of contextual factors that moderate the interrelationship between eating and emotion. A simulation experiment that generated data consistent with the empirical study further demonstrated that the procedure is promising in terms of recovering the parameters.

Adaptive quantification and longitudinal analysis of pulmonary emphysema with a hidden Markov measure field model.

PubMed

Hame, Yrjo; Angelini, Elsa D; Hoffman, Eric A; Barr, R Graham; Laine, Andrew F

2014-07-01

The extent of pulmonary emphysema is commonly estimated from CT scans by computing the proportional area of voxels below a predefined attenuation threshold. However, the reliability of this approach is limited by several factors that affect the CT intensity distributions in the lung. This work presents a novel method for emphysema quantification, based on parametric modeling of intensity distributions and a hidden Markov measure field model to segment emphysematous regions. The framework adapts to the characteristics of an image to ensure a robust quantification of emphysema under varying CT imaging protocols, and differences in parenchymal intensity distributions due to factors such as inspiration level. Compared to standard approaches, the presented model involves a larger number of parameters, most of which can be estimated from data, to handle the variability encountered in lung CT scans. The method was applied on a longitudinal data set with 87 subjects and a total of 365 scans acquired with varying imaging protocols. The resulting emphysema estimates had very high intra-subject correlation values. By reducing sensitivity to changes in imaging protocol, the method provides a more robust estimate than standard approaches. The generated emphysema delineations promise advantages for regional analysis of emphysema extent and progression.

Recovering hidden diagonal structures via non-negative matrix factorization with multiple constraints.

PubMed

Yang, Xi; Han, Guoqiang; Cai, Hongmin; Song, Yan

2017-03-31

Revealing data with intrinsically diagonal block structures is particularly useful for analyzing groups of highly correlated variables. Earlier researches based on non-negative matrix factorization (NMF) have been shown to be effective in representing such data by decomposing the observed data into two factors, where one factor is considered to be the feature and the other the expansion loading from a linear algebra perspective. If the data are sampled from multiple independent subspaces, the loading factor would possess a diagonal structure under an ideal matrix decomposition. However, the standard NMF method and its variants have not been reported to exploit this type of data via direct estimation. To address this issue, a non-negative matrix factorization with multiple constraints model is proposed in this paper. The constraints include an sparsity norm on the feature matrix and a total variational norm on each column of the loading matrix. The proposed model is shown to be capable of efficiently recovering diagonal block structures hidden in observed samples. An efficient numerical algorithm using the alternating direction method of multipliers model is proposed for optimizing the new model. Compared with several benchmark models, the proposed method performs robustly and effectively for simulated and real biological data.

Automated recognition of bird song elements from continuous recordings using dynamic time warping and hidden Markov models: a comparative study.

PubMed

Kogan, J A; Margoliash, D

1998-04-01

The performance of two techniques is compared for automated recognition of bird song units from continuous recordings. The advantages and limitations of dynamic time warping (DTW) and hidden Markov models (HMMs) are evaluated on a large database of male songs of zebra finches (Taeniopygia guttata) and indigo buntings (Passerina cyanea), which have different types of vocalizations and have been recorded under different laboratory conditions. Depending on the quality of recordings and complexity of song, the DTW-based technique gives excellent to satisfactory performance. Under challenging conditions such as noisy recordings or presence of confusing short-duration calls, good performance of the DTW-based technique requires careful selection of templates that may demand expert knowledge. Because HMMs are trained, equivalent or even better performance of HMMs can be achieved based only on segmentation and labeling of constituent vocalizations, albeit with many more training examples than DTW templates. One weakness in HMM performance is the misclassification of short-duration vocalizations or song units with more variable structure (e.g., some calls, and syllables of plastic songs). To address these and other limitations, new approaches for analyzing bird vocalizations are discussed.

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

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.

Temporal competition between differentiation programs determines cell fate choice

NASA Astrophysics Data System (ADS)

Kuchina, Anna; Espinar, Lorena; Cagatay, Tolga; Balbin, Alejandro; Alvarado, Alma; Garcia-Ojalvo, Jordi; Suel, Gurol

2011-03-01

During pluripotent differentiation, cells adopt one of several distinct fates. The dynamics of this decision-making process are poorly understood, since cell fate choice may be governed by interactions between differentiation programs that are active at the same time. We studied the dynamics of decision-making in the model organism Bacillus subtilis by simultaneously measuring the activities of competing differentiation programs (sporulation and competence) in single cells. We discovered a precise switch-like point of cell fate choice previously hidden by cell-cell variability. Engineered artificial crosslinks between competence and sporulation circuits revealed that the precision of this choice is generated by temporal competition between the key players of two differentiation programs. Modeling suggests that variable progression towards a switch-like decision might represent a general strategy to maximize adaptability and robustness of cellular decision-making.

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).

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.

EPRB Gedankenexperiment and Entanglement with Classical Light Waves

NASA Astrophysics Data System (ADS)

Rashkovskiy, Sergey A.

2018-06-01

In this article we show that results similar to those of the Einstein-Podolsky-Rosen-Bohm (EPRB) Gedankenexperiment and entanglement of photons can be obtained using weak classical light waves if we take into account the discrete (atomic) structure of the detectors and a specific nature of the light-atom interaction. We show that the CHSH (Clauser, Horne, Shimony, and Holt) criterion in the EPRB Gedankenexperiment with classical light waves can exceed not only the maximum value SHV=2 that is predicted by the local hidden-variable theories but also the maximum value S_{QM} = 2√2 predicted by quantum mechanics.

Bounding the Set of Classical Correlations of a Many-Body System

NASA Astrophysics Data System (ADS)

Fadel, Matteo; Tura, Jordi

2017-12-01

We present a method to certify the presence of Bell correlations in experimentally observed statistics, and to obtain new Bell inequalities. Our approach is based on relaxing the conditions defining the set of correlations obeying a local hidden variable model, yielding a convergent hierarchy of semidefinite programs (SDP's). Because the size of these SDP's is independent of the number of parties involved, this technique allows us to characterize correlations in many-body systems. As an example, we illustrate our method with the experimental data presented in Science 352, 441 (2016), 10.1126/science.aad8665.

Tight Bell Inequalities and Nonlocality in Weak Measurement

NASA Astrophysics Data System (ADS)

Waegell, Mordecai

A general class of Bell inequalities is derived based on strict adherence to probabilistic entanglement correlations observed in nature. This derivation gives significantly tighter bounds on local hidden variable theories for the well-known Clauser-Horne-Shimony-Holt (CHSH) inequality, and also leads to new proofs of the Greenberger-Horne-Zeilinger (GHZ) theorem. This method is applied to weak measurements and reveals nonlocal correlations between the weak value and the post-selection, which rules out various classical models of weak measurement. Implications of these results are discussed. Fetzer-Franklin Fund of the John E. Fetzer Memorial Trust.

Hidden instabilities in the Ti:sapphire Kerr lens mode-locked laser.

PubMed

Kovalsky, M G; Hnilo, A A; González Inchauspe, C M

1999-11-15

It is experimentally shown that pulse-to-pulse instabilities in the output of Kerr lens mode-locked Ti:sapphire lasers are usual and that they can affect some of the pulse variables (e.g., the spot size) and not others (e.g., pulse duration and energy). These instabilities are not detectable in the averaged signals (such as the autocorrelation of the pulse) that are customarily used for controlling the laser. But, if they are present but are disregarded, these instabilities have undesirable consequences in almost any application. A simple way to detect and eliminate the instabilities is described.

The Hidden Curriculum of Youth Policy: A Dutch Example

ERIC Educational Resources Information Center

Hopman, Marit; de Winter, Micha; Koops, Willem

2014-01-01

Youth policy is more than a mere response to the actual behavior of children, but it is equally influenced by values and beliefs of policy makers. These values are however rarely made explicit and, therefore, the authors refer to them as "the hidden curriculum" of youth policy. The study investigation explicates this hidden curriculum by…

Hidden School Dropout among Immigrant Students: A Cross-Sectional Study

ERIC Educational Resources Information Center

Makarova, Elena; Herzog, Walter

2013-01-01

Actual school dropout among immigrant youth has been addressed in a number of studies, but research on hidden school dropout among immigrant students is rare. Thus, the objective of this paper is to analyze hidden school dropout among primary school students with an immigrant background. The analyses were performed using survey data of 1186…

Secret Codes: The Hidden Curriculum of Semantic Web Technologies

ERIC Educational Resources Information Center

Edwards, Richard; Carmichael, Patrick

2012-01-01

There is a long tradition in education of examination of the hidden curriculum, those elements which are implicit or tacit to the formal goals of education. This article draws upon that tradition to open up for investigation the hidden curriculum and assumptions about students and knowledge that are embedded in the coding undertaken to facilitate…

Hidden Costs of Hospital Based Delivery from Two Tertiary Hospitals in Western Nepal.

PubMed

Acharya, Jeevan; Kaehler, Nils; Marahatta, Sujan Babu; Mishra, Shiva Raj; Subedi, Sudarshan; Adhikari, Bipin

2016-01-01

Hospital based delivery has been an expensive experience for poor households because of hidden costs which are usually unaccounted in hospital costs. The main aim of this study was to estimate the hidden costs of hospital based delivery and determine the factors associated with the hidden costs. A hospital based cross-sectional study was conducted among 384 post-partum mothers with their husbands/house heads during the discharge time in Manipal Teaching Hospital and Western Regional Hospital, Pokhara, Nepal. A face to face interview with each respondent was conducted using a structured questionnaire. Hidden costs were calculated based on the price rate of the market during the time of the study. The total hidden costs for normal delivery and C-section delivery were 243.4 USD (US Dollar) and 321.6 USD respectively. Of the total maternity care expenditures; higher mean expenditures were found for food & drinking (53.07%), clothes (9.8%) and transport (7.3%). For postpartum women with their husband or house head, the total mean opportunity cost of "days of work loss" were 84.1 USD and 81.9 USD for normal delivery and C-section respectively. Factors such as literate mother (p = 0.007), employed house head (p = 0.011), monthly family income more than 25,000 NRs (Nepalese Rupees) (p = 0.014), private hospital as a place of delivery (p = 0.0001), C-section as a mode of delivery (p = 0.0001), longer duration (>5days) of stay in hospital (p = 0.0001), longer distance (>15km) from house to hospital (p = 0.0001) and longer travel time (>240 minutes) from house to hospital (p = 0.007) showed a significant association with the higher hidden costs (>25000 NRs). Experiences of hidden costs on hospital based delivery and opportunity costs of days of work loss were found high. Several socio-demographic factors, delivery related factors (place and mode of delivery, length of stay, distance from hospital and travel time) were associated with hidden costs. Hidden costs can be a critical factor for many poor and remote households who attend the hospital for delivery. Current remuneration (10-15 USD for normal delivery, 30 USD for complicated delivery and 70 USD for caesarean section delivery) for maternity incentive needs to account the hidden costs by increasing it to 250 USD for normal delivery and 350 USD for C-section. Decentralization of the obstetric care to remote and under-privileged population might reduce the economic burden of pregnant women and can facilitate their attendance at the health care centers.

Dopamine reward prediction errors reflect hidden state inference across time

PubMed Central

Starkweather, Clara Kwon; Babayan, Benedicte M.; Uchida, Naoshige; Gershman, Samuel J.

2017-01-01

Midbrain dopamine neurons signal reward prediction error (RPE), or actual minus expected reward. The temporal difference (TD) learning model has been a cornerstone in understanding how dopamine RPEs could drive associative learning. Classically, TD learning imparts value to features that serially track elapsed time relative to observable stimuli. In the real world, however, sensory stimuli provide ambiguous information about the hidden state of the environment, leading to the proposal that TD learning might instead compute a value signal based on an inferred distribution of hidden states (a ‘belief state’). In this work, we asked whether dopaminergic signaling supports a TD learning framework that operates over hidden states. We found that dopamine signaling exhibited a striking difference between two tasks that differed only with respect to whether reward was delivered deterministically. Our results favor an associative learning rule that combines cached values with hidden state inference. PMID:28263301

Modelling proteins' hidden conformations to predict antibiotic resistance

NASA Astrophysics Data System (ADS)

Hart, Kathryn M.; Ho, Chris M. W.; Dutta, Supratik; Gross, Michael L.; Bowman, Gregory R.

2016-10-01

TEM β-lactamase confers bacteria with resistance to many antibiotics and rapidly evolves activity against new drugs. However, functional changes are not easily explained by differences in crystal structures. We employ Markov state models to identify hidden conformations and explore their role in determining TEM's specificity. We integrate these models with existing drug-design tools to create a new technique, called Boltzmann docking, which better predicts TEM specificity by accounting for conformational heterogeneity. Using our MSMs, we identify hidden states whose populations correlate with activity against cefotaxime. To experimentally detect our predicted hidden states, we use rapid mass spectrometric footprinting and confirm our models' prediction that increased cefotaxime activity correlates with reduced Ω-loop flexibility. Finally, we design novel variants to stabilize the hidden cefotaximase states, and find their populations predict activity against cefotaxime in vitro and in vivo. Therefore, we expect this framework to have numerous applications in drug and protein design.

Cosmological abundance of the QCD axion coupled to hidden photons

NASA Astrophysics Data System (ADS)

Kitajima, Naoya; Sekiguchi, Toyokazu; Takahashi, Fuminobu

2018-06-01

We study the cosmological evolution of the QCD axion coupled to hidden photons. For a moderately strong coupling, the motion of the axion field leads to an explosive production of hidden photons by tachyonic instability. We use lattice simulations to evaluate the cosmological abundance of the QCD axion. In doing so, we incorporate the backreaction of the produced hidden photons on the axion dynamics, which becomes significant in the non-linear regime. We find that the axion abundance is suppressed by at most O (102) for the decay constant fa =1016GeV, compared to the case without the coupling. For a sufficiently large coupling, the motion of the QCD axion becomes strongly damped, and as a result, the axion abundance is enhanced. Our results show that the cosmological upper bound on the axion decay constant can be relaxed by a few hundred for a certain range of the coupling to hidden photons.

Perspective: Disclosing hidden sources of funding.

PubMed

Resnik, David B

2009-09-01

In this article, the author discusses ethical and policy issues related to the disclosure of hidden sources of funding in research. The author argues that authors have an ethical obligation to disclose hidden sources of funding and that journals should adopt policies to enforce this obligation. Journal policies should require disclosure of hidden sources of funding that authors know about and that have a direct relation to their research. To stimulate this discussion, the author describes a recent case: investigators who conducted a lung cancer screening study had received funding from a private foundation that was supported by a tobacco company, but they did not disclose this relationship to the journal. Investigators and journal editors must be prepared to deal with these issues in a manner that promotes honesty, transparency, fairness, and accountability in research. The development of well-defined, reasonable policies pertaining to hidden sources of funding can be a step in this direction.

Modelling proteins’ hidden conformations to predict antibiotic resistance

PubMed Central

Hart, Kathryn M.; Ho, Chris M. W.; Dutta, Supratik; Gross, Michael L.; Bowman, Gregory R.

2016-01-01

TEM β-lactamase confers bacteria with resistance to many antibiotics and rapidly evolves activity against new drugs. However, functional changes are not easily explained by differences in crystal structures. We employ Markov state models to identify hidden conformations and explore their role in determining TEM’s specificity. We integrate these models with existing drug-design tools to create a new technique, called Boltzmann docking, which better predicts TEM specificity by accounting for conformational heterogeneity. Using our MSMs, we identify hidden states whose populations correlate with activity against cefotaxime. To experimentally detect our predicted hidden states, we use rapid mass spectrometric footprinting and confirm our models’ prediction that increased cefotaxime activity correlates with reduced Ω-loop flexibility. Finally, we design novel variants to stabilize the hidden cefotaximase states, and find their populations predict activity against cefotaxime in vitro and in vivo. Therefore, we expect this framework to have numerous applications in drug and protein design. PMID:27708258

Dopamine reward prediction errors reflect hidden-state inference across time.

PubMed

Starkweather, Clara Kwon; Babayan, Benedicte M; Uchida, Naoshige; Gershman, Samuel J

2017-04-01

Midbrain dopamine neurons signal reward prediction error (RPE), or actual minus expected reward. The temporal difference (TD) learning model has been a cornerstone in understanding how dopamine RPEs could drive associative learning. Classically, TD learning imparts value to features that serially track elapsed time relative to observable stimuli. In the real world, however, sensory stimuli provide ambiguous information about the hidden state of the environment, leading to the proposal that TD learning might instead compute a value signal based on an inferred distribution of hidden states (a 'belief state'). Here we asked whether dopaminergic signaling supports a TD learning framework that operates over hidden states. We found that dopamine signaling showed a notable difference between two tasks that differed only with respect to whether reward was delivered in a deterministic manner. Our results favor an associative learning rule that combines cached values with hidden-state inference.

Analysing biomass torrefaction supply chain costs.

PubMed

Svanberg, Martin; Olofsson, Ingemar; Flodén, Jonas; Nordin, Anders

2013-08-01

The objective of the present work was to develop a techno-economic system model to evaluate how logistics and production parameters affect the torrefaction supply chain costs under Swedish conditions. The model consists of four sub-models: (1) supply system, (2) a complete energy and mass balance of drying, torrefaction and densification, (3) investment and operating costs of a green field, stand-alone torrefaction pellet plant, and (4) distribution system to the gate of an end user. The results show that the torrefaction supply chain reaps significant economies of scale up to a plant size of about 150-200 kiloton dry substance per year (ktonDS/year), for which the total supply chain costs accounts to 31.8 euro per megawatt hour based on lower heating value (€/MWhLHV). Important parameters affecting total cost are amount of available biomass, biomass premium, logistics equipment, biomass moisture content, drying technology, torrefaction mass yield and torrefaction plant capital expenditures (CAPEX). Copyright © 2013 Elsevier Ltd. All rights reserved.

Development of the hybrid sulfur cycle for use with concentrated solar heat. I. Conceptual design

DOE PAGES

Gorensek, Maximilian B.; Corgnale, Claudio; Summers, William A.

2017-07-27

We propose a detailed conceptual design of a solar hybrid sulfur (HyS) cycle. Numerous design tradeoffs, including process operating conditions and strategies, methods of integration with solar energy sources, and solar design options were considered. A baseline design was selected, and process flowsheets were developed. Pinch analyses were performed to establish the limiting energy efficiency. Detailed material and energy balances were completed, and a full stream table prepared. Design assumptions include use of: location in the southwest US desert, falling particle concentrated solar receiver, indirect heat transfer via pressurized helium, continuous operation with thermal energy storage, liquid-fed electrolyzer with PBImore » membrane, and bayonet-type acid decomposer. Thermochemical cycle efficiency for the HyS process was estimated to be 35.0%, LHV basis. The solar-to-hydrogen (STH) energy conversion ratio was 16.9%. This thus exceeds the Year 2015 DOE STCH target of STH >10%, and shows promise for meeting the Year 2020 target of 20%.« less

High quality fuel gas from biomass pyrolysis with calcium oxide.

PubMed

Zhao, Baofeng; Zhang, Xiaodong; Chen, Lei; Sun, Laizhi; Si, Hongyu; Chen, Guanyi

2014-03-01

The removal of CO2 and tar in fuel gas produced by biomass thermal conversion has aroused more attention due to their adverse effects on the subsequent fuel gas application. High quality fuel gas production from sawdust pyrolysis with CaO was studied in this paper. The results of pyrolysis-gas chromatography/mass spectrometry (Py-GC/MS) experiments indicate that the mass ratio of CaO to sawdust (Ca/S) remarkably affects the behavior of sawdust pyrolysis. On the basis of Py-GC/MS results, one system of a moving bed pyrolyzer coupled with a fluid bed combustor has been developed to produce high quality fuel gas. The lower heating value (LHV) of the fuel gas was above 16MJ/Nm(3) and the content of tar was under 50mg/Nm(3), which is suitable for gas turbine application to generate electricity and heat. Therefore, this technology may be a promising route to achieve high quality fuel gas for biomass utilization. Copyright © 2014 Elsevier Ltd. All rights reserved.

Successful living donor liver transplant in a child with Abernethy malformation with biliary atresia, ventricular septal defect and intrapulmonary shunting.

PubMed

Singhal, Ashish; Srivastava, Ajitabh; Goyal, Neerav; Vij, Vivek; Wadhawan, Manav; Bera, Motilal; Gupta, Subash

2009-12-01

Congenital portosystemic shunts are the anomalies in which the mesenteric venous drainage bypasses the liver and drains directly into the systemic circulation. This is a report of a rare case of LDLT in a four-yr old male child suffering with biliary atresia (post-failed Kasai procedure) associated with (i) a large congenital CEPSh from the spleno-mesentric confluence to the LHV, (ii) intrapulmonary shunts, (iii) perimembranous VSD. The left lobe graft was procured from the mother of the child. Recipient IVC and the shunt vessel were preserved during the hepatectomy, and the caval and shunt clamping were remarkably short while performing the HV and portal anastomosis. Post-operative course was uneventful; intrapulmonary shunts regressed within three months after transplantation and currently after 18 months following transplant child is doing well with normal liver functions. CEPSh has been extensively discussed and all the published cases of liver transplantation for CEPSh were reviewed.

Development of the hybrid sulfur cycle for use with concentrated solar heat. I. Conceptual design

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

Gorensek, Maximilian B.; Corgnale, Claudio; Summers, William A.

We propose a detailed conceptual design of a solar hybrid sulfur (HyS) cycle. Numerous design tradeoffs, including process operating conditions and strategies, methods of integration with solar energy sources, and solar design options were considered. A baseline design was selected, and process flowsheets were developed. Pinch analyses were performed to establish the limiting energy efficiency. Detailed material and energy balances were completed, and a full stream table prepared. Design assumptions include use of: location in the southwest US desert, falling particle concentrated solar receiver, indirect heat transfer via pressurized helium, continuous operation with thermal energy storage, liquid-fed electrolyzer with PBImore » membrane, and bayonet-type acid decomposer. Thermochemical cycle efficiency for the HyS process was estimated to be 35.0%, LHV basis. The solar-to-hydrogen (STH) energy conversion ratio was 16.9%. This thus exceeds the Year 2015 DOE STCH target of STH >10%, and shows promise for meeting the Year 2020 target of 20%.« less

Beneficial synergetic effect on gas production during co-pyrolysis of sewage sludge and biomass in a vacuum reactor.

PubMed

Zhang, Weijiang; Yuan, Chengyong; Xu, Jiao; Yang, Xiao

2015-05-01

A vacuum fixed bed reactor was used to pyrolyze sewage sludge, biomass (rice husk) and their blend under high temperature (900°C). Pyrolytic products were kept in the vacuum reactor during the whole pyrolysis process, guaranteeing a long contact time (more than 2h) for their interactions. Remarkable synergetic effect on gas production was observed. Gas yield of blend fuel was evidently higher than that of both parent fuels. The syngas (CO and H2) content and gas lower heating value (LHV) were obviously improved as well. It was highly possible that sewage sludge provided more CO2 and H2O during co-pyrolysis, promoting intense CO2-char and H2O-char gasification, which benefited the increase of gas yield and lower heating value. The beneficial synergetic effect, as a result, made this method a feasible one for gas production. Copyright © 2015. Published by Elsevier Ltd.

Potential method for gas production: high temperature co-pyrolysis of lignite and sewage sludge with vacuum reactor and long contact time.

PubMed

Yang, Xiao; Yuan, Chengyong; Xu, Jiao; Zhang, Weijiang

2015-03-01

Lignite and sewage sludge were co-pyrolyzed in a vacuum reactor with high temperature (900°C) and long contact time (more than 2h). Beneficial synergetic effect on gas yield was clearly observed. Gas yield of blend fuel was evidently higher than that of both parent fuels. The gas volume yield, gas lower heating value (LHV), fixed carbon conversion and H2/CO ratio were 1.42 Nm(3)/kg(blend fuel), 10.57 MJ/Nm(3), 96.64% and 0.88% respectively, which indicated this new method a feasible one for gas production. It was possible that sewage sludge acted as gasification agents (CO2 and H2O) and catalyst (alkali and alkaline earth metals) provider during co-pyrolysis, promoting CO2-char and H2O-char gasification which, as a result, invited the improvement of gas volume yield, gas lower heating value and fixed carbon conversion. Copyright © 2014 Elsevier Ltd. All rights reserved.

The RDF/SRF torrefaction: An effect of temperature on characterization of the product - Carbonized Refuse Derived Fuel.

PubMed

Białowiec, Andrzej; Pulka, Jakub; Stępień, Paweł; Manczarski, Piotr; Gołaszewski, Janusz

2017-12-01

The influence of Refuse Derived Fuel (RDF)/Solid Recovery Fuel (SRF) torrefaction temperature on product characteristic was investigated. RDF/SRF thermal treatment experiment was conducted with 1-h residence time, under given temperatures: 200, 220, 240, 260, 280 and 300°C. Sawdust was used as reference material. The following parameters of torrefaction char from sawdust and Carbonized Refuse Derived Fuel (CRDF) from RDF/SRF were measured: moisture, calorific value, ash content, volatile compounds and sulfur content. Sawdust biochar was confirmed as a good quality solid fuel, due to significant fuel property increase. The study also indicated that RDF torrefaction reduced moisture significantly from 22.9% to 1.4% and therefore increased lower heating value (LHV) from 19.6 to 25.3MJ/kg. Results suggest that RDF torrefaction may be a good method for increasing attractiveness of RDF as an energy source, and it could help unify RDF properties on the market. Copyright © 2017 Elsevier Ltd. All rights reserved.

Torrefaction of agriculture straws and its application on biomass pyrolysis poly-generation.

PubMed

Chen, Yingquan; Yang, Haiping; Yang, Qing; Hao, Hongmeng; Zhu, Bo; Chen, Hanping

2014-03-01

This study investigated the properties of corn stalk and cotton stalk after torrefaction, and the effects of torrefaction on product properties obtained under the optimal condition of biomass pyrolysis polygeneration. The color of the torrefied biomass chars darkened, and the grindability was upgraded, with finer particles formed and grinding energy consumption reduced. The moisture and oxygen content significantly decreased whereas the carbon content increased considerably. It was found that torrefaction had different effects on the char, liquid oil and biogas from biomass pyrolysis polygeneration. Compared to raw straws, the output of chars from pyrolysis of torrefied straws increased and the quality of chars as a solid fuel had no significant change, while the output of liquid oil and biogas decreased. The liquid oil contained more concentrated phenols with less water content below 40wt.%, and the biogas contained more concentrated H2 and CH4 with higher LHV up to 15MJ/nm(3). Copyright © 2014 Elsevier Ltd. All rights reserved.

The catalytic pyrolysis of food waste by microwave heating.

PubMed

Liu, Haili; Ma, Xiaoqian; Li, Longjun; Hu, ZhiFeng; Guo, Pingsheng; Jiang, Yuhui

2014-08-01

This study describes a series of experiments that tested the use of microwave pyrolysis for treating food waste. Characteristics including rise in temperature, and the three-phase products, were analyzed at different microwave power levels, after adding 5% (mass basis) metal oxides and chloride salts to the food waste. Results indicated that, the metal oxides MgO, Fe₂O₃ and MnO₂ and the chloride salts CuCl₂ and NaCl can lower the yield of bio-oil and enhance the yield of gas. Meanwhile, the metal oxides MgO and MnO₂ can also lower the low heating value (LHV) of solid residues and increase the pH values of the lower layer bio-oils. However, the chloride salts CuCl₂ and NaCl had the opposite effects. The optimal microwave power for treating food waste was 400W; among the tested catalysts, CuCl₂ was the best catalyst and had the largest energy ratio of production to consumption (ERPC), followed by MnO₂. Copyright © 2014 Elsevier Ltd. All rights reserved.

Nurture Hidden Talents: Transform School Culture into One That Values Teacher Expertise

ERIC Educational Resources Information Center

Zimmerman, Diane P.

2014-01-01

This article looks into the school culture where teacher expertise is often hidden and underused. While the media-rich culture places a high value on talent, the irony is that talent is underrated in most schools, and educators often remain silent about their hidden talents. Many school cultures are not conducive to dialogue that supports displays…

Hidden Area and Mechanical Nonlinearities in Freestanding Graphene.

PubMed

Nicholl, Ryan J T; Lavrik, Nickolay V; Vlassiouk, Ivan; Srijanto, Bernadeta R; Bolotin, Kirill I

2017-06-30

We investigated the effect of out-of-plane crumpling on the mechanical response of graphene membranes. In our experiments, stress was applied to graphene membranes using pressurized gas while the strain state was monitored through two complementary techniques: interferometric profilometry and Raman spectroscopy. By comparing the data obtained through these two techniques, we determined the geometric hidden area which quantifies the crumpling strength. While the devices with hidden area ∼0% obeyed linear mechanics with biaxial stiffness 428±10  N/m, specimens with hidden area in the range 0.5%-1.0% were found to obey an anomalous nonlinear Hooke's law with an exponent ∼0.1.

Hidden Area and Mechanical Nonlinearities in Freestanding Graphene

NASA Astrophysics Data System (ADS)

Nicholl, Ryan J. T.; Lavrik, Nickolay V.; Vlassiouk, Ivan; Srijanto, Bernadeta R.; Bolotin, Kirill I.

2017-06-01

We investigated the effect of out-of-plane crumpling on the mechanical response of graphene membranes. In our experiments, stress was applied to graphene membranes using pressurized gas while the strain state was monitored through two complementary techniques: interferometric profilometry and Raman spectroscopy. By comparing the data obtained through these two techniques, we determined the geometric hidden area which quantifies the crumpling strength. While the devices with hidden area ˜0 % obeyed linear mechanics with biaxial stiffness 428 ±10 N /m , specimens with hidden area in the range 0.5%-1.0% were found to obey an anomalous nonlinear Hooke's law with an exponent ˜0.1 .

Multilayer neural networks with extensively many hidden units.

PubMed

Rosen-Zvi, M; Engel, A; Kanter, I

2001-08-13

The information processing abilities of a multilayer neural network with a number of hidden units scaling as the input dimension are studied using statistical mechanics methods. The mapping from the input layer to the hidden units is performed by general symmetric Boolean functions, whereas the hidden layer is connected to the output by either discrete or continuous couplings. Introducing an overlap in the space of Boolean functions as order parameter, the storage capacity is found to scale with the logarithm of the number of implementable Boolean functions. The generalization behavior is smooth for continuous couplings and shows a discontinuous transition to perfect generalization for discrete ones.

Hidden hyperchaos and electronic circuit application in a 5D self-exciting homopolar disc dynamo

NASA Astrophysics Data System (ADS)

Wei, Zhouchao; Moroz, Irene; Sprott, J. C.; Akgul, Akif; Zhang, Wei

2017-03-01

We report on the finding of hidden hyperchaos in a 5D extension to a known 3D self-exciting homopolar disc dynamo. The hidden hyperchaos is identified through three positive Lyapunov exponents under the condition that the proposed model has just two stable equilibrium states in certain regions of parameter space. The new 5D hyperchaotic self-exciting homopolar disc dynamo has multiple attractors including point attractors, limit cycles, quasi-periodic dynamics, hidden chaos or hyperchaos, as well as coexisting attractors. We use numerical integrations to create the phase plane trajectories, produce bifurcation diagram, and compute Lyapunov exponents to verify the hidden attractors. Because no unstable equilibria exist in two parameter regions, the system has a multistability and six kinds of complex dynamic behaviors. To the best of our knowledge, this feature has not been previously reported in any other high-dimensional system. Moreover, the 5D hyperchaotic system has been simulated using a specially designed electronic circuit and viewed on an oscilloscope, thereby confirming the results of the numerical integrations. Both Matlab and the oscilloscope outputs produce similar phase portraits. Such implementations in real time represent a new type of hidden attractor with important consequences for engineering applications.

Hidden hyperchaos and electronic circuit application in a 5D self-exciting homopolar disc dynamo.

PubMed

Wei, Zhouchao; Moroz, Irene; Sprott, J C; Akgul, Akif; Zhang, Wei

2017-03-01

We report on the finding of hidden hyperchaos in a 5D extension to a known 3D self-exciting homopolar disc dynamo. The hidden hyperchaos is identified through three positive Lyapunov exponents under the condition that the proposed model has just two stable equilibrium states in certain regions of parameter space. The new 5D hyperchaotic self-exciting homopolar disc dynamo has multiple attractors including point attractors, limit cycles, quasi-periodic dynamics, hidden chaos or hyperchaos, as well as coexisting attractors. We use numerical integrations to create the phase plane trajectories, produce bifurcation diagram, and compute Lyapunov exponents to verify the hidden attractors. Because no unstable equilibria exist in two parameter regions, the system has a multistability and six kinds of complex dynamic behaviors. To the best of our knowledge, this feature has not been previously reported in any other high-dimensional system. Moreover, the 5D hyperchaotic system has been simulated using a specially designed electronic circuit and viewed on an oscilloscope, thereby confirming the results of the numerical integrations. Both Matlab and the oscilloscope outputs produce similar phase portraits. Such implementations in real time represent a new type of hidden attractor with important consequences for engineering applications.

Humanism, the Hidden Curriculum, and Educational Reform: A Scoping Review and Thematic Analysis.

PubMed

Martimianakis, Maria Athina Tina; Michalec, Barret; Lam, Justin; Cartmill, Carrie; Taylor, Janelle S; Hafferty, Frederic W

2015-11-01

Medical educators have used the hidden curriculum concept for over three decades to make visible the effects of tacit learning, including how culture, structures, and institutions influence professional identity formation. In response to calls to see more humanistic-oriented training in medicine, the authors examined how the hidden curriculum construct has been applied in the English language medical education literature with a particular (and centering) look at its use within literature pertaining to humanism. They also explored the ends to which the hidden curriculum construct has been used in educational reform efforts (at the individual, organizational, and/or systems levels) related to nurturing and/or increasing humanism in health care. The authors conducted a scoping review and thematic analysis that draws from the tradition of critical discourse analysis. They identified 1,887 texts in the literature search, of which 200 met inclusion criteria. The analysis documents a strong preoccupation with negative effects of the hidden curriculum, particularly the moral erosion of physicians and the perceived undermining of humanistic values in health care. A conflation between professionalism and humanism was noted. Proposals for reform largely target medical students and medical school faculty, with very little consideration for how organizations, institutions, and sociopolitical relations more broadly contribute to problematic behaviors. The authors argue that there is a need to transcend conceptualizations of the hidden curriculum as antithetical to humanism and offer suggestions for future research that explores the necessity and value of humanism and the hidden curriculum in medical education and training.

Bayesian state space models for dynamic genetic network construction across multiple tissues.

PubMed

Liang, Yulan; Kelemen, Arpad

2016-08-01

Construction of gene-gene interaction networks and potential pathways is a challenging and important problem in genomic research for complex diseases while estimating the dynamic changes of the temporal correlations and non-stationarity are the keys in this process. In this paper, we develop dynamic state space models with hierarchical Bayesian settings to tackle this challenge for inferring the dynamic profiles and genetic networks associated with disease treatments. We treat both the stochastic transition matrix and the observation matrix time-variant and include temporal correlation structures in the covariance matrix estimations in the multivariate Bayesian state space models. The unevenly spaced short time courses with unseen time points are treated as hidden state variables. Hierarchical Bayesian approaches with various prior and hyper-prior models with Monte Carlo Markov Chain and Gibbs sampling algorithms are used to estimate the model parameters and the hidden state variables. We apply the proposed Hierarchical Bayesian state space models to multiple tissues (liver, skeletal muscle, and kidney) Affymetrix time course data sets following corticosteroid (CS) drug administration. Both simulation and real data analysis results show that the genomic changes over time and gene-gene interaction in response to CS treatment can be well captured by the proposed models. The proposed dynamic Hierarchical Bayesian state space modeling approaches could be expanded and applied to other large scale genomic data, such as next generation sequence (NGS) combined with real time and time varying electronic health record (EHR) for more comprehensive and robust systematic and network based analysis in order to transform big biomedical data into predictions and diagnostics for precision medicine and personalized healthcare with better decision making and patient outcomes.

Application of data mining techniques to explore predictors of HCC in Egyptian patients with HCV-related chronic liver disease.

PubMed

Omran, Dalia Abd El Hamid; Awad, AbuBakr Hussein; Mabrouk, Mahasen Abd El Rahman; Soliman, Ahmad Fouad; Aziz, Ashraf Omar Abdel

2015-01-01

Hepatocellular carcinoma (HCC) is the second most common malignancy in Egypt. Data mining is a method of predictive analysis which can explore tremendous volumes of information to discover hidden patterns and relationships. Our aim here was to develop a non-invasive algorithm for prediction of HCC. Such an algorithm should be economical, reliable, easy to apply and acceptable by domain experts. This cross-sectional study enrolled 315 patients with hepatitis C virus (HCV) related chronic liver disease (CLD); 135 HCC, 116 cirrhotic patients without HCC and 64 patients with chronic hepatitis C. Using data mining analysis, we constructed a decision tree learning algorithm to predict HCC. The decision tree algorithm was able to predict HCC with recall (sensitivity) of 83.5% and precession (specificity) of 83.3% using only routine data. The correctly classified instances were 259 (82.2%), and the incorrectly classified instances were 56 (17.8%). Out of 29 attributes, serum alpha fetoprotein (AFP), with an optimal cutoff value of ≥50.3 ng/ml was selected as the best predictor of HCC. To a lesser extent, male sex, presence of cirrhosis, AST>64U/L, and ascites were variables associated with HCC. Data mining analysis allows discovery of hidden patterns and enables the development of models to predict HCC, utilizing routine data as an alternative to CT and liver biopsy. This study has highlighted a new cutoff for AFP (≥50.3 ng/ml). Presence of a score of >2 risk variables (out of 5) can successfully predict HCC with a sensitivity of 96% and specificity of 82%.

Preparation of name and address data for record linkage using hidden Markov models

PubMed Central

Churches, Tim; Christen, Peter; Lim, Kim; Zhu, Justin Xi

2002-01-01

Background Record linkage refers to the process of joining records that relate to the same entity or event in one or more data collections. In the absence of a shared, unique key, record linkage involves the comparison of ensembles of partially-identifying, non-unique data items between pairs of records. Data items with variable formats, such as names and addresses, need to be transformed and normalised in order to validly carry out these comparisons. Traditionally, deterministic rule-based data processing systems have been used to carry out this pre-processing, which is commonly referred to as "standardisation". This paper describes an alternative approach to standardisation, using a combination of lexicon-based tokenisation and probabilistic hidden Markov models (HMMs). Methods HMMs were trained to standardise typical Australian name and address data drawn from a range of health data collections. The accuracy of the results was compared to that produced by rule-based systems. Results Training of HMMs was found to be quick and did not require any specialised skills. For addresses, HMMs produced equal or better standardisation accuracy than a widely-used rule-based system. However, acccuracy was worse when used with simpler name data. Possible reasons for this poorer performance are discussed. Conclusion Lexicon-based tokenisation and HMMs provide a viable and effort-effective alternative to rule-based systems for pre-processing more complex variably formatted data such as addresses. Further work is required to improve the performance of this approach with simpler data such as names. Software which implements the methods described in this paper is freely available under an open source license for other researchers to use and improve. PMID:12482326

Design of double fuzzy clustering-driven context neural networks.

PubMed

Kim, Eun-Hu; Oh, Sung-Kwun; Pedrycz, Witold

2018-08-01

In this study, we introduce a novel category of double fuzzy clustering-driven context neural networks (DFCCNNs). The study is focused on the development of advanced design methodologies for redesigning the structure of conventional fuzzy clustering-based neural networks. The conventional fuzzy clustering-based neural networks typically focus on dividing the input space into several local spaces (implied by clusters). In contrast, the proposed DFCCNNs take into account two distinct local spaces called context and cluster spaces, respectively. Cluster space refers to the local space positioned in the input space whereas context space concerns a local space formed in the output space. Through partitioning the output space into several local spaces, each context space is used as the desired (target) local output to construct local models. To complete this, the proposed network includes a new context layer for reasoning about context space in the output space. In this sense, Fuzzy C-Means (FCM) clustering is useful to form local spaces in both input and output spaces. The first one is used in order to form clusters and train weights positioned between the input and hidden layer, whereas the other one is applied to the output space to form context spaces. The key features of the proposed DFCCNNs can be enumerated as follows: (i) the parameters between the input layer and hidden layer are built through FCM clustering. The connections (weights) are specified as constant terms being in fact the centers of the clusters. The membership functions (represented through the partition matrix) produced by the FCM are used as activation functions located at the hidden layer of the "conventional" neural networks. (ii) Following the hidden layer, a context layer is formed to approximate the context space of the output variable and each node in context layer means individual local model. The outputs of the context layer are specified as a combination of both weights formed as linear function and the outputs of the hidden layer. The weights are updated using the least square estimation (LSE)-based method. (iii) At the output layer, the outputs of context layer are decoded to produce the corresponding numeric output. At this time, the weighted average is used and the weights are also adjusted with the use of the LSE scheme. From the viewpoint of performance improvement, the proposed design methodologies are discussed and experimented with the aid of benchmark machine learning datasets. Through the experiments, it is shown that the generalization abilities of the proposed DFCCNNs are better than those of the conventional FCNNs reported in the literature. Copyright © 2018 Elsevier Ltd. All rights reserved.

How Genes Modulate Patterns of Aging-Related Changes on the Way to 100: Biodemographic Models and Methods in Genetic Analyses of Longitudinal Data

PubMed Central

Yashin, Anatoliy I.; Arbeev, Konstantin G.; Wu, Deqing; Arbeeva, Liubov; Kulminski, Alexander; Kulminskaya, Irina; Akushevich, Igor; Ukraintseva, Svetlana V.

2016-01-01

Background and Objective To clarify mechanisms of genetic regulation of human aging and longevity traits, a number of genome-wide association studies (GWAS) of these traits have been performed. However, the results of these analyses did not meet expectations of the researchers. Most detected genetic associations have not reached a genome-wide level of statistical significance, and suffered from the lack of replication in the studies of independent populations. The reasons for slow progress in this research area include low efficiency of statistical methods used in data analyses, genetic heterogeneity of aging and longevity related traits, possibility of pleiotropic (e.g., age dependent) effects of genetic variants on such traits, underestimation of the effects of (i) mortality selection in genetically heterogeneous cohorts, (ii) external factors and differences in genetic backgrounds of individuals in the populations under study, the weakness of conceptual biological framework that does not fully account for above mentioned factors. One more limitation of conducted studies is that they did not fully realize the potential of longitudinal data that allow for evaluating how genetic influences on life span are mediated by physiological variables and other biomarkers during the life course. The objective of this paper is to address these issues. Data and Methods We performed GWAS of human life span using different subsets of data from the original Framingham Heart Study cohort corresponding to different quality control (QC) procedures and used one subset of selected genetic variants for further analyses. We used simulation study to show that approach to combining data improves the quality of GWAS. We used FHS longitudinal data to compare average age trajectories of physiological variables in carriers and non-carriers of selected genetic variants. We used stochastic process model of human mortality and aging to investigate genetic influence on hidden biomarkers of aging and on dynamic interaction between aging and longevity. We investigated properties of genes related to selected variants and their roles in signaling and metabolic pathways. Results We showed that the use of different QC procedures results in different sets of genetic variants associated with life span. We selected 24 genetic variants negatively associated with life span. We showed that the joint analyses of genetic data at the time of bio-specimen collection and follow up data substantially improved significance of associations of selected 24 SNPs with life span. We also showed that aging related changes in physiological variables and in hidden biomarkers of aging differ for the groups of carriers and non-carriers of selected variants. Conclusions . The results of these analyses demonstrated benefits of using biodemographic models and methods in genetic association studies of these traits. Our findings showed that the absence of a large number of genetic variants with deleterious effects may make substantial contribution to exceptional longevity. These effects are dynamically mediated by a number of physiological variables and hidden biomarkers of aging. The results of these research demonstrated benefits of using integrative statistical models of mortality risks in genetic studies of human aging and longevity. PMID:27773987

Behavioral and Temporal Pattern Detection Within Financial Data With Hidden Information

DTIC Science & Technology

2012-02-01

probabilistic pattern detector to monitor the pattern. 15. SUBJECT TERMS Runtime verification, Hidden data, Hidden Markov models, Formal specifications...sequences in many other fields besides financial systems [L, TV, LC, LZ ]. Rather, the technique suggested in this paper is positioned as a hybrid...operation of the pattern detector . Section 7 describes the operation of the probabilistic pattern-matching monitor, and section 8 describes three

Image Steganography for Hidden Communication

DTIC Science & Technology

2000-04-01

ARMY RESEARCH LABORATORY Image Steganography for Hidden Communication by Lisa M. Marvel sx:8 lÄPSilll msmmmmsi IH :’:-:’X^:-:-:-:o-x...2000 Image Steganography for Hidden Communication Lisa M. Marvel Information Science and Technology Directorate, ARL Approved for public release...Capacity for Image Steganography 14 3.4 Summary 1’ 4. Spread Spectrum Image Steganography (SSIS) 19 4.1 Modulation 21 4.1.1 Sign-Detector System

2015 Cataloging Hidden Special Collections and Archives Unconference and Symposium: Innovation, Collaboration, and Models. Proceedings of the CLIR Cataloging Hidden Special Collections and Archives Symposium (Philadelphia, Pennsylvania, March 12-13, 2015)

ERIC Educational Resources Information Center

Oestreicher, Cheryl, Ed.

2015-01-01

The 2015 CLIR Unconference & Symposium was the capstone event to seven years of grant funding through CLIR's Cataloging Hidden Special Collections and Archives program. These proceedings group presentations by theme. Collaborations provides examples of multi-institutional projects, including one international collaboration; Student and Faculty…

The Hidden Messages of Secondary Reading Programs: What Students Learn vs. What Teachers Teach.

ERIC Educational Resources Information Center

Battraw, Judith L.

Hidden messages are part of the culture of reading at any school, particularly at the secondary level. In many schools, the overt message that reading is essential to success on state-mandated tests and in society is jeopardized due to hidden messages about the nature of the reading process and the place of reading in everyday life. A qualitative…

[Becoming doctor: Highlight the hidden curriculum. Medical error as an example].

PubMed

Galam, Eric

2014-04-01

Medical culture is both individual and collective. It is also implicit, hidden (hidden curriculum) and binding.It spreads and builds from the beginning of the training.It strongly impacts the personalities and professional care practices. Awareness of its existence and identification of its main lines are the first steps for fruitful research. Copyright © 2013 Elsevier Masson SAS. All rights reserved.

The effect of newly induced mutations on the fitness of genotypes and populations of yeast (Saccharomyces cerevisiae).

PubMed

Orthen, E; Lange, P; Wöhrmann, K

1984-12-01

This paper analyses the fate of artificially induced mutations and their importance to the fitness of populations of the yeast, Saccharomyces cerevisiae, an increasingly important model organism in population genetics. Diploid strains, treated with UV and EMS, were cultured asexually for approximately 540 generations and under conditions where the asexual growth was interrupted by a sexual phase. Growth rates of 100 randomly sampled diploid clones were estimated at the beginning and at the end of the experiment. After the induction of sporulation the growth rates of 100 randomly sampled spores were measured. UV and EMS treatment decreases the average growth rate of the clones significantly but increases the variability in comparison to the untreated control. After selection over approximately 540 generations, variability in growth rates was reduced to that of the untreated control. No increase in mean population fitness was observed. However, the results show that after selection there still exists a large amount of hidden genetic variability in the populations which is revealed when the clones are cultivated in environments other than those in which selection took place. A sexual phase increased the reduction of the induced variability.

Gauge mediation scenario with hidden sector renormalization in MSSM

NASA Astrophysics Data System (ADS)

Arai, Masato; Kawai, Shinsuke; Okada, Nobuchika

2010-02-01

We study the hidden sector effects on the mass renormalization of a simplest gauge-mediated supersymmetry breaking scenario. We point out that possible hidden sector contributions render the soft scalar masses smaller, resulting in drastically different sparticle mass spectrum at low energy. In particular, in the 5+5¯ minimal gauge-mediated supersymmetry breaking with high messenger scale (that is favored by the gravitino cold dark matter scenario), we show that a stau can be the next lightest superparticle for moderate values of hidden sector self-coupling. This provides a very simple theoretical model of long-lived charged next lightest superparticles, which imply distinctive signals in ongoing and upcoming collider experiments.

Resonant conversions of QCD axions into hidden axions and suppressed isocurvature perturbations

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

Kitajima, Naoya; Takahashi, Fuminobu, E-mail: kitajima@tuhep.phys.tohoku.ac.jp, E-mail: fumi@tuhep.phys.tohoku.ac.jp

2015-01-01

We study in detail MSW-like resonant conversions of QCD axions into hidden axions, including cases where the adiabaticity condition is only marginally satisfied, and where anharmonic effects are non-negligible. When the resonant conversion is efficient, the QCD axion abundance is suppressed by the hidden and QCD axion mass ratio. We find that, when the resonant conversion is incomplete due to a weak violation of the adiabaticity, the CDM isocurvature perturbations can be significantly suppressed, while non-Gaussianity of the isocurvature perturbations generically remain unsuppressed. The isocurvature bounds on the inflation scale can therefore be relaxed by the partial resonant conversion ofmore » the QCD axions into hidden axions.« less

Mind wandering at the fingertips: automatic parsing of subjective states based on response time variability

PubMed Central

Bastian, Mikaël; Sackur, Jérôme

2013-01-01

Research from the last decade has successfully used two kinds of thought reports in order to assess whether the mind is wandering: random thought-probes and spontaneous reports. However, none of these two methods allows any assessment of the subjective state of the participant between two reports. In this paper, we present a step by step elaboration and testing of a continuous index, based on response time variability within Sustained Attention to Response Tasks (N = 106, for a total of 10 conditions). We first show that increased response time variability predicts mind wandering. We then compute a continuous index of response time variability throughout full experiments and show that the temporal position of a probe relative to the nearest local peak of the continuous index is predictive of mind wandering. This suggests that our index carries information about the subjective state of the subject even when he or she is not probed, and opens the way for on-line tracking of mind wandering. Finally we proceed a step further and infer the internal attentional states on the basis of the variability of response times. To this end we use the Hidden Markov Model framework, which allows us to estimate the durations of on-task and off-task episodes. PMID:24046753

Information asymmetry, social networking site word of mouth, and mobility effects on social commerce in Korea.

PubMed

Hwang, In Jeong; Lee, Bong Gyou; Kim, Ki Youn

2014-02-01

The purpose of this research is to examine the issues that affect customers' behavioral character and purchasing behavior. The study proposes a research hypothesis with independent variables that include social presence, trust, and information asymmetry, and the dependent variable purchase decision making, to explain differentiated customer decision making processes in social commerce (S-commerce). To prove the hypothesis, positive verification was performed by focusing on mediating effects through a customer uncertainty variable and moderating effects through mobility and social networking site word of mouth (SNS WOM) variables. The number of studies on customer trends has rapidly increased together with the market size of S-commerce. However, few studies have examined the negative variables that make customers hesitant to make decisions in S-commerce. This study investigates the causes of customer uncertainty and focuses on deducing the control variables that offset this negative relationship. The study finds that in customers' S-commerce purchasing actions, the SNS WOM and mobility variables show control effects between information asymmetry and uncertainty and between trust and uncertainty. Additionally, this research defines the variables related to customer uncertainty that are hidden in S-commerce, and statistically verifies their relationship. The research results can be used in Internet marketing practices to establish marketing mix strategies for customer demand or as research data to predict customer behavior. The results are scientifically meaningful as a precedent for research on customers in S-commerce.

Hidden sector dark matter and the Galactic Center gamma-ray excess: a closer look

DOE PAGES

Escudero, Miguel; Witte, Samuel J.; Hooper, Dan

2017-11-24

Stringent constraints from direct detection experiments and the Large Hadron Collider motivate us to consider models in which the dark matter does not directly couple to the Standard Model, but that instead annihilates into hidden sector particles which ultimately decay through small couplings to the Standard Model. We calculate the gamma-ray emission generated within the context of several such hidden sector models, including those in which the hidden sector couples to the Standard Model through the vector portal (kinetic mixing with Standard Model hypercharge), through the Higgs portal (mixing with the Standard Model Higgs boson), or both. In each case,more » we identify broad regions of parameter space in which the observed spectrum and intensity of the Galactic Center gamma-ray excess can easily be accommodated, while providing an acceptable thermal relic abundance and remaining consistent with all current constraints. Here, we also point out that cosmic-ray antiproton measurements could potentially discriminate some hidden sector models from more conventional dark matter scenarios.« less

A TWO-STATE MIXED HIDDEN MARKOV MODEL FOR RISKY TEENAGE DRIVING BEHAVIOR

PubMed Central

Jackson, John C.; Albert, Paul S.; Zhang, Zhiwei

2016-01-01

This paper proposes a joint model for longitudinal binary and count outcomes. We apply the model to a unique longitudinal study of teen driving where risky driving behavior and the occurrence of crashes or near crashes are measured prospectively over the first 18 months of licensure. Of scientific interest is relating the two processes and predicting crash and near crash outcomes. We propose a two-state mixed hidden Markov model whereby the hidden state characterizes the mean for the joint longitudinal crash/near crash outcomes and elevated g-force events which are a proxy for risky driving. Heterogeneity is introduced in both the conditional model for the count outcomes and the hidden process using a shared random effect. An estimation procedure is presented using the forward–backward algorithm along with adaptive Gaussian quadrature to perform numerical integration. The estimation procedure readily yields hidden state probabilities as well as providing for a broad class of predictors. PMID:27766124

Characteristics of Hidden Status Among Users of Crack, Powder Cocaine, and Heroin in Central Harlem

PubMed Central

Davis, W. Rees; Johnson, Bruce D.; Liberty, Hilary James; Randolph, Doris D.

2007-01-01

This article analyzes hidden status among crack, powder cocaine, and heroin users and setters, in contrast to more accessible users/sellers. Several sampling strategies acquired 657 users (N=559) and sellers (N=98). Indicators of hidden status were those who (1) paid rent in full in the last 30 days, (2) used nonstreet drug procurement. (3) had legal jobs, and (4) earned $1,000 or more in legal income in the last 30 days. Nearly half had at least one indicator: approximately 16% of users/sellers had two to four indicators. In logistic regression analyses, those who had not panhandled in the last 30 days, those who had used powder cocaine in the last 30 days, and those never arrested were the most likely to have hidden status, whether the analysis predicted those having any indicators or those having two to four indicators. The four indicators begin to operationally define hidden status among users of cocaine and heroin. PMID:17710217

Singlet scalar top partners from accidental supersymmetry

NASA Astrophysics Data System (ADS)

Cheng, Hsin-Chia; Li, Lingfeng; Salvioni, Ennio; Verhaaren, Christopher B.

2018-05-01

We present a model wherein the Higgs mass is protected from the quadratic one-loop top quark corrections by scalar particles that are complete singlets under the Standard Model (SM) gauge group. While bearing some similarity to Folded Supersymmetry, the construction is purely four dimensional and enjoys more parametric freedom, allowing electroweak symmetry breaking to occur easily. The cancelation of the top loop quadratic divergence is ensured by a Z 3 symmetry that relates the SM top sector and two hidden top sectors, each charged under its own hidden color group. In addition to the singlet scalars, the hidden sectors contain electroweak-charged supermultiplets below the TeV scale, which provide the main access to this model at colliders. The phenomenology presents both differences and similarities with respect to other realizations of neutral naturalness. Generally, the glueballs of hidden color have longer decay lengths. The production of hidden sector particles results in quirk or squirk bound states, which later annihilate. We survey the possible signatures and corresponding experimental constraints.

Hidden Sector Dark Matter and the Galactic Center Gamma-Ray Excess: A Closer Look

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

Escudero, Miguel; Witte, Samuel J.; Hooper, Dan

2017-09-20

Stringent constraints from direct detection experiments and the Large Hadron Collider motivate us to consider models in which the dark matter does not directly couple to the Standard Model, but that instead annihilates into hidden sector particles which ultimately decay through small couplings to the Standard Model. We calculate the gamma-ray emission generated within the context of several such hidden sector models, including those in which the hidden sector couples to the Standard Model through the vector portal (kinetic mixing with Standard Model hypercharge), through the Higgs portal (mixing with the Standard Model Higgs boson), or both. In each case,more » we identify broad regions of parameter space in which the observed spectrum and intensity of the Galactic Center gamma-ray excess can easily be accommodated, while providing an acceptable thermal relic abundance and remaining consistent with all current constraints. We also point out that cosmic-ray antiproton measurements could potentially discriminate some hidden sector models from more conventional dark matter scenarios.« less

Hidden sector dark matter and the Galactic Center gamma-ray excess: a closer look

NASA Astrophysics Data System (ADS)

Escudero, Miguel; Witte, Samuel J.; Hooper, Dan

2017-11-01

Stringent constraints from direct detection experiments and the Large Hadron Collider motivate us to consider models in which the dark matter does not directly couple to the Standard Model, but that instead annihilates into hidden sector particles which ultimately decay through small couplings to the Standard Model. We calculate the gamma-ray emission generated within the context of several such hidden sector models, including those in which the hidden sector couples to the Standard Model through the vector portal (kinetic mixing with Standard Model hypercharge), through the Higgs portal (mixing with the Standard Model Higgs boson), or both. In each case, we identify broad regions of parameter space in which the observed spectrum and intensity of the Galactic Center gamma-ray excess can easily be accommodated, while providing an acceptable thermal relic abundance and remaining consistent with all current constraints. We also point out that cosmic-ray antiproton measurements could potentially discriminate some hidden sector models from more conventional dark matter scenarios.

Hidden sector dark matter and the Galactic Center gamma-ray excess: a closer look

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

Escudero, Miguel; Witte, Samuel J.; Hooper, Dan

Stringent constraints from direct detection experiments and the Large Hadron Collider motivate us to consider models in which the dark matter does not directly couple to the Standard Model, but that instead annihilates into hidden sector particles which ultimately decay through small couplings to the Standard Model. We calculate the gamma-ray emission generated within the context of several such hidden sector models, including those in which the hidden sector couples to the Standard Model through the vector portal (kinetic mixing with Standard Model hypercharge), through the Higgs portal (mixing with the Standard Model Higgs boson), or both. In each case,more » we identify broad regions of parameter space in which the observed spectrum and intensity of the Galactic Center gamma-ray excess can easily be accommodated, while providing an acceptable thermal relic abundance and remaining consistent with all current constraints. Here, we also point out that cosmic-ray antiproton measurements could potentially discriminate some hidden sector models from more conventional dark matter scenarios.« less

Single-hidden-layer feed-forward quantum neural network based on Grover learning.

PubMed

Liu, Cheng-Yi; Chen, Chein; Chang, Ching-Ter; Shih, Lun-Min

2013-09-01

In this paper, a novel single-hidden-layer feed-forward quantum neural network model is proposed based on some concepts and principles in the quantum theory. By combining the quantum mechanism with the feed-forward neural network, we defined quantum hidden neurons and connected quantum weights, and used them as the fundamental information processing unit in a single-hidden-layer feed-forward neural network. The quantum neurons make a wide range of nonlinear functions serve as the activation functions in the hidden layer of the network, and the Grover searching algorithm outstands the optimal parameter setting iteratively and thus makes very efficient neural network learning possible. The quantum neuron and weights, along with a Grover searching algorithm based learning, result in a novel and efficient neural network characteristic of reduced network, high efficient training and prospect application in future. Some simulations are taken to investigate the performance of the proposed quantum network and the result show that it can achieve accurate learning. Copyright © 2013 Elsevier Ltd. All rights reserved.

Chimpanzees (Pan troglodytes) use markers to monitor the movement of a hidden item.

PubMed

Beran, Michael J; Beran, Mary M; Menzel, Charles R

2005-10-01

Four chimpanzees (Pan troglodytes) monitored the movement of hidden items in arrays of opaque cups. A chocolate candy was hidden in an array of four cups and temporarily presented paper markers indicated the location of the candy (which otherwise was not visible). These markers were either non-symbolic or symbolic (lexigram) stimuli that in other contexts acted as a label for the hidden candy, and the array was either rotated 180 degrees after the marker was removed or the array remained in the same location. For three of four chimpanzees, performance was better than chance in all conditions and there was no effect of the type of marker. These experiments indicate that chimpanzees can track the movement of a hidden item in an array of identical cups even when they never see the item itself, but only see a temporarily presented marker for the location of that item. However, there was no benefit to the use of symbolic as opposed to non-symbolic stimuli in this performance.

Rejoice in unexpected gifts from parrots and butterflies

NASA Astrophysics Data System (ADS)

Lakhtakia, Akhlesh

2016-04-01

New biological structures usually evolve from gradual modifications of old structures. Sometimes, biological structures contain hidden features, possibly vestigial. In addition to learning about functionalities, mechanisms, and structures readily apparent in nature, one must be alive to hidden features that could be useful. This aspect of engineered biomimicry is exemplified by two optical structures of psittacine and lepidopteran provenances. In both examples, a schemochrome is hidden by pigments.

A two particle hidden sector and the oscillations with photons

NASA Astrophysics Data System (ADS)

Alvarez, Pedro D.; Arias, Paola; Maldonado, Carlos

2018-01-01

We present a detailed study of the oscillations and optical properties for vacuum, in a model for the dark sector that contains axion-like particles and hidden photons. We provide bounds for the couplings versus the mass, using current results from ALPS-I and PVLAS. We also discuss the challenges for the detection of models with more than one hidden particle in light shining trough wall-like experiments.

Hidden symmetries of Eisenhart-Duval lift metrics and the Dirac equation with flux

NASA Astrophysics Data System (ADS)

Cariglia, Marco

2012-10-01

The Eisenhart-Duval lift allows embedding nonrelativistic theories into a Lorentzian geometrical setting. In this paper we study the lift from the point of view of the Dirac equation and its hidden symmetries. We show that dimensional reduction of the Dirac equation for the Eisenhart-Duval metric in general gives rise to the nonrelativistic Lévy-Leblond equation in lower dimension. We study in detail in which specific cases the lower dimensional limit is given by the Dirac equation, with scalar and vector flux, and the relation between lift, reduction, and the hidden symmetries of the Dirac equation. While there is a precise correspondence in the case of the lower dimensional massive Dirac equation with no flux, we find that for generic fluxes it is not possible to lift or reduce all solutions and hidden symmetries. As a by-product of this analysis, we construct new Lorentzian metrics with special tensors by lifting Killing-Yano and closed conformal Killing-Yano tensors and describe the general conformal Killing-Yano tensor of the Eisenhart-Duval lift metrics in terms of lower dimensional forms. Last, we show how, by dimensionally reducing the higher dimensional operators of the massless Dirac equation that are associated with shared hidden symmetries, it is possible to recover hidden symmetry operators for the Dirac equation with flux.

A market on both "sides" of the law: The use of the hidden web for the sale of new psychoactive substances.

PubMed

Wadsworth, Elle; Drummond, Colin; Kimergård, Andreas; Deluca, Paolo

2017-05-01

The hidden Web is used for the anonymous sale of drugs, and with the UK Psychoactive Substances Act, 2016, implemented on May 26th 2016; it could increase as a platform for obtaining new psychoactive substances (NPS). This study aims to describe the NPS market on the visible and hidden Web preban, and assess whether the hidden Web is a likely place for the sale of NPS postban. Data collection of 113 online shops took place in October 2015. Data collection of 22 cryptomarkets took place every 2 months from October 2015 to 2016 as part of the CASSANDRA project. All online shops with a UK domain location sold NPS that were uncontrolled by the UK Misuse of Drugs Act, 1971, and closed after the ban. Of the cryptomarkets analysed, the total number of vendors selling NPS, number of substances, and listings advertised, all increased over the year. The majority of the NPS advertised on the hidden Web were phenethylamines and cathinones, yet the majority of uncontrolled NPS were synthetic cannabinoids. Vendors selling and availability of NPS increased over the 12 months of data collection. Potential displacement from the visible Web to hidden Web should be taken into consideration. Copyright © 2017 John Wiley & Sons, Ltd.

Non-Equilibrium Effects on the Hidden Order of Microstructured URu2Si2

NASA Astrophysics Data System (ADS)

Winter, Laurel E.; Moll, Philip J. W.; Ramshaw, B. J.; Shekhter, Arkady; Harrison, N.; Bauer, Eric D.; McDonald, Ross D.

Despite extensive studies on the heavy-fermion URu2Si2, the order parameter associated with the hidden order state has yet to be established. It is known, however that the hidden order can be suppressed with pressure and high magnetic fields, which results in the development of antiferromagnetism, and the realization of a polarized state respectively. Focused Ion Beam lithography (FIB) of URu2Si2 has enabled high magnetic field observation of quantum oscillations in the resistance, indicating the preservation of sample quality to micron scale structures. These recent advances in FIB lithography have enabled the application of unprecedented electric fields while minimizing the effects of Joule heating in highly conductive metals at cryogenic temperatures. To this end, we have been able to create the necessary sample geometry to study the effect of an electric field upon hidden order in magnetic fields up to 15 T. Preliminary results suggest that above a characteristic threshold electric field, hidden order is suppressed revealing a state with similar magnetoresistive properties to the Kondo lattice in the absence of hidden order. Work supported by US Dept. of Energy through LANL/LDRD Program and G.T. Seaborg Institute, as well as NSF DMR-1157490 and the State of Florida.

The Hidden Ethics Curriculum in Two Canadian Psychiatry Residency Programs: A Qualitative Study.

PubMed

Gupta, Mona; Forlini, Cynthia; Lenton, Keith; Duchen, Raquel; Lohfeld, Lynne

2016-08-01

The authors describe the hidden ethics curriculum in two postgraduate psychiatry programs. Researchers investigated the formal, informal, and hidden ethics curricula at two demographically different postgraduate psychiatry programs in Canada. Using a case study design, they compared three sources: individual interviews with residents and with faculty and a semi-structured review of program documents. They identified the formal, informal, and hidden curricula at each program for six ethics topics and grouped the topics under two thematic areas. They tested the applicability of the themes against the specific examples under each topic. Results pertaining to one of the themes and its three topics are reported here. Divergences occurred between the curricula for each topic. The nature of these divergences differed according to local program characteristics. Yet, in both programs, choices for action in ethically challenging situations were mediated by a minimum standard of ethics that led individuals to avoid trouble even if this meant their behavior fell short of the accepted ideal. Effective ethics education in postgraduate psychiatry training will require addressing the hidden curriculum. In addition to profession-wide efforts to articulate high-level values, program-specific action on locally relevant issues constitutes a necessary mechanism for handling the impact of the hidden curriculum.

Hidden treasures - 50 km points of interests

NASA Astrophysics Data System (ADS)

Lommi, Matias; Kortelainen, Jaana

2015-04-01

Tampere is third largest city in Finland and a regional centre. During 70's there occurred several communal mergers. Nowadays this local area has both strong and diversed identity - from wilderness and agricultural fields to high density city living. Outside the city center there are interesting geological points unknown for modern city settlers. There is even a local proverb, "Go abroad to Teisko!". That is the area the Hidden Treasures -student project is focused on. Our school Tammerkoski Upper Secondary School (or Gymnasium) has emphasis on visual arts. We are going to offer our art students scientific and artistic experiences and knowledge about the hidden treasures of Teisko area and involve the Teisko inhabitants into this project. Hidden treasures - Precambrian subduction zone and a volcanism belt with dense bed of gold (Au) and arsenic (As), operating goldmines and quarries of minerals and metamorphic slates. - North of subduction zone a homogenic precambrian magmastone area with quarries, products known as Kuru Grey. - Former ashores of post-glasial Lake Näsijärvi and it's sediments enabled the developing agriculture and sustained settlement. Nowadays these ashores have both scenery and biodiversity values. - Old cattle sheds and dairy buildings made of local granite stones related to cultural stonebuilding inheritance. - Local active community of Kapee, about 100 inhabitants. Students will discover information of these "hidden" phenomena, and rendering this information trough Enviromental Art Method. Final form of this project will be published in several artistic and informative geocaches. These caches are achieved by a GPS-based special Hidden Treasures Cycling Route and by a website guiding people to find these hidden points of interests.

Hidden in plain sight: the formal, informal, and hidden curricula of a psychiatry clerkship.

PubMed

Wear, Delese; Skillicorn, Jodie

2009-04-01

To examine perceptions of the formal, informal, and hidden curricula in psychiatry as they are observed and experienced by (1) attending physicians who have teaching responsibilities for residents and medical students, (2) residents who are taught by those same physicians and who have teaching responsibilities for medical students, and (3) medical students who are taught by attendings and residents during their psychiatry rotation. From June to November 2007, the authors conducted focus groups with attendings, residents, and students in one midwestern academic setting. The sessions were audiotaped, transcribed, and analyzed for themes surrounding the formal, informal, and hidden curricula. All three groups offered a similar belief that the knowledge, skills, and values of the formal curriculum focused on building relationships. Similarly, all three suggested that elements of the informal and hidden curricula were expressed primarily as the values arising from attendings' role modeling, as the nature and amount of time attendings spend with patients, and as attendings' advice arising from experience and intuition versus "textbook learning." Whereas students and residents offered negative values arising from the informal and hidden curricula, attendings did not, offering instead the more positive values they intended to encourage through the informal and hidden curricula. The process described here has great potential in local settings across all disciplines. Asking teachers and learners in any setting to think about how they experience the educational environment and what sense they make of all curricular efforts can provide a reality check for educators and a values check for learners as they critically reflect on the meanings of what they are learning.

Empowering students with the hidden curriculum.

PubMed

Neve, Hilary; Collett, Tracey

2017-11-27

The hidden curriculum (HC) refers to unscripted, ad hoc learning that occurs outside the formal, taught curriculum and can have a powerful influence on the professional development of students. While this learning may be positive, it may conflict with that taught in the formal curriculum. Medical schools take a range of steps to address these negative effects; however, the existence and nature of the concept tends to be hidden from students. Since 2007, our medical school has incorporated into its small group programme an educational activity exploring the concept of the hidden curriculum. We undertook a qualitative evaluation of our intervention, conducting a thematic analysis of students' wiki reflections about the HC. We also analysed students' responses to a short questionnaire about the educational approach used. The majority of students felt that the HC session was important and relevant. Most appeared able to identify positive and negative HC experiences and consider how these might influence their learning and development, although a few students found the concept of the HC hard to grasp. Revealing and naming the hidden curriculum can make students aware of its existence and understand its potential impact. The hidden curriculum may also be a useful tool for triggering debate about issues such as power, patient centredness, personal resilience and career stereotypes in medicine. Supporting students to think critically about HC experiences may empower them to make active choices about which messages to take on board. The hidden curriculum can have a powerful influence on the professional development of students. © 2017 John Wiley & Sons Ltd and The Association for the Study of Medical Education.

You've got to know the rules to play the game: how medical students negotiate the hidden curriculum of surgical careers.

PubMed

Hill, Elspeth; Bowman, Katherine; Stalmeijer, Renée; Hart, Jo

2014-09-01

The hidden curriculum may be framed as the culture, beliefs and behaviours of a community that are passed to students outside formal course offerings. Medical careers involve diverse specialties, each with a different culture, yet how medical students negotiate these cultures has not been fully explored. Using surgery as a case study, we aimed to establish, first, whether a specialty-specific hidden curriculum existed for students, and second, how students encountered and negotiated surgical career options. Using a constructivist grounded theory approach, we explored students' thoughts, beliefs and experiences regarding career decisions and surgery. An exploratory questionnaire informed the discussion schedule for semi-structured individual interviews. Medical students were purposively sampled by year group, gender and career intentions in surgery. Data collection and analysis were iterative: analysis followed each interview and guided the adaptation of our discussion schedule to further our evolving model. Students held a clear sense of a hidden curriculum in surgery. To successfully negotiate a surgical career, students perceived that they must first build networks because careers information flows through relationships. They subsequently enacted what they learned by accruing the accolades ('ticking the boxes') and appropriating the dispositions ('walking the talk') of 'future surgeons'. This allowed them to identify themselves and to be identified by others as 'future surgeons' and to gain access to participation in the surgical world. Participation then enabled further network building and access to careers information in a positive feedback loop. For some, negotiating the hidden curriculum was more difficult, which, for them, rendered a surgical career unattractive or unattainable. Students perceive a clear surgery-specific hidden curriculum. Using a constructivist grounded theory approach, we have developed a model of how students encounter, uncover and enact this hidden curriculum to succeed. Drawing on concepts of Bourdieu, we discuss unequal access to the hidden curriculum, which was found to exclude many from the possibility of a surgical career. © 2014 John Wiley & Sons Ltd.

About the relationships among variables observed in the real world

NASA Astrophysics Data System (ADS)

Petkov, Boyan H.

2018-06-01

Since a stationary chaotic system is determined by nonlinear equations connecting its components, the appurtenance of two variables to such a system has been considered a sign of nontrivial relationships between them including also other quantities. These relationships could remain hidden for the approach usually employed in the research analyses, which is based on the extent of the correlation that characterises the dependence of one variable on the other. The appurtenance to the same system can be hypothesized if the topological features of the attractors reconstructed from two time series representing the evolution of the corresponding variables are close to each other. However, the possibility that both attractors represent different systems with similar behaviour cannot be excluded. For that reason, an approach allowing the reconstruction of the attractor by using jointly two time series was proposed and the conclusion about the common origin of the variables under study can be made if this attractor is topologically similar to those built separately from the two time series. In the present study, the features of the attractors were presented by the correlation dimension and the largest Lyapunov exponent and the proposed algorithm has been tested on numerically generated sequences obtained from various maps. It is believed that this approach could be used to reveal connections among the variables observed in experiments or field measurements.

The role of beginner’s luck in learning to prefer risky patches by socially foraging house sparrows

PubMed Central

2013-01-01

Although there has been extensive research on the evolution of individual decision making under risk (when facing variable outcomes), little is known on how the evolution of such decision-making mechanisms has been shaped by social learning and exploitation. We presented socially foraging house sparrows with a choice between scattered feeding wells in which millet seeds were hidden under 2 types of colored sand: green sand offering ~80 seeds with a probability of 0.1 (high risk–high reward) and yellow sand offering 1 seed with certainty (low risk–low reward). Although the expected benefit of choosing variable wells was 8 times higher than that of choosing constant wells, only some sparrows developed a preference for variable wells, whereas others developed a significant preference for constant wells. We found that this dichotomy could be explained by stochastic individual differences in sampling success during foraging, rather than by social foraging strategies (active searching vs. joining others). Moreover, preference for variable or constant wells was related to the sparrows’ success during searching, rather than during joining others or when picking exposed seeds (i.e., they learn when actively searching in the sand). Finally, although for many sparrows learning resulted in an apparently maladaptive risk aversion, group living still allowed them to enjoy profitable variable wells by occasionally joining variable-preferring sparrows. PMID:24137046

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

Miyadera, Takayuki; Imai, Hideki; Graduate School of Science and Engineering, Chuo University, 1-13-27 Kasuga, Bunkyo-ku, Tokyo 112-8551

This paper discusses the no-cloning theorem in a logicoalgebraic approach. In this approach, an orthoalgebra is considered as a general structure for propositions in a physical theory. We proved that an orthoalgebra admits cloning operation if and only if it is a Boolean algebra. That is, only classical theory admits the cloning of states. If unsharp propositions are to be included in the theory, then a notion of effect algebra is considered. We proved that an atomic Archimedean effect algebra admitting cloning operation is a Boolean algebra. This paper also presents a partial result, indicating a relation between the cloningmore » on effect algebras and hidden variables.« less

Critical reflections on methodological challenge in arts and dementia evaluation and research.

PubMed

Gray, Karen; Evans, Simon Chester; Griffiths, Amanda; Schneider, Justine

2017-01-01

Methodological rigour, or its absence, is often a focus of concern for the emerging field of evaluation and research around arts and dementia. However, this paper suggests that critical attention should also be paid to the way in which individual perceptions, hidden assumptions and underlying social and political structures influence methodological work in the field. Such attention will be particularly important for addressing methodological challenges relating to contextual variability, ethics, value judgement and signification identified through a literature review on this topic. Understanding how, where and when evaluators and researchers experience such challenges may help to identify fruitful approaches for future evaluation.

Conditional maximum-entropy method for selecting prior distributions in Bayesian statistics

NASA Astrophysics Data System (ADS)

Abe, Sumiyoshi

2014-11-01

The conditional maximum-entropy method (abbreviated here as C-MaxEnt) is formulated for selecting prior probability distributions in Bayesian statistics for parameter estimation. This method is inspired by a statistical-mechanical approach to systems governed by dynamics with largely separated time scales and is based on three key concepts: conjugate pairs of variables, dimensionless integration measures with coarse-graining factors and partial maximization of the joint entropy. The method enables one to calculate a prior purely from a likelihood in a simple way. It is shown, in particular, how it not only yields Jeffreys's rules but also reveals new structures hidden behind them.

Measuring correlations in non-separable vector beams using projective measurements

NASA Astrophysics Data System (ADS)

Subramanian, Keerthan; Viswanathan, Nirmal K.

2017-09-01

Doubts regarding the completeness of quantum mechanics as raised by Einstein, Podolsky and Rosen(EPR) have predominantly been resolved by resorting to a measurement of correlations between entangled photons which clearly demonstrate violation of Bell's inequality. This article is an attempt to reconcile incompatibility of hidden variable theories with reality by demonstrating experimentally a violation of Bell's inequality in locally correlated systems whose two degrees of freedom, the spin and orbital angular momentum, are maximally correlated. To this end we propose and demonstrate a linear, achromatic modified Sagnac interferometer to project orbital angular momentum states which we combine with spin projections to measure correlations.

How transfer flights shape the structure of the airline network.

PubMed

Ryczkowski, Tomasz; Fronczak, Agata; Fronczak, Piotr

2017-07-17

In this paper, we analyse the gravity model in the global passenger air-transport network. We show that in the standard form, the model is inadequate for correctly describing the relationship between passenger flows and typical geo-economic variables that characterize connected countries. We propose a model for transfer flights that allows exploitation of these discrepancies in order to discover hidden subflows in the network. We illustrate its usefulness by retrieving the distance coefficient in the gravity model, which is one of the determinants of the globalization process. Finally, we discuss the correctness of the presented approach by comparing the distance coefficient to several well-known economic events.

Hyperthyroidism hidden by congenital central hypoventilation syndrome.

PubMed

Fox, Danya A; Weese-Mayer, Debra E; Wensley, David F; Stewart, Laura L

2015-05-01

Congenital central hypoventilation syndrome (CCHS) is a rare neurocristopathy with severe central hypoventilation. CCHS results from a mutation in the paired-like homeobox 2B gene (PHOX2B). In addition to hypoventilation, patients with CCHS display a wide array of autonomic nervous system abnormalities, including decreased heart rate variability and abrupt sinus pauses, esophageal dysmotility, abnormal pupillary light response, and temperature dysregulation, to name a few. To date, there has been no documentation of a child with both CCHS and hyperthyroidism. We report the case of a young child with CCHS who presented with tachycardia, which was later found to be due to Grave's disease, after many months of investigation.

Testing Bell's inequality with cosmic photons: closing the setting-independence loophole.

PubMed

Gallicchio, Jason; Friedman, Andrew S; Kaiser, David I

2014-03-21

We propose a practical scheme to use photons from causally disconnected cosmic sources to set the detectors in an experimental test of Bell's inequality. In current experiments, with settings determined by quantum random number generators, only a small amount of correlation between detector settings and local hidden variables, established less than a millisecond before each experiment, would suffice to mimic the predictions of quantum mechanics. By setting the detectors using pairs of quasars or patches of the cosmic microwave background, observed violations of Bell's inequality would require any such coordination to have existed for billions of years-an improvement of 20 orders of magnitude.

Studying Climate Response to Forcing by the Nonlinear Dynamical Mode Decomposition

NASA Astrophysics Data System (ADS)

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

2017-04-01

An analysis of global climate response to external forcing, both anthropogenic (mainly, CO2 and aerosol) and natural (solar and volcanic), is needed for adequate predictions of global climate change. Being complex dynamical system, the climate reacts to external perturbations exciting feedbacks (both positive and negative) making the response non-trivial and poorly predictable. Thus an extraction of internal modes of climate system, investigation of their interaction with external forcings and further modeling and forecast of their dynamics, are all the problems providing the success of climate modeling. In the report the new method for principal mode extraction from climate data is presented. The method is based on the Nonlinear Dynamical Mode (NDM) expansion [1,2], but takes into account a number of external forcings applied to the system. Each NDM is represented by hidden time series governing the observed variability, which, together with external forcing time series, are mapped onto data space. While forcing time series are considered to be known, the hidden unknown signals underlying the internal climate dynamics are extracted from observed data by the suggested method. In particular, it gives us an opportunity to study the evolution of principal system's mode structure in changing external conditions and separate the internal climate variability from trends forced by external perturbations. Furthermore, the modes so obtained can be extrapolated beyond the observational time series, and long-term prognosis of modes' structure including characteristics of interconnections and responses to external perturbations, can be carried out. In this work the method is used for reconstructing and studying the principal modes of climate variability on inter-annual and decadal time scales accounting the external forcings such as anthropogenic emissions, variations of the solar activity and volcanic activity. The structure of the obtained modes as well as their response to external factors, e.g. forecast their change in 21 century under different CO2 emission scenarios, are discussed. [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 [2] Gavrilov, A., Mukhin, D., Loskutov, E., Volodin, E., Feigin, A., & Kurths, J. (2016). Method for reconstructing nonlinear modes with adaptive structure from multidimensional data. Chaos: An Interdisciplinary Journal of Nonlinear Science, 26(12), 123101. http://doi.org/10.1063/1.4968852

A Gradient-Field Pulsed Eddy Current Probe for Evaluation of Hidden Material Degradation in Conductive Structures Based on Lift-Off Invariance

PubMed Central

Li, Yong; Jing, Haoqing; Zainal Abidin, Ilham Mukriz; Yan, Bei

2017-01-01

Coated conductive structures are widely adopted in such engineering fields as aerospace, nuclear energy, etc. The hostile and corrosive environment leaves in-service coated conductive structures vulnerable to Hidden Material Degradation (HMD) occurring under the protection coating. It is highly demanded that HMD can be non-intrusively assessed using non-destructive evaluation techniques. In light of the advantages of Gradient-field Pulsed Eddy Current technique (GPEC) over other non-destructive evaluation methods in corrosion evaluation, in this paper the GPEC probe for quantitative evaluation of HMD is intensively investigated. Closed-form expressions of GPEC responses to HMD are formulated via analytical modeling. The Lift-off Invariance (LOI) in GPEC signals, which makes the HMD evaluation immune to the variation in thickness of the protection coating, is introduced and analyzed through simulations involving HMD with variable depths and conductivities. A fast inverse method employing magnitude and time of the LOI point in GPEC signals for simultaneously evaluating the conductivity and thickness of HMD region is proposed, and subsequently verified by finite element modeling and experiments. It has been found from the results that along with the proposed inverse method the GPEC probe is applicable to evaluation of HMD in coated conductive structures without much loss in accuracy. PMID:28441328

Differential expression analysis for RNAseq using Poisson mixed models

PubMed Central

Sun, Shiquan; Hood, Michelle; Scott, Laura; Peng, Qinke; Mukherjee, Sayan; Tung, Jenny

2017-01-01

Abstract Identifying differentially expressed (DE) genes from RNA sequencing (RNAseq) studies is among the most common analyses in genomics. However, RNAseq DE analysis presents several statistical and computational challenges, including over-dispersed read counts and, in some settings, sample non-independence. Previous count-based methods rely on simple hierarchical Poisson models (e.g. negative binomial) to model independent over-dispersion, but do not account for sample non-independence due to relatedness, population structure and/or hidden confounders. Here, we present a Poisson mixed model with two random effects terms that account for both independent over-dispersion and sample non-independence. We also develop a scalable sampling-based inference algorithm using a latent variable representation of the Poisson distribution. With simulations, we show that our method properly controls for type I error and is generally more powerful than other widely used approaches, except in small samples (n <15) with other unfavorable properties (e.g. small effect sizes). We also apply our method to three real datasets that contain related individuals, population stratification or hidden confounders. Our results show that our method increases power in all three data compared to other approaches, though the power gain is smallest in the smallest sample (n = 6). Our method is implemented in MACAU, freely available at www.xzlab.org/software.html. PMID:28369632

A characterization of performance by men and women in a virtual Morris water task: a large and reliable sex difference.

PubMed

Astur, R S; Ortiz, M L; Sutherland, R J

1998-06-01

In many mammalian species, it is known that males and females differ in place learning ability. The performance by men and women is commonly reported to also differ, despite a large amount of variability and ambiguity in measuring spatial abilities. In the non-human literature, the gold standard for measuring place learning ability in mammals is the Morris water task. This task requires subjects to use the spatial arrangement of cues outside of a circular pool to swim to a hidden goal platform located in a fixed location. We used a computerized version of the Morris water task to assess whether this task will generalize into the human domain and to examine whether sex differences exist in this domain of topographical learning and memory. Across three separate experiments, varying in attempts to maximize spatial performance, we consistently found males navigate to the hidden platform better than females across a variety of measures. The effect sizes of these differences are some of the largest ever reported and are robust and replicable across experiments. These results are the first to demonstrate the effectiveness and utility of the virtual Morris water task for humans and show a robust sex difference in virtual place learning.

QRS complex detection based on continuous density hidden Markov models using univariate observations

NASA Astrophysics Data System (ADS)

Sotelo, S.; Arenas, W.; Altuve, M.

2018-04-01

In the electrocardiogram (ECG), the detection of QRS complexes is a fundamental step in the ECG signal processing chain since it allows the determination of other characteristics waves of the ECG and provides information about heart rate variability. In this work, an automatic QRS complex detector based on continuous density hidden Markov models (HMM) is proposed. HMM were trained using univariate observation sequences taken either from QRS complexes or their derivatives. The detection approach is based on the log-likelihood comparison of the observation sequence with a fixed threshold. A sliding window was used to obtain the observation sequence to be evaluated by the model. The threshold was optimized by receiver operating characteristic curves. Sensitivity (Sen), specificity (Spc) and F1 score were used to evaluate the detection performance. The approach was validated using ECG recordings from the MIT-BIH Arrhythmia database. A 6-fold cross-validation shows that the best detection performance was achieved with 2 states HMM trained with QRS complexes sequences (Sen = 0.668, Spc = 0.360 and F1 = 0.309). We concluded that these univariate sequences provide enough information to characterize the QRS complex dynamics from HMM. Future works are directed to the use of multivariate observations to increase the detection performance.

Reciprocal Markov modeling of feedback mechanisms between emotion and dietary choice using experience sampling data

PubMed Central

Lu, Ji; Pan, Junhao; Zhang, Qiang; Dubé, Laurette; Ip, Edward H.

2015-01-01

With intensively collected longitudinal data, recent advances in Experience Sampling Method (ESM) benefit social science empirical research, but also pose important methodological challenges. As traditional statistical models are not generally well-equipped to analyze a system of variables that contain feedback loops, this paper proposes the utility of an extended hidden Markov model to model reciprocal relationship between momentary emotion and eating behavior. This paper revisited an ESM data set (Lu, Huet & Dube, 2011) that observed 160 participants’ food consumption and momentary emotions six times per day in 10 days. Focusing on the analyses on feedback loop between mood and meal healthiness decision, the proposed Reciprocal Markov Model (RMM) can accommodate both hidden (“general” emotional states: positive vs. negative state) and observed states (meal: healthier, same or less healthy than usual) without presuming independence between observations and smooth trajectories of mood or behavior changes. The results of RMM analyses illustrated the reciprocal chains of meal consumption and mood as well as the effect of contextual factors that moderate the interrelationship between eating and emotion. A simulation experiment that generated data consistent to the empirical study further demonstrated that the procedure is promising in terms of recovering the parameters. PMID:26717120

Finding hidden periodic signals in time series - an application to stock prices

NASA Astrophysics Data System (ADS)

O'Shea, Michael

2014-03-01

Data in the form of time series appear in many areas of science. In cases where the periodicity is apparent and the only other contribution to the time series is stochastic in origin, the data can be `folded' to improve signal to noise and this has been done for light curves of variable stars with the folding resulting in a cleaner light curve signal. Stock index prices versus time are classic examples of time series. Repeating patterns have been claimed by many workers and include unusually large returns on small-cap stocks during the month of January, and small returns on the Dow Jones Industrial average (DJIA) in the months June through September compared to the rest of the year. Such observations imply that these prices have a periodic component. We investigate this for the DJIA. If such a component exists it is hidden in a large non-periodic variation and a large stochastic variation. We show how to extract this periodic component and for the first time reveal its yearly (averaged) shape. This periodic component leads directly to the `Sell in May and buy at Halloween' adage. We also drill down and show that this yearly variation emerges from approximately half of the underlying stocks making up the DJIA index.

Artificial neural network-aided image analysis system for cell counting.

PubMed

Sjöström, P J; Frydel, B R; Wahlberg, L U

1999-05-01

In histological preparations containing debris and synthetic materials, it is difficult to automate cell counting using standard image analysis tools, i.e., systems that rely on boundary contours, histogram thresholding, etc. In an attempt to mimic manual cell recognition, an automated cell counter was constructed using a combination of artificial intelligence and standard image analysis methods. Artificial neural network (ANN) methods were applied on digitized microscopy fields without pre-ANN feature extraction. A three-layer feed-forward network with extensive weight sharing in the first hidden layer was employed and trained on 1,830 examples using the error back-propagation algorithm on a Power Macintosh 7300/180 desktop computer. The optimal number of hidden neurons was determined and the trained system was validated by comparison with blinded human counts. System performance at 50x and lO0x magnification was evaluated. The correlation index at 100x magnification neared person-to-person variability, while 50x magnification was not useful. The system was approximately six times faster than an experienced human. ANN-based automated cell counting in noisy histological preparations is feasible. Consistent histology and computer power are crucial for system performance. The system provides several benefits, such as speed of analysis and consistency, and frees up personnel for other tasks.

ENSO Dynamics and Trends, AN Alternate View

NASA Astrophysics Data System (ADS)

Rojo Hernandez, J. D.; Lall, U.; Mesa, O. J.

2017-12-01

El Niño - Southern Oscillation (ENSO) is the most important inter-annual climate fluctuation on a planetary level with great effects on the hydrological cycle, agriculture, ecosystems, health and society. This work demonstrates the use of the Non-Homogeneus hidden Markov Models (NHMM) to characterize ENSO using a set of discrete states with variable transition probabilities matrix using the data of sea surface temperature anomalies (SSTA) of the Kaplan Extended SST v2 between 120E -90W, 15N-15S from Jan-1856 to Dec-2016. ENSO spatial patterns, their temporal distribution, the transition probabilities between patterns and their temporal evolution are the main results of the NHHMM applied to ENSO. The five "hidden" states found appear to represent the different "Flavors" described in the literature: the Canonical El Niño, Central El Niño, a Neutral state, Central La Niña and the Canonical Niña. Using the whole record length of the SSTA it was possible to identify trends in the dynamic system, with a decrease in the probability of occurrence of the cold events and a significant increase of the warm events, in particular of Central El Niño events whose probability of occurrence has increased Dramatically since 1960 coupled with increases in global temperature.

A Gradient-Field Pulsed Eddy Current Probe for Evaluation of Hidden Material Degradation in Conductive Structures Based on Lift-Off Invariance.

PubMed

Li, Yong; Jing, Haoqing; Zainal Abidin, Ilham Mukriz; Yan, Bei

2017-04-25

Coated conductive structures are widely adopted in such engineering fields as aerospace, nuclear energy, etc. The hostile and corrosive environment leaves in-service coated conductive structures vulnerable to Hidden Material Degradation (HMD) occurring under the protection coating. It is highly demanded that HMD can be non-intrusively assessed using non-destructive evaluation techniques. In light of the advantages of Gradient-field Pulsed Eddy Current technique (GPEC) over other non-destructive evaluation methods in corrosion evaluation, in this paper the GPEC probe for quantitative evaluation of HMD is intensively investigated. Closed-form expressions of GPEC responses to HMD are formulated via analytical modeling. The Lift-off Invariance (LOI) in GPEC signals, which makes the HMD evaluation immune to the variation in thickness of the protection coating, is introduced and analyzed through simulations involving HMD with variable depths and conductivities. A fast inverse method employing magnitude and time of the LOI point in GPEC signals for simultaneously evaluating the conductivity and thickness of HMD region is proposed, and subsequently verified by finite element modeling and experiments. It has been found from the results that along with the proposed inverse method the GPEC probe is applicable to evaluation of HMD in coated conductive structures without much loss in accuracy.

Machine learning in sentiment reconstruction of the simulated stock market

NASA Astrophysics Data System (ADS)

Goykhman, Mikhail; Teimouri, Ali

2018-02-01

In this paper we continue the study of the simulated stock market framework defined by the driving sentiment processes. We focus on the market environment driven by the buy/sell trading sentiment process of the Markov chain type. We apply the methodology of the Hidden Markov Models and the Recurrent Neural Networks to reconstruct the transition probabilities matrix of the Markov sentiment process and recover the underlying sentiment states from the observed stock price behavior. We demonstrate that the Hidden Markov Model can successfully recover the transition probabilities matrix for the hidden sentiment process of the Markov Chain type. We also demonstrate that the Recurrent Neural Network can successfully recover the hidden sentiment states from the observed simulated stock price time series.

Revealing hidden antiferromagnetic correlations in doped Hubbard chains via string correlators

NASA Astrophysics Data System (ADS)

Hilker, Timon A.; Salomon, Guillaume; Grusdt, Fabian; Omran, Ahmed; Boll, Martin; Demler, Eugene; Bloch, Immanuel; Gross, Christian

2017-08-01

Topological phases, like the Haldane phase in spin-1 chains, defy characterization through local order parameters. Instead, nonlocal string order parameters can be employed to reveal their hidden order. Similar diluted magnetic correlations appear in doped one-dimensional lattice systems owing to the phenomenon of spin-charge separation. Here we report on the direct observation of such hidden magnetic correlations via quantum gas microscopy of hole-doped ultracold Fermi-Hubbard chains. The measurement of nonlocal spin-density correlation functions reveals a hidden finite-range antiferromagnetic order, a direct consequence of spin-charge separation. Our technique, which measures nonlocal order directly, can be readily extended to higher dimensions to study the complex interplay between magnetic order and density fluctuations.

A fast hidden line algorithm for plotting finite element models

NASA Technical Reports Server (NTRS)

Jones, G. K.

1982-01-01

Effective plotting of finite element models requires the use of fast hidden line plot techniques that provide interactive response. A high speed hidden line technique was developed to facilitate the plotting of NASTRAN finite element models. Based on testing using 14 different models, the new hidden line algorithm (JONES-D) appears to be very fast: its speed equals that for normal (all lines visible) plotting and when compared to other existing methods it appears to be substantially faster. It also appears to be very reliable: no plot errors were observed using the new method to plot NASTRAN models. The new algorithm was made part of the NPLOT NASTRAN plot package and was used by structural analysts for normal production tasks.

Hidden-Symmetry-Protected Topological Semimetals on a Square Lattice

NASA Astrophysics Data System (ADS)

Hou, Jing-Min

2013-09-01

We study a two-dimensional fermionic square lattice, which supports the existence of a two-dimensional Weyl semimetal, quantum anomalous Hall effect, and 2π-flux topological semimetal in different parameter ranges. We show that the band degenerate points of the two-dimensional Weyl semimetal and 2π-flux topological semimetal are protected by two distinct novel hidden symmetries, which both correspond to antiunitary composite operations. When these hidden symmetries are broken, a gap opens between the conduction and valence bands, turning the system into a insulator. With appropriate parameters, a quantum anomalous Hall effect emerges. The degenerate point at the boundary between the quantum anomalous Hall insulator and trivial band insulator is also protected by the hidden symmetry.

Deep neural network with weight sparsity control and pre-training extracts hierarchical features and enhances classification performance: Evidence from whole-brain resting-state functional connectivity patterns of schizophrenia

PubMed Central

Kim, Junghoe; Calhoun, Vince D.; Shim, Eunsoo; Lee, Jong-Hwan

2015-01-01

Functional connectivity (FC) patterns obtained from resting-state functional magnetic resonance imaging data are commonly employed to study neuropsychiatric conditions by using pattern classifiers such as the support vector machine (SVM). Meanwhile, a deep neural network (DNN) with multiple hidden layers has shown its ability to systematically extract lower-to-higher level information of image and speech data from lower-to-higher hidden layers, markedly enhancing classification accuracy. The objective of this study was to adopt the DNN for whole-brain resting-state FC pattern classification of schizophrenia (SZ) patients vs. healthy controls (HCs) and identification of aberrant FC patterns associated with SZ. We hypothesized that the lower-to-higher level features learned via the DNN would significantly enhance the classification accuracy, and proposed an adaptive learning algorithm to explicitly control the weight sparsity in each hidden layer via L1-norm regularization. Furthermore, the weights were initialized via stacked autoencoder based pre-training to further improve the classification performance. Classification accuracy was systematically evaluated as a function of (1) the number of hidden layers/nodes, (2) the use of L1-norm regularization, (3) the use of the pre-training, (4) the use of framewise displacement (FD) removal, and (5) the use of anatomical/functional parcellation. Using FC patterns from anatomically parcellated regions without FD removal, an error rate of 14.2% was achieved by employing three hidden layers and 50 hidden nodes with both L1-norm regularization and pre-training, which was substantially lower than the error rate from the SVM (22.3%). Moreover, the trained DNN weights (i.e., the learned features) were found to represent the hierarchical organization of aberrant FC patterns in SZ compared with HC. Specifically, pairs of nodes extracted from the lower hidden layer represented sparse FC patterns implicated in SZ, which was quantified by using kurtosis/modularity measures and features from the higher hidden layer showed holistic/global FC patterns differentiating SZ from HC. Our proposed schemes and reported findings attained by using the DNN classifier and whole-brain FC data suggest that such approaches show improved ability to learn hidden patterns in brain imaging data, which may be useful for developing diagnostic tools for SZ and other neuropsychiatric disorders and identifying associated aberrant FC patterns. PMID:25987366

Alerts and Advisories

MedlinePlus

... Elimidrol ‘Opiate Withdrawal’ Product (FTC 09/28/17 ) Physic Candy – Define contains hidden drug ingredients ( FDA 09/11/17 ) Physic Candy – Curve contains hidden drug ingredients ( FDA 08/ ...

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

Rare Z boson decays to a hidden sector

DOE PAGES

Blinov, Nikita; Izaguirre, Eder; Shuve, Brian

2018-01-18

We demonstrate that rare decays of the Standard Model Z boson can be used to discover and characterize the nature of new hidden-sector particles. We propose new searches for these particles in soft, high-multiplicity leptonic final states at the Large Hadron Collider. The proposed searches are sensitive to low-mass particles produced in Z decays, and we argue that these striking signatures can shed light on the hidden-sector couplings and mechanism for mass generation.

Rare Z boson decays to a hidden sector

DOE PAGES

Blinov, Nikita; Izaguirre, Eder; Shuve, Brian

2018-01-01

We demonstrate that rare decays of the Standard Model Z boson can be used to discover and characterize the nature of new hidden-sector particles. We propose new searches for these particles in soft, high-multiplicity leptonic final states at the Large Hadron Collider. The proposed searches are sensitive to low-mass particles produced in Z decays, and we argue that these striking signatures can shed light on the hidden-sector couplings and mechanism for mass generation.

Experimental search for hidden photon CDM in the eV mass range with a dish antenna

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

Suzuki, J.; Horie, T.; Inoue, Y.

2015-09-15

A search for hidden photon cold dark matter (HP CDM) using a new technique with a dish antenna is reported. From the result of the measurement, we found no evidence for the existence of HP CDM and set an upper limit on the photon-HP mixing parameter χ of ∼6×10{sup −12} for the hidden photon mass m{sub γ}=3.1±1.2 eV.

Rare Z boson decays to a hidden sector

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

Blinov, Nikita; Izaguirre, Eder; Shuve, Brian

We demonstrate that rare decays of the Standard Model Z boson can be used to discover and characterize the nature of new hidden-sector particles. We propose new searches for these particles in soft, high-multiplicity leptonic final states at the Large Hadron Collider. The proposed searches are sensitive to low-mass particles produced in Z decays, and we argue that these striking signatures can shed light on the hidden-sector couplings and mechanism for mass generation.

Hidden-sector Spectroscopy with Gravitational Waves from Binary Neutron Stars

NASA Astrophysics Data System (ADS)

Croon, Djuna; Nelson, Ann E.; Sun, Chen; Walker, Devin G. E.; Xianyu, Zhong-Zhi

2018-05-01

We show that neutron star (NS) binaries can be ideal laboratories to probe hidden sectors with a long-range force. In particular, it is possible for gravitational wave (GW) detectors such as LIGO and Virgo to resolve the correction of waveforms from ultralight dark gauge bosons coupled to NSs. We observe that the interaction of the hidden sector affects both the GW frequency and amplitude in a way that cannot be fitted by pure gravity.

Veiled EGM Jackpots: The Effects of Hidden and Mystery Jackpots on Gambling Intensity.

PubMed

Donaldson, Phillip; Langham, Erika; Rockloff, Matthew J; Browne, Matthew

2016-06-01

Understanding the impact of EGM Jackpots on gambling intensity may allow targeted strategies to be implemented that facilitate harm minimisation by acting to reduce losses of gamblers who play frequently, while maintaining the enjoyment and excitement of potential jackpots. The current study investigated the influences of Hidden and Mystery Jackpots on EGM gambling intensity. In a Hidden Jackpot, the prize value is not shown to the player, although the existence of a jackpot prize is advertised. In a Mystery Jackpot, the jackpot triggering state of the machine is unknown to players. One hundred and seven volunteers (males = 49, females = 58) played a laptop-simulated EGM with a starting $20 real-money stake and a chance to win a Jackpot ($500). Participants played for either a Hidden or Known Jackpot Value, with either a Mystery or Known winning symbol combination in a crossed design. Lastly, a control condition with no jackpot was included. Gambling intensity (speed of bets, persistence) was greater when the Jackpot value was unknown, especially when a winning-symbol combination suggested that a win was possible. While there is no evidence in the present investigation to suggest that Hidden or Mystery jackpots contribute to greater player enjoyment, there is some evidence to suggest a marginal positive contribution of hidden jackpots to risky playing behaviour.

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.

Multitask TSK fuzzy system modeling by mining intertask common hidden structure.

PubMed

Jiang, Yizhang; Chung, Fu-Lai; Ishibuchi, Hisao; Deng, Zhaohong; Wang, Shitong

2015-03-01

The classical fuzzy system modeling methods implicitly assume data generated from a single task, which is essentially not in accordance with many practical scenarios where data can be acquired from the perspective of multiple tasks. Although one can build an individual fuzzy system model for each task, the result indeed tells us that the individual modeling approach will get poor generalization ability due to ignoring the intertask hidden correlation. In order to circumvent this shortcoming, we consider a general framework for preserving the independent information among different tasks and mining hidden correlation information among all tasks in multitask fuzzy modeling. In this framework, a low-dimensional subspace (structure) is assumed to be shared among all tasks and hence be the hidden correlation information among all tasks. Under this framework, a multitask Takagi-Sugeno-Kang (TSK) fuzzy system model called MTCS-TSK-FS (TSK-FS for multiple tasks with common hidden structure), based on the classical L2-norm TSK fuzzy system, is proposed in this paper. The proposed model can not only take advantage of independent sample information from the original space for each task, but also effectively use the intertask common hidden structure among multiple tasks to enhance the generalization performance of the built fuzzy systems. Experiments on synthetic and real-world datasets demonstrate the applicability and distinctive performance of the proposed multitask fuzzy system model in multitask regression learning scenarios.

How hidden are hidden processes? A primer on crypticity and entropy convergence

NASA Astrophysics Data System (ADS)

Mahoney, John R.; Ellison, Christopher J.; James, Ryan G.; Crutchfield, James P.

2011-09-01

We investigate a stationary process's crypticity—a measure of the difference between its hidden state information and its observed information—using the causal states of computational mechanics. Here, we motivate crypticity and cryptic order as physically meaningful quantities that monitor how hidden a hidden process is. This is done by recasting previous results on the convergence of block entropy and block-state entropy in a geometric setting, one that is more intuitive and that leads to a number of new results. For example, we connect crypticity to how an observer synchronizes to a process. We show that the block-causal-state entropy is a convex function of block length. We give a complete analysis of spin chains. We present a classification scheme that surveys stationary processes in terms of their possible cryptic and Markov orders. We illustrate related entropy convergence behaviors using a new form of foliated information diagram. Finally, along the way, we provide a variety of interpretations of crypticity and cryptic order to establish their naturalness and pervasiveness. This is also a first step in developing applications in spatially extended and network dynamical systems.

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.

Hidden axion dark matter decaying through mixing with QCD axion and the 3.5 keV X-ray line

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

Higaki, Tetsutaro; Kitajima, Naoya; Takahashi, Fuminobu, E-mail: thigaki@post.kek.jp, E-mail: kitajima@tuhep.phys.tohoku.ac.jp, E-mail: fumi@tuhep.phys.tohoku.ac.jp

2014-12-01

Hidden axions may be coupled to the standard model particles through a kinetic or mass mixing with QCD axion. We study a scenario in which a hidden axion constitutes a part of or the whole of dark matter and decays into photons through the mixing, explaining the 3.5 keV X-ray line signal. Interestingly, the required long lifetime of the hidden axion dark matter can be realized for the QCD axion decay constant at an intermediate scale, if the mixing is sufficiently small. In such a two component dark matter scenario, the primordial density perturbations of the hidden axion can bemore » highly non-Gaussian, leading to a possible dispersion in the X-ray line strength from various galaxy clusters and near-by galaxies. We also discuss how the parallel and orthogonal alignment of two axions affects their couplings to gauge fields. In particular, the QCD axion decay constant can be much larger than the actual Peccei-Quinn symmetry breaking.« less

Generalizing the Network Scale-Up Method: A New Estimator for the Size of Hidden Populations*

PubMed Central

Feehan, Dennis M.; Salganik, Matthew J.

2018-01-01

The network scale-up method enables researchers to estimate the size of hidden populations, such as drug injectors and sex workers, using sampled social network data. The basic scale-up estimator offers advantages over other size estimation techniques, but it depends on problematic modeling assumptions. We propose a new generalized scale-up estimator that can be used in settings with non-random social mixing and imperfect awareness about membership in the hidden population. Further, the new estimator can be used when data are collected via complex sample designs and from incomplete sampling frames. However, the generalized scale-up estimator also requires data from two samples: one from the frame population and one from the hidden population. In some situations these data from the hidden population can be collected by adding a small number of questions to already planned studies. For other situations, we develop interpretable adjustment factors that can be applied to the basic scale-up estimator. We conclude with practical recommendations for the design and analysis of future studies. PMID:29375167

Factors influencing infants’ ability to update object representations in memory

PubMed Central

Moher, Mariko; Feigenson, Lisa

2013-01-01

Remembering persisting objects over occlusion is critical to representing a stable environment. Infants remember hidden objects at multiple locations and can update their representation of a hidden array when an object is added or subtracted. However, the factors influencing these updating abilities have received little systematic exploration. Here we examined the flexibility of infants’ ability to update object representations. We tested 11-month-olds in a looking-time task in which objects were added to or subtracted from two hidden arrays. Across five experiments, infants successfully updated their representations of hidden arrays when the updating occurred successively at one array before beginning at the other. But when updating required alternating between two arrays, infants failed. However, simply connecting the two arrays with a thin strip of foam-core led infants to succeed. Our results suggest that infants’ construal of an event strongly affects their ability to update memory representations of hidden objects. When construing an event as containing multiple updates to the same array, infants succeed, but when construing the event as requiring the revisiting and updating of previously attended arrays, infants fail. PMID:24049245

Sacrificial bonds and hidden length in biomaterials -- a kinetic description of strength and toughness in bone

NASA Astrophysics Data System (ADS)

Lieou, Charles K. C.; Elbanna, Ahmed E.; Carlson, Jean M.

2013-03-01

Sacrificial bonds and hidden length in structural molecules account for the greatly increased fracture toughness of biological materials compared to synthetic materials without such structural features, by providing a molecular-scale mechanism of energy dissipation. One example of occurrence of sacrificial bonds and hidden length is in the polymeric glue connection between collagen fibrils in animal bone. In this talk, we propose a simple kinetic model that describes the breakage of sacrificial bonds and the revelation of hidden length, based on Bell's theory. We postulate a master equation governing the rates of bond breakage and formation, at the mean-field level, allowing for the number of bonds and hidden lengths to take up non-integer values between successive, discrete bond-breakage events. This enables us to predict the mechanical behavior of a quasi-one-dimensional ensemble of polymers at different stretching rates. We find that both the rupture peak heights and maximum stretching distance increase with the stretching rate. In addition, our theory naturally permits the possibility of self-healing in such biological structures.

First Direct-Detection Constraints on eV-Scale Hidden-Photon Dark Matter with DAMIC at SNOLAB

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

Aguilar-Arevalo, A.; Amidei, D.; Bertou, X.

We present direct detection constraints on the absorption of hidden-photon dark matter with particle masses in the range 1.2-30 eVmore » $$c^{-2}$$ with the DAMIC experiment at SNOLAB. Under the assumption that the local dark matter is entirely constituted of hidden photons, the sensitivity to the kinetic mixing parameter $$\\kappa$$ is competitive with constraints from solar emission, reaching a minimum value of 2.2$$\\times$$$10^{-14}$$ at 17 eV$$c^{-2}$$. These results are the most stringent direct detection constraints on hidden-photon dark matter with masses 3-12 eV$$c^{-2}$$ and the first demonstration of direct experimental sensitivity to ionization signals $<$12 eV from dark matter interactions.« less

Hidden One-Dimensional Electronic Structure of η-Mo_4O_11

NASA Astrophysics Data System (ADS)

Gweon, G.-H.; Mo, S.-K.; Allen, J. W.; Höchst, H.; Sarrao, J. L.; Fisk, Z.

2002-03-01

η-Mo_4O_11 is a layered metal that undergoes two charge density wave (CDW) transitions at 109 K and 30 K, and is unique in showing a bulk quantum Hall effect. Research so far indicates that this material has a ``hidden one-dimensional'' (hidden-1d) Fermi surface (FS) in the normal state (T > 109 K), whose nesting property drives the 109 K CDW formation. Here, we directly confirm this picture by angle resolved photoemission spectroscopy (ARPES). We also observe a gap opening associated with the 109 K transition. Most interesting, this material shows the same ARPES line shape anomalies that suggest electron fractionalization in other hidden-1d materials like NaMo_6O_17 and KMo_6O_17. Studies of the 30 K transition are in progress.

NPLOT: an Interactive Plotting Program for NASTRAN Finite Element Models

NASA Technical Reports Server (NTRS)

Jones, G. K.; Mcentire, K. J.

1985-01-01

The NPLOT (NASTRAN Plot) is an interactive computer graphics program for plotting undeformed and deformed NASTRAN finite element models. Developed at NASA's Goddard Space Flight Center, the program provides flexible element selection and grid point, ASET and SPC degree of freedom labelling. It is easy to use and provides a combination menu and command driven user interface. NPLOT also provides very fast hidden line and haloed line algorithms. The hidden line algorithm in NPLOT proved to be both very accurate and several times faster than other existing hidden line algorithms. A fast spatial bucket sort and horizon edge computation are used to achieve this high level of performance. The hidden line and the haloed line algorithms are the primary features that make NPLOT different from other plotting programs.

Flu Widget

MedlinePlus

... 0" width="300" title="Flu I.Q. Widget" style="overflow: hidden;"> Flu ... 0" width="280" title="CDC Flu Vaccine Finder" style="overflow: hidden;"> FluView Widget < ...

Experimental search for hidden photon CDM in the eV mass range with a dish antenna

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

Suzuki, J.; Horie, T.; Minowa, M.

2015-09-01

A search for hidden photon cold dark matter (HP CDM) using a new technique with a dish antenna is reported. From the result of the measurement, we found no evidence for the existence of HP CDM and set an upper limit on the photon-HP mixing parameter χ of ∼ 6× 10{sup −12} for the hidden photon mass m{sub γ} = 3.1 ± 1.2 eV.

DYNA3D, INGRID, and TAURUS: an integrated, interactive software system for crashworthiness engineering

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

Benson, D.J.; Hallquist, J.O.; Stillman, D.W.

1985-04-01

Crashworthiness engineering has always been a high priority at Lawrence Livermore National Laboratory because of its role in the safe transport of radioactive material for the nuclear power industry and military. As a result, the authors have developed an integrated, interactive set of finite element programs for crashworthiness analysis. The heart of the system is DYNA3D, an explicit, fully vectorized, large deformation structural dynamics code. DYNA3D has the following four capabilities that are critical for the efficient and accurate analysis of crashes: (1) fully nonlinear solid, shell, and beam elements for representing a structure, (2) a broad range of constitutivemore » models for representing the materials, (3) sophisticated contact algorithms for the impact interactions, and (4) a rigid body capability to represent the bodies away from the impact zones at a greatly reduced cost without sacrificing any accuracy in the momentum calculations. To generate the large and complex data files for DYNA3D, INGRID, a general purpose mesh generator, is used. It runs on everything from IBM PCs to CRAYS, and can generate 1000 nodes/minute on a PC. With its efficient hidden line algorithms and many options for specifying geometry, INGRID also doubles as a geometric modeller. TAURUS, an interactive post processor, is used to display DYNA3D output. In addition to the standard monochrome hidden line display, time history plotting, and contouring, TAURUS generates interactive color displays on 8 color video screens by plotting color bands superimposed on the mesh which indicate the value of the state variables. For higher quality color output, graphic output files may be sent to the DICOMED film recorders. We have found that color is every bit as important as hidden line removal in aiding the analyst in understanding his results. In this paper the basic methodologies of the programs are presented along with several crashworthiness calculations.« less

Hidden Semi-Markov Models and Their Application

NASA Astrophysics Data System (ADS)

Beyreuther, M.; Wassermann, J.

2008-12-01

In the framework of detection and classification of seismic signals there are several different approaches. Our choice for a more robust detection and classification algorithm is to adopt Hidden Markov Models (HMM), a technique showing major success in speech recognition. HMM provide a powerful tool to describe highly variable time series based on a double stochastic model and therefore allow for a broader class description than e.g. template based pattern matching techniques. Being a fully probabilistic model, HMM directly provide a confidence measure of an estimated classification. Furthermore and in contrast to classic artificial neuronal networks or support vector machines, HMM are incorporating the time dependence explicitly in the models thus providing a adequate representation of the seismic signal. As the majority of detection algorithms, HMM are not based on the time and amplitude dependent seismogram itself but on features estimated from the seismogram which characterize the different classes. Features, or in other words characteristic functions, are e.g. the sonogram bands, instantaneous frequency, instantaneous bandwidth or centroid time. In this study we apply continuous Hidden Semi-Markov Models (HSMM), an extension of continuous HMM. The duration probability of a HMM is an exponentially decaying function of the time, which is not a realistic representation of the duration of an earthquake. In contrast HSMM use Gaussians as duration probabilities, which results in an more adequate model. The HSMM detection and classification system is running online as an EARTHWORM module at the Bavarian Earthquake Service. Here the signals that are to be classified simply differ in epicentral distance. This makes it possible to easily decide whether a classification is correct or wrong and thus allows to better evaluate the advantages and disadvantages of the proposed algorithm. The evaluation is based on several month long continuous data and the results are additionally compared to the previously published discrete HMM, continuous HMM and a classic STA/LTA. The intermediate evaluation results are very promising.

NUCLEAR X-RAY PROPERTIES OF THE PECULIAR RADIO-LOUD HIDDEN AGN 4C+29.30

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

Sobolewska, M. A.; Siemiginowska, Aneta; Migliori, G.

2012-10-20

We present results from a study of nuclear emission from a nearby radio galaxy, 4C+29.30, over a broad 0.5-200 keV X-ray band. This study used new XMM-Newton ({approx}17 ks) and Chandra ({approx}300 ks) data, and archival Swift/BAT data from the 58 month catalog. The hard (>2 keV) X-ray spectrum of 4C+29.30 can be decomposed into an intrinsic hard power law ({Gamma} {approx} 1.56) modified by a cold absorber with an intrinsic column density N {sub H,z} {approx} 5 Multiplication-Sign 10{sup 23} cm{sup -2}, and its reflection (|{Omega}/2{pi}| {approx} 0.3) from a neutral matter including a narrow iron K{alpha} emission linemore » at a rest-frame energy {approx}6.4 keV. The reflected component is less absorbed than the intrinsic one with an upper limit on the absorbing column of N {sup refl} {sub H,z} < 2.5 Multiplication-Sign 10{sup 22} cm{sup -2}. The X-ray spectrum varied between the XMM-Newton and Chandra observations. We show that a scenario invoking variations of the normalization of the power law is favored over a model with variable intrinsic column density. X-rays in the 0.5-2 keV band are dominated by diffuse emission modeled with a thermal bremsstrahlung component with temperature {approx}0.7 keV, and contain only a marginal contribution from the scattered power-law component. We hypothesize that 4C+29.30 belongs to a class of 'hidden' active galactic nuclei containing a geometrically thick torus. However, unlike the majority of hidden AGNs, 4C+29.30 is radio-loud. Correlations between the scattering fraction and Eddington luminosity ratio, and between black hole mass and stellar velocity dispersion, imply that 4C+29.30 hosts a black hole with {approx}10{sup 8} M {sub Sun} mass.« less

Unsupervised deep learning reveals prognostically relevant subtypes of glioblastoma.

PubMed

Young, Jonathan D; Cai, Chunhui; Lu, Xinghua

2017-10-03

One approach to improving the personalized treatment of cancer is to understand the cellular signaling transduction pathways that cause cancer at the level of the individual patient. In this study, we used unsupervised deep learning to learn the hierarchical structure within cancer gene expression data. Deep learning is a group of machine learning algorithms that use multiple layers of hidden units to capture hierarchically related, alternative representations of the input data. We hypothesize that this hierarchical structure learned by deep learning will be related to the cellular signaling system. Robust deep learning model selection identified a network architecture that is biologically plausible. Our model selection results indicated that the 1st hidden layer of our deep learning model should contain about 1300 hidden units to most effectively capture the covariance structure of the input data. This agrees with the estimated number of human transcription factors, which is approximately 1400. This result lends support to our hypothesis that the 1st hidden layer of a deep learning model trained on gene expression data may represent signals related to transcription factor activation. Using the 3rd hidden layer representation of each tumor as learned by our unsupervised deep learning model, we performed consensus clustering on all tumor samples-leading to the discovery of clusters of glioblastoma multiforme with differential survival. One of these clusters contained all of the glioblastoma samples with G-CIMP, a known methylation phenotype driven by the IDH1 mutation and associated with favorable prognosis, suggesting that the hidden units in the 3rd hidden layer representations captured a methylation signal without explicitly using methylation data as input. We also found differentially expressed genes and well-known mutations (NF1, IDH1, EGFR) that were uniquely correlated with each of these clusters. Exploring these unique genes and mutations will allow us to further investigate the disease mechanisms underlying each of these clusters. In summary, we show that a deep learning model can be trained to represent biologically and clinically meaningful abstractions of cancer gene expression data. Understanding what additional relationships these hidden layer abstractions have with the cancer cellular signaling system could have a significant impact on the understanding and treatment of cancer.

The hidden universe

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

Disney, M.

1985-01-01

Astronomer Disney has followed a somewhat different tack than that of most popular books on cosmology by concentrating on the notion of hidden (as in not directly observable by its own radiation) matter in the universe.

It Twins! Spitzer Finds Hidden Jet

NASA Image and Video Library

2011-04-04

NASA Spitzer Space Telescope took this image of a baby star sprouting two identical jets green lines emanating from fuzzy star. The left jet was hidden behind a dark cloud, which Spitzer can see through.

SECTION L FROM FLAGPOLE TOWARD SOLDIERS AND SAILORS MONUMENT (HIDDEN ...

Library of Congress Historic Buildings Survey, Historic Engineering Record, Historic Landscapes Survey

SECTION L FROM FLAGPOLE TOWARD SOLDIERS AND SAILORS MONUMENT (HIDDEN BY TREES). VIEW TO SOUTHEAST. - Bath National Cemetery, Department of Veterans Affairs Medical Center, San Juan Avenue, Bath, Steuben County, NY

A neural network based computational model to predict the output power of different types of photovoltaic cells.

PubMed

Xiao, WenBo; Nazario, Gina; Wu, HuaMing; Zhang, HuaMing; Cheng, Feng

2017-01-01

In this article, we introduced an artificial neural network (ANN) based computational model to predict the output power of three types of photovoltaic cells, mono-crystalline (mono-), multi-crystalline (multi-), and amorphous (amor-) crystalline. The prediction results are very close to the experimental data, and were also influenced by numbers of hidden neurons. The order of the solar generation power output influenced by the external conditions from smallest to biggest is: multi-, mono-, and amor- crystalline silicon cells. In addition, the dependences of power prediction on the number of hidden neurons were studied. For multi- and amorphous crystalline cell, three or four hidden layer units resulted in the high correlation coefficient and low MSEs. For mono-crystalline cell, the best results were achieved at the hidden layer unit of 8.

Hidden Nanobubbles in Undersaturated Liquids.

PubMed

Guo, Zhenjiang; Liu, Yawei; Xiao, Qianxiang; Zhang, Xianren

2016-11-01

Here, we propose theoretically the existence of a new type of nanobubble in undersaturated liquids. These nanobubbles have a concave vapor-liquid interface featured with a negative curvature rather than a positive curvature for nanobubbles in supersaturated liquids, so that they often hide inside of the substrate textures and it might not be easy to characterize them through atomic force microscopy (AFM) measurements. However, these hidden nanobubbles are still stabilized by the contact line pinning effect and stay at the thermodynamically metastable state. We further demonstrate that similar to the nanobubbles in supersaturated liquids the contact angle of the hidden nanobubbles is more sensitive to the nanobubble size rather than the substrate chemistry, and their curvature radius is dependent on the chemical potential but independent of the base radius. Finally, we show several potential situations for the appearance of the hidden nanobubbles.

First Direct-Detection Constraints on eV-Scale Hidden-Photon Dark Matter with DAMIC at SNOLAB.

PubMed

Aguilar-Arevalo, A; Amidei, D; Bertou, X; Butner, M; Cancelo, G; Castañeda Vázquez, A; Cervantes Vergara, B A; Chavarria, A E; Chavez, C R; de Mello Neto, J R T; D'Olivo, J C; Estrada, J; Fernandez Moroni, G; Gaïor, R; Guardincerri, Y; Hernández Torres, K P; Izraelevitch, F; Kavner, A; Kilminster, B; Lawson, I; Letessier-Selvon, A; Liao, J; Matalon, A; Mello, V B B; Molina, J; Privitera, P; Ramanathan, K; Sarkis, Y; Schwarz, T; Settimo, M; Sofo Haro, M; Thomas, R; Tiffenberg, J; Tiouchichine, E; Torres Machado, D; Trillaud, F; You, X; Zhou, J

2017-04-07

We present direct detection constraints on the absorption of hidden-photon dark matter with particle masses in the range 1.2-30  eV c^{-2} with the DAMIC experiment at SNOLAB. Under the assumption that the local dark matter is entirely constituted of hidden photons, the sensitivity to the kinetic mixing parameter κ is competitive with constraints from solar emission, reaching a minimum value of 2.2×10^{-14} at 17  eV c^{-2}. These results are the most stringent direct detection constraints on hidden-photon dark matter in the galactic halo with masses 3-12  eV c^{-2} and the first demonstration of direct experimental sensitivity to ionization signals <12  eV from dark matter interactions.

Hidden-Symmetry-Protected Topological Semimetals on a Square Lattice

NASA Astrophysics Data System (ADS)

Hou, Jing-Min

2014-03-01

We study a two-dimensional fermionic square lattice, which supports the existence of two-dimensional Weyl semimetal, quantum anomalous Hall effect, and 2 π -flux topological semimetal in different parameter ranges. We show that the band degenerate points of the two-dimensional Weyl semimetal and 2 π -flux topological semimetal are protected by two distinct novel hidden symmetries, which both corresponds to antiunitary composite operations. When these hidden symmetries are broken, a gap opens between the conduction and valence bands, turning the system into a insulator. With appropriate parameters, a quantum anomalous Hall effect emerges. The degenerate point at the boundary between the quantum anomalous Hall insulator and trivial band insulator is also protected by the hidden symmetry. [PRL 111, 130403(2013)] This work was supported by the National Natural Science Foundation of China under Grants No. 11004028 and No. 11274061.

Intuitive optics: what great apes infer from mirrors and shadows.

PubMed

Völter, Christoph J; Call, Josep

2018-05-02

There is ongoing debate about the extent to which nonhuman animals, like humans, can go beyond first-order perceptual information to abstract structural information from their environment. To provide more empirical evidence regarding this question, we examined what type of information great apes (chimpanzees, bonobos, and orangutans) gain from optical effects such as shadows and mirror images. In an initial experiment, we investigated whether apes would use mirror images and shadows to locate hidden food. We found that all examined ape species used these cues to find the food. Follow-up experiments showed that apes neither confused these optical effects with the food rewards nor did they merely associate cues with food. First, naïve chimpanzees used the shadow of the hidden food to locate it but they did not learn within the same number of trials to use a perceptually similar rubber patch as indicator of the hidden food reward. Second, apes made use of the mirror images to estimate the distance of the hidden food from their own body. Depending on the distance, apes either pointed into the direction of the food or tried to access the hidden food directly. Third, apes showed some sensitivity to the geometrical relation between mirror orientation and mirrored objects when searching hidden food. Fourth, apes tended to interpret mirror images and pictures of these mirror images differently depending on their prior knowledge. Together, these findings suggest that apes are sensitive to the optical relation between mirror images and shadows and their physical referents.

Complex Sequencing Rules of Birdsong Can be Explained by Simple Hidden Markov Processes

PubMed Central

Katahira, Kentaro; Suzuki, Kenta; Okanoya, Kazuo; Okada, Masato

2011-01-01

Complex sequencing rules observed in birdsongs provide an opportunity to investigate the neural mechanism for generating complex sequential behaviors. To relate the findings from studying birdsongs to other sequential behaviors such as human speech and musical performance, it is crucial to characterize the statistical properties of the sequencing rules in birdsongs. However, the properties of the sequencing rules in birdsongs have not yet been fully addressed. In this study, we investigate the statistical properties of the complex birdsong of the Bengalese finch (Lonchura striata var. domestica). Based on manual-annotated syllable labeles, we first show that there are significant higher-order context dependencies in Bengalese finch songs, that is, which syllable appears next depends on more than one previous syllable. We then analyze acoustic features of the song and show that higher-order context dependencies can be explained using first-order hidden state transition dynamics with redundant hidden states. This model corresponds to hidden Markov models (HMMs), well known statistical models with a large range of application for time series modeling. The song annotation with these models with first-order hidden state dynamics agreed well with manual annotation, the score was comparable to that of a second-order HMM, and surpassed the zeroth-order model (the Gaussian mixture model; GMM), which does not use context information. Our results imply that the hierarchical representation with hidden state dynamics may underlie the neural implementation for generating complex behavioral sequences with higher-order dependencies. PMID:21915345

Detection of latent fingerprint hidden beneath adhesive tape by optical coherence tomography.

PubMed

Zhang, Ning; Wang, Chengming; Sun, Zhenwen; Li, Zhigang; Xie, Lanchi; Yan, Yuwen; Xu, Lei; Guo, Jingjing; Huang, Wei; Li, Zhihui; Xue, Jing; Liu, Huan; Xu, Xiaojing

2018-06-01

Adhesive tape is one type of common item which can be encountered in criminal cases involving rape, murder, kidnapping and explosives. It is often the case that a suspect deposits latent fingerprints on the sticky side of adhesive tape material when tying up victims, manufacturing improvised explosive devices or packaging illegal goods. However, the adhesive tapes found at crime scenes are usually stuck together or attached to a certain substrate, and thus the latent fingerprints may be hidden beneath the tapes. Current methods to detect latent fingerprint hidden beneath adhesive tape need to peel it off first and then apply physical or chemical methods to develop the fingerprint, which undergo complicated procedures and would affect the original condition of latent print. Optical coherence tomography (OCT) is a novel applied techniques in forensics which enables obtaining cross-sectional structure with the advantages of non-invasive, in-situ, high resolution and high speed. In this paper, a custom-built spectral-domain OCT (SD-OCT) system with a hand-held probe was employed to detect fingerprints hidden beneath different types of adhesive tapes. Three-dimensional (3D) OCT reconstructions were performed and the en face images were presented to reveal the hidden fingerprints. The results demonstrate that OCT is a promising tool for rapidly detecting and recovering high quality image of latent fingerprint hidden beneath adhesive tape without any changes to the original state and preserve the integrity of the evidence. Copyright © 2018 Elsevier B.V. All rights reserved.

Simulation of electricity demand in a remote island for optimal planning of a hybrid renewable energy system

NASA Astrophysics Data System (ADS)

Koskinas, Aristotelis; Zacharopoulou, Eleni; Pouliasis, George; Engonopoulos, Ioannis; Mavroyeoryos, Konstantinos; Deligiannis, Ilias; Karakatsanis, Georgios; Dimitriadis, Panayiotis; Iliopoulou, Theano; Koutsoyiannis, Demetris; Tyralis, Hristos

2017-04-01

We simulate the electrical energy demand in the remote island of Astypalaia. To this end we first obtain information regarding the local socioeconomic conditions and energy demand. Secondly, the available hourly demand data are analysed at various time scales (hourly, weekly, daily, seasonal). The cross-correlations between the electrical energy demand and the mean daily temperature as well as other climatic variables for the same time period are computed. Also, we investigate the cross-correlation between those climatic variables and other variables related to renewable energy resources from numerous observations around the globe in order to assess the impact of each one to a hybrid renewable energy system. An exploratory data analysis including all variables is performed with the purpose to find hidden relationships. Finally, the demand is simulated considering all the periodicities found in the analysis. The simulation time series will be used in the development of a framework for planning of a hybrid renewable energy system in Astypalaia. Acknowledgement: This research is conducted within the frame of the undergraduate course "Stochastic Methods in Water Resources" of the National Technical University of Athens (NTUA). The School of Civil Engineering of NTUA provided moral support for the participation of the students in the Assembly.

Deep neural network with weight sparsity control and pre-training extracts hierarchical features and enhances classification performance: Evidence from whole-brain resting-state functional connectivity patterns of schizophrenia.

PubMed

Kim, Junghoe; Calhoun, Vince D; Shim, Eunsoo; Lee, Jong-Hwan

2016-01-01

Functional connectivity (FC) patterns obtained from resting-state functional magnetic resonance imaging data are commonly employed to study neuropsychiatric conditions by using pattern classifiers such as the support vector machine (SVM). Meanwhile, a deep neural network (DNN) with multiple hidden layers has shown its ability to systematically extract lower-to-higher level information of image and speech data from lower-to-higher hidden layers, markedly enhancing classification accuracy. The objective of this study was to adopt the DNN for whole-brain resting-state FC pattern classification of schizophrenia (SZ) patients vs. healthy controls (HCs) and identification of aberrant FC patterns associated with SZ. We hypothesized that the lower-to-higher level features learned via the DNN would significantly enhance the classification accuracy, and proposed an adaptive learning algorithm to explicitly control the weight sparsity in each hidden layer via L1-norm regularization. Furthermore, the weights were initialized via stacked autoencoder based pre-training to further improve the classification performance. Classification accuracy was systematically evaluated as a function of (1) the number of hidden layers/nodes, (2) the use of L1-norm regularization, (3) the use of the pre-training, (4) the use of framewise displacement (FD) removal, and (5) the use of anatomical/functional parcellation. Using FC patterns from anatomically parcellated regions without FD removal, an error rate of 14.2% was achieved by employing three hidden layers and 50 hidden nodes with both L1-norm regularization and pre-training, which was substantially lower than the error rate from the SVM (22.3%). Moreover, the trained DNN weights (i.e., the learned features) were found to represent the hierarchical organization of aberrant FC patterns in SZ compared with HC. Specifically, pairs of nodes extracted from the lower hidden layer represented sparse FC patterns implicated in SZ, which was quantified by using kurtosis/modularity measures and features from the higher hidden layer showed holistic/global FC patterns differentiating SZ from HC. Our proposed schemes and reported findings attained by using the DNN classifier and whole-brain FC data suggest that such approaches show improved ability to learn hidden patterns in brain imaging data, which may be useful for developing diagnostic tools for SZ and other neuropsychiatric disorders and identifying associated aberrant FC patterns. Copyright © 2015 Elsevier Inc. All rights reserved.

Hidden Broad-line Regions in Seyfert 2 Galaxies: From the Spectropolarimetric Perspective

NASA Astrophysics Data System (ADS)

Du, Pu; Wang, Jian-Min; Zhang, Zhi-Xiang

2017-05-01

The hidden broad-line regions (BLRs) in Seyfert 2 galaxies, which display broad emission lines (BELs) in their polarized spectra, are a key piece of evidence in support of the unified model for active galactic nuclei (AGNs). However, the detailed kinematics and geometry of hidden BLRs are still not fully understood. The virial factor obtained from reverberation mapping of type 1 AGNs may be a useful diagnostic of the nature of hidden BLRs in type 2 objects. In order to understand the hidden BLRs, we compile six type 2 objects from the literature with polarized BELs and dynamical measurements of black hole masses. All of them contain pseudobulges. We estimate their virial factors, and find the average value is 0.60 and the standard deviation is 0.69, which agree well with the value of type 1 AGNs with pseudobulges. This study demonstrates that (1) the geometry and kinematics of BLR are similar in type 1 and type 2 AGNs of the same bulge type (pseudobulges), and (2) the small values of virial factors in Seyfert 2 galaxies suggest that, similar to type 1 AGNs, BLRs tend to be very thick disks in type 2 objects.

Evaluation of cracks with different hidden depths and shapes using surface magnetic field measurements based on semi-analytical modelling

NASA Astrophysics Data System (ADS)

Jiang, Feng; Liu, Shulin

2018-03-01

In this paper, we present a feasibility study for detecting cracks with different hidden depths and shapes using information contained in the magnetic field excited by a rectangular coil with a rectangular cross section. First, we solve for the eigenvalues and the unknown coefficients of the magnetic vector potential by imposing artificial and natural boundary conditions. Thus, a semi-analytical solution for the magnetic field distribution around the surface of a conducting plate that contains a long hidden crack is formulated. Next, based on the proposed modelling, the influences of the different hidden depth cracks on the surface magnetic field are analysed. The results show that the horizontal and vertical components of the magnetic field near the crack are becoming weaker and that the phase information of the magnetic field can be used to qualitatively determine the hidden depth of the crack. In addition, the model is optimised to improve its accuracy in classifying crack types. The relationship between signal features and crack shapes is subsequently established. The modified model is validated by using finite element simulations, visually indicating the change in the magnetic field near the crack.

Magnetic Correlations in URu2Si2 under Chemical and Hydrostatic Pressure

NASA Astrophysics Data System (ADS)

Williams, Travis; Aczel, Adam; Broholm, Collin; Buyers, William; Leao, Juscelino; Luke, Graeme; Rodriguez-Riviera, Jose; Stone, Matthew; Wilson, Murray; Yamani, Zahra

URu2Si2 has been an intense area of study for the last 30 years due to a mysterious hidden order phase that appears below T0 = 17.5 K. The hidden order phase has been shown to be extremely sensitive to perturbations, being destroyed quickly by the application of a magnetic field, hydrostatic or uniaxial pressure, and chemical doping. While attempting to understand the properties of URu2Si2, neutron scattering has found spin correlations that are intimately related to this hidden order phase and which are also suppressed with these perturbations. Here, I will outline some recent neutron scattering work to study these correlations in two exceptional cases where the hidden order phase is enhanced: hydrostatic pressure and chemical pressure using Fe- and Os-doping. In both of these cases, T0 increases before an antiferromagnetic phase emerges. By performing a careful analysis of the neutron data, we show that these two phases are much more related than had been previously appreciated. This implies that the hidden order is likely compatible with an antiferromagnetic ground state, placing constraints on the nature of the missing order parameter.

Caries diagnosis using laser fluorescence

NASA Astrophysics Data System (ADS)

Zanin, Fatima A. A.; Pinheiro, Antonio L. B.; Souza-Campos, Dilma H.; Brugnera, Aldo, Jr.; Pecora, Jesus D.

2000-03-01

Caries prevention is a goal to be achieved by dentist in order to promote health. There are several methods used to detect dental caries each one presenting advantages and disadvantages, especially regarding hidden occlusal caries. The improvement of laser technology has permitted the use of laser fluorescence for early diagnosis of hidden occlusal caries. The aim of this study was to assess the efficacy of the use of 655 nm laser light on the detection of hidden occlusal caries. Forty molar teeth from patients of both sexes which ages ranging from 10 - 18 years old were used on this study. Following manufacture's instructions regarding the use of the equipment, the teeth had their occlusal surface examined with the DIAGNOdent. Twenty six of 40 teeth had hidden occlusal caries detected by the DIAGNOdent. However only 17 of these 26 teeth showed radiographic signs of caries the other 9 teeth showed no radiological signs of the lesion. Radiographic examination was able to identify 34,61% of false negative cases. This means that many caries would be left untreated due to the lack of diagnosis using both visual and radiographic examination. The use of the DIAGNOdent was effective in successfully detecting hidden occlusal caries.

Hidden Broad-line Regions in Seyfert 2 Galaxies: From the Spectropolarimetric Perspective

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

Du, Pu; Wang, Jian-Min; Zhang, Zhi-Xiang, E-mail: dupu@ihep.ac.cn

2017-05-01

The hidden broad-line regions (BLRs) in Seyfert 2 galaxies, which display broad emission lines (BELs) in their polarized spectra, are a key piece of evidence in support of the unified model for active galactic nuclei (AGNs). However, the detailed kinematics and geometry of hidden BLRs are still not fully understood. The virial factor obtained from reverberation mapping of type 1 AGNs may be a useful diagnostic of the nature of hidden BLRs in type 2 objects. In order to understand the hidden BLRs, we compile six type 2 objects from the literature with polarized BELs and dynamical measurements of blackmore » hole masses. All of them contain pseudobulges. We estimate their virial factors, and find the average value is 0.60 and the standard deviation is 0.69, which agree well with the value of type 1 AGNs with pseudobulges. This study demonstrates that (1) the geometry and kinematics of BLR are similar in type 1 and type 2 AGNs of the same bulge type (pseudobulges), and (2) the small values of virial factors in Seyfert 2 galaxies suggest that, similar to type 1 AGNs, BLRs tend to be very thick disks in type 2 objects.« less

A coupled hidden Markov model for disease interactions

PubMed Central

Sherlock, Chris; Xifara, Tatiana; Telfer, Sandra; Begon, Mike

2013-01-01

To investigate interactions between parasite species in a host, a population of field voles was studied longitudinally, with presence or absence of six different parasites measured repeatedly. Although trapping sessions were regular, a different set of voles was caught at each session, leading to incomplete profiles for all subjects. We use a discrete time hidden Markov model for each disease with transition probabilities dependent on covariates via a set of logistic regressions. For each disease the hidden states for each of the other diseases at a given time point form part of the covariate set for the Markov transition probabilities from that time point. This allows us to gauge the influence of each parasite species on the transition probabilities for each of the other parasite species. Inference is performed via a Gibbs sampler, which cycles through each of the diseases, first using an adaptive Metropolis–Hastings step to sample from the conditional posterior of the covariate parameters for that particular disease given the hidden states for all other diseases and then sampling from the hidden states for that disease given the parameters. We find evidence for interactions between several pairs of parasites and of an acquired immune response for two of the parasites. PMID:24223436

Perspectives of nursing and midwifery students regarding the role of the hidden curriculum in patient education: A qualitative study.

PubMed

Azadi, Zohreh; Ravanipour, Maryam; Yazdankhahfard, Mohammadreza; Motamed, Niloofar; Pouladi, Shahnaz

2017-01-01

Although education is one of the most substantial needs of patients that should be taught by nurses and midwives, it is not clearly defined through the hidden curriculum in students' teaching programs. The aim of this study was to explore the patient education through the hidden curriculum in the perspectives of nursing and midwifery students. A qualitative, content analysis study was performed and twenty nursing and midwifery students were interviewed. Data were collected using face-to-face semi-structured interviews and analyzed using conventional content analysis approach. Students' perception of the hidden curriculum in patient education emerged in three main themes concerning: (1) interactions, (2) teaching and learning opportunities, and (3) reflective evaluation. The hidden curriculum in patient education can be transferred as interactions between professors, students, nurses, doctors, and also patients who are rooted from paying attention to the human dimension of the patient, avoiding the materialistic treatment of the patient and treating the patient with dignity. Educational policies and students' assignments should be designed based on the patient's educational goals and the goal of evaluation has to be presented to the students clearly.

Perspectives of nursing and midwifery students regarding the role of the hidden curriculum in patient education: A qualitative study

PubMed Central

Azadi, Zohreh; Ravanipour, Maryam; Yazdankhahfard, Mohammadreza; Motamed, Niloofar; Pouladi, Shahnaz

2017-01-01

BACKGROUND: Although education is one of the most substantial needs of patients that should be taught by nurses and midwives, it is not clearly defined through the hidden curriculum in students’ teaching programs. The aim of this study was to explore the patient education through the hidden curriculum in the perspectives of nursing and midwifery students. MATERIALS AND METHODS: A qualitative, content analysis study was performed and twenty nursing and midwifery students were interviewed. Data were collected using face-to-face semi-structured interviews and analyzed using conventional content analysis approach. RESULTS: Students’ perception of the hidden curriculum in patient education emerged in three main themes concerning: (1) interactions, (2) teaching and learning opportunities, and (3) reflective evaluation. CONCLUSIONS: The hidden curriculum in patient education can be transferred as interactions between professors, students, nurses, doctors, and also patients who are rooted from paying attention to the human dimension of the patient, avoiding the materialistic treatment of the patient and treating the patient with dignity. Educational policies and students’ assignments should be designed based on the patient's educational goals and the goal of evaluation has to be presented to the students clearly. PMID:29296609

Foot morphometric phenomena.

PubMed

Agić, Ante

2007-06-01

Knowledge of the foot morphometry is important for proper foot structure and function. Foot structure as a vital part of human body is important for many reasons. The foot anthropometric and morphology phenomena are analyzed together with hidden biomechanical descriptors in order to fully characterize foot functionality. For Croatian student population the scatter data of the individual foot variables were interpolated by multivariate statistics. Foot morphometric descriptors are influenced by many factors, such as life style, climate, and things of great importance in human society. Dominant descriptors related to fit and comfort are determined by the use 3D foot shape and advanced foot biomechanics. Some practical recommendations and conclusions for medical, sportswear and footwear practice are highlighted.

Nonlocality in Bohmian mechanics

NASA Astrophysics Data System (ADS)

Ghafar, Zati Amalina binti Mohd Abdul; Radiman, Shahidan bin; Siong, Ch'ng Han

2018-04-01

The Einstein-Podolsky-Rosen (EPR) paradox demonstrates that entangled particles can interact in such a way that it is possible to measure both their position and momentum instantaneously. The position or momentum of one particle can be determined by measuring another identical particle that exists in another space. This instantaneous action is actually called nonlocality. The nonlocality has been proved by Bell's theorem that states that all quantum theories must be nonlocal. The Bell's theorem gives a strong support to the hidden variable theory, i.e. Bohmian mechanics. Using nonlocality, we present that the velocity field of one particle can be obtained by measuring the velocity of other particles. The trajectory of these particles is perhaps surrealistic trajectory due to the nonlocality.

Black Holes, Hidden Symmetry and Complete Integrability: Brief Review

NASA Astrophysics Data System (ADS)

Frolov, Valeri P.

This chapter contains a brief review of the remarkable properties of higher dimensional rotating black holes with the spherical topology of the horizon. We demonstrate that these properties are connected with and generated by a special geometrical object, the Principal Conformal Killing-Yano tensor (PCKYT). The most general solution, describing such black holes, Kerr-NUT-ADS metric, admits this structure. Moreover a solution of the Einstein Equations with (or without) a cosmological constant which possesses PCKYT is the Kerr-NUT-ADS metric. This object (PCKYT) is responsible for such remarkable properties of higher dimensional rotating black holes as: (i) complete integrability of geodesic equations and (ii) complete separation of variables of the important field equations.

Bell - Kochen - Specker theorem for any finite dimension ?

NASA Astrophysics Data System (ADS)

Cabello, Adán; García-Alcaine, Guillermo

1996-03-01

The Bell - Kochen - Specker theorem against non-contextual hidden variables can be proved by constructing a finite set of `totally non-colourable' directions, as Kochen and Specker did in a Hilbert space of dimension n = 3. We generalize Kochen and Specker's set to Hilbert spaces of any finite dimension 0305-4470/29/5/016/img2, in a three-step process that shows the relationship between different kinds of proofs (`continuum', `probabilistic', `state-specific' and `state-independent') of the Bell - Kochen - Specker theorem. At the same time, this construction of a totally non-colourable set of directions in any dimension explicitly solves the question raised by Zimba and Penrose about the existence of such a set for n = 5.

The Contextuality Loophole is Fatal for the Derivation of Bell Inequalities: Reply to a Comment by I. Schmelzer

NASA Astrophysics Data System (ADS)

Nieuwenhuizen, Theodorus M.; Kupczynski, Marian

2017-02-01

Ilya Schmelzer wrote recently: Nieuwenhuizen argued that there exists some "contextuality loophole" in Bell's theorem. This claim in unjustified. It is made clear that this arose from attaching a meaning to the title and the content of the paper different from the one intended by Nieuwenhuizen. "Contextual loophole" means only that if the supplementary parameters describing measuring instruments are correctly introduced, Bell and Bell-type inequalities may not be proven. It is also stressed that a hidden variable model suffers from a "contextuality loophole" if it tries to describe different sets of incompatible experiments using a unique probability space and a unique joint probability distribution.

Sparse Zero-Sum Games as Stable Functional Feature Selection

PubMed Central

Sokolovska, Nataliya; Teytaud, Olivier; Rizkalla, Salwa; Clément, Karine; Zucker, Jean-Daniel

2015-01-01

In large-scale systems biology applications, features are structured in hidden functional categories whose predictive power is identical. Feature selection, therefore, can lead not only to a problem with a reduced dimensionality, but also reveal some knowledge on functional classes of variables. In this contribution, we propose a framework based on a sparse zero-sum game which performs a stable functional feature selection. In particular, the approach is based on feature subsets ranking by a thresholding stochastic bandit. We provide a theoretical analysis of the introduced algorithm. We illustrate by experiments on both synthetic and real complex data that the proposed method is competitive from the predictive and stability viewpoints. PMID:26325268

Cascaded VLSI Chips Help Neural Network To Learn

NASA Technical Reports Server (NTRS)

Duong, Tuan A.; Daud, Taher; Thakoor, Anilkumar P.

1993-01-01

Cascading provides 12-bit resolution needed for learning. Using conventional silicon chip fabrication technology of VLSI, fully connected architecture consisting of 32 wide-range, variable gain, sigmoidal neurons along one diagonal and 7-bit resolution, electrically programmable, synaptic 32 x 31 weight matrix implemented on neuron-synapse chip. To increase weight nominally from 7 to 13 bits, synapses on chip individually cascaded with respective synapses on another 32 x 32 matrix chip with 7-bit resolution synapses only (without neurons). Cascade correlation algorithm varies number of layers effectively connected into network; adds hidden layers one at a time during learning process in such way as to optimize overall number of neurons and complexity and configuration of network.

Foundations of Quantum Mechanics: recent developments at INRIM

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

Genovese, Marco; Piacentini, Fabrizio

2011-09-23

This paper's purpose is to show some experiments performed in the 'Carlo Novero' labs of the Optics Division of the National Institute of Metrological Research (INRIM, Torino, Italy) in the last years, aiming to discriminate between Standard Quantum Mechanics and some specific, restricted class of Hidden Variable Theories (HVTs).The first experiment, realized in two different configurations, will perform the Alicki - Van Ryn non-classicality test on single particles, in our specific case heralded single photons. The second experiment instead will be on the testing of two restricted Local Realistic Theories (LRTs), properly built to describe polarization entangled photons experiments, whosemore » inequalities are not affected by the detection loophole.« less

Updraft gasification of poultry litter at farm-scale--A case study.

PubMed

Taupe, N C; Lynch, D; Wnetrzak, R; Kwapinska, M; Kwapinski, W; Leahy, J J

2016-04-01

Farm and animal wastes are increasingly being investigated for thermochemical conversion, such as gasification, due to the urgent necessity of finding new waste treatment options. We report on an investigation of the use of a farm-scale, auto-thermal gasification system for the production of a heating gas using poultry litter (PL) as a feedstock. The gasification process was robust and reliable. The PL's ash melting temperature was 639°C, therefore the reactor temperature was kept around this value. As a result of the low reactor temperature the process performance parameters were low, with a cold gas efficiency (CGE) of 0.26 and a carbon conversion efficiency (CCE) of 0.44. The calorific value of the clean product gas was 3.39 MJ m(-3)N (LHV). The tar was collected as an emulsion containing 87 wt.% water and the extracted organic compounds were identified. The residual char exceeds thresholds for Zn and Cu to obtain European biochar certification; however, has potential to be classified as a pyrogenic carbonaceous material (PCM), which resembles a high nutrient biochar. Copyright © 2016 Elsevier Ltd. All rights reserved.

Experimental investigation on an entrained flow type biomass gasification system using coconut coir dust as powdery biomass feedstock.

PubMed

Senapati, P K; Behera, S

2012-08-01

Based on an entrained flow concept, a prototype atmospheric gasification system has been designed and developed in the laboratory for gasification of powdery biomass feedstock such as rice husks, coconut coir dust, saw dust etc. The reactor was developed by adopting L/D (height to diameter) ratio of 10, residence time of about 2s and a turn down ratio (TDR) of 1.5. The experimental investigation was carried out using coconut coir dust as biomass feedstock with a mean operating feed rate of 40 kg/h The effects of equivalence ratio in the range of 0.21-0.3, steam feed at a fixed flow rate of 12 kg/h, preheat on reactor temperature, product gas yield and tar content were investigated. The gasifier could able to attain high temperatures in the range of 976-1100 °C with gas lower heating value (LHV) and peak cold gas efficiency (CGE) of 7.86 MJ/Nm3 and 87.6% respectively. Copyright © 2012 Elsevier Ltd. All rights reserved.

The Future of Warfare and Impact of Space Operations

DTIC Science & Technology

2011-01-01

cyber warfare is occurring as a preferred method of conflict between large players on the global stage. Smaller players also have reasons to avoid conventional warfare and remain hidden. In Iraq and Afghanistan, those who fight against us attempt to remain hidden. The individual who places an improvised explosive device (IED) attempts to engage us without exposure or identification. Those who aid the individual emplacing an IED do so with hidden networks of support. The IED is an anonymous weapon. Both cyber warfare and insurgent use of IEDs depend

Prediction of Narrow N* and {Lambda}* Resonances with Hidden Charm above 4 GeV

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

Wu Jiajun; Departamento de Fisica Teorica and IFIC, Centro Mixto Universidad de Valencia-CSIC, Institutos de Investigacion de Paterna, Apartado 22085, 46071 Valencia; Molina, R.

2010-12-03

The interaction between various charmed mesons and charmed baryons is studied within the framework of the coupled-channel unitary approach with the local hidden gauge formalism. Several meson-baryon dynamically generated narrow N{sup *} and {Lambda}{sup *} resonances with hidden charm are predicted with mass above 4 GeV and width smaller than 100 MeV. The predicted new resonances definitely cannot be accommodated by quark models with three constituent quarks and can be looked for in the forthcoming PANDA/FAIR experiments.

Desktop computer graphics for RMS/payload handling flight design

NASA Technical Reports Server (NTRS)

Homan, D. J.

1984-01-01

A computer program, the Multi-Adaptive Drawings, Renderings and Similitudes (MADRAS) program, is discussed. The modeling program, written for a desktop computer system (the Hewlett-Packard 9845/C), is written in BASIC and uses modular construction of objects while generating both wire-frame and hidden-line drawings from any viewpoint. The dimensions and placement of objects are user definable. Once the hidden-line calculations are made for a particular viewpoint, the viewpoint may be rotated in pan, tilt, and roll without further hidden-line calculations. The use and results of this program are discussed.

NuSTAR Seeks Hidden Black Holes

NASA Image and Video Library

2015-07-06

Top: An illustration of NASA's Nuclear Spectroscopic Telescope Array, or NuSTAR, in orbit. The unique school bus-long mast allows NuSTAR to focus high energy X-rays. Lower-left: A color image from NASA's Hubble Space Telescope of one of the nine galaxies targeted by NuSTAR in search of hidden black holes. Bottom-right: An artist's illustration of a supermassive black hole, actively feasting on its surroundings. The central black hole is hidden from direct view by a thick layer of encircling gas and dust. http://photojournal.jpl.nasa.gov/catalog/PIA19348

A New Chaotic Flow with Hidden Attractor: The First Hyperjerk System with No Equilibrium

NASA Astrophysics Data System (ADS)

Ren, Shuili; Panahi, Shirin; Rajagopal, Karthikeyan; Akgul, Akif; Pham, Viet-Thanh; Jafari, Sajad

2018-02-01

Discovering unknown aspects of non-equilibrium systems with hidden strange attractors is an attractive research topic. A novel quadratic hyperjerk system is introduced in this paper. It is noteworthy that this non-equilibrium system can generate hidden chaotic attractors. The essential properties of such systems are investigated by means of equilibrium points, phase portrait, bifurcation diagram, and Lyapunov exponents. In addition, a fractional-order differential equation of this new system is presented. Moreover, an electronic circuit is also designed and implemented to verify the feasibility of the theoretical model.

Gravitational lensing of photons coupled to massive particles

NASA Astrophysics Data System (ADS)

Glicenstein, J.-F.

2018-04-01

The gravitational deflection of massless and massive particles, both with and without spin, has been extensively studied. This paper discusses the lensing of a particle which oscillates between two interaction eigenstates. The deflection angle, lens equation and time delay between images are derived in a model of photon to hidden-photon oscillations. In the case of coherent oscillations, the coupled photon behaves as a massive particle with a mass equal to the product of the coupling constant and hidden-photon mass. The conditions for observing coherent photon-hidden photon lensing are discussed.

Hidden Symmetries in String Theory

NASA Astrophysics Data System (ADS)

Chervonyi, Iurii

In this thesis we study hidden symmetries within the framework of string theory. Symmetries play a very important role in physics: they lead to drastic simplifications, which allow one to compute various physical quantities without relying on perturbative techniques. There are two kinds of hidden symmetries investigated in this work: the first type is associated with dynamics of quantum fields and the second type is related to integrability of strings on various backgrounds. Integrability is a remarkable property of some theories that allows one to determine all dynamical properties of the system using purely analytical methods. The goals of this thesis are twofold: extension of hidden symmetries known in General Relativity to stringy backgrounds in higher dimensions and construction of new integrable string theories. In the context of the first goal we study hidden symmetries of stringy backgrounds, with and without supersymmetry. For supersymmetric geometries produced by D-branes we identify the backgrounds with solvable equations for geodesics, which can potentially give rise to integrable string theories. Relaxing the requirement of supersymmetry, we also study charged black holes in higher dimensions and identify their hidden symmetries encoded in so-called Killing(-Yano) tensors. We construct the explicit form of the Killing(-Yano) tensors for the charged rotating black hole in arbitrary number of dimensions, study behavior of such tensors under string dualities, and use the analysis of hidden symmetries to explain why exact solutions for black rings (black holes with non-spherical event horizons) in more than five dimensions remain elusive. As a byproduct we identify the standard parameterization of AdSp x Sq backgrounds with elliptic coordinates on a flat base. The second goal of this work is construction of new integrable string theories by applying continuous deformations of known examples. We use the recent developments called (generalized) lambda-deformation to construct new integrable backgrounds depending on several continuous parameters and study analytical properties of the such deformations.

Detect and exploit hidden structure in fatty acid signature data

USGS Publications Warehouse

Budge, Suzanne; Bromaghin, Jeffrey F.; Thiemann, Gregory

2017-01-01

Estimates of predator diet composition are essential to our understanding of their ecology. Although several methods of estimating diet are practiced, methods based on biomarkers have become increasingly common. Quantitative fatty acid signature analysis (QFASA) is a popular method that continues to be refined and extended. Quantitative fatty acid signature analysis is based on differences in the signatures of prey types, often species, which are recognized and designated by investigators. Similarly, predator signatures may be structured by known factors such as sex or age class, and the season or region of sample collection. The recognized structure in signature data inherently influences QFASA results in important and typically beneficial ways. However, predator and prey signatures may contain additional, hidden structure that investigators either choose not to incorporate into an analysis or of which they are unaware, being caused by unknown ecological mechanisms. Hidden structure also influences QFASA results, most often negatively. We developed a new method to explore signature data for hidden structure, called divisive magnetic clustering (DIMAC). Our DIMAC approach is based on the same distance measure used in diet estimation, closely linking methods of data exploration and parameter estimation, and it does not require data transformation or distributional assumptions, as do many multivariate ordination methods in common use. We investigated the potential benefits of the DIMAC method to detect and subsequently exploit hidden structure in signature data using two prey signature libraries with quite different characteristics. We found that the existence of hidden structure in prey signatures can increase the confusion between prey types and thereby reduce the accuracy and precision of QFASA diet estimates. Conversely, the detection and exploitation of hidden structure represent a potential opportunity to improve predator diet estimates and may lead to new insights into the ecology of either predator or prey. The DIMAC algorithm is implemented in the R diet estimation package qfasar.

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.

Discovering Hidden Connections among Diseases, Genes and Drugs Based on Microarray Expression Profiles with Negative-Term Filtering

PubMed Central

2014-01-01

Microarrays based on gene expression profiles (GEPs) can be tailored specifically for a variety of topics to provide a precise and efficient means with which to discover hidden information. This study proposes a novel means of employing existing GEPs to reveal hidden relationships among diseases, genes, and drugs within a rich biomedical database, PubMed. Unlike the co-occurrence method, which considers only the appearance of keywords, the proposed method also takes into account negative relationships and non-relationships among keywords, the importance of which has been demonstrated in previous studies. Three scenarios were conducted to verify the efficacy of the proposed method. In Scenario 1, disease and drug GEPs (disease: lymphoma cancer, lymph node cancer, and drug: cyclophosphamide) were used to obtain lists of disease- and drug-related genes. Fifteen hidden connections were identified between the diseases and the drug. In Scenario 2, we adopted different diseases and drug GEPs (disease: AML-ALL dataset and drug: Gefitinib) to obtain lists of important diseases and drug-related genes. In this case, ten hidden connections were identified. In Scenario 3, we obtained a list of disease-related genes from the disease-related GEP (liver cancer) and the drug (Capecitabine) on the PharmGKB website, resulting in twenty-two hidden connections. Experimental results demonstrate the efficacy of the proposed method in uncovering hidden connections among diseases, genes, and drugs. Following implementation of the weight function in the proposed method, a large number of the documents obtained in each of the scenarios were judged to be related: 834 of 4028 documents, 789 of 1216 documents, and 1928 of 3791 documents in Scenarios 1, 2, and 3, respectively. The negative-term filtering scheme also uncovered a large number of negative relationships as well as non-relationships among these connections: 97 of 834, 38 of 789, and 202 of 1928 in Scenarios 1, 2, and 3, respectively. PMID:24915461

An Audience Favorite Nebula

NASA Image and Video Library

2012-03-08

This nebula, which is in the constellation of Scutum, has no common name since it is hidden behind dust clouds. It takes an infrared telescope like NASA Spitzer to see through this dark veil and reveal this spectacular hidden nebula.

Hidden Patterns of Light Revealed by Spitzer

NASA Image and Video Library

2012-06-07

Astronomers have uncovered patterns of light that appear to be from the first stars and galaxies that formed in the universe. The light patterns were hidden within a strip of sky observed by NASA Spitzer Space Telescope.

A dynamic programming-based particle swarm optimization algorithm for an inventory management problem under uncertainty

NASA Astrophysics Data System (ADS)

Xu, Jiuping; Zeng, Ziqiang; Han, Bernard; Lei, Xiao

2013-07-01

This article presents a dynamic programming-based particle swarm optimization (DP-based PSO) algorithm for solving an inventory management problem for large-scale construction projects under a fuzzy random environment. By taking into account the purchasing behaviour and strategy under rules of international bidding, a multi-objective fuzzy random dynamic programming model is constructed. To deal with the uncertainties, a hybrid crisp approach is used to transform fuzzy random parameters into fuzzy variables that are subsequently defuzzified by using an expected value operator with optimistic-pessimistic index. The iterative nature of the authors' model motivates them to develop a DP-based PSO algorithm. More specifically, their approach treats the state variables as hidden parameters. This in turn eliminates many redundant feasibility checks during initialization and particle updates at each iteration. Results and sensitivity analysis are presented to highlight the performance of the authors' optimization method, which is very effective as compared to the standard PSO algorithm.

Detection of time delays and directional interactions based on time series from complex dynamical systems

NASA Astrophysics Data System (ADS)

Ma, Huanfei; Leng, Siyang; Tao, Chenyang; Ying, Xiong; Kurths, Jürgen; Lai, Ying-Cheng; Lin, Wei

2017-07-01

Data-based and model-free accurate identification of intrinsic time delays and directional interactions is an extremely challenging problem in complex dynamical systems and their networks reconstruction. A model-free method with new scores is proposed to be generally capable of detecting single, multiple, and distributed time delays. The method is applicable not only to mutually interacting dynamical variables but also to self-interacting variables in a time-delayed feedback loop. Validation of the method is carried out using physical, biological, and ecological models and real data sets. Especially, applying the method to air pollution data and hospital admission records of cardiovascular diseases in Hong Kong reveals the major air pollutants as a cause of the diseases and, more importantly, it uncovers a hidden time delay (about 30-40 days) in the causal influence that previous studies failed to detect. The proposed method is expected to be universally applicable to ascertaining and quantifying subtle interactions (e.g., causation) in complex systems arising from a broad range of disciplines.

Phase diagram of restricted Boltzmann machines and generalized Hopfield networks with arbitrary priors.

PubMed

Barra, Adriano; Genovese, Giuseppe; Sollich, Peter; Tantari, Daniele

2018-02-01

Restricted Boltzmann machines are described by the Gibbs measure of a bipartite spin glass, which in turn can be seen as a generalized Hopfield network. This equivalence allows us to characterize the state of these systems in terms of their retrieval capabilities, both at low and high load, of pure states. We study the paramagnetic-spin glass and the spin glass-retrieval phase transitions, as the pattern (i.e., weight) distribution and spin (i.e., unit) priors vary smoothly from Gaussian real variables to Boolean discrete variables. Our analysis shows that the presence of a retrieval phase is robust and not peculiar to the standard Hopfield model with Boolean patterns. The retrieval region becomes larger when the pattern entries and retrieval units get more peaked and, conversely, when the hidden units acquire a broader prior and therefore have a stronger response to high fields. Moreover, at low load retrieval always exists below some critical temperature, for every pattern distribution ranging from the Boolean to the Gaussian case.

Neural networks applied to discriminate botanical origin of honeys.

PubMed

Anjos, Ofélia; Iglesias, Carla; Peres, Fátima; Martínez, Javier; García, Ángela; Taboada, Javier

2015-05-15

The aim of this work is develop a tool based on neural networks to predict the botanical origin of honeys using physical and chemical parameters. The managed database consists of 49 honey samples of 2 different classes: monofloral (almond, holm oak, sweet chestnut, eucalyptus, orange, rosemary, lavender, strawberry trees, thyme, heather, sunflower) and multifloral. The moisture content, electrical conductivity, water activity, ashes content, pH, free acidity, colorimetric coordinates in CIELAB space (L(∗), a(∗), b(∗)) and total phenols content of the honey samples were evaluated. Those properties were considered as input variables of the predictive model. The neural network is optimised through several tests with different numbers of neurons in the hidden layer and also with different input variables. The reduced error rates (5%) allow us to conclude that the botanical origin of honey can be reliably and quickly known from the colorimetric information and the electrical conductivity of honey. Copyright © 2014 Elsevier Ltd. All rights reserved.

Resurrecting the buried self: fairy tales and the analytic encounter.

PubMed

Jacobs, Linda

2011-12-01

The author uses the lens of myth and fairy tales to examine the narratives generated by the analytic experience. Fairy tales are understood as representing fundamental developmental conflicts, accounting for their enduring power over time. The analytic encounter is seen as an analogue of the fairy tale in which the hidden self, damaged by loss and abandonment, reemerges only through the redemptive power of [an] other's love. Clinical material is presented in which hidden parts of the patient's self are projected into the analyst for safekeeping; these hidden parts resonate with the analyst's own lost, unrealized potential and form an intersubjective experience which the author believes is transformative. The patient's dormant powers emerge in a newly experienced atmosphere of recognition, and in this way, the analytic encounter resembles the fairy tale in providing an identificatory bond and a protective space for the patient's hidden vitality.

Field-induced spin-density wave beyond hidden order in URu2Si2

NASA Astrophysics Data System (ADS)

Knafo, W.; Duc, F.; Bourdarot, F.; Kuwahara, K.; Nojiri, H.; Aoki, D.; Billette, J.; Frings, P.; Tonon, X.; Lelièvre-Berna, E.; Flouquet, J.; Regnault, L.-P.

2016-10-01

URu2Si2 is one of the most enigmatic strongly correlated electron systems and offers a fertile testing ground for new concepts in condensed matter science. In spite of >30 years of intense research, no consensus on the order parameter of its low-temperature hidden-order phase exists. A strong magnetic field transforms the hidden order into magnetically ordered phases, whose order parameter has also been defying experimental observation. Here, thanks to neutron diffraction under pulsed magnetic fields up to 40 T, we identify the field-induced phases of URu2Si2 as a spin-density-wave state. The transition to the spin-density wave represents a unique touchstone for understanding the hidden-order phase. An intimate relationship between this magnetic structure, the magnetic fluctuations and the Fermi surface is emphasized, calling for dedicated band-structure calculations.

"Hidden Figures" Panel Discussion

NASA Image and Video Library

2016-12-12

In the Press Site auditorium at the Kennedy Space Center in Florida, members of the media participate in a news conference with key individuals from the upcoming motion picture "Hidden Figures." From the left are: Ted Melfi (partially visible), writer and director of “Hidden Figures”; Octavia Spencer, who portrays Dorothy Vaughan; Taraji P. Henson, who portrays Katherine Johnson in the film; Janelle Monáe, who portrays Mary Jackson; Pharrell Williams, musician and producer of “Hidden Figures"; and Bill Barry, NASA's chief historian. The movie is based on the book of the same title, by Margot Lee Shetterly. It chronicles the lives of Katherine Johnson, Dorothy Vaughan and Mary Jackson, three African-American women who worked for NASA as human "computers.” Their mathematical calculations were crucial to the success of Project Mercury missions including John Glenn’s orbital flight aboard Friendship 7 in 1962. The film is due in theaters in January 2017.

"Hidden Figures" Panel Discussion

NASA Image and Video Library

2016-12-12

In the Press Site auditorium at the Kennedy Space Center in Florida, members of the media participate in a news conference with key individuals from the upcoming motion picture "Hidden Figures." From the left are: former CNN space correspondent John Zarrella, serving as moderator; Ted Melfi, writer and director of “Hidden Figures”; Octavia Spencer, who portrays Dorothy Vaughan; Taraji P. Henson, who portrays Katherine Johnson in the film; Janelle Monáe, who portrays Mary Jackson; Pharrell Williams, musician and producer of “Hidden Figures"; and Bill Barry, NASA's chief historian. The movie is based on the book of the same title, by Margot Lee Shetterly. It chronicles the lives of Katherine Johnson, Dorothy Vaughan and Mary Jackson, three African-American women who worked for NASA as human "computers.” Their mathematical calculations were crucial to the success of Project Mercury missions including John Glenn’s orbital flight aboard Friendship 7 in 1962. The film is due in theaters in January 2017.

"Hidden Figures" Panel Discussion

NASA Image and Video Library

2016-12-12

In the Press Site auditorium at the Kennedy Space Center in Florida, members of the media participate in a news conference with key individuals from the upcoming motion picture "Hidden Figures." From the left are: Ted Melfi, writer and director of “Hidden Figures”; Octavia Spencer, who portrays Dorothy Vaughan; Taraji P. Henson, who portrays Katherine Johnson in the film; Janelle Monáe, who portrays Mary Jackson; Pharrell Williams, musician and producer of “Hidden Figures"; and Bill Barry, NASA's chief historian. The movie is based on the book of the same title, by Margot Lee Shetterly. It chronicles the lives of Katherine Johnson, Dorothy Vaughan and Mary Jackson, three African-American women who worked for NASA as human "computers.” Their mathematical calculations were crucial to the success of Project Mercury missions including John Glenn’s orbital flight aboard Friendship 7 in 1962. The film is due in theaters in January 2017.

Hidden Figures Tour Kennedy Space Center Visitor Complex

NASA Image and Video Library

2016-12-12

In the IMAX Theater of the Kennedy Space Center Visitor Complex Cast and crew members of the upcoming motion picture "Hidden Figures" participate in a question and answer session. From the left are Ted Melfi, writer and director of “Hidden Figures,” Octavia Spencer, who portrays Dorothy Vaughan in the film, Taraji P. Henson, who portrays Katherine Johnson, Pharrell Williams, musician and producer of “Hidden Figures," and Janelle Monáe, who portrays Mary Jackson. The movie is based on the book of the same title, by Margot Lee Shetterly. It chronicles the lives of Katherine Johnson, Dorothy Vaughan and Mary Jackson, three African-American women who worked for NASA as human "computers.” Their mathematical calculations were crucial to the success of Project Mercury missions including John Glenn’s orbital flight aboard Friendship 7 in 1962. The film is due in theaters in January 2017.

Hidden Figures Tour Kennedy Space Center Visitor Complex

NASA Image and Video Library

2016-12-12

In the IMAX Theater of the Kennedy Space Center Visitor Complex Cast and crew members of the upcoming motion picture "Hidden Figures" participate in a question and answer session. From the left are Octavia Spencer, who portrays Dorothy Vaughan in the film, Taraji P. Henson, who portrays Katherine Johnson, Janelle Monáe, who portrays Mary Jackson, Pharrell Williams, musician and producer of “Hidden Figures," Ted Melfi, writer and director of “Hidden Figures,” center director Bob Cabana, and Janet Petro, deputy center director. The movie is based on the book of the same title, by Margot Lee Shetterly. It chronicles the lives of Katherine Johnson, Dorothy Vaughan and Mary Jackson, three African-American women who worked for NASA as human "computers.” Their mathematical calculations were crucial to the success of Project Mercury missions including John Glenn’s orbital flight aboard Friendship 7 in 1962. The film is due in theaters in January 2017.

Multivariate longitudinal data analysis with mixed effects hidden Markov models.

PubMed

Raffa, Jesse D; Dubin, Joel A

2015-09-01

Multiple longitudinal responses are often collected as a means to capture relevant features of the true outcome of interest, which is often hidden and not directly measurable. We outline an approach which models these multivariate longitudinal responses as generated from a hidden disease process. We propose a class of models which uses a hidden Markov model with separate but correlated random effects between multiple longitudinal responses. This approach was motivated by a smoking cessation clinical trial, where a bivariate longitudinal response involving both a continuous and a binomial response was collected for each participant to monitor smoking behavior. A Bayesian method using Markov chain Monte Carlo is used. Comparison of separate univariate response models to the bivariate response models was undertaken. Our methods are demonstrated on the smoking cessation clinical trial dataset, and properties of our approach are examined through extensive simulation studies. © 2015, The International Biometric Society.

Lake-sediment evidence for the date of deglaciation of the Hidden Lake area, Kenai Peninsula, Alaska

NASA Astrophysics Data System (ADS)

Rymer, Michael J.; Sims, John D.

1982-06-01

An abrupt environmental change is reflected in a core from Hidden Lake, Alaska, by differences in sediment type, chlorite crystallinity, and content of organic carbon and water of the sediments. This abrupt change in the sedimentary record occurred about 14,500 14C yr ago and probably marks the time of recession of the glacier from the Hidden Lake drainage basin. Deglaciation of the area was then underway, and rock flour was being deposited in the lake. After recession of the glacier from the Hidden Lake drainage basin, rock flour was no longer introduced, and organic-matter content of the sediment increased. By the dating of these changes in sediment type, we show that retreat of glaciers in this area took place significantly earlier than previously estimated; this agrees with the timing of retreat of alpine glaciers elsewhere in western North America.

Constraints on hidden photons from current and future observations of CMB spectral distortions

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

Kunze, Kerstin E.; Vázquez-Mozo, Miguel Á., E-mail: kkunze@usal.es, E-mail: Miguel.Vazquez-Mozo@cern.ch

2015-12-01

A variety of beyond the standard model scenarios contain very light hidden sector U(1) gauge bosons undergoing kinetic mixing with the photon. The resulting oscillation between ordinary and hidden photons leads to spectral distortions of the cosmic microwave background. We update the bounds on the mixing parameter χ{sub 0} and the mass of the hidden photon m{sub γ'} for future experiments measuring CMB spectral distortions, such as PIXIE and PRISM/COrE. For 10{sup −14} eV∼< m{sub γ'}∼< 10{sup −13} eV, we find the kinetic mixing angle χ{sub 0} has to be less than 10{sup −8} at 95% CL. These bounds are more than an ordermore » of magnitude stronger than those derived from the COBE/FIRAS data.« less

Synchronisation, electronic circuit implementation, and fractional-order analysis of 5D ordinary differential equations with hidden hyperchaotic attractors

NASA Astrophysics Data System (ADS)

Wei, Zhouchao; Rajagopal, Karthikeyan; Zhang, Wei; Kingni, Sifeu Takougang; Akgül, Akif

2018-04-01

Hidden hyperchaotic attractors can be generated with three positive Lyapunov exponents in the proposed 5D hyperchaotic Burke-Shaw system with only one stable equilibrium. To the best of our knowledge, this feature has rarely been previously reported in any other higher-dimensional systems. Unidirectional linear error feedback coupling scheme is used to achieve hyperchaos synchronisation, which will be estimated by using two indicators: the normalised average root-mean squared synchronisation error and the maximum cross-correlation coefficient. The 5D hyperchaotic system has been simulated using a specially designed electronic circuit and viewed on an oscilloscope, thereby confirming the results of the numerical integration. In addition, fractional-order hidden hyperchaotic system will be considered from the following three aspects: stability, bifurcation analysis and FPGA implementation. Such implementations in real time represent hidden hyperchaotic attractors with important consequences for engineering applications.

The hidden life of integrative and conjugative elements

PubMed Central

Delavat, François; Miyazaki, Ryo; Carraro, Nicolas; Pradervand, Nicolas

2017-01-01

Abstract Integrative and conjugative elements (ICEs) are widespread mobile DNA that transmit both vertically, in a host-integrated state, and horizontally, through excision and transfer to new recipients. Different families of ICEs have been discovered with more or less restricted host ranges, which operate by similar mechanisms but differ in regulatory networks, evolutionary origin and the types of variable genes they contribute to the host. Based on reviewing recent experimental data, we propose a general model of ICE life style that explains the transition between vertical and horizontal transmission as a result of a bistable decision in the ICE–host partnership. In the large majority of cells, the ICE remains silent and integrated, but hidden at low to very low frequencies in the population specialized host cells appear in which the ICE starts its process of horizontal transmission. This bistable process leads to host cell differentiation, ICE excision and transfer, when suitable recipients are present. The ratio of ICE bistability (i.e. ratio of horizontal to vertical transmission) is the outcome of a balance between fitness costs imposed by the ICE horizontal transmission process on the host cell, and selection for ICE distribution (i.e. ICE ‘fitness’). From this emerges a picture of ICEs as elements that have adapted to a mostly confined life style within their host, but with a very effective and dynamic transfer from a subpopulation of dedicated cells. PMID:28369623

Detecting seismic waves using a binary hidden Markov model classifier

NASA Astrophysics Data System (ADS)

Ray, J.; Lefantzi, S.; Brogan, R. A.; Forrest, R.; Hansen, C. W.; Young, C. J.

2016-12-01

We explore the use of Hidden Markov Models (HMM) to detect the arrival of seismic waves using data captured by a seismogram. HMMs define the state of a station as a binary variable based on whether the station is receiving a signal or not. HMMs are simple and fast, allowing them to monitor multiple datastreams arising from a large distributed network of seismographs. In this study we examine the efficacy of HMM-based detectors with respect to their false positive and negative rates as well as the accuracy of the signal onset time as compared to the value determined by an expert analyst. The study uses 3 component International Monitoring System (IMS) data from a carefully analyzed 2 week period from May, 2010, for which our analyst tried to identify every signal. Part of this interval is used for training the HMM to recognize the transition between state from noise to signal, while the other is used for evaluating the effectiveness of our new detection algorithm. We compare our results with the STA/LTA detection processing applied by the IDC to assess potential for operational use. Sandia National Laboratories is a multi-program laboratory managed and operated by Sandia Corporation, a wholly owned subsidiary of Lockheed Martin Corporation, for the U.S. Department of Energy's National Nuclear Security Administration under contract DE-AC04-94AL85000.

Intratumoral heterogeneity analysis reveals hidden associations between protein expression losses and patient survival in clear cell renal cell carcinoma

PubMed Central

Devarajan, Karthik; Parsons, Theodore; Wang, Qiong; O'Neill, Raymond; Solomides, Charalambos; Peiper, Stephen C.; Testa, Joseph R.; Uzzo, Robert; Yang, Haifeng

2017-01-01

Intratumoral heterogeneity (ITH) is a prominent feature of kidney cancer. It is not known whether it has utility in finding associations between protein expression and clinical parameters. We used ITH that is detected by immunohistochemistry (IHC) to aid the association analysis between the loss of SWI/SNF components and clinical parameters.160 ccRCC tumors (40 per tumor stage) were used to generate tissue microarray (TMA). Four foci from different regions of each tumor were selected. IHC was performed against PBRM1, ARID1A, SETD2, SMARCA4, and SMARCA2. Statistical analyses were performed to correlate biomarker losses with patho-clinical parameters. Categorical variables were compared between groups using Fisher's exact tests. Univariate and multivariable analyses were used to correlate biomarker changes and patient survivals. Multivariable analyses were performed by constructing decision trees using the classification and regression trees (CART) methodology. IHC detected widespread ITH in ccRCC tumors. The statistical analysis of the “Truncal loss” (root loss) found additional correlations between biomarker losses and tumor stages than the traditional “Loss in tumor (total)”. Losses of SMARCA4 or SMARCA2 significantly improved prognosis for overall survival (OS). Losses of PBRM1, ARID1A or SETD2 had the opposite effect. Thus “Truncal Loss” analysis revealed hidden links between protein losses and patient survival in ccRCC. PMID:28445125

Differential expression analysis for RNAseq using Poisson mixed models.

PubMed

Sun, Shiquan; Hood, Michelle; Scott, Laura; Peng, Qinke; Mukherjee, Sayan; Tung, Jenny; Zhou, Xiang

2017-06-20

Identifying differentially expressed (DE) genes from RNA sequencing (RNAseq) studies is among the most common analyses in genomics. However, RNAseq DE analysis presents several statistical and computational challenges, including over-dispersed read counts and, in some settings, sample non-independence. Previous count-based methods rely on simple hierarchical Poisson models (e.g. negative binomial) to model independent over-dispersion, but do not account for sample non-independence due to relatedness, population structure and/or hidden confounders. Here, we present a Poisson mixed model with two random effects terms that account for both independent over-dispersion and sample non-independence. We also develop a scalable sampling-based inference algorithm using a latent variable representation of the Poisson distribution. With simulations, we show that our method properly controls for type I error and is generally more powerful than other widely used approaches, except in small samples (n <15) with other unfavorable properties (e.g. small effect sizes). We also apply our method to three real datasets that contain related individuals, population stratification or hidden confounders. Our results show that our method increases power in all three data compared to other approaches, though the power gain is smallest in the smallest sample (n = 6). Our method is implemented in MACAU, freely available at www.xzlab.org/software.html. © The Author(s) 2017. Published by Oxford University Press on behalf of Nucleic Acids Research.

Eavesdropping on insects hidden in soil and interior structures of plants.

PubMed

Mankin, R W; Brandhorst-Hubbard, J; Flanders, K L; Zhang, M; Crocker, R L; Lapointe, S L; McCoy, C W; Fisher, J R; Weaver, D K

2000-08-01

Accelerometer, electret microphone, and piezoelectric disk acoustic systems were evaluated for their potential to detect hidden insect infestations in soil and interior structures of plants. Coleopteran grubs (the scarabaeids Phyllophaga spp. and Cyclocephala spp.) and the curculionids Diaprepes abbreviatus (L.) and Otiorhynchus sulcatus (F.) weighing 50-300 mg were detected easily in the laboratory and in the field except under extremely windy or noisy conditions. Cephus cinctus Norton (Hymenoptera: Cephidae) larvae weighing 1-12 mg could be detected in small pots of wheat in the laboratory by taking moderate precautions to eliminate background noise. Insect sounds could be distinguished from background noises by differences in frequency and temporal patterns, but insects of similarly sized species could not be distinguished easily from each other. Insect activity was highly variable among individuals and species, although D. abbreviatus grubs tended to be more active than those of O. sulcatus. Tests were done to compare acoustically predicted infestations with the contents of soil samples taken at recording sites. Under laboratory or ideal field conditions, active insects within approximately 30 cm were identified with nearly 100% reliability. In field tests under adverse conditions, the reliability decreased to approximately 75%. These results indicate that acoustic systems with vibration sensors have considerable potential as activity monitors in the laboratory and as field tools for rapid, nondestructive scouting and mapping of soil insect populations.

Orangutans (Pongo abelii) seek information about tool functionality in a metacognition tubes task.

PubMed

Mulcahy, Nicholas J

2016-11-01

Nonhuman primates appear to engage in metacognition by knowing when they need to search for relevant information for solving the tubes task. The task involves presenting subjects with a number of tubes with only 1 having food hidden inside. Before choosing, subjects look inside the tubes more often when they do not know which 1 contains the food (hidden trials) compared to when they do know this information (visible trials). It is argued, however, that nonmetacognitive general food searching strategies can explain this looking behavior. To address this issue, 3 orangutans were tested with a novel tubes task in which they were only required to seek information about tool functionality. The results showed that subjects had the ability to search for tool functionality but no subject looked significantly more in hidden trials compared to visible trials. Subjects were retested with the same condition and given a second condition in which the cost of a wrong choice was increased. In both conditions, 2 subjects looked significantly more inside the hidden trials compared to the visible trials. Subjects were also tested with the traditional tubes task in which food was hidden inside 1 tube. All subjects looked inside the tubes significantly more in the hidden trials compared to the visible trials. However, subjects conducted more excessive looks compared to when looking for tool functionality. I suggest that excessive searches may be caused by food being a strong stimulus and discuss the relevance of this possibility for metacognitive research involving the tubes task. (PsycINFO Database Record (c) 2016 APA, all rights reserved).

Visualising inter-subject variability in fMRI using threshold-weighted overlap maps

NASA Astrophysics Data System (ADS)

Seghier, Mohamed L.; Price, Cathy J.

2016-02-01

Functional neuroimaging studies are revealing the neural systems sustaining many sensory, motor and cognitive abilities. A proper understanding of these systems requires an appreciation of the degree to which they vary across subjects. Some sources of inter-subject variability might be easy to measure (demographics, behavioural scores, or experimental factors), while others are more difficult (cognitive strategies, learning effects, and other hidden sources). Here, we introduce a simple way of visualising whole-brain consistency and variability in brain responses across subjects using threshold-weighted voxel-based overlap maps. The output quantifies the proportion of subjects activating a particular voxel or region over a wide range of statistical thresholds. The sensitivity of our approach was assessed in 30 healthy adults performing a matching task with their dominant hand. We show how overlap maps revealed many effects that were only present in a subsample of our group; we discuss how overlap maps can provide information that may be missed or misrepresented by standard group analysis, and how this information can help users to understand their data. In particular, we emphasize that functional overlap maps can be particularly useful when it comes to explaining typical (or atypical) compensatory mechanisms used by patients following brain damage.

Normal Weight Obesity: A Hidden Health Risk?

MedlinePlus

Normal weight obesity: A hidden health risk? Can you be considered obese if you have a normal body weight? Answers from ... considered obese — a condition known as normal weight obesity. Normal weight obesity means you may have the ...

Biomass waste gasification - Can be the two stage process suitable for tar reduction and power generation?

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

Sulc, Jindrich; Stojdl, Jiri; Richter, Miroslav

2012-04-15

Highlights: Black-Right-Pointing-Pointer Comparison of one stage (co-current) and two stage gasification of wood pellets. Black-Right-Pointing-Pointer Original arrangement with grate-less reactor and upward moving bed of the pellets. Black-Right-Pointing-Pointer Two stage gasification leads to drastic reduction of tar content in gas. Black-Right-Pointing-Pointer One stage gasification produces gas with higher LHV at lower overall ER. Black-Right-Pointing-Pointer Content of ammonia in gas is lower in two stage moving bed gasification. - Abstract: A pilot scale gasification unit with novel co-current, updraft arrangement in the first stage and counter-current downdraft in the second stage was developed and exploited for studying effects of two stagemore » gasification in comparison with one stage gasification of biomass (wood pellets) on fuel gas composition and attainable gas purity. Significant producer gas parameters (gas composition, heating value, content of tar compounds, content of inorganic gas impurities) were compared for the two stage and the one stage method of the gasification arrangement with only the upward moving bed (co-current updraft). The main novel features of the gasifier conception include grate-less reactor, upward moving bed of biomass particles (e.g. pellets) by means of a screw elevator with changeable rotational speed and gradual expanding diameter of the cylindrical reactor in the part above the upper end of the screw. The gasifier concept and arrangement are considered convenient for thermal power range 100-350 kW{sub th}. The second stage of the gasifier served mainly for tar compounds destruction/reforming by increased temperature (around 950 Degree-Sign C) and for gasification reaction of the fuel gas with char. The second stage used additional combustion of the fuel gas by preheated secondary air for attaining higher temperature and faster gasification of the remaining char from the first stage. The measurements of gas composition and tar compound contents confirmed superiority of the two stage gasification system, drastic decrease of aromatic compounds with two and higher number of benzene rings by 1-2 orders. On the other hand the two stage gasification (with overall ER = 0.71) led to substantial reduction of gas heating value (LHV = 3.15 MJ/Nm{sup 3}), elevation of gas volume and increase of nitrogen content in fuel gas. The increased temperature (>950 Degree-Sign C) at the entrance to the char bed caused also substantial decrease of ammonia content in fuel gas. The char with higher content of ash leaving the second stage presented only few mass% of the inlet biomass stream.« less

Functionally referential and intentional communication in the domestic dog: effects of spatial and social contexts.

PubMed

Gaunet, Florence; Deputte, Bertrand L

2011-11-01

In apes, four criteria are set to explore referential and intentional communication: (1) successive visual orienting between a partner and distant targets, (2) the presence of apparent attention-getting behaviours, (3) the requirement of an audience to exhibit the behaviours, and (4) the influence of the direction of attention of an observer on the behaviours. The present study aimed at identifying these criteria in behaviours used by dogs in communicative episodes with their owner when their toy is out of reach, i.e. gaze at a hidden target or at the owner, gaze alternation between a hidden target and the owner, vocalisations and contacts. In this study, an additional variable was analysed: the position of the dog in relation to the location of the target. Dogs witnessed the hiding of a favourite toy, in a place where they could not get access to. We analysed how dogs engaged in communicative deictic behaviours in the presence of their owner; four heights of the target were tested. To control for the motivational effects of the toy on the dogs' behaviour and for the referential nature of the behaviours, observations were staged where only the toy or only the owner was present, for one of the four heights. The results show that gazing at the container and gaze alternation were used as functionally referential and intentional communicative behaviours. Behavioural patterns of dog position, the new variable, fulfilled the operational criteria for functionally referential behaviour and a subset of operational criteria for intentional communication: the dogs used their own position as a local enhancement signal. Finally, our results suggest that the dogs gazed at their owner at optimal locations in the experimental area, with respect to the target height and their owner's (or their own) line of gaze. © Springer-Verlag 2011

A lithology identification method for continental shale oil reservoir based on BP neural network

NASA Astrophysics Data System (ADS)

Han, Luo; Fuqiang, Lai; Zheng, Dong; Weixu, Xia

2018-06-01

The Dongying Depression and Jiyang Depression of the Bohai Bay Basin consist of continental sedimentary facies with a variable sedimentary environment and the shale layer system has a variety of lithologies and strong heterogeneity. It is difficult to accurately identify the lithologies with traditional lithology identification methods. The back propagation (BP) neural network was used to predict the lithology of continental shale oil reservoirs. Based on the rock slice identification, x-ray diffraction bulk rock mineral analysis, scanning electron microscope analysis, and the data of well logging and logging, the lithology was divided with carbonate, clay and felsic as end-member minerals. According to the core-electrical relationship, the frequency histogram was then used to calculate the logging response range of each lithology. The lithology-sensitive curves selected from 23 logging curves (GR, AC, CNL, DEN, etc) were chosen as the input variables. Finally, the BP neural network training model was established to predict the lithology. The lithology in the study area can be divided into four types: mudstone, lime mudstone, lime oil-mudstone, and lime argillaceous oil-shale. The logging responses of lithology were complicated and characterized by the low values of four indicators and medium values of two indicators. By comparing the number of hidden nodes and the number of training times, we found that the number of 15 hidden nodes and 1000 times of training yielded the best training results. The optimal neural network training model was established based on the above results. The lithology prediction results of BP neural network of well XX-1 showed that the accuracy rate was over 80%, indicating that the method was suitable for lithology identification of continental shale stratigraphy. The study provided the basis for the reservoir quality and oily evaluation of continental shale reservoirs and was of great significance to shale oil and gas exploration.

Registration of 'Hidden Valley' meadow fescue

USDA-ARS?s Scientific Manuscript database

'Hidden Valley' (Reg. No. CV-xxxx, PI xxxxxx) meadow fescue [Schedonorus pratensis (Huds.) P. Beauv.; syn. Festuca pratensis Huds.; syn. Lolium pratense (Huds.) Darbysh.] is a synthetic population originating from 561 parental genotypes. The original germplasm is of unknown central or northern Europ...

Hidden simplicity of gauge theory amplitudes

NASA Astrophysics Data System (ADS)

Drummond, J. M.

2010-11-01

These notes were given as lectures at the CERN Winter School on Supergravity, Strings and Gauge Theory 2010. We describe the structure of scattering amplitudes in gauge theories, focussing on the maximally supersymmetric theory to highlight the hidden symmetries which appear. Using the Britto, Cachzo, Feng and Witten (BCFW) recursion relations we solve the tree-level S-matrix in \\ {N}=4 super Yang-Mills theory and describe how it produces a sum of invariants of a large symmetry algebra. We review amplitudes in the planar theory beyond tree level, describing the connection between amplitudes and Wilson loops, and discuss the implications of the hidden symmetries.

Hidden Cameras: Everything You Need to Know About Covert Recording, Undercover Cameras and Secret Filming Plomin Joe Hidden Cameras: Everything You Need to Know About Covert Recording, Undercover Cameras and Secret Filming 224pp £12.99 Jessica Kingsley 9781849056434 1849056439 [Formula: see text].

PubMed

2016-05-27

LAST YEAR, the Care Quality Commission issued guidance to families on using hidden cameras if they are concerned that their relatives are being abused or receiving poor care. Filming in care settings has also resulted in high profile prosecutions, and numerous TV documentaries. Joe Plomin, the author, was the undercover producer who exposed the abuse at Winterbourne View, near Bristol, in 2011.

Detecting hidden particles with MATHUSLA

NASA Astrophysics Data System (ADS)

Evans, Jared A.

2018-03-01

A hidden sector containing light long-lived particles provides a well-motivated place to find new physics. The recently proposed MATHUSLA experiment has the potential to be extremely sensitive to light particles originating from rare meson decays in the very long lifetime region. In this work, we illustrate this strength with the specific example of a light scalar mixed with the standard model-like Higgs boson, a model where MATHUSLA can further probe unexplored parameter space from exotic Higgs decays. Design augmentations should be considered in order to maximize the ability of MATHUSLA to discover very light hidden sector particles.

Detecting hidden exfoliation corrosion in aircraft wing skins using thermography

NASA Astrophysics Data System (ADS)

Prati, John

2000-03-01

A thermal wave (pulse) thermography inspection technique demonstrated the ability to detect hidden subsurface exfoliation corrosion adjacent to countersunk fasteners in aircraft wing skins. In the wing skin, exfoliation corrosion is the result of the interaction between the steel fastener and the aluminum skin material in the presence of moisture. This interaction results in corrosion cracks that tend to grow parallel to the skin surface. The inspection technique developed allows rapid detection and evaluation of hidden (not visible on the surface) corrosion, which extends beyond the head of fastener countersinks in the aluminum skins.