Do Tonkean macaques (Macaca tonkeana) perceive what conspecifics do and do not see?

PubMed Central

Piraux, Emilie; Poulin, Nicolas; Meunier, Hélène

2016-01-01

The understanding of the visual perception of others, also named visual perspective taking, is a component of Theory of Mind. Although strong evidence of visual perspective taking has been reported in great apes, the issue is more open to discussion in monkeys. We investigated whether Tonkean macaques (Macaca tonkeana) know what conspecifics do and do not see, using a food competition paradigm originally developed in great apes. We tested individuals in pairs, after establishing the dominance relationship within each pair. Twenty-one pairs were tested in four different conditions. In one condition, the subordinate had the choice between two pieces of food, one that was visible only to it and another that was also visible to the dominant. It was predicted that if the subordinate understands that the dominant cannot see both pieces of food because one is hidden from its view, the subordinate should preferentially go for the food visible only to itself. In the three other conditions, we varied the temporal and visual access to food for both individuals, to control for alternative explanations based on dominance. We recorded the first movement direction chosen by subjects, i.e. towards a) visible food b) hidden food or c) elsewhere; and the outcome of the test, i.e. the quantity of food obtained. Results showed that subordinates moved preferentially for the hidden food when released simultaneously with the dominant and also with a head start on the dominant. By contrast, dominants’ choices of the two pieces of food were random. We also describe and discuss some of the strategies used by subordinates in these tests. According to the whole of our results, Tonkean macaques seem capable of visual perspective taking despite the fact that a low-level explanation as behavior reading has not been totally excluded. PMID:26925323

Fairness Considerations When I Know More than You Do: Developmental Comparisons

PubMed Central

Overgaauw, Sandy; Güroğlu, Berna; Crone, Eveline A.

2012-01-01

The Ultimatum Game (UG) is a valuable paradigm to study fairness considerations. Here, we tested developmental differences between altruistic and strategic motivations in fairness considerations using a version of the UG with hidden conditions. Participants were proposers and could divide coins between themselves and an anonymous other. Hidden information conditions involved division of coins where some coins were only visible to the participant (e.g., 8/2 condition where, from the total of 10 coins, 8 coins were visible to both players and 2 coins only visible to the proposer). In total, 22 young adults and 79 children between ages 8 and 13 played multiple one-shot versions of the UG with hidden conditions with anonymous others. Overall analyses confirmed validity of the task and showed that participants of all age groups had strategic intentions. Specific task analyses revealed that adults divided the coins equally in the standard UG conditions, but gave less to the second player in the hidden information conditions. The developmental comparisons revealed an age × condition interaction, such that adults and 10- to 12-year-old children differentiated between standard and hidden conditions more than 8- to 9-year-old children. These findings indicate that young children have a basic understanding of different strategic motives, but that behavior of adults and older children is driven more by strategic intentions. PMID:23162494

Classical conditioning without verbal suggestions elicits placebo analgesia and nocebo hyperalgesia

PubMed Central

Bajcar, Elżbieta A.; Adamczyk, Wacław; Kicman, Paweł; Lisińska, Natalia; Świder, Karolina; Colloca, Luana

2017-01-01

The aim of this study was to examine the relationships among classical conditioning, expectancy, and fear in placebo analgesia and nocebo hyperalgesia. A total of 42 healthy volunteers were randomly assigned to three groups: placebo, nocebo, and control. They received 96 electrical stimuli, preceded by either orange or blue lights. A hidden conditioning procedure, in which participants were not informed about the meaning of coloured lights, was performed in the placebo and nocebo groups. Light of one colour was paired with pain stimuli of moderate intensity (control stimuli), and light of the other colour was paired with either nonpainful stimuli (in the placebo group) or painful stimuli of high intensity (in the nocebo group). In the control group, both colour lights were followed by control stimuli of moderate intensity without any conditioning procedure. Participants rated pain intensity, expectancy of pain intensity, and fear. In the testing phase, when both of the coloured lights were followed by identical moderate pain stimuli, we found a significant analgesic effect in the placebo group, and a significant hyperalgesic effect in the nocebo group. Neither expectancy nor fear ratings predicted placebo analgesia or nocebo hyperalgesia. It appears that a hidden conditioning procedure, without any explicit verbal suggestions, elicits placebo and nocebo effects, however we found no evidence that these effects are predicted by either expectancy or fear. These results suggest that classical conditioning may be a distinct mechanism for placebo and nocebo effects. PMID:28750001

Vertices cannot be hidden from quantum spatial search for almost all random graphs

NASA Astrophysics Data System (ADS)

Glos, Adam; Krawiec, Aleksandra; Kukulski, Ryszard; Puchała, Zbigniew

2018-04-01

In this paper, we show that all nodes can be found optimally for almost all random Erdős-Rényi G(n,p) graphs using continuous-time quantum spatial search procedure. This works for both adjacency and Laplacian matrices, though under different conditions. The first one requires p=ω (log ^8(n)/n), while the second requires p≥ (1+ɛ )log (n)/n, where ɛ >0. The proof was made by analyzing the convergence of eigenvectors corresponding to outlying eigenvalues in the \\Vert \\cdot \\Vert _∞ norm. At the same time for p<(1-ɛ )log (n)/n, the property does not hold for any matrix, due to the connectivity issues. Hence, our derivation concerning Laplacian matrix is tight.

Lotka-Volterra systems in environments with randomly disordered temporal periodicity.

PubMed

Naess, Arvid; Dimentberg, Michael F; Gaidai, Oleg

2008-08-01

A generalized Lotka-Volterra model for a pair of interacting populations of predators and prey is studied. The model accounts for the prey's interspecies competition and therefore is asymptotically stable, whereas its oscillatory behavior is induced by temporal variations in environmental conditions simulated by those in the prey's reproduction rate. Two models of the variations are considered, each of them combining randomness with "hidden" periodicity. The stationary joint probability density function (PDF) of the number of predators and prey is calculated numerically by the path integration (PI) method based on the use of characteristic functions and the fast Fourier transform. The numerical results match those for the asymptotic case of white-noise variations for which an analytical solution is available. Several examples are studied, with calculations of important characteristics of oscillations, for example the expected rate of up-crossings given the level of the predator number. The calculated PDFs may be of predominantly random (unimodal) or predominantly periodic nature (bimodal). Thus, the PI method has been demonstrated to be a powerful tool for studies of the dynamics of predator-prey pairs. The method captures the random oscillations as observed in nature, taking into account potential periodicity in the environmental conditions.

Efficient Text Encryption and Hiding with Double-Random Phase-Encoding

PubMed Central

Sang, Jun; Ling, Shenggui; Alam, Mohammad S.

2012-01-01

In this paper, a double-random phase-encoding technique-based text encryption and hiding method is proposed. First, the secret text is transformed into a 2-dimensional array and the higher bits of the elements in the transformed array are used to store the bit stream of the secret text, while the lower bits are filled with specific values. Then, the transformed array is encoded with double-random phase-encoding technique. Finally, the encoded array is superimposed on an expanded host image to obtain the image embedded with hidden data. The performance of the proposed technique, including the hiding capacity, the recovery accuracy of the secret text, and the quality of the image embedded with hidden data, is tested via analytical modeling and test data stream. Experimental results show that the secret text can be recovered either accurately or almost accurately, while maintaining the quality of the host image embedded with hidden data by properly selecting the method of transforming the secret text into an array and the superimposition coefficient. By using optical information processing techniques, the proposed method has been found to significantly improve the security of text information transmission, while ensuring hiding capacity at a prescribed level. PMID:23202003

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.

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.

Effects of tai chi qigong on psychosocial well-being among hidden elderly, using elderly neighborhood volunteer approach: a pilot randomized controlled trial.

PubMed

Chan, Aileen Wk; Yu, Doris Sf; Choi, K C

2017-01-01

To test the feasibility and preliminary effectiveness of a tai chi qigong program with the assistance of elderly neighborhood volunteers in strengthening social networks and enhancing the psychosocial well-being of hidden elderly. "Hidden elderly" is a term used to describe older adults who are socially isolated and refuse social participation. This pilot randomized controlled trial recruited 48 older adults aged 60 or above who did not engage in any social activity. They were randomized into tai chi qigong (n=24) and standard care control (n=24) groups. The former group underwent a three-month program of two 60-minute sessions each week, with the socially active volunteers paired up with them during practice. Standard care included regular home visits by social workers. Primary outcomes were assessed by means of the Lubben social network and De Jong Gieveld loneliness scales, and by a revised social support questionnaire. Secondary outcomes were covered by a mental health inventory and the Rosenberg self-esteem scale, and quality of life by using the 12-Item Short Form Health Survey. Data was collected at baseline, and at three and six months thereafter. The generalized estimating equations model revealed general improvement in outcomes among participants on the tai chi qigong program. In particular, participants reported a significantly greater improvement on the loneliness scale ( B =-1.32, 95% confidence interval [CI] -2.54 to -0.11, P =0.033) and the satisfaction component of the social support questionnaire ( B =3.43, 95% CI 0.10-6.76, P =0.044) than the control group. The pilot study confirmed that tai chi qigong with elderly neighborhood volunteers is a safe and feasible social intervention for hidden elderly. Its potential benefits in improving social and psychological health suggest the need for a full-scale randomized controlled trial to reveal its empirical effects.

Optimal random search for a single hidden target.

PubMed

Snider, Joseph

2011-01-01

A single target is hidden at a location chosen from a predetermined probability distribution. Then, a searcher must find a second probability distribution from which random search points are sampled such that the target is found in the minimum number of trials. Here it will be shown that if the searcher must get very close to the target to find it, then the best search distribution is proportional to the square root of the target distribution regardless of dimension. For a Gaussian target distribution, the optimum search distribution is approximately a Gaussian with a standard deviation that varies inversely with how close the searcher must be to the target to find it. For a network where the searcher randomly samples nodes and looks for the fixed target along edges, the optimum is either to sample a node with probability proportional to the square root of the out-degree plus 1 or not to do so at all.

Quasi-steady state reduction of molecular motor-based models of directed intermittent search.

PubMed

Newby, Jay M; Bressloff, Paul C

2010-10-01

We present a quasi-steady state reduction of a linear reaction-hyperbolic master equation describing the directed intermittent search for a hidden target by a motor-driven particle moving on a one-dimensional filament track. The particle is injected at one end of the track and randomly switches between stationary search phases and mobile nonsearch phases that are biased in the anterograde direction. There is a finite possibility that the particle fails to find the target due to an absorbing boundary at the other end of the track. Such a scenario is exemplified by the motor-driven transport of vesicular cargo to synaptic targets located on the axon or dendrites of a neuron. The reduced model is described by a scalar Fokker-Planck (FP) equation, which has an additional inhomogeneous decay term that takes into account absorption by the target. The FP equation is used to compute the probability of finding the hidden target (hitting probability) and the corresponding conditional mean first passage time (MFPT) in terms of the effective drift velocity V, diffusivity D, and target absorption rate λ of the random search. The quasi-steady state reduction determines V, D, and λ in terms of the various biophysical parameters of the underlying motor transport model. We first apply our analysis to a simple 3-state model and show that our quasi-steady state reduction yields results that are in excellent agreement with Monte Carlo simulations of the full system under physiologically reasonable conditions. We then consider a more complex multiple motor model of bidirectional transport, in which opposing motors compete in a "tug-of-war", and use this to explore how ATP concentration might regulate the delivery of cargo to synaptic targets.

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.

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

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

Hiding the Tobacco Power Wall Reduces Cigarette Smoking Risk in Adolescents: Using an Experimental Convenience Store to Assess Tobacco Regulatory Options at Retail Point-of-Sale

PubMed Central

Shadel, William G.; Martino, Steven; Setodji, Claude; Scharf, Deborah; Kusuke, Daniela; Sicker, Angela; Gong, Min

2015-01-01

Objectives This experiment tested whether changing the location or visibility of the tobacco power wall in a life sized replica of a convenience store had any effect on adolescents’ susceptibility to future cigarette smoking. Methods The study was conducted in the RAND StoreLab (RSL), a life sized replica of a convenience store that was developed to experimentally evaluate how changing aspects of tobacco advertising displays in retail point-of-sale environments influences tobacco use risk and behavior. A randomized, between-subjects experimental design with three conditions that varied the location or visibility of the tobacco power wall within the RSL was used. The conditions were: cashier (the tobacco power wall was located in its typical position behind the cash register counter); sidewall (the tobacco power wall was located on a sidewall away from the cash register); or hidden (the tobacco power wall was located behind the cashier but was hidden behind an opaque wall). The sample included 241 adolescents. Results Hiding the tobacco power wall significantly reduced adolescents’ susceptibility to future cigarette smoking compared to leaving it exposed (i.e., the cashier condition; p = .02). Locating the tobacco power wall on a sidewall away from the cashier had no effect on future cigarette smoking susceptibility compared to the cashier condition (p = 0.80). Conclusions Hiding the tobacco power wall at retail point-of-sale locations is a strong regulatory option for reducing the impact of the retail environment on cigarette smoking risk in adolescents. PMID:26598502

Automated brain tumor segmentation using spatial accuracy-weighted hidden Markov Random Field.

PubMed

Nie, Jingxin; Xue, Zhong; Liu, Tianming; Young, Geoffrey S; Setayesh, Kian; Guo, Lei; Wong, Stephen T C

2009-09-01

A variety of algorithms have been proposed for brain tumor segmentation from multi-channel sequences, however, most of them require isotropic or pseudo-isotropic resolution of the MR images. Although co-registration and interpolation of low-resolution sequences, such as T2-weighted images, onto the space of the high-resolution image, such as T1-weighted image, can be performed prior to the segmentation, the results are usually limited by partial volume effects due to interpolation of low-resolution images. To improve the quality of tumor segmentation in clinical applications where low-resolution sequences are commonly used together with high-resolution images, we propose the algorithm based on Spatial accuracy-weighted Hidden Markov random field and Expectation maximization (SHE) approach for both automated tumor and enhanced-tumor segmentation. SHE incorporates the spatial interpolation accuracy of low-resolution images into the optimization procedure of the Hidden Markov Random Field (HMRF) to segment tumor using multi-channel MR images with different resolutions, e.g., high-resolution T1-weighted and low-resolution T2-weighted images. In experiments, we evaluated this algorithm using a set of simulated multi-channel brain MR images with known ground-truth tissue segmentation and also applied it to a dataset of MR images obtained during clinical trials of brain tumor chemotherapy. The results show that more accurate tumor segmentation results can be obtained by comparing with conventional multi-channel segmentation algorithms.

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.

Hidden long evolutionary memory in a model biochemical network

NASA Astrophysics Data System (ADS)

Ali, Md. Zulfikar; Wingreen, Ned S.; Mukhopadhyay, Ranjan

2018-04-01

We introduce a minimal model for the evolution of functional protein-interaction networks using a sequence-based mutational algorithm, and apply the model to study neutral drift in networks that yield oscillatory dynamics. Starting with a functional core module, random evolutionary drift increases network complexity even in the absence of specific selective pressures. Surprisingly, we uncover a hidden order in sequence space that gives rise to long-term evolutionary memory, implying strong constraints on network evolution due to the topology of accessible sequence space.

Interactive learning in 2×2 normal form games by neural network agents

NASA Astrophysics Data System (ADS)

Spiliopoulos, Leonidas

2012-11-01

This paper models the learning process of populations of randomly rematched tabula rasa neural network (NN) agents playing randomly generated 2×2 normal form games of all strategic classes. This approach has greater external validity than the existing models in the literature, each of which is usually applicable to narrow subsets of classes of games (often a single game) and/or to fixed matching protocols. The learning prowess of NNs with hidden layers was impressive as they learned to play unique pure strategy equilibria with near certainty, adhered to principles of dominance and iterated dominance, and exhibited a preference for risk-dominant equilibria. In contrast, perceptron NNs were found to perform significantly worse than hidden layer NN agents and human subjects in experimental studies.

A novel attack method about double-random-phase-encoding-based image hiding method

NASA Astrophysics Data System (ADS)

Xu, Hongsheng; Xiao, Zhijun; Zhu, Xianchen

2018-03-01

By using optical image processing techniques, a novel text encryption and hiding method applied by double-random phase-encoding technique is proposed in the paper. The first step is that the secret message is transformed into a 2-dimension array. The higher bits of the elements in the array are used to fill with the bit stream of the secret text, while the lower bits are stored specific values. Then, the transformed array is encoded by double random phase encoding technique. Last, the encoded array is embedded on a public host image to obtain the image embedded with hidden text. The performance of the proposed technique is tested via analytical modeling and test data stream. Experimental results show that the secret text can be recovered either accurately or almost accurately, while maintaining the quality of the host image embedded with hidden data by properly selecting the method of transforming the secret text into an array and the superimposition coefficient.

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).

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 ...

Estimates of Storage Capacity of Multilayer Perceptron with Threshold Logic Hidden Units.

PubMed

Kowalczyk, Adam

1997-11-01

We estimate the storage capacity of multilayer perceptron with n inputs, h(1) threshold logic units in the first hidden layer and 1 output. We show that if the network can memorize 50% of all dichotomies of a randomly selected N-tuple of points of R(n) with probability 1, then N

Reward-Based Spatial Learning in Teens With Bulimia Nervosa

PubMed Central

Cyr, Marilyn; Wang, Zhishun; Tau, Gregory Z.; Zhao, Guihu; Friedl, Eve; Stefan, Mihaela; Terranova, Kate; Marsh, Rachel

2016-01-01

Objective To assess the functioning of mesolimbic and fronto-striatal areas involved in reward-based spatial learning in teenaged girls with bulimia nervosa (BN) that might be involved in the development and maintenance of maladaptive behaviors characteristic of the disorder. Method We compared functional magnetic resonance imaging blood oxygen level dependent response in 27 adolescent girls with BN to that of 27 healthy, age-matched control participants during a reward-based learning task that required learning to use extra-maze cues to navigate a virtual 8-arm radial maze to find hidden rewards. We compared groups in their patterns of brain activation associated with reward-based spatial learning versus a control condition in which rewards were unexpected because they were allotted pseudo-randomly to experimentally prevent learning. Results Both groups learned to navigate the maze to find hidden rewards, but group differences in brain activity associated with maze navigation and reward processing were detected in fronto-striatal regions and right anterior hippocampus. Unlike healthy adolescents, those with BN did not engage right inferior frontal gyrus during maze navigation, activated right anterior hippocampus during the receipt of unexpected rewards (control condition), and deactivated left superior frontal gyrus and right anterior hippocampus during expected reward receipt (learning condition). These patterns of hippocampal activation in the control condition were significantly associated with the frequency of binge-eating episodes. Conclusion Adolescents with BN displayed abnormal functioning of anterior hippocampus and fronto-striatal regions during reward-based spatial learning. These findings suggest that an imbalance in control and reward circuits may arise early in the course of BN. Clinical trial registration information An fMRI Study of Self-regulation in Adolescents With Bulimia Nervosa; https://clinicaltrials.gov/ct2/show/NCT00345943; NCT00345943. PMID:27806864

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

A Hidden Transhydrogen Activity of a FMN-Bound Diaphorase under Anaerobic Conditions

DTIC Science & Technology

2016-05-04

RESEARCH ARTICLE A Hidden Transhydrogen Activity of a FMN- Bound Diaphorase under Anaerobic Conditions John Collins1, Ting Zhang1, Scott Huston1... metabolic pathways for facilitating the electron transfer from one molecule to another in redox reactions. Transhy- drogenase plays an important role in...March 2, 2016 Accepted: April 20, 2016 Published: May 4, 2016 Copyright: © 2016 Collins et al. This is an open access article distributed under the

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

On some dynamical chameleon systems

NASA Astrophysics Data System (ADS)

Burkin, I. M.; Kuznetsova, O. I.

2018-03-01

It is now well known that dynamical systems can be categorized into systems with self-excited attractors and systems with hidden attractors. A self-excited attractor has a basin of attraction that is associated with an unstable equilibrium, while a hidden attractor has a basin of attraction that does not intersect with small neighborhoods of any equilibrium points. Hidden attractors play the important role in engineering applications because they allow unexpected and potentially disastrous responses to perturbations in a structure like a bridge or an airplane wing. In addition, complex behaviors of chaotic systems have been applied in various areas from image watermarking, audio encryption scheme, asymmetric color pathological image encryption, chaotic masking communication to random number generator. Recently, researchers have discovered the so-called “chameleon systems”. These systems were so named because they demonstrate self-excited or hidden oscillations depending on the value of parameters. The present paper offers a simple algorithm of synthesizing one-parameter chameleon systems. The authors trace the evolution of Lyapunov exponents and the Kaplan-Yorke dimension of such systems which occur when parameters change.

Constructing 1/omegaalpha noise from reversible Markov chains.

PubMed

Erland, Sveinung; Greenwood, Priscilla E

2007-09-01

This paper gives sufficient conditions for the output of 1/omegaalpha noise from reversible Markov chains on finite state spaces. We construct several examples exhibiting this behavior in a specified range of frequencies. We apply simple representations of the covariance function and the spectral density in terms of the eigendecomposition of the probability transition matrix. The results extend to hidden Markov chains. We generalize the results for aggregations of AR1-processes of C. W. J. Granger [J. Econometrics 14, 227 (1980)]. Given the eigenvalue function, there is a variety of ways to assign values to the states such that the 1/omegaalpha condition is satisfied. We show that a random walk on a certain state space is complementary to the point process model of 1/omega noise of B. Kaulakys and T. Meskauskas [Phys. Rev. E 58, 7013 (1998)]. Passing to a continuous state space, we construct 1/omegaalpha noise which also has a long memory.

Hearing: The Future of Sensory Rehabilitation?

PubMed

Skoe, Erika

2017-11-06

A new randomized, double-blind controlled study has found that playing a video game modeled from sensory foraging behavior can improve the aging brain's ability to hear complex signals hidden in background noise. Copyright © 2017 Elsevier Ltd. All rights reserved.

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

An information hidden model holding cover distributions

NASA Astrophysics Data System (ADS)

Fu, Min; Cai, Chao; Dai, Zuxu

2018-03-01

The goal of steganography is to embed secret data into a cover so no one apart from the sender and intended recipients can find the secret data. Usually, the way the cover changing was decided by a hidden function. There were no existing model could be used to find an optimal function which can greatly reduce the distortion the cover suffered. This paper considers the cover carrying secret message as a random Markov chain, taking the advantages of a deterministic relation between initial distributions and transferring matrix of the Markov chain, and takes the transferring matrix as a constriction to decrease statistical distortion the cover suffered in the process of information hiding. Furthermore, a hidden function is designed and the transferring matrix is also presented to be a matrix from the original cover to the stego cover. Experiment results show that the new model preserves a consistent statistical characterizations of original and stego cover.

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.

Pseudo-random bit generator based on lag time series

NASA Astrophysics Data System (ADS)

García-Martínez, M.; Campos-Cantón, E.

2014-12-01

In this paper, we present a pseudo-random bit generator (PRBG) based on two lag time series of the logistic map using positive and negative values in the bifurcation parameter. In order to hidden the map used to build the pseudo-random series we have used a delay in the generation of time series. These new series when they are mapped xn against xn+1 present a cloud of points unrelated to the logistic map. Finally, the pseudo-random sequences have been tested with the suite of NIST giving satisfactory results for use in stream ciphers.

Quantile regression reveals hidden bias and uncertainty in habitat models

Treesearch

Brian S. Cade; Barry R. Noon; Curtis H. Flather

2005-01-01

We simulated the effects of missing information on statistical distributions of animal response that covaried with measured predictors of habitat to evaluate the utility and performance of quantile regression for providing more useful intervals of uncertainty in habitat relationships. These procedures were evaulated for conditions in which heterogeneity and hidden bias...

Intelligent data analysis to model and understand live cell time-lapse sequences.

PubMed

Paterson, Allan; Ashtari, M; Ribé, D; Stenbeck, G; Tucker, A

2012-01-01

One important aspect of cellular function, which is at the basis of tissue homeostasis, is the delivery of proteins to their correct destinations. Significant advances in live cell microscopy have allowed tracking of these pathways by following the dynamics of fluorescently labelled proteins in living cells. This paper explores intelligent data analysis techniques to model the dynamic behavior of proteins in living cells as well as to classify different experimental conditions. We use a combination of decision tree classification and hidden Markov models. In particular, we introduce a novel approach to "align" hidden Markov models so that hidden states from different models can be cross-compared. Our models capture the dynamics of two experimental conditions accurately with a stable hidden state for control data and multiple (less stable) states for the experimental data recapitulating the behaviour of particle trajectories within live cell time-lapse data. In addition to having successfully developed an automated framework for the classification of protein transport dynamics from live cell time-lapse data our model allows us to understand the dynamics of a complex trafficking pathway in living cells in culture.

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.

Is extreme learning machine feasible? A theoretical assessment (part I).

PubMed

Liu, Xia; Lin, Shaobo; Fang, Jian; Xu, Zongben

2015-01-01

An extreme learning machine (ELM) is a feedforward neural network (FNN) like learning system whose connections with output neurons are adjustable, while the connections with and within hidden neurons are randomly fixed. Numerous applications have demonstrated the feasibility and high efficiency of ELM-like systems. It has, however, been open if this is true for any general applications. In this two-part paper, we conduct a comprehensive feasibility analysis of ELM. In Part I, we provide an answer to the question by theoretically justifying the following: 1) for some suitable activation functions, such as polynomials, Nadaraya-Watson and sigmoid functions, the ELM-like systems can attain the theoretical generalization bound of the FNNs with all connections adjusted, i.e., they do not degrade the generalization capability of the FNNs even when the connections with and within hidden neurons are randomly fixed; 2) the number of hidden neurons needed for an ELM-like system to achieve the theoretical bound can be estimated; and 3) whenever the activation function is taken as polynomial, the deduced hidden layer output matrix is of full column-rank, therefore the generalized inverse technique can be efficiently applied to yield the solution of an ELM-like system, and, furthermore, for the nonpolynomial case, the Tikhonov regularization can be applied to guarantee the weak regularity while not sacrificing the generalization capability. In Part II, however, we reveal a different aspect of the feasibility of ELM: there also exists some activation functions, which makes the corresponding ELM degrade the generalization capability. The obtained results underlie the feasibility and efficiency of ELM-like systems, and yield various generalizations and improvements of the systems as well.

A Hybrid Generalized Hidden Markov Model-Based Condition Monitoring Approach for Rolling Bearings

PubMed Central

Liu, Jie; Hu, Youmin; Wu, Bo; Wang, Yan; Xie, Fengyun

2017-01-01

The operating condition of rolling bearings affects productivity and quality in the rotating machine process. Developing an effective rolling bearing condition monitoring approach is critical to accurately identify the operating condition. In this paper, a hybrid generalized hidden Markov model-based condition monitoring approach for rolling bearings is proposed, where interval valued features are used to efficiently recognize and classify machine states in the machine process. In the proposed method, vibration signals are decomposed into multiple modes with variational mode decomposition (VMD). Parameters of the VMD, in the form of generalized intervals, provide a concise representation for aleatory and epistemic uncertainty and improve the robustness of identification. The multi-scale permutation entropy method is applied to extract state features from the decomposed signals in different operating conditions. Traditional principal component analysis is adopted to reduce feature size and computational cost. With the extracted features’ information, the generalized hidden Markov model, based on generalized interval probability, is used to recognize and classify the fault types and fault severity levels. Finally, the experiment results show that the proposed method is effective at recognizing and classifying the fault types and fault severity levels of rolling bearings. This monitoring method is also efficient enough to quantify the two uncertainty components. PMID:28524088

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

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

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

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

Scalable learning method for feedforward neural networks using minimal-enclosing-ball approximation.

PubMed

Wang, Jun; Deng, Zhaohong; Luo, Xiaoqing; Jiang, Yizhang; Wang, Shitong

2016-06-01

Training feedforward neural networks (FNNs) is one of the most critical issues in FNNs studies. However, most FNNs training methods cannot be directly applied for very large datasets because they have high computational and space complexity. In order to tackle this problem, the CCMEB (Center-Constrained Minimum Enclosing Ball) problem in hidden feature space of FNN is discussed and a novel learning algorithm called HFSR-GCVM (hidden-feature-space regression using generalized core vector machine) is developed accordingly. In HFSR-GCVM, a novel learning criterion using L2-norm penalty-based ε-insensitive function is formulated and the parameters in the hidden nodes are generated randomly independent of the training sets. Moreover, the learning of parameters in its output layer is proved equivalent to a special CCMEB problem in FNN hidden feature space. As most CCMEB approximation based machine learning algorithms, the proposed HFSR-GCVM training algorithm has the following merits: The maximal training time of the HFSR-GCVM training is linear with the size of training datasets and the maximal space consumption is independent of the size of training datasets. The experiments on regression tasks confirm the above conclusions. Copyright © 2016 Elsevier Ltd. All rights reserved.

Exponential gain of randomness certified by quantum contextuality

NASA Astrophysics Data System (ADS)

Um, Mark; Zhang, Junhua; Wang, Ye; Wang, Pengfei; Kim, Kihwan

2017-04-01

We demonstrate the protocol of exponential gain of randomness certified by quantum contextuality in a trapped ion system. The genuine randomness can be produced by quantum principle and certified by quantum inequalities. Recently, randomness expansion protocols based on inequality of Bell-text and Kochen-Specker (KS) theorem, have been demonstrated. These schemes have been theoretically innovated to exponentially expand the randomness and amplify the randomness from weak initial random seed. Here, we report the experimental evidence of such exponential expansion of randomness. In the experiment, we use three states of a 138Ba + ion between a ground state and two quadrupole states. In the 138Ba + ion system, we do not have detection loophole and we apply a methods to rule out certain hidden variable models that obey a kind of extended noncontextuality.

Semantic Stability is More Pleasurable in Unstable Episodic Contexts. On the Relevance of Perceptual Challenge in Art Appreciation.

PubMed

Muth, Claudia; Raab, Marius H; Carbon, Claus-Christian

2016-01-01

Research in the field of psychological aesthetics points to the appeal of stimuli which defy easy recognition by being "semantically unstable" but which still allow for creating meaning-in the ongoing process of elaborative perception or as an end product of the entire process. Such effects were reported for hidden images (Muth and Carbon, 2013) as well as Cubist artworks concealing detectable-although fragmented-objects (Muth et al., 2013). To test the stability of the relationship between semantic determinacy and appreciation across different episodic contexts, 30 volunteers evaluated an artistic movie continuously on visual determinacy or liking via the Continuous Evaluation Procedure (CEP, Muth et al., 2015b). The movie consisted of five episodes with emerging Gestalts. In the first between-participants condition, the hidden Gestalts in the movie episodes were of increasing determinacy, in the second condition, the episodes showed decreasing determinacies of hidden Gestalts. In the increasing-determinacy group, visual determinacy was rated higher and showed better predictive quality for liking than in the decreasing-determinacy group. Furthermore, when the movie started with low visual determinacy of hidden Gestalts, unexpectedly strong increases in visual determinacy had a bigger effect on liking than in the condition which allowed for weaker Gestalt recognition after having started with highly determinate Gestalts. The resulting pattern calls for consideration of the episodic context when examining art appreciation.

Clustering coefficients of protein-protein interaction networks

NASA Astrophysics Data System (ADS)

Miller, Gerald A.; Shi, Yi Y.; Qian, Hong; Bomsztyk, Karol

2007-05-01

The properties of certain networks are determined by hidden variables that are not explicitly measured. The conditional probability (propagator) that a vertex with a given value of the hidden variable is connected to k other vertices determines all measurable properties. We study hidden variable models and find an averaging approximation that enables us to obtain a general analytical result for the propagator. Analytic results showing the validity of the approximation are obtained. We apply hidden variable models to protein-protein interaction networks (PINs) in which the hidden variable is the association free energy, determined by distributions that depend on biochemistry and evolution. We compute degree distributions as well as clustering coefficients of several PINs of different species; good agreement with measured data is obtained. For the human interactome two different parameter sets give the same degree distributions, but the computed clustering coefficients differ by a factor of about 2. This shows that degree distributions are not sufficient to determine the properties of PINs.

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.

A Heavy Tailed Expectation Maximization Hidden Markov Random Field Model with Applications to Segmentation of MRI

PubMed Central

Castillo-Barnes, Diego; Peis, Ignacio; Martínez-Murcia, Francisco J.; Segovia, Fermín; Illán, Ignacio A.; Górriz, Juan M.; Ramírez, Javier; Salas-Gonzalez, Diego

2017-01-01

A wide range of segmentation approaches assumes that intensity histograms extracted from magnetic resonance images (MRI) have a distribution for each brain tissue that can be modeled by a Gaussian distribution or a mixture of them. Nevertheless, intensity histograms of White Matter and Gray Matter are not symmetric and they exhibit heavy tails. In this work, we present a hidden Markov random field model with expectation maximization (EM-HMRF) modeling the components using the α-stable distribution. The proposed model is a generalization of the widely used EM-HMRF algorithm with Gaussian distributions. We test the α-stable EM-HMRF model in synthetic data and brain MRI data. The proposed methodology presents two main advantages: Firstly, it is more robust to outliers. Secondly, we obtain similar results than using Gaussian when the Gaussian assumption holds. This approach is able to model the spatial dependence between neighboring voxels in tomographic brain MRI. PMID:29209194

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.

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.

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.

Reward-Based Spatial Learning in Teens With Bulimia Nervosa.

PubMed

Cyr, Marilyn; Wang, Zhishun; Tau, Gregory Z; Zhao, Guihu; Friedl, Eve; Stefan, Mihaela; Terranova, Kate; Marsh, Rachel

2016-11-01

To assess the functioning of mesolimbic and fronto-striatal areas involved in reward-based spatial learning in teenaged girls with bulimia nervosa (BN) that might be involved in the development and maintenance of maladaptive behaviors characteristic of the disorder. We compared functional magnetic resonance imaging blood oxygen level-dependent response in 27 adolescent girls with BN to that of 27 healthy, age-matched control participants during a reward-based learning task that required learning to use extra-maze cues to navigate a virtual 8-arm radial maze to find hidden rewards. We compared groups in their patterns of brain activation associated with reward-based spatial learning versus a control condition in which rewards were unexpected because they were allotted pseudo-randomly to experimentally prevent learning. Both groups learned to navigate the maze to find hidden rewards, but group differences in brain activity associated with maze navigation and reward processing were detected in the fronto-striatal regions and right anterior hippocampus. Unlike healthy adolescents, those with BN did not engage the right inferior frontal gyrus during maze navigation, activated the right anterior hippocampus during the receipt of unexpected rewards (control condition), and deactivated the left superior frontal gyrus and right anterior hippocampus during expected reward receipt (learning condition). These patterns of hippocampal activation in the control condition were significantly associated with the frequency of binge-eating episodes. Adolescents with BN displayed abnormal functioning of the anterior hippocampus and fronto-striatal regions during reward-based spatial learning. These findings suggest that an imbalance in control and reward circuits may arise early in the course of BN. Clinical trial registration information-An fMRI Study of Self-Regulation in Adolescents With Bulimia Nervosa; https://clinicaltrials.gov/; NCT00345943. Copyright © 2016 American Academy of Child and Adolescent Psychiatry. Published by Elsevier Inc. All rights reserved.

A Fast SVD-Hidden-nodes based Extreme Learning Machine for Large-Scale Data Analytics.

PubMed

Deng, Wan-Yu; Bai, Zuo; Huang, Guang-Bin; Zheng, Qing-Hua

2016-05-01

Big dimensional data is a growing trend that is emerging in many real world contexts, extending from web mining, gene expression analysis, protein-protein interaction to high-frequency financial data. Nowadays, there is a growing consensus that the increasing dimensionality poses impeding effects on the performances of classifiers, which is termed as the "peaking phenomenon" in the field of machine intelligence. To address the issue, dimensionality reduction is commonly employed as a preprocessing step on the Big dimensional data before building the classifiers. In this paper, we propose an Extreme Learning Machine (ELM) approach for large-scale data analytic. In contrast to existing approaches, we embed hidden nodes that are designed using singular value decomposition (SVD) into the classical ELM. These SVD nodes in the hidden layer are shown to capture the underlying characteristics of the Big dimensional data well, exhibiting excellent generalization performances. The drawback of using SVD on the entire dataset, however, is the high computational complexity involved. To address this, a fast divide and conquer approximation scheme is introduced to maintain computational tractability on high volume data. The resultant algorithm proposed is labeled here as Fast Singular Value Decomposition-Hidden-nodes based Extreme Learning Machine or FSVD-H-ELM in short. In FSVD-H-ELM, instead of identifying the SVD hidden nodes directly from the entire dataset, SVD hidden nodes are derived from multiple random subsets of data sampled from the original dataset. Comprehensive experiments and comparisons are conducted to assess the FSVD-H-ELM against other state-of-the-art algorithms. The results obtained demonstrated the superior generalization performance and efficiency of the FSVD-H-ELM. Copyright © 2016 Elsevier Ltd. All rights reserved.

The hidden curriculum in undergraduate medical education: qualitative study of medical students' perceptions of teaching.

PubMed

Lempp, Heidi; Seale, Clive

2004-10-02

To study medical students' views about the quality of the teaching they receive during their undergraduate training, especially in terms of the hidden curriculum. Semistructured interviews with individual students. One medical school in the United Kingdom. 36 undergraduate medical students, across all stages of their training, selected by random and quota sampling, stratified by sex and ethnicity, with the whole medical school population as a sampling frame. Medical students' experiences and perceptions of the quality of teaching received during their undergraduate training. Students reported many examples of positive role models and effective, approachable teachers, with valued characteristics perceived according to traditional gendered stereotypes. They also described a hierarchical and competitive atmosphere in the medical school, in which haphazard instruction and teaching by humiliation occur, especially during the clinical training years. Following on from the recent reforms of the manifest curriculum, the hidden curriculum now needs attention to produce the necessary fundamental changes in the culture of undergraduate medical education.

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.

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

PubMed

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

2016-11-11

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

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.

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

NASA Astrophysics Data System (ADS)

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

2007-02-01

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

Multiscale hidden Markov models for photon-limited imaging

NASA Astrophysics Data System (ADS)

Nowak, Robert D.

1999-06-01

Photon-limited image analysis is often hindered by low signal-to-noise ratios. A novel Bayesian multiscale modeling and analysis method is developed in this paper to assist in these challenging situations. In addition to providing a very natural and useful framework for modeling an d processing images, Bayesian multiscale analysis is often much less computationally demanding compared to classical Markov random field models. This paper focuses on a probabilistic graph model called the multiscale hidden Markov model (MHMM), which captures the key inter-scale dependencies present in natural image intensities. The MHMM framework presented here is specifically designed for photon-limited imagin applications involving Poisson statistics, and applications to image intensity analysis are examined.

Constructing 1/ωα noise from reversible Markov chains

NASA Astrophysics Data System (ADS)

Erland, Sveinung; Greenwood, Priscilla E.

2007-09-01

This paper gives sufficient conditions for the output of 1/ωα noise from reversible Markov chains on finite state spaces. We construct several examples exhibiting this behavior in a specified range of frequencies. We apply simple representations of the covariance function and the spectral density in terms of the eigendecomposition of the probability transition matrix. The results extend to hidden Markov chains. We generalize the results for aggregations of AR1-processes of C. W. J. Granger [J. Econometrics 14, 227 (1980)]. Given the eigenvalue function, there is a variety of ways to assign values to the states such that the 1/ωα condition is satisfied. We show that a random walk on a certain state space is complementary to the point process model of 1/ω noise of B. Kaulakys and T. Meskauskas [Phys. Rev. E 58, 7013 (1998)]. Passing to a continuous state space, we construct 1/ωα noise which also has a long memory.

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.

Manifestation Determination Decisions and Students with Emotional/Behavioral Disorders

ERIC Educational Resources Information Center

Walker, Jennifer D.; Brigham, Frederick J.

2017-01-01

Sixteen general and special education teachers were randomly assigned to one of four teams that were to make manifestation determinations using two different "hidden profiles" case studies based on students with an emotional behavioral disability. One case study was constructed to support a decision of the behavior not being a…

[Influence of different surgeries on growth and development of alar cartilage in young-rabbit].

PubMed

Jiang, Lian; Dong, Xiqian; Song, Qinggao; Chen, Shang; Zou, Sihai

2011-01-01

The purpose of this study is to observe the affection of different clinical surgeries on alar nasal cartilages' growth and development. The experimental results can provide some theory basis for clinical surgeries. Twenty-eight New Zealand immature rabbits were used in this study, and divided into normal control group, hidden dissection group and cutting off alar nasal cartilages group randomly, which included 4,12 and 12 rabbits, separately. Arc incision were made on the mucous membrane of nasal cavity,and then dissect the alar nasal cartilages hidden or cut off the alar nasal cartilages, separately. The growth and development of the alar cartilage were observed at different stages after the surgery using histological and immuno-histochemical methods. Four weeks, eight weeks, twelve weeks and sixteen weeks after surgery, there were no significant differences in the indexes of chondrocytes between hidden dissection group and control group. In cutting off alar nasal cartilages group, fiber tissue were observed in the vacancy left after being cut off cartilages, and even mucous membrane tissue could be seen in some slices. There is no adverse influence on the growth and development of the alar cartilage after being hidden dissected. Contrarily, the restoring capability of transparent cartilage cannot counteract the injury resulted form the surgery after the alar nasal cartilages being cut off.

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.

Adaptive partially hidden Markov models with application to bilevel image coding.

PubMed

Forchhammer, S; Rasmussen, T S

1999-01-01

Partially hidden Markov models (PHMMs) have previously been introduced. The transition and emission/output probabilities from hidden states, as known from the HMMs, are conditioned on the past. This way, the HMM may be applied to images introducing the dependencies of the second dimension by conditioning. In this paper, the PHMM is extended to multiple sequences with a multiple token version and adaptive versions of PHMM coding are presented. The different versions of the PHMM are applied to lossless bilevel image coding. To reduce and optimize the model cost and size, the contexts are organized in trees and effective quantization of the parameters is introduced. The new coding methods achieve results that are better than the JBIG standard on selected test images, although at the cost of increased complexity. By the minimum description length principle, the methods presented for optimizing the code length may apply as guidance for training (P)HMMs for, e.g., segmentation or recognition purposes. Thereby, the PHMM models provide a new approach to image modeling.

Differential Susceptibility Experiments: Going beyond Correlational Evidence--Comment on beyond Mental Health, Differential Susceptibility Articles

ERIC Educational Resources Information Center

van IJzendoorn, Marinus H.; Bakermans-Kranenburg, Marian J.

2012-01-01

Reviewing the studies on differential susceptibility presented in this section, we argue that the time is ripe to go beyond correlational designs to differential susceptibility experiments. In such experiments, randomization prevents hidden moderator effects on the environment and guarantees the independence of moderator and outcome, while the…

Development of a restricted state space stochastic differential equation model for bacterial growth in rich media.

PubMed

Møller, Jan Kloppenborg; Bergmann, Kirsten Riber; Christiansen, Lasse Engbo; Madsen, Henrik

2012-07-21

In the present study, bacterial growth in a rich media is analysed in a Stochastic Differential Equation (SDE) framework. It is demonstrated that the SDE formulation and smoothened state estimates provide a systematic framework for data driven model improvements, using random walk hidden states. Bacterial growth is limited by the available substrate and the inclusion of diffusion must obey this natural restriction. By inclusion of a modified logistic diffusion term it is possible to introduce a diffusion term flexible enough to capture both the growth phase and the stationary phase, while concentration is restricted to the natural state space (substrate and bacteria non-negative). The case considered is the growth of Salmonella and Enterococcus in a rich media. It is found that a hidden state is necessary to capture the lag phase of growth, and that a flexible logistic diffusion term is needed to capture the random behaviour of the growth model. Further, it is concluded that the Monod effect is not needed to capture the dynamics of bacterial growth in the data presented. Copyright © 2012 Elsevier Ltd. All rights reserved.

Information sampling behavior with explicit sampling costs

PubMed Central

Juni, Mordechai Z.; Gureckis, Todd M.; Maloney, Laurence T.

2015-01-01

The decision to gather information should take into account both the value of information and its accrual costs in time, energy and money. Here we explore how people balance the monetary costs and benefits of gathering additional information in a perceptual-motor estimation task. Participants were rewarded for touching a hidden circular target on a touch-screen display. The target’s center coincided with the mean of a circular Gaussian distribution from which participants could sample repeatedly. Each “cue” — sampled one at a time — was plotted as a dot on the display. Participants had to repeatedly decide, after sampling each cue, whether to stop sampling and attempt to touch the hidden target or continue sampling. Each additional cue increased the participants’ probability of successfully touching the hidden target but reduced their potential reward. Two experimental conditions differed in the initial reward associated with touching the hidden target and the fixed cost per cue. For each condition we computed the optimal number of cues that participants should sample, before taking action, to maximize expected gain. Contrary to recent claims that people gather less information than they objectively should before taking action, we found that participants over-sampled in one experimental condition, and did not significantly under- or over-sample in the other. Additionally, while the ideal observer model ignores the current sample dispersion, we found that participants used it to decide whether to stop sampling and take action or continue sampling, a possible consequence of imperfect learning of the underlying population dispersion across trials. PMID:27429991

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.

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

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.

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

PubMed

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

2006-11-01

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

Damage evaluation by a guided wave-hidden Markov model based method

NASA Astrophysics Data System (ADS)

Mei, Hanfei; Yuan, Shenfang; Qiu, Lei; Zhang, Jinjin

2016-02-01

Guided wave based structural health monitoring has shown great potential in aerospace applications. However, one of the key challenges of practical engineering applications is the accurate interpretation of the guided wave signals under time-varying environmental and operational conditions. This paper presents a guided wave-hidden Markov model based method to improve the damage evaluation reliability of real aircraft structures under time-varying conditions. In the proposed approach, an HMM based unweighted moving average trend estimation method, which can capture the trend of damage propagation from the posterior probability obtained by HMM modeling is used to achieve a probabilistic evaluation of the structural damage. To validate the developed method, experiments are performed on a hole-edge crack specimen under fatigue loading condition and a real aircraft wing spar under changing structural boundary conditions. Experimental results show the advantage of the proposed method.

Estimating the Information Extracted by a Single Spiking Neuron from a Continuous Input Time Series.

PubMed

Zeldenrust, Fleur; de Knecht, Sicco; Wadman, Wytse J; Denève, Sophie; Gutkin, Boris

2017-01-01

Understanding the relation between (sensory) stimuli and the activity of neurons (i.e., "the neural code") lies at heart of understanding the computational properties of the brain. However, quantifying the information between a stimulus and a spike train has proven to be challenging. We propose a new ( in vitro ) method to measure how much information a single neuron transfers from the input it receives to its output spike train. The input is generated by an artificial neural network that responds to a randomly appearing and disappearing "sensory stimulus": the hidden state. The sum of this network activity is injected as current input into the neuron under investigation. The mutual information between the hidden state on the one hand and spike trains of the artificial network or the recorded spike train on the other hand can easily be estimated due to the binary shape of the hidden state. The characteristics of the input current, such as the time constant as a result of the (dis)appearance rate of the hidden state or the amplitude of the input current (the firing frequency of the neurons in the artificial network), can independently be varied. As an example, we apply this method to pyramidal neurons in the CA1 of mouse hippocampi and compare the recorded spike trains to the optimal response of the "Bayesian neuron" (BN). We conclude that like in the BN, information transfer in hippocampal pyramidal cells is non-linear and amplifying: the information loss between the artificial input and the output spike train is high if the input to the neuron (the firing of the artificial network) is not very informative about the hidden state. If the input to the neuron does contain a lot of information about the hidden state, the information loss is low. Moreover, neurons increase their firing rates in case the (dis)appearance rate is high, so that the (relative) amount of transferred information stays constant.

Inferring hidden causal relations between pathway members using reduced Google matrix of directed biological networks

PubMed Central

2018-01-01

Signaling pathways represent parts of the global biological molecular network which connects them into a seamless whole through complex direct and indirect (hidden) crosstalk whose structure can change during development or in pathological conditions. We suggest a novel methodology, called Googlomics, for the structural analysis of directed biological networks using spectral analysis of their Google matrices, using parallels with quantum scattering theory, developed for nuclear and mesoscopic physics and quantum chaos. We introduce analytical “reduced Google matrix” method for the analysis of biological network structure. The method allows inferring hidden causal relations between the members of a signaling pathway or a functionally related group of genes. We investigate how the structure of hidden causal relations can be reprogrammed as a result of changes in the transcriptional network layer during cancerogenesis. The suggested Googlomics approach rigorously characterizes complex systemic changes in the wiring of large causal biological networks in a computationally efficient way. PMID:29370181

The Effect of Visual Signals on Spatial Decision Making

ERIC Educational Resources Information Center

Danziger, Shai; Rafal, Robert

2009-01-01

We examined the effect of an irrelevant visual transient on the decision where to look for a hidden object. Participants also performed a conventional "inhibition of return" localization task. In Experiments 1 and 2 the two tasks were blocked and in Experiments 3 and 4 they were randomly interleaved. In every experiment there was a bias to select…

Random intermittent search and the tug-of-war model of motor-driven transport

NASA Astrophysics Data System (ADS)

Newby, Jay; Bressloff, Paul C.

2010-04-01

We formulate the 'tug-of-war' model of microtubule cargo transport by multiple molecular motors as an intermittent random search for a hidden target. A motor complex consisting of multiple molecular motors with opposing directional preference is modeled using a discrete Markov process. The motors randomly pull each other off of the microtubule so that the state of the motor complex is determined by the number of bound motors. The tug-of-war model prescribes the state transition rates and corresponding cargo velocities in terms of experimentally measured physical parameters. We add space to the resulting Chapman-Kolmogorov (CK) equation so that we can consider delivery of the cargo to a hidden target at an unknown location along the microtubule track. The target represents some subcellular compartment such as a synapse in a neuron's dendrites, and target delivery is modeled as a simple absorption process. Using a quasi-steady-state (QSS) reduction technique we calculate analytical approximations of the mean first passage time (MFPT) to find the target. We show that there exists an optimal adenosine triphosphate (ATP) concentration that minimizes the MFPT for two different cases: (i) the motor complex is composed of equal numbers of kinesin motors bound to two different microtubules (symmetric tug-of-war model) and (ii) the motor complex is composed of different numbers of kinesin and dynein motors bound to a single microtubule (asymmetric tug-of-war model).

Reservoir computing on the hypersphere

NASA Astrophysics Data System (ADS)

Andrecut, M.

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

Directed intermittent search for a hidden target on a dendritic tree

NASA Astrophysics Data System (ADS)

Newby, Jay M.; Bressloff, Paul C.

2009-08-01

Motivated by experimental observations of active (motor-driven) intracellular transport in neuronal dendrites, we analyze a stochastic model of directed intermittent search on a tree network. A particle injected from the cell body or soma into the primary branch of the dendritic tree randomly switches between a stationary search phase and a mobile nonsearch phase that is biased in the forward direction. A (synaptic) target is presented somewhere within the tree, which the particle can locate if it is within a certain range and in the searching phase. We approximate the moment generating function using Green’s function methods. The moment generating function is then used to compute the hitting probability and conditional mean first passage time to the target. We show that in contrast to a previously explored finite interval case, there is a range of parameters for which a bidirectional search strategy is more efficient than a unidirectional one in finding the target.

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.

Single-channel 40 Gbit/s digital coherent QAM quantum noise stream cipher transmission over 480 km.

PubMed

Yoshida, Masato; Hirooka, Toshihiko; Kasai, Keisuke; Nakazawa, Masataka

2016-01-11

We demonstrate the first 40 Gbit/s single-channel polarization-multiplexed, 5 Gsymbol/s, 16 QAM quantum noise stream cipher (QNSC) transmission over 480 km by incorporating ASE quantum noise from EDFAs as well as the quantum shot noise of the coherent state with multiple photons for the random masking of data. By using a multi-bit encoded scheme and digital coherent transmission techniques, secure optical communication with a record data capacity and transmission distance has been successfully realized. In this system, the signal level received by Eve is hidden by both the amplitude and the phase noise. The highest number of masked signals, 7.5 x 10(4), was achieved by using a QAM scheme with FEC, which makes it possible to reduce the output power from the transmitter while maintaining an error free condition for Bob. We have newly measured the noise distribution around I and Q encrypted data and shown experimentally with a data size of as large as 2(25) that the noise has a Gaussian distribution with no correlations. This distribution is suitable for the random masking of data.

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.

Nonlinear unitary quantum collapse model with self-generated noise

NASA Astrophysics Data System (ADS)

Geszti, Tamás

2018-04-01

Collapse models including some external noise of unknown origin are routinely used to describe phenomena on the quantum-classical border; in particular, quantum measurement. Although containing nonlinear dynamics and thereby exposed to the possibility of superluminal signaling in individual events, such models are widely accepted on the basis of fully reproducing the non-signaling statistical predictions of quantum mechanics. Here we present a deterministic nonlinear model without any external noise, in which randomness—instead of being universally present—emerges in the measurement process, from deterministic irregular dynamics of the detectors. The treatment is based on a minimally nonlinear von Neumann equation for a Stern–Gerlach or Bell-type measuring setup, containing coordinate and momentum operators in a self-adjoint skew-symmetric, split scalar product structure over the configuration space. The microscopic states of the detectors act as a nonlocal set of hidden parameters, controlling individual outcomes. The model is shown to display pumping of weights between setup-defined basis states, with a single winner randomly selected and the rest collapsing to zero. Environmental decoherence has no role in the scenario. Through stochastic modelling, based on Pearle’s ‘gambler’s ruin’ scheme, outcome probabilities are shown to obey Born’s rule under a no-drift or ‘fair-game’ condition. This fully reproduces quantum statistical predictions, implying that the proposed non-linear deterministic model satisfies the non-signaling requirement. Our treatment is still vulnerable to hidden signaling in individual events, which remains to be handled by future research.

Scalability, Complexity and Reliability in Quantum Information Processing

DTIC Science & Technology

2007-03-01

hidden subgroup framework to abelian groups which are not finitely generated. An extension of the basic algorithm breaks the Buchmann-Williams...finding short lattice vectors . In [2], we showed that the generalization of the standard method --- random coset state preparation followed by fourier...sampling --- required exponential time for sufficiently non-abelian groups including the symmetric group , at least when the fourier transforms are

Improving Classification Performance through an Advanced Ensemble Based Heterogeneous Extreme Learning Machines.

PubMed

Abuassba, Adnan O M; Zhang, Dezheng; Luo, Xiong; Shaheryar, Ahmad; Ali, Hazrat

2017-01-01

Extreme Learning Machine (ELM) is a fast-learning algorithm for a single-hidden layer feedforward neural network (SLFN). It often has good generalization performance. However, there are chances that it might overfit the training data due to having more hidden nodes than needed. To address the generalization performance, we use a heterogeneous ensemble approach. We propose an Advanced ELM Ensemble (AELME) for classification, which includes Regularized-ELM, L 2 -norm-optimized ELM (ELML2), and Kernel-ELM. The ensemble is constructed by training a randomly chosen ELM classifier on a subset of training data selected through random resampling. The proposed AELM-Ensemble is evolved by employing an objective function of increasing diversity and accuracy among the final ensemble. Finally, the class label of unseen data is predicted using majority vote approach. Splitting the training data into subsets and incorporation of heterogeneous ELM classifiers result in higher prediction accuracy, better generalization, and a lower number of base classifiers, as compared to other models (Adaboost, Bagging, Dynamic ELM ensemble, data splitting ELM ensemble, and ELM ensemble). The validity of AELME is confirmed through classification on several real-world benchmark datasets.

Improving Classification Performance through an Advanced Ensemble Based Heterogeneous Extreme Learning Machines

PubMed Central

Abuassba, Adnan O. M.; Ali, Hazrat

2017-01-01

Extreme Learning Machine (ELM) is a fast-learning algorithm for a single-hidden layer feedforward neural network (SLFN). It often has good generalization performance. However, there are chances that it might overfit the training data due to having more hidden nodes than needed. To address the generalization performance, we use a heterogeneous ensemble approach. We propose an Advanced ELM Ensemble (AELME) for classification, which includes Regularized-ELM, L2-norm-optimized ELM (ELML2), and Kernel-ELM. The ensemble is constructed by training a randomly chosen ELM classifier on a subset of training data selected through random resampling. The proposed AELM-Ensemble is evolved by employing an objective function of increasing diversity and accuracy among the final ensemble. Finally, the class label of unseen data is predicted using majority vote approach. Splitting the training data into subsets and incorporation of heterogeneous ELM classifiers result in higher prediction accuracy, better generalization, and a lower number of base classifiers, as compared to other models (Adaboost, Bagging, Dynamic ELM ensemble, data splitting ELM ensemble, and ELM ensemble). The validity of AELME is confirmed through classification on several real-world benchmark datasets. PMID:28546808

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

NASA Astrophysics Data System (ADS)

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

2018-05-01

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

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

PubMed

Ranganayaki, V; Deepa, S N

2016-01-01

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

Short-term memory in networks of dissociated cortical neurons.

PubMed

Dranias, Mark R; Ju, Han; Rajaram, Ezhilarasan; VanDongen, Antonius M J

2013-01-30

Short-term memory refers to the ability to store small amounts of stimulus-specific information for a short period of time. It is supported by both fading and hidden memory processes. Fading memory relies on recurrent activity patterns in a neuronal network, whereas hidden memory is encoded using synaptic mechanisms, such as facilitation, which persist even when neurons fall silent. We have used a novel computational and optogenetic approach to investigate whether these same memory processes hypothesized to support pattern recognition and short-term memory in vivo, exist in vitro. Electrophysiological activity was recorded from primary cultures of dissociated rat cortical neurons plated on multielectrode arrays. Cultures were transfected with ChannelRhodopsin-2 and optically stimulated using random dot stimuli. The pattern of neuronal activity resulting from this stimulation was analyzed using classification algorithms that enabled the identification of stimulus-specific memories. Fading memories for different stimuli, encoded in ongoing neural activity, persisted and could be distinguished from each other for as long as 1 s after stimulation was terminated. Hidden memories were detected by altered responses of neurons to additional stimulation, and this effect persisted longer than 1 s. Interestingly, network bursts seem to eliminate hidden memories. These results are similar to those that have been reported from similar experiments in vivo and demonstrate that mechanisms of information processing and short-term memory can be studied using cultured neuronal networks, thereby setting the stage for therapeutic applications using this platform.

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

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

PubMed Central

Ranganayaki, V.; Deepa, S. N.

2016-01-01

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

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

PubMed Central

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

2015-01-01

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

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.

Evidence of hidden leprosy in a supposedly low endemic area of Brazil.

PubMed

Bernardes, Fred; Paula, Natália Aparecida de; Leite, Marcel Nani; Abi-Rached, Thania Loyola Cordeiro; Vernal, Sebastian; Silva, Moises Batista da; Barreto, Josafá Gonçalves; Spencer, John Stewart; Frade, Marco Andrey Cipriani

2017-12-01

Show that hidden endemic leprosy exists in a municipality of inner São Paulo state (Brazil) with active surveillance actions based on clinical and immunological evaluations. The study sample was composed by people randomly selected by a dermatologist during medical care in the public emergency department and by active surveillance carried out during two days at a mobile clinic. All subjects received a dermato-neurological examination and blood sampling to determine anti-PGL-I antibody titers by enzyme-linked immunosorbent assay (ELISA). From July to December 2015, 24 new cases of leprosy were diagnosed; all were classified as multibacillary (MB) leprosy, one with severe Lucio's phenomenon. Seventeen (75%) were found with grade-1 or 2 disability at the moment of diagnosis. Anti-PGL-I titer was positive in 31/133 (23.3%) individuals, only 6/24 (25%) were positive in newly diagnosed leprosy cases. During the last ten years before this study, the average new case detection rate (NCDR) in this town was 2.62/100,000 population. After our work, the NCDR was raised to 42.8/100,000. These results indicate a very high number of hidden leprosy cases in this supposedly low endemic area of Brazil.

Bayesian structural inference for hidden processes.

PubMed

Strelioff, Christopher C; Crutchfield, James P

2014-04-01

We introduce a Bayesian approach to discovering patterns in structurally complex processes. The proposed method of Bayesian structural inference (BSI) relies on a set of candidate unifilar hidden Markov model (uHMM) topologies for inference of process structure from a data series. We employ a recently developed exact enumeration of topological ε-machines. (A sequel then removes the topological restriction.) This subset of the uHMM topologies has the added benefit that inferred models are guaranteed to be ε-machines, irrespective of estimated transition probabilities. Properties of ε-machines and uHMMs allow for the derivation of analytic expressions for estimating transition probabilities, inferring start states, and comparing the posterior probability of candidate model topologies, despite process internal structure being only indirectly present in data. We demonstrate BSI's effectiveness in estimating a process's randomness, as reflected by the Shannon entropy rate, and its structure, as quantified by the statistical complexity. We also compare using the posterior distribution over candidate models and the single, maximum a posteriori model for point estimation and show that the former more accurately reflects uncertainty in estimated values. We apply BSI to in-class examples of finite- and infinite-order Markov processes, as well to an out-of-class, infinite-state hidden process.

Bayesian structural inference for hidden processes

NASA Astrophysics Data System (ADS)

Strelioff, Christopher C.; Crutchfield, James P.

2014-04-01

We introduce a Bayesian approach to discovering patterns in structurally complex processes. The proposed method of Bayesian structural inference (BSI) relies on a set of candidate unifilar hidden Markov model (uHMM) topologies for inference of process structure from a data series. We employ a recently developed exact enumeration of topological ɛ-machines. (A sequel then removes the topological restriction.) This subset of the uHMM topologies has the added benefit that inferred models are guaranteed to be ɛ-machines, irrespective of estimated transition probabilities. Properties of ɛ-machines and uHMMs allow for the derivation of analytic expressions for estimating transition probabilities, inferring start states, and comparing the posterior probability of candidate model topologies, despite process internal structure being only indirectly present in data. We demonstrate BSI's effectiveness in estimating a process's randomness, as reflected by the Shannon entropy rate, and its structure, as quantified by the statistical complexity. We also compare using the posterior distribution over candidate models and the single, maximum a posteriori model for point estimation and show that the former more accurately reflects uncertainty in estimated values. We apply BSI to in-class examples of finite- and infinite-order Markov processes, as well to an out-of-class, infinite-state hidden process.

A Game of Hide and Seek: Expectations of Clumpy Resources Influence Hiding and Searching Patterns

PubMed Central

Wilke, Andreas; Minich, Steven; Panis, Megane; Langen, Tom A.; Skufca, Joseph D.; Todd, Peter M.

2015-01-01

Resources are often distributed in clumps or patches in space, unless an agent is trying to protect them from discovery and theft using a dispersed distribution. We uncover human expectations of such spatial resource patterns in collaborative and competitive settings via a sequential multi-person game in which participants hid resources for the next participant to seek. When collaborating, resources were mostly hidden in clumpy distributions, but when competing, resources were hidden in more dispersed (random or hyperdispersed) patterns to increase the searching difficulty for the other player. More dispersed resource distributions came at the cost of higher overall hiding (as well as searching) times, decreased payoffs, and an increased difficulty when the hider had to recall earlier hiding locations at the end of the experiment. Participants’ search strategies were also affected by their underlying expectations, using a win-stay lose-shift strategy appropriate for clumpy resources when searching for collaboratively-hidden items, but moving equally far after finding or not finding an item in competitive settings, as appropriate for dispersed resources. Thus participants showed expectations for clumpy versus dispersed spatial resources that matched the distributions commonly found in collaborative versus competitive foraging settings. PMID:26154661

New prospects in fixed target searches for dark forces with the SeaQuest experiment at Fermilab

DOE PAGES

Gardner, S.; Holt, R. J.; Tadepalli, A. S.

2016-06-10

An intense 120 GeV proton beam incident on an extremely long iron target generates enormous numbers of light-mass particles that also decay within that target. If one of these particles decays to a final state with a hidden gauge boson, or if such a particle is produced as a result of the initial collision, then that weakly interacting hidden-sector particle may traverse the remainder of the target and be detected downstream through its possible decay to an e +e –, μ +μ –, or π +π – final state. These conditions can be realized through an extension of the SeaQuestmore » experiment at Fermilab, and in this initial investigation we consider how it can serve as an ultrasensitive probe of hidden vector gauge forces, both Abelian and non-Abelian. Here a light, weakly coupled hidden sector may well explain the dark matter established through astrophysical observations, and the proposed search can provide tangible evidence for its existence—or, alternatively, constrain a “sea” of possibilities.« less

Wireless ultrasonic wavefield imaging via laser for hidden damage detection inside a steel box girder bridge

NASA Astrophysics Data System (ADS)

An, Yun-Kyu; Song, Homin; Sohn, Hoon

2014-09-01

This paper presents a wireless ultrasonic wavefield imaging (WUWI) technique for detecting hidden damage inside a steel box girder bridge. The proposed technique allows (1) complete wireless excitation of piezoelectric transducers and noncontact sensing of the corresponding responses using laser beams, (2) autonomous damage visualization without comparing against baseline data previously accumulated from the pristine condition of a target structure and (3) robust damage diagnosis even for real structures with complex structural geometries. First, a new WUWI hardware system was developed by integrating optoelectronic-based signal transmitting and receiving devices and a scanning laser Doppler vibrometer. Next, a damage visualization algorithm, self-referencing f-k filter (SRF), was introduced to isolate and visualize only crack-induced ultrasonic modes from measured ultrasonic wavefield images. Finally, the performance of the proposed technique was validated through hidden crack visualization at a decommissioned Ramp-G Bridge in South Korea. The experimental results reveal that the proposed technique instantaneously detects and successfully visualizes hidden cracks even in the complex structure of a real bridge.

Failure monitoring in dynamic systems: Model construction without fault training data

NASA Technical Reports Server (NTRS)

Smyth, P.; Mellstrom, J.

1993-01-01

Advances in the use of autoregressive models, pattern recognition methods, and hidden Markov models for on-line health monitoring of dynamic systems (such as DSN antennas) have recently been reported. However, the algorithms described in previous work have the significant drawback that data acquired under fault conditions are assumed to be available in order to train the model used for monitoring the system under observation. This article reports that this assumption can be relaxed and that hidden Markov monitoring models can be constructed using only data acquired under normal conditions and prior knowledge of the system characteristics being measured. The method is described and evaluated on data from the DSS 13 34-m beam wave guide antenna. The primary conclusion from the experimental results is that the method is indeed practical and holds considerable promise for application at the 70-m antenna sites where acquisition of fault data under controlled conditions is not realistic.

Multi-category micro-milling tool wear monitoring with continuous hidden Markov models

NASA Astrophysics Data System (ADS)

Zhu, Kunpeng; Wong, Yoke San; Hong, Geok Soon

2009-02-01

In-process monitoring of tool conditions is important in micro-machining due to the high precision requirement and high tool wear rate. Tool condition monitoring in micro-machining poses new challenges compared to conventional machining. In this paper, a multi-category classification approach is proposed for tool flank wear state identification in micro-milling. Continuous Hidden Markov models (HMMs) are adapted for modeling of the tool wear process in micro-milling, and estimation of the tool wear state given the cutting force features. For a noise-robust approach, the HMM outputs are connected via a medium filter to minimize the tool state before entry into the next state due to high noise level. A detailed study on the selection of HMM structures for tool condition monitoring (TCM) is presented. Case studies on the tool state estimation in the micro-milling of pure copper and steel demonstrate the effectiveness and potential of these methods.

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

The Effects of Visual Discriminability and Rotation Angle on 30-Month-Olds’ Search Performance in Spatial Rotation Tasks

PubMed Central

Ebersbach, Mirjam; Nawroth, Christian

2016-01-01

Tracking objects that are hidden and then moved is a crucial ability related to object permanence, which develops across several stages in early childhood. In spatial rotation tasks, children observe a target object that is hidden in one of two or more containers before the containers are rotated around a fixed axis. Usually, 30-month-olds fail to find the hidden object after it was rotated by 180°. We examined whether visual discriminability of the containers improves 30-month-olds’ success in this task and whether children perform better after 90° than after 180° rotations. Two potential hiding containers with same or different colors were placed on a board that was rotated by 90° or 180° in a within-subjects design. Children (N = 29) performed above chance level in all four conditions. Their overall success in finding the object did not improve by differently colored containers. However, different colors prevented children from showing an inhibition bias in 90° rotations, that is, choosing the empty container more often when it was located close to them than when it was farther away: This bias emerged in the same colors condition but not in the different colors condition. Results are discussed in view of particular challenges that might facilitate or deteriorate spatial rotation tasks for young children. PMID:27812346

The Effects of Visual Discriminability and Rotation Angle on 30-Month-Olds' Search Performance in Spatial Rotation Tasks.

PubMed

Ebersbach, Mirjam; Nawroth, Christian

2016-01-01

Tracking objects that are hidden and then moved is a crucial ability related to object permanence, which develops across several stages in early childhood. In spatial rotation tasks, children observe a target object that is hidden in one of two or more containers before the containers are rotated around a fixed axis. Usually, 30-month-olds fail to find the hidden object after it was rotated by 180°. We examined whether visual discriminability of the containers improves 30-month-olds' success in this task and whether children perform better after 90° than after 180° rotations. Two potential hiding containers with same or different colors were placed on a board that was rotated by 90° or 180° in a within-subjects design. Children ( N = 29) performed above chance level in all four conditions. Their overall success in finding the object did not improve by differently colored containers. However, different colors prevented children from showing an inhibition bias in 90° rotations, that is, choosing the empty container more often when it was located close to them than when it was farther away: This bias emerged in the same colors condition but not in the different colors condition. Results are discussed in view of particular challenges that might facilitate or deteriorate spatial rotation tasks for young children.

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

Nominal ISOMERs (Incorrect Spellings Of Medicines Eluding Researchers)—variants in the spellings of drug names in PubMed: a database review

PubMed Central

Aronson, Jeffrey K

2016-01-01

Objective To examine how misspellings of drug names could impede searches for published literature. Design Database review. Data source PubMed. Review methods The study included 30 drug names that are commonly misspelt on prescription charts in hospitals in Birmingham, UK (test set), and 30 control names randomly chosen from a hospital formulary (control set). The following definitions were used: standard names—the international non-proprietary names, variant names—deviations in spelling from standard names that are not themselves standard names in English language nomenclature, and hidden reference variants—variant spellings that identified publications in textword (tw) searches of PubMed or other databases, and which were not identified by textword searches for the standard names. Variant names were generated from standard names by applying letter substitutions, omissions, additions, transpositions, duplications, deduplications, and combinations of these. Searches were carried out in PubMed (30 June 2016) for “standard name[tw]” and “variant name[tw] NOT standard name[tw].” Results The 30 standard names of drugs in the test set gave 325 979 hits in total, and 160 hidden reference variants gave 3872 hits (1.17%). The standard names of the control set gave 470 064 hits, and 79 hidden reference variants gave 766 hits (0.16%). Letter substitutions (particularly i to y and vice versa) and omissions together accounted for 2924 (74%) of the variants. Amitriptyline (8530 hits) yielded 18 hidden reference variants (179 (2.1%) hits). Names ending in “in,” “ine,” or “micin” were commonly misspelt. Failing to search for hidden reference variants of “gentamicin,” “amitriptyline,” “mirtazapine,” and “trazodone” would miss at least 19 systematic reviews. A hidden reference variant related to Christmas, “No-el”, was rare; variants of “X-miss” were rarer. Conclusion When performing searches, researchers should include misspellings of drug names among their search terms. PMID:27974346

Nominal ISOMERs (Incorrect Spellings Of Medicines Eluding Researchers)-variants in the spellings of drug names in PubMed: a database review.

PubMed

Ferner, Robin E; Aronson, Jeffrey K

2016-12-14

 To examine how misspellings of drug names could impede searches for published literature.  Database review.  PubMed.  The study included 30 drug names that are commonly misspelt on prescription charts in hospitals in Birmingham, UK (test set), and 30 control names randomly chosen from a hospital formulary (control set). The following definitions were used: standard names-the international non-proprietary names, variant names-deviations in spelling from standard names that are not themselves standard names in English language nomenclature, and hidden reference variants-variant spellings that identified publications in textword (tw) searches of PubMed or other databases, and which were not identified by textword searches for the standard names. Variant names were generated from standard names by applying letter substitutions, omissions, additions, transpositions, duplications, deduplications, and combinations of these. Searches were carried out in PubMed (30 June 2016) for "standard name[tw]" and "variant name[tw] NOT standard name[tw]."  The 30 standard names of drugs in the test set gave 325 979 hits in total, and 160 hidden reference variants gave 3872 hits (1.17%). The standard names of the control set gave 470 064 hits, and 79 hidden reference variants gave 766 hits (0.16%). Letter substitutions (particularly i to y and vice versa) and omissions together accounted for 2924 (74%) of the variants. Amitriptyline (8530 hits) yielded 18 hidden reference variants (179 (2.1%) hits). Names ending in "in," "ine," or "micin" were commonly misspelt. Failing to search for hidden reference variants of "gentamicin," "amitriptyline," "mirtazapine," and "trazodone" would miss at least 19 systematic reviews. A hidden reference variant related to Christmas, "No-el", was rare; variants of "X-miss" were rarer.  When performing searches, researchers should include misspellings of drug names among their search terms. Published by the BMJ Publishing Group Limited. For permission to use (where not already granted under a licence) please go to http://group.bmj.com/group/rights-licensing/permissions.

Training health professionals to recruit into challenging randomized controlled trials improved confidence: the development of the QuinteT randomized controlled trial recruitment training intervention.

PubMed

Mills, Nicola; Gaunt, Daisy; Blazeby, Jane M; Elliott, Daisy; Husbands, Samantha; Holding, Peter; Rooshenas, Leila; Jepson, Marcus; Young, Bridget; Bower, Peter; Tudur Smith, Catrin; Gamble, Carrol; Donovan, Jenny L

2018-03-01

The objective of this study was to describe and evaluate a training intervention for recruiting patients to randomized controlled trials (RCTs), particularly for those anticipated to be difficult for recruitment. One of three training workshops was offered to surgeons and one to research nurses. Self-confidence in recruitment was measured through questionnaires before and up to 3 months after training; perceived impact of training on practice was assessed after. Data were analyzed using two-sample t-tests and supplemented with findings from the content analysis of free-text comments. Sixty-seven surgeons and 32 nurses attended. Self-confidence scores for all 10 questions increased after training [range of mean scores before 5.1-6.9 and after 6.9-8.2 (scale 0-10, all 95% confidence intervals are above 0 and all P-values <0.05)]. Awareness of hidden challenges of recruitment following training was high-surgeons' mean score 8.8 [standard deviation (SD), 1.2] and nurses' 8.4 (SD, 1.3) (scale 0-10); 50% (19/38) of surgeons and 40% (10/25) of nurses reported on a 4-point Likert scale that training had made "a lot" of difference to their RCT discussions. Analysis of free text revealed this was mostly in relation to how to convey equipoise, explain randomization, and manage treatment preferences. Surgeons and research nurses reported increased self-confidence in discussing RCTs with patients, a raised awareness of hidden challenges and a positive impact on recruitment practice following QuinteT RCT Recruitment Training. Training will be made more available and evaluated in relation to recruitment rates and informed consent. Copyright © 2017 The Authors. Published by Elsevier Inc. All rights reserved.

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

Inclusive Education for Children with Special Health Care Needs.

ERIC Educational Resources Information Center

Janz, Janice; And Others

This paper discusses issues concerning inclusion of children with special health care needs in the regular classroom. Six categories of health conditions are discussed in terms of their implications for the educational setting. These are: (1) "hidden" conditions (e.g., juvenile rheumatoid arthritis, sickle cell anemia, asthma, and cystic…

The full spectrum of climate change adaptation: testing an analytical framework in Tyrolean mountain agriculture (Austria).

PubMed

Grüneis, Heidelinde; Penker, Marianne; Höferl, Karl-Michael

2016-01-01

Our scientific view on climate change adaptation (CCA) is unsatisfying in many ways: It is often dominated by a modernistic perspective of planned pro-active adaptation, with a selective focus on measures directly responding to climate change impacts and thus it is far from real-life conditions of those who are actually affected by climate change. Farmers have to simultaneously adapt to multiple changes. Therefore, also empirical climate change adaptation research needs a more integrative perspective on real-life climate change adaptations. This also has to consider "hidden" adaptations, which are not explicitly and directly motivated by CCA but actually contribute to the sector's adaptability to climate change. The aim of the present study is to develop and test an analytic framework that contributes to a broader understanding of CCA and to bridge the gap between scientific expertise and practical action. The framework distinguishes three types of CCA according to their climate related motivations: explicit adaptations, multi-purpose adaptations, and hidden adaptations. Although agriculture is among the sectors that are most affected by climate change, results from the case study of Tyrolean mountain agriculture show that climate change is ranked behind other more pressing "real-life-challenges" such as changing agricultural policies or market conditions. We identified numerous hidden adaptations which make a valuable contribution when dealing with climate change impacts. We conclude that these hidden adaptations have not only to be considered to get an integrative und more realistic view on CCA; they also provide a great opportunity for linking adaptation strategies to farmers' realities.

Statistical Inference in Hidden Markov Models Using k-Segment Constraints

PubMed Central

Titsias, Michalis K.; Holmes, Christopher C.; Yau, Christopher

2016-01-01

Hidden Markov models (HMMs) are one of the most widely used statistical methods for analyzing sequence data. However, the reporting of output from HMMs has largely been restricted to the presentation of the most-probable (MAP) hidden state sequence, found via the Viterbi algorithm, or the sequence of most probable marginals using the forward–backward algorithm. In this article, we expand the amount of information we could obtain from the posterior distribution of an HMM by introducing linear-time dynamic programming recursions that, conditional on a user-specified constraint in the number of segments, allow us to (i) find MAP sequences, (ii) compute posterior probabilities, and (iii) simulate sample paths. We collectively call these recursions k-segment algorithms and illustrate their utility using simulated and real examples. We also highlight the prospective and retrospective use of k-segment constraints for fitting HMMs or exploring existing model fits. Supplementary materials for this article are available online. PMID:27226674

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

The way to uncover community structure with core and diversity

NASA Astrophysics Data System (ADS)

Chang, Y. F.; Han, S. K.; Wang, X. D.

2018-07-01

Communities are ubiquitous in nature and society. Individuals that share common properties often self-organize to form communities. Avoiding the shortages of computation complexity, pre-given information and unstable results in different run, in this paper, we propose a simple and efficient method to deepen our understanding of the emergence and diversity of communities in complex systems. By introducing the rational random selection, our method reveals the hidden deterministic and normal diverse community states of community structure. To demonstrate this method, we test it with real-world systems. The results show that our method could not only detect community structure with high sensitivity and reliability, but also provide instructional information about the hidden deterministic community world and the real normal diverse community world by giving out the core-community, the real-community, the tide and the diversity. Thizs is of paramount importance in understanding, predicting, and controlling a variety of collective behaviors in complex systems.

A Novel Extreme Learning Control Framework of Unmanned Surface Vehicles.

PubMed

Wang, Ning; Sun, Jing-Chao; Er, Meng Joo; Liu, Yan-Cheng

2016-05-01

In this paper, an extreme learning control (ELC) framework using the single-hidden-layer feedforward network (SLFN) with random hidden nodes for tracking an unmanned surface vehicle suffering from unknown dynamics and external disturbances is proposed. By combining tracking errors with derivatives, an error surface and transformed states are defined to encapsulate unknown dynamics and disturbances into a lumped vector field of transformed states. The lumped nonlinearity is further identified accurately by an extreme-learning-machine-based SLFN approximator which does not require a priori system knowledge nor tuning input weights. Only output weights of the SLFN need to be updated by adaptive projection-based laws derived from the Lyapunov approach. Moreover, an error compensator is incorporated to suppress approximation residuals, and thereby contributing to the robustness and global asymptotic stability of the closed-loop ELC system. Simulation studies and comprehensive comparisons demonstrate that the ELC framework achieves high accuracy in both tracking and approximation.

Statistical patterns of visual search for hidden objects

PubMed Central

Credidio, Heitor F.; Teixeira, Elisângela N.; Reis, Saulo D. S.; Moreira, André A.; Andrade Jr, José S.

2012-01-01

The movement of the eyes has been the subject of intensive research as a way to elucidate inner mechanisms of cognitive processes. A cognitive task that is rather frequent in our daily life is the visual search for hidden objects. Here we investigate through eye-tracking experiments the statistical properties associated with the search of target images embedded in a landscape of distractors. Specifically, our results show that the twofold process of eye movement, composed of sequences of fixations (small steps) intercalated by saccades (longer jumps), displays characteristic statistical signatures. While the saccadic jumps follow a log-normal distribution of distances, which is typical of multiplicative processes, the lengths of the smaller steps in the fixation trajectories are consistent with a power-law distribution. Moreover, the present analysis reveals a clear transition between a directional serial search to an isotropic random movement as the difficulty level of the searching task is increased. PMID:23226829

Exact solution of the hidden Markov processes.

PubMed

Saakian, David B

2017-11-01

We write a master equation for the distributions related to hidden Markov processes (HMPs) and solve it using a functional equation. Thus the solution of HMPs is mapped exactly to the solution of the functional equation. For a general case the latter can be solved only numerically. We derive an exact expression for the entropy of HMPs. Our expression for the entropy is an alternative to the ones given before by the solution of integral equations. The exact solution is possible because actually the model can be considered as a generalized random walk on a one-dimensional strip. While we give the solution for the two second-order matrices, our solution can be easily generalized for the L values of the Markov process and M values of observables: We should be able to solve a system of L functional equations in the space of dimension M-1.

Exact solution of the hidden Markov processes

NASA Astrophysics Data System (ADS)

Saakian, David B.

2017-11-01

We write a master equation for the distributions related to hidden Markov processes (HMPs) and solve it using a functional equation. Thus the solution of HMPs is mapped exactly to the solution of the functional equation. For a general case the latter can be solved only numerically. We derive an exact expression for the entropy of HMPs. Our expression for the entropy is an alternative to the ones given before by the solution of integral equations. The exact solution is possible because actually the model can be considered as a generalized random walk on a one-dimensional strip. While we give the solution for the two second-order matrices, our solution can be easily generalized for the L values of the Markov process and M values of observables: We should be able to solve a system of L functional equations in the space of dimension M -1 .

Total Quality Management: A Guide to Implementation

DTIC Science & Technology

1989-08-01

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

Locating Encrypted Data Hidden Among Non-Encrypted Data Using Statistical Tools

DTIC Science & Technology

2007-03-01

length of a compressed sequence). If a bit sequence can be significantly compressed , then it is not random. Lempel - Ziv Compression Test This test...communication, targeting, and a host other of tasks. This software will most assuredly contain classified data or algorithms requiring protection in...containing the classified data and algorithms . As the program is executed the solider would have access to the common unclassified tasks, however, to

Measuring the volume of brain tumour and determining its location in T2-weighted MRI images using hidden Markov random field: expectation maximization algorithm

NASA Astrophysics Data System (ADS)

Mat Jafri, Mohd. Zubir; Abdulbaqi, Hayder Saad; Mutter, Kussay N.; Mustapha, Iskandar Shahrim; Omar, Ahmad Fairuz

2017-06-01

A brain tumour is an abnormal growth of tissue in the brain. Most tumour volume measurement processes are carried out manually by the radiographer and radiologist without relying on any auto program. This manual method is a timeconsuming task and may give inaccurate results. Treatment, diagnosis, signs and symptoms of the brain tumours mainly depend on the tumour volume and its location. In this paper, an approach is proposed to improve volume measurement of brain tumors as well as using a new method to determine the brain tumour location. The current study presents a hybrid method that includes two methods. One method is hidden Markov random field - expectation maximization (HMRFEM), which employs a positive initial classification of the image. The other method employs the threshold, which enables the final segmentation. In this method, the tumour volume is calculated using voxel dimension measurements. The brain tumour location was determined accurately in T2- weighted MRI image using a new algorithm. According to the results, this process was proven to be more useful compared to the manual method. Thus, it provides the possibility of calculating the volume and determining location of a brain tumour.

Virtual screening by a new Clustering-based Weighted Similarity Extreme Learning Machine approach

PubMed Central

Kudisthalert, Wasu

2018-01-01

Machine learning techniques are becoming popular in virtual screening tasks. One of the powerful machine learning algorithms is Extreme Learning Machine (ELM) which has been applied to many applications and has recently been applied to virtual screening. We propose the Weighted Similarity ELM (WS-ELM) which is based on a single layer feed-forward neural network in a conjunction of 16 different similarity coefficients as activation function in the hidden layer. It is known that the performance of conventional ELM is not robust due to random weight selection in the hidden layer. Thus, we propose a Clustering-based WS-ELM (CWS-ELM) that deterministically assigns weights by utilising clustering algorithms i.e. k-means clustering and support vector clustering. The experiments were conducted on one of the most challenging datasets–Maximum Unbiased Validation Dataset–which contains 17 activity classes carefully selected from PubChem. The proposed algorithms were then compared with other machine learning techniques such as support vector machine, random forest, and similarity searching. The results show that CWS-ELM in conjunction with support vector clustering yields the best performance when utilised together with Sokal/Sneath(1) coefficient. Furthermore, ECFP_6 fingerprint presents the best results in our framework compared to the other types of fingerprints, namely ECFP_4, FCFP_4, and FCFP_6. PMID:29652912

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.

Colonoscopy video quality assessment using hidden Markov random fields

NASA Astrophysics Data System (ADS)

Park, Sun Young; Sargent, Dusty; Spofford, Inbar; Vosburgh, Kirby

2011-03-01

With colonoscopy becoming a common procedure for individuals aged 50 or more who are at risk of developing colorectal cancer (CRC), colon video data is being accumulated at an ever increasing rate. However, the clinically valuable information contained in these videos is not being maximally exploited to improve patient care and accelerate the development of new screening methods. One of the well-known difficulties in colonoscopy video analysis is the abundance of frames with no diagnostic information. Approximately 40% - 50% of the frames in a colonoscopy video are contaminated by noise, acquisition errors, glare, blur, and uneven illumination. Therefore, filtering out low quality frames containing no diagnostic information can significantly improve the efficiency of colonoscopy video analysis. To address this challenge, we present a quality assessment algorithm to detect and remove low quality, uninformative frames. The goal of our algorithm is to discard low quality frames while retaining all diagnostically relevant information. Our algorithm is based on a hidden Markov model (HMM) in combination with two measures of data quality to filter out uninformative frames. Furthermore, we present a two-level framework based on an embedded hidden Markov model (EHHM) to incorporate the proposed quality assessment algorithm into a complete, automated diagnostic image analysis system for colonoscopy video.

Weakly supervised visual dictionary learning by harnessing image attributes.

PubMed

Gao, Yue; Ji, Rongrong; Liu, Wei; Dai, Qionghai; Hua, Gang

2014-12-01

Bag-of-features (BoFs) representation has been extensively applied to deal with various computer vision applications. To extract discriminative and descriptive BoF, one important step is to learn a good dictionary to minimize the quantization loss between local features and codewords. While most existing visual dictionary learning approaches are engaged with unsupervised feature quantization, the latest trend has turned to supervised learning by harnessing the semantic labels of images or regions. However, such labels are typically too expensive to acquire, which restricts the scalability of supervised dictionary learning approaches. In this paper, we propose to leverage image attributes to weakly supervise the dictionary learning procedure without requiring any actual labels. As a key contribution, our approach establishes a generative hidden Markov random field (HMRF), which models the quantized codewords as the observed states and the image attributes as the hidden states, respectively. Dictionary learning is then performed by supervised grouping the observed states, where the supervised information is stemmed from the hidden states of the HMRF. In such a way, the proposed dictionary learning approach incorporates the image attributes to learn a semantic-preserving BoF representation without any genuine supervision. Experiments in large-scale image retrieval and classification tasks corroborate that our approach significantly outperforms the state-of-the-art unsupervised dictionary learning approaches.

Incorporating teleconnection information into reservoir operating policies using Stochastic Dynamic Programming and a Hidden Markov Model

NASA Astrophysics Data System (ADS)

Turner, Sean; Galelli, Stefano; Wilcox, Karen

2015-04-01

Water reservoir systems are often affected by recurring large-scale ocean-atmospheric anomalies, known as teleconnections, that cause prolonged periods of climatological drought. Accurate forecasts of these events -- at lead times in the order of weeks and months -- may enable reservoir operators to take more effective release decisions to improve the performance of their systems. In practice this might mean a more reliable water supply system, a more profitable hydropower plant or a more sustainable environmental release policy. To this end, climate indices, which represent the oscillation of the ocean-atmospheric system, might be gainfully employed within reservoir operating models that adapt the reservoir operation as a function of the climate condition. This study develops a Stochastic Dynamic Programming (SDP) approach that can incorporate climate indices using a Hidden Markov Model. The model simulates the climatic regime as a hidden state following a Markov chain, with the state transitions driven by variation in climatic indices, such as the Southern Oscillation Index. Time series analysis of recorded streamflow data reveals the parameters of separate autoregressive models that describe the inflow to the reservoir under three representative climate states ("normal", "wet", "dry"). These models then define inflow transition probabilities for use in a classic SDP approach. The key advantage of the Hidden Markov Model is that it allows conditioning the operating policy not only on the reservoir storage and the antecedent inflow, but also on the climate condition, thus potentially allowing adaptability to a broader range of climate conditions. In practice, the reservoir operator would effect a water release tailored to a specific climate state based on available teleconnection data and forecasts. The approach is demonstrated on the operation of a realistic, stylised water reservoir with carry-over capacity in South-East Australia. Here teleconnections relating to both the El Niño Southern Oscillation and the Indian Ocean Dipole influence local hydro-meteorological processes; statistically significant lag correlations have already been established. Simulation of the derived operating policies, which are benchmarked against standard policies conditioned on the reservoir storage and the antecedent inflow, demonstrates the potential of the proposed approach. Future research will further develop the model for sensitivity analysis and regional studies examining the economic value of incorporating long range forecasts into reservoir operation.

For What Conditions Are Assistive Devices Used?

MedlinePlus

... walking or other movement, inability to use a computer mouse, slow response time, limited fine or gross ... people with hidden disabilities can benefit from assistive technologies for certain activities or during certain stages of ...

The Effects of Explanatory Conversations on Children's Emotion Understanding

ERIC Educational Resources Information Center

Tenenbaum, Harriet R.; Alfieri, Louis; Brooks, Patricia J.; Dunne, Guler

2008-01-01

Ninety-three children ranging in age from 5 to 8 years (M = 82.46 months, SD = 13.20) participated in a training study designed to improve their emotion understanding. Children either explained (self-explanation condition) or listened to an experimenter who explained (experimenter-explanation condition) the causes of protagonists' hidden and…

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

PubMed

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

2015-01-01

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

Consequences of recent loophole-free experiments on a relaxation of measurement independence

NASA Astrophysics Data System (ADS)

Hnilo, Alejandro A.

2017-02-01

Recent experiments using innovative optical detectors and techniques have strongly increased the capacity of testing the violation of the Bell's inequalities in Nature. Most of them have used the Eberhard's inequality (EI) to close the "detection" loophole. Closing the "locality" loophole has been attempted by spacelike separated detections and fast changes of the bases of observation, driven by random number generators of new design. Also, pulsed pumping and time-resolved data recording to close the "time-coincidence" loophole, and sophisticated statistical methods to close the "memory" loophole, have been used. In this paper, the meaning of the EI is reviewed. A simple hidden variables theory based on a relaxation of the condition of "measurement independence," which was devised long ago for the Clauser-Horne-Shimony and Holt inequality, is adapted to the EI case. It is used here to evaluate the significance of the results of the recent experiments, which are briefly described. A table summarizes the main results.

Keyring models: An approach to steerability

NASA Astrophysics Data System (ADS)

Miller, Carl A.; Colbeck, Roger; Shi, Yaoyun

2018-02-01

If a measurement is made on one half of a bipartite system, then, conditioned on the outcome, the other half has a new reduced state. If these reduced states defy classical explanation—that is, if shared randomness cannot produce these reduced states for all possible measurements—the bipartite state is said to be steerable. Determining which states are steerable is a challenging problem even for low dimensions. In the case of two-qubit systems, a criterion is known for T-states (that is, those with maximally mixed marginals) under projective measurements. In the current work, we introduce the concept of keyring models—a special class of local hidden state models. When the measurements made correspond to real projectors, these allow us to study steerability beyond T-states. Using keyring models, we completely solve the steering problem for real projective measurements when the state arises from mixing a pure two-qubit state with uniform noise. We also give a partial solution in the case when the uniform noise is replaced by independent depolarizing channels.

Haptic over visual information in the distribution of visual attention after tool-use in near and far space.

PubMed

Park, George D; Reed, Catherine L

2015-10-01

Despite attentional prioritization for grasping space near the hands, tool-use appears to transfer attentional bias to the tool's end/functional part. The contributions of haptic and visual inputs to attentional distribution along a tool were investigated as a function of tool-use in near (Experiment 1) and far (Experiment 2) space. Visual attention was assessed with a 50/50, go/no-go, target discrimination task, while a tool was held next to targets appearing near the tool-occupied hand or tool-end. Target response times (RTs) and sensitivity (d-prime) were measured at target locations, before and after functional tool practice for three conditions: (1) open-tool: tool-end visible (visual + haptic inputs), (2) hidden-tool: tool-end visually obscured (haptic input only), and (3) short-tool: stick missing tool's length/end (control condition: hand occupied but no visual/haptic input). In near space, both open- and hidden-tool groups showed a tool-end, attentional bias (faster RTs toward tool-end) before practice; after practice, RTs near the hand improved. In far space, the open-tool group showed no bias before practice; after practice, target RTs near the tool-end improved. However, the hidden-tool group showed a consistent tool-end bias despite practice. Lack of short-tool group results suggested that hidden-tool group results were specific to haptic inputs. In conclusion, (1) allocation of visual attention along a tool due to tool practice differs in near and far space, and (2) visual attention is drawn toward the tool's end even when visually obscured, suggesting haptic input provides sufficient information for directing attention along the tool.

Detection of Objects Hidden in Highly Scattering Media Using Time-Gated Imaging Methods

NASA Technical Reports Server (NTRS)

Galland, Pierre A.; Wang, L.; Liang, X.; Ho, P. P.; Alfano, R. R.

2000-01-01

Non-intrusive and non-invasive optical imaging techniques has generated great interest among researchers for their potential applications to biological study, device characterization, surface defect detection, and jet fuel dynamics. Non-linear optical parametric amplification gate (NLOPG) has been used to detect back-scattered images of objects hidden in diluted Intralipid solutions. To directly detect objects hidden in highly scattering media, the diffusive component of light needs to be sorted out from early arrived ballistic and snake photons. In an optical imaging system, images are collected in transmission or back-scattered geometry. The early arrival photons in the transmission approach, always carry the direct information of the hidden object embedded in the turbid medium. In the back-scattered approach, the result is not so forth coming. In the presence of a scattering host, the first arrival photons in back-scattered approach will be directly photons from the host material. In the presentation, NLOPG was applied to acquire time resolved back-scattered images under the phase matching condition. A time-gated amplified signal was obtained through this NLOPG process. The system's gain was approximately 100 times. The time-gate was achieved through phase matching condition where only coherent photons retain their phase. As a result, the diffusive photons, which were the primary contributor to the background, were removed. With a large dynamic range and high resolution, time-gated early light imaging has the potential for improving rocket/aircraft design by determining jets shape and particle sizes. Refinements to these techniques may enable drop size measurements in the highly scattering, optically dense region of multi-element rocket injectors. These types of measurements should greatly enhance the design of stable, and higher performing rocket engines.

A Multidisciplinary Approach to Health Monitoring and Materials Damage Prognosis for Metallic Aerospace Systems

DTIC Science & Technology

2013-03-01

framework of orientation distribution functions and crack-induced texture o Quantify effects of temperature on damage behavior and damage monitoring...measurement model was obtained from hidden Markov modeling (HMM) of joint time-frequency (TF) features extracted from the PZT sensor signals using the...considered PZT sensor signals recorded from a bolted aluminum plate. About only 20% of the samples of a signal were first randomly selected as

Effects of demanding foraging conditions on cache retrival accuracy in food-caching mountain chickadees (Poecile gambeli).

PubMed

Pravosudov, V V; Clayton, N S

2001-02-22

Birds rely, at least in part, on spatial memory for recovering previously hidden caches but accurate cache recovery may be more critical for birds that forage in harsh conditions where the food supply is limited and unpredictable. Failure to find caches in these conditions may potentially result in death from starvation. In order to test this hypothesis we compared the cache recovery behaviour of 24 wild-caught mountain chickadees (Poecile gambeli), half of which were maintained on a limited and unpredictable food supply while the rest were maintained on an ad libitum food supply for 60 days. We then tested their cache retrieval accuracy by allowing birds from both groups to cache seeds in the experimental room and recover them 5 hours later. Our results showed that birds maintained on a limited and unpredictable food supply made significantly fewer visits to non-cache sites when recovering their caches compared to birds maintained on ad libitum food. We found the same difference in performance in two versions of a one-trial associative learning task in which the birds had to rely on memory to find previously encountered hidden food. In a non-spatial memory version of the task, in which the baited feeder was clearly marked, there were no significant differences between the two groups. We therefore concluded that the two groups differed in their efficiency at cache retrieval. We suggest that this difference is more likely to be attributable to a difference in memory (encoding or recall) than to a difference in their motivation to search for hidden food, although the possibility of some motivational differences still exists. Overall, our results suggest that demanding foraging conditions favour more accurate cache retrieval in food-caching birds.

Temporal stability of visual search-driven biometrics

NASA Astrophysics Data System (ADS)

Yoon, Hong-Jun; Carmichael, Tandy R.; Tourassi, Georgia

2015-03-01

Previously, we have shown the potential of using an individual's visual search pattern as a possible biometric. That study focused on viewing images displaying dot-patterns with different spatial relationships to determine which pattern can be more effective in establishing the identity of an individual. In this follow-up study we investigated the temporal stability of this biometric. We performed an experiment with 16 individuals asked to search for a predetermined feature of a random-dot pattern as we tracked their eye movements. Each participant completed four testing sessions consisting of two dot patterns repeated twice. One dot pattern displayed concentric circles shifted to the left or right side of the screen overlaid with visual noise, and participants were asked which side the circles were centered on. The second dot-pattern displayed a number of circles (between 0 and 4) scattered on the screen overlaid with visual noise, and participants were asked how many circles they could identify. Each session contained 5 untracked tutorial questions and 50 tracked test questions (200 total tracked questions per participant). To create each participant's "fingerprint", we constructed a Hidden Markov Model (HMM) from the gaze data representing the underlying visual search and cognitive process. The accuracy of the derived HMM models was evaluated using cross-validation for various time-dependent train-test conditions. Subject identification accuracy ranged from 17.6% to 41.8% for all conditions, which is significantly higher than random guessing (1/16 = 6.25%). The results suggest that visual search pattern is a promising, temporally stable personalized fingerprint of perceptual organization.

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

Yoon, Hong-Jun; Carmichael, Tandy; Tourassi, Georgia

Previously, we have shown the potential of using an individual s visual search pattern as a possible biometric. That study focused on viewing images displaying dot-patterns with different spatial relationships to determine which pattern can be more effective in establishing the identity of an individual. In this follow-up study we investigated the temporal stability of this biometric. We performed an experiment with 16 individuals asked to search for a predetermined feature of a random-dot pattern as we tracked their eye movements. Each participant completed four testing sessions consisting of two dot patterns repeated twice. One dot pattern displayed concentric circlesmore » shifted to the left or right side of the screen overlaid with visual noise, and participants were asked which side the circles were centered on. The second dot-pattern displayed a number of circles (between 0 and 4) scattered on the screen overlaid with visual noise, and participants were asked how many circles they could identify. Each session contained 5 untracked tutorial questions and 50 tracked test questions (200 total tracked questions per participant). To create each participant s "fingerprint", we constructed a Hidden Markov Model (HMM) from the gaze data representing the underlying visual search and cognitive process. The accuracy of the derived HMM models was evaluated using cross-validation for various time-dependent train-test conditions. Subject identification accuracy ranged from 17.6% to 41.8% for all conditions, which is significantly higher than random guessing (1/16 = 6.25%). The results suggest that visual search pattern is a promising, fairly stable personalized fingerprint of perceptual organization.« less

Use of a Parabolic Microphone to Detect Hidden Subjects in Search and Rescue.

PubMed

Bowditch, Nathaniel L; Searing, Stanley K; Thomas, Jeffrey A; Thompson, Peggy K; Tubis, Jacqueline N; Bowditch, Sylvia P

2018-03-01

This study compares a parabolic microphone to unaided hearing in detecting and comprehending hidden callers at ranges of 322 to 2510 m. Eight subjects were placed 322 to 2510 m away from a central listening point. The subjects were concealed, and their calling volume was calibrated. In random order, subjects were asked to call the name of a state for 5 minutes. Listeners with parabolic microphones and others with unaided hearing recorded the direction of the call (detection) and name of the state (comprehension). The parabolic microphone was superior to unaided hearing in both detecting subjects and comprehending their calls, with an effect size (Cohen's d) of 1.58 for detection and 1.55 for comprehension. For each of the 8 hidden subjects, there were 24 detection attempts with the parabolic microphone and 54 to 60 attempts by unaided listeners. At the longer distances (1529-2510 m), the parabolic microphone was better at detecting callers (83% vs 51%; P<0.00001 by χ 2 ) and comprehension (57% vs 12%; P<0.00001). At the shorter distances (322-1190 m), the parabolic microphone offered advantages in detection (100% vs 83%; P=0.000023) and comprehension (86% vs 51%; P<0.00001), although not as pronounced as at the longer distances. Use of a 66-cm (26-inch) parabolic microphone significantly improved detection and comprehension of hidden calling subjects at distances between 322 and 2510 m when compared with unaided hearing. This study supports the use of a parabolic microphone in search and rescue to locate responsive subjects in favorable weather and terrain. Copyright © 2017 The Authors. Published by Elsevier Inc. All rights reserved.

Hidden acoustic information revealed by intentional nonlinearity

NASA Astrophysics Data System (ADS)

Dowling, David R.

2017-11-01

Acoustic waves are omnipresent in modern life and are well described by the linearized equations of fluid dynamics. Once generated, acoustic waves carry and collect information about their source and the environment through which they propagate, respectively, and this information may be retrieved by analyzing recordings of these waves. Because of this, acoustics is the primary means for observation, surveillance, reconnaissance, and remote sensing in otherwise opaque environments, such as the Earth's oceans and crust, and the interior of the human body. For such information-retrieval tasks, acoustic fields are nearly always interrogated within their recorded frequency range or bandwidth. However, this frequency-range restriction is not general; acoustic fields may also carry (hidden) information at frequencies outside their bandwidth. Although such a claim may seem counter intuitive, hidden acoustic-field information can be revealed by re-introducing a marquee trait of fluid dynamics: nonlinearity. In particular, an intentional quadratic nonlinearity - a form of intra-signal heterodyning - can be used to obtain acoustic field information at frequencies outside a recorded acoustic field's bandwidth. This quadratic nonlinearity enables a variety of acoustic remote sensing applications that were long thought to be impossible. In particular, it allows the detrimental effects of sparse recordings and random scattering to be suppressed when the original acoustic field has sufficient bandwidth. In this presentation, the topic is developed heuristically, with a just brief exposition of the relevant mathematics. Hidden acoustic field information is then revealed from simulated and measured acoustic fields in simple and complicated acoustic environments involving frequencies from a few Hertz to more than 100 kHz, and propagation distances from tens of centimeters to hundreds of kilometers. Sponsored by ONR, NAVSEA, and NSF.

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.

A preliminary study of sex differences in brain activation during a spatial navigation task in healthy adults.

PubMed

Sneider, Jennifer Tropp; Sava, Simona; Rogowska, Jadwiga; Yurgelun-Todd, Deborah A

2011-10-01

The hippocampus plays a significant role in spatial memory processing, with sex differences being prominent on various spatial tasks. This study examined sex differences in healthy adults, using functional magnetic resonance imaging (fMRI) in areas implicated in spatial processing during navigation of a virtual analogue of the Morris water-maze. There were three conditions: learning, hidden, and visible control. There were no significant differences in performance measures. However, sex differences were found in regional brain activation during learning in the right hippocampus, right parahippocampal gyrus, and the cingulate cortex. During the hidden condition, the hippocampus, parahippocampal gyrus, and cingulate cortex were activated in both men and women. Additional brain areas involved in spatial processing may be recruited in women when learning information about the environment, by utilizing external cues (landmarks) more than do men, contributing to the observed sex differences in brain activation.

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.

Holographic quantitative imaging of sample hidden by turbid medium or occluding objects

NASA Astrophysics Data System (ADS)

Bianco, V.; Miccio, L.; Merola, F.; Memmolo, P.; Gennari, O.; Paturzo, Melania; Netti, P. A.; Ferraro, P.

2015-03-01

Digital Holography (DH) numerical procedures have been developed to allow imaging through turbid media. A fluid is considered turbid when dispersed particles provoke strong light scattering, thus destroying the image formation by any standard optical system. Here we show that sharp amplitude imaging and phase-contrast mapping of object hidden behind turbid medium and/or occluding objects are possible in harsh noise conditions and with a large field-of view by Multi-Look DH microscopy. In particular, it will be shown that both amplitude imaging and phase-contrast mapping of cells hidden behind a flow of Red Blood Cells can be obtained. This allows, in a noninvasive way, the quantitative evaluation of living processes in Lab on Chip platforms where conventional microscopy techniques fail. The combination of this technique with endoscopic imaging can pave the way for the holographic blood vessel inspection, e.g. to look for settled cholesterol plaques as well as blood clots for a rapid diagnostics of blood diseases.

New high resolution measurements of open and hidden charm production in proton-nucleus collisions at √{ s} = 110GeV with LHCb

NASA Astrophysics Data System (ADS)

Maurice, Émilie; LHCb Collaboration

2017-11-01

Open and hidden charm production in nucleus-nucleus collisions is considered as a key probe of Quark Gluon Plasma (QGP) formation. In the search of specific QGP effects, proton-nucleus collisions are used as the reference as they account for the corresponding Cold Nuclear Matter (CNM) effects. The LHCb experiment, thanks to its System for Measuring Overlap with Gas (SMOG) can be operated in a fixed target mode with the LHC beams, at an intermediate center-of-mass energy between nominal SPS and RHIC energies. In 2015, for the first time, reactions of incident LHC proton beams on noble gas targets have been recorded by the LHCb experiment at a center-of-mass energy of 110 GeV and within the center-of-mass rapidity range - 2.77

Phasic Triplet Markov Chains.

PubMed

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

2014-11-01

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

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

PubMed Central

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

2016-01-01

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

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.

Hidden Nickel Deficiency? Nickel Fertilization via Soil Improves Nitrogen Metabolism and Grain Yield in Soybean Genotypes.

PubMed

Siqueira Freitas, Douglas; Wurr Rodak, Bruna; Rodrigues Dos Reis, André; de Barros Reis, Fabio; Soares de Carvalho, Teotonio; Schulze, Joachim; Carbone Carneiro, Marco A; Guimarães Guilherme, Luiz R

2018-01-01

Nickel (Ni)-a component of urease and hydrogenase-was the latest nutrient to be recognized as an essential element for plants. However, to date there are no records of Ni deficiency for annual species cultivated under field conditions, possibly because of the non-appearance of obvious and distinctive symptoms, i.e., a hidden (or latent) deficiency. Soybean, a crop cultivated on soils poor in extractable Ni, has a high dependence on biological nitrogen fixation (BNF), in which Ni plays a key role. Thus, we hypothesized that Ni fertilization in soybean genotypes results in a better nitrogen physiological function and in higher grain production due to the hidden deficiency of this micronutrient. To verify this hypothesis, two simultaneous experiments were carried out, under greenhouse and field conditions, with Ni supply of 0.0 or 0.5 mg of Ni kg -1 of soil. For this, we used 15 soybean genotypes and two soybean isogenic lines (urease positive, Eu3 ; urease activity-null, eu3-a , formerly eu3-e1 ). Plants were evaluated for yield, Ni and N concentration, photosynthesis, and N metabolism. Nickel fertilization resulted in greater grain yield in some genotypes, indicating the hidden deficiency of Ni in both conditions. Yield gains of up to 2.9 g per plant in greenhouse and up to 1,502 kg ha -1 in field conditions were associated with a promoted N metabolism, namely, leaf N concentration, ammonia, ureides, urea, and urease activity, which separated the genotypes into groups of Ni responsiveness. Nickel supply also positively affected photosynthesis in the genotypes, never causing detrimental effects, except for the eu3-a mutant, which due to the absence of ureolytic activity accumulated excess urea in leaves and had reduced yield. In summary, the effect of Ni on the plants was positive and the extent of this effect was controlled by genotype-environment interaction. The application of 0.5 mg kg -1 of Ni resulted in safe levels of this element in grains for human health consumption. Including Ni applications in fertilization programs may provide significant yield benefits in soybean production on low Ni soil. This might also be the case for other annual crops, especially legumes.

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

PubMed Central

Liu, Yongxiang; Huo, Kai; Zhang, Zhongshuai

2018-01-01

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

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

PubMed

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

2018-01-10

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

Bearings fault detection in helicopters using frequency readjustment and cyclostationary analysis

NASA Astrophysics Data System (ADS)

Girondin, Victor; Pekpe, Komi Midzodzi; Morel, Herve; Cassar, Jean-Philippe

2013-07-01

The objective of this paper is to propose a vibration-based automated framework dealing with local faults occurring on bearings in the transmission of a helicopter. The knowledge of the shaft speed and kinematic computation provide theoretical frequencies that reveal deteriorations on the inner and outer races, on the rolling elements or on the cage. In practice, the theoretical frequencies of bearing faults may be shifted. They may also be masked by parasitical frequencies because the numerous noisy vibrations and the complexity of the transmission mechanics make the signal spectrum very profuse. Consequently, detection methods based on the monitoring of the theoretical frequencies may lead to wrong decisions. In order to deal with this drawback, we propose to readjust the fault frequencies from the theoretical frequencies using the redundancy introduced by the harmonics. The proposed method provides the confidence index of the readjusted frequency. Minor variations in shaft speed may induce random jitters. The change of the contact surface or of the transmission path brings also a random component in amplitude and phase. These random components in the signal destroy spectral localization of frequencies and thus hide the fault occurrence in the spectrum. Under the hypothesis that these random signals can be modeled as cyclostationary signals, the envelope spectrum can reveal that hidden patterns. In order to provide an indicator estimating fault severity, statistics are proposed. They make the hypothesis that the harmonics at the readjusted frequency are corrupted with an additive normally distributed noise. In this case, the statistics computed from the spectra are chi-square distributed and a signal-to-noise indicator is proposed. The algorithms are then tested with data from two test benches and from flight conditions. The bearing type and the radial load are the main differences between the experiences on the benches. The fault is mainly visible in the spectrum for the radially constrained bearing and only visible in the envelope spectrum for the "load-free" bearing. Concerning results in flight conditions, frequency readjustment demonstrates good performances when applied on the spectrum, showing that a fully automated bearing decision procedure is applicable for operational helicopter monitoring.

Funding Building Projects in a Tough Economy: Hidden Money Will Help You Construct and Maintain Your Buildings

ERIC Educational Resources Information Center

Love, Paula

2012-01-01

The federal government last formally assessed the state of the nation's schools in the 1999 report "Condition of America's Public School," which estimated that it would take $127 billion to bring the nation's schools to "good condition." The American Society of Civil Engineers (ASCE) issued its own report card the same year. In…

Security of BB84 with weak randomness and imperfect qubit encoding

NASA Astrophysics Data System (ADS)

Zhao, Liang-Yuan; Yin, Zhen-Qiang; Li, Hong-Wei; Chen, Wei; Fang, Xi; Han, Zheng-Fu; Huang, Wei

2018-03-01

The main threats for the well-known Bennett-Brassard 1984 (BB84) practical quantum key distribution (QKD) systems are that its encoding is inaccurate and measurement device may be vulnerable to particular attacks. Thus, a general physical model or security proof to tackle these loopholes simultaneously and quantitatively is highly desired. Here we give a framework on the security of BB84 when imperfect qubit encoding and vulnerability of measurement device are both considered. In our analysis, the potential attacks to measurement device are generalized by the recently proposed weak randomness model which assumes the input random numbers are partially biased depending on a hidden variable planted by an eavesdropper. And the inevitable encoding inaccuracy is also introduced here. From a fundamental view, our work reveals the potential information leakage due to encoding inaccuracy and weak randomness input. For applications, our result can be viewed as a useful tool to quantitatively evaluate the security of a practical QKD system.

One-step estimation of networked population size: Respondent-driven capture-recapture with anonymity.

PubMed

Khan, Bilal; Lee, Hsuan-Wei; Fellows, Ian; Dombrowski, Kirk

2018-01-01

Size estimation is particularly important for populations whose members experience disproportionate health issues or pose elevated health risks to the ambient social structures in which they are embedded. Efforts to derive size estimates are often frustrated when the population is hidden or hard-to-reach in ways that preclude conventional survey strategies, as is the case when social stigma is associated with group membership or when group members are involved in illegal activities. This paper extends prior research on the problem of network population size estimation, building on established survey/sampling methodologies commonly used with hard-to-reach groups. Three novel one-step, network-based population size estimators are presented, for use in the context of uniform random sampling, respondent-driven sampling, and when networks exhibit significant clustering effects. We give provably sufficient conditions for the consistency of these estimators in large configuration networks. Simulation experiments across a wide range of synthetic network topologies validate the performance of the estimators, which also perform well on a real-world location-based social networking data set with significant clustering. Finally, the proposed schemes are extended to allow them to be used in settings where participant anonymity is required. Systematic experiments show favorable tradeoffs between anonymity guarantees and estimator performance. Taken together, we demonstrate that reasonable population size estimates are derived from anonymous respondent driven samples of 250-750 individuals, within ambient populations of 5,000-40,000. The method thus represents a novel and cost-effective means for health planners and those agencies concerned with health and disease surveillance to estimate the size of hidden populations. We discuss limitations and future work in the concluding section.

Feasibility study of hidden flow imaging based on laser speckle technique using multiperspectives contrast images

NASA Astrophysics Data System (ADS)

Abookasis, David; Moshe, Tomer

2014-11-01

This paper demonstrates the insertion of lens array in the front of a CCD camera in a laser speckle imaging (LSI) like-technique to acquire multiple speckle reflectance projections for imaging blood flow in an intact biological tissue. In some of LSI applications, flow imaging is obtained by thinning or removing of the upper tissue layers to access blood vessels. In contrast, with the proposed approach flow imaging can be achieved while the tissue is intact. In the system, each lens from an hexagonal lens array observed the sample from slightly different perspectives and captured with a CCD camera. In the computer, these multiview raw images are converted to speckled contrast maps. Then, a self-deconvolution shift-and-add algorithm is employed for processing yields high contrast flow information. The method is experimentally validated first with a plastic tube filled with scattering liquid running at different controlled flow rates hidden in a biological tissue and then extensively tested for imaging of cerebral blood flow in an intact rodent head experience different conditions. A total of fifteen mice were used in the experiments divided randomly into three groups as follows: Group 1 (n=5) consisted of injured mice experience hypoxic ischemic brain injury monitored for ~40 min. Group 2 (n=5) injured mice experience anoxic brain injury monitored up to 20 min. Group 3 (n=5) experience functional activation monitored up to ~35 min. To increase tissue transparency and the penetration depth of photons through head tissue layers, an optical clearing method was employed. To our knowledge, this work presents for the first time the use of lens array in LSI scheme.

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

PubMed

Rouhani, Modjtaba; Javan, Dawood S

2016-03-01

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

Stress-induced cortisol secretion impairs detection performance in x-ray baggage screening for hidden weapons by screening novices.

PubMed

Thomas, Livia; Schwaninger, Adrian; Heimgartner, Nadja; Hedinger, Patrik; Hofer, Franziska; Ehlert, Ulrike; Wirtz, Petra H

2014-09-01

Aviation security strongly depends on screeners' performance in the detection of threat objects in x-ray images of passenger bags. We examined for the first time the effects of stress and stress-induced cortisol increases on detection performance of hidden weapons in an x-ray baggage screening task. We randomly assigned 48 participants either to a stress or a nonstress group. The stress group was exposed to a standardized psychosocial stress test (TSST). Before and after stress/nonstress, participants had to detect threat objects in a computer-based object recognition test (X-ray ORT). We repeatedly measured salivary cortisol and X-ray ORT performance before and after stress/nonstress. Cortisol increases in reaction to psychosocial stress induction but not to nonstress independently impaired x-ray detection performance. Our results suggest that stress-induced cortisol increases at peak reactivity impair x-ray screening performance. Copyright © 2014 Society for Psychophysiological Research.

Analysis of world terror networks from the reduced Google matrix of Wikipedia

NASA Astrophysics Data System (ADS)

El Zant, Samer; Frahm, Klaus M.; Jaffrès-Runser, Katia; Shepelyansky, Dima L.

2018-01-01

We apply the reduced Google matrix method to analyze interactions between 95 terrorist groups and determine their relationships and influence on 64 world countries. This is done on the basis of the Google matrix of the English Wikipedia (2017) composed of 5 416 537 articles which accumulate a great part of global human knowledge. The reduced Google matrix takes into account the direct and hidden links between a selection of 159 nodes (articles) appearing due to all paths of a random surfer moving over the whole network. As a result we obtain the network structure of terrorist groups and their relations with selected countries including hidden indirect links. Using the sensitivity of PageRank to a weight variation of specific links we determine the geopolitical sensitivity and influence of specific terrorist groups on world countries. The world maps of the sensitivity of various countries to influence of specific terrorist groups are obtained. We argue that this approach can find useful application for more extensive and detailed data bases analysis.

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

NASA Astrophysics Data System (ADS)

Xiong, Yan; Reichenbach, Stephen E.

1999-01-01

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

Enhancing speech recognition using improved particle swarm optimization based hidden Markov model.

PubMed

Selvaraj, Lokesh; Ganesan, Balakrishnan

2014-01-01

Enhancing speech recognition is the primary intention of this work. In this paper a novel speech recognition method based on vector quantization and improved particle swarm optimization (IPSO) is suggested. The suggested methodology contains four stages, namely, (i) denoising, (ii) feature mining (iii), vector quantization, and (iv) IPSO based hidden Markov model (HMM) technique (IP-HMM). At first, the speech signals are denoised using median filter. Next, characteristics such as peak, pitch spectrum, Mel frequency Cepstral coefficients (MFCC), mean, standard deviation, and minimum and maximum of the signal are extorted from the denoised signal. Following that, to accomplish the training process, the extracted characteristics are given to genetic algorithm based codebook generation in vector quantization. The initial populations are created by selecting random code vectors from the training set for the codebooks for the genetic algorithm process and IP-HMM helps in doing the recognition. At this point the creativeness will be done in terms of one of the genetic operation crossovers. The proposed speech recognition technique offers 97.14% accuracy.

Doppler Radar Vital Signs Detection Method Based on Higher Order Cyclostationary.

PubMed

Yu, Zhibin; Zhao, Duo; Zhang, Zhiqiang

2017-12-26

Due to the non-contact nature, using Doppler radar sensors to detect vital signs such as heart and respiration rates of a human subject is getting more and more attention. However, the related detection-method research meets lots of challenges due to electromagnetic interferences, clutter and random motion interferences. In this paper, a novel third-order cyclic cummulant (TOCC) detection method, which is insensitive to Gaussian interference and non-cyclic signals, is proposed to investigate the heart and respiration rate based on continuous wave Doppler radars. The k -th order cyclostationary properties of the radar signal with hidden periodicities and random motions are analyzed. The third-order cyclostationary detection theory of the heart and respiration rate is studied. Experimental results show that the third-order cyclostationary approach has better estimation accuracy for detecting the vital signs from the received radar signal under low SNR, strong clutter noise and random motion interferences.

Cover estimation and payload location using Markov random fields

NASA Astrophysics Data System (ADS)

Quach, Tu-Thach

2014-02-01

Payload location is an approach to find the message bits hidden in steganographic images, but not necessarily their logical order. Its success relies primarily on the accuracy of the underlying cover estimators and can be improved if more estimators are used. This paper presents an approach based on Markov random field to estimate the cover image given a stego image. It uses pairwise constraints to capture the natural two-dimensional statistics of cover images and forms a basis for more sophisticated models. Experimental results show that it is competitive against current state-of-the-art estimators and can locate payload embedded by simple LSB steganography and group-parity steganography. Furthermore, when combined with existing estimators, payload location accuracy improves significantly.

Scalar mixtures in porous media

NASA Astrophysics Data System (ADS)

Kree, Mihkel; Villermaux, Emmanuel

2017-10-01

Using a technique allowing for in situ measurements of concentrations fields, the evolution of scalar mixtures flowing within a porous medium made of a three-dimensional random stack of solid spheres, is addressed. Two distinct fluorescent dyes are injected from separate sources. Their evolution as they disperse and mix through the medium is directly observed and quantified, which is made possible by matching the refractive indices of the spheres and the flowing interstitial liquid. We decipher the nature of the interaction rule between the scalar sources, explaining the phenomenon that alters the concentration distribution of the overall mixture as it decays toward uniformity. Any residual correlation of the initially merged sources is progressively hidden, leading to an effective fully random interaction rule of the two distinct subfields.

Availability and mean time between failures of redundant systems with random maintenance of subsystems

NASA Technical Reports Server (NTRS)

Schneeweiss, W.

1977-01-01

It is shown how the availability and MTBF (Mean Time Between Failures) of a redundant system with subsystems maintenanced at the points of so-called stationary renewal processes can be determined from the distributions of the intervals between maintenance actions and of the failure-free operating intervals of the subsystems. The results make it possible, for example, to determine the frequency and duration of hidden failure states in computers which are incidentally corrected during the repair of observed failures.

Collective purchase behavior toward retail price changes

NASA Astrophysics Data System (ADS)

Ueno, Hiromichi; Watanabe, Tsutomu; Takayasu, Hideki; Takayasu, Misako

2011-02-01

By analyzing a huge amount of point-of-sale data collected from Japanese supermarkets, we find power law relationships between price and sales numbers. The estimated values of the exponents of these power laws depend on the category of products; however, they are independent of the stores, thereby implying the existence of universal human purchase behavior. The rate of sales numbers around these power laws are generally approximated by log-normal distributions implying that there are hidden random parameters, which might proportionally affect the purchase activity.

A half-blind color image hiding and encryption method in fractional Fourier domains

NASA Astrophysics Data System (ADS)

Ge, Fan; Chen, Linfei; Zhao, Daomu

2008-09-01

We have proposed a new technique for digital image encryption and hiding based on fractional Fourier transforms with double random phases. An original hidden image is encrypted two times and the keys are increased to strengthen information protection. Color image hiding and encryption with wavelength multiplexing is proposed by embedding and encryption in R, G and B three channels. The robustness against occlusion attacks and noise attacks are analyzed. And computer simulations are presented with the corresponding results.

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.

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

PubMed Central

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

2016-01-01

Feedforward deep neural networks (DNN), artificial neural networks with multiple hidden layers, have recently demonstrated a record-breaking performance in multiple areas of applications in computer vision and speech processing. Following the success, DNNs have been applied to neuroimaging modalities including functional/structural magnetic resonance imaging (MRI) and positron-emission tomography data. However, no study has explicitly applied DNNs to 3D whole-brain fMRI volumes and thereby extracted hidden volumetric representations of fMRI that are discriminative for a task performed as the fMRI volume was acquired. Our study applied fully connected feedforward DNN to fMRI volumes collected in four sensorimotor tasks (i.e., left-hand clenching, right-hand clenching, auditory attention, and visual stimulus) undertaken by 12 healthy participants. Using a leave-one-subject-out cross-validation scheme, a restricted Boltzmann machine-based deep belief network was pretrained and used to initialize weights of the DNN. The pretrained DNN was fine-tuned while systematically controlling weight-sparsity levels across hidden layers. Optimal weight-sparsity levels were determined from a minimum validation error rate of fMRI volume classification. Minimum error rates (mean ± standard deviation; %) of 6.9 (± 3.8) were obtained from the three-layer DNN with the sparsest condition of weights across the three hidden layers. These error rates were even lower than the error rates from the single-layer network (9.4 ± 4.6) and the two-layer network (7.4 ± 4.1). The estimated DNN weights showed spatial patterns that are remarkably task-specific, particularly in the higher layers. The output values of the third hidden layer represented distinct patterns/codes of the 3D whole-brain fMRI volume and encoded the information of the tasks as evaluated from representational similarity analysis. Our reported findings show the ability of the DNN to classify a single fMRI volume based on the extraction of hidden representations of fMRI volumes associated with tasks across multiple hidden layers. Our study may be beneficial to the automatic classification/diagnosis of neuropsychiatric and neurological diseases and prediction of disease severity and recovery in (pre-) clinical settings using fMRI volumes without requiring an estimation of activation patterns or ad hoc statistical evaluation. PMID:27079534

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

PubMed

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

2017-01-15

Feedforward deep neural networks (DNNs), artificial neural networks with multiple hidden layers, have recently demonstrated a record-breaking performance in multiple areas of applications in computer vision and speech processing. Following the success, DNNs have been applied to neuroimaging modalities including functional/structural magnetic resonance imaging (MRI) and positron-emission tomography data. However, no study has explicitly applied DNNs to 3D whole-brain fMRI volumes and thereby extracted hidden volumetric representations of fMRI that are discriminative for a task performed as the fMRI volume was acquired. Our study applied fully connected feedforward DNN to fMRI volumes collected in four sensorimotor tasks (i.e., left-hand clenching, right-hand clenching, auditory attention, and visual stimulus) undertaken by 12 healthy participants. Using a leave-one-subject-out cross-validation scheme, a restricted Boltzmann machine-based deep belief network was pretrained and used to initialize weights of the DNN. The pretrained DNN was fine-tuned while systematically controlling weight-sparsity levels across hidden layers. Optimal weight-sparsity levels were determined from a minimum validation error rate of fMRI volume classification. Minimum error rates (mean±standard deviation; %) of 6.9 (±3.8) were obtained from the three-layer DNN with the sparsest condition of weights across the three hidden layers. These error rates were even lower than the error rates from the single-layer network (9.4±4.6) and the two-layer network (7.4±4.1). The estimated DNN weights showed spatial patterns that are remarkably task-specific, particularly in the higher layers. The output values of the third hidden layer represented distinct patterns/codes of the 3D whole-brain fMRI volume and encoded the information of the tasks as evaluated from representational similarity analysis. Our reported findings show the ability of the DNN to classify a single fMRI volume based on the extraction of hidden representations of fMRI volumes associated with tasks across multiple hidden layers. Our study may be beneficial to the automatic classification/diagnosis of neuropsychiatric and neurological diseases and prediction of disease severity and recovery in (pre-) clinical settings using fMRI volumes without requiring an estimation of activation patterns or ad hoc statistical evaluation. Copyright © 2016 Elsevier Inc. All rights reserved.

Sun tracker for clear or cloudy weather

NASA Technical Reports Server (NTRS)

Scott, D. R.; White, P. R.

1979-01-01

Sun tracker orients solar collector so that they absorb maximum possible sunlight without being fooled by bright clouds, holes in cloud cover, or other atmospheric conditions. Tracker follows sun within 0.25 deg arc and is accurate within + or - 5 deg when sun is hidden.

Monthly streamflow forecasting based on hidden Markov model and Gaussian Mixture Regression

NASA Astrophysics Data System (ADS)

Liu, Yongqi; Ye, Lei; Qin, Hui; Hong, Xiaofeng; Ye, Jiajun; Yin, Xingli

2018-06-01

Reliable streamflow forecasts can be highly valuable for water resources planning and management. In this study, we combined a hidden Markov model (HMM) and Gaussian Mixture Regression (GMR) for probabilistic monthly streamflow forecasting. The HMM is initialized using a kernelized K-medoids clustering method, and the Baum-Welch algorithm is then executed to learn the model parameters. GMR derives a conditional probability distribution for the predictand given covariate information, including the antecedent flow at a local station and two surrounding stations. The performance of HMM-GMR was verified based on the mean square error and continuous ranked probability score skill scores. The reliability of the forecasts was assessed by examining the uniformity of the probability integral transform values. The results show that HMM-GMR obtained reasonably high skill scores and the uncertainty spread was appropriate. Different HMM states were assumed to be different climate conditions, which would lead to different types of observed values. We demonstrated that the HMM-GMR approach can handle multimodal and heteroscedastic data.

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

PubMed

Savitha, R; Suresh, S; Sundararajan, N

2012-08-01

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

Experimental Design for the Evaluation of Detection Techniques of Hidden Corrosion Beneath the Thermal Protective System of the Space Shuttle Orbiter

NASA Technical Reports Server (NTRS)

Kemmerer, Catherine C.; Jacoby, Joseph A.; Lomness, Janice K.; Hintze, Paul E.; Russell, Richard W.

2007-01-01

The detection of corrosion beneath Space Shuttle Orbiter thermal protective system is traditionally accomplished by removing the Reusable Surface Insulation tiles and performing a visual inspection of the aluminum substrate and corrosion protection system. This process is time consuming and has the potential to damage high cost tiles. To evaluate non-intrusive NDE methods, a Proof of Concept (PoC) experiment was designed and test panels were manufactured. The objective of the test plan was three-fold: establish the ability to detect corrosion hidden from view by tiles; determine the key factor affecting detectability; roughly quantify the detection threshold. The plan consisted of artificially inducing dimensionally controlled corrosion spots in two panels and rebonding tile over the spots to model the thermal protective system of the orbiter. The corrosion spot diameter ranged from 0.100" to 0.600" inches and the depth ranged from 0.003" to 0.020". One panel consisted of a complete factorial array of corrosion spots with and without tile coverage. The second panel consisted of randomized factorial points replicated and hidden by tile. Conventional methods such as ultrasonics, infrared, eddy current and microwave methods have shortcomings. Ultrasonics and IR cannot sufficiently penetrate the tiles, while eddy current and microwaves have inadequate resolution. As such, the panels were interrogated using Backscatter Radiography and Terahertz Imaging. The terahertz system successfully detected artificially induced corrosion spots under orbiter tile and functional testing is in-work in preparation for implementation.

Flexible Ultrathin Endoscope Integrated with Irrigation Suction Apparatus for Assisting Microneurosurgery.

PubMed

Otani, Naoki; Morimoto, Yuji; Fujii, Kazuya; Toyooka, Terushige; Wada, Kojiro; Mori, Kentaro

2017-12-01

Endoscopy can observe the anatomical components in a deeply located and/or hidden area during neurosurgical procedures under the operating microscope. We have newly developed a flexible ultrathin endoscope integrated with irrigation suction apparatus (FUEISA) to visualize deeply located and/or hidden areas for assisting microneurosurgery. The present study investigated the usefulness of the FUEISA system for direct clipping surgery of cerebral aneurysms. Twenty-one patients underwent microneurosurgery assisted with the FUEISA system for direct clipping of cerebral aneurysms. The flexible ultrathin endoscope (outer diameter 0.75mm) consists of an image guide (6000 dpi) and a light guide, integrated with the irrigation suction apparatus. This endoscopic system was inserted before and after clipping to observe the anatomical conditions surrounding the lesions. In all cases, handling and operation of the FUEISA was technically successful during the surgical procedure. The ultrathin endoscope was adequately integrated with the irrigation suction apparatus in all cases. General anatomy visualization including the lenticulostriate arteries, medial striate arteries, and/or internal carotid artery perforators was possible, and the correct clip positioning and vessel conditions were easily checked. The endoscope revealed that the clip had been positioned incorrectly in one case. No complications associated with the endoscopic system occurred. The FUEISA system can be applied with safe manipulation, which was remarkably useful for confirmation of the presence of perforators and cranial nerves behind the lesions, particularly anatomical components located in deep and/or hidden areas during clipping of cerebral aneurysms. Copyright © 2017 Elsevier Inc. All rights reserved.

SU-E-J-191: Motion Prediction Using Extreme Learning Machine in Image Guided Radiotherapy

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

Jia, J; Cao, R; Pei, X

Purpose: Real-time motion tracking is a critical issue in image guided radiotherapy due to the time latency caused by image processing and system response. It is of great necessity to fast and accurately predict the future position of the respiratory motion and the tumor location. Methods: The prediction of respiratory position was done based on the positioning and tracking module in ARTS-IGRT system which was developed by FDS Team (www.fds.org.cn). An approach involving with the extreme learning machine (ELM) was adopted to predict the future respiratory position as well as the tumor’s location by training the past trajectories. For themore » training process, a feed-forward neural network with one single hidden layer was used for the learning. First, the number of hidden nodes was figured out for the single layered feed forward network (SLFN). Then the input weights and hidden layer biases of the SLFN were randomly assigned to calculate the hidden neuron output matrix. Finally, the predicted movement were obtained by applying the output weights and compared with the actual movement. Breathing movement acquired from the external infrared markers was used to test the prediction accuracy. And the implanted marker movement for the prostate cancer was used to test the implementation of the tumor motion prediction. Results: The accuracy of the predicted motion and the actual motion was tested. Five volunteers with different breathing patterns were tested. The average prediction time was 0.281s. And the standard deviation of prediction accuracy was 0.002 for the respiratory motion and 0.001 for the tumor motion. Conclusion: The extreme learning machine method can provide an accurate and fast prediction of the respiratory motion and the tumor location and therefore can meet the requirements of real-time tumor-tracking in image guided radiotherapy.« less

Random telegraph noise in 2D hexagonal boron nitride dielectric films

NASA Astrophysics Data System (ADS)

Ranjan, A.; Puglisi, F. M.; Raghavan, N.; O'Shea, S. J.; Shubhakar, K.; Pavan, P.; Padovani, A.; Larcher, L.; Pey, K. L.

2018-03-01

This study reports the observation of low frequency random telegraph noise (RTN) in a 2D layered hexagonal boron nitride dielectric film in the pre- and post-soft breakdown phases using conductive atomic force microscopy as a nanoscale spectroscopy tool. The RTN traces of the virgin and electrically stressed dielectric (after percolation breakdown) were compared, and the signal features were statistically analyzed using the Factorial Hidden Markov Model technique. We observe a combination of both two-level and multi-level RTN signals in h-BN, akin to the trends commonly observed for bulk oxides such as SiO2 and HfO2. Experimental evidence suggests frequent occurrence of unstable and anomalous RTN traces in 2D dielectrics which makes extraction of defect energetics challenging.

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

PubMed

Pols, A J K

2017-06-01

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

Discovering the Sequential Structure of Thought

ERIC Educational Resources Information Center

Anderson, John R.; Fincham, Jon M.

2014-01-01

Multi-voxel pattern recognition techniques combined with Hidden Markov models can be used to discover the mental states that people go through in performing a task. The combined method identifies both the mental states and how their durations vary with experimental conditions. We apply this method to a task where participants solve novel…

Knock at Any School.

ERIC Educational Resources Information Center

Parish, Ralph; And Others

1989-01-01

In poor, urban schools, so much time is spent controlling and disciplining children to obey authority (or to learn the hidden curriculum), that scant time is left for "real" teaching and learning. This article shows how school culture (conditions, norms, relationships, and structures) can be changed to educate all children adequately. Includes 10…

Hidden Hearing Loss and Computational Models of the Auditory Pathway: Predicting Speech Intelligibility Decline

DTIC Science & Technology

2016-11-28

of low spontaneous rate auditory nerve fibers (ANFs) and reduction of auditory brainstem response wave-I amplitudes. The goal of this research is...auditory nerve (AN) responses to speech stimuli under a variety of difficult listening conditions. The resulting cochlear neurogram, a spectrogram

Beyond the Curriculum: Creating the Conditions for Learning.

ERIC Educational Resources Information Center

Grauer, Stuart

Using current mind/brain research, this paper explores the "hidden curriculum" in the contexts of teaching, learning and supervision. It explains ways in which current research on the nature of learning can fit into today's typical, "clinical" teaching techniques. The importance of respecting individual modes of learning is stressed; further to…

Unmasking Abilities Hidden by Developmental Conditions.

ERIC Educational Resources Information Center

Mallik, Kalisankar, Ed.; Shaver, Elaine M., Ed.

This document contains 16 papers that were scheduled to be presented at a conference (which was canceled) on approaches and programs for helping developmentally disabled persons to be more self-sufficient. The book is divided into three sections: (1) unmasking vocational abilities, (2) enhancing functional independence, and (3) medical and…

Risk Management in Adventure Programs with Special Populations: Two Hidden Dangers.

ERIC Educational Resources Information Center

Stich, Thomas; Gaylor, Michael S.

The paper addresses two significant risk management considerations in conducting an adventure program in a therapeutic setting: the potential hazards of psychiatric medications and psychological emergencies. Focusing on the potential hazards of psychiatric medications, the first section discusses climatic conditions (heat, cold, and sun) and the…

A Note on Causes of Effects

DTIC Science & Technology

2014-09-29

gone. Is it because I took aspirin ?”], let alone formulate conditions for its estimation in a counterfactual-free language (Pearl, 2000b, p. 429). 1...to take aspirin was unrelated to the (then hidden) values of the potential responses.” Now this additional assumption is unreasonable unless the joint

[Treatment of Urinary incontinence associated with genital prolapse: Clinical practrice guidelines].

PubMed

Cortesse, A; Cardot, V; Basset, V; Le Normand, L; Donon, L

2016-07-01

Prolapse and urinary incontinence are frequently associated. Patente (or proven) stress urinary incontinence (SUI) is defined by a leakage of urine that occurs with coughing or Valsalva, in the absence of any prolapse reduction manipulation. Masked urinary incontinence results in leakage of urine occurring during reduction of prolapse during the clinical examination in a patient who does not describe incontinence symptoms at baseline. The purpose of this chapter is to consider on the issue of systematic support or not of urinary incontinence, patent or hidden, during the cure of pelvic organs prolapse by abdominal or vaginal approach. This work is based on an systematic review of the literature (PubMed, Medline, Cochrane Library, Cochrane database of systematic reviews, EMBASE) for meta-analyzes, randomized trials, registries, literature reviews, controlled studies and major not controlled studies, published on the subject. Its implementation has followed the methodology of the HAS on the recommendations for clinical practice, with a scientific argument (with the level of evidence, NP) and a recommendation grade (A, B, C, and professional agreement). In case of patent IUE, concomitant treatment of prolapse and SUI reduces the risk of postoperative SUI. However, the isolated treatment of prolapse can treat up to 30% of preoperative SUI. Concomitant treatment of SUI exposed to a specific overactive bladder and dysuria morbidity. The presence of a hidden IUE represents a risk of postoperative SUI, but there is no clinical or urodynamic test to predict individually the risk of postoperative SUI. Moreover, the isolated treatment of prolapse can treat up to 60% of the masked SUI. Concomitant treatment of the hidden IUE therefore exposes again to overtreatment and a specific overactive bladder and dysuria morbidity. In case of overt or hidden urinary incontinence, concomitant treatment of SUI and prolapse reduces the risk of postoperative SUI but exposes to a specific overactive bladder and dysuria morbidity (NP3). The isolated treatment of prolapse often allows itself to treat preoperative SUI. We can suggest not to treat SUI (whether patent or hidden) at the same time, providing that women are informed of the possibility of 2 stages surgery (Grade C). © 2016 Published by Elsevier Masson SAS. © 2016 Elsevier Masson SAS. Tous droits réservés.

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

PubMed

Yang, Yimin; Wang, Yaonan; Yuan, Xiaofang

2012-09-01

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

Clustered mixed nonhomogeneous Poisson process spline models for the analysis of recurrent event panel data.

PubMed

Nielsen, J D; Dean, C B

2008-09-01

A flexible semiparametric model for analyzing longitudinal panel count data arising from mixtures is presented. Panel count data refers here to count data on recurrent events collected as the number of events that have occurred within specific follow-up periods. The model assumes that the counts for each subject are generated by mixtures of nonhomogeneous Poisson processes with smooth intensity functions modeled with penalized splines. Time-dependent covariate effects are also incorporated into the process intensity using splines. Discrete mixtures of these nonhomogeneous Poisson process spline models extract functional information from underlying clusters representing hidden subpopulations. The motivating application is an experiment to test the effectiveness of pheromones in disrupting the mating pattern of the cherry bark tortrix moth. Mature moths arise from hidden, but distinct, subpopulations and monitoring the subpopulation responses was of interest. Within-cluster random effects are used to account for correlation structures and heterogeneity common to this type of data. An estimating equation approach to inference requiring only low moment assumptions is developed and the finite sample properties of the proposed estimating functions are investigated empirically by simulation.

Numerical predictions and experiments for optimizing hidden corrosion detection in aircraft structures using Lamb modes.

PubMed

Terrien, N; Royer, D; Lepoutre, F; Déom, A

2007-06-01

To increase the sensitivity of Lamb waves to hidden corrosion in aircraft structures, a preliminary step is to understand the phenomena governing this interaction. A hybrid model combining a finite element approach and a modal decomposition method is used to investigate the interaction of Lamb modes with corrosion pits. The finite element mesh is used to describe the region surrounding the corrosion pits while the modal decomposition method permits to determine the waves reflected and transmitted by the damaged area. Simulations make easier the interpretation of some parts of the measured waveform corresponding to superposition of waves diffracted by the corroded area. Numerical results permit to extract significant information from the transmitted waveform and thus to optimize the signal processing for the detection of corrosion at an early stage. Now, we are able to detect corrosion pits down to 80-mum depth distributed randomly on a square centimeter of an aluminum plate. Moreover, thickness variations present on aircraft structures can be discriminated from a slightly corroded area. Finally, using this experimental setup, aircraft structures have been tested.

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

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.

Effectiveness Testing of Embedded User Support for U.S. Army Installation-Level Software

DTIC Science & Technology

1991-06-01

under what conditions Dynamic Help could influence performance and satisfaction. The ACIFS program was modified to provide automatic collection of all...under what conditions Dynamic Help can influence user performance and satisfaction. This chapter reports the design, implementation, and analysis of...ambiguous or is hidden in the body of the message. The ACIFS program has many user interface deficiencies, but it does allow the user to use trial and

Demystifying the memory effect: A geometrical approach to understanding speckle correlations

NASA Astrophysics Data System (ADS)

Prunty, Aaron C.; Snieder, Roel K.

2017-05-01

The memory effect has seen a surge of research into its fundamental properties and applications since its discovery by Feng et al. [Phys. Rev. Lett. 61, 834 (1988)]. While the wave trajectories for which the memory effect holds are hidden implicitly in the diffusion probability function [Phys. Rev. B 40, 737 (1989)], the physical intuition of why these trajectories satisfy the memory effect has often been masked by the derivation of the memory correlation function itself. In this paper, we explicitly derive the specific trajectories through a random medium for which the memory effect holds. Our approach shows that the memory effect follows from a simple conservation argument, which imposes geometrical constraints on the random trajectories that contribute to the memory effect. We illustrate the time-domain effects of these geometrical constraints with numerical simulations of pulse transmission through a random medium. The results of our derivation and numerical simulations are consistent with established theory and experimentation.

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.

Mental simulation of drawing actions enhances delayed recall of a complex figure.

PubMed

De Lucia, Natascia; Trojano, Luigi; Senese, Vincenzo Paolo; Conson, Massimiliano

2016-10-01

Motor simulation implies that the same motor representations involved in action execution are re-enacted during observation or imagery of actions. Neurofunctional data suggested that observation of letters or abstract paintings can elicit simulation of writing or drawing gestures. We performed four behavioural experiments on right-handed healthy participants to test whether observation of a static and complex geometrical figure implies re-enactment of drawing actions. In Experiment 1, participants had to observe the stimulus without explicit instruction (observation-only condition), while performing irrelevant finger tapping (motor dual task), or while articulating irrelevant verbal material (verbal dual task). Delayed drawing of the stimulus was less accurate in the motor dual-task (interfering with simulation of hand actions) than in verbal dual-task and observation-only conditions. In Experiment 2, delayed drawing in the observation only was as accurate as when participants encoded the stimulus by copying it; in both conditions, accuracy was higher than when participants were instructed to observe the stimulus to recall it later verbally (observe to recall), thus being discouraged from engaging motor simulation. In Experiment 3, delayed drawing was as accurate in the observation-only condition as when participants imagined copying the stimulus; accuracy in both conditions was higher than in the observe-to-recall condition. In Experiment 4, in the observe-only condition participants who observed the stimulus with their right arm hidden behind their back were significantly less accurate than participants who had their left arm hidden. These findings converge in suggesting that mere observation of a geometrical stimulus can activate motor simulation and re-enactment of drawing actions.

Estimating Sampling Selection Bias in Human Genetics: A Phenomenological Approach

PubMed Central

Risso, Davide; Taglioli, Luca; De Iasio, Sergio; Gueresi, Paola; Alfani, Guido; Nelli, Sergio; Rossi, Paolo; Paoli, Giorgio; Tofanelli, Sergio

2015-01-01

This research is the first empirical attempt to calculate the various components of the hidden bias associated with the sampling strategies routinely-used in human genetics, with special reference to surname-based strategies. We reconstructed surname distributions of 26 Italian communities with different demographic features across the last six centuries (years 1447–2001). The degree of overlapping between "reference founding core" distributions and the distributions obtained from sampling the present day communities by probabilistic and selective methods was quantified under different conditions and models. When taking into account only one individual per surname (low kinship model), the average discrepancy was 59.5%, with a peak of 84% by random sampling. When multiple individuals per surname were considered (high kinship model), the discrepancy decreased by 8–30% at the cost of a larger variance. Criteria aimed at maximizing locally-spread patrilineages and long-term residency appeared to be affected by recent gene flows much more than expected. Selection of the more frequent family names following low kinship criteria proved to be a suitable approach only for historically stable communities. In any other case true random sampling, despite its high variance, did not return more biased estimates than other selective methods. Our results indicate that the sampling of individuals bearing historically documented surnames (founders' method) should be applied, especially when studying the male-specific genome, to prevent an over-stratification of ancient and recent genetic components that heavily biases inferences and statistics. PMID:26452043

Estimating Sampling Selection Bias in Human Genetics: A Phenomenological Approach.

PubMed

Risso, Davide; Taglioli, Luca; De Iasio, Sergio; Gueresi, Paola; Alfani, Guido; Nelli, Sergio; Rossi, Paolo; Paoli, Giorgio; Tofanelli, Sergio

2015-01-01

This research is the first empirical attempt to calculate the various components of the hidden bias associated with the sampling strategies routinely-used in human genetics, with special reference to surname-based strategies. We reconstructed surname distributions of 26 Italian communities with different demographic features across the last six centuries (years 1447-2001). The degree of overlapping between "reference founding core" distributions and the distributions obtained from sampling the present day communities by probabilistic and selective methods was quantified under different conditions and models. When taking into account only one individual per surname (low kinship model), the average discrepancy was 59.5%, with a peak of 84% by random sampling. When multiple individuals per surname were considered (high kinship model), the discrepancy decreased by 8-30% at the cost of a larger variance. Criteria aimed at maximizing locally-spread patrilineages and long-term residency appeared to be affected by recent gene flows much more than expected. Selection of the more frequent family names following low kinship criteria proved to be a suitable approach only for historically stable communities. In any other case true random sampling, despite its high variance, did not return more biased estimates than other selective methods. Our results indicate that the sampling of individuals bearing historically documented surnames (founders' method) should be applied, especially when studying the male-specific genome, to prevent an over-stratification of ancient and recent genetic components that heavily biases inferences and statistics.

Time series modeling by a regression approach based on a latent process.

PubMed

Chamroukhi, Faicel; Samé, Allou; Govaert, Gérard; Aknin, Patrice

2009-01-01

Time series are used in many domains including finance, engineering, economics and bioinformatics generally to represent the change of a measurement over time. Modeling techniques may then be used to give a synthetic representation of such data. A new approach for time series modeling is proposed in this paper. It consists of a regression model incorporating a discrete hidden logistic process allowing for activating smoothly or abruptly different polynomial regression models. The model parameters are estimated by the maximum likelihood method performed by a dedicated Expectation Maximization (EM) algorithm. The M step of the EM algorithm uses a multi-class Iterative Reweighted Least-Squares (IRLS) algorithm to estimate the hidden process parameters. To evaluate the proposed approach, an experimental study on simulated data and real world data was performed using two alternative approaches: a heteroskedastic piecewise regression model using a global optimization algorithm based on dynamic programming, and a Hidden Markov Regression Model whose parameters are estimated by the Baum-Welch algorithm. Finally, in the context of the remote monitoring of components of the French railway infrastructure, and more particularly the switch mechanism, the proposed approach has been applied to modeling and classifying time series representing the condition measurements acquired during switch operations.

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

NASA Astrophysics Data System (ADS)

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

2018-04-01

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

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.

Social exclusion, health and hidden homelessness.

PubMed

Watson, J; Crawley, J; Kane, D

2016-10-01

Homelessness and poverty are extreme forms of social exclusion which extend beyond the lack of physical or material needs. The purpose of this study was to explore and expand the concept of social exclusion within the social determinants of health perspective - to understand how the social environment, health behaviours and health status are associated with material and social deprivation. Fundamental qualitative description with tones of focused ethnography. Participants who identified as hidden homeless described their everyday living conditions and how these everyday conditions were impacted and influenced by their social environments, coping/health behaviours and current health status. Research Ethics Board approval was granted and informed consents were obtained from 21 participants prior to the completion of individual interviews. Qualitative content analysis examined the descriptions of men and women experiencing hidden homelessness. Participants described the 'lack of quality social interactions and supports' and their 'daily struggles of street life'. They also shared the 'pain of addiction' and how coping strategies influenced health. Participants were hopeful that their insights would 'better the health of homeless people' by helping shape public policy and funding of community resources that would reduce barriers and improve overall health. Health professionals who understand health behaviours as coping mechanisms for poor quality social environments can provide more comprehensive and holistic care. The findings of this study can be used to support the importance of housing as a key factor in the health and well-being of people experiencing poverty, homelessness and social exclusion; and consequently, reinforces the need for a national housing strategy. Copyright © 2016 The Royal Society for Public Health. Published by Elsevier Ltd. All rights reserved.

Cornmeal and starch influence the dynamic of fumonisin B, A and C production and masking in Fusarium verticillioides and F. proliferatum.

PubMed

Lazzaro, Irene; Falavigna, Claudia; Galaverna, Gianni; Dall'Asta, Chiara; Battilani, Paola

2013-08-16

Fusarium verticillioides and F. proliferatum can infect maize ears and produce fumonisins. The fumonisin B (FB) series is the most prolifically produced, followed by fumonisin C (FC), A (FA) and P (FP); moreover hidden forms of fumonisins have been detected in maize and derivatives. There is a lack of information about which maize component may affect fumonisin pattern production. Therefore, in this work we studied the role of cornmeal and corn starch, as the sole source of nutrition, in the production dynamic of all fumonisin series, hidden forms included, in different strains of F. verticillioides and F. proliferatum incubated at 25°C for 7-45days. Both Fusarium species produced high amounts of FB, following the chemotype FB1>FB2>FB3; FC and FA were produced in lesser amounts, showing the chemotypes: FA2+FA3>FA1 and FC1>FC2+FC3>FC4, respectively; while no FP were detected. F. verticillioides was more prolific than F. proliferatum in fumonisin production (ten times more on average) in all the tested conditions. Fumonisin production was higher in cornmeal than in starch based medium in both Fusarium species; FA and FC were detected only in the former medium. An important role of amylopectin as an inducing factor for fumonisin biosynthesis was suggested, as were acid pH conditions. Fumonisin hidden forms may occur in cornmeal medium, whereas they were never found at significant levels in corn starch medium. Copyright © 2013 Elsevier B.V. All rights reserved.

The Hidden Curriculum as Emancipatory and Non-Emancipatory Tools.

ERIC Educational Resources Information Center

Kanpol, Barry

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

Modeling carbachol-induced hippocampal network synchronization using hidden Markov models

NASA Astrophysics Data System (ADS)

Dragomir, Andrei; Akay, Yasemin M.; Akay, Metin

2010-10-01

In this work we studied the neural state transitions undergone by the hippocampal neural network using a hidden Markov model (HMM) framework. We first employed a measure based on the Lempel-Ziv (LZ) estimator to characterize the changes in the hippocampal oscillation patterns in terms of their complexity. These oscillations correspond to different modes of hippocampal network synchronization induced by the cholinergic agonist carbachol in the CA1 region of mice hippocampus. HMMs are then used to model the dynamics of the LZ-derived complexity signals as first-order Markov chains. Consequently, the signals corresponding to our oscillation recordings can be segmented into a sequence of statistically discriminated hidden states. The segmentation is used for detecting transitions in neural synchronization modes in data recorded from wild-type and triple transgenic mice models (3xTG) of Alzheimer's disease (AD). Our data suggest that transition from low-frequency (delta range) continuous oscillation mode into high-frequency (theta range) oscillation, exhibiting repeated burst-type patterns, occurs always through a mode resembling a mixture of the two patterns, continuous with burst. The relatively random patterns of oscillation during this mode may reflect the fact that the neuronal network undergoes re-organization. Further insight into the time durations of these modes (retrieved via the HMM segmentation of the LZ-derived signals) reveals that the mixed mode lasts significantly longer (p < 10-4) in 3xTG AD mice. These findings, coupled with the documented cholinergic neurotransmission deficits in the 3xTG mice model, may be highly relevant for the case of AD.

Emotional Abuse of Students of Color: The Hidden Inhumanity in Our Schools

ERIC Educational Resources Information Center

McKenzie, Kathryn Bell

2009-01-01

Illuminating and understanding the emotional abuse inflicted on many students of color is a necessity in creating conditions for their school success. However, this topic is rarely discussed among educators and those preparing educators. However, from the author's recent experiences conducting research in racially diverse schools as well as her…

Hidden Contradictions and Conditionality: Conceptualisations of Inclusive Education in International Human Rights Law

ERIC Educational Resources Information Center

Byrne, Bronagh

2013-01-01

The nature of education that children with disabilities should receive has been subject to much debate. This article critically assesses the ways in which the international human rights framework has conceptualised "inclusive education". It argues that the right to education for children with disabilities in international law is…

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

ERIC Educational Resources Information Center

Stellman, Jeanne M.

1977-01-01

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

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.

Development of a Fault Monitoring Technique for Wind Turbines Using a Hidden Markov Model.

PubMed

Shin, Sung-Hwan; Kim, SangRyul; Seo, Yun-Ho

2018-06-02

Regular inspection for the maintenance of the wind turbines is difficult because of their remote locations. For this reason, condition monitoring systems (CMSs) are typically installed to monitor their health condition. The purpose of this study is to propose a fault detection algorithm for the mechanical parts of the wind turbine. To this end, long-term vibration data were collected over two years by a CMS installed on a 3 MW wind turbine. The vibration distribution at a specific rotating speed of main shaft is approximated by the Weibull distribution and its cumulative distribution function is utilized for determining the threshold levels that indicate impending failure of mechanical parts. A Hidden Markov model (HMM) is employed to propose the statistical fault detection algorithm in the time domain and the method whereby the input sequence for HMM is extracted is also introduced by considering the threshold levels and the correlation between the signals. Finally, it was demonstrated that the proposed HMM algorithm achieved a greater than 95% detection success rate by using the long-term signals.

Fumonisins B, A and C profile and masking in Fusarium verticillioides strains on fumonisin-inducing and maize-based media.

PubMed

Lazzaro, Irene; Falavigna, Claudia; Dall'asta, Chiara; Proctor, Robert H; Galaverna, Gianni; Battilani, Paola

2012-10-01

The production of fumonisin B, A and C and hidden and partially hydrolysed fumonisin occurrence was investigated in 3 strains of Fusarium verticillioides isolated from maize, cultured for 21-45days on malt extract medium at 25°C and 0.955-0.990 water activity (a(w)). Fumonisin A-B and C series were produced by all the strains in all conditions studied, with B-fumonisin≫C-fumonisin>A-fumonisin following a similar trend. The dynamic of fumonisin production was significantly influenced by factors considered and their interaction, with a(w)=0.990 as favourable condition in ITEM 10026 and ITEM 10027. All fumonisins were maximised at 30days incubation in ITEM 10027 and ITEM 1744 and at 45days incubation in ITEM 10026. Partially hydrolysed fumonisins were detected only for the B-group. Hidden fumonisins were never observed in Fusarium cultures grown on malt extract medium but were detected in the additional trial on maize-based medium, suggesting that the masking phenomenon can occur only in a complex matrix. Copyright © 2012 Elsevier B.V. All rights reserved.

Target intersection probabilities for parallel-line and continuous-grid types of search

USGS Publications Warehouse

McCammon, R.B.

1977-01-01

The expressions for calculating the probability of intersection of hidden targets of different sizes and shapes for parallel-line and continuous-grid types of search can be formulated by vsing the concept of conditional probability. When the prior probability of the orientation of a widden target is represented by a uniform distribution, the calculated posterior probabilities are identical with the results obtained by the classic methods of probability. For hidden targets of different sizes and shapes, the following generalizations about the probability of intersection can be made: (1) to a first approximation, the probability of intersection of a hidden target is proportional to the ratio of the greatest dimension of the target (viewed in plane projection) to the minimum line spacing of the search pattern; (2) the shape of the hidden target does not greatly affect the probability of the intersection when the largest dimension of the target is small relative to the minimum spacing of the search pattern, (3) the probability of intersecting a target twice for a particular type of search can be used as a lower bound if there is an element of uncertainty of detection for a particular type of tool; (4) the geometry of the search pattern becomes more critical when the largest dimension of the target equals or exceeds the minimum spacing of the search pattern; (5) for elongate targets, the probability of intersection is greater for parallel-line search than for an equivalent continuous square-grid search when the largest dimension of the target is less than the minimum spacing of the search pattern, whereas the opposite is true when the largest dimension exceeds the minimum spacing; (6) the probability of intersection for nonorthogonal continuous-grid search patterns is not greatly different from the probability of intersection for the equivalent orthogonal continuous-grid pattern when the orientation of the target is unknown. The probability of intersection for an elliptically shaped target can be approximated by treating the ellipse as intermediate between a circle and a line. A search conducted along a continuous rectangular grid can be represented as intermediate between a search along parallel lines and along a continuous square grid. On this basis, an upper and lower bound for the probability of intersection of an elliptically shaped target for a continuous rectangular grid can be calculated. Charts have been constructed that permit the values for these probabilities to be obtained graphically. The use of conditional probability allows the explorationist greater flexibility in considering alternate search strategies for locating hidden targets. ?? 1977 Plenum Publishing Corp.

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

NASA Astrophysics Data System (ADS)

Koyama, Takuya; Kakino, Satoko; Matsuura, Yuji

2017-04-01

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

--No Title--

Science.gov Websites

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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.

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

Maximum likelihood: Extracting unbiased information from complex networks

NASA Astrophysics Data System (ADS)

Garlaschelli, Diego; Loffredo, Maria I.

2008-07-01

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

When maths trumps logic: probabilistic judgements in chimpanzees.

PubMed

Hanus, Daniel; Call, Josep

2014-12-01

When searching for hidden food, do chimpanzees take into account both the number of hidden items and the number of potential hiding locations? We presented chimpanzees with two trays, each of them containing a different food/cup ratio and therefore a different likelihood of finding a baited cup among empty alternatives. Subjects' performance was directly influenced by the relative difference (probability ratio (PR)) between the two given probabilities. Interestingly, however, they did not appreciate the special value of a truly safe option (with P = 1.0). Instead, they seemed to 'blindly' rely on the PR between the two options, systematically preferring the more likely one once a certain threshold had been reached. A control condition ruled out the possibility of low-level learning explanations for the observed performance. © 2014 The Author(s) Published by the Royal Society. All rights reserved.

Hidden Markov models for fault detection in dynamic systems

NASA Technical Reports Server (NTRS)

Smyth, Padhraic J. (Inventor)

1995-01-01

The invention is a system failure monitoring method and apparatus which learns the symptom-fault mapping directly from training data. The invention first estimates the state of the system at discrete intervals in time. A feature vector x of dimension k is estimated from sets of successive windows of sensor data. A pattern recognition component then models the instantaneous estimate of the posterior class probability given the features, p(w(sub i) (vertical bar)/x), 1 less than or equal to i isless than or equal to m. Finally, a hidden Markov model is used to take advantage of temporal context and estimate class probabilities conditioned on recent past history. In this hierarchical pattern of information flow, the time series data is transformed and mapped into a categorical representation (the fault classes) and integrated over time to enable robust decision-making.

Hidden Markov models for fault detection in dynamic systems

NASA Technical Reports Server (NTRS)

Smyth, Padhraic J. (Inventor)

1993-01-01

The invention is a system failure monitoring method and apparatus which learns the symptom-fault mapping directly from training data. The invention first estimates the state of the system at discrete intervals in time. A feature vector x of dimension k is estimated from sets of successive windows of sensor data. A pattern recognition component then models the instantaneous estimate of the posterior class probability given the features, p(w(sub i) perpendicular to x), 1 less than or equal to i is less than or equal to m. Finally, a hidden Markov model is used to take advantage of temporal context and estimate class probabilities conditioned on recent past history. In this hierarchical pattern of information flow, the time series data is transformed and mapped into a categorical representation (the fault classes) and integrated over time to enable robust decision-making.

A hidden Markov model approach to neuron firing patterns.

PubMed

Camproux, A C; Saunier, F; Chouvet, G; Thalabard, J C; Thomas, G

1996-11-01

Analysis and characterization of neuronal discharge patterns are of interest to neurophysiologists and neuropharmacologists. In this paper we present a hidden Markov model approach to modeling single neuron electrical activity. Basically the model assumes that each interspike interval corresponds to one of several possible states of the neuron. Fitting the model to experimental series of interspike intervals by maximum likelihood allows estimation of the number of possible underlying neuron states, the probability density functions of interspike intervals corresponding to each state, and the transition probabilities between states. We present an application to the analysis of recordings of a locus coeruleus neuron under three pharmacological conditions. The model distinguishes two states during halothane anesthesia and during recovery from halothane anesthesia, and four states after administration of clonidine. The transition probabilities yield additional insights into the mechanisms of neuron firing.

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

Spatial Relational Memory in 9-Month-Old Macaque Monkeys

ERIC Educational Resources Information Center

Lavenex, Pierre; Lavenex, Pamela Banta

2006-01-01

This experiment assesses spatial and nonspatial relational memory in freely moving 9-mo-old and adult (11-13-yr-old) macaque monkeys ("Macaca mulatta"). We tested the use of proximal landmarks, two different objects placed at the center of an open-field arena, as conditional cues allowing monkeys to predict the location of food rewards hidden in…

Method Accelerates Training Of Some Neural Networks

NASA Technical Reports Server (NTRS)

Shelton, Robert O.

1992-01-01

Three-layer networks trained faster provided two conditions are satisfied: numbers of neurons in layers are such that majority of work done in synaptic connections between input and hidden layers, and number of neurons in input layer at least as great as number of training pairs of input and output vectors. Based on modified version of back-propagation method.

On-line diagnosis of inter-turn short circuit fault for DC brushed motor.

PubMed

Zhang, Jiayuan; Zhan, Wei; Ehsani, Mehrdad

2018-06-01

Extensive research effort has been made in fault diagnosis of motors and related components such as winding and ball bearing. In this paper, a new concept of inter-turn short circuit fault for DC brushed motors is proposed to include the short circuit ratio and short circuit resistance. A first-principle model is derived for motors with inter-turn short circuit fault. A statistical model based on Hidden Markov Model is developed for fault diagnosis purpose. This new method not only allows detection of motor winding short circuit fault, it can also provide estimation of the fault severity, as indicated by estimation of the short circuit ratio and the short circuit resistance. The estimated fault severity can be used for making appropriate decisions in response to the fault condition. The feasibility of the proposed methodology is studied for inter-turn short circuit of DC brushed motors using simulation in MATLAB/Simulink environment. In addition, it is shown that the proposed methodology is reliable with the presence of small random noise in the system parameters and measurement. Copyright © 2018 ISA. Published by Elsevier Ltd. All rights reserved.

A latent discriminative model-based approach for classification of imaginary motor tasks from EEG data.

PubMed

Saa, Jaime F Delgado; Çetin, Müjdat

2012-04-01

We consider the problem of classification of imaginary motor tasks from electroencephalography (EEG) data for brain-computer interfaces (BCIs) and propose a new approach based on hidden conditional random fields (HCRFs). HCRFs are discriminative graphical models that are attractive for this problem because they (1) exploit the temporal structure of EEG; (2) include latent variables that can be used to model different brain states in the signal; and (3) involve learned statistical models matched to the classification task, avoiding some of the limitations of generative models. Our approach involves spatial filtering of the EEG signals and estimation of power spectra based on autoregressive modeling of temporal segments of the EEG signals. Given this time-frequency representation, we select certain frequency bands that are known to be associated with execution of motor tasks. These selected features constitute the data that are fed to the HCRF, parameters of which are learned from training data. Inference algorithms on the HCRFs are used for the classification of motor tasks. We experimentally compare this approach to the best performing methods in BCI competition IV as well as a number of more recent methods and observe that our proposed method yields better classification accuracy.

Learning a Dictionary of Shape Epitomes with Applications to Image Labeling

PubMed Central

Chen, Liang-Chieh; Papandreou, George; Yuille, Alan L.

2015-01-01

The first main contribution of this paper is a novel method for representing images based on a dictionary of shape epitomes. These shape epitomes represent the local edge structure of the image and include hidden variables to encode shift and rotations. They are learnt in an unsupervised manner from groundtruth edges. This dictionary is compact but is also able to capture the typical shapes of edges in natural images. In this paper, we illustrate the shape epitomes by applying them to the image labeling task. In other work, described in the supplementary material, we apply them to edge detection and image modeling. We apply shape epitomes to image labeling by using Conditional Random Field (CRF) Models. They are alternatives to the superpixel or pixel representations used in most CRFs. In our approach, the shape of an image patch is encoded by a shape epitome from the dictionary. Unlike the superpixel representation, our method avoids making early decisions which cannot be reversed. Our resulting hierarchical CRFs efficiently capture both local and global class co-occurrence properties. We demonstrate its quantitative and qualitative properties of our approach with image labeling experiments on two standard datasets: MSRC-21 and Stanford Background. PMID:26321886

Long-term activity recognition from wristwatch accelerometer data.

PubMed

Garcia-Ceja, Enrique; Brena, Ramon F; Carrasco-Jimenez, Jose C; Garrido, Leonardo

2014-11-27

With the development of wearable devices that have several embedded sensors, it is possible to collect data that can be analyzed in order to understand the user's needs and provide personalized services. Examples of these types of devices are smartphones, fitness-bracelets, smartwatches, just to mention a few. In the last years, several works have used these devices to recognize simple activities like running, walking, sleeping, and other physical activities. There has also been research on recognizing complex activities like cooking, sporting, and taking medication, but these generally require the installation of external sensors that may become obtrusive to the user. In this work we used acceleration data from a wristwatch in order to identify long-term activities. We compare the use of Hidden Markov Models and Conditional Random Fields for the segmentation task. We also added prior knowledge into the models regarding the duration of the activities by coding them as constraints and sequence patterns were added in the form of feature functions. We also performed subclassing in order to deal with the problem of intra-class fragmentation, which arises when the same label is applied to activities that are conceptually the same but very different from the acceleration point of view.

"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.

[Respondent-Driven Sampling: a new sampling method to study visible and hidden populations].

PubMed

Mantecón, Alejandro; Juan, Montse; Calafat, Amador; Becoña, Elisardo; Román, Encarna

2008-01-01

The paper introduces a variant of chain-referral sampling: respondent-driven sampling (RDS). This sampling method shows that methods based on network analysis can be combined with the statistical validity of standard probability sampling methods. In this sense, RDS appears to be a mathematical improvement of snowball sampling oriented to the study of hidden populations. However, we try to prove its validity with populations that are not within a sampling frame but can nonetheless be contacted without difficulty. The basics of RDS are explained through our research on young people (aged 14 to 25) who go clubbing, consume alcohol and other drugs, and have sex. Fieldwork was carried out between May and July 2007 in three Spanish regions: Baleares, Galicia and Comunidad Valenciana. The presentation of the study shows the utility of this type of sampling when the population is accessible but there is a difficulty deriving from the lack of a sampling frame. However, the sample obtained is not a random representative one in statistical terms of the target population. It must be acknowledged that the final sample is representative of a 'pseudo-population' that approximates to the target population but is not identical to it.

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.

Online games: a novel approach to explore how partial information influences human random searches

NASA Astrophysics Data System (ADS)

Martínez-García, Ricardo; Calabrese, Justin M.; López, Cristóbal

2017-01-01

Many natural processes rely on optimizing the success ratio of a search process. We use an experimental setup consisting of a simple online game in which players have to find a target hidden on a board, to investigate how the rounds are influenced by the detection of cues. We focus on the search duration and the statistics of the trajectories traced on the board. The experimental data are explained by a family of random-walk-based models and probabilistic analytical approximations. If no initial information is given to the players, the search is optimized for cues that cover an intermediate spatial scale. In addition, initial information about the extension of the cues results, in general, in faster searches. Finally, strategies used by informed players turn into non-stationary processes in which the length of e ach displacement evolves to show a well-defined characteristic scale that is not found in non-informed searches.

Stego on FPGA: An IWT Approach

PubMed Central

Ramalingam, Balakrishnan

2014-01-01

A reconfigurable hardware architecture for the implementation of integer wavelet transform (IWT) based adaptive random image steganography algorithm is proposed. The Haar-IWT was used to separate the subbands namely, LL, LH, HL, and HH, from 8 × 8 pixel blocks and the encrypted secret data is hidden in the LH, HL, and HH blocks using Moore and Hilbert space filling curve (SFC) scan patterns. Either Moore or Hilbert SFC was chosen for hiding the encrypted data in LH, HL, and HH coefficients, whichever produces the lowest mean square error (MSE) and the highest peak signal-to-noise ratio (PSNR). The fixated random walk's verdict of all blocks is registered which is nothing but the furtive key. Our system took 1.6 µs for embedding the data in coefficient blocks and consumed 34% of the logic elements, 22% of the dedicated logic register, and 2% of the embedded multiplier on Cyclone II field programmable gate array (FPGA). PMID:24723794

Online games: a novel approach to explore how partial information influences human random searches.

PubMed

Martínez-García, Ricardo; Calabrese, Justin M; López, Cristóbal

2017-01-06

Many natural processes rely on optimizing the success ratio of a search process. We use an experimental setup consisting of a simple online game in which players have to find a target hidden on a board, to investigate how the rounds are influenced by the detection of cues. We focus on the search duration and the statistics of the trajectories traced on the board. The experimental data are explained by a family of random-walk-based models and probabilistic analytical approximations. If no initial information is given to the players, the search is optimized for cues that cover an intermediate spatial scale. In addition, initial information about the extension of the cues results, in general, in faster searches. Finally, strategies used by informed players turn into non-stationary processes in which the length of e ach displacement evolves to show a well-defined characteristic scale that is not found in non-informed searches.

Statistical mechanics of unsupervised feature learning in a restricted Boltzmann machine with binary synapses

NASA Astrophysics Data System (ADS)

Huang, Haiping

2017-05-01

Revealing hidden features in unlabeled data is called unsupervised feature learning, which plays an important role in pretraining a deep neural network. Here we provide a statistical mechanics analysis of the unsupervised learning in a restricted Boltzmann machine with binary synapses. A message passing equation to infer the hidden feature is derived, and furthermore, variants of this equation are analyzed. A statistical analysis by replica theory describes the thermodynamic properties of the model. Our analysis confirms an entropy crisis preceding the non-convergence of the message passing equation, suggesting a discontinuous phase transition as a key characteristic of the restricted Boltzmann machine. Continuous phase transition is also confirmed depending on the embedded feature strength in the data. The mean-field result under the replica symmetric assumption agrees with that obtained by running message passing algorithms on single instances of finite sizes. Interestingly, in an approximate Hopfield model, the entropy crisis is absent, and a continuous phase transition is observed instead. We also develop an iterative equation to infer the hyper-parameter (temperature) hidden in the data, which in physics corresponds to iteratively imposing Nishimori condition. Our study provides insights towards understanding the thermodynamic properties of the restricted Boltzmann machine learning, and moreover important theoretical basis to build simplified deep networks.

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

Self-Similar Random Process and Chaotic Behavior In Serrated Flow of High Entropy Alloys

PubMed Central

Chen, Shuying; Yu, Liping; Ren, Jingli; Xie, Xie; Li, Xueping; Xu, Ying; Zhao, Guangfeng; Li, Peizhen; Yang, Fuqian; Ren, Yang; Liaw, Peter K.

2016-01-01

The statistical and dynamic analyses of the serrated-flow behavior in the nanoindentation of a high-entropy alloy, Al0.5CoCrCuFeNi, at various holding times and temperatures, are performed to reveal the hidden order associated with the seemingly-irregular intermittent flow. Two distinct types of dynamics are identified in the high-entropy alloy, which are based on the chaotic time-series, approximate entropy, fractal dimension, and Hurst exponent. The dynamic plastic behavior at both room temperature and 200 °C exhibits a positive Lyapunov exponent, suggesting that the underlying dynamics is chaotic. The fractal dimension of the indentation depth increases with the increase of temperature, and there is an inflection at the holding time of 10 s at the same temperature. A large fractal dimension suggests the concurrent nucleation of a large number of slip bands. In particular, for the indentation with the holding time of 10 s at room temperature, the slip process evolves as a self-similar random process with a weak negative correlation similar to a random walk. PMID:27435922

Self-similar random process and chaotic behavior in serrated flow of high entropy alloys

DOE PAGES

Chen, Shuying; Yu, Liping; Ren, Jingli; ...

2016-07-20

Here, the statistical and dynamic analyses of the serrated-flow behavior in the nanoindentation of a high-entropy alloy, Al 0.5CoCrCuFeNi, at various holding times and temperatures, are performed to reveal the hidden order associated with the seemingly-irregular intermittent flow. Two distinct types of dynamics are identified in the high-entropy alloy, which are based on the chaotic time-series, approximate entropy, fractal dimension, and Hurst exponent. The dynamic plastic behavior at both room temperature and 200 °C exhibits a positive Lyapunov exponent, suggesting that the underlying dynamics is chaotic. The fractal dimension of the indentation depth increases with the increase of temperature, andmore » there is an inflection at the holding time of 10 s at the same temperature. A large fractal dimension suggests the concurrent nucleation of a large number of slip bands. In particular, for the indentation with the holding time of 10 s at room temperature, the slip process evolves as a self-similar random process with a weak negative correlation similar to a random walk.« less

Self-Similar Random Process and Chaotic Behavior In Serrated Flow of High Entropy Alloys.

PubMed

Chen, Shuying; Yu, Liping; Ren, Jingli; Xie, Xie; Li, Xueping; Xu, Ying; Zhao, Guangfeng; Li, Peizhen; Yang, Fuqian; Ren, Yang; Liaw, Peter K

2016-07-20

The statistical and dynamic analyses of the serrated-flow behavior in the nanoindentation of a high-entropy alloy, Al0.5CoCrCuFeNi, at various holding times and temperatures, are performed to reveal the hidden order associated with the seemingly-irregular intermittent flow. Two distinct types of dynamics are identified in the high-entropy alloy, which are based on the chaotic time-series, approximate entropy, fractal dimension, and Hurst exponent. The dynamic plastic behavior at both room temperature and 200 °C exhibits a positive Lyapunov exponent, suggesting that the underlying dynamics is chaotic. The fractal dimension of the indentation depth increases with the increase of temperature, and there is an inflection at the holding time of 10 s at the same temperature. A large fractal dimension suggests the concurrent nucleation of a large number of slip bands. In particular, for the indentation with the holding time of 10 s at room temperature, the slip process evolves as a self-similar random process with a weak negative correlation similar to a random walk.

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.

Feminist Collaboratives and Intercultural Inquiry: Constructing an Alternative to the (Not So) Hidden Logics and Practices of University Outreach and Microlending

ERIC Educational Resources Information Center

Clifton, Jennifer

2014-01-01

In an era of globalization, public-private partnerships often tip too easily toward privatization, where global processes of consumption, production, and migration complicate the conditions and consequences of engagement in public life. Like the logic of service, the logic of activist capitalism underlying social entrepreneurship and microlending…

Evaluation of extra virgin olive oil stability by artificial neural network.

PubMed

Silva, Simone Faria; Anjos, Carlos Alberto Rodrigues; Cavalcanti, Rodrigo Nunes; Celeghini, Renata Maria dos Santos

2015-07-15

The stability of extra virgin olive oil in polyethylene terephthalate bottles and tinplate cans stored for 6 months under dark and light conditions was evaluated. The following analyses were carried out: free fatty acids, peroxide value, specific extinction at 232 and 270 nm, chlorophyll, L(∗)C(∗)h color, total phenolic compounds, tocopherols and squalene. The physicochemical changes were evaluated by artificial neural network (ANN) modeling with respect to light exposure conditions and packaging material. The optimized ANN structure consists of 11 input neurons, 18 hidden neurons and 5 output neurons using hyperbolic tangent and softmax activation functions in hidden and output layers, respectively. The five output neurons correspond to five possible classifications according to packaging material (PET amber, PET transparent and tinplate can) and light exposure (dark and light storage). The predicted physicochemical changes agreed very well with the experimental data showing high classification accuracy for test (>90%) and training set (>85). Sensitivity analysis showed that free fatty acid content, peroxide value, L(∗)Cab(∗)hab(∗) color parameters, tocopherol and chlorophyll contents were the physicochemical attributes with the most discriminative power. Copyright © 2015 Elsevier Ltd. All rights reserved.

Hidden phase in parent Fe-pnictide superconductors

NASA Astrophysics Data System (ADS)

Ali, Khadiza; Adhikary, Ganesh; Thakur, Sangeeta; Patil, Swapnil; Mahatha, Sanjoy K.; Thamizhavel, A.; De Ninno, Giovanni; Moras, Paolo; Sheverdyaeva, Polina M.; Carbone, Carlo; Petaccia, Luca; Maiti, Kalobaran

2018-02-01

We investigate the origin of exoticity in Fe-based systems via studying the fermiology of CaFe2As2 employing angle-resolved photoemission spectroscopy. While the Fermi surfaces (FSs) at 200 K and 31 K are observed to exhibit two-dimensional and three-dimensional (3D) topology, respectively, the FSs at intermediate temperatures reveal the emergence of the 3D topology at a temperature much lower than the structural and magnetic phase transition temperature (170 K, for the sample under scrutiny). This leads to the conclusion that the evolution of FS topology is not directly driven by the structural transition. In addition, we discover the existence in ambient conditions of energy bands related to the cT phase. These bands are distinctly resolved in the high-photon energy spectra exhibiting strong Fe 3 d character. They gradually move to higher binding energies due to thermal compression with cooling, leading to the emergence of 3D topology in the Fermi surface. These results reveal the so-far hidden existence of a cT phase under ambient conditions, which is argued to lead to quantum fluctuations responsible for the exotic electronic properties in Fe-pnictide superconductors.

Controlling the metal-to-insulator relaxation of the metastable hidden quantum state in 1T-TaS2.

PubMed

Vaskivskyi, Igor; Gospodaric, Jan; Brazovskii, Serguei; Svetin, Damjan; Sutar, Petra; Goreshnik, Evgeny; Mihailovic, Ian A; Mertelj, Tomaz; Mihailovic, Dragan

2015-07-01

Controllable switching between metastable macroscopic quantum states under nonequilibrium conditions induced either by light or with an external electric field is rapidly becoming of great fundamental interest. We investigate the relaxation properties of a "hidden" (H) charge density wave (CDW) state in thin single crystals of the layered dichalcogenide 1T-TaS2, which can be reached by either a single 35-fs optical laser pulse or an ~30-ps electrical pulse. From measurements of the temperature dependence of the resistivity under different excitation conditions, we find that the metallic H state relaxes to the insulating Mott ground state through a sequence of intermediate metastable states via discrete jumps over a "Devil's staircase." In between the discrete steps, an underlying glassy relaxation process is observed, which arises because of reciprocal-space commensurability frustration between the CDW and the underlying lattice. We show that the metastable state relaxation rate may be externally stabilized by substrate strain, thus opening the way to the design of nonvolatile ultrafast high-temperature memory devices based on switching between CDW states with large intrinsic differences in electrical resistance.

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.

Hydrologic conditions and hazards in the Kennicott River basin, Wrangell-St. Elias National Park Preserve, Alaska

USGS Publications Warehouse

Rickman, R.L.; Rosenkrans, D.S.

1997-01-01

McCarthy, Alaska, is on the Kennicott River, about 1 mile from the terminus of Kennicott Glacier in the Wrangell-St. Elias National Park and Preserve. Most visitors to McCarthy and the park cross the West Fork Kennicott River using a hand-pulled tram and cross the East Fork Kennicott River on a temporary footbridge. Outburst floods from glacier-dammed lakes result in channel erosion, aggradation, and migration of the Kennicott River, which disrupt transportation links, destroy property, and threaten life. Hidden Creek Lake, the largest of six glacier-dammed lakes in the Kennicott River Basin, has annual outbursts that cause the largest floods on the Kennicott River. Outbursts from Hidden Creek Lake occur from early fall to mid-summer, and lake levels at the onset of the outbursts have declined between 1909 and 1995. Criteria for impending outbursts for Hidden Creek Lake include lake stage near or above 3,000 to 3,020 feet, stationary or declining lake stage, evidence of recent calving of large ice blocks from the ice margin, slush ice and small icebergs stranded on the lakeshore, and fresh fractures in the ice-margin region. The lower Kennicott Glacier has thinned and retreated since about 1860. The East and West Fork Kennicott River channels migrated in response to changes in the lower Kennicott Glacier. The largest channel changes occur during outburst floods from Hidden Creek Lake, whereas channel changes from the other glacier-dammed lake outbursts are small. Each year, the West Fork Kennicott River conveys a larger percentage of the Kennicott Glacier drainage than it did the previous year. Outburst floods on the Kennicott River cause the river stage to rise over a period of several hours. Smaller spike peaks have a very rapid stage rise. Potential flood magnitude was estimated by combining known maximum discharges from Hidden Creek Lake and Lake Erie outburst floods with a theoretical large regional flood. Flood hazard areas at the transportation corridor were delineated, and possible future geomorphological changes were hypothesized. McCarthy, Alaska, is on the Kennicott River, about 1 mile from the terminus of Kennicott Glacier in the Wrangell-St. Elias National Park and Preserve. Most visitors to McCarthy and the park cross the West Fork Kennicott River using a hand-pulled tram and cross the East Fork Kennicott River on a temporary footbridge. Outburst floods from glacier-dammed lakes result in channel erosion, aggradation, and migration of the Kennicott River, which disrupt transportation links, destroy property, and threaten life. Hidden Creek Lake, the largest of six glacier-dammed lakes in the Kennicott River Basin, has annual outbursts that cause the largest floods on the Kennicott River. Outbursts from Hidden Creek Lake occur from early fall to mid-summer, and lake levels at the onset of the outbursts have declined between 1909 and 1995. Criteria for impending outbursts for Hidden Creek Lake include lake stage near or above 3,000 to 3,020 feet, stationary or declining lake stage, evidence of recent calving of large ice blocks from the ice margin, slush ice and small icebergs stranded on the lakeshore, and fresh fractures in the ice-margin region. The lower Kennicott Glacier has thinned and retreated since about 1860. The East and West Fork Kennicott River channels migrated in response to changes in the lower Kennicott Glacier. The largest channel changes occur during outburst floods from Hidden Creek Lake, whereas channel changes from the other glacier-dammed lake outbursts are small. Each year, the West Fork Kennicott River conveys a larger percentage of the Kennicott Glacier drainage than it did the previous year. Outburst floods on the Kennicott River cause the river stage to rise over a period of several hours. Smaller spike peaks have a very rapid stage rise. Potential flood magnitude was estimated by combining known maximum discharges from Hidden Creek Lake and Lake Erie outburst floods with

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

NASA Astrophysics Data System (ADS)

Schoess, Jeffrey N.; Seifert, Greg

1998-07-01

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

Smart fastener for KC-135 structural integrity monitoring

NASA Astrophysics Data System (ADS)

Schoess, Jeffrey N.; Seifert, Greg

1997-06-01

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

A study on the real-time reliability of on-board equipment of train control system

NASA Astrophysics Data System (ADS)

Zhang, Yong; Li, Shiwei

2018-05-01

Real-time reliability evaluation is conducive to establishing a condition based maintenance system for the purpose of guaranteeing continuous train operation. According to the inherent characteristics of the on-board equipment, the connotation of reliability evaluation of on-board equipment is defined and the evaluation index of real-time reliability is provided in this paper. From the perspective of methodology and practical application, the real-time reliability of the on-board equipment is discussed in detail, and the method of evaluating the realtime reliability of on-board equipment at component level based on Hidden Markov Model (HMM) is proposed. In this method the performance degradation data is used directly to realize the accurate perception of the hidden state transition process of on-board equipment, which can achieve a better description of the real-time reliability of the equipment.

Multistability and hidden attractors in an impulsive Goodwin oscillator with time delay

NASA Astrophysics Data System (ADS)

Zhusubaliyev, Z. T.; Mosekilde, E.; Churilov, A. N.; Medvedev, A.

2015-07-01

The release of luteinizing hormone (LH) is driven by intermittent bursts of activity in the hypothalamic nerve centers of the brain. Luteinizing hormone again stimulates release of the male sex hormone testosterone (Te) and, via the circulating concentration of Te, the hypothalamic nerve centers are subject to a negative feedback regulation that is capable of modifying the intermittent bursts into more regular pulse trains. Bifurcation analysis of a hybrid model that attempts to integrate the intermittent bursting activity with a continuous hormone secretion has recently demonstrated a number of interesting nonlinear dynamic phenomena, including bistability and deterministic chaos. The present paper focuses on the additional complexity that arises when the time delay in the continuous part of the model exceeds the typical bursting interval of the feedback. Under these conditions, the hybrid model is capable of displaying quasiperiodicity and border collisions as well as multistability and hidden attractors.

Camouflaging in Digital Image for Secure Communication

NASA Astrophysics Data System (ADS)

Jindal, B.; Singh, A. P.

2013-06-01

The present paper reports on a new type of camouflaging in digital image for hiding crypto-data using moderate bit alteration in the pixel. In the proposed method, cryptography is combined with steganography to provide a two layer security to the hidden data. The novelty of the algorithm proposed in the present work lies in the fact that the information about hidden bit is reflected by parity condition in one part of the image pixel. The remaining part of the image pixel is used to perform local pixel adjustment to improve the visual perception of the cover image. In order to examine the effectiveness of the proposed method, image quality measuring parameters are computed. In addition to this, security analysis is also carried by comparing the histograms of cover and stego images. This scheme provides a higher security as well as robustness to intentional as well as unintentional attacks.

[Learning to solve a spatial task in a water maze in aggressive and submissive mice].

PubMed

Dubrovina, N I; Tomilenko, R A

2007-01-01

Learning and retention of the spatial memory were studied in mice with alternative under conditions of various experimental protocols. Visible and hidden platform acquisition in a simple model of the water maze was similarly fast both in aggressive and submissive mice, but extinction differed. Retention of the platform location preference persisted in aggressive mice in four testing trials. In submissive mice, extiction of the spatial memory was accompanied with a prolongation of search with parallel production of episodes of "passive drift". Differences in spatial learning between aggressive and submissive mice were revealed in a water maze complicated with partitions. In this case, aggressors were able to learn the position of a hidden platform (in contrast to submissive mice with the dominant response of "passive drift"). During testing the response, aggressive mice longer retained the spatial preference without extinction.

A hidden Markov model approach to neuron firing patterns.

PubMed Central

Camproux, A C; Saunier, F; Chouvet, G; Thalabard, J C; Thomas, G

1996-01-01

Analysis and characterization of neuronal discharge patterns are of interest to neurophysiologists and neuropharmacologists. In this paper we present a hidden Markov model approach to modeling single neuron electrical activity. Basically the model assumes that each interspike interval corresponds to one of several possible states of the neuron. Fitting the model to experimental series of interspike intervals by maximum likelihood allows estimation of the number of possible underlying neuron states, the probability density functions of interspike intervals corresponding to each state, and the transition probabilities between states. We present an application to the analysis of recordings of a locus coeruleus neuron under three pharmacological conditions. The model distinguishes two states during halothane anesthesia and during recovery from halothane anesthesia, and four states after administration of clonidine. The transition probabilities yield additional insights into the mechanisms of neuron firing. Images FIGURE 3 PMID:8913581

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.

Resisting persuasion by the skin of one's teeth: the hidden success of resisted persuasive messages.

PubMed

Tormala, Zakary L; Clarkson, Joshua J; Petty, Richard E

2006-09-01

Recent research has suggested that when people resist persuasion they can perceive this resistance and, under specifiable conditions, become more certain of their initial attitudes (e.g., Z. L. Tormala & R. E. Petty, 2002). Within the same metacognitive framework, the present research provides evidence for the opposite phenomenon--that is, when people resist persuasion, they sometimes become less certain of their initial attitudes. Four experiments demonstrate that when people perceive that they have done a poor job resisting persuasion (e.g., they believe they generated weak arguments against a persuasive message), they lose attitude certainty, show reduced attitude-behavioral intention correspondence, and become more vulnerable to subsequent persuasive attacks. These findings suggest that resisted persuasive attacks can sometimes have a hidden yet important success by reducing the strength of the target attitude. ((c) 2006 APA, all rights reserved).

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.

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.

Data characteristic analysis of air conditioning load based on fast Fourier transform

NASA Astrophysics Data System (ADS)

Li, Min; Zhang, Yanchi; Xie, Da

2018-04-01

With the development of economy and the improvement of people's living standards, air conditioning equipment is more and more popular. The influence of air conditioning load for power grid is becoming more and more serious. In this context it is necessary to study the characteristics of air conditioning load. This paper analyzes the data of air conditioning power consumption in an office building. The data is used for Fast Fourier Transform by data analysis software. Then a series of maps are drawn for the transformed data. The characteristics of each map were analyzed separately. The hidden rules of these data are mined from the angle of frequency domain. And these rules are hard to find in the time domain.

Experimental Design for the Evaluation of Detection Techniques of Hidden Corrosion Beneath the Thermal Protective System of the Space Shuttle Orbiter

NASA Technical Reports Server (NTRS)

Kammerer, Catherine C.; Jacoby, Joseph A.; Lomness, Janice K.; Hintze, Paul E.; Russell, Richard W.

2007-01-01

The United States Space Operational Space Shuttle Fleet Consists of three shuttles with an average age of 19.7 years. Shuttles are exposed to corrosive conditions while undergoing final closeout for missions at the launch pad and extreme conditions during ascent, orbit, and descent that may accelerate the corrosion process. Structural corrosion under TPS could progress undetected (without tile removal) and eventually result in reduction in structural capability sufficient to create negative margins of . safety and ultimate loss of local structural capability.

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.

Evidence that hidden hearing loss underlies amplitude modulation encoding deficits in individuals with and without tinnitus.

PubMed

Paul, Brandon T; Bruce, Ian C; Roberts, Larry E

2017-02-01

Damage to auditory nerve fibers that expresses with suprathreshold sounds but is hidden from the audiogram has been proposed to underlie deficits in temporal coding ability observed among individuals with otherwise normal hearing, and to be present in individuals experiencing chronic tinnitus with clinically normal audiograms. We tested whether these individuals may have hidden synaptic losses on auditory nerve fibers with low spontaneous rates of firing (low-SR fibers) that are important for coding suprathreshold sounds in noise while high-SR fibers determining threshold responses in quiet remain relatively unaffected. Tinnitus and control subjects were required to detect the presence of amplitude modulation (AM) in a 5 kHz, suprathreshold tone (a frequency in the tinnitus frequency region of the tinnitus subjects, whose audiometric thresholds were normal to 12 kHz). The AM tone was embedded within background noise intended to degrade the contribution of high-SR fibers, such that AM coding was preferentially reliant on low-SR fibers. We also recorded by electroencephalography the "envelope following response" (EFR, generated in the auditory midbrain) to a 5 kHz, 85 Hz AM tone presented in the same background noise, and also in quiet (both low-SR and high-SR fibers contributing to AM coding in the latter condition). Control subjects with EFRs that were comparatively resistant to the addition of background noise had better AM detection thresholds than controls whose EFRs were more affected by noise. Simulated auditory nerve responses to our stimulus conditions using a well-established peripheral model suggested that low-SR fibers were better preserved in the former cases. Tinnitus subjects had worse AM detection thresholds and reduced EFRs overall compared to controls. Simulated auditory nerve responses found that in addition to severe low-SR fiber loss, a degree of high-SR fiber loss that would not be expected to affect audiometric thresholds was needed to explain the results in tinnitus subjects. The results indicate that hidden hearing loss could be sufficient to account for impaired temporal coding in individuals with normal audiograms as well as for cases of tinnitus without audiometric hearing loss. Copyright © 2016 Elsevier B.V. All rights reserved.

Opto-digital spectrum encryption by using Baker mapping and gyrator transform

NASA Astrophysics Data System (ADS)

Chen, Hang; Zhao, Jiguang; Liu, Zhengjun; Du, Xiaoping

2015-03-01

A concept of spectrum information hidden technology is proposed in this paper. We present an optical encryption algorithm for hiding both the spatial and spectrum information by using the Baker mapping in gyrator transform domains. The Baker mapping is introduced for scrambling the every single band of the hyperspectral image before adding the random phase functions. Subsequently, three thin cylinder lenses are controlled by PC for implementing the gyrator transform. The amplitude and phase information in the output plane can be regarded as the encrypted information and main key. Some numerical simulations are made to test the validity and capability of the proposed encryption algorithm.

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.

Design of the Indian NCA study (Indian national collaboration on AIDS): a cluster randomized trial to evaluate the effectiveness of integrated care centers to improve HIV outcomes among men who have sex with men and persons who inject drugs in India.

PubMed

Solomon, Sunil S; Lucas, Gregory M; Celentano, David D; McFall, Allison M; Ogburn, Elizabeth; Moulton, Lawrence H; Srikrishnan, Aylur K; Kumar, M Suresh; Anand, Santhanam; Solomon, Suniti; Mehta, Shruti H

2016-11-14

Globally, men who have sex with men and people who inject drugs remain disproportionately affected by HIV, but they have not been the focus of prevention and treatment interventions in many resource-limited settings. This cluster-randomized trial (conducted from June 2012 to June 2017), evaluates whether single-venue, integrated delivery of core HIV services to vulnerable high-risk populations improves service utilization and consequently, HIV testing and other outcomes along the HIV care continuum. Core services include: HIV counseling and testing, information, education and communication, condom distribution, needle and syringe exchange programs, opioid agonist therapy, management of sexually transmitted infections, tuberculosis screening, diagnosis, and treatment, and antiretroviral therapy. Stratified restricted randomization was used to allocate 22 Indian cities (10 men who have sex with men and 12 people who inject drugs sites) at a 1:1 ratio to either the intervention or control condition. Integrated care centers were scaled-up and implemented in the 11 intervention cities and outcomes will be assessed by pre- and post-intervention surveys at intervention and control sites. As men who have sex with men and people who inject drugs are hidden populations, with no sampling frame, respondent-driven sampling will be used to accrue samples for the two independent cross-sectional surveys. For an AIDS-free generation to be realized, prevention, care and treatment services need to reach all populations at risk for HIV infection. There is a clear gap in access to services among men who have sex with men and people who inject drugs. Trials need to be designed to optimize utilization of services in these populations. ClinicalTrials.gov Identifier: NCT01686750 Date of Registration: September 13, 2012.

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.

Filling of a Poisson trap by a population of random intermittent searchers.

PubMed

Bressloff, Paul C; Newby, Jay M

2012-03-01

We extend the continuum theory of random intermittent search processes to the case of N independent searchers looking to deliver cargo to a single hidden target located somewhere on a semi-infinite track. Each searcher randomly switches between a stationary state and either a leftward or rightward constant velocity state. We assume that all of the particles start at one end of the track and realize sample trajectories independently generated from the same underlying stochastic process. The hidden target is treated as a partially absorbing trap in which a particle can only detect the target and deliver its cargo if it is stationary and within range of the target; the particle is removed from the system after delivering its cargo. As a further generalization of previous models, we assume that up to n successive particles can find the target and deliver its cargo. Assuming that the rate of target detection scales as 1/N, we show that there exists a well-defined mean-field limit N→∞, in which the stochastic model reduces to a deterministic system of linear reaction-hyperbolic equations for the concentrations of particles in each of the internal states. These equations decouple from the stochastic process associated with filling the target with cargo. The latter can be modeled as a Poisson process in which the time-dependent rate of filling λ(t) depends on the concentration of stationary particles within the target domain. Hence, we refer to the target as a Poisson trap. We analyze the efficiency of filling the Poisson trap with n particles in terms of the waiting time density f(n)(t). The latter is determined by the integrated Poisson rate μ(t)=∫(0)(t)λ(s)ds, which in turn depends on the solution to the reaction-hyperbolic equations. We obtain an approximate solution for the particle concentrations by reducing the system of reaction-hyperbolic equations to a scalar advection-diffusion equation using a quasisteady-state analysis. We compare our analytical results for the mean-field model with Monte Carlo simulations for finite N. We thus determine how the mean first passage time (MFPT) for filling the target depends on N and n.

Analysis of informational redundancy in the protein-assembling machinery

NASA Astrophysics Data System (ADS)

Berkovich, Simon

2004-03-01

Entropy analysis of the DNA structure does not reveal a significant departure from randomness indicating lack of informational redundancy. This signifies the absence of a hidden meaning in the genome text and supports the 'barcode' interpretation of DNA given in [1]. Lack of informational redundancy is a characteristic property of an identification label rather than of a message of instructions. Yet randomness of DNA has to induce non-random structures of the proteins. Protein synthesis is a two-step process: transcription into RNA with gene splicing and formation a structure of amino acids. Entropy estimations, performed by A. Djebbari, show typical values of redundancy of the biomolecules along these pathways: DNA gene 4proteins 15-40in gene expression, the RNA copy carries the same information as the original DNA template. Randomness is essentially eliminated only at the step of the protein creation by a degenerate code. According to [1], the significance of the substitution of U for T with a subsequent gene splicing is that these transformations result in a different pattern of RNA oscillations, so the vital DNA communications are protected against extraneous noise coming from the protein making activities. 1. S. Berkovich, "On the 'barcode' functionality of DNA, or the Phenomenon of Life in the Physical Universe", Dorrance Publishing Co., Pittsburgh, 2003

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

Different Social Motives in the Gestural Communication of Chimpanzees and Human Children

ERIC Educational Resources Information Center

Bullinger, Anke F.; Zimmermann, Felizitas; Kaminski, Juliane; Tomasello, Michael

2011-01-01

Both chimpanzees and human infants use the pointing gesture with human adults, but it is not clear if they are doing so for the same social motives. In two studies, we presented chimpanzees and human 25-month-olds with the opportunity to point for a hidden tool (in the presence of a non-functional distractor). In one condition it was clear that…

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.

Adaptive hidden Markov model-based online learning framework for bearing faulty detection and performance degradation monitoring

NASA Astrophysics Data System (ADS)

Yu, Jianbo

2017-01-01

This study proposes an adaptive-learning-based method for machine faulty detection and health degradation monitoring. The kernel of the proposed method is an "evolving" model that uses an unsupervised online learning scheme, in which an adaptive hidden Markov model (AHMM) is used for online learning the dynamic health changes of machines in their full life. A statistical index is developed for recognizing the new health states in the machines. Those new health states are then described online by adding of new hidden states in AHMM. Furthermore, the health degradations in machines are quantified online by an AHMM-based health index (HI) that measures the similarity between two density distributions that describe the historic and current health states, respectively. When necessary, the proposed method characterizes the distinct operating modes of the machine and can learn online both abrupt as well as gradual health changes. Our method overcomes some drawbacks of the HIs (e.g., relatively low comprehensibility and applicability) based on fixed monitoring models constructed in the offline phase. Results from its application in a bearing life test reveal that the proposed method is effective in online detection and adaptive assessment of machine health degradation. This study provides a useful guide for developing a condition-based maintenance (CBM) system that uses an online learning method without considerable human intervention.

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.

The Hidden Curriculum in Distance Education: An Updated View.

ERIC Educational Resources Information Center

Anderson, Terry

2001-01-01

Addressing recent criticism of distance education, explores the distinctive hidden curriculum (supposed "real" agenda) of distance education, focusing on both its positive and negative expressions. Also offers an updated view of the hidden curriculum of traditional, campus-based education, grounded in an emerging worldwide context of broadening…

77 FR 8253 - Notice of Proposed Settlement Agreement and Opportunity for Public Comment: Hidden Lane Landfill...

Federal Register 2010, 2011, 2012, 2013, 2014

2012-02-14

... ENVIRONMENTAL PROTECTION AGENCY [FRL-9631-3] Notice of Proposed Settlement Agreement and Opportunity for Public Comment: Hidden Lane Landfill Superfund Site ACTION: Notice. SUMMARY: In accordance... (``DOJ'') on behalf of EPA, in connection with the Hidden Lane Landfill Superfund Site, Sterling, Loudoun...

Hidden Curriculum as One of Current Issue of Curriculum

ERIC Educational Resources Information Center

Alsubaie, Merfat Ayesh

2015-01-01

There are several issues in the education system, especially in the curriculum field that affect education. Hidden curriculum is one of current controversial curriculum issues. Many hidden curricular issues are the result of assumptions and expectations that are not formally communicated, established, or conveyed within the learning environment.…

Hidden Variable Theories and Quantum Nonlocality

ERIC Educational Resources Information Center

Boozer, A. D.

2009-01-01

We clarify the meaning of Bell's theorem and its implications for the construction of hidden variable theories by considering an example system consisting of two entangled spin-1/2 particles. Using this example, we present a simplified version of Bell's theorem and describe several hidden variable theories that agree with the predictions of…

Building Simple Hidden Markov Models. Classroom Notes

ERIC Educational Resources Information Center

Ching, Wai-Ki; Ng, Michael K.

2004-01-01

Hidden Markov models (HMMs) are widely used in bioinformatics, speech recognition and many other areas. This note presents HMMs via the framework of classical Markov chain models. A simple example is given to illustrate the model. An estimation method for the transition probabilities of the hidden states is also discussed.

Seuss's Butter Battle Book: Is There Hidden Harm?

ERIC Educational Resources Information Center

Van Cleaf, David W.; Martin, Rita J.

1986-01-01

Examines whether elementary school children relate to the "harmful hidden message" about nuclear war in Dr. Seuss's THE BUTTER BATTLE BOOK. After ascertaining the children's cognitive level, they participated in activities to find hidden meanings in stories, including Seuss's book. Students failed to identify the nuclear war message in…

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

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

Nagata, Koji

Malley discussed [Phys. Rev. A 69, 022118 (2004)] that all quantum observables in a hidden-variable model for quantum events must commute simultaneously. In this comment, we discuss that Malley's theorem is indeed valid for the hidden-variable theoretical assumptions, which were introduced by Kochen and Specker. However, we give an example that the local hidden-variable (LHV) model for quantum events preserves noncommutativity of quantum observables. It turns out that Malley's theorem is not related to the LHV model for quantum events, in general.

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

PubMed

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

2014-04-01

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

Using SINEs to probe ancient explosive speciation: "hidden" radiation of African cichlids?

PubMed

Terai, Yohey; Takahashi, Kazuhiko; Nishida, Mutsumi; Sato, Tetsu; Okada, Norihiro

2003-06-01

Cichlid fishes of the east African Great Lakes represent a paradigm of adaptive radiation. We conducted a phylogenetic analysis of cichlids including pan-African and west African species by using insertion patterns of short interspersed elements (SINEs) at orthologous loci. The monophyly of the east African cichlids was consistently supported by seven independent insertions of SINE sequences that are uniquely shared by these species. In addition, data from four other loci indicated that the genera Tilapia (pan-African) and Steatocranus (west African) are the closest relatives to east African cichlids. However, relationships among Tilapia, Steatocranus, and the east African clade were ambiguous because of incongruencies among topologies suggested by insertion patterns of SINEs at six other loci. One plausible explanation for this phenomenon is incomplete lineage sorting of alleles containing or missing a SINE insertion at these loci during ancestral speciation. Such incomplete sorting may have taken place earlier than 14 MYA, followed by random and stochastic fixation of the alleles in subsequent lineages. These observations prompted us to consider the possibility that cichlid speciation occurred at an accelerated rate during this period when the African Great Lakes did not exist. The SINE method could be useful for detecting ancient exclusive speciation events that tend to remain hidden during conventional sequence analyses because of accumulated point mutations.

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

Localization of Hidden Insulinomas with ⁶⁸Ga-DOTA-Exendin-4 PET/CT: A Pilot Study.

PubMed

Antwi, Kwadwo; Fani, Melpomeni; Nicolas, Guillaume; Rottenburger, Christof; Heye, Tobias; Reubi, Jean Claude; Gloor, Beat; Christ, Emanuel; Wild, Damian

2015-07-01

(111)In-DOTA-exendin-4 SPECT/CT has been shown to be highly efficient in the detection of insulinomas. We aimed at determining whether novel PET/CT imaging with [Nle(14),Lys(40)(Ahx-DOTA-(68)Ga)NH2]exendin-4 ((68)Ga-DOTA-exendin-4) is feasible and sensitive in detecting benign insulinomas. (68)Ga-DOTA-exendin-4 PET/CT and (111)In-DOTA-exendin-4 SPECT/CT were performed in a randomized cross-over order on 5 patients with endogenous hyperinsulinemic hypoglycemia. The gold standard for comparison was the histologic diagnosis after surgery. In 4 patients histologic diagnosis confirmed a benign insulinoma, whereas one patient refused surgery despite a positive (68)Ga-DOTA-exendin-4 PET/CT scan. In 4 of 5 patients, previously performed conventional imaging (CT or MR imaging) was not able to localize the insulinoma. (68)Ga-DOTA-exendin-4 PET/CT correctly identified the insulinoma in 4 of 4 patients, whereas (111)In-DOTA-exendin-4 SPECT/CT correctly identified the insulinoma in only 2 of 4 patients. These preliminary data suggest that the use of (68)Ga-DOTA-exendin-4 PET/CT in detecting hidden insulinomas is feasible. © 2015 by the Society of Nuclear Medicine and Molecular Imaging, Inc.

Challenges to Recruiting Population Representative Samples of Female Sex Workers in China Using Respondent Driven Sampling1

PubMed Central

Merli, M. Giovanna; Moody, James; Smith, Jeffrey; Li, Jing; Weir, Sharon; Chen, Xiangsheng

2014-01-01

We explore the network coverage of a sample of female sex workers (FSWs) in China recruited through Respondent Drive Sampling (RDS) as part of an effort to evaluate the claim of RDS of population representation with empirical data. We take advantage of unique information on the social networks of FSWs obtained from two overlapping studies --RDS and a venue-based sampling approach (PLACE) -- and use an exponential random graph modeling (ERGM) framework from local networks to construct a likely network from which our observed RDS sample is drawn. We then run recruitment chains over this simulated network to assess the assumption that the RDS chain referral process samples participants in proportion to their degree and the extent to which RDS satisfactorily covers certain parts of the network. We find evidence that, contrary to assumptions, RDS oversamples low degree nodes and geographically central areas of the network. Unlike previous evaluations of RDS which have explored the performance of RDS sampling chains on a non-hidden population, or the performance of simulated chains over previously mapped realistic social networks, our study provides a robust, empirically grounded evaluation of the performance of RDS chains on a real-world hidden population. PMID:24834869

Detecting 2LSB steganography using extended pairs of values analysis

NASA Astrophysics Data System (ADS)

Khalind, Omed; Aziz, Benjamin

2014-05-01

In this paper, we propose an extended pairs of values analysis to detect and estimate the amount of secret messages embedded with 2LSB replacement in digital images based on chi-square attack and regularity rate in pixel values. The detection process is separated from the estimation of the hidden message length, as it is the main requirement of any steganalysis method. Hence, the detection process acts as a discrete classifier, which classifies a given set of images into stego and clean classes. The method can accurately detect 2LSB replacement even when the message length is about 10% of the total capacity, it also reaches its best performance with an accuracy of higher than 0.96 and a true positive rate of more than 0.997 when the amount of data are 20% to 100% of the total capacity. However, the method puts no assumptions neither on the image nor the secret message, as it tested with two sets of 3000 images, compressed and uncompressed, embedded with a random message for each case. This method of detection could also be used as an automated tool to analyse a bulk of images for hidden contents, which could be used by digital forensics analysts in their investigation process.

A behavioural analysis of spatial localization following electrolytic, kainate- or colchicine-induced damage to the hippocampal formation in the rat.

PubMed

Sutherland, R J; Whishaw, I Q; Kolb, B

1983-02-01

This experiment examines the notion that in the rat the hippocampal formation is an essential structure in the neurological representation of spatial abilities. Spatial localization by rats with different types of hippocampal damage, including bilateral electrolytic lesions, unilateral and bilateral kainic acid-induced CA3-CA4 lesions, and unilateral and bilateral colchicine-induced dentate gyrus lesions, was compared with vehicle-injected and normal control groups in the Morris water task. The task required the rats to escape from cold water by finding a submerged and hidden platform located at a fixed place within the room. The start point was varied randomly from trial to trial and there were no local cues available to indicate the position of the hidden platform. After training, the platform was moved. Escape latencies and the initial swimming headings revealed that all lesion groups, except the unilateral CA3-damaged group, were impaired at finding the platform: the dentate-damaged rats exhibited the greatest deficit. When the platform was moved the control rats swam mainly in the part of the pool that had previously contained the platform and, on finding it in the new location, they showed a marked dishabituation of rearing. None of the bilateral lesion groups showed these effects.

Adaptive sampling in research on risk-related behaviors.

PubMed

Thompson, Steven K; Collins, Linda M

2002-11-01

This article introduces adaptive sampling designs to substance use researchers. Adaptive sampling is particularly useful when the population of interest is rare, unevenly distributed, hidden, or hard to reach. Examples of such populations are injection drug users, individuals at high risk for HIV/AIDS, and young adolescents who are nicotine dependent. In conventional sampling, the sampling design is based entirely on a priori information, and is fixed before the study begins. By contrast, in adaptive sampling, the sampling design adapts based on observations made during the survey; for example, drug users may be asked to refer other drug users to the researcher. In the present article several adaptive sampling designs are discussed. Link-tracing designs such as snowball sampling, random walk methods, and network sampling are described, along with adaptive allocation and adaptive cluster sampling. It is stressed that special estimation procedures taking the sampling design into account are needed when adaptive sampling has been used. These procedures yield estimates that are considerably better than conventional estimates. For rare and clustered populations adaptive designs can give substantial gains in efficiency over conventional designs, and for hidden populations link-tracing and other adaptive procedures may provide the only practical way to obtain a sample large enough for the study objectives.

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.

Beyond Captions: Linking Figures with Abstract Sentences in Biomedical Articles

PubMed Central

Bockhorst, Joseph P.; Conroy, John M.; Agarwal, Shashank; O’Leary, Dianne P.; Yu, Hong

2012-01-01

Although figures in scientific articles have high information content and concisely communicate many key research findings, they are currently under utilized by literature search and retrieval systems. Many systems ignore figures, and those that do not typically only consider caption text. This study describes and evaluates a fully automated approach for associating figures in the body of a biomedical article with sentences in its abstract. We use supervised methods to learn probabilistic language models, hidden Markov models, and conditional random fields for predicting associations between abstract sentences and figures. Three kinds of evidence are used: text in abstract sentences and figures, relative positions of sentences and figures, and the patterns of sentence/figure associations across an article. Each information source is shown to have predictive value, and models that use all kinds of evidence are more accurate than models that do not. Our most accurate method has an -score of 69% on a cross-validation experiment, is competitive with the accuracy of human experts, has significantly better predictive accuracy than state-of-the-art methods and enables users to access figures associated with an abstract sentence with an average of 1.82 fewer mouse clicks. A user evaluation shows that human users find our system beneficial. The system is available at http://FigureItOut.askHERMES.org. PMID:22815711

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

Smart Annotation of Cyclic Data Using Hierarchical Hidden Markov Models.

PubMed

Martindale, Christine F; Hoenig, Florian; Strohrmann, Christina; Eskofier, Bjoern M

2017-10-13

Cyclic signals are an intrinsic part of daily life, such as human motion and heart activity. The detailed analysis of them is important for clinical applications such as pathological gait analysis and for sports applications such as performance analysis. Labeled training data for algorithms that analyze these cyclic data come at a high annotation cost due to only limited annotations available under laboratory conditions or requiring manual segmentation of the data under less restricted conditions. This paper presents a smart annotation method that reduces this cost of labeling for sensor-based data, which is applicable to data collected outside of strict laboratory conditions. The method uses semi-supervised learning of sections of cyclic data with a known cycle number. A hierarchical hidden Markov model (hHMM) is used, achieving a mean absolute error of 0.041 ± 0.020 s relative to a manually-annotated reference. The resulting model was also used to simultaneously segment and classify continuous, 'in the wild' data, demonstrating the applicability of using hHMM, trained on limited data sections, to label a complete dataset. This technique achieved comparable results to its fully-supervised equivalent. Our semi-supervised method has the significant advantage of reduced annotation cost. Furthermore, it reduces the opportunity for human error in the labeling process normally required for training of segmentation algorithms. It also lowers the annotation cost of training a model capable of continuous monitoring of cycle characteristics such as those employed to analyze the progress of movement disorders or analysis of running technique.

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)

Driving style recognition method using braking characteristics based on hidden Markov model

PubMed Central

Wu, Chaozhong; Lyu, Nengchao; Huang, Zhen

2017-01-01

Since the advantage of hidden Markov model in dealing with time series data and for the sake of identifying driving style, three driving style (aggressive, moderate and mild) are modeled reasonably through hidden Markov model based on driver braking characteristics to achieve efficient driving style. Firstly, braking impulse and the maximum braking unit area of vacuum booster within a certain time are collected from braking operation, and then general braking and emergency braking characteristics are extracted to code the braking characteristics. Secondly, the braking behavior observation sequence is used to describe the initial parameters of hidden Markov model, and the generation of the hidden Markov model for differentiating and an observation sequence which is trained and judged by the driving style is introduced. Thirdly, the maximum likelihood logarithm could be implied from the observable parameters. The recognition accuracy of algorithm is verified through experiments and two common pattern recognition algorithms. The results showed that the driving style discrimination based on hidden Markov model algorithm could realize effective discriminant of driving style. PMID:28837580

A possible loophole in the theorem of Bell.

PubMed

Hess, K; Philipp, W

2001-12-04

The celebrated inequalities of Bell are based on the assumption that local hidden parameters exist. When combined with conflicting experimental results, these inequalities appear to prove that local hidden parameters cannot exist. This contradiction suggests to many that only instantaneous action at a distance can explain the Einstein, Podolsky, and Rosen type of experiments. We show that, in addition to the assumption that hidden parameters exist, Bell tacitly makes a variety of other assumptions that contribute to his being able to obtain the desired contradiction. For instance, Bell assumes that the hidden parameters do not depend on time and are governed by a single probability measure independent of the analyzer settings. We argue that the exclusion of time has neither a physical nor a mathematical basis but is based on Bell's translation of the concept of Einstein locality into the language of probability theory. Our additional set of local hidden variables includes time-like correlated parameters and a generalized probability density. We prove that our extended space of local hidden variables does not permit Bell-type proofs to go forward.

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.

The Detection Method of Fire Abnormal Based on Directional Drilling in Complex Conditions of Mine

NASA Astrophysics Data System (ADS)

Huijun, Duan; Shijun, Hao; Jie, Feng

2018-06-01

In the light of more and more urgent hidden fire abnormal detection problem in complex conditions of mine, a method which is used directional drilling technology is put forward. The method can avoid the obstacles in mine, and complete the fire abnormal detection. This paper based on analyzing the trajectory control of directional drilling, measurement while drilling and the characteristic of open branch process, the project of the directional drilling is formulated combination with a complex condition mine, and the detection of fire abnormal is implemented. This method can provide technical support for fire prevention, which also can provide a new way for fire anomaly detection in the similar mine.

Repair, Evaluation, Maintenance, and Rehabilitation Research Program. Inspection of the Engineering Condition of Underwater Concrete Structures.

DTIC Science & Technology

1989-04-01

corrosion of rebar Spalling of concrete surface IIl Detect hidden and beginning Location of rebar damage Beginning corrosion of rebar ...honeycombs MD Moderate defects: spalling of concrete minor corrosion of exposed rebar rust stains along rebar with or without visible cracking softening of...velocity. . Replenishment of the attacking chemical hgents. h. Higher temperatures. i. Corrosion of reinforcing steel. 46. Note that concrete which

Cluster-based adaptive power control protocol using Hidden Markov Model for Wireless Sensor Networks

NASA Astrophysics Data System (ADS)

Vinutha, C. B.; Nalini, N.; Nagaraja, M.

2017-06-01

This paper presents strategies for an efficient and dynamic transmission power control technique, in order to reduce packet drop and hence energy consumption of power-hungry sensor nodes operated in highly non-linear channel conditions of Wireless Sensor Networks. Besides, we also focus to prolong network lifetime and scalability by designing cluster-based network structure. Specifically we consider weight-based clustering approach wherein, minimum significant node is chosen as Cluster Head (CH) which is computed stemmed from the factors distance, remaining residual battery power and received signal strength (RSS). Further, transmission power control schemes to fit into dynamic channel conditions are meticulously implemented using Hidden Markov Model (HMM) where probability transition matrix is formulated based on the observed RSS measurements. Typically, CH estimates initial transmission power of its cluster members (CMs) from RSS using HMM and broadcast this value to its CMs for initialising their power value. Further, if CH finds that there are variations in link quality and RSS of the CMs, it again re-computes and optimises the transmission power level of the nodes using HMM to avoid packet loss due noise interference. We have demonstrated our simulation results to prove that our technique efficiently controls the power levels of sensing nodes to save significant quantity of energy for different sized network.

Resolution of Singularities Introduced by Hierarchical Structure in Deep Neural Networks.

PubMed

Nitta, Tohru

2017-10-01

We present a theoretical analysis of singular points of artificial deep neural networks, resulting in providing deep neural network models having no critical points introduced by a hierarchical structure. It is considered that such deep neural network models have good nature for gradient-based optimization. First, we show that there exist a large number of critical points introduced by a hierarchical structure in deep neural networks as straight lines, depending on the number of hidden layers and the number of hidden neurons. Second, we derive a sufficient condition for deep neural networks having no critical points introduced by a hierarchical structure, which can be applied to general deep neural networks. It is also shown that the existence of critical points introduced by a hierarchical structure is determined by the rank and the regularity of weight matrices for a specific class of deep neural networks. Finally, two kinds of implementation methods of the sufficient conditions to have no critical points are provided. One is a learning algorithm that can avoid critical points introduced by the hierarchical structure during learning (called avoidant learning algorithm). The other is a neural network that does not have some critical points introduced by the hierarchical structure as an inherent property (called avoidant neural network).

Understanding the ontogeny of foraging behaviour: insights from combining marine predator bio-logging with satellite-derived oceanography in hidden Markov models.

PubMed

Grecian, W James; Lane, Jude V; Michelot, Théo; Wade, Helen M; Hamer, Keith C

2018-06-01

The development of foraging strategies that enable juveniles to efficiently identify and exploit predictable habitat features is critical for survival and long-term fitness. In the marine environment, meso- and sub-mesoscale features such as oceanographic fronts offer a visible cue to enhanced foraging conditions, but how individuals learn to identify these features is a mystery. In this study, we investigate age-related differences in the fine-scale foraging behaviour of adult (aged ≥ 5 years) and immature (aged 2-4 years) northern gannets Morus bassanus Using high-resolution GPS-loggers, we reveal that adults have a much narrower foraging distribution than immature birds and much higher individual foraging site fidelity. By conditioning the transition probabilities of a hidden Markov model on satellite-derived measures of frontal activity, we then demonstrate that adults show a stronger response to frontal activity than immature birds, and are more likely to commence foraging behaviour as frontal intensity increases. Together, these results indicate that adult gannets are more proficient foragers than immatures, supporting the hypothesis that foraging specializations are learned during individual exploratory behaviour in early life. Such memory-based individual foraging strategies may also explain the extended period of immaturity observed in gannets and many other long-lived species. © 2018 The Authors.

Histogram equalization with Bayesian estimation for noise robust speech recognition.

PubMed

Suh, Youngjoo; Kim, Hoirin

2018-02-01

The histogram equalization approach is an efficient feature normalization technique for noise robust automatic speech recognition. However, it suffers from performance degradation when some fundamental conditions are not satisfied in the test environment. To remedy these limitations of the original histogram equalization methods, class-based histogram equalization approach has been proposed. Although this approach showed substantial performance improvement under noise environments, it still suffers from performance degradation due to the overfitting problem when test data are insufficient. To address this issue, the proposed histogram equalization technique employs the Bayesian estimation method in the test cumulative distribution function estimation. It was reported in a previous study conducted on the Aurora-4 task that the proposed approach provided substantial performance gains in speech recognition systems based on the acoustic modeling of the Gaussian mixture model-hidden Markov model. In this work, the proposed approach was examined in speech recognition systems with deep neural network-hidden Markov model (DNN-HMM), the current mainstream speech recognition approach where it also showed meaningful performance improvement over the conventional maximum likelihood estimation-based method. The fusion of the proposed features with the mel-frequency cepstral coefficients provided additional performance gains in DNN-HMM systems, which otherwise suffer from performance degradation in the clean test condition.

Adaptive Online Sequential ELM for Concept Drift Tackling

PubMed Central

Basaruddin, Chan

2016-01-01

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

Behavioral manifestations of audiometrically-defined "slight" or "hidden" hearing loss revealed by measures of binaural detection.

PubMed

Bernstein, Leslie R; Trahiotis, Constantine

2016-11-01

This study assessed whether audiometrically-defined "slight" or "hidden" hearing losses might be associated with degradations in binaural processing as measured in binaural detection experiments employing interaurally delayed signals and maskers. Thirty-one listeners participated, all having no greater than slight hearing losses (i.e., no thresholds greater than 25 dB HL). Across the 31 listeners and consistent with the findings of Bernstein and Trahiotis [(2015). J. Acoust. Soc. Am. 138, EL474-EL479] binaural detection thresholds at 500 Hz and 4 kHz increased with increasing magnitude of interaural delay, suggesting a loss of precision of coding with magnitude of interaural delay. Binaural detection thresholds were consistently found to be elevated for listeners whose absolute thresholds at 4 kHz exceeded 7.5 dB HL. No such elevations were observed in conditions having no binaural cues available to aid detection (i.e., "monaural" conditions). Partitioning and analyses of the data revealed that those elevated thresholds (1) were more attributable to hearing level than to age and (2) result from increased levels of internal noise. The data suggest that listeners whose high-frequency monaural hearing status would be classified audiometrically as being normal or "slight loss" may exhibit substantial and perceptually meaningful losses of binaural processing.

A Bell inequality for a class of multilocal ring networks

NASA Astrophysics Data System (ADS)

Frey, Michael

2017-11-01

Quantum networks with independent sources of entanglement (hidden variables) and nodes that execute joint quantum measurements can create strong quantum correlations spanning the breadth of the network. Understanding of these correlations has to the present been limited to standard Bell experiments with one source of shared randomness, bilocal arrangements having two local sources of shared randomness, and multilocal networks with tree topologies. We introduce here a class of quantum networks with ring topologies comprised of subsystems each with its own internally shared source of randomness. We prove a Bell inequality for these networks, and to demonstrate violations of this inequality, we focus on ring networks with three-qubit subsystems. Three qubits are capable of two non-equivalent types of entanglement, GHZ and W-type. For rings of any number N of three-qubit subsystems, our inequality is violated when the subsystems are each internally GHZ-entangled. This violation is consistently stronger when N is even. This quantitative even-odd difference for GHZ entanglement becomes extreme in the case of W-type entanglement. When the ring size N is even, the presence of W-type entanglement is successfully detected; when N is odd, the inequality consistently fails to detect its presence.

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).

Discriminative motif discovery via simulated evolution and random under-sampling.

PubMed

Song, Tao; Gu, Hong

2014-01-01

Conserved motifs in biological sequences are closely related to their structure and functions. Recently, discriminative motif discovery methods have attracted more and more attention. However, little attention has been devoted to the data imbalance problem, which is one of the main reasons affecting the performance of the discriminative models. In this article, a simulated evolution method is applied to solve the multi-class imbalance problem at the stage of data preprocessing, and at the stage of Hidden Markov Models (HMMs) training, a random under-sampling method is introduced for the imbalance between the positive and negative datasets. It is shown that, in the task of discovering targeting motifs of nine subcellular compartments, the motifs found by our method are more conserved than the methods without considering data imbalance problem and recover the most known targeting motifs from Minimotif Miner and InterPro. Meanwhile, we use the found motifs to predict protein subcellular localization and achieve higher prediction precision and recall for the minority classes.

Sustained State-Independent Quantum Contextual Correlations from a Single Ion

NASA Astrophysics Data System (ADS)

Leupold, F. M.; Malinowski, M.; Zhang, C.; Negnevitsky, V.; Alonso, J.; Home, J. P.; Cabello, A.

2018-05-01

We use a single trapped-ion qutrit to demonstrate the quantum-state-independent violation of noncontextuality inequalities using a sequence of randomly chosen quantum nondemolition projective measurements. We concatenate 53 ×106 sequential measurements of 13 observables, and unambiguously violate an optimal noncontextual bound. We use the same data set to characterize imperfections including signaling and repeatability of the measurements. The experimental sequence was generated in real time with a quantum random number generator integrated into our control system to select the subsequent observable with a latency below 50 μ s , which can be used to constrain contextual hidden-variable models that might describe our results. The state-recycling experimental procedure is resilient to noise and independent of the qutrit state, substantiating the fact that the contextual nature of quantum physics is connected to measurements and not necessarily to designated states. The use of extended sequences of quantum nondemolition measurements finds applications in the fields of sensing and quantum information.

DeepDeath: Learning to predict the underlying cause of death with Big Data.

PubMed

Hassanzadeh, Hamid Reza; Ying Sha; Wang, May D

2017-07-01

Multiple cause-of-death data provides a valuable source of information that can be used to enhance health standards by predicting health related trajectories in societies with large populations. These data are often available in large quantities across U.S. states and require Big Data techniques to uncover complex hidden patterns. We design two different classes of models suitable for large-scale analysis of mortality data, a Hadoop-based ensemble of random forests trained over N-grams, and the DeepDeath, a deep classifier based on the recurrent neural network (RNN). We apply both classes to the mortality data provided by the National Center for Health Statistics and show that while both perform significantly better than the random classifier, the deep model that utilizes long short-term memory networks (LSTMs), surpasses the N-gram based models and is capable of learning the temporal aspect of the data without a need for building ad-hoc, expert-driven features.

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.

Noise-enhanced convolutional neural networks.

PubMed

Audhkhasi, Kartik; Osoba, Osonde; Kosko, Bart

2016-06-01

Injecting carefully chosen noise can speed convergence in the backpropagation training of a convolutional neural network (CNN). The Noisy CNN algorithm speeds training on average because the backpropagation algorithm is a special case of the generalized expectation-maximization (EM) algorithm and because such carefully chosen noise always speeds up the EM algorithm on average. The CNN framework gives a practical way to learn and recognize images because backpropagation scales with training data. It has only linear time complexity in the number of training samples. The Noisy CNN algorithm finds a special separating hyperplane in the network's noise space. The hyperplane arises from the likelihood-based positivity condition that noise-boosts the EM algorithm. The hyperplane cuts through a uniform-noise hypercube or Gaussian ball in the noise space depending on the type of noise used. Noise chosen from above the hyperplane speeds training on average. Noise chosen from below slows it on average. The algorithm can inject noise anywhere in the multilayered network. Adding noise to the output neurons reduced the average per-iteration training-set cross entropy by 39% on a standard MNIST image test set of handwritten digits. It also reduced the average per-iteration training-set classification error by 47%. Adding noise to the hidden layers can also reduce these performance measures. The noise benefit is most pronounced for smaller data sets because the largest EM hill-climbing gains tend to occur in the first few iterations. This noise effect can assist random sampling from large data sets because it allows a smaller random sample to give the same or better performance than a noiseless sample gives. Copyright © 2015 Elsevier Ltd. All rights reserved.

A simple approach for the sonochemical loading of Au, Ag and Pd nanoparticle on functionalized MWCNT and subsequent dispersion studies for removal of organic dyes: Artificial neural network and response surface methodology studies.

PubMed

Moghaddari, Mitra; Yousefi, Fakhri; Ghaedi, Mehrorang; Dashtian, Kheibar

2018-04-01

In this study, the artificial neural network (ANN) and response surface methodology (RSM) based on central composite design (CCD) were applied for modeling and optimization of the simultaneous ultrasound-assisted removal of quinoline yellow (QY) and eosin B (EB). The MWCNT-NH 2 and its composites were prepared by sonochemistry method and characterized by scanning electron microscopy (SEM), X-ray diffraction (XRD) and energy dispersive spectroscopy (EDS) analysis's. Initial dyes concentrations, adsorbent mass, sonication time and pH contribution on QY and EB removal percentage were investigated by CCD and replication of experiments at conditions suggested by model has results which statistically are close to experimented data. The ultrasound irradiation is associated with raising mass transfer of process so that small amount of the adsorbent (0.025 g) is able to remove high percentage (88.00% and 91.00%) of QY and EB, respectively in short time (6.0 min) at pH = 6. Analysis of experimental data by conventional models is good indication of Langmuir efficiency for fitting and explanation of experimented data. The ANN based on the Levenberg-Marquardt algorithm (LMA) combined of linear transfer function at output layer and tangent sigmoid transfer function at hidden layer with 20 hidden neurons supply best operation conditions for good prediction of adsorption data. Accurate and efficient artificial neural network was obtained by changing the number of neurons in the hidden layer, while data was divided into training, test and validation sets which contained 70, 15 and 15% of data points respectively. The Average absolute deviation (AAD)% of a collection of 128 data points for MWCNT-NH 2 and composites is 0.58%.for EB and 0.55 for YQ. Copyright © 2017 Elsevier B.V. All rights reserved.

Learning history and cholinergic modulation in the dorsal hippocampus are necessary for rats to infer the status of a hidden event.

PubMed

Fast, Cynthia D; Flesher, M Melissa; Nocera, Nathanial A; Fanselow, Michael S; Blaisdell, Aaron P

2016-06-01

Identifying statistical patterns between environmental stimuli enables organisms to respond adaptively when cues are later observed. However, stimuli are often obscured from detection, necessitating behavior under conditions of ambiguity. Considerable evidence indicates decisions under ambiguity rely on inference processes that draw on past experiences to generate predictions under novel conditions. Despite the high demand for this process and the observation that it deteriorates disproportionately with age, the underlying mechanisms remain unknown. We developed a rodent model of decision-making during ambiguity to examine features of experience that contribute to inference. Rats learned either a simple (positive patterning) or complex (negative patterning) instrumental discrimination between the illumination of one or two lights. During test, only one light was lit while the other relevant light was blocked from physical detection (covered by an opaque shield, rendering its status ambiguous). We found experience with the complex negative patterning discrimination was necessary for rats to behave sensitively to the ambiguous test situation. These rats behaved as if they inferred the presence of the hidden light, responding differently than when the light was explicitly absent (uncovered and unlit). Differential expression profiles of the immediate early gene cFos indicated hippocampal involvement in the inference process while localized microinfusions of the muscarinic antagonist, scopolamine, into the dorsal hippocampus caused rats to behave as if only one light was present. That is, blocking cholinergic modulation prevented the rat from inferring the presence of the hidden light. Collectively, these results suggest cholinergic modulation mediates recruitment of hippocampal processes related to past experiences and transfer of these processes to make decisions during ambiguous situations. Our results correspond with correlations observed between human brain function and inference abilities, suggesting our experiments may inform interventions to alleviate or prevent cognitive dysfunction. © 2015 Wiley Periodicals, Inc. © 2015 Wiley Periodicals, Inc.

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

PubMed

Zhao, Zhibiao

2011-06-01

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

A novelty detection diagnostic methodology for gearboxes operating under fluctuating operating conditions using probabilistic techniques

NASA Astrophysics Data System (ADS)

Schmidt, S.; Heyns, P. S.; de Villiers, J. P.

2018-02-01

In this paper, a fault diagnostic methodology is developed which is able to detect, locate and trend gear faults under fluctuating operating conditions when only vibration data from a single transducer, measured on a healthy gearbox are available. A two-phase feature extraction and modelling process is proposed to infer the operating condition and based on the operating condition, to detect changes in the machine condition. Information from optimised machine and operating condition hidden Markov models are statistically combined to generate a discrepancy signal which is post-processed to infer the condition of the gearbox. The discrepancy signal is processed and combined with statistical methods for automatic fault detection and localisation and to perform fault trending over time. The proposed methodology is validated on experimental data and a tacholess order tracking methodology is used to enhance the cost-effectiveness of the diagnostic methodology.

State Space Model with hidden variables for reconstruction of gene regulatory networks.

PubMed

Wu, Xi; Li, Peng; Wang, Nan; Gong, Ping; Perkins, Edward J; Deng, Youping; Zhang, Chaoyang

2011-01-01

State Space Model (SSM) is a relatively new approach to inferring gene regulatory networks. It requires less computational time than Dynamic Bayesian Networks (DBN). There are two types of variables in the linear SSM, observed variables and hidden variables. SSM uses an iterative method, namely Expectation-Maximization, to infer regulatory relationships from microarray datasets. The hidden variables cannot be directly observed from experiments. How to determine the number of hidden variables has a significant impact on the accuracy of network inference. In this study, we used SSM to infer Gene regulatory networks (GRNs) from synthetic time series datasets, investigated Bayesian Information Criterion (BIC) and Principle Component Analysis (PCA) approaches to determining the number of hidden variables in SSM, and evaluated the performance of SSM in comparison with DBN. True GRNs and synthetic gene expression datasets were generated using GeneNetWeaver. Both DBN and linear SSM were used to infer GRNs from the synthetic datasets. The inferred networks were compared with the true networks. Our results show that inference precision varied with the number of hidden variables. For some regulatory networks, the inference precision of DBN was higher but SSM performed better in other cases. Although the overall performance of the two approaches is compatible, SSM is much faster and capable of inferring much larger networks than DBN. This study provides useful information in handling the hidden variables and improving the inference precision.

Diagnosing Autism Spectrum Disorder from Brain Resting-State Functional Connectivity Patterns Using a Deep Neural Network with a Novel Feature Selection Method.

PubMed

Guo, Xinyu; Dominick, Kelli C; Minai, Ali A; Li, Hailong; Erickson, Craig A; Lu, Long J

2017-01-01

The whole-brain functional connectivity (FC) pattern obtained from resting-state functional magnetic resonance imaging data are commonly applied to study neuropsychiatric conditions such as autism spectrum disorder (ASD) by using different machine learning models. Recent studies indicate that both hyper- and hypo- aberrant ASD-associated FCs were widely distributed throughout the entire brain rather than only in some specific brain regions. Deep neural networks (DNN) with multiple hidden layers have shown the ability to systematically extract lower-to-higher level information from high dimensional data across a series of neural hidden layers, significantly improving classification accuracy for such data. In this study, a DNN with a novel feature selection method (DNN-FS) is developed for the high dimensional whole-brain resting-state FC pattern classification of ASD patients vs. typical development (TD) controls. The feature selection method is able to help the DNN generate low dimensional high-quality representations of the whole-brain FC patterns by selecting features with high discriminating power from multiple trained sparse auto-encoders. For the comparison, a DNN without the feature selection method (DNN-woFS) is developed, and both of them are tested with different architectures (i.e., with different numbers of hidden layers/nodes). Results show that the best classification accuracy of 86.36% is generated by the DNN-FS approach with 3 hidden layers and 150 hidden nodes (3/150). Remarkably, DNN-FS outperforms DNN-woFS for all architectures studied. The most significant accuracy improvement was 9.09% with the 3/150 architecture. The method also outperforms other feature selection methods, e.g., two sample t -test and elastic net. In addition to improving the classification accuracy, a Fisher's score-based biomarker identification method based on the DNN is also developed, and used to identify 32 FCs related to ASD. These FCs come from or cross different pre-defined brain networks including the default-mode, cingulo-opercular, frontal-parietal, and cerebellum. Thirteen of them are statically significant between ASD and TD groups (two sample t -test p < 0.05) while 19 of them are not. The relationship between the statically significant FCs and the corresponding ASD behavior symptoms is discussed based on the literature and clinician's expert knowledge. Meanwhile, the potential reason of obtaining 19 FCs which are not statistically significant is also provided.

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…

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

NASA Astrophysics Data System (ADS)

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

1996-05-01

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

45,X/47,XXX/47,XX, del(Y)(p?)/46,XX mosaicism causing true hermaphroditism.

PubMed

Nieto, Karem; Peña, Rocío; Palma, Icela; Dorantes, Luis M; Eraña, Luis; Alvarez, Rebeca; García-Cavazos, Ricardo; Kofman-Alfaro, Susana; Queipo, Gloria

2004-10-15

Sex differentiation in humans depends on the presence of the Y-linked gene SRY, which is activated in the pre-Sertoli cells of the developing gonadal primordium to trigger testicular differentiation. Occasionally testicular formation can take place in subjects lacking a Y chromosome resulting in a 46,XX sex reversal condition. True hermaphroditism (TH) is a rare form of intersexuality characterized by the presence of testicular and ovarian tissue in the same individual. Genetic heterogeneity has been proposed as a cause of dual gonadal development in some cases and recently, hidden mosaicism was reported to cause TH in some 46,XX SRY negative patients. Here we report a TH case in which hidden mosaicism for the Y and X chromosome was detected by PCR and FISH in peripheral blood and gonadal tissue, supporting the fact that mosaicism may cause TH and that molecular analysis of gonadal tissue should be performed in all 46,XX cases.

Results and experiences from the NATO Common Shield DAT#7 experiment for the Defence Against Terrorism program

NASA Astrophysics Data System (ADS)

Peichl, Markus; Dill, Stephan; Jirousek, Matthias; Süß, Helmut

2009-05-01

Passive microwave imaging allows a daytime independent observation and examination of objects and persons without artificial exposure under nearly all weather conditions. The penetration capability of microwaves allows the detection of hidden objects like weapons and explosive devices under the clothing. In August/September 2008 a comprehensive military experiment was conducted by the German armed forces at the naval base Eckernfoerde, Germany. One activity in the Eckernfoerde trial was the simulation of a military entrance portal by a tent including various imaging and a chemical sensor suite. Besides commercial optical and infrared cameras various passive millimeter-wave imagers have been used from different German research institutions. The DLR Microwaves and Radar Institute, Department for Reconnaissance and Security (HR-AS), provided an imaging radiometer scanner operating at W band. A multitude of situations have been simulated and many persons carrying hidden objects under their clothing have been scanned. Some exemplary results from the trial are shown and discussed in the paper.

(In)Visibility Online: The Benefits of Online Patient Forums for People with a Hidden Illness: The Case of Multiple Chemical Sensitivity (MCS).

PubMed

Phillips, Tarryn; Rees, Tyson

2018-06-01

Sufferers of medically unexplained conditions that are not observable in the clinic can experience multiple layers of invisibility: a lack of biomedical diagnosis; legal skepticism; political disinterest; and a loss of their prior social identity. For those with environmental sensitivities, this is compounded by literal hiddenness due to often being housebound. Drawing on an online survey of people with multiple chemical sensitivity, this article examines how the everyday experience of invisibility is mitigated by engaging with other patients online. Respondents used online forums to undertake various forms of "visibility work," including attempts to crystallize their suffering into something recognizable medically, legally, and politically, and to reconstruct an identity considered valid and deserving-although the therapeutic potential of online support was contingent on intra-group politics. This study demonstrates that online forums allow biomedicine's "invisible others" to struggle for alternative forms of recognition beyond the clinical gaze. © 2017 by the American Anthropological Association.

On equivalent parameter learning in simplified feature space based on Bayesian asymptotic analysis.

PubMed

Yamazaki, Keisuke

2012-07-01

Parametric models for sequential data, such as hidden Markov models, stochastic context-free grammars, and linear dynamical systems, are widely used in time-series analysis and structural data analysis. Computation of the likelihood function is one of primary considerations in many learning methods. Iterative calculation of the likelihood such as the model selection is still time-consuming though there are effective algorithms based on dynamic programming. The present paper studies parameter learning in a simplified feature space to reduce the computational cost. Simplifying data is a common technique seen in feature selection and dimension reduction though an oversimplified space causes adverse learning results. Therefore, we mathematically investigate a condition of the feature map to have an asymptotically equivalent convergence point of estimated parameters, referred to as the vicarious map. As a demonstration to find vicarious maps, we consider the feature space, which limits the length of data, and derive a necessary length for parameter learning in hidden Markov models. Copyright © 2012 Elsevier Ltd. All rights reserved.

Projecting sensations to external objects: evidence from skin conductance response.

PubMed

Armel, K Carrie; Ramachandran, V S

2003-07-22

Subjects perceived touch sensations as arising from a table (or a rubber hand) when both the table (or the rubber hand) and their own real hand were repeatedly tapped and stroked in synchrony with the real hand hidden from view. If the table or rubber hand was then 'injured', subjects displayed a strong skin conductance response (SCR) even though nothing was done to the real hand. Sensations could even be projected to anatomically impossible locations. The illusion was much less vivid, as indicated by subjective reports and SCR, if the real hand was simultaneously visible during stroking, or if the real hand was hidden but touched asynchronously. The fact that the illusion could be significantly diminished when the real hand was simultaneously visible suggests that the illusion and associated SCRs were due to perceptual assimilation of the table (or rubber hand) into one's body image rather than associative conditioning. These experiments demonstrate the malleability of body image and the brain's remarkable capacity for detecting statistical correlations in the sensory input.

Projecting sensations to external objects: evidence from skin conductance response.

PubMed Central

Armel, K Carrie; Ramachandran, V S

2003-01-01

Subjects perceived touch sensations as arising from a table (or a rubber hand) when both the table (or the rubber hand) and their own real hand were repeatedly tapped and stroked in synchrony with the real hand hidden from view. If the table or rubber hand was then 'injured', subjects displayed a strong skin conductance response (SCR) even though nothing was done to the real hand. Sensations could even be projected to anatomically impossible locations. The illusion was much less vivid, as indicated by subjective reports and SCR, if the real hand was simultaneously visible during stroking, or if the real hand was hidden but touched asynchronously. The fact that the illusion could be significantly diminished when the real hand was simultaneously visible suggests that the illusion and associated SCRs were due to perceptual assimilation of the table (or rubber hand) into one's body image rather than associative conditioning. These experiments demonstrate the malleability of body image and the brain's remarkable capacity for detecting statistical correlations in the sensory input. PMID:12965016

High prevalence of parental delivery of plastic debris in Cory's shearwaters (Calonectris diomedea).

PubMed

Rodríguez, Airam; Rodríguez, Beneharo; Nazaret Carrasco, María

2012-10-01

Plastic ingestion by adult Procellariiformes has been widely recorded, but few studies have evaluated intergenerational transfer. We assessed the prevalence of plastic particles, as well as their basic characteristics, in the gut content of dead Cory's shearwater fledglings stranded by light pollution on Canary Islands. Eighty-three percent of birds were affected, containing on average 8.0 plastic pieces per bird. The average plastic weight per bird was low (2.97±3.97mg) compared with other petrel species. We found no relationships between plastic loads and body condition or body size, but negative effects may be hidden or delayed. We propose to use the fledglings stranded by light pollution to carry out more precise studies to understand the potential hidden costs of plastic ingestion; and to monitor in a long-term the marine debris to develop management actions for the control of pollution at the marine environment. Copyright © 2012 Elsevier Ltd. All rights reserved.

'Einselection' of pointer observables: The new H-theorem?

NASA Astrophysics Data System (ADS)

Kastner, Ruth E.

2014-11-01

In attempting to derive irreversible macroscopic thermodynamics from reversible microscopic dynamics, Boltzmann inadvertently smuggled in a premise that assumed the very irreversibility he was trying to prove: 'molecular chaos'. The program of 'einselection' (environmentally induced superselection) within Everettian approaches faces a similar 'Loschmidt's Paradox': the universe, according to the Everettian picture, is a closed system obeying only unitary dynamics, and it therefore contains no distinguishable environmental subsystems with the necessary 'phase randomness' to effect einselection of a pointer observable. The theoretically unjustified assumption of distinguishable environmental subsystems is the hidden premise that makes the derivation of einselection circular. In effect, it presupposes the 'emergent' structures from the beginning. Thus the problem of basis ambiguity remains unsolved in Everettian interpretations.

Unlocking hidden genomic sequence

PubMed Central

Keith, Jonathan M.; Cochran, Duncan A. E.; Lala, Gita H.; Adams, Peter; Bryant, Darryn; Mitchelson, Keith R.

2004-01-01

Despite the success of conventional Sanger sequencing, significant regions of many genomes still present major obstacles to sequencing. Here we propose a novel approach with the potential to alleviate a wide range of sequencing difficulties. The technique involves extracting target DNA sequence from variants generated by introduction of random mutations. The introduction of mutations does not destroy original sequence information, but distributes it amongst multiple variants. Some of these variants lack problematic features of the target and are more amenable to conventional sequencing. The technique has been successfully demonstrated with mutation levels up to an average 18% base substitution and has been used to read previously intractable poly(A), AT-rich and GC-rich motifs. PMID:14973330

Location-oblivious data transfer with flying entangled qudits

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

Kent, Adrian

2011-07-15

We present a simple and practical quantum protocol involving two mistrustful agencies in Minkowski space, which allows Alice to transfer data to Bob at a space-time location that neither can predict in advance. The location depends on both Alice's and Bob's actions. The protocol guarantees unconditionally to Alice that Bob learns the data at a randomly determined location; it guarantees to Bob that Alice will not learn the transfer location even after the protocol is complete. The task implemented, transferring data at a space-time location that remains hidden from the transferrer, has no precise analog in nonrelativistic quantum cryptography. Itmore » illustrates further the scope for novel cryptographic applications of relativistic quantum theory.« less

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.

Position sense at the human elbow joint measured by arm matching or pointing.

PubMed

Tsay, Anthony; Allen, Trevor J; Proske, Uwe

2016-10-01

Position sense at the human elbow joint has traditionally been measured in blindfolded subjects using a forearm matching task. Here we compare position errors in a matching task with errors generated when the subject uses a pointer to indicate the position of a hidden arm. Evidence from muscle vibration during forearm matching supports a role for muscle spindles in position sense. We have recently shown using vibration, as well as muscle conditioning, which takes advantage of muscle's thixotropic property, that position errors generated in a forearm pointing task were not consistent with a role by muscle spindles. In the present study we have used a form of muscle conditioning, where elbow muscles are co-contracted at the test angle, to further explore differences in position sense measured by matching and pointing. For fourteen subjects, in a matching task where the reference arm had elbow flexor and extensor muscles contracted at the test angle and the indicator arm had its flexors conditioned at 90°, matching errors lay in the direction of flexion by 6.2°. After the same conditioning of the reference arm and extension conditioning of the indicator at 0°, matching errors lay in the direction of extension (5.7°). These errors were consistent with predictions based on a role by muscle spindles in determining forearm matching outcomes. In the pointing task subjects moved a pointer to align it with the perceived position of the hidden arm. After conditioning of the reference arm as before, pointing errors all lay in a more extended direction than the actual position of the arm by 2.9°-7.3°, a distribution not consistent with a role by muscle spindles. We propose that in pointing muscle spindles do not play the major role in signalling limb position that they do in matching, but that other sources of sensory input should be given consideration, including afferents from skin and joint.

Hiding the tobacco power wall reduces cigarette smoking risk in adolescents: using an experimental convenience store to assess tobacco regulatory options at retail point-of-sale.

PubMed

Shadel, William G; Martino, Steven C; Setodji, Claude M; Scharf, Deborah M; Kusuke, Daniela; Sicker, Angela; Gong, Min

2015-11-23

This experiment tested whether changing the location or visibility of the tobacco power wall in a life sized replica of a convenience store had any effect on adolescents' susceptibility to future cigarette smoking. The study was conducted in the RAND StoreLab (RSL), a life sized replica of a convenience store that was developed to experimentally evaluate how changing aspects of tobacco advertising displays in retail point-of-sale environments influences tobacco use risk and behaviour. A randomised, between-subjects experimental design with three conditions that varied the location or visibility of the tobacco power wall within the RSL was used. The conditions were: cashier (the tobacco power wall was located in its typical position behind the cash register counter); sidewall (the tobacco power wall was located on a sidewall away from the cash register); or hidden (the tobacco power wall was located behind the cashier but was hidden behind an opaque wall). The sample included 241 adolescents. Hiding the tobacco power wall significantly reduced adolescents' susceptibility to future cigarette smoking compared to leaving it exposed (ie, the cashier condition; p=0.02). Locating the tobacco power wall on a sidewall away from the cashier had no effect on future cigarette smoking susceptibility compared to the cashier condition (p=0.80). Hiding the tobacco power wall at retail point-of-sale locations is a strong regulatory option for reducing the impact of the retail environment on cigarette smoking risk in adolescents. Published by the BMJ Publishing Group Limited. For permission to use (where not already granted under a licence) please go to http://www.bmj.com/company/products-services/rights-and-licensing/

Epidemiology of forest malaria in Central Vietnam: the hidden parasite reservoir.

PubMed

Thanh, Pham Vinh; Van Hong, Nguyen; Van Van, Nguyen; Van Malderen, Carine; Obsomer, Valérie; Rosanas-Urgell, Anna; Grietens, Koen Peeters; Xa, Nguyen Xuan; Bancone, Germana; Chowwiwat, Nongnud; Duong, Tran Thanh; D'Alessandro, Umberto; Speybroeck, Niko; Erhart, Annette

2015-02-19

After successfully reducing the malaria burden to pre-elimination levels over the past two decades, the national malaria programme in Vietnam has recently switched from control to elimination. However, in forested areas of Central Vietnam malaria elimination is likely to be jeopardized by the high occurrence of asymptomatic and submicroscopic infections as shown by previous reports. This paper presents the results of a malaria survey carried out in a remote forested area of Central Vietnam where we evaluated malaria prevalence and risk factors for infection. After a full census (four study villages = 1,810 inhabitants), the study population was screened for malaria infections by standard microscopy and, if needed, treated according to national guidelines. An additional blood sample on filter paper was also taken in a random sample of the population for later polymerase chain reaction (PCR) and more accurate estimation of the actual burden of malaria infections. The risk factor analysis for malaria infections was done using survey multivariate logistic regression as well as the classification and regression tree method (CART). A total of 1,450 individuals were screened. Malaria prevalence by microscopy was 7.8% (ranging from 3.9 to 10.9% across villages) mostly Plasmodium falciparum (81.4%) or Plasmodium vivax (17.7%) mono-infections; a large majority (69.9%) was asymptomatic. By PCR, the prevalence was estimated at 22.6% (ranging from 16.4 to 42.5%) with a higher proportion of P. vivax mono-infections (43.2%). The proportion of sub-patent infections increased with increasing age and with decreasing prevalence across villages. The main risk factors were young age, village, house structure, and absence of bed net. This study confirmed that in Central Vietnam a substantial part of the human malaria reservoir is hidden. Additional studies are urgently needed to assess the contribution of this hidden reservoir to the maintenance of malaria transmission. Such evidence will be crucial for guiding elimination strategies.

Forecasting the prognosis of choroidal melanoma with an artificial neural network.

PubMed

Kaiserman, Igor; Rosner, Mordechai; Pe'er, Jacob

2005-09-01

To develop an artificial neural network (ANN) that will forecast the 5-year mortality from choroidal melanoma. Retrospective, comparative, observational cohort study. One hundred fifty-three eyes of 153 consecutive patients with choroidal melanoma (age, 58.4+/-14.6 years) who were treated with ruthenium 106 brachytherapy between 1988 and 1998 at the Department of Ophthalmology, Hadassah University Hospital, Jerusalem, Israel. Patients were observed clinically and ultrasonographically (A- and B-mode standardized ultrasonography). Metastatic screening included liver function tests and liver imaging. Backpropagation ANNs composed of 3 or 4 layers of neurons with various types of transfer functions and training protocols were assessed for their ability to predict the 5-year mortality. The ANNs were trained on 77 randomly selected patients and tested on a different set of 76 patients. Artificial neural networks were compared based on their sensitivity, specificity, forecasting accuracy, area under the receiver operating curves, and likelihood ratios (LRs). The best ANN was compared with the results of logistic regression and the performance of an ocular oncologist. The ability of the ANNs to forecast the 5-year mortality from choroidal melanoma. Thirty-one patients died during the follow-up period of metastatic choroidal melanoma. The best ANN (one hidden layer of 16 neurons) had 84% forecasting accuracy and an LR of 31.5. The number of hidden neurons significantly influenced the ANNs' performance (P<0.001). The performance of the ANNs was not significantly influenced by the training protocol, the number of hidden layers, or the type of transfer function. In comparison, logistic regression reached 86% forecasting accuracy, with a very low LR (0.8), whereas the human expert forecasting ability was <70% (LR, 1.85). Artificial neural networks can be used for forecasting the prognosis of choroidal melanoma and may support decision-making in treating this malignancy.

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…

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

PubMed Central

Zhao, Zhibiao

2011-01-01

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

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.

Detection of hidden explosives by using tagged neutron beams: Status and perspectives

NASA Astrophysics Data System (ADS)

Viesti, Giuseppe; Pesente, Silvia; Nebbia, Giancarlo; Lunardon, Marcello; Sudac, Davorin; Nađ, Karlo; Blagus, Sasha; Valković, Vladivoj

2005-12-01

Non-destructive inspections have been simulated in laboratory conditions by using our tagged neutron inspection system (TNIS), using YAP:Ce scintillators to tag the neutron beam and an array of BaF2 crystals to detect the γ-rays. The system has been operated up to 2 × 108 neutron/s. Further developments of the TNIS concept are discussed in the light of our current projects for cargo container inspections.

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.

[Comparison of different modes of using tranexamic acid administration on reducing hidden blood loss in total hip arthroplasty].

PubMed

Ni, Jin-Rong; Wang, Li-Xin; Chen, Xin-Jun

2016-08-25

To compare the clinical efficacy of using tranexamic acid in different ways to reduce the hidden blood loss in patients who receiving total hip arthroplasty (THA). Totally 68 patients with osteonecrosis of the femeral head treated by total hip arthroplasty in our hospital from February 2010 to July 2015 were randomly divided into the intravenous drip group (group A) and the topical application group (group B). In group A, there were 19 males and 15 females, with an average age of (62.0±6.4) years old, preoperative average hemoglobin was (121.30±8.15) g/L, average Hematocrit was (0.470±0.039) L/L. In group B, there were 18 males and 16 females, with an average age of (64.0±7.5) years old, preoperative average hemoglobin was (125.28±9.37) g/L, average Hematocrit was (0.490±0.041) L/L. The operation incision were performed through the posterolateral approach and the normal operation mode, biological prosthesis was selected. Through different ways the tranexamic acid was used to control of intraoperative and postoperative bleeding. Tranexamic acid was intra articular injection as a dose of 10 mg/kg 10 min to patient before anesthesia in intravenous drip group. In topic group, 3 g of tranexamic acid was dissolved in 120 ml saline and divided into three equal parts, then two pieces of gauze were immersed in 40 ml tranexamic acid solution. One gauze with 40 ml tranexamic acid was used to soak the acetabulum for 5 minutes after the acetabular preparation, another gauze was inserted in the femoral canal for 5 minutes after femoral canal broach preparation. The remaining 40 ml tranexamic acid fluid was injected into the hip joint after fascia closure. Place the drainage tube and clip it for 3 hours. Hemoglobin (Hb) and Hematocrit (Hct) were recorded at 72 hours after operation. The total blood loss, dominant blood loss, and hidden blood loss were calculated. In group A, postoperative hemoglobin difference before and after operation was (32.34±7.42) g/L, total blood loss was (833.6±81.4) ml, the hidden blood loss was (276.3±57.9) ml, red blood cell volume was (10.1±1.4) L/L;In group B, hemoglobin difference before and after operation was (28.2±6.1) g/L, total blood loss was (792.5±61.8) ml, the hidden blood loss was (297.5±50.3) ml, red blood cell volume was (9.2±1.2) L/L. There was no statistical significance about those aspect ( P >0.05). Compared of blood coagulation function between two groups, in group A: PT (12.78±2.03) s, APTT (34.27±3.91) s, INR (32.34±7.42); and in group B: PT (13.17±2.19) s, APTT (32.36±3.18) s, INR (28.24±6.14). There was no significant differences also ( P >0.05). Compared with intravenous application, topical application of tranexamic acid could also effectively reduce total blood loss and hidden blood loss, postoperative blood transfusion rate in primary total hip arthroplasty, while does not increase the risk of DVT.

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.

Improved longitudinal gray and white matter atrophy assessment via application of a 4-dimensional hidden Markov random field model.

PubMed

Dwyer, Michael G; Bergsland, Niels; Zivadinov, Robert

2014-04-15

SIENA and similar techniques have demonstrated the utility of performing "direct" measurements as opposed to post-hoc comparison of cross-sectional data for the measurement of whole brain (WB) atrophy over time. However, gray matter (GM) and white matter (WM) atrophy are now widely recognized as important components of neurological disease progression, and are being actively evaluated as secondary endpoints in clinical trials. Direct measures of GM/WM change with advantages similar to SIENA have been lacking. We created a robust and easily-implemented method for direct longitudinal analysis of GM/WM atrophy, SIENAX multi-time-point (SIENAX-MTP). We built on the basic halfway-registration and mask composition components of SIENA to improve the raw output of FMRIB's FAST tissue segmentation tool. In addition, we created LFAST, a modified version of FAST incorporating a 4th dimension in its hidden Markov random field model in order to directly represent time. The method was validated by scan-rescan, simulation, comparison with SIENA, and two clinical effect size comparisons. All validation approaches demonstrated improved longitudinal precision with the proposed SIENAX-MTP method compared to SIENAX. For GM, simulation showed better correlation with experimental volume changes (r=0.992 vs. 0.941), scan-rescan showed lower standard deviations (3.8% vs. 8.4%), correlation with SIENA was more robust (r=0.70 vs. 0.53), and effect sizes were improved by up to 68%. Statistical power estimates indicated a potential drop of 55% in the number of subjects required to detect the same treatment effect with SIENAX-MTP vs. SIENAX. The proposed direct GM/WM method significantly improves on the standard SIENAX technique by trading a small amount of bias for a large reduction in variance, and may provide more precise data and additional statistical power in longitudinal studies. Copyright © 2013 Elsevier Inc. All rights reserved.

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.

Designing and implementing a socioeconomic intervention to enhance TB control: operational evidence from the CRESIPT project in Peru.

PubMed

Wingfield, Tom; Boccia, Delia; Tovar, Marco A; Huff, Doug; Montoya, Rosario; Lewis, James J; Gilman, Robert H; Evans, Carlton A

2015-08-21

Cash transfers are key interventions in the World Health Organisation's post-2015 global TB policy. However, evidence guiding TB-specific cash transfer implementation is limited. We designed, implemented and refined a novel TB-specific socioeconomic intervention that included cash transfers, which aimed to support TB prevention and cure in resource-constrained shantytowns in Lima, Peru for: the Community Randomized Evaluation of a Socioeconomic Intervention to Prevent TB (CRESIPT) project. Newly-diagnosed TB patients from study-site healthposts were eligible to receive the intervention consisting of economic and social support. Economic support was provided to patient households through cash transfers on meeting the following conditions: screening for TB in household contacts and MDR TB in patients; adhering to TB treatment and chemoprophylaxis; and engaging with CRESIPT social support (household visits and community meetings). To evaluate project acceptability, quantitative and qualitative feedback was collected using a mixed-methods approach during formative activities. Formative activities included consultations, focus group discussions and questionnaires conducted with the project team, project participants, civil society and stakeholders. Over 7 months, 135 randomly-selected patients and their 647 household contacts were recruited from 32 impoverished shantytown communities. Of 1299 potential cash transfers, 964 (74 %) were achieved, 259 (19 %) were not achieved, and 76 (7 %) were yet to be achieved. Of those achieved, 885/964 (92 %) were achieved optimally and 79/964 (8 %) sub-optimally. Key project successes were identified during 135 formative activities and included: strong multi-sectorial collaboration; generation of new evidence for TB-specific cash transfer; and the project being perceived as patient-centred and empowering. Challenges included: participant confidence being eroded through cash transfer delays, hidden account-charges and stigma; access to the initial bank-provider being limited; and conditions requiring participation of all TB-affected household members (e.g. community meetings) being hard to achieve. Refinements were made to improve project acceptability and future impact: the initial bank-provider was changed; conditional and unconditional cash transfers were combined; cash transfer sums were increased to a locally-appropriate, evidence-based amount; and cash transfer size varied according to patient household size to maximally reduce mitigation of TB-related costs and be more responsive to household needs. A novel TB-specific socioeconomic intervention including conditional cash transfers has been designed, implemented, refined and is ready for impact assessment, including by the CRESIPT project. The lessons learnt during this research will inform policy-makers and decision-makers for future implementation of related interventions.

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.

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

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.

Artificial Neural Network Based Fault Diagnostics of Rolling Element Bearings Using Time-Domain Features

NASA Astrophysics Data System (ADS)

Samanta, B.; Al-Balushi, K. R.

2003-03-01

A procedure is presented for fault diagnosis of rolling element bearings through artificial neural network (ANN). The characteristic features of time-domain vibration signals of the rotating machinery with normal and defective bearings have been used as inputs to the ANN consisting of input, hidden and output layers. The features are obtained from direct processing of the signal segments using very simple preprocessing. The input layer consists of five nodes, one each for root mean square, variance, skewness, kurtosis and normalised sixth central moment of the time-domain vibration signals. The inputs are normalised in the range of 0.0 and 1.0 except for the skewness which is normalised between -1.0 and 1.0. The output layer consists of two binary nodes indicating the status of the machine—normal or defective bearings. Two hidden layers with different number of neurons have been used. The ANN is trained using backpropagation algorithm with a subset of the experimental data for known machine conditions. The ANN is tested using the remaining set of data. The effects of some preprocessing techniques like high-pass, band-pass filtration, envelope detection (demodulation) and wavelet transform of the vibration signals, prior to feature extraction, are also studied. The results show the effectiveness of the ANN in diagnosis of the machine condition. The proposed procedure requires only a few features extracted from the measured vibration data either directly or with simple preprocessing. The reduced number of inputs leads to faster training requiring far less iterations making the procedure suitable for on-line condition monitoring and diagnostics of machines.

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.

Parsimonious extreme learning machine using recursive orthogonal least squares.

PubMed

Wang, Ning; Er, Meng Joo; Han, Min

2014-10-01

Novel constructive and destructive parsimonious extreme learning machines (CP- and DP-ELM) are proposed in this paper. By virtue of the proposed ELMs, parsimonious structure and excellent generalization of multiinput-multioutput single hidden-layer feedforward networks (SLFNs) are obtained. The proposed ELMs are developed by innovative decomposition of the recursive orthogonal least squares procedure into sequential partial orthogonalization (SPO). The salient features of the proposed approaches are as follows: 1) Initial hidden nodes are randomly generated by the ELM methodology and recursively orthogonalized into an upper triangular matrix with dramatic reduction in matrix size; 2) the constructive SPO in the CP-ELM focuses on the partial matrix with the subcolumn of the selected regressor including nonzeros as the first column while the destructive SPO in the DP-ELM operates on the partial matrix including elements determined by the removed regressor; 3) termination criteria for CP- and DP-ELM are simplified by the additional residual error reduction method; and 4) the output weights of the SLFN need not be solved in the model selection procedure and is derived from the final upper triangular equation by backward substitution. Both single- and multi-output real-world regression data sets are used to verify the effectiveness and superiority of the CP- and DP-ELM in terms of parsimonious architecture and generalization accuracy. Innovative applications to nonlinear time-series modeling demonstrate superior identification results.

Hidden Connectivity in Networks with Vulnerable Classes of Nodes

NASA Astrophysics Data System (ADS)

Krause, Sebastian M.; Danziger, Michael M.; Zlatić, Vinko

2016-10-01

In many complex systems representable as networks, nodes can be separated into different classes. Often these classes can be linked to a mutually shared vulnerability. Shared vulnerabilities may be due to a shared eavesdropper or correlated failures. In this paper, we show the impact of shared vulnerabilities on robust connectivity and how the heterogeneity of node classes can be exploited to maintain functionality by utilizing multiple paths. Percolation is the field of statistical physics that is generally used to analyze connectivity in complex networks, but in its existing forms, it cannot treat the heterogeneity of multiple vulnerable classes. To analyze the connectivity under these constraints, we describe each class as a color and develop a "color-avoiding" percolation. We present an analytic theory for random networks and a numerical algorithm for all networks, with which we can determine which nodes are color-avoiding connected and whether the maximal set percolates in the system. We find that the interaction of topology and color distribution implies a rich critical behavior, with critical values and critical exponents depending both on the topology and on the color distribution. Applying our physics-based theory to the Internet, we show how color-avoiding percolation can be used as the basis for new topologically aware secure communication protocols. Beyond applications to cybersecurity, our framework reveals a new layer of hidden structure in a wide range of natural and technological systems.

Occurrence of Fusarium Mycotoxins in Cereal Crops and Processed Products (Ogi) from Nigeria

PubMed Central

Chilaka, Cynthia Adaku; De Boevre, Marthe; Atanda, Olusegun Oladimeji; De Saeger, Sarah

2016-01-01

In Nigeria, maize, sorghum, and millet are very important cash crops. They are consumed on a daily basis in different processed forms in diverse cultural backgrounds. These crops are prone to fungi infestation, and subsequently may be contaminated with mycotoxins. A total of 363 samples comprising of maize (136), sorghum (110), millet (87), and ogi (30) were collected from randomly selected markets in four agro-ecological zones in Nigeria. Samples were assessed for Fusarium mycotoxins contamination using a multi-mycotoxin liquid chromatography-tandem mass spectrometry (LC-MS/MS) method. Subsequently, some selected samples were analysed for the occurrence of hidden fumonisins. Overall, 64% of the samples were contaminated with at least one toxin, at the rate of 77%, 44%, 59%, and 97% for maize, sorghum, millet, and ogi, respectively. Fumonisins were the most dominant, especially in maize and ogi, occurring at the rate of 65% and 93% with mean values of 935 and 1128 μg/kg, respectively. The prevalence of diacetoxyscirpenol was observed in maize (13%), sorghum (18%), and millet (29%), irrespective of the agro-ecological zone. Other mycotoxins detected were deoxynivalenol, zearalenone, and their metabolites, nivalenol, fusarenon-X, HT-2 toxin, and hidden fumonisins. About 43% of the samples were contaminated with more than one toxin. This study suggests that consumption of cereals and cereal-based products, ogi particularly by infants may be a source of exposure to Fusarium mycotoxins. PMID:27869703

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.

What about These Children? Assessing Poverty among the "Hidden Population" of Multiracial Children in Single-Mother Families. University of Kentucky Center for Poverty Research Discussion Paper Series, DP2010-09

ERIC Educational Resources Information Center

Bratter, Jenifer; Damaske, Sarah

2010-01-01

Capturing the conditions of children of color living in single-parent families has become more complex due to the growing presence of interracial households. This analysis assesses the size and poverty status of single-female headed families housing multiracial children. Using data from the 2000 Census, we find that 9 percent of female-headed…

Mobile Link - a theory-based messaging intervention for improving sexual and reproductive health of female entertainment workers in Cambodia: study protocol of a randomized controlled trial.

PubMed

Brody, Carinne; Tuot, Sovannary; Chhoun, Pheak; Swendenman, Dallas; Kaplan, Kathryn C; Yi, Siyan

2018-04-19

In Cambodia, HIV prevalence is concentrated in key populations including among female entertainment workers (FEWs) who may engage in direct or indirect sex work. Reaching FEWs with sexual and reproductive health (SRH) services has been difficult because of their hidden and stigmatized nature. Mobile-phone-based interventions may be an effective way to reach this population and connect them with the existing services. This article describes study design and implementation of a randomized controlled trial (RCT) of a mobile health intervention (the Mobile Link) aiming to improve SRH and related outcomes among FEWs in Cambodia. A two-arm RCT will be used to determine the effectiveness of a mobile-phone-based text/voice messaging intervention. The intervention will be developed through a participatory process. Focus group discussions and in-depth interviews have been conducted to inform and tailor behavior change theory-based text and voice messages. During the implementation phase, 600 FEWs will be recruited and randomly assigned into one of the two arms: (1) a control group and (2) a mobile phone message group (either text messages [SMS] or voice messages [VM], a delivery method chosen by participants). Participants in the control group will also receive a weekly monitoring survey, which will provide real-time information to implementing partners to streamline outreach efforts and be able to quickly identify geographic trends. The primary outcome measures will include self-reported HIV and sexually transmitted infections (STI) testing and treatment, condom use, contraceptive use, and gender-based violence (GBV). If the Mobile Link trial is successful, participants will report an increase in condom use, linkages to screening and treatment for HIV and STI, and contraception use as well as a reduction in GBV. This trial is unique in a number of ways. First, the option of participation mode (SMS or VM) allows participants to choose the message medium that best links them to services. Second, this is the first RCT of a mobile-phone-based behavior change intervention using SMS/VMs to support linkage to SRH services in Cambodia. Lastly, we are working with a hidden, hard-to-reach, and dynamic population with which existing methods of outreach have not been fully successful. Clinical trials.gov, NCT03117842 . Registered on 31 March 2017.

A robust omnifont open-vocabulary Arabic OCR system using pseudo-2D-HMM

NASA Astrophysics Data System (ADS)

Rashwan, Abdullah M.; Rashwan, Mohsen A.; Abdel-Hameed, Ahmed; Abdou, Sherif; Khalil, A. H.

2012-01-01

Recognizing old documents is highly desirable since the demand for quickly searching millions of archived documents has recently increased. Using Hidden Markov Models (HMMs) has been proven to be a good solution to tackle the main problems of recognizing typewritten Arabic characters. These attempts however achieved a remarkable success for omnifont OCR under very favorable conditions, they didn't achieve the same performance in practical conditions, i.e. noisy documents. In this paper we present an omnifont, large-vocabulary Arabic OCR system using Pseudo Two Dimensional Hidden Markov Model (P2DHMM), which is a generalization of the HMM. P2DHMM offers a more efficient way to model the Arabic characters, such model offer both minimal dependency on the font size/style (omnifont), and high level of robustness against noise. The evaluation results of this system are very promising compared to a baseline HMM system and best OCRs available in the market (Sakhr and NovoDynamics). The recognition accuracy of the P2DHMM classifier is measured against the classic HMM classifier, the average word accuracy rates for P2DHMM and HMM classifiers are 79% and 66% respectively. The overall system accuracy is measured against Sakhr and NovoDynamics OCR systems, the average word accuracy rates for P2DHMM, NovoDynamics, and Sakhr are 74%, 71%, and 61% respectively.

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.

Optimal no-go theorem on hidden-variable predictions of effect expectations

NASA Astrophysics Data System (ADS)

Blass, Andreas; Gurevich, Yuri

2018-03-01

No-go theorems prove that, under reasonable assumptions, classical hidden-variable theories cannot reproduce the predictions of quantum mechanics. Traditional no-go theorems proved that hidden-variable theories cannot predict correctly the values of observables. Recent expectation no-go theorems prove that hidden-variable theories cannot predict the expectations of observables. We prove the strongest expectation-focused no-go theorem to date. It is optimal in the sense that the natural weakenings of the assumptions and the natural strengthenings of the conclusion make the theorem fail. The literature on expectation no-go theorems strongly suggests that the expectation-focused approach is more general than the value-focused one. We establish that the expectation approach is not more general.

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.

Optimal source coding, removable noise elimination, and natural coordinate system construction for general vector sources using replicator neural networks

NASA Astrophysics Data System (ADS)

Hecht-Nielsen, Robert

1997-04-01

A new universal one-chart smooth manifold model for vector information sources is introduced. Natural coordinates (a particular type of chart) for such data manifolds are then defined. Uniformly quantized natural coordinates form an optimal vector quantization code for a general vector source. Replicator neural networks (a specialized type of multilayer perceptron with three hidden layers) are the introduced. As properly configured examples of replicator networks approach minimum mean squared error (e.g., via training and architecture adjustment using randomly chosen vectors from the source), these networks automatically develop a mapping which, in the limit, produces natural coordinates for arbitrary source vectors. The new concept of removable noise (a noise model applicable to a wide variety of real-world noise processes) is then discussed. Replicator neural networks, when configured to approach minimum mean squared reconstruction error (e.g., via training and architecture adjustment on randomly chosen examples from a vector source, each with randomly chosen additive removable noise contamination), in the limit eliminate removable noise and produce natural coordinates for the data vector portions of the noise-corrupted source vectors. Consideration regarding selection of the dimension of a data manifold source model and the training/configuration of replicator neural networks are discussed.

Learning in the Machine: Random Backpropagation and the Deep Learning Channel.

PubMed

Baldi, Pierre; Sadowski, Peter; Lu, Zhiqin

2018-07-01

Random backpropagation (RBP) is a variant of the backpropagation algorithm for training neural networks, where the transpose of the forward matrices are replaced by fixed random matrices in the calculation of the weight updates. It is remarkable both because of its effectiveness, in spite of using random matrices to communicate error information, and because it completely removes the taxing requirement of maintaining symmetric weights in a physical neural system. To better understand random backpropagation, we first connect it to the notions of local learning and learning channels. Through this connection, we derive several alternatives to RBP, including skipped RBP (SRPB), adaptive RBP (ARBP), sparse RBP, and their combinations (e.g. ASRBP) and analyze their computational complexity. We then study their behavior through simulations using the MNIST and CIFAR-10 bechnmark datasets. These simulations show that most of these variants work robustly, almost as well as backpropagation, and that multiplication by the derivatives of the activation functions is important. As a follow-up, we study also the low-end of the number of bits required to communicate error information over the learning channel. We then provide partial intuitive explanations for some of the remarkable properties of RBP and its variations. Finally, we prove several mathematical results, including the convergence to fixed points of linear chains of arbitrary length, the convergence to fixed points of linear autoencoders with decorrelated data, the long-term existence of solutions for linear systems with a single hidden layer and convergence in special cases, and the convergence to fixed points of non-linear chains, when the derivative of the activation functions is included.

Lack of Pannexin 1 Alters Synaptic GluN2 Subunit Composition and Spatial Reversal Learning in Mice.

PubMed

Gajardo, Ivana; Salazar, Claudia S; Lopez-Espíndola, Daniela; Estay, Carolina; Flores-Muñoz, Carolina; Elgueta, Claudio; Gonzalez-Jamett, Arlek M; Martínez, Agustín D; Muñoz, Pablo; Ardiles, Álvaro O

2018-01-01

Long-term potentiation (LTP) and long-term depression (LTD) are two forms of synaptic plasticity that have been considered as the cellular substrate of memory formation. Although LTP has received considerable more attention, recent evidences indicate that LTD plays also important roles in the acquisition and storage of novel information in the brain. Pannexin 1 (Panx1) is a membrane protein that forms non-selective channels which have been shown to modulate the induction of hippocampal synaptic plasticity. Animals lacking Panx1 or blockade of Pannexin 1 channels precludes the induction of LTD and facilitates LTP. To evaluate if the absence of Panx1 also affects the acquisition of rapidly changing information we trained Panx1 knockout (KO) mice and wild type (WT) littermates in a visual and hidden version of the Morris water maze (MWM). We found that KO mice find the hidden platform similarly although slightly quicker than WT animals, nonetheless, when the hidden platform was located in the opposite quadrant (OQ) to the previous learned location, KO mice spent significantly more time in the previous quadrant than in the new location indicating that the absence of Panx1 affects the reversion of a previously acquired spatial memory. Consistently, we observed changes in the content of synaptic proteins critical to LTD, such as GluN2 subunits of N-methyl-D-aspartate receptors (NMDARs), which changed their contribution to synaptic plasticity in conditions of Panx1 ablation. Our findings give further support to the role of Panx1 channels on the modulation of synaptic plasticity induction, learning and memory processes.

Diagnosing Autism Spectrum Disorder from Brain Resting-State Functional Connectivity Patterns Using a Deep Neural Network with a Novel Feature Selection Method

PubMed Central

Guo, Xinyu; Dominick, Kelli C.; Minai, Ali A.; Li, Hailong; Erickson, Craig A.; Lu, Long J.

2017-01-01

The whole-brain functional connectivity (FC) pattern obtained from resting-state functional magnetic resonance imaging data are commonly applied to study neuropsychiatric conditions such as autism spectrum disorder (ASD) by using different machine learning models. Recent studies indicate that both hyper- and hypo- aberrant ASD-associated FCs were widely distributed throughout the entire brain rather than only in some specific brain regions. Deep neural networks (DNN) with multiple hidden layers have shown the ability to systematically extract lower-to-higher level information from high dimensional data across a series of neural hidden layers, significantly improving classification accuracy for such data. In this study, a DNN with a novel feature selection method (DNN-FS) is developed for the high dimensional whole-brain resting-state FC pattern classification of ASD patients vs. typical development (TD) controls. The feature selection method is able to help the DNN generate low dimensional high-quality representations of the whole-brain FC patterns by selecting features with high discriminating power from multiple trained sparse auto-encoders. For the comparison, a DNN without the feature selection method (DNN-woFS) is developed, and both of them are tested with different architectures (i.e., with different numbers of hidden layers/nodes). Results show that the best classification accuracy of 86.36% is generated by the DNN-FS approach with 3 hidden layers and 150 hidden nodes (3/150). Remarkably, DNN-FS outperforms DNN-woFS for all architectures studied. The most significant accuracy improvement was 9.09% with the 3/150 architecture. The method also outperforms other feature selection methods, e.g., two sample t-test and elastic net. In addition to improving the classification accuracy, a Fisher's score-based biomarker identification method based on the DNN is also developed, and used to identify 32 FCs related to ASD. These FCs come from or cross different pre-defined brain networks including the default-mode, cingulo-opercular, frontal-parietal, and cerebellum. Thirteen of them are statically significant between ASD and TD groups (two sample t-test p < 0.05) while 19 of them are not. The relationship between the statically significant FCs and the corresponding ASD behavior symptoms is discussed based on the literature and clinician's expert knowledge. Meanwhile, the potential reason of obtaining 19 FCs which are not statistically significant is also provided. PMID:28871217

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.

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.

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.

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.

Reverberation negatively impacts musical sound quality for cochlear implant users.

PubMed

Roy, Alexis T; Vigeant, Michelle; Munjal, Tina; Carver, Courtney; Jiradejvong, Patpong; Limb, Charles J

2015-09-01

Satisfactory musical sound quality remains a challenge for many cochlear implant (CI) users. In particular, questionnaires completed by CI users suggest that reverberation due to room acoustics can negatively impact their music listening experience. The objective of this study was to more specifically characterize of the effect of reverberation on musical sound quality in CI users, normal hearing (NH) non-musicians, and NH musicians using a previously designed assessment method, called Cochlear Implant-MUltiple Stimulus with Hidden Reference and Anchor (CI-MUSHRA). In this method, listeners were randomly presented with an anechoic musical segment and five-versions of this segment in which increasing amounts of reverberation were artificially added. Participants listened to the six reverberation versions and provided sound quality ratings between 0 (very poor) and 100 (excellent). Results demonstrated that on average CI users and NH non-musicians preferred the sound quality of anechoic versions to more reverberant versions. In comparison, NH musicians could be delineated into those who preferred the sound quality of anechoic pieces and those who preferred pieces with some reverberation. This is the first study, to our knowledge, to objectively compare the effects of reverberation on musical sound quality ratings in CI users. These results suggest that musical sound quality for CI users can be improved by non-reverberant listening conditions and musical stimuli in which reverberation is removed.

Strategic use of preference confirmation in group decision making: the role of competition and dissent.

PubMed

Toma, Claudia; Gilles, Ingrid; Butera, Fabrizio

2013-03-01

The present research investigates the moderating role of goal interdependence and dissent on individual preference confirmation in hidden-profile tasks. We propose that preference confirmation can be used strategically to deal with competition and dissent likely to arise in group decision making. In two studies, participants first received incomplete information about a car accident investigation, and then read a fictitious discussion with two other participants containing full information. The interaction with the fictitious participants was presented either as cooperative or competitive. We predicted and found preference confirmation to be higher in competition than cooperation, when initial preferences were dissenting (Studies 1 & 2), but to be higher in cooperation than in competition, when initial preferences were consensual (Study 2). Also, the increased versus decreased preference confirmation in competition with, respectively, dissent and no dissent were found to be predicted by self-enhancement strategies (Study 2). These findings contribute to a better understanding of the boundary conditions of preference confirmation in hidden profiles and shed a new light on the role of motivated information processing in these tasks. © 2011 The British Psychological Society.

Domestic horses send signals to humans when they face with an unsolvable task.

PubMed

Ringhofer, Monamie; Yamamoto, Shinya

2017-05-01

Some domestic animals are thought to be skilled at social communication with humans due to the process of domestication. Horses, being in close relationship with humans, similar to dogs, might be skilled at communication with humans. Previous studies have indicated that they are sensitive to bodily signals and the attentional state of humans; however, there are few studies that investigate communication with humans and responses to the knowledge state of humans. Our first question was whether and how horses send signals to their potentially helpful but ignorant caretakers in a problem-solving situation where a food item was hidden in a bucket that was accessible only to the caretakers. We then examined whether horses alter their behaviours on the basis of the caretakers' knowledge of where the food was hidden. We found that horses communicated to their caretakers using visual and tactile signals. The signalling behaviour of the horses significantly increased in conditions where the caretakers had not seen the hiding of the food. These results suggest that horses alter their communicative behaviour towards humans in accordance with humans' knowledge state.

Occurrence and stability of masked fumonisins in corn silage samples.

PubMed

Latorre, Alicia; Dagnac, Thierry; Lorenzo, Bruno Fernández; Llompart, María

2015-12-15

Corn plants contaminated with Fusarium verticilloides were harvested at two dates and ensiled in laboratory silos. The stability of Fumonisins B1 and B2 (FB1, FB2) was studied and the effects of inoculant use (Lactobacillus buchneri) and of the ensiling time were assessed. The occurrence of masked fumonisins was also investigated. After the extraction of the free forms (FB1, FB2), the residue was subjected to an alkaline hydrolysis resulting in the release of derivates subsequently detected by LC-HESI-MS/MS. The ensiling time has shown to be a significant factor for the evolution of free FB1 and FB2 at the 2nd harvest date. Moreover, the use of inoculant had a significant effect on the stability of hidden and total FB1 at the two harvest dates. Samples previously ensiled and exposed to aerobic conditions for 7days have shown higher fumonisin levels than those not exposed to air. Our results showed that 65% and 39% of the total FB1 and FB2 contents in silage were due to hidden fumonisins. Copyright © 2015 Elsevier Ltd. All rights reserved.

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

Childhood temperament: passive gene-environment correlation, gene-environment interaction, and the hidden importance of the family environment.

PubMed

Lemery-Chalfant, Kathryn; Kao, Karen; Swann, Gregory; Goldsmith, H Hill

2013-02-01

Biological parents pass on genotypes to their children, as well as provide home environments that correlate with their genotypes; thus, the association between the home environment and children's temperament can be genetically (i.e., passive gene-environment correlation) or environmentally mediated. Furthermore, family environments may suppress or facilitate the heritability of children's temperament (i.e., gene-environment interaction). The sample comprised 807 twin pairs (mean age = 7.93 years) from the longitudinal Wisconsin Twin Project. Important passive gene-environment correlations emerged, such that home environments were less chaotic for children with high effortful control, and this association was genetically mediated. Children with high extraversion/surgency experienced more chaotic home environments, and this correlation was also genetically mediated. In addition, heritability of children's temperament was moderated by home environments, such that effortful control and extraversion/surgency were more heritable in chaotic homes, and negative affectivity was more heritable under crowded or unsafe home conditions. Modeling multiple types of gene-environment interplay uncovered the complex role of genetic factors and the hidden importance of the family environment for children's temperament and development more generally.

Characterizing and Differentiating Brain State Dynamics via Hidden Markov Models

PubMed Central

Ou, Jinli; Xie, Li; Jin, Changfeng; Li, Xiang; Zhu, Dajiang; Jiang, Rongxin; Chen, Yaowu

2014-01-01

Functional connectivity measured from resting state fMRI (R-fMRI) data has been widely used to examine the brain’s functional activities and has been recently used to characterize and differentiate brain conditions. However, the dynamical transition patterns of the brain’s functional states have been less explored. In this work, we propose a novel computational framework to quantitatively characterize the brain state dynamics via hidden Markov models (HMMs) learned from the observations of temporally dynamic functional connectomics, denoted as functional connectome states. The framework has been applied to the R-fMRI dataset including 44 post-traumatic stress disorder (PTSD) patients and 51 normal control (NC) subjects. Experimental results show that both PTSD and NC brains were undergoing remarkable changes in resting state and mainly transiting amongst a few brain states. Interestingly, further prediction with the best-matched HMM demonstrates that PTSD would enter into, but could not disengage from, a negative mood state. Importantly, 84 % of PTSD patients and 86 % of NC subjects are successfully classified via multiple HMMs using majority voting. PMID:25331991

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.

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.

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.

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

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.

Detecting brain tumor in computed tomography images using Markov random fields and fuzzy C-means clustering techniques

NASA Astrophysics Data System (ADS)

Abdulbaqi, Hayder Saad; Jafri, Mohd Zubir Mat; Omar, Ahmad Fairuz; Mustafa, Iskandar Shahrim Bin; Abood, Loay Kadom

2015-04-01

Brain tumors, are an abnormal growth of tissues in the brain. They may arise in people of any age. They must be detected early, diagnosed accurately, monitored carefully, and treated effectively in order to optimize patient outcomes regarding both survival and quality of life. Manual segmentation of brain tumors from CT scan images is a challenging and time consuming task. Size and location accurate detection of brain tumor plays a vital role in the successful diagnosis and treatment of tumors. Brain tumor detection is considered a challenging mission in medical image processing. The aim of this paper is to introduce a scheme for tumor detection in CT scan images using two different techniques Hidden Markov Random Fields (HMRF) and Fuzzy C-means (FCM). The proposed method has been developed in this research in order to construct hybrid method between (HMRF) and threshold. These methods have been applied on 4 different patient data sets. The result of comparison among these methods shows that the proposed method gives good results for brain tissue detection, and is more robust and effective compared with (FCM) techniques.

Fuzzy Markov random fields versus chains for multispectral image segmentation.

PubMed

Salzenstein, Fabien; Collet, Christophe

2006-11-01

This paper deals with a comparison of recent statistical models based on fuzzy Markov random fields and chains for multispectral image segmentation. The fuzzy scheme takes into account discrete and continuous classes which model the imprecision of the hidden data. In this framework, we assume the dependence between bands and we express the general model for the covariance matrix. A fuzzy Markov chain model is developed in an unsupervised way. This method is compared with the fuzzy Markovian field model previously proposed by one of the authors. The segmentation task is processed with Bayesian tools, such as the well-known MPM (Mode of Posterior Marginals) criterion. Our goal is to compare the robustness and rapidity for both methods (fuzzy Markov fields versus fuzzy Markov chains). Indeed, such fuzzy-based procedures seem to be a good answer, e.g., for astronomical observations when the patterns present diffuse structures. Moreover, these approaches allow us to process missing data in one or several spectral bands which correspond to specific situations in astronomy. To validate both models, we perform and compare the segmentation on synthetic images and raw multispectral astronomical data.

Revisiting the European sovereign bonds with a permutation-information-theory approach

NASA Astrophysics Data System (ADS)

Fernández Bariviera, Aurelio; Zunino, Luciano; Guercio, María Belén; Martinez, Lisana B.; Rosso, Osvaldo A.

2013-12-01

In this paper we study the evolution of the informational efficiency in its weak form for seventeen European sovereign bonds time series. We aim to assess the impact of two specific economic situations in the hypothetical random behavior of these time series: the establishment of a common currency and a wide and deep financial crisis. In order to evaluate the informational efficiency we use permutation quantifiers derived from information theory. Specifically, time series are ranked according to two metrics that measure the intrinsic structure of their correlations: permutation entropy and permutation statistical complexity. These measures provide the rectangular coordinates of the complexity-entropy causality plane; the planar location of the time series in this representation space reveals the degree of informational efficiency. According to our results, the currency union contributed to homogenize the stochastic characteristics of the time series and produced synchronization in the random behavior of them. Additionally, the 2008 financial crisis uncovered differences within the apparently homogeneous European sovereign markets and revealed country-specific characteristics that were partially hidden during the monetary union heyday.

Thermodynamic limit of random partitions and dispersionless Toda hierarchy

NASA Astrophysics Data System (ADS)

Takasaki, Kanehisa; Nakatsu, Toshio

2012-01-01

We study the thermodynamic limit of random partition models for the instanton sum of 4D and 5D supersymmetric U(1) gauge theories deformed by some physical observables. The physical observables correspond to external potentials in the statistical model. The partition function is reformulated in terms of the density function of Maya diagrams. The thermodynamic limit is governed by a limit shape of Young diagrams associated with dominant terms in the partition function. The limit shape is characterized by a variational problem, which is further converted to a scalar-valued Riemann-Hilbert problem. This Riemann-Hilbert problem is solved with the aid of a complex curve, which may be thought of as the Seiberg-Witten curve of the deformed U(1) gauge theory. This solution of the Riemann-Hilbert problem is identified with a special solution of the dispersionless Toda hierarchy that satisfies a pair of generalized string equations. The generalized string equations for the 5D gauge theory are shown to be related to hidden symmetries of the statistical model. The prepotential and the Seiberg-Witten differential are also considered.

Multiplicative processes in visual cognition

NASA Astrophysics Data System (ADS)

Credidio, H. F.; Teixeira, E. N.; Reis, S. D. S.; Moreira, A. A.; Andrade, J. S.

2014-03-01

The Central Limit Theorem (CLT) is certainly one of the most important results in the field of statistics. The simple fact that the addition of many random variables can generate the same probability curve, elucidated the underlying process for a broad spectrum of natural systems, ranging from the statistical distribution of human heights to the distribution of measurement errors, to mention a few. An extension of the CLT can be applied to multiplicative processes, where a given measure is the result of the product of many random variables. The statistical signature of these processes is rather ubiquitous, appearing in a diverse range of natural phenomena, including the distributions of incomes, body weights, rainfall, and fragment sizes in a rock crushing process. Here we corroborate results from previous studies which indicate the presence of multiplicative processes in a particular type of visual cognition task, namely, the visual search for hidden objects. Precisely, our results from eye-tracking experiments show that the distribution of fixation times during visual search obeys a log-normal pattern, while the fixational radii of gyration follow a power-law behavior.

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.

Stochastic tools hidden behind the empirical dielectric relaxation laws

NASA Astrophysics Data System (ADS)

Stanislavsky, Aleksander; Weron, Karina

2017-03-01

The paper is devoted to recent advances in stochastic modeling of anomalous kinetic processes observed in dielectric materials which are prominent examples of disordered (complex) systems. Theoretical studies of dynamical properties of ‘structures with variations’ (Goldenfield and Kadanoff 1999 Science 284 87-9) require application of such mathematical tools—by means of which their random nature can be analyzed and, independently of the details distinguishing various systems (dipolar materials, glasses, semiconductors, liquid crystals, polymers, etc), the empirical universal kinetic patterns can be derived. We begin with a brief survey of the historical background of the dielectric relaxation study. After a short outline of the theoretical ideas providing the random tools applicable to modeling of relaxation phenomena, we present probabilistic implications for the study of the relaxation-rate distribution models. In the framework of the probability distribution of relaxation rates we consider description of complex systems, in which relaxing entities form random clusters interacting with each other and single entities. Then we focus on stochastic mechanisms of the relaxation phenomenon. We discuss the diffusion approach and its usefulness for understanding of anomalous dynamics of relaxing systems. We also discuss extensions of the diffusive approach to systems under tempered random processes. Useful relationships among different stochastic approaches to the anomalous dynamics of complex systems allow us to get a fresh look at this subject. The paper closes with a final discussion on achievements of stochastic tools describing the anomalous time evolution of complex systems.

Assessing differences in groups randomized by recruitment chain in a respondent-driven sample of Seattle-area injection drug users.

PubMed

Burt, Richard D; Thiede, Hanne

2014-11-01

Respondent-driven sampling (RDS) is a form of peer-based study recruitment and analysis that incorporates features designed to limit and adjust for biases in traditional snowball sampling. It is being widely used in studies of hidden populations. We report an empirical evaluation of RDS's consistency and variability, comparing groups recruited contemporaneously, by identical methods and using identical survey instruments. We randomized recruitment chains from the RDS-based 2012 National HIV Behavioral Surveillance survey of injection drug users in the Seattle area into two groups and compared them in terms of sociodemographic characteristics, drug-associated risk behaviors, sexual risk behaviors, human immunodeficiency virus (HIV) status and HIV testing frequency. The two groups differed in five of the 18 variables examined (P ≤ .001): race (e.g., 60% white vs. 47%), gender (52% male vs. 67%), area of residence (32% downtown Seattle vs. 44%), an HIV test in the previous 12 months (51% vs. 38%). The difference in serologic HIV status was particularly pronounced (4% positive vs. 18%). In four further randomizations, differences in one to five variables attained this level of significance, although the specific variables involved differed. We found some material differences between the randomized groups. Although the variability of the present study was less than has been reported in serial RDS surveys, these findings indicate caution in the interpretation of RDS results. Copyright © 2014 Elsevier Inc. All rights reserved.

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MedlinePlus

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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.

Hidden care: Revelations of a case-note audit of physical health care in a community mental health service.

PubMed

Lawn, Sharon; Zabeen, Sara; Rowlands, Nikki; Picot, Sharon

2018-05-24

People with severe mental illness (SMI) are widely reported to be at an increased risk of morbidity and premature death due to physical health conditions. Mental health nurses are ideally placed to address physical and mental health comorbidity as part of their day-to-day practice. This study involved an audit of hardcopy and electronic clinical case-notes of a random sample of 100 people with SMI case managed by community mental health service in metropolitan South Australia, to determine how well physical health conditions and risk factors, screening, and follow-up are recorded within their service records. Every contact between 1 July 2015 and 30 June 2016 was read. One-way ANOVA, Scheffe's test, and Fisher's exact test determined any significant associations across audit variables, which included gender, age, income, living arrangement, diagnosis, lifestyle factors, recording of physical health measures, and carer status. A focus on physical health care was evident from everyday case-note records; however, because this information was 'buried' within the plethora of entries and not brought to the fore with other key information about the person's psychiatric needs, it remained difficult to gain a full picture of potential gaps in physical health care for this population. Under-reporting, gaps and inconsistencies in the systematic recording of physical health information for this population are likely to undermine the quality of care they receive from mental health services, the ability of mental health service providers to respond in a timely way to their physical healthcare needs, and their communication with other healthcare providers. © 2018 Australian College of Mental Health Nurses Inc.

Observation of 'hidden' planar defects in boron carbide nanowires and identification of their orientations.

PubMed

Guan, Zhe; Cao, Baobao; Yang, Yang; Jiang, Youfei; Li, Deyu; Xu, Terry T

2014-01-15

The physical properties of nanostructures strongly depend on their structures, and planar defects in particular could significantly affect the behavior of the nanowires. In this work, planar defects (twins or stacking faults) in boron carbide nanowires are extensively studied by transmission electron microscopy (TEM). Results show that these defects can easily be invisible, i.e., no presence of characteristic defect features like modulated contrast in high-resolution TEM images and streaks in diffraction patterns. The simplified reason of this invisibility is that the viewing direction during TEM examination is not parallel to the (001)-type planar defects. Due to the unique rhombohedral structure of boron carbide, planar defects are only distinctive when the viewing direction is along the axial or short diagonal directions ([100], [010], or 1¯10) within the (001) plane (in-zone condition). However, in most cases, these three characteristic directions are not parallel to the viewing direction when boron carbide nanowires are randomly dispersed on TEM grids. To identify fault orientations (transverse faults or axial faults) of those nanowires whose planar defects are not revealed by TEM, a new approach is developed based on the geometrical analysis between the projected preferred growth direction of a nanowire and specific diffraction spots from diffraction patterns recorded along the axial or short diagonal directions out of the (001) plane (off-zone condition). The approach greatly alleviates tedious TEM examination of the nanowire and helps to establish the reliable structure-property relations. Our study calls attention to researchers to be extremely careful when studying nanowires with potential planar defects by TEM. Understanding the true nature of planar defects is essential in tuning the properties of these nanostructures through manipulating their structures.

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

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.

MSL: A Measure to Evaluate Three-dimensional Patterns in Gene Expression Data

PubMed Central

Gutiérrez-Avilés, David; Rubio-Escudero, Cristina

2015-01-01

Microarray technology is highly used in biological research environments due to its ability to monitor the RNA concentration levels. The analysis of the data generated represents a computational challenge due to the characteristics of these data. Clustering techniques are widely applied to create groups of genes that exhibit a similar behavior. Biclustering relaxes the constraints for grouping, allowing genes to be evaluated only under a subset of the conditions. Triclustering appears for the analysis of longitudinal experiments in which the genes are evaluated under certain conditions at several time points. These triclusters provide hidden information in the form of behavior patterns from temporal experiments with microarrays relating subsets of genes, experimental conditions, and time points. We present an evaluation measure for triclusters called Multi Slope Measure, based on the similarity among the angles of the slopes formed by each profile formed by the genes, conditions, and times of the tricluster. PMID:26124630

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.

Environmental enrichment of brown capuchins (Cebus apella): Behavioral and plasma and fecal cortisol measures of effectiveness

USGS Publications Warehouse

Boinski, S.; Swing, S.P.; Gross, T.S.; Davis, J.K.

1999-01-01

No consensus exists about the quantity and variety of environmental enrichment needed to achieve an acceptable level of psychological well-being among singly housed primates. Behavioral and plasma and fecal cortisol measures were used to evaluate the effectiveness of four levels of toy and foraging enrichment provided to eight wild-caught, singly housed adult male brown capuchins (Cebus apella). The 16-week-long study comprised six conditions and began with a 4-week-long preexperimental and ended with a 4-week-long postexperimental period during which the subjects were maintained at baseline enrichment levels. During the intervening 8 weeks, the subjects were randomly assigned to a sequence of four 2-week-long experimental conditions: control (baseline conditions), toy (the addition of two plastic toys to each cage), box (access to a foraging box with food treats hidden within crushed alfalfa), and box and toy (the addition of two plastic toys and access to a foraging box). Behavioral responses to changes in enrichment were rapid and extensive. Within-subject repeated-measure ANOVAs with planned post hoc contrasts identified highly significant reductions in abnormal and undesirable behaviors (and increases in normal behaviors) as the level of enrichment increased from control to toy to box to box and toy. No significant behavioral differences were found between the control and pre- and postexperimental conditions. Plasma and fecal cortisol measures revealed a different response to changing enrichment levels. Repeated-measure ANOVA models found significant changes in both these measures across the six conditions. The planned post hoc analyses, however, while finding dramatic increases in cortisol titers in both the pre- and postexperimental conditions relative to the control condition, did not distinguish cortisol responses among the four enrichment levels. Linear regressions among weekly group means in behavioral and cortisol measures (n = 16) found that plasma cortisol was significantly predicted by the proportions of both normal and abnormal behaviors; as the proportion of normal behaviors increased, the plasma cortisol measures decreased. Plasma cortisol weekly group means were also significantly and positively predicted by fecal cortisol weekly group means, but no behavioral measure significantly predicted fecal cortisol weekly group means. In sum, these findings argue strongly that access to a variety of toy and foraging enrichment positively affects behavioral and physiological responses to stress and enhances psychological well-being in singly housed brown capuchins.

Environmental enrichment of brown capuchins (Cebus apella): behavioral and plasma and fecal cortisol measures of effectiveness.

PubMed

Boinski, S; Swing, S P; Gross, T S; Davis, J K

1999-01-01

No consensus exists about the quantity and variety of environmental enrichment needed to achieve an acceptable level of psychological well-being among singly housed primates. Behavioral and plasma and fecal cortisol measures were used to evaluate the effectiveness of four levels of toy and foraging enrichment provided to eight wild-caught, singly housed adult male brown capuchins (Cebus apella). The 16-week-long study comprised six conditions and began with a 4-week-long preexperimental and ended with a 4-week-long postexperimental period during which the subjects were maintained at baseline enrichment levels. During the intervening 8 weeks, the subjects were randomly assigned to a sequence of four 2-week-long experimental conditions: control (baseline conditions), toy (the addition of two plastic toys to each cage), box (access to a foraging box with food treats hidden within crushed alfalfa), and box & toy (the addition of two plastic toys and access to a foraging box). Behavioral responses to changes in enrichment were rapid and extensive. Within-subject repeated-measure ANOVAs with planned post hoc contrasts identified highly significant reductions in abnormal and undesirable behaviors (and increases in normal behaviors) as the level of enrichment increased from control to toy to box to box & toy. No significant behavioral differences were found between the control and pre- and postexperimental conditions. Plasma and fecal cortisol measures revealed a different response to changing enrichment levels. Repeated-measure ANOVA models found significant changes in both these measures across the six conditions. The planned post hoc analyses, however, while finding dramatic increases in cortisol titers in both the pre- and postexperimental conditions relative to the control condition, did not distinguish cortisol responses among the four enrichment levels. Linear regressions among weekly group means in behavioral and cortisol measures (n=16) found that plasma cortisol was significantly predicted by the proportions of both normal and abnormal behaviors; as the proportion of normal behaviors increased, the plasma cortisol measures decreased. Plasma cortisol weekly group means were also significantly and positively predicted by fecal cortisol weekly group means, but no behavioral measure significantly predicted fecal cortisol weekly group means. In sum, these findings argue strongly that access to a variety of toy and foraging enrichment positively affects behavioral and physiological responses to stress and enhances psychological well-being in singly housed brown capuchins.

Coding of level of ambiguity within neural systems mediating choice.

PubMed

Lopez-Paniagua, Dan; Seger, Carol A

2013-01-01

Data from previous neuroimaging studies exploring neural activity associated with uncertainty suggest varying levels of activation associated with changing degrees of uncertainty in neural regions that mediate choice behavior. The present study used a novel task that parametrically controlled the amount of information hidden from the subject; levels of uncertainty ranged from full ambiguity (no information about probability of winning) through multiple levels of partial ambiguity, to a condition of risk only (zero ambiguity with full knowledge of the probability of winning). A parametric analysis compared a linear model in which weighting increased as a function of level of ambiguity, and an inverted-U quadratic models in which partial ambiguity conditions were weighted most heavily. Overall we found that risk and all levels of ambiguity recruited a common "fronto-parietal-striatal" network including regions within the dorsolateral prefrontal cortex, intraparietal sulcus, and dorsal striatum. Activation was greatest across these regions and additional anterior and superior prefrontal regions for the quadratic function which most heavily weighs trials with partial ambiguity. These results suggest that the neural regions involved in decision processes do not merely track the absolute degree ambiguity or type of uncertainty (risk vs. ambiguity). Instead, recruitment of prefrontal regions may result from greater degree of difficulty in conditions of partial ambiguity: when information regarding reward probabilities important for decision making is hidden or not easily obtained the subject must engage in a search for tractable information. Additionally, this study identified regions of activity related to the valuation of potential gains associated with stimuli or options (including the orbitofrontal and medial prefrontal cortices and dorsal striatum) and related to winning (including orbitofrontal cortex and ventral striatum).

Coding of level of ambiguity within neural systems mediating choice

PubMed Central

Lopez-Paniagua, Dan; Seger, Carol A.

2013-01-01

Data from previous neuroimaging studies exploring neural activity associated with uncertainty suggest varying levels of activation associated with changing degrees of uncertainty in neural regions that mediate choice behavior. The present study used a novel task that parametrically controlled the amount of information hidden from the subject; levels of uncertainty ranged from full ambiguity (no information about probability of winning) through multiple levels of partial ambiguity, to a condition of risk only (zero ambiguity with full knowledge of the probability of winning). A parametric analysis compared a linear model in which weighting increased as a function of level of ambiguity, and an inverted-U quadratic models in which partial ambiguity conditions were weighted most heavily. Overall we found that risk and all levels of ambiguity recruited a common “fronto—parietal—striatal” network including regions within the dorsolateral prefrontal cortex, intraparietal sulcus, and dorsal striatum. Activation was greatest across these regions and additional anterior and superior prefrontal regions for the quadratic function which most heavily weighs trials with partial ambiguity. These results suggest that the neural regions involved in decision processes do not merely track the absolute degree ambiguity or type of uncertainty (risk vs. ambiguity). Instead, recruitment of prefrontal regions may result from greater degree of difficulty in conditions of partial ambiguity: when information regarding reward probabilities important for decision making is hidden or not easily obtained the subject must engage in a search for tractable information. Additionally, this study identified regions of activity related to the valuation of potential gains associated with stimuli or options (including the orbitofrontal and medial prefrontal cortices and dorsal striatum) and related to winning (including orbitofrontal cortex and ventral striatum). PMID:24367286

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

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

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.

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

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.

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

Measuring the effectiveness of protected area networks in reducing deforestation.

PubMed

Andam, Kwaw S; Ferraro, Paul J; Pfaff, Alexander; Sanchez-Azofeifa, G Arturo; Robalino, Juan A

2008-10-21

Global efforts to reduce tropical deforestation rely heavily on the establishment of protected areas. Measuring the effectiveness of these areas is difficult because the amount of deforestation that would have occurred in the absence of legal protection cannot be directly observed. Conventional methods of evaluating the effectiveness of protected areas can be biased because protection is not randomly assigned and because protection can induce deforestation spillovers (displacement) to neighboring forests. We demonstrate that estimates of effectiveness can be substantially improved by controlling for biases along dimensions that are observable, measuring spatial spillovers, and testing the sensitivity of estimates to potential hidden biases. We apply matching methods to evaluate the impact on deforestation of Costa Rica's renowned protected-area system between 1960 and 1997. We find that protection reduced deforestation: approximately 10% of the protected forests would have been deforested had they not been protected. Conventional approaches to evaluating conservation impact, which fail to control for observable covariates correlated with both protection and deforestation, substantially overestimate avoided deforestation (by over 65%, based on our estimates). We also find that deforestation spillovers from protected to unprotected forests are negligible. Our conclusions are robust to potential hidden bias, as well as to changes in modeling assumptions. Our results show that, with appropriate empirical methods, conservation scientists and policy makers can better understand the relationships between human and natural systems and can use this to guide their attempts to protect critical ecosystem services.

On the use of hidden Markov models for gaze pattern modeling

NASA Astrophysics Data System (ADS)

Mannaru, Pujitha; Balasingam, Balakumar; Pattipati, Krishna; Sibley, Ciara; Coyne, Joseph

2016-05-01

Some of the conventional metrics derived from gaze patterns (on computer screens) to study visual attention, engagement and fatigue are saccade counts, nearest neighbor index (NNI) and duration of dwells/fixations. Each of these metrics has drawbacks in modeling the behavior of gaze patterns; one such drawback comes from the fact that some portions on the screen are not as important as some other portions on the screen. This is addressed by computing the eye gaze metrics corresponding to important areas of interest (AOI) on the screen. There are some challenges in developing accurate AOI based metrics: firstly, the definition of AOI is always fuzzy; secondly, it is possible that the AOI may change adaptively over time. Hence, there is a need to introduce eye-gaze metrics that are aware of the AOI in the field of view; at the same time, the new metrics should be able to automatically select the AOI based on the nature of the gazes. In this paper, we propose a novel way of computing NNI based on continuous hidden Markov models (HMM) that model the gazes as 2D Gaussian observations (x-y coordinates of the gaze) with the mean at the center of the AOI and covariance that is related to the concentration of gazes. The proposed modeling allows us to accurately compute the NNI metric in the presence of multiple, undefined AOI on the screen in the presence of intermittent casual gazing that is modeled as random gazes on the screen.

Human Taeniasis in the Republic of Korea: Hidden or Gone?

PubMed Central

2013-01-01

History and current status of human taeniasis in the Republic of Korea, due to Taenia solium, Taenia asiatica, and Taenia saginata, are briefly reviewed. Until the 1980s, human taeniasis had been quite common in various localities of Korea. A study from 1924 reported 12.0% egg prevalence in fecal examinations. Thereafter, the prevalence of Taenia spp. ranged from 3% to 14% depending on the time and locality. Jeju-do, where pigs were reared in a conventional way, was the highest endemic area of taeniasis. An analysis of internal transcribed spacer 2 and mitochondrial cytochrome c oxidase 1 genes of 68 taeniasis cases reported from 1935 to 2005 in Korea by a research group revealed the relative occurrence of the 3 Taenia spp. as follows: T. solium (4.4%), T. asiatica (75.0%), and T. saginata (20.6%). However, national surveys on intestinal helminths conducted every 5 years on randomly selected people revealed that the Taenia egg prevalence dropped from 1.9% in 1971 to 0.02% in 1997 and finally to 0.0% in 2004. With the exception of 3 egg-positive cases reported in 2008 and 2 worm-proven cases in 2011, no more cases have been officially recorded. Based on these surveys and also on other literature, it can be concluded that taeniasis has virtually disappeared from Korea, although a few sporadic cases may remain hidden. Human cysticercosis is also expected to disappear within a couple of decades in Korea. PMID:23467688

Human taeniasis in the Republic of Korea: hidden or gone?

PubMed

Chai, Jong-Yil

2013-02-01

History and current status of human taeniasis in the Republic of Korea, due to Taenia solium, Taenia asiatica, and Taenia saginata, are briefly reviewed. Until the 1980s, human taeniasis had been quite common in various localities of Korea. A study from 1924 reported 12.0% egg prevalence in fecal examinations. Thereafter, the prevalence of Taenia spp. ranged from 3% to 14% depending on the time and locality. Jeju-do, where pigs were reared in a conventional way, was the highest endemic area of taeniasis. An analysis of internal transcribed spacer 2 and mitochondrial cytochrome c oxidase 1 genes of 68 taeniasis cases reported from 1935 to 2005 in Korea by a research group revealed the relative occurrence of the 3 Taenia spp. as follows: T. solium (4.4%), T. asiatica (75.0%), and T. saginata (20.6%). However, national surveys on intestinal helminths conducted every 5 years on randomly selected people revealed that the Taenia egg prevalence dropped from 1.9% in 1971 to 0.02% in 1997 and finally to 0.0% in 2004. With the exception of 3 egg-positive cases reported in 2008 and 2 worm-proven cases in 2011, no more cases have been officially recorded. Based on these surveys and also on other literature, it can be concluded that taeniasis has virtually disappeared from Korea, although a few sporadic cases may remain hidden. Human cysticercosis is also expected to disappear within a couple of decades in Korea.

Hidden in the background: a local approach to CMB anomalies

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

Sánchez, Juan C. Bueno, E-mail: juan.c.bueno@correounivalle.edu.co

2016-09-01

We investigate a framework aiming to provide a common origin for the large-angle anomalies detected in the Cosmic Microwave Background (CMB), which are hypothesized as the result of the statistical inhomogeneity developed by different isocurvature fields of mass m ∼ H present during inflation. The inhomogeneity arises as the combined effect of ( i ) the initial conditions for isocurvature fields (obtained after a fast-roll stage finishing many e -foldings before cosmological scales exit the horizon), ( ii ) their inflationary fluctuations and ( iii ) their coupling to other degrees of freedom. Our case of interest is when thesemore » fields (interpreted as the precursors of large-angle anomalies) leave an observable imprint only in isolated patches of the Universe. When the latter intersect the last scattering surface, such imprints arise in the CMB. Nevertheless, due to their statistically inhomogeneous nature, these imprints are difficult to detect, for they become hidden in the background similarly to the Cold Spot. We then compute the probability that a single isocurvature field becomes inhomogeneous at the end of inflation and find that, if the appropriate conditions are given (which depend exclusively on the preexisting fast-roll stage), this probability is at the percent level. Finally, we discuss several mechanisms (including the curvaton and the inhomogeneous reheating) to investigate whether an initial statistically inhomogeneous isocurvature field fluctuation might give rise to some of the observed anomalies. In particular, we focus on the Cold Spot, the power deficit at low multipoles and the breaking of statistical isotropy.« less

The effect of food quality during growth on spatial memory consolidation in adult pigeons.

PubMed

Scriba, M F; Gasparini, J; Jacquin, L; Mettke-Hofmann, C; Rattenborg, N C; Roulin, A

2017-02-15

Poor environmental conditions experienced during early development can have negative long-term consequences on fitness. Animals can compensate for negative developmental effects through phenotypic plasticity by diverting resources from non-vital to vital traits such as spatial memory to enhance foraging efficiency. We tested in young feral pigeons ( Columba livia ) how diets of different nutritional value during development affect the capacity to retrieve food hidden in a spatially complex environment, a process we refer to as 'spatial memory'. Parents were fed with either high- or low-quality food from egg laying until young fledged, after which all young pigeons received the same high-quality diet until memory performance was tested at 6 months of age. The pigeons were trained to learn a food location out of 18 possible locations in one session, and then their memory of this location was tested 24 h later. Birds reared with the low-quality diet made fewer errors in the memory test. These results demonstrate that food quality during development has long-lasting effects on memory, with a moderate nutritional deficit improving spatial memory performance in a foraging context. It might be that under poor feeding conditions resources are redirected from non-vital to vital traits, or pigeons raised with low-quality food might be better in using environmental cues such as the position of the sun to find where food was hidden. © 2017. Published by The Company of Biologists Ltd.

Hidden vorticity in binary Bose-Einstein condensates

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

Brtka, Marijana; Gammal, Arnaldo; Malomed, Boris A.

We consider a binary Bose-Einstein condensate (BEC) described by a system of two-dimensional (2D) Gross-Pitaevskii equations with the harmonic-oscillator trapping potential. The intraspecies interactions are attractive, while the interaction between the species may have either sign. The same model applies to the copropagation of bimodal beams in photonic-crystal fibers. We consider a family of trapped hidden-vorticity (HV) modes in the form of bound states of two components with opposite vorticities S{sub 1,2}={+-}1, the total angular momentum being zero. A challenging problem is the stability of the HV modes. By means of a linear-stability analysis and direct simulations, stability domains aremore » identified in a relevant parameter plane. In direct simulations, stable HV modes feature robustness against large perturbations, while unstable ones split into fragments whose number is identical to the azimuthal index of the fastest growing perturbation eigenmode. Conditions allowing for the creation of the HV modes in the experiment are discussed too. For comparison, a similar but simpler problem is studied in an analytical form, viz., the modulational instability of an HV state in a one-dimensional (1D) system with periodic boundary conditions (this system models a counterflow in a binary BEC mixture loaded into a toroidal trap or a bimodal optical beam coupled into a cylindrical shell). We demonstrate that the stabilization of the 1D HV modes is impossible, which stresses the significance of the stabilization of the HV modes in the 2D setting.« less

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.

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