Low field SQUID MRI devices, components and methods

NASA Technical Reports Server (NTRS)

Penanen, Konstantin I. (Inventor); Eom, Byeong H (Inventor); Hahn, Inseob (Inventor)

2010-01-01

Low field SQUID MRI devices, components and methods are disclosed. They include a portable low field (SQUID)-based MRI instrument and a portable low field SQUID-based MRI system to be operated under a bed where a subject is adapted to be located. Also disclosed is a method of distributing wires on an image encoding coil system adapted to be used with an NMR or MRI device for analyzing a sample or subject and a second order superconducting gradiometer adapted to be used with a low field SQUID-based MRI device as a sensing component for an MRI signal related to a subject or sample.

Two-stage sequential sampling: A neighborhood-free adaptive sampling procedure

USGS Publications Warehouse

Salehi, M.; Smith, D.R.

2005-01-01

Designing an efficient sampling scheme for a rare and clustered population is a challenging area of research. Adaptive cluster sampling, which has been shown to be viable for such a population, is based on sampling a neighborhood of units around a unit that meets a specified condition. However, the edge units produced by sampling neighborhoods have proven to limit the efficiency and applicability of adaptive cluster sampling. We propose a sampling design that is adaptive in the sense that the final sample depends on observed values, but it avoids the use of neighborhoods and the sampling of edge units. Unbiased estimators of population total and its variance are derived using Murthy's estimator. The modified two-stage sampling design is easy to implement and can be applied to a wider range of populations than adaptive cluster sampling. We evaluate the proposed sampling design by simulating sampling of two real biological populations and an artificial population for which the variable of interest took the value either 0 or 1 (e.g., indicating presence and absence of a rare event). We show that the proposed sampling design is more efficient than conventional sampling in nearly all cases. The approach used to derive estimators (Murthy's estimator) opens the door for unbiased estimators to be found for similar sequential sampling designs. ?? 2005 American Statistical Association and the International Biometric Society.

Stochastic detection of enantiomers.

PubMed

Kang, Xiao-Feng; Cheley, Stephen; Guan, Xiyun; Bayley, Hagan

2006-08-23

The rapid quantification of the enantiomers of small chiral molecules is very important, notably in pharmacology. Here, we show that the enantiomers of drug molecules can be distinguished by stochastic sensing, a single-molecule detection technique. The sensing element is an engineered alpha-hemolysin protein pore, fitted with a beta-cyclodextrin adapter. By using the approach, the enantiomeric composition of samples of ibuprofen and thalidomide can be determined in less than 1 s.

Adaptive Sampling in Autonomous Marine Sensor Networks

DTIC Science & Technology

2006-06-01

Analog Processing Section A high-performance preamplifier with low noise characteristics is vital to obtaining quality sonar data. The preamplifier ...research assistantships through the Generic Ocean Array Technology Sonar (GOATS) project, contract N00014-97-1-0202 and contract N00014-05-G-0106 Delivery...Formation Behavior ..................................... 60 5 An AUV Intelligent Sensor for Real-Time Adaptive Sensing 63 5.1 A Logical Sonar Sensor

Adaptive Sensing of Time Series with Application to Remote Exploration

NASA Technical Reports Server (NTRS)

Thompson, David R.; Cabrol, Nathalie A.; Furlong, Michael; Hardgrove, Craig; Low, Bryan K. H.; Moersch, Jeffrey; Wettergreen, David

2013-01-01

We address the problem of adaptive informationoptimal data collection in time series. Here a remote sensor or explorer agent throttles its sampling rate in order to track anomalous events while obeying constraints on time and power. This problem is challenging because the agent has limited visibility -- all collected datapoints lie in the past, but its resource allocation decisions require predicting far into the future. Our solution is to continually fit a Gaussian process model to the latest data and optimize the sampling plan on line to maximize information gain. We compare the performance characteristics of stationary and nonstationary Gaussian process models. We also describe an application based on geologic analysis during planetary rover exploration. Here adaptive sampling can improve coverage of localized anomalies and potentially benefit mission science yield of long autonomous traverses.

Implementation of time-efficient adaptive sampling function design for improved undersampled MRI reconstruction

NASA Astrophysics Data System (ADS)

Choi, Jinhyeok; Kim, Hyeonjin

2016-12-01

To improve the efficacy of undersampled MRI, a method of designing adaptive sampling functions is proposed that is simple to implement on an MR scanner and yet effectively improves the performance of the sampling functions. An approximation of the energy distribution of an image (E-map) is estimated from highly undersampled k-space data acquired in a prescan and efficiently recycled in the main scan. An adaptive probability density function (PDF) is generated by combining the E-map with a modeled PDF. A set of candidate sampling functions are then prepared from the adaptive PDF, among which the one with maximum energy is selected as the final sampling function. To validate its computational efficiency, the proposed method was implemented on an MR scanner, and its robust performance in Fourier-transform (FT) MRI and compressed sensing (CS) MRI was tested by simulations and in a cherry tomato. The proposed method consistently outperforms the conventional modeled PDF approach for undersampling ratios of 0.2 or higher in both FT-MRI and CS-MRI. To fully benefit from undersampled MRI, it is preferable that the design of adaptive sampling functions be performed online immediately before the main scan. In this way, the proposed method may further improve the efficacy of the undersampled MRI.

Adaptive optical microscope for brain imaging in vivo

NASA Astrophysics Data System (ADS)

Wang, Kai

2017-04-01

The optical heterogeneity of biological tissue imposes a major limitation to acquire detailed structural and functional information deep in the biological specimens using conventional microscopes. To restore optimal imaging performance, we developed an adaptive optical microscope based on direct wavefront sensing technique. This microscope can reliably measure and correct biological samples induced aberration. We demonstrated its performance and application in structural and functional brain imaging in various animal models, including fruit fly, zebrafish and mouse.

Pupil-segmentation-based adaptive optics for microscopy

NASA Astrophysics Data System (ADS)

Ji, Na; Milkie, Daniel E.; Betzig, Eric

2011-03-01

Inhomogeneous optical properties of biological samples make it difficult to obtain diffraction-limited resolution in depth. Correcting the sample-induced optical aberrations needs adaptive optics (AO). However, the direct wavefront-sensing approach commonly used in astronomy is not suitable for most biological samples due to their strong scattering of light. We developed an image-based AO approach that is insensitive to sample scattering. By comparing images of the sample taken with different segments of the pupil illuminated, local tilt in the wavefront is measured from image shift. The aberrated wavefront is then obtained either by measuring the local phase directly using interference or with phase reconstruction algorithms similar to those used in astronomical AO. We implemented this pupil-segmentation-based approach in a two-photon fluorescence microscope and demonstrated that diffraction-limited resolution can be recovered from nonbiological and biological samples.

Solar adaptive optics: specificities, lessons learned, and open alternatives

NASA Astrophysics Data System (ADS)

Montilla, I.; Marino, J.; Asensio Ramos, A.; Collados, M.; Montoya, L.; Tallon, M.

2016-07-01

First on sky adaptive optics experiments were performed on the Dunn Solar Telescope on 1979, with a shearing interferometer and limited success. Those early solar adaptive optics efforts forced to custom-develop many components, such as Deformable Mirrors and WaveFront Sensors, which were not available at that time. Later on, the development of the correlation Shack-Hartmann marked a breakthrough in solar adaptive optics. Since then, successful Single Conjugate Adaptive Optics instruments have been developed for many solar telescopes, i.e. the National Solar Observatory, the Vacuum Tower Telescope and the Swedish Solar Telescope. Success with the Multi Conjugate Adaptive Optics systems for GREGOR and the New Solar Telescope has proved to be more difficult to attain. Such systems have a complexity not only related to the number of degrees of freedom, but also related to the specificities of the Sun, used as reference, and the sensing method. The wavefront sensing is performed using correlations on images with a field of view of 10", averaging wavefront information from different sky directions, affecting the sensing and sampling of high altitude turbulence. Also due to the low elevation at which solar observations are performed we have to include generalized fitting error and anisoplanatism, as described by Ragazzoni and Rigaut, as non-negligible error sources in the Multi Conjugate Adaptive Optics error budget. For the development of the next generation Multi Conjugate Adaptive Optics systems for the Daniel K. Inouye Solar Telescope and the European Solar Telescope we still need to study and understand these issues, to predict realistically the quality of the achievable reconstruction. To improve their designs other open issues have to be assessed, i.e. possible alternative sensing methods to avoid the intrinsic anisoplanatism of the wide field correlation Shack-Hartmann, new parameters to estimate the performance of an adaptive optics solar system, alternatives to the Strehl and the Point Spread Function used in night time adaptive optics but not really suitable to the solar systems, and new control strategies more complex than the ones used in nowadays solar Multi Conjugate Adaptive Optics systems. In this paper we summarize the lessons learned with past and current solar adaptive optics systems and focus on the discussion on the new alternatives to solve present open issues limiting their performance.

Haptic adaptation to slant: No transfer between exploration modes

PubMed Central

van Dam, Loes C. J.; Plaisier, Myrthe A.; Glowania, Catharina; Ernst, Marc O.

2016-01-01

Human touch is an inherently active sense: to estimate an object’s shape humans often move their hand across its surface. This way the object is sampled both in a serial (sampling different parts of the object across time) and parallel fashion (sampling using different parts of the hand simultaneously). Both the serial (moving a single finger) and parallel (static contact with the entire hand) exploration modes provide reliable and similar global shape information, suggesting the possibility that this information is shared early in the sensory cortex. In contrast, we here show the opposite. Using an adaptation-and-transfer paradigm, a change in haptic perception was induced by slant-adaptation using either the serial or parallel exploration mode. A unified shape-based coding would predict that this would equally affect perception using other exploration modes. However, we found that adaptation-induced perceptual changes did not transfer between exploration modes. Instead, serial and parallel exploration components adapted simultaneously, but to different kinaesthetic aspects of exploration behaviour rather than object-shape per se. These results indicate that a potential combination of information from different exploration modes can only occur at down-stream cortical processing stages, at which adaptation is no longer effective. PMID:27698392

Faster and less phototoxic 3D fluorescence microscopy using a versatile compressed sensing scheme

PubMed Central

Woringer, Maxime; Darzacq, Xavier; Zimmer, Christophe

2017-01-01

Three-dimensional fluorescence microscopy based on Nyquist sampling of focal planes faces harsh trade-offs between acquisition time, light exposure, and signal-to-noise. We propose a 3D compressed sensing approach that uses temporal modulation of the excitation intensity during axial stage sweeping and can be adapted to fluorescence microscopes without hardware modification. We describe implementations on a lattice light sheet microscope and an epifluorescence microscope, and show that images of beads and biological samples can be reconstructed with a 5-10 fold reduction of light exposure and acquisition time. Our scheme opens a new door towards faster and less damaging 3D fluorescence microscopy. PMID:28788909

State-Of in Uav Remote Sensing Survey - First Insights Into Applications of Uav Sensing Systems

NASA Astrophysics Data System (ADS)

Aasen, H.

2017-08-01

UAVs are increasingly adapted as remote sensing platforms. Together with specialized sensors, they become powerful sensing systems for environmental monitoring and surveying. Spectral data has great capabilities to the gather information about biophysical and biochemical properties. Still, capturing meaningful spectral data in a reproducible way is not trivial. Since a couple of years small and lightweight spectral sensors, which can be carried on small flexible platforms, have become available. With their adaption in the community, the responsibility to ensure the quality of the data is increasingly shifted from specialized companies and agencies to individual researchers or research teams. Due to the complexity of the data acquisition of spectral data, this poses a challenge for the community and standardized protocols, metadata and best practice procedures are needed to make data intercomparable. In November 2016, the ESSEM COST action Innovative optical Tools for proximal sensing of ecophysiological processes (OPTIMISE; http://optimise.dcs.aber.ac.uk/) held a workshop on best practices for UAV spectral sampling. The objective of this meeting was to trace the way from particle to pixel and identify influences on the data quality / reliability, to figure out how well we are currently doing with spectral sampling from UAVs and how we can improve. Additionally, a survey was designed to be distributed within the community to get an overview over the current practices and raise awareness for the topic. This talk will introduce the approach of the OPTIMISE community towards best practises in UAV spectral sampling and present first results of the survey (http://optimise.dcs.aber.ac.uk/uav-survey/). This contribution briefly introduces the survey and gives some insights into the first results given by the interviewees.

Brillouin micro-spectroscopy through aberrations via sensorless adaptive optics

NASA Astrophysics Data System (ADS)

Edrei, Eitan; Scarcelli, Giuliano

2018-04-01

Brillouin spectroscopy is a powerful optical technique for non-contact viscoelastic characterizations which has recently found applications in three-dimensional mapping of biological samples. Brillouin spectroscopy performances are rapidly degraded by optical aberrations and have therefore been limited to homogenous transparent samples. In this work, we developed an adaptive optics (AO) configuration designed for Brillouin scattering spectroscopy to engineer the incident wavefront and correct for aberrations. Our configuration does not require direct wavefront sensing and the injection of a "guide-star"; hence, it can be implemented without the need for sample pre-treatment. We used our AO-Brillouin spectrometer in aberrated phantoms and biological samples and obtained improved precision and resolution of Brillouin spectral analysis; we demonstrated 2.5-fold enhancement in Brillouin signal strength and 1.4-fold improvement in axial resolution because of the correction of optical aberrations.

Predictors of adaptation in Icelandic and American families of young children with chronic asthma.

PubMed

Svavarsdottir, Erla Kolbrun; Rayens, Mary Kay; McCubbin, Marilyn

2005-01-01

The purposes of this international study were to determine the predictors of adaptation and to assess potential moderating effects of parents' sense of coherence and family hardiness on the relationship of severity of illness of a child with asthma and family and caregiving demands as predictors of family adaptation. For both parents, sense of coherence and family hardiness predicted family adaptation. Icelandic mothers perceived their family's adaptation more favorably than did their American counterparts. For the fathers, family demands predicted adaptation. Sense of coherence moderated the effect of family demands on adaptation for both parents. These findings underscore the importance of strengthening individual and family resiliency as a mechanism for improving family adaptation.

Development of a measure of sense of community for individuals with serious mental illness residing in community settings.

PubMed

Townley, Greg; Kloos, Bret

2009-03-03

The psychological sense of community is one of the most commonly investigated constructs in community psychology. Sense of community may be particularly important for individuals with serious mental illness (SMI) because they often face societal barriers to participation in community living, including stigma and discrimination. To date, no published studies have investigated the psychometric qualities of sense of community measures among individuals with SMI. The current study tested a series of confirmatory factor analyses using the Brief Sense of Community Index (BSCI, Long & Perkins, 2003) in a sample of 416 persons with SMI living in community settings to suggest a model of sense of community for individuals with SMI and other disabilities. The resulting scale, the Brief Sense of Community Index- Disability (BSCI-D), demonstrated good model fit and construct validity. Implications are discussed for how this scale may be used in research investigating community integration and adaptive functioning in community settings.

Development of a measure of sense of community for individuals with serious mental illness residing in community settings

PubMed Central

Townley, Greg; Kloos, Bret

2008-01-01

The psychological sense of community is one of the most commonly investigated constructs in community psychology. Sense of community may be particularly important for individuals with serious mental illness (SMI) because they often face societal barriers to participation in community living, including stigma and discrimination. To date, no published studies have investigated the psychometric qualities of sense of community measures among individuals with SMI. The current study tested a series of confirmatory factor analyses using the Brief Sense of Community Index (BSCI, Long & Perkins, 2003) in a sample of 416 persons with SMI living in community settings to suggest a model of sense of community for individuals with SMI and other disabilities. The resulting scale, the Brief Sense of Community Index- Disability (BSCI-D), demonstrated good model fit and construct validity. Implications are discussed for how this scale may be used in research investigating community integration and adaptive functioning in community settings. PMID:19305637

Widefield compressive multiphoton microscopy.

PubMed

Alemohammad, Milad; Shin, Jaewook; Tran, Dung N; Stroud, Jasper R; Chin, Sang Peter; Tran, Trac D; Foster, Mark A

2018-06-15

A single-pixel compressively sensed architecture is exploited to simultaneously achieve a 10× reduction in acquired data compared with the Nyquist rate, while alleviating limitations faced by conventional widefield temporal focusing microscopes due to scattering of the fluorescence signal. Additionally, we demonstrate an adaptive sampling scheme that further improves the compression and speed of our approach.

Making sense of polarities in health organizations for policy and leadership.

PubMed

Martin, Carmel M

2010-10-01

Making sense of complex adaptive clinical practice and health systems is a pressing challenge as health services continue to struggle to adapt to changing internal and external constraints. In this Forum, we begin with Dervin's Sense-Making theories and research in communications. This provides a conceptual and theoretical context for this editions research on comparative complexity of family medicine consultations in the USA, models for adaptive leadership in clinical care and social networking to make sense of health promotion challenges for young people. Finally, a Sense-Making schema is proposed. © 2010 Blackwell Publishing Ltd.

Soft Ultrathin Electronics Innervated Adaptive Fully Soft Robots.

PubMed

Wang, Chengjun; Sim, Kyoseung; Chen, Jin; Kim, Hojin; Rao, Zhoulyu; Li, Yuhang; Chen, Weiqiu; Song, Jizhou; Verduzco, Rafael; Yu, Cunjiang

2018-03-01

Soft robots outperform the conventional hard robots on significantly enhanced safety, adaptability, and complex motions. The development of fully soft robots, especially fully from smart soft materials to mimic soft animals, is still nascent. In addition, to date, existing soft robots cannot adapt themselves to the surrounding environment, i.e., sensing and adaptive motion or response, like animals. Here, compliant ultrathin sensing and actuating electronics innervated fully soft robots that can sense the environment and perform soft bodied crawling adaptively, mimicking an inchworm, are reported. The soft robots are constructed with actuators of open-mesh shaped ultrathin deformable heaters, sensors of single-crystal Si optoelectronic photodetectors, and thermally responsive artificial muscle of carbon-black-doped liquid-crystal elastomer (LCE-CB) nanocomposite. The results demonstrate that adaptive crawling locomotion can be realized through the conjugation of sensing and actuation, where the sensors sense the environment and actuators respond correspondingly to control the locomotion autonomously through regulating the deformation of LCE-CB bimorphs and the locomotion of the robots. The strategy of innervating soft sensing and actuating electronics with artificial muscles paves the way for the development of smart autonomous soft robots. © 2018 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

Measuring aberrations in the rat brain by coherence-gated wavefront sensing using a Linnik interferometer

PubMed Central

Wang, Jinyu; Léger, Jean-François; Binding, Jonas; Boccara, A. Claude; Gigan, Sylvain; Bourdieu, Laurent

2012-01-01

Aberrations limit the resolution, signal intensity and achievable imaging depth in microscopy. Coherence-gated wavefront sensing (CGWS) allows the fast measurement of aberrations in scattering samples and therefore the implementation of adaptive corrections. However, CGWS has been demonstrated so far only in weakly scattering samples. We designed a new CGWS scheme based on a Linnik interferometer and a SLED light source, which is able to compensate dispersion automatically and can be implemented on any microscope. In the highly scattering rat brain tissue, where multiply scattered photons falling within the temporal gate of the CGWS can no longer be neglected, we have measured known defocus and spherical aberrations up to a depth of 400 µm. PMID:23082292

Measuring aberrations in the rat brain by coherence-gated wavefront sensing using a Linnik interferometer.

PubMed

Wang, Jinyu; Léger, Jean-François; Binding, Jonas; Boccara, A Claude; Gigan, Sylvain; Bourdieu, Laurent

2012-10-01

Aberrations limit the resolution, signal intensity and achievable imaging depth in microscopy. Coherence-gated wavefront sensing (CGWS) allows the fast measurement of aberrations in scattering samples and therefore the implementation of adaptive corrections. However, CGWS has been demonstrated so far only in weakly scattering samples. We designed a new CGWS scheme based on a Linnik interferometer and a SLED light source, which is able to compensate dispersion automatically and can be implemented on any microscope. In the highly scattering rat brain tissue, where multiply scattered photons falling within the temporal gate of the CGWS can no longer be neglected, we have measured known defocus and spherical aberrations up to a depth of 400 µm.

Sensor selection and chemo-sensory optimization: toward an adaptable chemo-sensory system.

PubMed

Vergara, Alexander; Llobet, Eduard

2011-01-01

Over the past two decades, despite the tremendous research on chemical sensors and machine olfaction to develop micro-sensory systems that will accomplish the growing existent needs in personal health (implantable sensors), environment monitoring (widely distributed sensor networks), and security/threat detection (chemo/bio warfare agents), simple, low-cost molecular sensing platforms capable of long-term autonomous operation remain beyond the current state-of-the-art of chemical sensing. A fundamental issue within this context is that most of the chemical sensors depend on interactions between the targeted species and the surfaces functionalized with receptors that bind the target species selectively, and that these binding events are coupled with transduction processes that begin to change when they are exposed to the messy world of real samples. With the advent of fundamental breakthroughs at the intersection of materials science, micro- and nano-technology, and signal processing, hybrid chemo-sensory systems have incorporated tunable, optimizable operating parameters, through which changes in the response characteristics can be modeled and compensated as the environmental conditions or application needs change. The objective of this article, in this context, is to bring together the key advances at the device, data processing, and system levels that enable chemo-sensory systems to "adapt" in response to their environments. Accordingly, in this review we will feature the research effort made by selected experts on chemical sensing and information theory, whose work has been devoted to develop strategies that provide tunability and adaptability to single sensor devices or sensory array systems. Particularly, we consider sensor-array selection, modulation of internal sensing parameters, and active sensing. The article ends with some conclusions drawn from the results presented and a visionary look toward the future in terms of how the field may evolve.

A novel multi-scale adaptive sampling-based approach for energy saving in leak detection for WSN-based water pipelines

NASA Astrophysics Data System (ADS)

Saqib, Najam us; Faizan Mysorewala, Muhammad; Cheded, Lahouari

2017-12-01

In this paper, we propose a novel monitoring strategy for a wireless sensor networks (WSNs)-based water pipeline network. Our strategy uses a multi-pronged approach to reduce energy consumption based on the use of two types of vibration sensors and pressure sensors, all having different energy levels, and a hierarchical adaptive sampling mechanism to determine the sampling frequency. The sampling rate of the sensors is adjusted according to the bandwidth of the vibration signal being monitored by using a wavelet-based adaptive thresholding scheme that calculates the new sampling frequency for the following cycle. In this multimodal sensing scheme, the duty-cycling approach is used for all sensors to reduce the sampling instances, such that the high-energy, high-precision (HE-HP) vibration sensors have low duty cycles, and the low-energy, low-precision (LE-LP) vibration sensors have high duty cycles. The low duty-cycling (HE-HP) vibration sensor adjusts the sampling frequency of the high duty-cycling (LE-LP) vibration sensor. The simulated test bed considered here consists of a water pipeline network which uses pressure and vibration sensors, with the latter having different energy consumptions and precision levels, at various locations in the network. This is all the more useful for energy conservation for extended monitoring. It is shown that by using the novel features of our proposed scheme, a significant reduction in energy consumption is achieved and the leak is effectively detected by the sensor node that is closest to it. Finally, both the total energy consumed by monitoring as well as the time to detect the leak by a WSN node are computed, and show the superiority of our proposed hierarchical adaptive sampling algorithm over a non-adaptive sampling approach.

Blind compressed sensing image reconstruction based on alternating direction method

NASA Astrophysics Data System (ADS)

Liu, Qinan; Guo, Shuxu

2018-04-01

In order to solve the problem of how to reconstruct the original image under the condition of unknown sparse basis, this paper proposes an image reconstruction method based on blind compressed sensing model. In this model, the image signal is regarded as the product of a sparse coefficient matrix and a dictionary matrix. Based on the existing blind compressed sensing theory, the optimal solution is solved by the alternative minimization method. The proposed method solves the problem that the sparse basis in compressed sensing is difficult to represent, which restrains the noise and improves the quality of reconstructed image. This method ensures that the blind compressed sensing theory has a unique solution and can recover the reconstructed original image signal from a complex environment with a stronger self-adaptability. The experimental results show that the image reconstruction algorithm based on blind compressed sensing proposed in this paper can recover high quality image signals under the condition of under-sampling.

Colorimetric and Fluorescent Dual Mode Sensing of Alcoholic Strength in Spirit Samples with Stimuli-Responsive Infinite Coordination Polymers.

PubMed

Deng, Jingjing; Ma, Wenjie; Yu, Ping; Mao, Lanqun

2015-07-07

This study demonstrates a new strategy for colorimetric and fluorescent dual mode sensing of alcoholic strength (AS) in spirit samples based on stimuli-responsive infinite coordination polymers (ICPs). The ICP supramolecular network is prepared with 1,4-bis(imidazol-1-ylmethyl)benzene (bix) as the ligand and Zn(2+) as the central metal ion in ethanol, in which rhodamine B (RhB) is encapsulated through self-adaptive chemistry. In pure ethanol solvent, the as-formed RhB/Zn(bix) is well dispersed and quite stable. However, the addition of water into the ethanol dispersion of RhB/Zn(bix) destroys Zn(bix) network structure, resulting in the release of RhB from ICP into the solvent. As a consequence, the solvent displays the color of released RhB and, at the meantime, turns on the fluorescence of RhB, which constitutes a new mechanism for colorimetric and fluorescent dual mode sensing of AS in commercial spirit samples. With the method developed here, we could distinguish the AS of different commercial spirit samples by the naked eye within a wide linear range from 20 to 100% vol and by monitoring the increase of fluorescent intensity of the released RhB. This study not only offers a new method for on-spot visible detection of AS in commercial spirit samples, but also provides a strategy for designing dual mode sensing mechanisms for different analytical purposes based on novel stimuli-responsive materials.

Under-sampling trajectory design for compressed sensing based DCE-MRI.

PubMed

Liu, Duan-duan; Liang, Dong; Zhang, Na; Liu, Xin; Zhang, Yuan-ting

2013-01-01

Dynamic contrast-enhanced magnetic resonance imaging (DCE-MRI) needs high temporal and spatial resolution to accurately estimate quantitative parameters and characterize tumor vasculature. Compressed Sensing (CS) has the potential to accomplish this mutual importance. However, the randomness in CS under-sampling trajectory designed using the traditional variable density (VD) scheme may translate to uncertainty in kinetic parameter estimation when high reduction factors are used. Therefore, accurate parameter estimation using VD scheme usually needs multiple adjustments on parameters of Probability Density Function (PDF), and multiple reconstructions even with fixed PDF, which is inapplicable for DCE-MRI. In this paper, an under-sampling trajectory design which is robust to the change on PDF parameters and randomness with fixed PDF is studied. The strategy is to adaptively segment k-space into low-and high frequency domain, and only apply VD scheme in high-frequency domain. Simulation results demonstrate high accuracy and robustness comparing to VD design.

Digital adaptive optics line-scanning confocal imaging system.

PubMed

Liu, Changgeng; Kim, Myung K

2015-01-01

A digital adaptive optics line-scanning confocal imaging (DAOLCI) system is proposed by applying digital holographic adaptive optics to a digital form of line-scanning confocal imaging system. In DAOLCI, each line scan is recorded by a digital hologram, which allows access to the complex optical field from one slice of the sample through digital holography. This complex optical field contains both the information of one slice of the sample and the optical aberration of the system, thus allowing us to compensate for the effect of the optical aberration, which can be sensed by a complex guide star hologram. After numerical aberration compensation, the corrected optical fields of a sequence of line scans are stitched into the final corrected confocal image. In DAOLCI, a numerical slit is applied to realize the confocality at the sensor end. The width of this slit can be adjusted to control the image contrast and speckle noise for scattering samples. DAOLCI dispenses with the hardware pieces, such as Shack–Hartmann wavefront sensor and deformable mirror, and the closed-loop feedbacks adopted in the conventional adaptive optics confocal imaging system, thus reducing the optomechanical complexity and cost. Numerical simulations and proof-of-principle experiments are presented that demonstrate the feasibility of this idea.

Cognitive Nonlinear Radar

DTIC Science & Technology

2013-01-01

intelligently selecting waveform parameters using adaptive algorithms. The adaptive algorithms optimize the waveform parameters based on (1) the EM...the environment. 15. SUBJECT TERMS cognitive radar, adaptive sensing, spectrum sensing, multi-objective optimization, genetic algorithms, machine...detection and classification block diagram. .........................................................6 Figure 5. Genetic algorithm block diagram

Deep learning with domain adaptation for accelerated projection-reconstruction MR.

PubMed

Han, Yoseob; Yoo, Jaejun; Kim, Hak Hee; Shin, Hee Jung; Sung, Kyunghyun; Ye, Jong Chul

2018-09-01

The radial k-space trajectory is a well-established sampling trajectory used in conjunction with magnetic resonance imaging. However, the radial k-space trajectory requires a large number of radial lines for high-resolution reconstruction. Increasing the number of radial lines causes longer acquisition time, making it more difficult for routine clinical use. On the other hand, if we reduce the number of radial lines, streaking artifact patterns are unavoidable. To solve this problem, we propose a novel deep learning approach with domain adaptation to restore high-resolution MR images from under-sampled k-space data. The proposed deep network removes the streaking artifacts from the artifact corrupted images. To address the situation given the limited available data, we propose a domain adaptation scheme that employs a pre-trained network using a large number of X-ray computed tomography (CT) or synthesized radial MR datasets, which is then fine-tuned with only a few radial MR datasets. The proposed method outperforms existing compressed sensing algorithms, such as the total variation and PR-FOCUSS methods. In addition, the calculation time is several orders of magnitude faster than the total variation and PR-FOCUSS methods. Moreover, we found that pre-training using CT or MR data from similar organ data is more important than pre-training using data from the same modality for different organ. We demonstrate the possibility of a domain-adaptation when only a limited amount of MR data is available. The proposed method surpasses the existing compressed sensing algorithms in terms of the image quality and computation time. © 2018 International Society for Magnetic Resonance in Medicine.

ARGOS wavefront sensing: from detection to correction

NASA Astrophysics Data System (ADS)

Orban de Xivry, Gilles; Bonaglia, M.; Borelli, J.; Busoni, L.; Connot, C.; Esposito, S.; Gaessler, W.; Kulas, M.; Mazzoni, T.; Puglisi, A.; Rabien, S.; Storm, J.; Ziegleder, J.

2014-08-01

Argos is the ground-layer adaptive optics system for the Large Binocular Telescope. In order to perform its wide-field correction, Argos uses three laser guide stars which sample the atmospheric turbulence. To perform the correction, Argos has at disposal three different wavefront sensing measurements : its three laser guide stars, a NGS tip-tilt, and a third wavefront sensor. We present the wavefront sensing architecture and its individual components, in particular: the finalized Argos pnCCD camera detecting the 3 laser guide stars at 1kHz, high quantum efficiency and 4e- noise; the Argos tip-tilt sensor based on a quad-cell avalanche photo-diodes; and the Argos wavefront computer. Being in the middle of the commissioning, we present the first wavefront sensing configurations and operations performed at LBT, and discuss further improvements in the measurements of the 3 laser guide star slopes as detected by the pnCCD.

Measurement of specimen-induced aberrations of biological samples using phase stepping interferometry.

PubMed

Schwertner, M; Booth, M J; Neil, M A A; Wilson, T

2004-01-01

Confocal or multiphoton microscopes, which deliver optical sections and three-dimensional (3D) images of thick specimens, are widely used in biology. These techniques, however, are sensitive to aberrations that may originate from the refractive index structure of the specimen itself. The aberrations cause reduced signal intensity and the 3D resolution of the instrument is compromised. It has been suggested to correct for aberrations in confocal microscopes using adaptive optics. In order to define the design specifications for such adaptive optics systems, one has to know the amount of aberrations present for typical applications such as with biological samples. We have built a phase stepping interferometer microscope that directly measures the aberration of the wavefront. The modal content of the wavefront is extracted by employing Zernike mode decomposition. Results for typical biological specimens are presented. It was found for all samples investigated that higher order Zernike modes give only a small contribution to the overall aberration. Therefore, these higher order modes can be neglected in future adaptive optics sensing and correction schemes implemented into confocal or multiphoton microscopes, leading to more efficient designs.

[Application of remote sensing and GIS in study of suitability distribution of Swertia mussotii, a Tibetan medicine in Sichuan province].

PubMed

Dong, Yong-Bo; Luo, Yao; Zhu, Cong; Peng, Wen-Fu; Xu, Xin-Liang; Fang, Qing-Mao

2017-11-01

Swertia mussotii is a kind of rare medicinal materials, the relevant researches are mainly concentrated on its medicinal efficacy and medicinal value till now, researches of adaptive distribution by applying remote sensing and GIS are relatively less. This study is to analyze the adaptive distribution of S.mussotii in Sichuan province by applying remote sensing and GIS technology, and provide scientific basis for the protection and development of wild resources, artificial cultivation and adjustment of Chinese medicine industrial distribution in Sichuan province. Based on literature review and ecological factors such as altitude, annual precipitation and annual average temperature, this study extracted ecological factors, overlay analysis in GIS, as well as combining GPS field validation data by means of remote sensing and GIS, discusses the adaptive distribution of SMF sin Sichuan province. ①The area of adaptive distribution of S. mussotii in Sichuan province is 1 543.749 km², mainly in Dege county, Ganzi county, Daofu county, Kangding county, Barkam, Jinchuan county, Xiaojin county, Danba county, Daocheng county, Xiangcheng county, Xinlong county, Aba county, Muli county and other counties and cities, accounts for about 7.25% in total area. ② Combining statistical information and field validation, this study found that S. mussotii adaptive distribution gained by remote sensing and GIS is in conformity with its actual distribution. The study shows that remote sensing and GIS technology are feasible to obtain the S. mussotii adaptive distribution, they can further be applied to studies on adaptive distributions of other rare Chinese medicinal herb. Copyright© by the Chinese Pharmaceutical Association.

Cultural adaptation and psychometric properties of the family questionnaire in a Brazilian sample of relatives of schizophrenia outpatients.

PubMed

Zanetti, Ana C G; Wiedemann, Georg; Dantas, Rosana A S; Hayashida, Miyeko; de Azevedo-Marques, João M; Galera, Sueli A F

2013-06-01

To evaluate the internal reliability and validity of the Brazilian Portuguese version of the Family Questionnaire among families of schizophrenia outpatients. The main studies about the family environment of schizophrenia patients are related to the concept of Expressed Emotion. There is currently no instrument to evaluate this concept in Brazil that is easily applicable and comparable with studies from other countries. Methodological and cross-sectional research design. A convenience sample of 130 relatives of schizophrenia outpatients was selected. The translation and cultural adaptation of the instrument involved experts in mental health and experts in the German language and included back translation, semantic evaluation of items and pretesting of the instrument with 30 relatives of schizophrenia outpatients. The psychometric properties of the instrument were studied with another 100 relatives, which fulfilled the requirements for the Brazilian Portuguese version of the instrument. The psychometric properties of the instrument were assessed by construct validity (using an analysis of its key components, comparisons between distinct groups-convergent validity with the Antonovsky's Sense of Coherence Scale) and reliability (checking the internal consistency of its items and its test-retest reproducibility). The analysis of main components confirmed dimensionality patterns that were comparable between the original and adapted versions. In two domains of the instrument, critical comments and emotional over-involvement had moderate and significant correlations, respectively, with Antonovsky's Sense of Coherence Scale, appropriate values of Cronbach's alpha and strong and significant correlations, respectively, in test-retest reproducibility. We observed significant differences between distinct groups of parents in the category of emotional over-involvement. We conclude that the Portuguese-adapted version of the Family Questionnaire is valid and reliable for the study sample. This study provided evidence that the Family Questionnaire is a reliable and valid instrument for assessing expressed emotion. It is easy and practical to use and is acceptable for use in a Brazilian cultural population. © 2012 Blackwell Publishing Ltd.

Adaptive Transcutaneous Power Transfer to Implantable Devices: A State of the Art Review

PubMed Central

Bocan, Kara N.; Sejdić, Ervin

2016-01-01

Wireless energy transfer is a broad research area that has recently become applicable to implantable medical devices. Wireless powering of and communication with implanted devices is possible through wireless transcutaneous energy transfer. However, designing wireless transcutaneous systems is complicated due to the variability of the environment. The focus of this review is on strategies to sense and adapt to environmental variations in wireless transcutaneous systems. Adaptive systems provide the ability to maintain performance in the face of both unpredictability (variation from expected parameters) and variability (changes over time). Current strategies in adaptive (or tunable) systems include sensing relevant metrics to evaluate the function of the system in its environment and adjusting control parameters according to sensed values through the use of tunable components. Some challenges of applying adaptive designs to implantable devices are challenges common to all implantable devices, including size and power reduction on the implant, efficiency of power transfer and safety related to energy absorption in tissue. Challenges specifically associated with adaptation include choosing relevant and accessible parameters to sense and adjust, minimizing the tuning time and complexity of control, utilizing feedback from the implanted device and coordinating adaptation at the transmitter and receiver. PMID:26999154

Adaptive Transcutaneous Power Transfer to Implantable Devices: A State of the Art Review.

PubMed

Bocan, Kara N; Sejdić, Ervin

2016-03-18

Wireless energy transfer is a broad research area that has recently become applicable to implantable medical devices. Wireless powering of and communication with implanted devices is possible through wireless transcutaneous energy transfer. However, designing wireless transcutaneous systems is complicated due to the variability of the environment. The focus of this review is on strategies to sense and adapt to environmental variations in wireless transcutaneous systems. Adaptive systems provide the ability to maintain performance in the face of both unpredictability (variation from expected parameters) and variability (changes over time). Current strategies in adaptive (or tunable) systems include sensing relevant metrics to evaluate the function of the system in its environment and adjusting control parameters according to sensed values through the use of tunable components. Some challenges of applying adaptive designs to implantable devices are challenges common to all implantable devices, including size and power reduction on the implant, efficiency of power transfer and safety related to energy absorption in tissue. Challenges specifically associated with adaptation include choosing relevant and accessible parameters to sense and adjust, minimizing the tuning time and complexity of control, utilizing feedback from the implanted device and coordinating adaptation at the transmitter and receiver.

Compressed sensing system considerations for ECG and EMG wireless biosensors.

PubMed

Dixon, Anna M R; Allstot, Emily G; Gangopadhyay, Daibashish; Allstot, David J

2012-04-01

Compressed sensing (CS) is an emerging signal processing paradigm that enables sub-Nyquist processing of sparse signals such as electrocardiogram (ECG) and electromyogram (EMG) biosignals. Consequently, it can be applied to biosignal acquisition systems to reduce the data rate to realize ultra-low-power performance. CS is compared to conventional and adaptive sampling techniques and several system-level design considerations are presented for CS acquisition systems including sparsity and compression limits, thresholding techniques, encoder bit-precision requirements, and signal recovery algorithms. Simulation studies show that compression factors greater than 16X are achievable for ECG and EMG signals with signal-to-quantization noise ratios greater than 60 dB.

TH-E-17A-06: Anatomical-Adaptive Compressed Sensing (AACS) Reconstruction for Thoracic 4-Dimensional Cone-Beam CT

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

Shieh, C; Kipritidis, J; OBrien, R

2014-06-15

Purpose: The Feldkamp-Davis-Kress (FDK) algorithm currently used for clinical thoracic 4-dimensional (4D) cone-beam CT (CBCT) reconstruction suffers from noise and streaking artifacts due to projection under-sampling. Compressed sensing theory enables reconstruction of under-sampled datasets via total-variation (TV) minimization, but TV-minimization algorithms such as adaptive-steepest-descent-projection-onto-convex-sets (ASD-POCS) often converge slowly and are prone to over-smoothing anatomical details. These disadvantages can be overcome by incorporating general anatomical knowledge via anatomy segmentation. Based on this concept, we have developed an anatomical-adaptive compressed sensing (AACS) algorithm for thoracic 4D-CBCT reconstruction. Methods: AACS is based on the ASD-POCS framework, where each iteration consists of a TV-minimizationmore » step and a data fidelity constraint step. Prior to every AACS iteration, four major thoracic anatomical structures - soft tissue, lungs, bony anatomy, and pulmonary details - were segmented from the updated solution image. Based on the segmentation, an anatomical-adaptive weighting was applied to the TV-minimization step, so that TV-minimization was enhanced at noisy/streaky regions and suppressed at anatomical structures of interest. The image quality and convergence speed of AACS was compared to conventional ASD-POCS using an XCAT digital phantom and a patient scan. Results: For the XCAT phantom, the AACS image represented the ground truth better than the ASD-POCS image, giving a higher structural similarity index (0.93 vs. 0.84) and lower absolute difference (1.1*10{sup 4} vs. 1.4*10{sup 4}). For the patient case, while both algorithms resulted in much less noise and streaking than FDK, the AACS image showed considerably better contrast and sharpness of the vessels, tumor, and fiducial marker than the ASD-POCS image. In addition, AACS converged over 50% faster than ASD-POCS in both cases. Conclusions: The proposed AACS algorithm was shown to reconstruct thoracic 4D-CBCT images more accurately and with faster convergence compared to ASD-POCS. The superior image quality and rapid convergence makes AACS promising for future clinical use.« less

Evolutionary Quantitative Genomics of Populus trichocarpa

PubMed Central

McKown, Athena D.; La Mantia, Jonathan; Guy, Robert D.; Ingvarsson, Pär K.; Hamelin, Richard; Mansfield, Shawn D.; Ehlting, Jürgen; Douglas, Carl J.; El-Kassaby, Yousry A.

2015-01-01

Forest trees generally show high levels of local adaptation and efforts focusing on understanding adaptation to climate will be crucial for species survival and management. Here, we address fundamental questions regarding the molecular basis of adaptation in undomesticated forest tree populations to past climatic environments by employing an integrative quantitative genetics and landscape genomics approach. Using this comprehensive approach, we studied the molecular basis of climate adaptation in 433 Populus trichocarpa (black cottonwood) genotypes originating across western North America. Variation in 74 field-assessed traits (growth, ecophysiology, phenology, leaf stomata, wood, and disease resistance) was investigated for signatures of selection (comparing Q ST -F ST) using clustering of individuals by climate of origin (temperature and precipitation). 29,354 SNPs were investigated employing three different outlier detection methods and marker-inferred relatedness was estimated to obtain the narrow-sense estimate of population differentiation in wild populations. In addition, we compared our results with previously assessed selection of candidate SNPs using the 25 topographical units (drainages) across the P. trichocarpa sampling range as population groupings. Narrow-sense Q ST for 53% of distinct field traits was significantly divergent from expectations of neutrality (indicating adaptive trait variation); 2,855 SNPs showed signals of diversifying selection and of these, 118 SNPs (within 81 genes) were associated with adaptive traits (based on significant Q ST). Many SNPs were putatively pleiotropic for functionally uncorrelated adaptive traits, such as autumn phenology, height, and disease resistance. Evolutionary quantitative genomics in P. trichocarpa provides an enhanced understanding regarding the molecular basis of climate-driven selection in forest trees and we highlight that important loci underlying adaptive trait variation also show relationship to climate of origin. We consider our approach the most comprehensive, as it uncovers the molecular mechanisms of adaptation using multiple methods and tests. We also provide a detailed outline of the required analyses for studying adaptation to the environment in a population genomics context to better understand the species’ potential adaptive capacity to future climatic scenarios. PMID:26599762

Career Adaptability Development in Adolescence: Multiple Predictors and Effect on Sense of Power and Life Satisfaction

ERIC Educational Resources Information Center

Hirschi, Andreas

2009-01-01

This longitudinal panel study investigated predictors of career adaptability development and its effect on development of sense of power and experience of life satisfaction among 330 Swiss eighth graders. A multivariate measure of career adaptability consisting of career choice readiness, planning, exploration, and confidence was applied. Based on…

Factors of caregiver burden and family functioning among Taiwanese family caregivers living with schizophrenia.

PubMed

Hsiao, Chiu-Yueh; Tsai, Yun-Fang

2015-06-01

To assess the degree of caregiver burden and family functioning among Taiwanese primary family caregivers of people with schizophrenia and to test its association with demographic characteristics, family demands, sense of coherence and family hardiness. Family caregiving is a great concern in mental illness. Yet, the correlates of caregiver burden and family functioning in primary family caregivers of individuals with schizophrenia still remain unclear. A cross-sectional descriptive study. A convenience sample of 137 primary family caregivers was recruited from two psychiatric outpatient clinics in Taiwan. Measures included a demographic information sheet and the Chinese versions of the Family Stressors Index, Family Strains Index, 13-item Sense of Coherence Scale, 18-item Caregiver Burden Scale, Family Hardiness Index and Family Adaptability, Partnership, Growth, Affection, and Resolve Index. Data analysis included descriptive statistics, Pearson's product-moment correlation coefficients, t-test, one-way analysis of variance and a stepwise multiple linear regression. Female caregivers, additional dependent relatives, increased family demands and decreased sense of coherence significantly increased caregiver burden, whereas siblings as caregivers reported lower degrees of burden than parental caregivers. Family caregivers with lower family demands, increased family hardiness and higher educational level had significantly enhanced family functioning. Sense of coherence was significantly correlated with family hardiness. Our findings highlighted the importance of sense of coherence and family hardiness in individual and family adaptation. Special attention needs to focus on therapeutic interventions that enhance sense of coherence and family hardiness, thereby improving the perception of burden of care and family functioning. Given the nature of family caregiving in schizophrenia, understanding of correlates of caregiver burden and family functioning would help provide useful avenues for the development of family-focused intervention in psychiatric mental health nursing practice. © 2014 John Wiley & Sons Ltd.

A NDVI assisted remote sensing image adaptive scale segmentation method

NASA Astrophysics Data System (ADS)

Zhang, Hong; Shen, Jinxiang; Ma, Yanmei

2018-03-01

Multiscale segmentation of images can effectively form boundaries of different objects with different scales. However, for the remote sensing image which widely coverage with complicated ground objects, the number of suitable segmentation scales, and each of the scale size is still difficult to be accurately determined, which severely restricts the rapid information extraction of the remote sensing image. A great deal of experiments showed that the normalized difference vegetation index (NDVI) can effectively express the spectral characteristics of a variety of ground objects in remote sensing images. This paper presents a method using NDVI assisted adaptive segmentation of remote sensing images, which segment the local area by using NDVI similarity threshold to iteratively select segmentation scales. According to the different regions which consist of different targets, different segmentation scale boundaries could be created. The experimental results showed that the adaptive segmentation method based on NDVI can effectively create the objects boundaries for different ground objects of remote sensing images.

Live imaging using adaptive optics with fluorescent protein guide-stars

PubMed Central

Tao, Xiaodong; Crest, Justin; Kotadia, Shaila; Azucena, Oscar; Chen, Diana C.; Sullivan, William; Kubby, Joel

2012-01-01

Spatially and temporally dependent optical aberrations induced by the inhomogeneous refractive index of live samples limit the resolution of live dynamic imaging. We introduce an adaptive optical microscope with a direct wavefront sensing method using a Shack-Hartmann wavefront sensor and fluorescent protein guide-stars for live imaging. The results of imaging Drosophila embryos demonstrate its ability to correct aberrations and achieve near diffraction limited images of medial sections of large Drosophila embryos. GFP-polo labeled centrosomes can be observed clearly after correction but cannot be observed before correction. Four dimensional time lapse images are achieved with the correction of dynamic aberrations. These studies also demonstrate that the GFP-tagged centrosome proteins, Polo and Cnn, serve as excellent biological guide-stars for adaptive optics based microscopy. PMID:22772285

Thriving and Adapting: Resilience, Sense of Community, and Syndemics among Young Black Gay and Bisexual Men.

PubMed

Reed, Sarah J; Miller, Robin Lin

2016-03-01

We examined resilience associated with the avoidance of psychosocial health conditions (i.e., syndemics) that increase vulnerability for HIV among young Black gay and bisexual men. We used analytic induction to compare a sample of 23 men who showed no evidence of syndemic conditions to a sample of 23 men who experienced syndemic conditions. The men who avoided syndemics reported supportive relationships with people who helped them to develop a strong sense of identity, provided them with opportunities to give back to their communities, and promoted positive norms about health. In contrast, the men experiencing syndemic conditions described numerous instances of trauma and oppression that infringed upon their desire to form positive relationships. Among these men, experiences of oppression were associated with shame, identity incongruence, social isolation, relational disconnection, mistrust of men, and expectations of further marginalization. We examined participants' experiences through the framework of the psychosocial sense of community. Results of this study provide evidence for using strength-based intervention strategies to prevent syndemic conditions. Findings suggest that to attenuate socio-structural barriers to health and comorbid psychosocial health concerns, interventions must address young men's social isolation and promote positive identity and sense of community. © Society for Community Research and Action 2016.

Advanced Soil Moisture Network Technologies; Developments in Collecting in situ Measurements for Remote Sensing Missions

NASA Astrophysics Data System (ADS)

Moghaddam, M.; Silva, A. R. D.; Akbar, R.; Clewley, D.

2015-12-01

The Soil moisture Sensing Controller And oPtimal Estimator (SoilSCAPE) wireless sensor network has been developed to support Calibration and Validation activities (Cal/Val) for large scale soil moisture remote sensing missions (SMAP and AirMOSS). The technology developed here also readily supports small scale hydrological studies by providing sub-kilometer widespread soil moisture observations. An extensive collection of semi-sparse sensor clusters deployed throughout north-central California and southern Arizona provide near real time soil moisture measurements. Such a wireless network architecture, compared to conventional single points measurement profiles, allows for significant and expanded soil moisture sampling. The work presented here aims at discussing and highlighting novel and new technology developments which increase in situ soil moisture measurements' accuracy, reliability, and robustness with reduced data delivery latency. High efficiency and low maintenance custom hardware have been developed and in-field performance has been demonstrated for a period of three years. The SoilSCAPE technology incorporates (a) intelligent sensing to prevent erroneous measurement reporting, (b) on-board short term memory for data redundancy, (c) adaptive scheduling and sampling capabilities to enhance energy efficiency. A rapid streamlined data delivery architecture openly provides distribution of in situ measurements to SMAP and AirMOSS cal/val activities and other interested parties.

MultiSense: A Multimodal Sensor Tool Enabling the High-Throughput Analysis of Respiration.

PubMed

Keil, Peter; Liebsch, Gregor; Borisjuk, Ljudmilla; Rolletschek, Hardy

2017-01-01

The high-throughput analysis of respiratory activity has become an important component of many biological investigations. Here, a technological platform, denoted the "MultiSense tool," is described. The tool enables the parallel monitoring of respiration in 100 samples over an extended time period, by dynamically tracking the concentrations of oxygen (O 2 ) and/or carbon dioxide (CO 2 ) and/or pH within an airtight vial. Its flexible design supports the quantification of respiration based on either oxygen consumption or carbon dioxide release, thereby allowing for the determination of the physiologically significant respiratory quotient (the ratio between the quantities of CO 2 released and the O 2 consumed). It requires an LED light source to be mounted above the sample, together with a CCD camera system, adjusted to enable the capture of analyte-specific wavelengths, and fluorescent sensor spots inserted into the sample vial. Here, a demonstration is given of the use of the MultiSense tool to quantify respiration in imbibing plant seeds, for which an appropriate step-by-step protocol is provided. The technology can be easily adapted for a wide range of applications, including the monitoring of gas exchange in any kind of liquid culture system (algae, embryo and tissue culture, cell suspensions, microbial cultures).

Improving the Forecast Accuracy of an Ocean Observation and Prediction System by Adaptive Control of the Sensor Network

NASA Astrophysics Data System (ADS)

Talukder, A.; Panangadan, A. V.; Blumberg, A. F.; Herrington, T.; Georgas, N.

2008-12-01

The New York Harbor Observation and Prediction System (NYHOPS) is a real-time, estuarine and coastal ocean observing and modeling system for the New York Harbor and surrounding waters. Real-time measurements from in-situ mobile and stationary sensors in the NYHOPS networks are assimilated into marine forecasts in order to reduce the discrepancy with ground truth. The forecasts are obtained from the ECOMSED hydrodynamic model, a shallow water derivative of the Princeton Ocean Model. Currently, all sensors in the NYHOPS system are operated in a fixed mode with uniform sampling rates. This technology infusion effort demonstrates the use of Model Predictive Control (MPC) to autonomously adapt the operation of both mobile and stationary sensors in response to changing events that are -automatically detected from the ECOMSED forecasts. The controller focuses sensing resources on those regions that are expected to be impacted by the detected events. The MPC approach involves formulating the problem of calculating the optimal sensor parameters as a constrained multi-objective optimization problem. We have developed an objective function that takes into account the spatiotemporal relationship of the in-situ sensor locations and the locations of events detected by the model. Experiments in simulation were carried out using data collected during a freshwater flooding event. The location of the resulting freshwater plume was calculated from the corresponding model forecasts and was used by the MPC controller to derive control parameters for the sensing assets. The operational parameters that are controlled include the sampling rates of stationary sensors, paths of unmanned underwater vehicles (UUVs), and data transfer routes between sensors and the central modeling computer. The simulation experiments show that MPC-based sensor control reduces the RMS error in the forecast by a factor of 380% as compared to uniform sampling. The paths of multiple UUVs were simultaneously calculated such that measurements from on-board sensors would lead to maximal reduction in the forecast error after data assimilation. The MPC controller also reduces the consumption of system resources such as energy expended in sampling and wireless communication. The MPC-based control approach can be generalized to accept data from remote sensing satellites. This will enable in-situ sensors to be regulated using forecasts generated by assimilating local high resolution in-situ measurements with wide-area observations from remote sensing satellites.

Topics in the two-dimensional sampling and reconstruction of images. [in remote sensing

NASA Technical Reports Server (NTRS)

Schowengerdt, R.; Gray, S.; Park, S. K.

1984-01-01

Mathematical analysis of image sampling and interpolative reconstruction is summarized and extended to two dimensions for application to data acquired from satellite sensors such as the Thematic mapper and SPOT. It is shown that sample-scene phase influences the reconstruction of sampled images, adds a considerable blur to the average system point spread function, and decreases the average system modulation transfer function. It is also determined that the parametric bicubic interpolator with alpha = -0.5 is more radiometrically accurate than the conventional bicubic interpolator with alpha = -1, and this at no additional cost. Finally, the parametric bicubic interpolator is found to be suitable for adaptive implementation by relating the alpha parameter to the local frequency content of an image.

Social Capital: Its Constructs and Survey Development

ERIC Educational Resources Information Center

Enfield, Richard P.; Nathaniel, Keith C.

2013-01-01

This article reports on experiences and methods of adapting a valid adult social capital assessment to youth audiences in order to measure social capital and sense of place. The authors outline the process of adapting, revising, prepiloting, piloting, and administering a youth survey exploring young people's sense of community, involvement in the…

Analyte sensing mediated by adapter/carrier molecules

DOEpatents

Bayley, Hagan; Braha, Orit; Gu, LiQun

2002-07-30

This invention relates to an improved method and system for sensing of one or more analytes. A host molecule, which serves as an adapter/carrier, is used to facilitate interaction between the analyte and the sensor element. A detectable signal is produced reflecting the identity and concentration of analyte present.

Sensor Selection and Chemo-Sensory Optimization: Toward an Adaptable Chemo-Sensory System

PubMed Central

Vergara, Alexander; Llobet, Eduard

2011-01-01

Over the past two decades, despite the tremendous research on chemical sensors and machine olfaction to develop micro-sensory systems that will accomplish the growing existent needs in personal health (implantable sensors), environment monitoring (widely distributed sensor networks), and security/threat detection (chemo/bio warfare agents), simple, low-cost molecular sensing platforms capable of long-term autonomous operation remain beyond the current state-of-the-art of chemical sensing. A fundamental issue within this context is that most of the chemical sensors depend on interactions between the targeted species and the surfaces functionalized with receptors that bind the target species selectively, and that these binding events are coupled with transduction processes that begin to change when they are exposed to the messy world of real samples. With the advent of fundamental breakthroughs at the intersection of materials science, micro- and nano-technology, and signal processing, hybrid chemo-sensory systems have incorporated tunable, optimizable operating parameters, through which changes in the response characteristics can be modeled and compensated as the environmental conditions or application needs change. The objective of this article, in this context, is to bring together the key advances at the device, data processing, and system levels that enable chemo-sensory systems to “adapt” in response to their environments. Accordingly, in this review we will feature the research effort made by selected experts on chemical sensing and information theory, whose work has been devoted to develop strategies that provide tunability and adaptability to single sensor devices or sensory array systems. Particularly, we consider sensor-array selection, modulation of internal sensing parameters, and active sensing. The article ends with some conclusions drawn from the results presented and a visionary look toward the future in terms of how the field may evolve. PMID:22319492

The relationship between motivational structure, sense of control, intrinsic motivation and university students' alcohol consumption.

PubMed

Shamloo, Zohreh Sepehri; Cox, W Miles

2010-02-01

The aim of this study was to determine how sense of control and intrinsic motivation are related to university students' motivational structure and alcohol consumption. Participants were 94 university students who completed the Personal Concerns Inventory, Shapiro Control Inventory, Helplessness Questionnaire, Intrinsic-Extrinsic Aspirations Scale, and Alcohol Use Questionnaire. Results showed that sense of control and intrinsic motivation were positively correlated with adaptive motivation and negatively correlated with alcohol consumption. Mediational analyses indicated that adaptive motivation fully mediated the relationship between sense of control/intrinsic motivation and alcohol consumption.

Practical considerations in experimental computational sensing

NASA Astrophysics Data System (ADS)

Poon, Phillip K.

Computational sensing has demonstrated the ability to ameliorate or eliminate many trade-offs in traditional sensors. Rather than attempting to form a perfect image, then sampling at the Nyquist rate, and reconstructing the signal of interest prior to post-processing, the computational sensor attempts to utilize a priori knowledge, active or passive coding of the signal-of-interest combined with a variety of algorithms to overcome the trade-offs or to improve various task-specific metrics. While it is a powerful approach to radically new sensor architectures, published research tends to focus on architecture concepts and positive results. Little attention is given towards the practical issues when faced with implementing computational sensing prototypes. I will discuss the various practical challenges that I encountered while developing three separate applications of computational sensors. The first is a compressive sensing based object tracking camera, the SCOUT, which exploits the sparsity of motion between consecutive frames while using no moving parts to create a psuedo-random shift variant point-spread function. The second is a spectral imaging camera, the AFSSI-C, which uses a modified version of Principal Component Analysis with a Bayesian strategy to adaptively design spectral filters for direct spectral classification using a digital micro-mirror device (DMD) based architecture. The third demonstrates two separate architectures to perform spectral unmixing by using an adaptive algorithm or a hybrid techniques of using Maximum Noise Fraction and random filter selection from a liquid crystal on silicon based computational spectral imager, the LCSI. All of these applications demonstrate a variety of challenges that have been addressed or continue to challenge the computational sensing community. One issue is calibration, since many computational sensors require an inversion step and in the case of compressive sensing, lack of redundancy in the measurement data. Another issue is over multiplexing, as more light is collected per sample, the finite amount of dynamic range and quantization resolution can begin to degrade the recovery of the relevant information. A priori knowledge of the sparsity and or other statistics of the signal or noise is often used by computational sensors to outperform their isomorphic counterparts. This is demonstrated in all three of the sensors I have developed. These challenges and others will be discussed using a case-study approach through these three applications.

Use of atmospheric backscattering for adaptive formation of the initial wave front of a laser beam by the method of aperture sensing

NASA Astrophysics Data System (ADS)

Gordeev, E. V.; Kuskov, V. V.; Razenkov, I. A.; Shesternin, A. N.

2017-11-01

The quality of adaptive suppression of initial aberrations of the wave front of a main laser beam with the use of the method of aperture sensing by the signal of atmospheric backscattering of the additional (sensing) laser radiation at a different wavelength has been studied experimentally. It is shown that wavefront distortions of the main laser beam were decreased significantly during the setup operation.

Infrared super-resolution imaging based on compressed sensing

NASA Astrophysics Data System (ADS)

Sui, Xiubao; Chen, Qian; Gu, Guohua; Shen, Xuewei

2014-03-01

The theoretical basis of traditional infrared super-resolution imaging method is Nyquist sampling theorem. The reconstruction premise is that the relative positions of the infrared objects in the low-resolution image sequences should keep fixed and the image restoration means is the inverse operation of ill-posed issues without fixed rules. The super-resolution reconstruction ability of the infrared image, algorithm's application area and stability of reconstruction algorithm are limited. To this end, we proposed super-resolution reconstruction method based on compressed sensing in this paper. In the method, we selected Toeplitz matrix as the measurement matrix and realized it by phase mask method. We researched complementary matching pursuit algorithm and selected it as the recovery algorithm. In order to adapt to the moving target and decrease imaging time, we take use of area infrared focal plane array to acquire multiple measurements at one time. Theoretically, the method breaks though Nyquist sampling theorem and can greatly improve the spatial resolution of the infrared image. The last image contrast and experiment data indicate that our method is effective in improving resolution of infrared images and is superior than some traditional super-resolution imaging method. The compressed sensing super-resolution method is expected to have a wide application prospect.

Sensing Free Sulfur Dioxide in Wine

PubMed Central

Monro, Tanya M.; Moore, Rachel L.; Nguyen, Mai-Chi; Ebendorff-Heidepriem, Heike; Skouroumounis, George K.; Elsey, Gordon M.; Taylor, Dennis K.

2012-01-01

Sulfur dioxide (SO2) is important in the winemaking process as it aids in preventing microbial growth and the oxidation of wine. These processes and others consume the SO2 over time, resulting in wines with little SO2 protection. Furthermore, SO2 and sulfiting agents are known to be allergens to many individuals and for that reason their levels need to be monitored and regulated in final wine products. Many of the current techniques for monitoring SO2 in wine require the SO2 to be separated from the wine prior to analysis. This investigation demonstrates a technique capable of measuring free sulfite concentrations in low volume liquid samples in white wine. This approach adapts a known colorimetric reaction to a suspended core optical fiber sensing platform, and exploits the interaction between guided light located within the fiber voids and a mixture of the wine sample and a colorimetric analyte. We have shown that this technique enables measurements to be made without dilution of the wine samples, thus paving the way towards real time in situ wine monitoring. PMID:23112627

A Novel approach to monitor chlorophyll-a concentration using an adaptive model from MODIS data at 250 metres spatial resolution

NASA Astrophysics Data System (ADS)

El Alem, A.; Chokmani, K.; Laurion, I.; El Adlouni, S.

2013-12-01

Occurrence and extent of Harmful Algal Bloom (HAB) has increased in inland water bodies around the world. The appearance of these blooms reflects the advanced state of eutrophication of several aquatic systems caused by urban, agricultural, and industrial development. Algal blooms, especially those cyanobacterial origins, are capable to produce and release toxins, threatening human and animal health, quality of drinking water, and recreational water bodies. Conventional monitoring networks, based on infrequent sampling in a few fixed monitoring stations, cannot provide the information needed as HABs are spatially and temporally heterogeneous. Remote sensing represents an interesting alternative to provide the required spatial and temporal coverage. The usefulness of air-borne and satellite remote sensing data to detect HABs was demonstrated since three decades ago, and since several empirical and semi-empirical models, using satellite imagery, were developed to estimate chlorophyll-a concentration [Chl-a] as a proxy to detect bloom proliferations. However, most of those models presented several weaknesses that are generally linked to the range of [Chl-a] to be estimated. Indeed, models originally calibrated for high [Chl-a] fail to estimate low concentrations and vice versa. In this study, an adaptive model to estimate [Chl-a], spread over a wide range of concentrations, is developed for optically complex inland water bodies based on combination of water spectral response classification and three developed semi-empirical algorithms using a multivariate regression. Three distinct water types (low, medium, and high [Chl-a]) are first identified using the Classification and Regression Tree (CART) method performed on remote sensing reflectance over a dataset of 44 [Chl-a] samples collected from Lakes over Quebec province. Based on the water classification, a specific multivariate model to each water type is developed using the same dataset and the MODIS data at 250-m spatial resolution. By pre-clustering inland water bodies, the results were very interesting as the determination coefficients as well as the relative RMSE of the cross-validation were of 0.99, 0.98 and 0.95 and of 0.5%, 8% and 17% for high, medium, and low [Chl-a], respectively. On the other hand, the adaptive model reached a global success rate of 92% using an independent, semi-qualitative, [Chl-a] samples collected over more than twenty inland water bodies for the years 2009 and 2010 over the Quebec province.

Contrast-based sensorless adaptive optics for retinal imaging.

PubMed

Zhou, Xiaolin; Bedggood, Phillip; Bui, Bang; Nguyen, Christine T O; He, Zheng; Metha, Andrew

2015-09-01

Conventional adaptive optics ophthalmoscopes use wavefront sensing methods to characterize ocular aberrations for real-time correction. However, there are important situations in which the wavefront sensing step is susceptible to difficulties that affect the accuracy of the correction. To circumvent these, wavefront sensorless adaptive optics (or non-wavefront sensing AO; NS-AO) imaging has recently been developed and has been applied to point-scanning based retinal imaging modalities. In this study we show, for the first time, contrast-based NS-AO ophthalmoscopy for full-frame in vivo imaging of human and animal eyes. We suggest a robust image quality metric that could be used for any imaging modality, and test its performance against other metrics using (physical) model eyes.

Active machine learning for rapid landslide inventory mapping with VHR satellite images (Invited)

NASA Astrophysics Data System (ADS)

Stumpf, A.; Lachiche, N.; Malet, J.; Kerle, N.; Puissant, A.

2013-12-01

VHR satellite images have become a primary source for landslide inventory mapping after major triggering events such as earthquakes and heavy rainfalls. Visual image interpretation is still the prevailing standard method for operational purposes but is time-consuming and not well suited to fully exploit the increasingly better supply of remote sensing data. Recent studies have addressed the development of more automated image analysis workflows for landslide inventory mapping. In particular object-oriented approaches that account for spatial and textural image information have been demonstrated to be more adequate than pixel-based classification but manually elaborated rule-based classifiers are difficult to adapt under changing scene characteristics. Machine learning algorithm allow learning classification rules for complex image patterns from labelled examples and can be adapted straightforwardly with available training data. In order to reduce the amount of costly training data active learning (AL) has evolved as a key concept to guide the sampling for many applications. The underlying idea of AL is to initialize a machine learning model with a small training set, and to subsequently exploit the model state and data structure to iteratively select the most valuable samples that should be labelled by the user. With relatively few queries and labelled samples, an AL strategy yields higher accuracies than an equivalent classifier trained with many randomly selected samples. This study addressed the development of an AL method for landslide mapping from VHR remote sensing images with special consideration of the spatial distribution of the samples. Our approach [1] is based on the Random Forest algorithm and considers the classifier uncertainty as well as the variance of potential sampling regions to guide the user towards the most valuable sampling areas. The algorithm explicitly searches for compact regions and thereby avoids a spatially disperse sampling pattern inherent to most other AL methods. The accuracy, the sampling time and the computational runtime of the algorithm were evaluated on multiple satellite images capturing recent large scale landslide events. Sampling between 1-4% of the study areas the accuracies between 74% and 80% were achieved, whereas standard sampling schemes yielded only accuracies between 28% and 50% with equal sampling costs. Compared to commonly used point-wise AL algorithm the proposed approach significantly reduces the number of iterations and hence the computational runtime. Since the user can focus on relatively few compact areas (rather than on hundreds of distributed points) the overall labeling time is reduced by more than 50% compared to point-wise queries. An experimental evaluation of multiple expert mappings demonstrated strong relationships between the uncertainties of the experts and the machine learning model. It revealed that the achieved accuracies are within the range of the inter-expert disagreement and that it will be indispensable to consider ground truth uncertainties to truly achieve further enhancements in the future. The proposed method is generally applicable to a wide range of optical satellite images and landslide types. [1] A. Stumpf, N. Lachiche, J.-P. Malet, N. Kerle, and A. Puissant, Active learning in the spatial domain for remote sensing image classification, IEEE Transactions on Geosciece and Remote Sensing. 2013, DOI 10.1109/TGRS.2013.2262052.

Biodiversity and agriculture in dynamic landscapes: Integrating ground and remotely-sensed baseline surveys.

PubMed

Gillison, Andrew N; Asner, Gregory P; Fernandes, Erick C M; Mafalacusser, Jacinto; Banze, Aurélio; Izidine, Samira; da Fonseca, Ambrósio R; Pacate, Hermenegildo

2016-07-15

Sustainable biodiversity and land management require a cost-effective means of forecasting landscape response to environmental change. Conventional species-based, regional biodiversity assessments are rarely adequate for policy planning and decision making. We show how new ground and remotely-sensed survey methods can be coordinated to help elucidate and predict relationships between biodiversity, land use and soil properties along complex biophysical gradients that typify many similar landscapes worldwide. In the lower Zambezi valley, Mozambique we used environmental, gradient-directed transects (gradsects) to sample vascular plant species, plant functional types, vegetation structure, soil properties and land-use characteristics. Soil fertility indices were derived using novel multidimensional scaling of soil properties. To facilitate spatial analysis, we applied a probabilistic remote sensing approach, analyzing Landsat 7 satellite imagery to map photosynthetically active and inactive vegetation and bare soil along each gradsect. Despite the relatively low sample number, we found highly significant correlations between single and combined sets of specific plant, soil and remotely sensed variables that permitted testable spatial projections of biodiversity and soil fertility across the regional land-use mosaic. This integrative and rapid approach provides a low-cost, high-return and readily transferable methodology that permits the ready identification of testable biodiversity indicators for adaptive management of biodiversity and potential agricultural productivity. Copyright © 2016 Elsevier Ltd. All rights reserved.

Making Sense by Building Sense: Kindergarten Children's Construction and Understanding of Adaptive Robot Behaviors

ERIC Educational Resources Information Center

Mioduser, David; Levy, Sharona T.

2010-01-01

This study explores young children's ability to construct and explain adaptive behaviors of a behaving artifact, an autonomous mobile robot with sensors. A central component of the behavior construction environment is the RoboGan software that supports children's construction of spatiotemporal events with an a-temporal rule structure. Six…

Optimized quantum sensing with a single electron spin using real-time adaptive measurements.

PubMed

Bonato, C; Blok, M S; Dinani, H T; Berry, D W; Markham, M L; Twitchen, D J; Hanson, R

2016-03-01

Quantum sensors based on single solid-state spins promise a unique combination of sensitivity and spatial resolution. The key challenge in sensing is to achieve minimum estimation uncertainty within a given time and with high dynamic range. Adaptive strategies have been proposed to achieve optimal performance, but their implementation in solid-state systems has been hindered by the demanding experimental requirements. Here, we realize adaptive d.c. sensing by combining single-shot readout of an electron spin in diamond with fast feedback. By adapting the spin readout basis in real time based on previous outcomes, we demonstrate a sensitivity in Ramsey interferometry surpassing the standard measurement limit. Furthermore, we find by simulations and experiments that adaptive protocols offer a distinctive advantage over the best known non-adaptive protocols when overhead and limited estimation time are taken into account. Using an optimized adaptive protocol we achieve a magnetic field sensitivity of 6.1 ± 1.7 nT Hz(-1/2) over a wide range of 1.78 mT. These results open up a new class of experiments for solid-state sensors in which real-time knowledge of the measurement history is exploited to obtain optimal performance.

Optimized quantum sensing with a single electron spin using real-time adaptive measurements

NASA Astrophysics Data System (ADS)

Bonato, C.; Blok, M. S.; Dinani, H. T.; Berry, D. W.; Markham, M. L.; Twitchen, D. J.; Hanson, R.

2016-03-01

Quantum sensors based on single solid-state spins promise a unique combination of sensitivity and spatial resolution. The key challenge in sensing is to achieve minimum estimation uncertainty within a given time and with high dynamic range. Adaptive strategies have been proposed to achieve optimal performance, but their implementation in solid-state systems has been hindered by the demanding experimental requirements. Here, we realize adaptive d.c. sensing by combining single-shot readout of an electron spin in diamond with fast feedback. By adapting the spin readout basis in real time based on previous outcomes, we demonstrate a sensitivity in Ramsey interferometry surpassing the standard measurement limit. Furthermore, we find by simulations and experiments that adaptive protocols offer a distinctive advantage over the best known non-adaptive protocols when overhead and limited estimation time are taken into account. Using an optimized adaptive protocol we achieve a magnetic field sensitivity of 6.1 ± 1.7 nT Hz-1/2 over a wide range of 1.78 mT. These results open up a new class of experiments for solid-state sensors in which real-time knowledge of the measurement history is exploited to obtain optimal performance.

RZA-NLMF algorithm-based adaptive sparse sensing for realizing compressive sensing

NASA Astrophysics Data System (ADS)

Gui, Guan; Xu, Li; Adachi, Fumiyuki

2014-12-01

Nonlinear sparse sensing (NSS) techniques have been adopted for realizing compressive sensing in many applications such as radar imaging. Unlike the NSS, in this paper, we propose an adaptive sparse sensing (ASS) approach using the reweighted zero-attracting normalized least mean fourth (RZA-NLMF) algorithm which depends on several given parameters, i.e., reweighted factor, regularization parameter, and initial step size. First, based on the independent assumption, Cramer-Rao lower bound (CRLB) is derived as for the performance comparisons. In addition, reweighted factor selection method is proposed for achieving robust estimation performance. Finally, to verify the algorithm, Monte Carlo-based computer simulations are given to show that the ASS achieves much better mean square error (MSE) performance than the NSS.

Multiplatform Mission Planning and Operations Simulation Environment for Adaptive Remote Sensors

NASA Astrophysics Data System (ADS)

Smith, G.; Ball, C.; O'Brien, A.; Johnson, J. T.

2017-12-01

We report on the design and development of mission simulator libraries to support the emerging field of adaptive remote sensors. We will outline the current state of the art in adaptive sensing, provide analysis of how the current approach to performing observing system simulation experiments (OSSEs) must be changed to enable adaptive sensors for remote sensing, and present an architecture to enable their inclusion in future OSSEs.The growing potential of sensors capable of real-time adaptation of their operational parameters calls for a new class of mission planning and simulation tools. Existing simulation tools used in OSSEs assume a fixed set of sensor parameters in terms of observation geometry, frequencies used, resolution, or observation time, which allows simplifications to be made in the simulation and allows sensor observation errors to be characterized a priori. Adaptive sensors may vary these parameters depending on the details of the scene observed, so that sensor performance is not simple to model without conducting OSSE simulations that include sensor adaptation in response to varying observational environment. Adaptive sensors are of significance to resource-constrained, small satellite platforms because they enable the management of power and data volumes while providing methods for multiple sensors to collaborate.The new class of OSSEs required to utilize adaptive sensors located on multiple platforms must answer the question: If the physical act of sensing has a cost, how does the system determine if the science value of a measurement is worth the cost and how should that cost be shared among the collaborating sensors?Here we propose to answer this question using an architecture structured around three modules: ADAPT, MANAGE and COLLABORATE. The ADAPT module is a set of routines to facilitate modeling of adaptive sensors, the MANAGE module will implement a set of routines to facilitate simulations of sensor resource management when power and data volume are constrained, and the COLLABORATE module will support simulations of coordination among multiple platforms with adaptive sensors. When used together these modules will for a simulation OSSEs that can enable both the design of adaptive algorithms to support remote sensing and the prediction of the sensor performance.

Deep neural network-based domain adaptation for classification of remote sensing images

NASA Astrophysics Data System (ADS)

Ma, Li; Song, Jiazhen

2017-10-01

We investigate the effectiveness of deep neural network for cross-domain classification of remote sensing images in this paper. In the network, class centroid alignment is utilized as a domain adaptation strategy, making the network able to transfer knowledge from the source domain to target domain on a per-class basis. Since predicted labels of target data should be used to estimate the centroid of each class, we use overall centroid alignment as a coarse domain adaptation method to improve the estimation accuracy. In addition, rectified linear unit is used as the activation function to produce sparse features, which may improve the separation capability. The proposed network can provide both aligned features and an adaptive classifier, as well as obtain label-free classification of target domain data. The experimental results using Hyperion, NCALM, and WorldView-2 remote sensing images demonstrated the effectiveness of the proposed approach.

Adaptive optics for array telescopes using piston-and-tilt wave-front sensing

NASA Technical Reports Server (NTRS)

Wizinowich, P.; Mcleod, B.; Lloyd-Yhart, M.; Angel, J. R. P.; Colucci, D.; Dekany, R.; Mccarthy, D.; Wittman, D.; Scott-Fleming, I.

1992-01-01

A near-infrared adaptive optics system operating at about 50 Hz has been used to control phase errors adaptively between two mirrors of the Multiple Mirror Telescope by stabilizing the position of the interference fringe in the combined unresolved far-field image. The resultant integrated images have angular resolutions of better than 0.1 arcsec and fringe contrasts of more than 0.6. Measurements of wave-front tilt have confirmed the wavelength independence of image motion. These results show that interferometric sensing of phase errors, when combined with a system for sensing the wave-front tilt of the individual telescopes, will provide a means of achieving a stable diffraction-limited focus with segmented telescopes or arrays of telescopes.

Contrast-based sensorless adaptive optics for retinal imaging

PubMed Central

Zhou, Xiaolin; Bedggood, Phillip; Bui, Bang; Nguyen, Christine T.O.; He, Zheng; Metha, Andrew

2015-01-01

Conventional adaptive optics ophthalmoscopes use wavefront sensing methods to characterize ocular aberrations for real-time correction. However, there are important situations in which the wavefront sensing step is susceptible to difficulties that affect the accuracy of the correction. To circumvent these, wavefront sensorless adaptive optics (or non-wavefront sensing AO; NS-AO) imaging has recently been developed and has been applied to point-scanning based retinal imaging modalities. In this study we show, for the first time, contrast-based NS-AO ophthalmoscopy for full-frame in vivo imaging of human and animal eyes. We suggest a robust image quality metric that could be used for any imaging modality, and test its performance against other metrics using (physical) model eyes. PMID:26417525

Volatile organic compound sensing devices

DOEpatents

Lancaster, G.D.; Moore, G.A.; Stone, M.L.; Reagen, W.K.

1995-08-29

Apparatus employing vapochromic materials in the form of inorganic double complex salts which change color reversibly when exposed to volatile organic compound (VOC) vapors is adapted for VOC vapor detection, VOC aqueous matrix detection, and selective VOC vapor detection. The basic VOC vapochromic sensor is incorporated in various devices such as a ground probe sensor, a wristband sensor, a periodic sampling monitor, a soil/water penetrometer, an evaporative purge sensor, and various vacuum-based sensors which are particularly adapted for reversible/reusable detection, remote detection, continuous monitoring, or rapid screening of environmental remediation and waste management sites. The vapochromic sensor is used in combination with various fiber optic arrangements to provide a calibrated qualitative and/or quantitative indication of the presence of VOCs. 15 figs.

Volatile organic compound sensing devices

DOEpatents

Lancaster, Gregory D.; Moore, Glenn A.; Stone, Mark L.; Reagen, William K.

1995-01-01

Apparatus employing vapochromic materials in the form of inorganic double complex salts which change color reversibly when exposed to volatile organic compound (VOC) vapors is adapted for VOC vapor detection, VOC aqueous matrix detection, and selective VOC vapor detection. The basic VOC vapochromic sensor is incorporated in various devices such as a ground probe sensor, a wristband sensor, a periodic sampling monitor, a soil/water penetrometer, an evaporative purge sensor, and various vacuum-based sensors which are particularly adapted for reversible/reusable detection, remote detection, continuous monitoring, or rapid screening of environmental remediation and waste management sites. The vapochromic sensor is used in combination with various fiber optic arrangements to provide a calibrated qualitative and/or quantitative indication of the presence of VOCs.

Climate Change Adaptation Science Activities at NASA Johnson Space Center

NASA Technical Reports Server (NTRS)

Stefanov, William L.; Lulla, Kamlesh

2012-01-01

The Johnson Space Center (JSC), located in the southeast metropolitan region of Houston, TX is the prime NASA center for human spaceflight operations and astronaut training, but it also houses the unique collection of returned extraterrestrial samples, including lunar samples from the Apollo missions. The Center's location adjacent to Clear Lake and the Clear Creek watershed, an estuary of Galveston Bay, puts it at direct annual risk from hurricanes, but also from a number of other climate-related hazards including drought, floods, sea level rise, heat waves, and high wind events all assigned Threat Levels of 2 or 3 in the most recent NASA Center Disaster/Risk Matrix produced by the Climate Adaptation Science Investigator Working Group. Based on prior CASI workshops at other NASA centers, it is recognized that JSC is highly vulnerable to climate-change related hazards and has a need for adaptation strategies. We will present an overview of prior CASI-related work at JSC, including publication of a climate change and adaptation informational data brochure, and a Resilience and Adaptation to Climate Risks Workshop that was held at JSC in early March 2012. Major outcomes of that workshop that form a basis for work going forward are 1) a realization that JSC is embedded in a regional environmental and social context, and that potential climate change effects and adaptation strategies will not, and should not, be constrained by the Center fence line; 2) a desire to coordinate data collection and adaptation planning activities with interested stakeholders to form a regional climate change adaptation center that could facilitate interaction with CASI; 3) recognition that there is a wide array of basic data (remotely sensed, in situ, GIS/mapping, and historical) available through JSC and other stakeholders, but this data is not yet centrally accessible for planning purposes.

Motion Coordination and Adaptation Using Deception and Human Interactions

DTIC Science & Technology

2016-11-18

evolves an interface (front) by embedding it as a hyper - surface in a higher dimension, where time is the augmented dimension. Automatic handling of...the open- loop system trajectories. The results are depicted in Fig. 32. From the shape of the value function in Fig. 32(b) it is seen that the value is...estimate of the value function only over the area of the state space visited by the sampled (open- loop ) trajectories. In that sense, the areas not

Autonomous Sensing of Layered Structures in Hawaiian Waters

DTIC Science & Technology

2008-01-01

layers in the sea. APPROACH In March of 2007 we were awarded $112,842 for the fabrication of an autonomous profiler (the SeaHorse ) for the...detection of thin layers of phytoplankton in the coastal ocean. The SeaHorse (Figures 1, 2) makes use of wave energy to power extended, high-resolution...to adaptively change the sample rate of the SeaHorse profiler itself. For example, if we observe a layer at 10 m depth, we can instruct the profiler

Adaptive MCS selection and resource planning for energy-efficient communication in LTE-M based IoT sensing platform.

PubMed

Dao, Nhu-Ngoc; Park, Minho; Kim, Joongheon; Cho, Sungrae

2017-01-01

As an important part of IoTization trends, wireless sensing technologies have been involved in many fields of human life. In cellular network evolution, the long term evolution advanced (LTE-A) networks including machine-type communication (MTC) features (named LTE-M) provide a promising infrastructure for a proliferation of Internet of things (IoT) sensing platform. However, LTE-M may not be optimally exploited for directly supporting such low-data-rate devices in terms of energy efficiency since it depends on core technologies of LTE that are originally designed for high-data-rate services. Focusing on this circumstance, we propose a novel adaptive modulation and coding selection (AMCS) algorithm to address the energy consumption problem in the LTE-M based IoT-sensing platform. The proposed algorithm determines the optimal pair of MCS and the number of primary resource blocks (#PRBs), at which the transport block size is sufficient to packetize the sensing data within the minimum transmit power. In addition, a quantity-oriented resource planning (QORP) technique that utilizes these optimal MCS levels as main criteria for spectrum allocation has been proposed for better adapting to the sensing node requirements. The simulation results reveal that the proposed approach significantly reduces the energy consumption of IoT sensing nodes and #PRBs up to 23.09% and 25.98%, respectively.

Adaptive MCS selection and resource planning for energy-efficient communication in LTE-M based IoT sensing platform

PubMed Central

Dao, Nhu-Ngoc; Park, Minho; Kim, Joongheon

2017-01-01

As an important part of IoTization trends, wireless sensing technologies have been involved in many fields of human life. In cellular network evolution, the long term evolution advanced (LTE-A) networks including machine-type communication (MTC) features (named LTE-M) provide a promising infrastructure for a proliferation of Internet of things (IoT) sensing platform. However, LTE-M may not be optimally exploited for directly supporting such low-data-rate devices in terms of energy efficiency since it depends on core technologies of LTE that are originally designed for high-data-rate services. Focusing on this circumstance, we propose a novel adaptive modulation and coding selection (AMCS) algorithm to address the energy consumption problem in the LTE-M based IoT-sensing platform. The proposed algorithm determines the optimal pair of MCS and the number of primary resource blocks (#PRBs), at which the transport block size is sufficient to packetize the sensing data within the minimum transmit power. In addition, a quantity-oriented resource planning (QORP) technique that utilizes these optimal MCS levels as main criteria for spectrum allocation has been proposed for better adapting to the sensing node requirements. The simulation results reveal that the proposed approach significantly reduces the energy consumption of IoT sensing nodes and #PRBs up to 23.09% and 25.98%, respectively. PMID:28796804

Piezoelectric self-sensing actuator for active vibration control of motorized spindle based on adaptive signal separation

NASA Astrophysics Data System (ADS)

He, Ye; Chen, Xiaoan; Liu, Zhi; Qin, Yi

2018-06-01

The motorized spindle is the core component of CNC machine tools, and the vibration of it reduces the machining precision and service life of the machine tools. Owing to the fast response, large output force, and displacement of the piezoelectric stack, it is often used as the actuator in the active vibration control of the spindle. A piezoelectric self-sensing actuator (SSA) can reduce the cost of the active vibration control system and simplify the structure by eliminating the use of a sensor, because a SSA can have both actuating and sensing functions at the same time. The signal separation method of a SSA based on a bridge circuit is widely applied because of its simple principle and easy implementation. However, it is difficult to maintain dynamic balance of the circuit. Prior research has used adaptive algorithm to balance of the bridge circuit on the flexible beam dynamically, but those algorithms need no correlation between sensing and control voltage, which limit the applications of SSA in the vibration control of the rotor-bearing system. Here, the electromechanical coupling model of the piezoelectric stack is established, followed by establishment of the dynamic model of the spindle system. Next, a new adaptive signal separation method based on the bridge circuit is proposed, which can separate relative small sensing voltage from related mixed voltage adaptively. The experimental results show that when the self-sensing signal obtained from the proposed method is used as a displacement signal, the vibration of the motorized spindle can be suppressed effectively through a linear quadratic Gaussian (LQG) algorithm.

Efficient Compressed Sensing Based MRI Reconstruction using Nonconvex Total Variation Penalties

NASA Astrophysics Data System (ADS)

Lazzaro, D.; Loli Piccolomini, E.; Zama, F.

2016-10-01

This work addresses the problem of Magnetic Resonance Image Reconstruction from highly sub-sampled measurements in the Fourier domain. It is modeled as a constrained minimization problem, where the objective function is a non-convex function of the gradient of the unknown image and the constraints are given by the data fidelity term. We propose an algorithm, Fast Non Convex Reweighted (FNCR), where the constrained problem is solved by a reweighting scheme, as a strategy to overcome the non-convexity of the objective function, with an adaptive adjustment of the penalization parameter. We propose a fast iterative algorithm and we can prove that it converges to a local minimum because the constrained problem satisfies the Kurdyka-Lojasiewicz property. Moreover the adaptation of non convex l0 approximation and penalization parameters, by means of a continuation technique, allows us to obtain good quality solutions, avoiding to get stuck in unwanted local minima. Some numerical experiments performed on MRI sub-sampled data show the efficiency of the algorithm and the accuracy of the solution.

Translational Imaging Spectroscopy for Proximal Sensing

PubMed Central

Rogass, Christian; Koerting, Friederike M.; Mielke, Christian; Brell, Maximilian; Boesche, Nina K.; Bade, Maria; Hohmann, Christian

2017-01-01

Proximal sensing as the near field counterpart of remote sensing offers a broad variety of applications. Imaging spectroscopy in general and translational laboratory imaging spectroscopy in particular can be utilized for a variety of different research topics. Geoscientific applications require a precise pre-processing of hyperspectral data cubes to retrieve at-surface reflectance in order to conduct spectral feature-based comparison of unknown sample spectra to known library spectra. A new pre-processing chain called GeoMAP-Trans for at-surface reflectance retrieval is proposed here as an analogue to other algorithms published by the team of authors. It consists of a radiometric, a geometric and a spectral module. Each module consists of several processing steps that are described in detail. The processing chain was adapted to the broadly used HySPEX VNIR/SWIR imaging spectrometer system and tested using geological mineral samples. The performance was subjectively and objectively evaluated using standard artificial image quality metrics and comparative measurements of mineral and Lambertian diffuser standards with standard field and laboratory spectrometers. The proposed algorithm provides highly qualitative results, offers broad applicability through its generic design and might be the first one of its kind to be published. A high radiometric accuracy is achieved by the incorporation of the Reduction of Miscalibration Effects (ROME) framework. The geometric accuracy is higher than 1 μpixel. The critical spectral accuracy was relatively estimated by comparing spectra of standard field spectrometers to those from HySPEX for a Lambertian diffuser. The achieved spectral accuracy is better than 0.02% for the full spectrum and better than 98% for the absorption features. It was empirically shown that point and imaging spectrometers provide different results for non-Lambertian samples due to their different sensing principles, adjacency scattering impacts on the signal and anisotropic surface reflection properties. PMID:28800111

Drought Management Activities of the National Drought Mitigation Center (NDMC): Contributions Toward a Global Drought Early Warning System (GDEWS)

NASA Astrophysics Data System (ADS)

Stumpf, A.; Lachiche, N.; Malet, J.; Kerle, N.; Puissant, A.

2011-12-01

VHR satellite images have become a primary source for landslide inventory mapping after major triggering events such as earthquakes and heavy rainfalls. Visual image interpretation is still the prevailing standard method for operational purposes but is time-consuming and not well suited to fully exploit the increasingly better supply of remote sensing data. Recent studies have addressed the development of more automated image analysis workflows for landslide inventory mapping. In particular object-oriented approaches that account for spatial and textural image information have been demonstrated to be more adequate than pixel-based classification but manually elaborated rule-based classifiers are difficult to adapt under changing scene characteristics. Machine learning algorithm allow learning classification rules for complex image patterns from labelled examples and can be adapted straightforwardly with available training data. In order to reduce the amount of costly training data active learning (AL) has evolved as a key concept to guide the sampling for many applications. The underlying idea of AL is to initialize a machine learning model with a small training set, and to subsequently exploit the model state and data structure to iteratively select the most valuable samples that should be labelled by the user. With relatively few queries and labelled samples, an AL strategy yields higher accuracies than an equivalent classifier trained with many randomly selected samples. This study addressed the development of an AL method for landslide mapping from VHR remote sensing images with special consideration of the spatial distribution of the samples. Our approach [1] is based on the Random Forest algorithm and considers the classifier uncertainty as well as the variance of potential sampling regions to guide the user towards the most valuable sampling areas. The algorithm explicitly searches for compact regions and thereby avoids a spatially disperse sampling pattern inherent to most other AL methods. The accuracy, the sampling time and the computational runtime of the algorithm were evaluated on multiple satellite images capturing recent large scale landslide events. Sampling between 1-4% of the study areas the accuracies between 74% and 80% were achieved, whereas standard sampling schemes yielded only accuracies between 28% and 50% with equal sampling costs. Compared to commonly used point-wise AL algorithm the proposed approach significantly reduces the number of iterations and hence the computational runtime. Since the user can focus on relatively few compact areas (rather than on hundreds of distributed points) the overall labeling time is reduced by more than 50% compared to point-wise queries. An experimental evaluation of multiple expert mappings demonstrated strong relationships between the uncertainties of the experts and the machine learning model. It revealed that the achieved accuracies are within the range of the inter-expert disagreement and that it will be indispensable to consider ground truth uncertainties to truly achieve further enhancements in the future. The proposed method is generally applicable to a wide range of optical satellite images and landslide types. [1] A. Stumpf, N. Lachiche, J.-P. Malet, N. Kerle, and A. Puissant, Active learning in the spatial domain for remote sensing image classification, IEEE Transactions on Geosciece and Remote Sensing. 2013, DOI 10.1109/TGRS.2013.2262052.

Towards a Cognitive Radar: Canada's Third-Generation High Frequency Surface Wave Radar (HFSWR) for Surveillance of the 200 Nautical Mile Exclusive Economic Zone.

PubMed

Ponsford, Anthony; McKerracher, Rick; Ding, Zhen; Moo, Peter; Yee, Derek

2017-07-07

Canada's third-generation HFSWR forms the foundation of a maritime domain awareness system that provides enforcement agencies with real-time persistent surveillance out to and beyond the 200 nautical mile exclusive economic zone (EEZ). Cognitive sense-and-adapt technology and dynamic spectrum management ensures robust and resilient operation in the highly congested High Frequency (HF) band. Dynamic spectrum access enables the system to simultaneously operate on two frequencies on a non-interference and non-protected basis, without impacting other spectrum users. Sense-and-adapt technologies ensure that the system instantaneously switches to a new vacant channel on the detection of another user or unwanted jamming signal. Adaptive signal processing techniques mitigate against electrical noise, interference and clutter. Sense-and-adapt techniques applied at the detector and tracker stages maximize the probability of track initiation whilst minimizing the probability of false or otherwise erroneous track data.

Signaling Network of Environmental Sensing and Adaptation in Plants:. Key Roles of Calcium Ion

NASA Astrophysics Data System (ADS)

Kurusu, Takamitsu; Kuchitsu, Kazuyuki

2011-01-01

Considering the important issues concerning food, environment, and energy that humans are facing in the 21st century, humans mostly depend on plants. Unlike animals which move from an inappropriate environment, plants do not move, but rapidly sense diverse environmental changes or invasion by other organisms such as pathogens and insects in the place they root, and adapt themselves by changing their own bodies, through which they developed adaptability. Whole genetic information corresponding to the blueprints of many biological systems has recently been analyzed, and comparative genomic studies facilitated tracing strategies of each organism in their evolutional processes. Comparison of factors involved in intracellular signal transduction between animals and plants indicated diversification of different gene sets. Reversible binding of Ca2+ to sensor proteins play key roles as a molecular switch both in animals and plants. Molecular mechanisms for signaling network of environmental sensing and adaptation in plants will be discussed with special reference to Ca2+ as a key element in information processing.

Towards a Cognitive Radar: Canada’s Third-Generation High Frequency Surface Wave Radar (HFSWR) for Surveillance of the 200 Nautical Mile Exclusive Economic Zone

PubMed Central

Ponsford, Anthony; McKerracher, Rick; Ding, Zhen; Moo, Peter; Yee, Derek

2017-01-01

Canada’s third-generation HFSWR forms the foundation of a maritime domain awareness system that provides enforcement agencies with real-time persistent surveillance out to and beyond the 200 nautical mile exclusive economic zone (EEZ). Cognitive sense-and-adapt technology and dynamic spectrum management ensures robust and resilient operation in the highly congested High Frequency (HF) band. Dynamic spectrum access enables the system to simultaneously operate on two frequencies on a non-interference and non-protected basis, without impacting other spectrum users. Sense-and-adapt technologies ensure that the system instantaneously switches to a new vacant channel on the detection of another user or unwanted jamming signal. Adaptive signal processing techniques mitigate against electrical noise, interference and clutter. Sense-and-adapt techniques applied at the detector and tracker stages maximize the probability of track initiation whilst minimizing the probability of false or otherwise erroneous track data. PMID:28686198

Action Enhances Acoustic Cues for 3-D Target Localization by Echolocating Bats

PubMed Central

Wohlgemuth, Melville J.

2016-01-01

Under natural conditions, animals encounter a barrage of sensory information from which they must select and interpret biologically relevant signals. Active sensing can facilitate this process by engaging motor systems in the sampling of sensory information. The echolocating bat serves as an excellent model to investigate the coupling between action and sensing because it adaptively controls both the acoustic signals used to probe the environment and movements to receive echoes at the auditory periphery. We report here that the echolocating bat controls the features of its sonar vocalizations in tandem with the positioning of the outer ears to maximize acoustic cues for target detection and localization. The bat’s adaptive control of sonar vocalizations and ear positioning occurs on a millisecond timescale to capture spatial information from arriving echoes, as well as on a longer timescale to track target movement. Our results demonstrate that purposeful control over sonar sound production and reception can serve to improve acoustic cues for localization tasks. This finding also highlights the general importance of movement to sensory processing across animal species. Finally, our discoveries point to important parallels between spatial perception by echolocation and vision. PMID:27608186

An optimal stratified Simon two-stage design.

PubMed

Parashar, Deepak; Bowden, Jack; Starr, Colin; Wernisch, Lorenz; Mander, Adrian

2016-07-01

In Phase II oncology trials, therapies are increasingly being evaluated for their effectiveness in specific populations of interest. Such targeted trials require designs that allow for stratification based on the participants' molecular characterisation. A targeted design proposed by Jones and Holmgren (JH) Jones CL, Holmgren E: 'An adaptive Simon two-stage design for phase 2 studies of targeted therapies', Contemporary Clinical Trials 28 (2007) 654-661.determines whether a drug only has activity in a disease sub-population or in the wider disease population. Their adaptive design uses results from a single interim analysis to decide whether to enrich the study population with a subgroup or not; it is based on two parallel Simon two-stage designs. We study the JH design in detail and extend it by providing a few alternative ways to control the familywise error rate, in the weak sense as well as the strong sense. We also introduce a novel optimal design by minimising the expected sample size. Our extended design contributes to the much needed framework for conducting Phase II trials in stratified medicine. © 2016 The Authors Pharmaceutical Statistics Published by John Wiley & Sons Ltd. © 2016 The Authors Pharmaceutical Statistics Published by John Wiley & Sons Ltd.

Adaptive multifocus image fusion using block compressed sensing with smoothed projected Landweber integration in the wavelet domain.

PubMed

V S, Unni; Mishra, Deepak; Subrahmanyam, G R K S

2016-12-01

The need for image fusion in current image processing systems is increasing mainly due to the increased number and variety of image acquisition techniques. Image fusion is the process of combining substantial information from several sensors using mathematical techniques in order to create a single composite image that will be more comprehensive and thus more useful for a human operator or other computer vision tasks. This paper presents a new approach to multifocus image fusion based on sparse signal representation. Block-based compressive sensing integrated with a projection-driven compressive sensing (CS) recovery that encourages sparsity in the wavelet domain is used as a method to get the focused image from a set of out-of-focus images. Compression is achieved during the image acquisition process using a block compressive sensing method. An adaptive thresholding technique within the smoothed projected Landweber recovery process reconstructs high-resolution focused images from low-dimensional CS measurements of out-of-focus images. Discrete wavelet transform and dual-tree complex wavelet transform are used as the sparsifying basis for the proposed fusion. The main finding lies in the fact that sparsification enables a better selection of the fusion coefficients and hence better fusion. A Laplacian mixture model fit is done in the wavelet domain and estimation of the probability density function (pdf) parameters by expectation maximization leads us to the proper selection of the coefficients of the fused image. Using the proposed method compared with the fusion scheme without employing the projected Landweber (PL) scheme and the other existing CS-based fusion approaches, it is observed that with fewer samples itself, the proposed method outperforms other approaches.

Absorbance and fluorometric sensing with capillary wells microplates.

PubMed

Tan, Han Yen; Cheong, Brandon Huey-Ping; Neild, Adrian; Liew, Oi Wah; Ng, Tuck Wah

2010-12-01

Detection and readout from small volume assays in microplates are a challenge. The capillary wells microplate approach [Ng et al., Appl. Phys. Lett. 93, 174105 (2008)] offers strong advantages in small liquid volume management. An adapted design is described and shown here to be able to detect, in a nonimaging manner, fluorescence and absorbance assays minus the error often associated with meniscus forming at the air-liquid interface. The presence of bubbles in liquid samples residing in microplate wells can cause inaccuracies. Pipetting errors, if not adequately managed, can result in misleading data and wrong interpretations of assay results; particularly in the context of high throughput screening. We show that the adapted design is also able to detect for bubbles and pipetting errors during actual assay runs to ensure accuracy in screening.

Stress and family quality of life in parents of children with autism spectrum disorder: parent gender and the double ABCX model.

PubMed

McStay, Rebecca L; Trembath, David; Dissanayake, Cheryl

2014-12-01

Past research has supported the utility of the Double ABCX model of family adaptation for parents raising a child with autism spectrum disorder (ASD). What remains unclear is the impact of family-related variables on outcomes in both mothers and fathers within the same family. We explored the potential predictors of maternal and paternal stress and family quality of life in an Australian sample of 196 parents of children with ASD aged 3-16 years. Using a cross-sectional design, parents completed questionnaires assessing factors within the Double ABCX model attributed to family adaptation. Findings provide further evidence of the negative impact of child externalising behaviours and highlight the importance of family sense of coherence on positive parental outcomes.

Ocean Observing Public-Private Collaboration to Improve Tropical Storm and Hurricane Predictions in the Gulf of Mexico

NASA Astrophysics Data System (ADS)

Perry, R.; Leung, P.; McCall, W.; Martin, K. M.; Howden, S. D.; Vandermeulen, R. A.; Kim, H. S. S.; Kirkpatrick, B. A.; Watson, S.; Smith, W.

2016-02-01

In 2008, Shell partnered with NOAA to explore opportunities for improving storm predictions in the Gulf of Mexico. Since, the collaboration has grown to include partners from Shell, NOAA National Data Buoy Center and National Center for Environmental Information, National Center for Environmental Prediction, University of Southern Mississippi, and the Gulf of Mexico Coastal Ocean Observing System. The partnership leverages complementary strengths of each collaborator to build a comprehensive and sustainable monitoring and data program to expand observing capacity and protect offshore assets and Gulf communities from storms and hurricanes. The program combines in situ and autonomous platforms with remote sensing and numerical modeling. Here we focus on profiling gliders and the benefits of a public-private partnership model for expanding regional ocean observing capacity. Shallow and deep gliders measure ocean temperature to derive ocean heat content (OHC), along with salinity, dissolved oxygen, fluorescence, and CDOM, in the central and eastern Gulf shelf and offshore. Since 2012, gliders have collected 4500+ vertical profiles and surveyed 5000+ nautical miles. Adaptive sampling and mission coordination with NCEP modelers provides specific datasets to assimilate into EMC's coupled HYCOM-HWRF model and 'connect-the-dots' between well-established Eulerian metocean measurements by obtaining (and validating) data between fixed stations (e.g. platform and buoy ADCPs) . Adaptive sampling combined with remote sensing provides satellite-derived OHC validation and the ability to sample productive coastal waters advected offshore by the Loop Current. Tracking coastal waters with remote sensing provides another verification of estimate Loop Current and eddy boundaries, as well as quantifying productivity and analyzing water quality on the Gulf coast, shelf break and offshore. Incorporating gliders demonstrates their value as tools to better protect offshore oil and gas assets and the greater Gulf coast communities from storms and hurricanes. Data collected under the collaboration, along with deployment of gliders, will have long-term benefits in helping to understand the ecological and environmental health of the Gulf by monitoring real-time annual and seasonal physical variability.

An open trial assessment of "The Number Race", an adaptive computer game for remediation of dyscalculia

PubMed Central

Wilson, Anna J; Revkin, Susannah K; Cohen, David; Cohen, Laurent; Dehaene, Stanislas

2006-01-01

Background In a companion article [1], we described the development and evaluation of software designed to remediate dyscalculia. This software is based on the hypothesis that dyscalculia is due to a "core deficit" in number sense or in its access via symbolic information. Here we review the evidence for this hypothesis, and present results from an initial open-trial test of the software in a sample of nine 7–9 year old children with mathematical difficulties. Methods Children completed adaptive training on numerical comparison for half an hour a day, four days a week over a period of five-weeks. They were tested before and after intervention on their performance in core numerical tasks: counting, transcoding, base-10 comprehension, enumeration, addition, subtraction, and symbolic and non-symbolic numerical comparison. Results Children showed specific increases in performance on core number sense tasks. Speed of subitizing and numerical comparison increased by several hundred msec. Subtraction accuracy increased by an average of 23%. Performance on addition and base-10 comprehension tasks did not improve over the period of the study. Conclusion Initial open-trial testing showed promising results, and suggested that the software was successful in increasing number sense over the short period of the study. However these results need to be followed up with larger, controlled studies. The issues of transfer to higher-level tasks, and of the best developmental time window for intervention also need to be addressed. PMID:16734906

Convolutional neural network using generated data for SAR ATR with limited samples

NASA Astrophysics Data System (ADS)

Cong, Longjian; Gao, Lei; Zhang, Hui; Sun, Peng

2018-03-01

Being able to adapt all weather at all times, it has been a hot research topic that using Synthetic Aperture Radar(SAR) for remote sensing. Despite all the well-known advantages of SAR, it is hard to extract features because of its unique imaging methodology, and this challenge attracts the research interest of traditional Automatic Target Recognition(ATR) methods. With the development of deep learning technologies, convolutional neural networks(CNNs) give us another way out to detect and recognize targets, when a huge number of samples are available, but this premise is often not hold, when it comes to monitoring a specific type of ships. In this paper, we propose a method to enhance the performance of Faster R-CNN with limited samples to detect and recognize ships in SAR images.

The Adaptation of Scale of School as a Caring Community Profile for Secondary School Students into Turkish: Adaptation of School as a Caring Community Scale

ERIC Educational Resources Information Center

Çinkir, Sakir; Nayir, K. Funda; Çetin, Saadet Kuru

2016-01-01

Schools are social organizations where children came together from different cultures. Creating sense of community is important for schools for the formation of social culture. In schools where sense of community is formed, it is observed that students treat each other with respect, are caring and sharing and have high academic success, and rates…

Adaptive Bayes classifiers for remotely sensed data

NASA Technical Reports Server (NTRS)

Raulston, H. S.; Pace, M. O.; Gonzalez, R. C.

1975-01-01

An algorithm is developed for a learning, adaptive, statistical pattern classifier for remotely sensed data. The estimation procedure consists of two steps: (1) an optimal stochastic approximation of the parameters of interest, and (2) a projection of the parameters in time and space. The results reported are for Gaussian data in which the mean vector of each class may vary with time or position after the classifier is trained.

An adaptive inverse kinematics algorithm for robot manipulators

NASA Technical Reports Server (NTRS)

Colbaugh, R.; Glass, K.; Seraji, H.

1990-01-01

An adaptive algorithm for solving the inverse kinematics problem for robot manipulators is presented. The algorithm is derived using model reference adaptive control (MRAC) theory and is computationally efficient for online applications. The scheme requires no a priori knowledge of the kinematics of the robot if Cartesian end-effector sensing is available, and it requires knowledge of only the forward kinematics if joint position sensing is used. Computer simulation results are given for the redundant seven-DOF robotics research arm, demonstrating that the proposed algorithm yields accurate joint angle trajectories for a given end-effector position/orientation trajectory.

Gait Phase Estimation Based on Noncontact Capacitive Sensing and Adaptive Oscillators.

PubMed

Zheng, Enhao; Manca, Silvia; Yan, Tingfang; Parri, Andrea; Vitiello, Nicola; Wang, Qining

2017-10-01

This paper presents a novel strategy aiming to acquire an accurate and walking-speed-adaptive estimation of the gait phase through noncontact capacitive sensing and adaptive oscillators (AOs). The capacitive sensing system is designed with two sensing cuffs that can measure the leg muscle shape changes during walking. The system can be dressed above the clothes and free human skin from contacting to electrodes. In order to track the capacitance signals, the gait phase estimator is designed based on the AO dynamic system due to its ability of synchronizing with quasi-periodic signals. After the implementation of the whole system, we first evaluated the offline estimation performance by experiments with 12 healthy subjects walking on a treadmill with changing speeds. The strategy achieved an accurate and consistent gait phase estimation with only one channel of capacitance signal. The average root-mean-square errors in one stride were 0.19 rad (3.0% of one gait cycle) for constant walking speeds and 0.31 rad (4.9% of one gait cycle) for speed transitions even after the subjects rewore the sensing cuffs. We then validated our strategy in a real-time gait phase estimation task with three subjects walking with changing speeds. Our study indicates that the strategy based on capacitive sensing and AOs is a promising alternative for the control of exoskeleton/orthosis.

Adaptation of trees, forests and forestry to climate change

Treesearch

Daniel J. Chmura; Glenn T. Howe; Paul D. Anderson; Bradley J. St Clair

2010-01-01

Ongoing climate change will likely expose trees and forests to new stresses and disturbances during this century. Trees naturally adapt to changes in climate, but their natural adaptive ability may be compromised by the rapid changes projected for this century. In the broad sense, adaptation to climate change also includes the purposeful adaptation of human systems,...

On the search for extant life on Mars

NASA Technical Reports Server (NTRS)

Klein, H. P.

1996-01-01

Proposals for continuing the search for extant life on Mars are primarily predicated on the assumption that specialized environmental niches that could support a biota may exist on the planet. Before attempting any critical tests for extant organisms, either in situ or on returned samples, it is imperative to determine whether any such sites actually exist. If, through remote sensing and landed instrumentation, sites of potential biological interest are discovered and characterized, biological tests can then more effectively be planned to elicit the presence of organisms that are adapted to living in these particular environments.

On the search for extant life on Mars.

PubMed

Klein, H P

1996-01-01

Proposals for continuing the search for extant life on Mars are primarily predicated on the assumption that specialized environmental niches that could support a biota may exist on the planet. Before attempting any critical tests for extant organisms, either in situ or on returned samples, it is imperative to determine whether any such sites actually exist. If, through remote sensing and landed instrumentation, sites of potential biological interest are discovered and characterized, biological tests can then more effectively be planned to elicit the presence of organisms that are adapted to living in these particular environments.

High-Resolution Adaptive Optics Test-Bed for Vision Science

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

Wilks, S C; Thomspon, C A; Olivier, S S

2001-09-27

We discuss the design and implementation of a low-cost, high-resolution adaptive optics test-bed for vision research. It is well known that high-order aberrations in the human eye reduce optical resolution and limit visual acuity. However, the effects of aberration-free eyesight on vision are only now beginning to be studied using adaptive optics to sense and correct the aberrations in the eye. We are developing a high-resolution adaptive optics system for this purpose using a Hamamatsu Parallel Aligned Nematic Liquid Crystal Spatial Light Modulator. Phase-wrapping is used to extend the effective stroke of the device, and the wavefront sensing and wavefrontmore » correction are done at different wavelengths. Issues associated with these techniques will be discussed.« less

Adaptation of sensor morphology: an integrative view of perception from biologically inspired robotics perspective

PubMed Central

Nurzaman, Surya G.

2016-01-01

Sensor morphology, the morphology of a sensing mechanism which plays a role of shaping the desired response from physical stimuli from surroundings to generate signals usable as sensory information, is one of the key common aspects of sensing processes. This paper presents a structured review of researches on bioinspired sensor morphology implemented in robotic systems, and discusses the fundamental design principles. Based on literature review, we propose two key arguments: first, owing to its synthetic nature, biologically inspired robotics approach is a unique and powerful methodology to understand the role of sensor morphology and how it can evolve and adapt to its task and environment. Second, a consideration of an integrative view of perception by looking into multidisciplinary and overarching mechanisms of sensor morphology adaptation across biology and engineering enables us to extract relevant design principles that are important to extend our understanding of the unfinished concepts in sensing and perception. PMID:27499843

A neural algorithm for the non-uniform and adaptive sampling of biomedical data.

PubMed

Mesin, Luca

2016-04-01

Body sensors are finding increasing applications in the self-monitoring for health-care and in the remote surveillance of sensitive people. The physiological data to be sampled can be non-stationary, with bursts of high amplitude and frequency content providing most information. Such data could be sampled efficiently with a non-uniform schedule that increases the sampling rate only during activity bursts. A real time and adaptive algorithm is proposed to select the sampling rate, in order to reduce the number of measured samples, but still recording the main information. The algorithm is based on a neural network which predicts the subsequent samples and their uncertainties, requiring a measurement only when the risk of the prediction is larger than a selectable threshold. Four examples of application to biomedical data are discussed: electromyogram, electrocardiogram, electroencephalogram, and body acceleration. Sampling rates are reduced under the Nyquist limit, still preserving an accurate representation of the data and of their power spectral densities (PSD). For example, sampling at 60% of the Nyquist frequency, the percentage average rectified errors in estimating the signals are on the order of 10% and the PSD is fairly represented, until the highest frequencies. The method outperforms both uniform sampling and compressive sensing applied to the same data. The discussed method allows to go beyond Nyquist limit, still preserving the information content of non-stationary biomedical signals. It could find applications in body sensor networks to lower the number of wireless communications (saving sensor power) and to reduce the occupation of memory. Copyright © 2016 Elsevier Ltd. All rights reserved.

Chromostereopsis in "virtual reality" adapters with electrically tuneable liquid lens oculars

NASA Astrophysics Data System (ADS)

Ozolinsh, Maris; Muizniece, Kristine; Berzinsh, Janis

2016-10-01

Chromostereopsis can be sight and feel in "Virtual Reality" adapters, that induces the appearance of color dependant depth sense and, finally, combines this sense with the source conceived depth scenario. Present studies are devoted to investigation the induced chromastereopsis when using adapted "Virtual Reality" frame together with mobile devices as smartphones. We did observation of composite visual stimuli presented on the high spatial resolution screen of the mobile phone placed inside a portable "Virtual Reality" adapter. Separated for the left and right eyes stimuli consisted of two areas: a) identical for both eyes color chromostereopsis part, and b) additional conventional color neutral random-dot stereopsis part with a stereodisparity based on the horizontal shift of a random-dot segment in images for the left and right eyes, correspondingly. The observer task was to equalize the depth sense for neutral and colored stimuli areas. Such scheme allows to determine actual observed chromostereopsis disparity value versus eye stimuli color difference. At standard observation conditions for adapter with +2D ocular lenses for mobile red-blue stimuli, the perceptual chromostereopsis depth sensitivity on color difference was linearly approximated with a slope SChS ≈ 2.1[arcmin/(Labcolor difference)] for red-blue pairs. Additional to standard application in adapter the tuneable "Varioptic" liquid lens oculars were incorporated, that allowed stimuli eye magnification, vergence and disparity values control electrically.

Silicone sensing phase for detection of aromatic hydrocarbons in water employing near-infrared spectroscopy.

PubMed

Albuquerque, Jackson S; Pimentel, M Fernanda; Silva, Valdinete L; Raimundo, Ivo M; Rohwedder, Jarbas J R; Pasquini, Celio

2005-01-01

The use of silicone for detection of aromatic hydrocarbons in water using near-infrared spectroscopy is proposed. A sensing phase of poly(dimethylsiloxane) (PDMS) was prepared, and a rod of this material was adapted to a transflectance probe for measurements from 850 to 1800 nm. Deionized water samples contaminated separately with known amounts of benzene, toluene, ethylbenzene, and m-xylene were used for evaluation of the PDMS sensing phase, and measurements were made in a closed reactor with constant stirring. Equilibrium states were obtained after 90, 180, 360, and 405 min for benzene, toluene, ethylbenzene, and m-xylene, respectively. The PDMS sensing phase showed a reversible response, presenting linear response ranges up to 360, 290, 100, and 80 mg L(-1), with detection limits of 8.0, 7.0, 2.6, and 3.0 mg L(-1) for benzene, toluene, ethylbenzene, and m-xylene, respectively. Reference spectra obtained with different rods showed a relative standard deviation of 0.5%, indicating repeatability in the sensing phase preparation. A relative standard deviation of 6.7% was obtained for measurements performed with six different rods, using a 52 mg L(-1) toluene aqueous solution. The sensing phase was evaluated for identification of sources of contamination of water in simulated studies, employing Brazilian gasoline type A (without ethanol), gasoline type C (with 25% of anhydrous ethanol), and diesel fuel. Principal component analysis was able to classify the water in distinct groups, contaminated by gasoline A, gasoline C, or diesel fuel.

Absorbance and fluorometric sensing with capillary wells microplates

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

Tan, Han Yen; Cheong, Brandon Huey-Ping; Neild, Adrian

2010-12-15

Detection and readout from small volume assays in microplates are a challenge. The capillary wells microplate approach [Ng et al., Appl. Phys. Lett. 93, 174105 (2008)] offers strong advantages in small liquid volume management. An adapted design is described and shown here to be able to detect, in a nonimaging manner, fluorescence and absorbance assays minus the error often associated with meniscus forming at the air-liquid interface. The presence of bubbles in liquid samples residing in microplate wells can cause inaccuracies. Pipetting errors, if not adequately managed, can result in misleading data and wrong interpretations of assay results; particularly inmore » the context of high throughput screening. We show that the adapted design is also able to detect for bubbles and pipetting errors during actual assay runs to ensure accuracy in screening.« less

Keck adaptive optics: control subsystem

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

Brase, J.M.; An, J.; Avicola, K.

1996-03-08

Adaptive optics on the Keck 10 meter telescope will provide an unprecedented level of capability in high resolution ground based astronomical imaging. The system is designed to provide near diffraction limited imaging performance with Strehl {gt} 0.3 n median Keck seeing of r0 = 25 cm, T =10 msec at 500 nm wavelength. The system will be equipped with a 20 watt sodium laser guide star to provide nearly full sky coverage. The wavefront control subsystem is responsible for wavefront sensing and the control of the tip-tilt and deformable mirrors which actively correct atmospheric turbulence. The spatial sampling interval formore » the wavefront sensor and deformable mirror is de=0.56 m which gives us 349 actuators and 244 subapertures. This paper summarizes the wavefront control system and discusses particular issues in designing a wavefront controller for the Keck telescope.« less

A semisupervised support vector regression method to estimate biophysical parameters from remotely sensed images

NASA Astrophysics Data System (ADS)

Castelletti, Davide; Demir, Begüm; Bruzzone, Lorenzo

2014-10-01

This paper presents a novel semisupervised learning (SSL) technique defined in the context of ɛ-insensitive support vector regression (SVR) to estimate biophysical parameters from remotely sensed images. The proposed SSL method aims to mitigate the problems of small-sized biased training sets without collecting any additional samples with reference measures. This is achieved on the basis of two consecutive steps. The first step is devoted to inject additional priors information in the learning phase of the SVR in order to adapt the importance of each training sample according to distribution of the unlabeled samples. To this end, a weight is initially associated to each training sample based on a novel strategy that defines higher weights for the samples located in the high density regions of the feature space while giving reduced weights to those that fall into the low density regions of the feature space. Then, in order to exploit different weights for training samples in the learning phase of the SVR, we introduce a weighted SVR (WSVR) algorithm. The second step is devoted to jointly exploit labeled and informative unlabeled samples for further improving the definition of the WSVR learning function. To this end, the most informative unlabeled samples that have an expected accurate target values are initially selected according to a novel strategy that relies on the distribution of the unlabeled samples in the feature space and on the WSVR function estimated at the first step. Then, we introduce a restructured WSVR algorithm that jointly uses labeled and unlabeled samples in the learning phase of the WSVR algorithm and tunes their importance by different values of regularization parameters. Experimental results obtained for the estimation of single-tree stem volume show the effectiveness of the proposed SSL method.

Wireless powering and data telemetry for biomedical implants.

PubMed

Young, Darrin J

2009-01-01

Wireless powering and data telemetry techniques for two biomedical implant studies based on (1) wireless in vivo EMG sensor for intelligent prosthetic control and (2) adaptively RF powered implantable bio-sensing microsystem for real-time genetically engineered mice monitoring are presented. Inductive-coupling-based RF powering and passive data telemetry is effective for wireless in vivo EMG sensing, where the internal and external RF coils are positioned with a small separation distance and fixed orientation. Adaptively controlled RF powering and active data transmission are critical for mobile implant application such as real-time physiological monitoring of untethered laboratory animals. Animal implant studies have been successfully completed to demonstrate the wireless and batteryless in vivo sensing capabilities.

Peripheral adaptive filtering in human olfaction? Three studies on prevalence and effects of olfactory training in specific anosmia in more than 1600 participants.

PubMed

Croy, Ilona; Olgun, Selda; Mueller, Laura; Schmidt, Anna; Muench, Marcus; Hummel, Cornelia; Gisselmann, Guenter; Hatt, Hanns; Hummel, Thomas

2015-12-01

Selective processing of environmental stimuli improves processing capacity and allows adaptive modulation of behavior. The thalamus provides an effective filter of central sensory information processing. As olfactory projections, however, largely bypass the thalamus, other filter mechanisms must consequently have evolved for the sense of smell. We investigated whether specific anosmia - the inability to perceive a specific odor whereas detection of other substances is unaffected - represents an effective peripheral filter of olfactory information processing. In contrast to previous studies, we showed in a sample of 1600 normosmic subjects, that specific anosmia is by no means a rare phenomenon. Instead, while the affected odor is highly individual, the general probability of occurrence of specific anosmia is close to 1. In addition, 25 subjects performed daily olfactory training sessions with enhanced exposure to their particular "missing" smells for the duration of three months. This resulted in a significant improvement of sensitivity towards the respective specific odors. We propose specific anosmia to occur as a rule, rather than an exception, in the sense of smell. The lack of perception of certain odors may constitute a flexible peripheral filter mechanism, which can be altered by exposure. Copyright © 2015 Elsevier Ltd. All rights reserved.

Adaptive Temporal Matched Filtering for Noise Suppression in Fiber Optic Distributed Acoustic Sensing.

PubMed

Ölçer, İbrahim; Öncü, Ahmet

2017-06-05

Distributed vibration sensing based on phase-sensitive optical time domain reflectometry ( ϕ -OTDR) is being widely used in several applications. However, one of the main challenges in coherent detection-based ϕ -OTDR systems is the fading noise, which impacts the detection performance. In addition, typical signal averaging and differentiating techniques are not suitable for detecting high frequency events. This paper presents a new approach for reducing the effect of fading noise in fiber optic distributed acoustic vibration sensing systems without any impact on the frequency response of the detection system. The method is based on temporal adaptive processing of ϕ -OTDR signals. The fundamental theory underlying the algorithm, which is based on signal-to-noise ratio (SNR) maximization, is presented, and the efficacy of our algorithm is demonstrated with laboratory experiments and field tests. With the proposed digital processing technique, the results show that more than 10 dB of SNR values can be achieved without any reduction in the system bandwidth and without using additional optical amplifier stages in the hardware. We believe that our proposed adaptive processing approach can be effectively used to develop fiber optic-based distributed acoustic vibration sensing systems.

Adaptive Temporal Matched Filtering for Noise Suppression in Fiber Optic Distributed Acoustic Sensing

PubMed Central

Ölçer, İbrahim; Öncü, Ahmet

2017-01-01

Distributed vibration sensing based on phase-sensitive optical time domain reflectometry (ϕ-OTDR) is being widely used in several applications. However, one of the main challenges in coherent detection-based ϕ-OTDR systems is the fading noise, which impacts the detection performance. In addition, typical signal averaging and differentiating techniques are not suitable for detecting high frequency events. This paper presents a new approach for reducing the effect of fading noise in fiber optic distributed acoustic vibration sensing systems without any impact on the frequency response of the detection system. The method is based on temporal adaptive processing of ϕ-OTDR signals. The fundamental theory underlying the algorithm, which is based on signal-to-noise ratio (SNR) maximization, is presented, and the efficacy of our algorithm is demonstrated with laboratory experiments and field tests. With the proposed digital processing technique, the results show that more than 10 dB of SNR values can be achieved without any reduction in the system bandwidth and without using additional optical amplifier stages in the hardware. We believe that our proposed adaptive processing approach can be effectively used to develop fiber optic-based distributed acoustic vibration sensing systems. PMID:28587240

Identification of robust adaptation gene regulatory network parameters using an improved particle swarm optimization algorithm.

PubMed

Huang, X N; Ren, H P

2016-05-13

Robust adaptation is a critical ability of gene regulatory network (GRN) to survive in a fluctuating environment, which represents the system responding to an input stimulus rapidly and then returning to its pre-stimulus steady state timely. In this paper, the GRN is modeled using the Michaelis-Menten rate equations, which are highly nonlinear differential equations containing 12 undetermined parameters. The robust adaption is quantitatively described by two conflicting indices. To identify the parameter sets in order to confer the GRNs with robust adaptation is a multi-variable, multi-objective, and multi-peak optimization problem, which is difficult to acquire satisfactory solutions especially high-quality solutions. A new best-neighbor particle swarm optimization algorithm is proposed to implement this task. The proposed algorithm employs a Latin hypercube sampling method to generate the initial population. The particle crossover operation and elitist preservation strategy are also used in the proposed algorithm. The simulation results revealed that the proposed algorithm could identify multiple solutions in one time running. Moreover, it demonstrated a superior performance as compared to the previous methods in the sense of detecting more high-quality solutions within an acceptable time. The proposed methodology, owing to its universality and simplicity, is useful for providing the guidance to design GRN with superior robust adaptation.

Useless hearing in male Emblemasoma auditrix (Diptera, Sarcophagidae)--a case of intralocus sexual conflict during evolution of a complex sense organ?

PubMed

Lakes-Harlan, Reinhard; Devries, Thomas; Stölting, Heiko; Stumpner, Andreas

2014-01-01

Sensory modalities typically are important for both sexes, although sex-specific functional adaptations may occur frequently. This is true for hearing as well. Consequently, distinct behavioural functions were identified for the different insect hearing systems. Here we describe a first case, where a trait of an evolutionary novelty and a highly specialized hearing organ is adaptive in only one sex. The main function of hearing of the parasitoid fly Emblemasoma auditrix is to locate the host, males of the cicada species Okanagana rimosa, by their calling song. This task is performed by female flies, which deposit larvae into the host. We show that male E. auditrix possess a hearing sense as well. The morphology of the tympanal organ of male E. auditrix is rather similar to the female ear, which is 8% broader than the male ear. In both sexes the physiological hearing threshold is tuned to 5 kHz. Behavioural tests show that males are able to orient towards the host calling song, although phonotaxis often is incomplete. However, despite extensive observations in the field and substantial knowledge of the biology of E. auditrix, no potentially adaptive function of the male auditory sense has been identified. This unique hearing system might represent an intralocus sexual conflict, as the complex sense organ and the behavioural relevant neuronal network is adaptive for only one sex. The correlated evolution of the sense organ in both sexes might impose substantial constraints on the sensory properties of the ear. Similar constraints, although hidden, might also apply to other sensory systems in which behavioural functions differ between sexes.

Research in the Optical Sciences.

DTIC Science & Technology

1987-12-15

been chosen for the wavefront sensor. REFERENCES 1. C. L. Koliopoulos, " Wavefront sensing of the turbulent atmosphere using a lateral shearing...technique would permit wavefront sensing in the image plane without employing an elaborate method to obtain a reference wavefront . Background Initial...and R. H. Potoff ......... 87 0rd . . .. El WAVEFRONT SENSING AND ADAPTIVE OPTICS C . K oliopoulos ............................................. 97

Toward accelerating landslide mapping with interactive machine learning techniques

NASA Astrophysics Data System (ADS)

Stumpf, André; Lachiche, Nicolas; Malet, Jean-Philippe; Kerle, Norman; Puissant, Anne

2013-04-01

Despite important advances in the development of more automated methods for landslide mapping from optical remote sensing images, the elaboration of inventory maps after major triggering events still remains a tedious task. Image classification with expert defined rules typically still requires significant manual labour for the elaboration and adaption of rule sets for each particular case. Machine learning algorithm, on the contrary, have the ability to learn and identify complex image patterns from labelled examples but may require relatively large amounts of training data. In order to reduce the amount of required training data active learning has evolved as key concept to guide the sampling for applications such as document classification, genetics and remote sensing. The general underlying idea of most active learning approaches is to initialize a machine learning model with a small training set, and to subsequently exploit the model state and/or the data structure to iteratively select the most valuable samples that should be labelled by the user and added in the training set. With relatively few queries and labelled samples, an active learning strategy should ideally yield at least the same accuracy than an equivalent classifier trained with many randomly selected samples. Our study was dedicated to the development of an active learning approach for landslide mapping from VHR remote sensing images with special consideration of the spatial distribution of the samples. The developed approach is a region-based query heuristic that enables to guide the user attention towards few compact spatial batches rather than distributed points resulting in time savings of 50% and more compared to standard active learning techniques. The approach was tested with multi-temporal and multi-sensor satellite images capturing recent large scale triggering events in Brazil and China and demonstrated balanced user's and producer's accuracies between 74% and 80%. The assessment also included an experimental evaluation of the uncertainties of manual mappings from multiple experts and demonstrated strong relationships between the uncertainty of the experts and the machine learning model.

Position and speed control of brushless DC motors using sensorless techniques and application trends.

PubMed

Gamazo-Real, José Carlos; Vázquez-Sánchez, Ernesto; Gómez-Gil, Jaime

2010-01-01

This paper provides a technical review of position and speed sensorless methods for controlling Brushless Direct Current (BLDC) motor drives, including the background analysis using sensors, limitations and advances. The performance and reliability of BLDC motor drivers have been improved because the conventional control and sensing techniques have been improved through sensorless technology. Then, in this paper sensorless advances are reviewed and recent developments in this area are introduced with their inherent advantages and drawbacks, including the analysis of practical implementation issues and applications. The study includes a deep overview of state-of-the-art back-EMF sensing methods, which includes Terminal Voltage Sensing, Third Harmonic Voltage Integration, Terminal Current Sensing, Back-EMF Integration and PWM strategies. Also, the most relevant techniques based on estimation and models are briefly analysed, such as Sliding-mode Observer, Extended Kalman Filter, Model Reference Adaptive System, Adaptive observers (Full-order and Pseudoreduced-order) and Artificial Neural Networks.

Artificial neural network does better spatiotemporal compressive sampling

NASA Astrophysics Data System (ADS)

Lee, Soo-Young; Hsu, Charles; Szu, Harold

2012-06-01

Spatiotemporal sparseness is generated naturally by human visual system based on artificial neural network modeling of associative memory. Sparseness means nothing more and nothing less than the compressive sensing achieves merely the information concentration. To concentrate the information, one uses the spatial correlation or spatial FFT or DWT or the best of all adaptive wavelet transform (cf. NUS, Shen Shawei). However, higher dimensional spatiotemporal information concentration, the mathematics can not do as flexible as a living human sensory system. The reason is obviously for survival reasons. The rest of the story is given in the paper.

Remote sensing estimation of colored dissolved organic matter (CDOM) in optically shallow waters

NASA Astrophysics Data System (ADS)

Li, Jiwei; Yu, Qian; Tian, Yong Q.; Becker, Brian L.

2017-06-01

It is not well understood how bottom reflectance of optically shallow waters affects the algorithm performance of colored dissolved organic matters (CDOM) retrieval. This study proposes a new algorithm that considers bottom reflectance in estimating CDOM absorption from optically shallow inland or coastal waters. The field sampling was conducted during four research cruises within the Saginaw River, Kawkawlin River and Saginaw Bay of Lake Huron. A stratified field sampling campaign collected water samples, determined the depth at each sampling location and measured optical properties. The sampled CDOM absorption at 440 nm broadly ranged from 0.12 to 8.46 m-1. Field sample analysis revealed that bottom reflectance does significantly change water apparent optical properties. We developed a CDOM retrieval algorithm (Shallow water Bio-Optical Properties algorithm, SBOP) that effectively reduces uncertainty by considering bottom reflectance in shallow waters. By incorporating the bottom contribution in upwelling radiances, the SBOP algorithm was able to explain 74% of the variance of CDOM values (RMSE = 0.22 and R2 = 0.74). The bottom effect index (BEI) was introduced to efficiently separate optically shallow and optically deep waters. Based on the BEI, an adaptive approach was proposed that references the amount of bottom effect in order to identify the most suitable algorithm (optically shallow water algorithm [SBOP] or optically deep water algorithm [QAA-CDOM]) to improve CDOM estimation (RMSE = 0.22 and R2 = 0.81). Our results potentially help to advance the capability of remote sensing in monitoring carbon pools at the land-water interface.

Low-rank and Adaptive Sparse Signal (LASSI) Models for Highly Accelerated Dynamic Imaging

PubMed Central

Ravishankar, Saiprasad; Moore, Brian E.; Nadakuditi, Raj Rao; Fessler, Jeffrey A.

2017-01-01

Sparsity-based approaches have been popular in many applications in image processing and imaging. Compressed sensing exploits the sparsity of images in a transform domain or dictionary to improve image recovery from undersampled measurements. In the context of inverse problems in dynamic imaging, recent research has demonstrated the promise of sparsity and low-rank techniques. For example, the patches of the underlying data are modeled as sparse in an adaptive dictionary domain, and the resulting image and dictionary estimation from undersampled measurements is called dictionary-blind compressed sensing, or the dynamic image sequence is modeled as a sum of low-rank and sparse (in some transform domain) components (L+S model) that are estimated from limited measurements. In this work, we investigate a data-adaptive extension of the L+S model, dubbed LASSI, where the temporal image sequence is decomposed into a low-rank component and a component whose spatiotemporal (3D) patches are sparse in some adaptive dictionary domain. We investigate various formulations and efficient methods for jointly estimating the underlying dynamic signal components and the spatiotemporal dictionary from limited measurements. We also obtain efficient sparsity penalized dictionary-blind compressed sensing methods as special cases of our LASSI approaches. Our numerical experiments demonstrate the promising performance of LASSI schemes for dynamic magnetic resonance image reconstruction from limited k-t space data compared to recent methods such as k-t SLR and L+S, and compared to the proposed dictionary-blind compressed sensing method. PMID:28092528

Low-Rank and Adaptive Sparse Signal (LASSI) Models for Highly Accelerated Dynamic Imaging.

PubMed

Ravishankar, Saiprasad; Moore, Brian E; Nadakuditi, Raj Rao; Fessler, Jeffrey A

2017-05-01

Sparsity-based approaches have been popular in many applications in image processing and imaging. Compressed sensing exploits the sparsity of images in a transform domain or dictionary to improve image recovery fromundersampledmeasurements. In the context of inverse problems in dynamic imaging, recent research has demonstrated the promise of sparsity and low-rank techniques. For example, the patches of the underlying data are modeled as sparse in an adaptive dictionary domain, and the resulting image and dictionary estimation from undersampled measurements is called dictionary-blind compressed sensing, or the dynamic image sequence is modeled as a sum of low-rank and sparse (in some transform domain) components (L+S model) that are estimated from limited measurements. In this work, we investigate a data-adaptive extension of the L+S model, dubbed LASSI, where the temporal image sequence is decomposed into a low-rank component and a component whose spatiotemporal (3D) patches are sparse in some adaptive dictionary domain. We investigate various formulations and efficient methods for jointly estimating the underlying dynamic signal components and the spatiotemporal dictionary from limited measurements. We also obtain efficient sparsity penalized dictionary-blind compressed sensing methods as special cases of our LASSI approaches. Our numerical experiments demonstrate the promising performance of LASSI schemes for dynamicmagnetic resonance image reconstruction from limited k-t space data compared to recent methods such as k-t SLR and L+S, and compared to the proposed dictionary-blind compressed sensing method.

Adaptive optics improves multiphoton super-resolution imaging

NASA Astrophysics Data System (ADS)

Zheng, Wei; Wu, Yicong; Winter, Peter; Shroff, Hari

2018-02-01

Three dimensional (3D) fluorescence microscopy has been essential for biological studies. It allows interrogation of structure and function at spatial scales spanning the macromolecular, cellular, and tissue levels. Critical factors to consider in 3D microscopy include spatial resolution, signal-to-noise (SNR), signal-to-background (SBR), and temporal resolution. Maintaining high quality imaging becomes progressively more difficult at increasing depth (where optical aberrations, induced by inhomogeneities of refractive index in the sample, degrade resolution and SNR), and in thick or densely labeled samples (where out-of-focus background can swamp the valuable, in-focus-signal from each plane). In this report, we introduce our new instrumentation to address these problems. A multiphoton structured illumination microscope was simply modified to integrate an adpative optics system for optical aberrations correction. Firstly, the optical aberrations are determined using direct wavefront sensing with a nonlinear guide star and subsequently corrected using a deformable mirror, restoring super-resolution information. We demonstrate the flexibility of our adaptive optics approach on a variety of semi-transparent samples, including bead phantoms, cultured cells in collagen gels and biological tissues. The performance of our super-resolution microscope is improved in all of these samples, as peak intensity is increased (up to 40-fold) and resolution recovered (up to 176+/-10 nm laterally and 729+/-39 nm axially) at depths up to 250 μm from the coverslip surface.

Using Remotely Sensed Data for Climate Change Mitigation and Adaptation: A Collaborative Effort Between the Climate Change Adaptation Science Investigators Workgroup (CASI), NASA Johnson Space Center, and Jacobs Technology

NASA Technical Reports Server (NTRS)

Jagge, Amy

2016-01-01

With ever changing landscapes and environmental conditions due to human induced climate change, adaptability is imperative for the long-term success of facilities and Federal agency missions. To mitigate the effects of climate change, indicators such as above-ground biomass change must be identified to establish a comprehensive monitoring effort. Researching the varying effects of climate change on ecosystems can provide a scientific framework that will help produce informative, strategic and tactical policies for environmental adaptation. As a proactive approach to climate change mitigation, NASA tasked the Climate Change Adaptation Science Investigators Workgroup (CASI) to provide climate change expertise and data to Center facility managers and planners in order to ensure sustainability based on predictive models and current research. Generation of historical datasets that will be used in an agency-wide effort to establish strategies for climate change mitigation and adaptation at NASA facilities is part of the CASI strategy. Using time series of historical remotely sensed data is well-established means of measuring change over time. CASI investigators have acquired multispectral and hyperspectral optical and LiDAR remotely sensed datasets from NASA Earth Observation Satellites (including the International Space Station), airborne sensors, and astronaut photography using hand held digital cameras to create a historical dataset for the Johnson Space Center, as well as the Houston and Galveston area. The raster imagery within each dataset has been georectified, and the multispectral and hyperspectral imagery has been atmospherically corrected. Using ArcGIS for Server, the CASI-Regional Remote Sensing data has been published as an image service, and can be visualized through a basic web mapping application. Future work will include a customized web mapping application created using a JavaScript Application Programming Interface (API), and inclusion of the CASI data for the NASA Johnson Space Center into a NASA-Wide GIS Institutional Portal.

An adaptive optics package designed for astronomical use with a laser guide star tuned to an absorption line of atomic sodium

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

Salmon, J.T.; Avicola, K.; Brase, J.M.

1994-04-11

We present the design and implementation of a very compact adaptive optic system that senses the return light from a sodium guide-star and controls a deformable mirror and a pointing mirror to compensate atmospheric perturbations in the wavefront. The deformable mirror has 19 electrostrictive actuators and triangular subapertures. The wavefront sensor is a Hartmann sensor with lenslets on triangular centers. The high-bandwidth steering mirror assembly incorporates an analog controller that samples the tilt with an avalanche photodiode quad cell. An {line_integral}/25 imaging leg focuses the light into a science camera that can either obtain long-exposure images or speckle data. Inmore » laboratory tests overall Strehl ratios were improved by a factor of 3 when a mylar sheet was used as an aberrator. The crossover frequency at unity gain is 30 Hz.« less

Estimating the Effective Permittivity for Reconstructing Accurate Microwave-Radar Images.

PubMed

Lavoie, Benjamin R; Okoniewski, Michal; Fear, Elise C

2016-01-01

We present preliminary results from a method for estimating the optimal effective permittivity for reconstructing microwave-radar images. Using knowledge of how microwave-radar images are formed, we identify characteristics that are typical of good images, and define a fitness function to measure the relative image quality. We build a polynomial interpolant of the fitness function in order to identify the most likely permittivity values of the tissue. To make the estimation process more efficient, the polynomial interpolant is constructed using a locally and dimensionally adaptive sampling method that is a novel combination of stochastic collocation and polynomial chaos. Examples, using a series of simulated, experimental and patient data collected using the Tissue Sensing Adaptive Radar system, which is under development at the University of Calgary, are presented. These examples show how, using our method, accurate images can be reconstructed starting with only a broad estimate of the permittivity range.

Miniaturized optical wavelength sensors

NASA Astrophysics Data System (ADS)

Kung, Helen Ling-Ning

Recently semiconductor processing technology has been applied to the miniaturization of optical wavelength sensors. Compact sensors enable new applications such as integrated diode-laser wavelength monitors and frequency lockers, portable chemical and biological detection, and portable and adaptive hyperspectral imaging arrays. Small sensing systems have trade-offs between resolution, operating range, throughput, multiplexing and complexity. We have developed a new wavelength sensing architecture that balances these parameters for applications involving hyperspectral imaging spectrometer arrays. In this thesis we discuss and demonstrate two new wavelength-sensing architectures whose single-pixel designs can easily be extended into spectrometer arrays. The first class of devices is based on sampling a standing wave. These devices are based on measuring the wavelength-dependent period of optical standing waves formed by the interference of forward and reflected waves at a mirror. We fabricated two different devices based on this principle. The first device is a wavelength monitor, which measures the wavelength and power of a monochromatic source. The second device is a spectrometer that can also act as a selective spectral coherence sensor. The spectrometer contains a large displacement piston-motion MEMS mirror and a thin GaAs photodiode flip-chip bonded to a quartz substrate. The performance of this spectrometer is similar to that of a Michelson in resolution, operating range, throughput and multiplexing but with the added advantages of fewer components and one-dimensional architecture. The second class of devices is based on the Talbot self-imaging effect. The Talbot effect occurs when a periodic object is illuminated with a spatially coherent wave. Periodically spaced self-images are formed behind the object. The spacing of the self-images is proportional to wavelength of the incident light. We discuss and demonstrate how this effect can be used for spectroscopy. In the conclusion we compare these two new miniaturized spectrometer architectures to existing miniaturized spectrometers. We believe that the combination of miniaturized wavelength sensors and smart processing should facilitate the development real-time, adaptive and portable sensing systems.

Development of fiber optic sensing interrogators for launchers

NASA Astrophysics Data System (ADS)

Plattner, M. P.; Buck, T. C.; Eder, B.; Reutlinger, A.; McKenzie, I.

2017-11-01

We present our work about the development of two complementary interrogation schemes based on fiber optic sensing for the use of structural and thermal monitoring of Ariane launchers. The advantages of fiber optic sensing in particular light-weight, immunity to electromagnetic interferences and the possibility of sensor distribution along optical fibers are driving factors for utilization of this technology in space crafts [1]. The edge-filter (EF) and scanning-laser (SL) interrogators for determination of the mean wavelength of fiber Bragg grating (FBG) sensors have been implemented as two separate demonstrators. Within this paper we describe the functional principles of both interrogators. Furthermore we present test results where the developed systems have been used for readout of FBG sensors which are implemented in an Ariane structural demonstrator during thermal, thermal-vacuum and vibration tests. Functionality of both systems is demonstrated and their potential for further development towards space qualified systems is shown. Since the performance characteristics of the two systems are different from each other, they are dedicated for different sensing applications on a launcher. The EF sensor interrogator provides a sample rate of 20 kHz at a number of 4 connected sensors and supports parallel readout and aliasing free operation. Therefore it is best suited for high priority measurement. Structural monitoring which requires the acquisition of real time sensor information in order to support control of the launcher is one operation area for a future EF system. The SL interrogator provides an overall measurement rate of 1 kHz at a number of 24 connected sensors distributed on three sensor channels. It can be adapted to any sensors that have design wavelengths lying within the output spectrum of the laser diode. Furthermore the number of overall sensors to be read out with this system can be adapted easily. Thermal mapping of satellite panels is one possible future application for the SL interrogator.

How little data is enough? Phase-diagram analysis of sparsity-regularized X-ray computed tomography

PubMed Central

Jørgensen, J. S.; Sidky, E. Y.

2015-01-01

We introduce phase-diagram analysis, a standard tool in compressed sensing (CS), to the X-ray computed tomography (CT) community as a systematic method for determining how few projections suffice for accurate sparsity-regularized reconstruction. In CS, a phase diagram is a convenient way to study and express certain theoretical relations between sparsity and sufficient sampling. We adapt phase-diagram analysis for empirical use in X-ray CT for which the same theoretical results do not hold. We demonstrate in three case studies the potential of phase-diagram analysis for providing quantitative answers to questions of undersampling. First, we demonstrate that there are cases where X-ray CT empirically performs comparably with a near-optimal CS strategy, namely taking measurements with Gaussian sensing matrices. Second, we show that, in contrast to what might have been anticipated, taking randomized CT measurements does not lead to improved performance compared with standard structured sampling patterns. Finally, we show preliminary results of how well phase-diagram analysis can predict the sufficient number of projections for accurately reconstructing a large-scale image of a given sparsity by means of total-variation regularization. PMID:25939620

How little data is enough? Phase-diagram analysis of sparsity-regularized X-ray computed tomography.

PubMed

Jørgensen, J S; Sidky, E Y

2015-06-13

We introduce phase-diagram analysis, a standard tool in compressed sensing (CS), to the X-ray computed tomography (CT) community as a systematic method for determining how few projections suffice for accurate sparsity-regularized reconstruction. In CS, a phase diagram is a convenient way to study and express certain theoretical relations between sparsity and sufficient sampling. We adapt phase-diagram analysis for empirical use in X-ray CT for which the same theoretical results do not hold. We demonstrate in three case studies the potential of phase-diagram analysis for providing quantitative answers to questions of undersampling. First, we demonstrate that there are cases where X-ray CT empirically performs comparably with a near-optimal CS strategy, namely taking measurements with Gaussian sensing matrices. Second, we show that, in contrast to what might have been anticipated, taking randomized CT measurements does not lead to improved performance compared with standard structured sampling patterns. Finally, we show preliminary results of how well phase-diagram analysis can predict the sufficient number of projections for accurately reconstructing a large-scale image of a given sparsity by means of total-variation regularization.

GOATS 2008 Autonomous, Adaptive Multistatic Acoustic Sensing

DTIC Science & Technology

2008-09-30

To develop net-centric, autonomous underwater vehicle sensing concepts for littoral MCM and ASW, exploiting collaborative and environmentally...unlimited 13. SUPPLEMENTARY NOTES code 1 only 14. ABSTRACT To develop net-centric, autonomous underwater vehicle sensing concepts for littoral MCM and...of autonomous underwater vehicle networks as platforms for new sonar concepts exploring the full 3-D acoustic environment of shallow water (SW) and

Remote sensing with intense filaments enhanced by adaptive optics

NASA Astrophysics Data System (ADS)

Daigle, J.-F.; Kamali, Y.; Châteauneuf, M.; Tremblay, G.; Théberge, F.; Dubois, J.; Roy, G.; Chin, S. L.

2009-11-01

A method involving a closed loop adaptive optic system is investigated as a tool to significantly enhance the collected optical emissions, for remote sensing applications involving ultrafast laser filamentation. The technique combines beam expansion and geometrical focusing, assisted by an adaptive optics system to correct the wavefront aberrations. Targets, such as a gaseous mixture of air and hydrocarbons, solid lead and airborne clouds of contaminated aqueous aerosols, were remotely probed with filaments generated at distances up to 118 m after the focusing beam expander. The integrated backscattered signals collected by the detection system (15-28 m from the filaments) were increased up to a factor of 7, for atmospheric N2 and solid lead, when the wavefronts were corrected by the adaptive optic system. Moreover, an extrapolation based on a simplified version of the LIDAR equation showed that the adaptive optic system improved the detection distance for N2 molecular fluorescence, from 45 m for uncorrected wavefronts to 125 m for corrected.

Exploring Adaptability through Learning Layers and Learning Loops

ERIC Educational Resources Information Center

Lof, Annette

2010-01-01

Adaptability in social-ecological systems results from individual and collective action, and multi-level interactions. It can be understood in a dual sense as a system's ability to adapt to disturbance and change, and to navigate system transformation. Inherent in this conception, as found in resilience thinking, are the concepts of learning and…

Adaptive compressive ghost imaging based on wavelet trees and sparse representation.

PubMed

Yu, Wen-Kai; Li, Ming-Fei; Yao, Xu-Ri; Liu, Xue-Feng; Wu, Ling-An; Zhai, Guang-Jie

2014-03-24

Compressed sensing is a theory which can reconstruct an image almost perfectly with only a few measurements by finding its sparsest representation. However, the computation time consumed for large images may be a few hours or more. In this work, we both theoretically and experimentally demonstrate a method that combines the advantages of both adaptive computational ghost imaging and compressed sensing, which we call adaptive compressive ghost imaging, whereby both the reconstruction time and measurements required for any image size can be significantly reduced. The technique can be used to improve the performance of all computational ghost imaging protocols, especially when measuring ultra-weak or noisy signals, and can be extended to imaging applications at any wavelength.

A Charge-Based Low-Power High-SNR Capacitive Sensing Interface Circuit

PubMed Central

Peng, Sheng-Yu; Qureshi, Muhammad S.; Hasler, Paul E.; Basu, Arindam; Degertekin, F. L.

2008-01-01

This paper describes a low-power approach to capacitive sensing that achieves a high signal-to-noise ratio. The circuit is composed of a capacitive feedback charge amplifier and a charge adaptation circuit. Without the adaptation circuit, the charge amplifier only consumes 1 μW to achieve the audio band SNR of 69.34dB. An adaptation scheme using Fowler-Nordheim tunneling and channel hot electron injection mechanisms to stabilize the DC output voltage is demonstrated. This scheme provides a very low frequency pole at 0.2Hz. The measured noise spectrums show that this slow-time scale adaptation does not degrade the circuit performance. The DC path can also be provided by a large feedback resistance without causing extra power consumption. A charge amplifier with a MOS-bipolar pseudo-resistor feedback scheme is interfaced with a capacitive micromachined ultrasonic transducer to demonstrate the feasibility of this approach for ultrasound applications. PMID:18787650

Genomic scan as a tool for assessing the genetic component of phenotypic variance in wild populations.

PubMed

Herrera, Carlos M

2012-01-01

Methods for estimating quantitative trait heritability in wild populations have been developed in recent years which take advantage of the increased availability of genetic markers to reconstruct pedigrees or estimate relatedness between individuals, but their application to real-world data is not exempt from difficulties. This chapter describes a recent marker-based technique which, by adopting a genomic scan approach and focusing on the relationship between phenotypes and genotypes at the individual level, avoids the problems inherent to marker-based estimators of relatedness. This method allows the quantification of the genetic component of phenotypic variance ("degree of genetic determination" or "heritability in the broad sense") in wild populations and is applicable whenever phenotypic trait values and multilocus data for a large number of genetic markers (e.g., amplified fragment length polymorphisms, AFLPs) are simultaneously available for a sample of individuals from the same population. The method proceeds by first identifying those markers whose variation across individuals is significantly correlated with individual phenotypic differences ("adaptive loci"). The proportion of phenotypic variance in the sample that is statistically accounted for by individual differences in adaptive loci is then estimated by fitting a linear model to the data, with trait value as the dependent variable and scores of adaptive loci as independent ones. The method can be easily extended to accommodate quantitative or qualitative information on biologically relevant features of the environment experienced by each sampled individual, in which case estimates of the environmental and genotype × environment components of phenotypic variance can also be obtained.

Adaptive decision making in a dynamic environment: a test of a sequential sampling model of relative judgment.

PubMed

Vuckovic, Anita; Kwantes, Peter J; Neal, Andrew

2013-09-01

Research has identified a wide range of factors that influence performance in relative judgment tasks. However, the findings from this research have been inconsistent. Studies have varied with respect to the identification of causal variables and the perceptual and decision-making mechanisms underlying performance. Drawing on the ecological rationality approach, we present a theory of the judgment and decision-making processes involved in a relative judgment task that explains how people judge a stimulus and adapt their decision process to accommodate their own uncertainty associated with those judgments. Undergraduate participants performed a simulated air traffic control conflict detection task. Across two experiments, we systematically manipulated variables known to affect performance. In the first experiment, we manipulated the relative distances of aircraft to a common destination while holding aircraft speeds constant. In a follow-up experiment, we introduced a direct manipulation of relative speed. We then fit a sequential sampling model to the data, and used the best fitting parameters to infer the decision-making processes responsible for performance. Findings were consistent with the theory that people adapt to their own uncertainty by adjusting their criterion and the amount of time they take to collect evidence in order to make a more accurate decision. From a practical perspective, the paper demonstrates that one can use a sequential sampling model to understand performance in a dynamic environment, allowing one to make sense of and interpret complex patterns of empirical findings that would otherwise be difficult to interpret using standard statistical analyses. PsycINFO Database Record (c) 2013 APA, all rights reserved.

Multilattice sampling strategies for region of interest dynamic MRI.

PubMed

Rilling, Gabriel; Tao, Yuehui; Marshall, Ian; Davies, Mike E

2013-08-01

A multilattice sampling approach is proposed for dynamic MRI with Cartesian trajectories. It relies on the use of sampling patterns composed of several different lattices and exploits an image model where only some parts of the image are dynamic, whereas the rest is assumed static. Given the parameters of such an image model, the methodology followed for the design of a multilattice sampling pattern adapted to the model is described. The multi-lattice approach is compared to single-lattice sampling, as used by traditional acceleration methods such as UNFOLD (UNaliasing by Fourier-Encoding the Overlaps using the temporal Dimension) or k-t BLAST, and random sampling used by modern compressed sensing-based methods. On the considered image model, it allows more flexibility and higher accelerations than lattice sampling and better performance than random sampling. The method is illustrated on a phase-contrast carotid blood velocity mapping MR experiment. Combining the multilattice approach with the KEYHOLE technique allows up to 12× acceleration factors. Simulation and in vivo undersampling results validate the method. Compared to lattice and random sampling, multilattice sampling provides significant gains at high acceleration factors. © 2012 Wiley Periodicals, Inc.

Ultra-sensitive chemical and biological analysis via specialty fibers with built-in microstructured optofluidic channels.

PubMed

Zhang, Nan; Li, Kaiwei; Cui, Ying; Wu, Zhifang; Shum, Perry Ping; Auguste, Jean-Louis; Dinh, Xuan Quyen; Humbert, Georges; Wei, Lei

2018-02-13

All-in-fiber optofluidics is an analytical tool that provides enhanced sensing performance with simplified analyzing system design. Currently, its advance is limited either by complicated liquid manipulation and light injection configuration or by low sensitivity resulting from inadequate light-matter interaction. In this work, we design and fabricate a side-channel photonic crystal fiber (SC-PCF) and exploit its versatile sensing capabilities in in-line optofluidic configurations. The built-in microfluidic channel of the SC-PCF enables strong light-matter interaction and easy lateral access of liquid samples in these analytical systems. In addition, the sensing performance of the SC-PCF is demonstrated with methylene blue for absorptive molecular detection and with human cardiac troponin T protein by utilizing a Sagnac interferometry configuration for ultra-sensitive and specific biomolecular specimen detection. Owing to the features of great flexibility and compactness, high-sensitivity to the analyte variation, and efficient liquid manipulation/replacement, the demonstrated SC-PCF offers a generic solution to be adapted to various fiber-waveguide sensors to detect a wide range of analytes in real time, especially for applications from environmental monitoring to biological diagnosis.

An adaptive field detection method for bridge scour monitoring using motion-sensing radio transponders (RFIDs).

DOT National Transportation Integrated Search

2014-01-01

A comprehensive field detection method is proposed that is aimed at developing advanced capability for : reliable monitoring, inspection and life estimation of bridge infrastructure. The goal is to utilize Motion-Sensing Radio Transponders (RFIDS) on...

Laser driving and data processing concept for mobile trace gas sensing: Design and implementation

NASA Astrophysics Data System (ADS)

Liu, Chang; Tuzson, Béla; Scheidegger, Philipp; Looser, Herbert; Bereiter, Bernhard; Graf, Manuel; Hundt, Morten; Aseev, Oleg; Maas, Deran; Emmenegger, Lukas

2018-06-01

High precision mobile sensing of multi-species gases is greatly demanded in a wide range of applications. Although quantum cascade laser absorption spectroscopy demonstrates excellent field-deployment capabilities for gas sensing, the implementation of this measurement technique into sensor-like portable instrumentation still remains challenging. In this paper, two crucial elements, the laser driving and data acquisition electronics, are addressed. Therefore, we exploit the benefits of the time-division multiplexed intermittent continuous wave driving concept and the real-time signal pre-processing capabilities of a commercial System-on-Chip (SoC, Red Pitaya). We describe a re-designed current driver that offers a universal solution for operating a wide range of multi-wavelength quantum cascade laser device types and allows stacking for the purpose of multiple laser configurations. Its adaptation to the various driving situations is enabled by numerous field programmable gate array (FPGA) functionalities that were developed on the SoC, such as flexible generation of a large variety of synchronized trigger signals and digital inputs/outputs (DIOs). The same SoC is used to sample the spectroscopic signal at rates up to 125 MS/s with 14-bit resolution. Additional FPGA functionalities were implemented to enable on-board averaging of consecutive spectral scans in real-time, resulting in optimized memory bandwidth and hardware resource utilisation and autonomous system operation. Thus, we demonstrate how a cost-effective, compact, and commercial SoC can successfully be adapted to obtain a fully operational research-grade laser spectrometer. The overall system performance was examined in a spectroscopic setup by analyzing low pressure absorption features of CO2 at 4.3 μm.

Monitoring terrestrial dissolved organic carbon export at land-water interfaces using remote sensing

NASA Astrophysics Data System (ADS)

Yu, Q.; Li, J.; Tian, Y. Q.

2017-12-01

Carbon flux from land to oceans and lakes is a crucial component of carbon cycling. However, this lateral carbon flow at land-water interface is often neglected in the terrestrial carbon cycle budget, mainly because observations of the carbon dynamics are very limited. Monitoring CDOM/DOC dynamics using remote sensing and assessing DOC export from land to water remains a challenge. Current CDOM retrieval algorithms in the field of ocean color are not simply applicable to inland aquatic ecosystems since they were developed for coarse resolution ocean-viewing imagery and less complex water types in open-sea. We developed a new semi-analytical algorithm, called SBOP (Shallow water Bio-Optical Properties algorithm) to adapt to shallow inland waters. SBOP was first developed and calibrated based on in situ hyperspectral radiometer data. Then we applied it to the Landsat-8 OLI images and evaluated the effectiveness of the multispectral images on inversion of CDOM absorption based on our field sampling at the Saginaw Bay in the Lake Huron. The algorithm performances (RMSE = 0.17 and R2 = 0.87 in the Saginaw Bay; R2 = 0.80 in the northeastern US lakes) is promising and we conclude the CDOM absorption can be derived from Landsat-8 OLI image in both optically deep and optically shallow waters with high accuracy. Our method addressed challenges on employing appropriate atmospheric correction, determining bottom reflectance influence for shallow waters, and improving for bio-optical properties retrieval, as well as adapting to both hyperspectral and the multispectral remote sensing imagery. Over 100 Landsat-8 images in Lake Huron, northeastern US lakes, and the Arctic major rivers were processed to understand the CDOM spatio-temporal dynamics and its associated driving factors.

Vision-based algorithms for near-host object detection and multilane sensing

NASA Astrophysics Data System (ADS)

Kenue, Surender K.

1995-01-01

Vision-based sensing can be used for lane sensing, adaptive cruise control, collision warning, and driver performance monitoring functions of intelligent vehicles. Current computer vision algorithms are not robust for handling multiple vehicles in highway scenarios. Several new algorithms are proposed for multi-lane sensing, near-host object detection, vehicle cut-in situations, and specifying regions of interest for object tracking. These algorithms were tested successfully on more than 6000 images taken from real-highway scenes under different daytime lighting conditions.

Adaptive mutation: has the unicorn landed?

PubMed

Foster, P L

1998-04-01

Reversion of an episomal Lac- allele during lactose selection has been studied as a model for adaptive mutation. Although recent results show that the mutations that arise during selection are not "adaptive" in the original sense, the mutagenic mechanism that produces these mutations may nonetheless be of evolutionary significance. In addition, a transient mutational state induced in a subpopulation of starving cells could provide a species with a mechanism for adaptive evolution.

An efficient cloud detection method for high resolution remote sensing panchromatic imagery

NASA Astrophysics Data System (ADS)

Li, Chaowei; Lin, Zaiping; Deng, Xinpu

2018-04-01

In order to increase the accuracy of cloud detection for remote sensing satellite imagery, we propose an efficient cloud detection method for remote sensing satellite panchromatic images. This method includes three main steps. First, an adaptive intensity threshold value combined with a median filter is adopted to extract the coarse cloud regions. Second, a guided filtering process is conducted to strengthen the textural features difference and then we conduct the detection process of texture via gray-level co-occurrence matrix based on the acquired texture detail image. Finally, the candidate cloud regions are extracted by the intersection of two coarse cloud regions above and we further adopt an adaptive morphological dilation to refine them for thin clouds in boundaries. The experimental results demonstrate the effectiveness of the proposed method.

Vestibular-somatosensory convergence in head movement control during locomotion after long-duration space flight.

PubMed

Mulavara, A P; Ruttley, T; Cohen, H S; Peters, B T; Miller, C; Brady, R; Merkle, L; Bloomberg, J J

2012-01-01

Space flight causes astronauts to be exposed to adaptation in both the vestibular and body load-sensing somatosensory systems. The goal of these studies was to examine the contributions of vestibular and body load-sensing somatosensory influences on vestibular mediated head movement control during locomotion after long-duration space flight. Subjects walked on a motor driven treadmill while performing a gaze stabilization task. Data were collected from three independent subject groups that included bilateral labyrinthine deficient (LD) patients, normal subjects before and after 30 minutes of 40% bodyweight unloaded treadmill walking, and astronauts before and after long-duration space flight. Motion data from the head and trunk segments were used to calculate the amplitude of angular head pitch and trunk vertical translation movement while subjects performed a gaze stabilization task, to estimate the contributions of vestibular reflexive mechanisms in head pitch movements. Exposure to unloaded locomotion caused a significant increase in head pitch movements in normal subjects, whereas the head pitch movements of LD patients were significantly decreased. This is the first evidence of adaptation of vestibular mediated head movement responses to unloaded treadmill walking. Astronaut subjects showed a heterogeneous response of both increases and decreases in the amplitude of head pitch movement. We infer that body load-sensing somatosensory input centrally modulates vestibular input and can adaptively modify vestibularly mediated head-movement control during locomotion. Thus, space flight may cause central adaptation of the converging vestibular and body load-sensing somatosensory systems leading to alterations in head movement control.

A Novel Technique for Maximum Power Point Tracking of a Photovoltaic Based on Sensing of Array Current Using Adaptive Neuro-Fuzzy Inference System (ANFIS)

NASA Astrophysics Data System (ADS)

El-Zoghby, Helmy M.; Bendary, Ahmed F.

2016-10-01

Maximum Power Point Tracking (MPPT) is now widely used method in increasing the photovoltaic (PV) efficiency. The conventional MPPT methods have many problems concerning the accuracy, flexibility and efficiency. The MPP depends on the PV temperature and solar irradiation that randomly varied. In this paper an artificial intelligence based controller is presented through implementing of an Adaptive Neuro-Fuzzy Inference System (ANFIS) to obtain maximum power from PV. The ANFIS inputs are the temperature and cell current, and the output is optimal voltage at maximum power. During operation the trained ANFIS senses the PV current using suitable sensor and also senses the temperature to determine the optimal operating voltage that corresponds to the current at MPP. This voltage is used to control the boost converter duty cycle. The MATLAB simulation results shows the effectiveness of the ANFIS with sensing the PV current in obtaining the MPPT from the PV.

Laboratory MCAO Test-Bed for Developing Wavefront Sensing Concepts.

PubMed

Goncharov, A V; Dainty, J C; Esposito, S; Puglisi, A

2005-07-11

An experimental optical bench test-bed for developing new wavefront sensing concepts for Multi-Conjugate Adaptive Optics (MCAO) systems is described. The main objective is to resolve imaging problems associated with wavefront sensing of the atmospheric turbulence for future MCAO systems on Extremely Large Telescopes (ELTs). The test-bed incorporates five reference sources, two deformable mirrors (DMs) and atmospheric phase screens to simulate a scaled version of a 10-m adaptive telescope operating at the K band. A recently proposed compact tomographic wavefront sensor is employed for star-oriented DMs control in the MCAO system. The MCAO test-bed is used to verify the feasibility of the wavefront sensing concept utilizing a field lenslet array for multi-pupil imaging on a single detector. First experimental results of MCAO correction with the proposed tomographic wavefront sensor are presented and compared to the theoretical prediction based on the characteristics of the phase screens, actuator density of the DMs and the guide star configuration.

Adaptive compressed sensing of remote-sensing imaging based on the sparsity prediction

NASA Astrophysics Data System (ADS)

Yang, Senlin; Li, Xilong; Chong, Xin

2017-10-01

The conventional compressive sensing works based on the non-adaptive linear projections, and the parameter of its measurement times is usually set empirically. As a result, the quality of image reconstruction is always affected. Firstly, the block-based compressed sensing (BCS) with conventional selection for compressive measurements was given. Then an estimation method for the sparsity of image was proposed based on the two dimensional discrete cosine transform (2D DCT). With an energy threshold given beforehand, the DCT coefficients were processed with both energy normalization and sorting in descending order, and the sparsity of the image can be achieved by the proportion of dominant coefficients. And finally, the simulation result shows that, the method can estimate the sparsity of image effectively, and provides an active basis for the selection of compressive observation times. The result also shows that, since the selection of observation times is based on the sparse degree estimated with the energy threshold provided, the proposed method can ensure the quality of image reconstruction.

Position and Speed Control of Brushless DC Motors Using Sensorless Techniques and Application Trends

PubMed Central

Gamazo-Real, José Carlos; Vázquez-Sánchez, Ernesto; Gómez-Gil, Jaime

2010-01-01

This paper provides a technical review of position and speed sensorless methods for controlling Brushless Direct Current (BLDC) motor drives, including the background analysis using sensors, limitations and advances. The performance and reliability of BLDC motor drivers have been improved because the conventional control and sensing techniques have been improved through sensorless technology. Then, in this paper sensorless advances are reviewed and recent developments in this area are introduced with their inherent advantages and drawbacks, including the analysis of practical implementation issues and applications. The study includes a deep overview of state-of-the-art back-EMF sensing methods, which includes Terminal Voltage Sensing, Third Harmonic Voltage Integration, Terminal Current Sensing, Back-EMF Integration and PWM strategies. Also, the most relevant techniques based on estimation and models are briefly analysed, such as Sliding-mode Observer, Extended Kalman Filter, Model Reference Adaptive System, Adaptive observers (Full-order and Pseudoreduced-order) and Artificial Neural Networks. PMID:22163582

An Adaptive 6-DOF Tracking Method by Hybrid Sensing for Ultrasonic Endoscopes

PubMed Central

Du, Chengyang; Chen, Xiaodong; Wang, Yi; Li, Junwei; Yu, Daoyin

2014-01-01

In this paper, a novel hybrid sensing method for tracking an ultrasonic endoscope within the gastrointestinal (GI) track is presented, and the prototype of the tracking system is also developed. We implement 6-DOF localization by sensing integration and information fusion. On the hardware level, a tri-axis gyroscope and accelerometer, and a magnetic angular rate and gravity (MARG) sensor array are attached at the end of endoscopes, and three symmetric cylindrical coils are placed around patients' abdomens. On the algorithm level, an adaptive fast quaternion convergence (AFQC) algorithm is introduced to determine the orientation by fusing inertial/magnetic measurements, in which the effects of magnetic disturbance and acceleration are estimated to gain an adaptive convergence output. A simplified electro-magnetic tracking (SEMT) algorithm for dimensional position is also implemented, which can easily integrate the AFQC's results and magnetic measurements. Subsequently, the average position error is under 0.3 cm by reasonable setting, and the average orientation error is 1° without noise. If magnetic disturbance or acceleration exists, the average orientation error can be controlled to less than 3.5°. PMID:24915179

A data acquisition protocol for a reactive wireless sensor network monitoring application.

PubMed

Aderohunmu, Femi A; Brunelli, Davide; Deng, Jeremiah D; Purvis, Martin K

2015-04-30

Limiting energy consumption is one of the primary aims for most real-world deployments of wireless sensor networks. Unfortunately, attempts to optimize energy efficiency are often in conflict with the demand for network reactiveness to transmit urgent messages. In this article, we propose SWIFTNET: a reactive data acquisition scheme. It is built on the synergies arising from a combination of the data reduction methods and energy-efficient data compression schemes. Particularly, it combines compressed sensing, data prediction and adaptive sampling strategies. We show how this approach dramatically reduces the amount of unnecessary data transmission in the deployment for environmental monitoring and surveillance networks. SWIFTNET targets any monitoring applications that require high reactiveness with aggressive data collection and transmission. To test the performance of this method, we present a real-world testbed for a wildfire monitoring as a use-case. The results from our in-house deployment testbed of 15 nodes have proven to be favorable. On average, over 50% communication reduction when compared with a default adaptive prediction method is achieved without any loss in accuracy. In addition, SWIFTNET is able to guarantee reactiveness by adjusting the sampling interval from 5 min up to 15 s in our application domain.

A Data Acquisition Protocol for a Reactive Wireless Sensor Network Monitoring Application

PubMed Central

Aderohunmu, Femi A.; Brunelli, Davide; Deng, Jeremiah D.; Purvis, Martin K.

2015-01-01

Limiting energy consumption is one of the primary aims for most real-world deployments of wireless sensor networks. Unfortunately, attempts to optimize energy efficiency are often in conflict with the demand for network reactiveness to transmit urgent messages. In this article, we propose SWIFTNET: a reactive data acquisition scheme. It is built on the synergies arising from a combination of the data reduction methods and energy-efficient data compression schemes. Particularly, it combines compressed sensing, data prediction and adaptive sampling strategies. We show how this approach dramatically reduces the amount of unnecessary data transmission in the deployment for environmental monitoring and surveillance networks. SWIFTNET targets any monitoring applications that require high reactiveness with aggressive data collection and transmission. To test the performance of this method, we present a real-world testbed for a wildfire monitoring as a use-case. The results from our in-house deployment testbed of 15 nodes have proven to be favorable. On average, over 50% communication reduction when compared with a default adaptive prediction method is achieved without any loss in accuracy. In addition, SWIFTNET is able to guarantee reactiveness by adjusting the sampling interval from 5 min up to 15 s in our application domain. PMID:25942642

Coding Strategies and Implementations of Compressive Sensing

NASA Astrophysics Data System (ADS)

Tsai, Tsung-Han

This dissertation studies the coding strategies of computational imaging to overcome the limitation of conventional sensing techniques. The information capacity of conventional sensing is limited by the physical properties of optics, such as aperture size, detector pixels, quantum efficiency, and sampling rate. These parameters determine the spatial, depth, spectral, temporal, and polarization sensitivity of each imager. To increase sensitivity in any dimension can significantly compromise the others. This research implements various coding strategies subject to optical multidimensional imaging and acoustic sensing in order to extend their sensing abilities. The proposed coding strategies combine hardware modification and signal processing to exploiting bandwidth and sensitivity from conventional sensors. We discuss the hardware architecture, compression strategies, sensing process modeling, and reconstruction algorithm of each sensing system. Optical multidimensional imaging measures three or more dimensional information of the optical signal. Traditional multidimensional imagers acquire extra dimensional information at the cost of degrading temporal or spatial resolution. Compressive multidimensional imaging multiplexes the transverse spatial, spectral, temporal, and polarization information on a two-dimensional (2D) detector. The corresponding spectral, temporal and polarization coding strategies adapt optics, electronic devices, and designed modulation techniques for multiplex measurement. This computational imaging technique provides multispectral, temporal super-resolution, and polarization imaging abilities with minimal loss in spatial resolution and noise level while maintaining or gaining higher temporal resolution. The experimental results prove that the appropriate coding strategies may improve hundreds times more sensing capacity. Human auditory system has the astonishing ability in localizing, tracking, and filtering the selected sound sources or information from a noisy environment. Using engineering efforts to accomplish the same task usually requires multiple detectors, advanced computational algorithms, or artificial intelligence systems. Compressive acoustic sensing incorporates acoustic metamaterials in compressive sensing theory to emulate the abilities of sound localization and selective attention. This research investigates and optimizes the sensing capacity and the spatial sensitivity of the acoustic sensor. The well-modeled acoustic sensor allows localizing multiple speakers in both stationary and dynamic auditory scene; and distinguishing mixed conversations from independent sources with high audio recognition rate.

Extended use of two crossed Babinet compensators for wavefront sensing in adaptive optics

NASA Astrophysics Data System (ADS)

Paul, Lancelot; Kumar Saxena, Ajay

2010-12-01

An extended use of two crossed Babinet compensators as a wavefront sensor for adaptive optics applications is proposed. This method is based on the lateral shearing interferometry technique in two directions. A single record of the fringes in a pupil plane provides the information about the wavefront. The theoretical simulations based on this approach for various atmospheric conditions and other errors of optical surfaces are provided for better understanding of this method. Derivation of the results from a laboratory experiment using simulated atmospheric conditions demonstrates the steps involved in data analysis and wavefront evaluation. It is shown that this method has a higher degree of freedom in terms of subapertures and on the choice of detectors, and can be suitably adopted for real-time wavefront sensing for adaptive optics.

Adaptive statistical pattern classifiers for remotely sensed data

NASA Technical Reports Server (NTRS)

Gonzalez, R. C.; Pace, M. O.; Raulston, H. S.

1975-01-01

A technique for the adaptive estimation of nonstationary statistics necessary for Bayesian classification is developed. The basic approach to the adaptive estimation procedure consists of two steps: (1) an optimal stochastic approximation of the parameters of interest and (2) a projection of the parameters in time or position. A divergence criterion is developed to monitor algorithm performance. Comparative results of adaptive and nonadaptive classifier tests are presented for simulated four dimensional spectral scan data.

Adaptive mutation: has the unicorn landed?

PubMed Central

Foster, P L

1998-01-01

Reversion of an episomal Lac- allele during lactose selection has been studied as a model for adaptive mutation. Although recent results show that the mutations that arise during selection are not "adaptive" in the original sense, the mutagenic mechanism that produces these mutations may nonetheless be of evolutionary significance. In addition, a transient mutational state induced in a subpopulation of starving cells could provide a species with a mechanism for adaptive evolution. PMID:9560365

Interband cascade laser based mid-infrared methane sensor system using a novel electrical-domain self-adaptive direct laser absorption spectroscopy (SA-DLAS).

PubMed

Song, Fang; Zheng, Chuantao; Yan, Wanhong; Ye, Weilin; Wang, Yiding; Tittel, Frank K

2017-12-11

To suppress sensor noise with unknown statistical properties, a novel self-adaptive direct laser absorption spectroscopy (SA-DLAS) technique was proposed by incorporating a recursive, least square (RLS) self-adaptive denoising (SAD) algorithm and a 3291 nm interband cascade laser (ICL) for methane (CH 4 ) detection. Background noise was suppressed by introducing an electrical-domain noise-channel and an expectation-known-based RLS SAD algorithm. Numerical simulations and measurements were carried out to validate the function of the SA-DLAS technique by imposing low-frequency, high-frequency, White-Gaussian and hybrid noise on the ICL scan signal. Sensor calibration, stability test and dynamic response measurement were performed for the SA-DLAS sensor using standard or diluted CH 4 samples. With the intrinsic sensor noise considered only, an Allan deviation of ~43.9 ppbv with a ~6 s averaging time was obtained and it was further decreased to 6.3 ppbv with a ~240 s averaging time, through the use of self-adaptive filtering (SAF). The reported SA-DLAS technique shows enhanced sensitivity compared to a DLAS sensor using a traditional sensing architecture and filtering method. Indoor and outdoor atmospheric CH 4 measurements were conducted to validate the normal operation of the reported SA-DLAS technique.

Controlled microfluidic interfaces for microsensors

NASA Astrophysics Data System (ADS)

Jiang, H.

2009-02-01

Lab on a chip has found many applications in biological and chemical analysis, including pathogen detections. Because these labs on chips involve handling of fluids at the microscale, surface tension profoundly affects the behavior and performance of these systems. Through careful engineering, controlled liquid-liquid or liquid-gas interfaces at the microscale can be formed and used in many interesting applications. In this talk, I will present our work on applying such interfaces to microsensing. These interfaces are created at hydrophobic-hydrophilic boundaries formed within microfluidic channels and pinned by surface tension. We have designed and fabricated a few microsensing techniques including chemical and biological sensing using dissolvable micromembranes in microchannels, chemical and biological sensing at liquid crystals interfacing either air or aqueous solutions, and collection of gaseous samples and aerosols through air-liquid microfludic interfaces. I will next introduce on-chip microlenses and microlens arrays for optical detection, including smart and adaptive liquid microlenses actuated by stimuli-responsive hydrogels, and liquid microlenses in situ formed within microfluidic channels via pneumatic control of droplets.

HIGH-SPEED IMAGING AND WAVEFRONT SENSING WITH AN INFRARED AVALANCHE PHOTODIODE ARRAY

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

Baranec, Christoph; Atkinson, Dani; Hall, Donald

2015-08-10

Infrared avalanche photodiode (APD) arrays represent a panacea for many branches of astronomy by enabling extremely low-noise, high-speed, and even photon-counting measurements at near-infrared wavelengths. We recently demonstrated the use of an early engineering-grade infrared APD array that achieves a correlated double sampling read noise of 0.73 e{sup −} in the lab, and a total noise of 2.52 e{sup −} on sky, and supports simultaneous high-speed imaging and tip-tilt wavefront sensing with the Robo-AO visible-light laser adaptive optics (AO) system at the Palomar Observatory 1.5 m telescope. Here we report on the improved image quality simultaneously achieved at visible andmore » infrared wavelengths by using the array as part of an image stabilization control loop with AO-sharpened guide stars. We also discuss a newly enabled survey of nearby late M-dwarf multiplicity, as well as future uses of this technology in other AO and high-contrast imaging applications.« less

Sense of coherence moderates late effects of early childhood Holocaust exposure.

PubMed

van der Hal-van Raalte, Elisheva A M; van IJzendoorn, Marinus H; Bakermans-Kranenburg, Marian J

2008-12-01

This study evaluated child Holocaust survivors with an emphasis on potential protective factors facilitating participants' adaptation to post-Holocaust life. We examined Antonovsky's (1979, 1987) salutogenic paradigm, testing the mediating and moderating effect of participants' sense of coherence (SOC) on the association between early childhood deprivation due to Holocaust persecution and posttraumatic stress later in life. The nonclinical sample, composed of 203 child Holocaust survivors born between 1935 and 1944 completed questionnaires on Holocaust survival exposure, inventories on current health, posttraumatic stress, and SOC. The results indicated that SOC moderates the association between traumatic experiences during the war and posttraumatic stress, and SOC acts as a protective factor, buffering the impact of traumatic Holocaust experiences on child survivors in old age. Survivors with a less coherent perspective on the meaning of their life showed greater vulnerability for posttraumatic complaints. The moderating role of the SOC may suggest promising avenues of therapeutic interventions for child Holocaust survivors and other adults with early childhood trauma. (c) 2008 Wiley Periodicals, Inc.

a Cloud Boundary Detection Scheme Combined with Aslic and Cnn Using ZY-3, GF-1/2 Satellite Imagery

NASA Astrophysics Data System (ADS)

Guo, Z.; Li, C.; Wang, Z.; Kwok, E.; Wei, X.

2018-04-01

Remote sensing optical image cloud detection is one of the most important problems in remote sensing data processing. Aiming at the information loss caused by cloud cover, a cloud detection method based on convolution neural network (CNN) is presented in this paper. Firstly, a deep CNN network is used to extract the multi-level feature generation model of cloud from the training samples. Secondly, the adaptive simple linear iterative clustering (ASLIC) method is used to divide the detected images into superpixels. Finally, the probability of each superpixel belonging to the cloud region is predicted by the trained network model, thereby generating a cloud probability map. The typical region of GF-1/2 and ZY-3 were selected to carry out the cloud detection test, and compared with the traditional SLIC method. The experiment results show that the average accuracy of cloud detection is increased by more than 5 %, and it can detected thin-thick cloud and the whole cloud boundary well on different imaging platforms.

Assessing Structure and Condition of Temperate And Tropical Forests: Fusion of Terrestrial Lidar and Airborne Multi-Angle and Lidar Remote Sensing

NASA Astrophysics Data System (ADS)

Saenz, Edward J.

Forests provide vital ecosystem functions and services that maintain the integrity of our natural and human environment. Understanding the structural components of forests (extent, tree density, heights of multi-story canopies, biomass, etc.) provides necessary information to preserve ecosystem services. Increasingly, remote sensing resources have been used to map and monitor forests globally. However, traditional satellite and airborne multi-angle imagery only provide information about the top of the canopy and little about the forest structure and understory. In this research, we investigative the use of rapidly evolving lidar technology, and how the fusion of aerial and terrestrial lidar data can be utilized to better characterize forest stand information. We further apply a novel terrestrial lidar methodology to characterize a Hemlock Woolly Adelgid infestation in Harvard Forest, Massachusetts, and adapt a dynamic terrestrial lidar sampling scheme to identify key structural vegetation profiles of tropical rainforests in La Selva, Costa Rica.

On-board multispectral classification study. Volume 2: Supplementary tasks. [adaptive control

NASA Technical Reports Server (NTRS)

Ewalt, D.

1979-01-01

The operational tasks of the onboard multispectral classification study were defined. These tasks include: sensing characteristics for future space applications; information adaptive systems architectural approaches; data set selection criteria; and onboard functional requirements for interfacing with global positioning satellites.

An Adaptive Data Gathering Scheme for Multi-Hop Wireless Sensor Networks Based on Compressed Sensing and Network Coding.

PubMed

Yin, Jun; Yang, Yuwang; Wang, Lei

2016-04-01

Joint design of compressed sensing (CS) and network coding (NC) has been demonstrated to provide a new data gathering paradigm for multi-hop wireless sensor networks (WSNs). By exploiting the correlation of the network sensed data, a variety of data gathering schemes based on NC and CS (Compressed Data Gathering--CDG) have been proposed. However, these schemes assume that the sparsity of the network sensed data is constant and the value of the sparsity is known before starting each data gathering epoch, thus they ignore the variation of the data observed by the WSNs which are deployed in practical circumstances. In this paper, we present a complete design of the feedback CDG scheme where the sink node adaptively queries those interested nodes to acquire an appropriate number of measurements. The adaptive measurement-formation procedure and its termination rules are proposed and analyzed in detail. Moreover, in order to minimize the number of overall transmissions in the formation procedure of each measurement, we have developed a NP-complete model (Maximum Leaf Nodes Minimum Steiner Nodes--MLMS) and realized a scalable greedy algorithm to solve the problem. Experimental results show that the proposed measurement-formation method outperforms previous schemes, and experiments on both datasets from ocean temperature and practical network deployment also prove the effectiveness of our proposed feedback CDG scheme.

Identifying drought adaptive traits in upland cotton using a proximal sensing cart for high-throughput phenotyping

USDA-ARS?s Scientific Manuscript database

Field-based high-throughput phenotyping is an emerging approach to characterize difficult, time-sensitive plant traits in relevant growing conditions. Proximal sensing carts have been developed as an alternative platform to more costly high-clearance tractors for phenotyping dynamic traits in the fi...

Fiber optic temperature sensor

NASA Technical Reports Server (NTRS)

Quick, William H. (Inventor); August, Rudolf R. (Inventor); James, Kenneth A. (Inventor); Strahan, Jr., Virgil H. (Inventor); Nichols, Donald K. (Inventor)

1980-01-01

An inexpensive, lightweight fiber optic micro-sensor that is suitable for applications which may require remote temperature sensing. The disclosed temperature sensor includes a phosphor material that, after receiving incident light stimulation, is adapted to emit phosphorescent radiation output signals, the amplitude decay rate and wavelength of which are functions of the sensed temperature.

Mobile Phone Middleware Architecture for Energy and Context Awareness in Location-Based Services

PubMed Central

Galeana-Zapién, Hiram; Torres-Huitzil, César; Rubio-Loyola, Javier

2014-01-01

The disruptive innovation of smartphone technology has enabled the development of mobile sensing applications leveraged on specialized sensors embedded in the device. These novel mobile phone applications rely on advanced sensor information processes, which mainly involve raw data acquisition, feature extraction, data interpretation and transmission. However, the continuous accessing of sensing resources to acquire sensor data in smartphones is still very expensive in terms of energy, particularly due to the periodic use of power-intensive sensors, such as the Global Positioning System (GPS) receiver. The key underlying idea to design energy-efficient schemes is to control the duty cycle of the GPS receiver. However, adapting the sensing rate based on dynamic context changes through a flexible middleware has received little attention in the literature. In this paper, we propose a novel modular middleware architecture and runtime environment to directly interface with application programming interfaces (APIs) and embedded sensors in order to manage the duty cycle process based on energy and context aspects. The proposed solution has been implemented in the Android software stack. It allows continuous location tracking in a timely manner and in a transparent way to the user. It also enables the deployment of sensing policies to appropriately control the sampling rate based on both energy and perceived context. We validate the proposed solution taking into account a reference location-based service (LBS) architecture. A cloud-based storage service along with online mobility analysis tools have been used to store and access sensed data. Experimental measurements demonstrate the feasibility and efficiency of our middleware, in terms of energy and location resolution. PMID:25513821

Hypothesis on human eye perceiving optical spectrum rather than an image

NASA Astrophysics Data System (ADS)

Zheng, Yufeng; Szu, Harold

2015-05-01

It is a common knowledge that we see the world because our eyes can perceive an optical image. A digital camera seems a good example of simulating the eye imaging system. However, the signal sensing and imaging on human retina is very complicated. There are at least five layers (of neurons) along the signal pathway: photoreceptors (cones and rods), bipolar, horizontal, amacrine and ganglion cells. To sense an optical image, it seems that photoreceptors (as sensors) plus ganglion cells (converting to electrical signals for transmission) are good enough. Image sensing does not require ununiformed distribution of photoreceptors like fovea. There are some challenging questions, for example, why don't we feel the "blind spots" (never fibers exiting the eyes)? Similar situation happens to glaucoma patients who do not feel their vision loss until 50% or more nerves died. Now our hypothesis is that human retina initially senses optical (i.e., Fourier) spectrum rather than optical image. Due to the symmetric property of Fourier spectrum the signal loss from a blind spot or the dead nerves (for glaucoma patients) can be recovered. Eye logarithmic response to input light intensity much likes displaying Fourier magnitude. The optics and structures of human eyes satisfy the needs of optical Fourier spectrum sampling. It is unsure that where and how inverse Fourier transform is performed in human vision system to obtain an optical image. Phase retrieval technique in compressive sensing domain enables image reconstruction even without phase inputs. The spectrum-based imaging system can potentially tolerate up to 50% of bad sensors (pixels), adapt to large dynamic range (with logarithmic response), etc.

Mobile phone middleware architecture for energy and context awareness in location-based services.

PubMed

Galeana-Zapién, Hiram; Torres-Huitzil, César; Rubio-Loyola, Javier

2014-12-10

The disruptive innovation of smartphone technology has enabled the development of mobile sensing applications leveraged on specialized sensors embedded in the device. These novel mobile phone applications rely on advanced sensor information processes, which mainly involve raw data acquisition, feature extraction, data interpretation and transmission. However, the continuous accessing of sensing resources to acquire sensor data in smartphones is still very expensive in terms of energy, particularly due to the periodic use of power-intensive sensors, such as the Global Positioning System (GPS) receiver. The key underlying idea to design energy-efficient schemes is to control the duty cycle of the GPS receiver. However, adapting the sensing rate based on dynamic context changes through a flexible middleware has received little attention in the literature. In this paper, we propose a novel modular middleware architecture and runtime environment to directly interface with application programming interfaces (APIs) and embedded sensors in order to manage the duty cycle process based on energy and context aspects. The proposed solution has been implemented in the Android software stack. It allows continuous location tracking in a timely manner and in a transparent way to the user. It also enables the deployment of sensing policies to appropriately control the sampling rate based on both energy and perceived context. We validate the proposed solution taking into account a reference location-based service (LBS) architecture. A cloud-based storage service along with online mobility analysis tools have been used to store and access sensed data. Experimental measurements demonstrate the feasibility and efficiency of our middleware, in terms of energy and location resolution.

Phase Contrast Wavefront Sensing for Adaptive Optics

NASA Technical Reports Server (NTRS)

Bloemhof, E. E.; Wallace, J. K.; Bloemhof, E. E.

2004-01-01

Most ground-based adaptive optics systems use one of a small number of wavefront sensor technologies, notably (for relatively high-order systems) the Shack-Hartmann sensor, which provides local measurements of the phase slope (first-derivative) at a number of regularly-spaced points across the telescope pupil. The curvature sensor, with response proportional to the second derivative of the phase, is also sometimes used, but has undesirable noise propagation properties during wavefront reconstruction as the number of actuators becomes large. It is interesting to consider the use for astronomical adaptive optics of the "phase contrast" technique, originally developed for microscopy by Zemike to allow convenient viewing of phase objects. In this technique, the wavefront sensor provides a direct measurement of the local value of phase in each sub-aperture of the pupil. This approach has some obvious disadvantages compared to Shack-Hartmann wavefront sensing, but has some less obvious but substantial advantages as well. Here we evaluate the relative merits in a practical ground-based adaptive optics system.

Cystic fibrosis–adapted Pseudomonas aeruginosa quorum sensing lasR mutants cause hyperinflammatory responses

PubMed Central

LaFayette, Shantelle L.; Houle, Daniel; Beaudoin, Trevor; Wojewodka, Gabriella; Radzioch, Danuta; Hoffman, Lucas R.; Burns, Jane L.; Dandekar, Ajai A.; Smalley, Nicole E.; Chandler, Josephine R.; Zlosnik, James E.; Speert, David P.; Bernier, Joanie; Matouk, Elias; Brochiero, Emmanuelle; Rousseau, Simon; Nguyen, Dao

2015-01-01

Cystic fibrosis lung disease is characterized by chronic airway infections with the opportunistic pathogen Pseudomonas aeruginosa and severe neutrophilic pulmonary inflammation. P. aeruginosa undergoes extensive genetic adaptation to the cystic fibrosis (CF) lung environment, and adaptive mutations in the quorum sensing regulator gene lasR commonly arise. We sought to define how mutations in lasR alter host-pathogen relationships. We demonstrate that lasR mutants induce exaggerated host inflammatory responses in respiratory epithelial cells, with increased accumulation of proinflammatory cytokines and neutrophil recruitment due to the loss of bacterial protease–dependent cytokine degradation. In subacute pulmonary infections, lasR mutant–infected mice show greater neutrophilic inflammation and immunopathology compared with wild-type infections. Finally, we observed that CF patients infected with lasR mutants have increased plasma interleukin-8 (IL-8), a marker of inflammation. These findings suggest that bacterial adaptive changes may worsen pulmonary inflammation and directly contribute to the pathogenesis and progression of chronic lung disease in CF patients. PMID:26457326

Nanoparticle–Film Plasmon Ruler Interrogated with Transmission Visible Spectroscopy

PubMed Central

2015-01-01

The widespread use of plasmonic nanorulers (PNRs) in sensing platforms has been plagued by technical challenges associated with the development of methods to fabricate precisely controlled nanostructures with high yield and characterize them with high throughput. We have previously shown that creating PNRs in a nanoparticle–film (NP–film) format enables the fabrication of an extremely large population of uniform PNRs with 100% yield using a self-assembly approach, which facilitates high-throughput PNR characterization using ensemble spectroscopic measurements and eliminates the need for expensive microscopy systems required by many other PNR platforms. We expand upon this prior work herein, showing that the NP–film PNR can be made compatible with aqueous sensing studies by adapting it for use in a transmission localized surface plasmon resonance spectroscopy format, where the coupled NP–film resonance responsible for the PNR signal is directly probed using an extinction measurement from a standard spectrophotometer. We designed slide holders that fit inside standard spectrophotometer cuvettes and position NP–film samples so that the coupled NP–film resonance can be detected in a collinear optical configuration. Once the NP–film PNR samples are cuvette-compatible, it is straightforward to calibrate the PNR in aqueous solution and use it to characterize dynamic, angstrom-scale distance changes resulting from pH-induced swelling of polyelectrolyte (PE) spacer layers as thin as 1 PE layer and also of a self-assembled monolayer of an amine-terminated alkanethiol. This development is an important step toward making PNR sensors more user-friendly and encouraging their widespread use in various sensing schemes. PMID:25541618

An infrared-visible image fusion scheme based on NSCT and compressed sensing

NASA Astrophysics Data System (ADS)

Zhang, Qiong; Maldague, Xavier

2015-05-01

Image fusion, as a research hot point nowadays in the field of infrared computer vision, has been developed utilizing different varieties of methods. Traditional image fusion algorithms are inclined to bring problems, such as data storage shortage and computational complexity increase, etc. Compressed sensing (CS) uses sparse sampling without knowing the priori knowledge and greatly reconstructs the image, which reduces the cost and complexity of image processing. In this paper, an advanced compressed sensing image fusion algorithm based on non-subsampled contourlet transform (NSCT) is proposed. NSCT provides better sparsity than the wavelet transform in image representation. Throughout the NSCT decomposition, the low-frequency and high-frequency coefficients can be obtained respectively. For the fusion processing of low-frequency coefficients of infrared and visible images , the adaptive regional energy weighting rule is utilized. Thus only the high-frequency coefficients are specially measured. Here we use sparse representation and random projection to obtain the required values of high-frequency coefficients, afterwards, the coefficients of each image block can be fused via the absolute maximum selection rule and/or the regional standard deviation rule. In the reconstruction of the compressive sampling results, a gradient-based iterative algorithm and the total variation (TV) method are employed to recover the high-frequency coefficients. Eventually, the fused image is recovered by inverse NSCT. Both the visual effects and the numerical computation results after experiments indicate that the presented approach achieves much higher quality of image fusion, accelerates the calculations, enhances various targets and extracts more useful information.

The NRL relocatable ocean/acoustic ensemble forecast system

NASA Astrophysics Data System (ADS)

Rowley, C.; Martin, P.; Cummings, J.; Jacobs, G.; Coelho, E.; Bishop, C.; Hong, X.; Peggion, G.; Fabre, J.

2009-04-01

A globally relocatable regional ocean nowcast/forecast system has been developed to support rapid implementation of new regional forecast domains. The system is in operational use at the Naval Oceanographic Office for a growing number of regional and coastal implementations. The new system is the basis for an ocean acoustic ensemble forecast and adaptive sampling capability. We present an overview of the forecast system and the ocean ensemble and adaptive sampling methods. The forecast system consists of core ocean data analysis and forecast modules, software for domain configuration, surface and boundary condition forcing processing, and job control, and global databases for ocean climatology, bathymetry, tides, and river locations and transports. The analysis component is the Navy Coupled Ocean Data Assimilation (NCODA) system, a 3D multivariate optimum interpolation system that produces simultaneous analyses of temperature, salinity, geopotential, and vector velocity using remotely-sensed SST, SSH, and sea ice concentration, plus in situ observations of temperature, salinity, and currents from ships, buoys, XBTs, CTDs, profiling floats, and autonomous gliders. The forecast component is the Navy Coastal Ocean Model (NCOM). The system supports one-way nesting and multiple assimilation methods. The ensemble system uses the ensemble transform technique with error variance estimates from the NCODA analysis to represent initial condition error. Perturbed surface forcing or an atmospheric ensemble is used to represent errors in surface forcing. The ensemble transform Kalman filter is used to assess the impact of adaptive observations on future analysis and forecast uncertainty for both ocean and acoustic properties.

Co-Adaptive Aiding and Automation Enhance Operator Performance

DTIC Science & Technology

2013-03-01

activation system. There is a close relation between physiologically activated adaptive aiding and brain- computer interfaces ( BCI ). BCI here refers...classification of EEG signals (Farwell & Donchin, 1988). Physiologically activated adaptive aiding is, in a sense, a special case of BCI wherein the...as passive BCI , e.g. Zander, Kothe, Jatzev, & 3 Distribution A: Approved for public release; distribution unlimited. 88 ABW Cleared 05/13/2013

Towards a framework for agent-based image analysis of remote-sensing data

PubMed Central

Hofmann, Peter; Lettmayer, Paul; Blaschke, Thomas; Belgiu, Mariana; Wegenkittl, Stefan; Graf, Roland; Lampoltshammer, Thomas Josef; Andrejchenko, Vera

2015-01-01

Object-based image analysis (OBIA) as a paradigm for analysing remotely sensed image data has in many cases led to spatially and thematically improved classification results in comparison to pixel-based approaches. Nevertheless, robust and transferable object-based solutions for automated image analysis capable of analysing sets of images or even large image archives without any human interaction are still rare. A major reason for this lack of robustness and transferability is the high complexity of image contents: Especially in very high resolution (VHR) remote-sensing data with varying imaging conditions or sensor characteristics, the variability of the objects’ properties in these varying images is hardly predictable. The work described in this article builds on so-called rule sets. While earlier work has demonstrated that OBIA rule sets bear a high potential of transferability, they need to be adapted manually, or classification results need to be adjusted manually in a post-processing step. In order to automate these adaptation and adjustment procedures, we investigate the coupling, extension and integration of OBIA with the agent-based paradigm, which is exhaustively investigated in software engineering. The aims of such integration are (a) autonomously adapting rule sets and (b) image objects that can adopt and adjust themselves according to different imaging conditions and sensor characteristics. This article focuses on self-adapting image objects and therefore introduces a framework for agent-based image analysis (ABIA). PMID:27721916

Towards a framework for agent-based image analysis of remote-sensing data.

PubMed

Hofmann, Peter; Lettmayer, Paul; Blaschke, Thomas; Belgiu, Mariana; Wegenkittl, Stefan; Graf, Roland; Lampoltshammer, Thomas Josef; Andrejchenko, Vera

2015-04-03

Object-based image analysis (OBIA) as a paradigm for analysing remotely sensed image data has in many cases led to spatially and thematically improved classification results in comparison to pixel-based approaches. Nevertheless, robust and transferable object-based solutions for automated image analysis capable of analysing sets of images or even large image archives without any human interaction are still rare. A major reason for this lack of robustness and transferability is the high complexity of image contents: Especially in very high resolution (VHR) remote-sensing data with varying imaging conditions or sensor characteristics, the variability of the objects' properties in these varying images is hardly predictable. The work described in this article builds on so-called rule sets. While earlier work has demonstrated that OBIA rule sets bear a high potential of transferability, they need to be adapted manually, or classification results need to be adjusted manually in a post-processing step. In order to automate these adaptation and adjustment procedures, we investigate the coupling, extension and integration of OBIA with the agent-based paradigm, which is exhaustively investigated in software engineering. The aims of such integration are (a) autonomously adapting rule sets and (b) image objects that can adopt and adjust themselves according to different imaging conditions and sensor characteristics. This article focuses on self-adapting image objects and therefore introduces a framework for agent-based image analysis (ABIA).

Balancing Vibrations at Harmonic Frequencies by Injecting Harmonic Balancing Signals into the Armature of a Linear Motor/Alternator Coupled to a Stirling Machine

NASA Technical Reports Server (NTRS)

Holliday, Ezekiel S. (Inventor)

2014-01-01

Vibrations at harmonic frequencies are reduced by injecting harmonic balancing signals into the armature of a linear motor/alternator coupled to a Stirling machine. The vibrations are sensed to provide a signal representing the mechanical vibrations. A harmonic balancing signal is generated for selected harmonics of the operating frequency by processing the sensed vibration signal with adaptive filter algorithms of adaptive filters for each harmonic. Reference inputs for each harmonic are applied to the adaptive filter algorithms at the frequency of the selected harmonic. The harmonic balancing signals for all of the harmonics are summed with a principal control signal. The harmonic balancing signals modify the principal electrical drive voltage and drive the motor/alternator with a drive voltage component in opposition to the vibration at each harmonic.

Energy-efficient sensing in wireless sensor networks using compressed sensing.

PubMed

Razzaque, Mohammad Abdur; Dobson, Simon

2014-02-12

Sensing of the application environment is the main purpose of a wireless sensor network. Most existing energy management strategies and compression techniques assume that the sensing operation consumes significantly less energy than radio transmission and reception. This assumption does not hold in a number of practical applications. Sensing energy consumption in these applications may be comparable to, or even greater than, that of the radio. In this work, we support this claim by a quantitative analysis of the main operational energy costs of popular sensors, radios and sensor motes. In light of the importance of sensing level energy costs, especially for power hungry sensors, we consider compressed sensing and distributed compressed sensing as potential approaches to provide energy efficient sensing in wireless sensor networks. Numerical experiments investigating the effectiveness of compressed sensing and distributed compressed sensing using real datasets show their potential for efficient utilization of sensing and overall energy costs in wireless sensor networks. It is shown that, for some applications, compressed sensing and distributed compressed sensing can provide greater energy efficiency than transform coding and model-based adaptive sensing in wireless sensor networks.

Wheat proteomics: proteome modulation and abiotic stress acclimation

PubMed Central

Komatsu, Setsuko; Kamal, Abu H. M.; Hossain, Zahed

2014-01-01

Cellular mechanisms of stress sensing and signaling represent the initial plant responses to adverse conditions. The development of high-throughput “Omics” techniques has initiated a new era of the study of plant molecular strategies for adapting to environmental changes. However, the elucidation of stress adaptation mechanisms in plants requires the accurate isolation and characterization of stress-responsive proteins. Because the functional part of the genome, namely the proteins and their post-translational modifications, are critical for plant stress responses, proteomic studies provide comprehensive information about the fine-tuning of cellular pathways that primarily involved in stress mitigation. This review summarizes the major proteomic findings related to alterations in the wheat proteomic profile in response to abiotic stresses. Moreover, the strengths and weaknesses of different sample preparation techniques, including subcellular protein extraction protocols, are discussed in detail. The continued development of proteomic approaches in combination with rapidly evolving bioinformatics tools and interactive databases will facilitate understanding of the plant mechanisms underlying stress tolerance. PMID:25538718

Morphology of the eyeball from the Humpback whale (Megaptera novaeangliae).

PubMed

Rodrigues, Fernanda M; Silva, Fernanda M O; Trompieri-Silveira, Ana Carolina; Vergara-Parente, Jociery E; Miglino, Maria Angélica; Guimarães, Juliana P

2014-05-01

Aquatic mammals underwent morphological and physiological adaptations due to the transition from terrestrial to aquatic environment. One of the morphological changes regards their vision since cetaceans' eyes are able to withstand mechanical, chemical, osmotic, and optical water conditions. Due to insufficient information about these animals, especially regarding their sense organs, this study aimed to describe the morphology of the Humpback whale (Megaptera novaeangliae) eyeball. Three newborn females, stranded dead on the coast of Sergipe and Bahia, Brazil, were used. Samples were fixed in a 10% formalin solution, dissected, photographed, collected, and evaluated through light and electron microscopy techniques. The Humpback whale sclera was thick and had an irregular surface with mechanoreceptors in its lamina propria. Lens was dense, transparent, and ellipsoidal, consisting of three layers, and the vascularized choroid contains melanocytes, mechanoreceptors, and a fibrous tapetum lucidum. The Humpback whale eyeball is similar to other cetaceans and suggests an adaptation to diving and migration, contributing to the perception of differences in temperature, pressure, and lighting. Copyright © 2014 Wiley Periodicals, Inc.

The PALM-3000 high-order adaptive optics system for Palomar Observatory

NASA Astrophysics Data System (ADS)

Bouchez, Antonin H.; Dekany, Richard G.; Angione, John R.; Baranec, Christoph; Britton, Matthew C.; Bui, Khanh; Burruss, Rick S.; Cromer, John L.; Guiwits, Stephen R.; Henning, John R.; Hickey, Jeff; McKenna, Daniel L.; Moore, Anna M.; Roberts, Jennifer E.; Trinh, Thang Q.; Troy, Mitchell; Truong, Tuan N.; Velur, Viswa

2008-07-01

Deployed as a multi-user shared facility on the 5.1 meter Hale Telescope at Palomar Observatory, the PALM-3000 highorder upgrade to the successful Palomar Adaptive Optics System will deliver extreme AO correction in the near-infrared, and diffraction-limited images down to visible wavelengths, using both natural and sodium laser guide stars. Wavefront control will be provided by two deformable mirrors, a 3368 active actuator woofer and 349 active actuator tweeter, controlled at up to 3 kHz using an innovative wavefront processor based on a cluster of 17 graphics processing units. A Shack-Hartmann wavefront sensor with selectable pupil sampling will provide high-order wavefront sensing, while an infrared tip/tilt sensor and visible truth wavefront sensor will provide low-order LGS control. Four back-end instruments are planned at first light: the PHARO near-infrared camera/spectrograph, the SWIFT visible light integral field spectrograph, Project 1640, a near-infrared coronagraphic integral field spectrograph, and 888Cam, a high-resolution visible light imager.

The cellular transducer in bone: What is it?

PubMed

Taylor, David; Hazenberg, Jan; Lee, T Clive

2006-01-01

Bone is able to detect its strain environment and respond accordingly. In particular it is able to adapt to over-use and under-use by bone deposition or resorption. How can bone sense strain? Various physical mechanisms have been proposed for the so-called cellular transducer, but there is no conclusive proof for any one of them. This paper examines the theories and evidence, with particular reference to a new theory proposed by the authors, involving damage to cellular processes by microcracks. Experiments on bone samples ex-vivo showed that cracks cannot fracture osteocytes, but that cellular processes which span the crack can be broken. A theoretical model was developed for predicting the number of broken processes as a function of crack size and applied stress. This showed that signals emitted by fractured processes could be used to detect cracks which needed repairing and to provide information on the overall level of damage which could be used to initiate repair and adaptation responses.

Innate Immune sensing of DNA viruses

PubMed Central

Rathinam, Vijay A. K.; Fitzgerald, Katherine A.

2011-01-01

DNA viruses are a significant contributor to human morbidity and mortality. The immune system protects against viral infections through coordinated innate and adaptive immune responses. While the antigen-specific adaptive mechanisms have been extensively studied, the critical contributions of innate immunity to anti-viral defenses have only been revealed in the very recent past. Central to these anti-viral defenses is the recognition of viral pathogens by a diverse set of germ-line encoded receptors that survey nearly all cellular compartments for the presence of pathogens. In this review, we discuss the recent advances in the innate immune sensing of DNA viruses and focus on the recognition mechanisms involved. PMID:21334037

Using a Microbial Physiologic and Genetic Approach to Investigate How Bacteria Sense Physical Stimuli

ERIC Educational Resources Information Center

Mussi, María Alejandra; Actis, Luis A.; de Mendoza, Diego; Cybulski, Larisa E.

2014-01-01

A laboratory exercise was designed to illustrate how physical stimuli such as temperature and light are sensed and processed by bacteria to elaborate adaptive responses. In particular, we use the well-characterized Des pathway of "Bacillus subtilis" to show that temperature modulates gene expression, resulting ultimately in modification…

A hyper-temporal remote sensing protocol for detecting ecosystem disturbance, classifying ecological state, and assessing soil resilience

USDA-ARS?s Scientific Manuscript database

Hyper-temporal remote sensing is capable of detecting detailed information on vegetation dynamics relating to plant functional types (PFT), a useful proxy for estimating soil physical and chemical properties. A central concept of PFT is that plant morphological and physiological adaptations are link...

Mapping high-resolution soil moisture and properties using distributed temperature sensing data and an adaptive particle batch smoother

USDA-ARS?s Scientific Manuscript database

This study demonstrated a new method for mapping high-resolution (spatial: 1 m, and temporal: 1 h) soil moisture by assimilating distributed temperature sensing (DTS) observed soil temperatures at intermediate scales. In order to provide robust soil moisture and property estimates, we first proposed...

Experimental results for correlation-based wavefront sensing

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

Poyneer, L A; Palmer, D W; LaFortune, K N

2005-07-01

Correlation wave-front sensing can improve Adaptive Optics (AO) system performance in two keys areas. For point-source-based AO systems, Correlation is more accurate, more robust to changing conditions and provides lower noise than a centroiding algorithm. Experimental results from the Lick AO system and the SSHCL laser AO system confirm this. For remote imaging, Correlation enables the use of extended objects for wave-front sensing. Results from short horizontal-path experiments will show algorithm properties and requirements.

Evolutionary Specialization of Tactile Perception in Vertebrates.

PubMed

Schneider, Eve R; Gracheva, Elena O; Bagriantsev, Slav N

2016-05-01

Evolution has endowed vertebrates with the remarkable tactile ability to explore the world through the perception of physical force. Yet the sense of touch remains one of the least well understood senses at the cellular and molecular level. Vertebrates specializing in tactile perception can highlight general principles of mechanotransduction. Here, we review cellular and molecular adaptations that underlie the sense of touch in typical and acutely mechanosensitive vertebrates. ©2016 Int. Union Physiol. Sci./Am. Physiol. Soc.

Optimize the Coverage Probability of Prediction Interval for Anomaly Detection of Sensor-Based Monitoring Series

PubMed Central

Liu, Datong; Peng, Yu; Peng, Xiyuan

2018-01-01

Effective anomaly detection of sensing data is essential for identifying potential system failures. Because they require no prior knowledge or accumulated labels, and provide uncertainty presentation, the probability prediction methods (e.g., Gaussian process regression (GPR) and relevance vector machine (RVM)) are especially adaptable to perform anomaly detection for sensing series. Generally, one key parameter of prediction models is coverage probability (CP), which controls the judging threshold of the testing sample and is generally set to a default value (e.g., 90% or 95%). There are few criteria to determine the optimal CP for anomaly detection. Therefore, this paper designs a graphic indicator of the receiver operating characteristic curve of prediction interval (ROC-PI) based on the definition of the ROC curve which can depict the trade-off between the PI width and PI coverage probability across a series of cut-off points. Furthermore, the Youden index is modified to assess the performance of different CPs, by the minimization of which the optimal CP is derived by the simulated annealing (SA) algorithm. Experiments conducted on two simulation datasets demonstrate the validity of the proposed method. Especially, an actual case study on sensing series from an on-orbit satellite illustrates its significant performance in practical application. PMID:29587372

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.

Spatio-Temporal Super-Resolution Reconstruction of Remote-Sensing Images Based on Adaptive Multi-Scale Detail Enhancement

PubMed Central

Zhu, Hong; Tang, Xinming; Xie, Junfeng; Song, Weidong; Mo, Fan; Gao, Xiaoming

2018-01-01

There are many problems in existing reconstruction-based super-resolution algorithms, such as the lack of texture-feature representation and of high-frequency details. Multi-scale detail enhancement can produce more texture information and high-frequency information. Therefore, super-resolution reconstruction of remote-sensing images based on adaptive multi-scale detail enhancement (AMDE-SR) is proposed in this paper. First, the information entropy of each remote-sensing image is calculated, and the image with the maximum entropy value is regarded as the reference image. Subsequently, spatio-temporal remote-sensing images are processed using phase normalization, which is to reduce the time phase difference of image data and enhance the complementarity of information. The multi-scale image information is then decomposed using the L0 gradient minimization model, and the non-redundant information is processed by difference calculation and expanding non-redundant layers and the redundant layer by the iterative back-projection (IBP) technique. The different-scale non-redundant information is adaptive-weighted and fused using cross-entropy. Finally, a nonlinear texture-detail-enhancement function is built to improve the scope of small details, and the peak signal-to-noise ratio (PSNR) is used as an iterative constraint. Ultimately, high-resolution remote-sensing images with abundant texture information are obtained by iterative optimization. Real results show an average gain in entropy of up to 0.42 dB for an up-scaling of 2 and a significant promotion gain in enhancement measure evaluation for an up-scaling of 2. The experimental results show that the performance of the AMED-SR method is better than existing super-resolution reconstruction methods in terms of visual and accuracy improvements. PMID:29414893

Spatio-Temporal Super-Resolution Reconstruction of Remote-Sensing Images Based on Adaptive Multi-Scale Detail Enhancement.

PubMed

Zhu, Hong; Tang, Xinming; Xie, Junfeng; Song, Weidong; Mo, Fan; Gao, Xiaoming

2018-02-07

There are many problems in existing reconstruction-based super-resolution algorithms, such as the lack of texture-feature representation and of high-frequency details. Multi-scale detail enhancement can produce more texture information and high-frequency information. Therefore, super-resolution reconstruction of remote-sensing images based on adaptive multi-scale detail enhancement (AMDE-SR) is proposed in this paper. First, the information entropy of each remote-sensing image is calculated, and the image with the maximum entropy value is regarded as the reference image. Subsequently, spatio-temporal remote-sensing images are processed using phase normalization, which is to reduce the time phase difference of image data and enhance the complementarity of information. The multi-scale image information is then decomposed using the L ₀ gradient minimization model, and the non-redundant information is processed by difference calculation and expanding non-redundant layers and the redundant layer by the iterative back-projection (IBP) technique. The different-scale non-redundant information is adaptive-weighted and fused using cross-entropy. Finally, a nonlinear texture-detail-enhancement function is built to improve the scope of small details, and the peak signal-to-noise ratio (PSNR) is used as an iterative constraint. Ultimately, high-resolution remote-sensing images with abundant texture information are obtained by iterative optimization. Real results show an average gain in entropy of up to 0.42 dB for an up-scaling of 2 and a significant promotion gain in enhancement measure evaluation for an up-scaling of 2. The experimental results show that the performance of the AMED-SR method is better than existing super-resolution reconstruction methods in terms of visual and accuracy improvements.

Online vegetation parameter estimation using passive microwave remote sensing observations

USDA-ARS?s Scientific Manuscript database

In adaptive system identification the Kalman filter can be used to identify the coefficient of the observation operator of a linear system. Here the ensemble Kalman filter is tested for adaptive online estimation of the vegetation opacity parameter of a radiative transfer model. A state augmentatio...

Adaptive compressive learning for prediction of protein-protein interactions from primary sequence.

PubMed

Zhang, Ya-Nan; Pan, Xiao-Yong; Huang, Yan; Shen, Hong-Bin

2011-08-21

Protein-protein interactions (PPIs) play an important role in biological processes. Although much effort has been devoted to the identification of novel PPIs by integrating experimental biological knowledge, there are still many difficulties because of lacking enough protein structural and functional information. It is highly desired to develop methods based only on amino acid sequences for predicting PPIs. However, sequence-based predictors are often struggling with the high-dimensionality causing over-fitting and high computational complexity problems, as well as the redundancy of sequential feature vectors. In this paper, a novel computational approach based on compressed sensing theory is proposed to predict yeast Saccharomyces cerevisiae PPIs from primary sequence and has achieved promising results. The key advantage of the proposed compressed sensing algorithm is that it can compress the original high-dimensional protein sequential feature vector into a much lower but more condensed space taking the sparsity property of the original signal into account. What makes compressed sensing much more attractive in protein sequence analysis is its compressed signal can be reconstructed from far fewer measurements than what is usually considered necessary in traditional Nyquist sampling theory. Experimental results demonstrate that proposed compressed sensing method is powerful for analyzing noisy biological data and reducing redundancy in feature vectors. The proposed method represents a new strategy of dealing with high-dimensional protein discrete model and has great potentiality to be extended to deal with many other complicated biological systems. Copyright © 2011 Elsevier Ltd. All rights reserved.

Contribution of the cyclic nucleotide gated channel subunit, CNG-3, to olfactory plasticity in Caenorhabditis elegans.

PubMed

O'Halloran, Damien M; Altshuler-Keylin, Svetlana; Zhang, Xiao-Dong; He, Chao; Morales-Phan, Christopher; Yu, Yawei; Kaye, Julia A; Brueggemann, Chantal; Chen, Tsung-Yu; L'Etoile, Noelle D

2017-03-13

In Caenorhabditis elegans, the AWC neurons are thought to deploy a cGMP signaling cascade in the detection of and response to AWC sensed odors. Prolonged exposure to an AWC sensed odor in the absence of food leads to reversible decreases in the animal's attraction to that odor. This adaptation exhibits two stages referred to as short-term and long-term adaptation. Previously, the protein kinase G (PKG), EGL-4/PKG-1, was shown necessary for both stages of adaptation and phosphorylation of its target, the beta-type cyclic nucleotide gated (CNG) channel subunit, TAX-2, was implicated in the short term stage. Here we uncover a novel role for the CNG channel subunit, CNG-3, in short term adaptation. We demonstrate that CNG-3 is required in the AWC for adaptation to short (thirty minute) exposures of odor, and contains a candidate PKG phosphorylation site required to tune odor sensitivity. We also provide in vivo data suggesting that CNG-3 forms a complex with both TAX-2 and TAX-4 CNG channel subunits in AWC. Finally, we examine the physiology of different CNG channel subunit combinations.

Automated touch sensing in the mouse tapered beam test using Raspberry Pi.

PubMed

Ardesch, Dirk Jan; Balbi, Matilde; Murphy, Timothy H

2017-11-01

Rodent models of neurological disease such as stroke are often characterized by motor deficits. One of the tests that are used to assess these motor deficits is the tapered beam test, which provides a sensitive measure of bilateral motor function based on foot faults (slips) made by a rodent traversing a gradually narrowing beam. However, manual frame-by-frame scoring of video recordings is necessary to obtain test results, which is time-consuming and prone to human rater bias. We present a cost-effective method for automated touch sensing in the tapered beam test. Capacitive touch sensors detect foot faults onto the beam through a layer of conductive paint, and results are processed and stored on a Raspberry Pi computer. Automated touch sensing using this method achieved high sensitivity (96.2%) as compared to 'gold standard' manual video scoring. Furthermore, it provided a reliable measure of lateralized motor deficits in mice with unilateral photothrombotic stroke: results indicated an increased number of contralesional foot faults for up to 6days after ischemia. The automated adaptation of the tapered beam test produces results immediately after each trial, without the need for labor-intensive post-hoc video scoring. It also increases objectivity of the data as it requires less experimenter involvement during analysis. Automated touch sensing may provide a useful adaptation to the existing tapered beam test in mice, while the simplicity of the hardware lends itself to potential further adaptations to related behavioral tests. Copyright © 2017 Elsevier B.V. All rights reserved.

Small numbers are sensed directly, high numbers constructed from size and density.

PubMed

Zimmermann, Eckart

2018-04-01

Two theories compete to explain how we estimate the numerosity of visual object sets. The first suggests that the apparent numerosity is derived from an analysis of more low-level features like size and density of the set. The second theory suggests that numbers are sensed directly. Consistent with the latter claim is the existence of neurons in parietal cortex which are specialized for processing the numerosity of elements in the visual scene. However, recent evidence suggests that only low numbers can be sensed directly whereas the perception of high numbers is supported by the analysis of low-level features. Processing of low and high numbers, being located at different levels of the neural hierarchy should involve different receptive field sizes. Here, I tested this idea with visual adaptation. I measured the spatial spread of number adaptation for low and high numerosities. A focused adaptation spread of high numerosities suggested the involvement of early neural levels where receptive fields are comparably small and the broad spread for low numerosities was consistent with processing of number neurons which have larger receptive fields. These results provide evidence for the claim that different mechanism exist generating the perception of visual numerosity. Whereas low numbers are sensed directly as a primary visual attribute, the estimation of high numbers however likely depends on the area size over which the objects are spread. Copyright © 2017 Elsevier B.V. All rights reserved.

A Bioinspired Mineral Hydrogel as a Self-Healable, Mechanically Adaptable Ionic Skin for Highly Sensitive Pressure Sensing.

PubMed

Lei, Zhouyue; Wang, Quankang; Sun, Shengtong; Zhu, Wencheng; Wu, Peiyi

2017-06-01

In the past two decades, artificial skin-like materials have received increasing research interests for their broad applications in artificial intelligence, wearable devices, and soft robotics. However, profound challenges remain in terms of imitating human skin because of its unique combination of mechanical and sensory properties. In this work, a bioinspired mineral hydrogel is developed to fabricate a novel type of mechanically adaptable ionic skin sensor. Due to its unique viscoelastic properties, the hydrogel-based capacitive sensor is compliant, self-healable, and can sense subtle pressure changes, such as a gentle finger touch, human motion, or even small water droplets. It might not only show great potential in applications such as artificial intelligence, human/machine interactions, personal healthcare, and wearable devices, but also promote the development of next-generation mechanically adaptable intelligent skin-like devices. © 2017 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

Adaptive tracking of a time-varying field with a quantum sensor

NASA Astrophysics Data System (ADS)

Bonato, Cristian; Berry, Dominic W.

2017-05-01

Sensors based on single spins can enable magnetic-field detection with very high sensitivity and spatial resolution. Previous work has concentrated on sensing of a constant magnetic field or a periodic signal. Here, we instead investigate the problem of estimating a field with nonperiodic variation described by a Wiener process. We propose and study, by numerical simulations, an adaptive tracking protocol based on Bayesian estimation. The tracking protocol updates the probability distribution for the magnetic field based on measurement outcomes and adapts the choice of sensing time and phase in real time. By taking the statistical properties of the signal into account, our protocol strongly reduces the required measurement time. This leads to a reduction of the error in the estimation of a time-varying signal by up to a factor of four compare with protocols that do not take this information into account.

Driving an Active Vibration Balancer to Minimize Vibrations at the Fundamental and Harmonic Frequencies

NASA Technical Reports Server (NTRS)

Holliday, Ezekiel S. (Inventor)

2014-01-01

Vibrations of a principal machine are reduced at the fundamental and harmonic frequencies by driving the drive motor of an active balancer with balancing signals at the fundamental and selected harmonics. Vibrations are sensed to provide a signal representing the mechanical vibrations. A balancing signal generator for the fundamental and for each selected harmonic processes the sensed vibration signal with adaptive filter algorithms of adaptive filters for each frequency to generate a balancing signal for each frequency. Reference inputs for each frequency are applied to the adaptive filter algorithms of each balancing signal generator at the frequency assigned to the generator. The harmonic balancing signals for all of the frequencies are summed and applied to drive the drive motor. The harmonic balancing signals drive the drive motor with a drive voltage component in opposition to the vibration at each frequency.

MobiDiC: Context Adaptive Digital Signage with Coupons

NASA Astrophysics Data System (ADS)

Müller, Jörg; Krüger, Antonio

In this paper we present a field study of a digital signage system that measures audience response with coupons in order to enable context adaptivity. In the concept for context adaptivity, the signs sense their environment; decide which content to show, and then sense the audience reaction to the content shown. From this audience measurement, the strategies which content to show in which situation are refined. As one instantiation of audience measurement, we propose a novel simple couponing system, where customers can photograph the coupons at the signs. Thus, it can be measured whether customers really went to the shop. To investigate the feasibility of this approach, we implemented a prototype of 20 signs in the city center of Münster, Germany. During one year of deployment, we investigated usage of the system through interviews with shop owners and customers. Our experiences show that customer attention towards the signs is a major hurdle to overcome.

Control of adaptive immunity by the innate immune system.

PubMed

Iwasaki, Akiko; Medzhitov, Ruslan

2015-04-01

Microbial infections are recognized by the innate immune system both to elicit immediate defense and to generate long-lasting adaptive immunity. To detect and respond to vastly different groups of pathogens, the innate immune system uses several recognition systems that rely on sensing common structural and functional features associated with different classes of microorganisms. These recognition systems determine microbial location, viability, replication and pathogenicity. Detection of these features by recognition pathways of the innate immune system is translated into different classes of effector responses though specialized populations of dendritic cells. Multiple mechanisms for the induction of immune responses are variations on a common design principle wherein the cells that sense infections produce one set of cytokines to induce lymphocytes to produce another set of cytokines, which in turn activate effector responses. Here we discuss these emerging principles of innate control of adaptive immunity.

Interplay between environmentally modulated feedback loops - hypoxia and circadian rhythms - two sides of the same coin?

PubMed

Depping, Reinhard; Oster, Henrik

2017-11-01

Sensing of environmental parameters is critically important for cells of metazoan organisms. Members of the superfamily of bHLH-PAS transcription factors, involved in oxygen sensing and circadian rhythm generation, are important players in such molecular pathways. The interplay between both networks includes a so far unknown factor, connecting PER2 (circadian clocks) to hypoxia sensing (HIF-1 α) to result in a more adapted state of homeostasis at the right time. © 2017 Federation of European Biochemical Societies.

USDA/federal user of LANDSAT remote sensing

NASA Technical Reports Server (NTRS)

Allen, R.

1981-01-01

Developed and potential uses of remote sensing in crop condition and acreage assessment, renewable resources inventories, conservation practices, and water and forest management applications are described. Operational approaches, the adaptation of procedures to needs, and the agency's concern about data continuity and cost are discussed as well as support for future technology development for enhanced sensing capability. The use of improved camera systems for soil mapping and conservation monitoring from space shuttle, and of aerospace radar to improve soil moisture monitoring are mentioned.

Lack of Interaction between Sensing-Intuitive Learning Styles and Problem-First versus Information-First Instruction: A Randomized Crossover Trial

ERIC Educational Resources Information Center

Cook, David A.; Thompson, Warren G.; Thomas, Kris G.; Thomas, Matthew R.

2009-01-01

Background: Adaptation to learning styles has been proposed to enhance learning. Objective: We hypothesized that learners with sensing learning style would perform better using a problem-first instructional method while intuitive learners would do better using an information-first method. Design: Randomized, controlled, crossover trial. Setting:…

Common Sense Parenting of Toddlers and Preschoolers. A Girls and Boys Town Program.

ERIC Educational Resources Information Center

Barnes, Bridget A.; York, Steven M.

Based on the view that parents need to balance nurturing behaviors that demonstrate love and affection with the discipline that children need in order to learn and thrive, this book presents the Common Sense Parenting program from Girls and Boys Town as adapted for parents of toddlers and preschoolers. Offering logical techniques and foundations…

University Students' Sense of Belonging to the Home Town: The Role of Residential Mobility

ERIC Educational Resources Information Center

Cicognani, Elvira; Menezes, Isabel; Nata, Gil

2011-01-01

In the study of young people's relationships with residential contexts, it is important to consider the role of developmental tasks (e.g. identity construction, academic and professional choices, etc.) in influencing Place Identity and Sense of Community. Residential mobility may represent an adaptive strategy for modifying some aspects of one's…

Measurement Equivalence of Teachers' Sense of Efficacy Scale Using Latent Growth Methods

ERIC Educational Resources Information Center

Basokçu, T. Oguz; Ögretmen, T.

2016-01-01

This study is based on the application of latent growth modeling, which is one of structural equation models on real data. Teachers' Sense of Efficacy Scale (TSES), which was previously adapted into Turkish was administered to 200 preservice teachers at different time intervals for three times and study data was collected. Measurement equivalence…

Level of Sense-Making in Children with Autistic Disorder and Intellectual Disability: Patterns of Delay and Deviance in Development

ERIC Educational Resources Information Center

Maljaars, Jarymke; Noens, Ilse; Scholte, Evert; van Berckelaer-Onnes, Ina

2012-01-01

The present study examined levels of sense-making in relation to adaptive functioning and autism symptomatology in low-functioning children with autistic disorder. Thirty-six children with autistic disorder and intellectual disability were compared with 27 children with intellectual disability and 33 typically developing children with a comparable…

Principles underlying the design of "The Number Race", an adaptive computer game for remediation of dyscalculia.

PubMed

Wilson, Anna J; Dehaene, Stanislas; Pinel, Philippe; Revkin, Susannah K; Cohen, Laurent; Cohen, David

2006-05-30

Adaptive game software has been successful in remediation of dyslexia. Here we describe the cognitive and algorithmic principles underlying the development of similar software for dyscalculia. Our software is based on current understanding of the cerebral representation of number and the hypotheses that dyscalculia is due to a "core deficit" in number sense or in the link between number sense and symbolic number representations. "The Number Race" software trains children on an entertaining numerical comparison task, by presenting problems adapted to the performance level of the individual child. We report full mathematical specifications of the algorithm used, which relies on an internal model of the child's knowledge in a multidimensional "learning space" consisting of three difficulty dimensions: numerical distance, response deadline, and conceptual complexity (from non-symbolic numerosity processing to increasingly complex symbolic operations). The performance of the software was evaluated both by mathematical simulations and by five weeks of use by nine children with mathematical learning difficulties. The results indicate that the software adapts well to varying levels of initial knowledge and learning speeds. Feedback from children, parents and teachers was positive. A companion article describes the evolution of number sense and arithmetic scores before and after training. The software, open-source and freely available online, is designed for learning disabled children aged 5-8, and may also be useful for general instruction of normal preschool children. The learning algorithm reported is highly general, and may be applied in other domains.

Construction of a remotely sensed area sampling frame for Southern Brazil

NASA Technical Reports Server (NTRS)

Fecso, R.; Gardner, W.; Hale, B.; Johnson, V.; Pavlasek, S. (Principal Investigator)

1982-01-01

A remotely sensed area sampling frame was constructed for selected areas in Southern Brazil. The sampling unit information was stored in digital form in a latitudinal/longitudinal characterized population. Computerized sampling procedures were developed which allow for flexibility in sample unit specifications and sampling designs.

Motion-adaptive spatio-temporal regularization for accelerated dynamic MRI.

PubMed

Asif, M Salman; Hamilton, Lei; Brummer, Marijn; Romberg, Justin

2013-09-01

Accelerated magnetic resonance imaging techniques reduce signal acquisition time by undersampling k-space. A fundamental problem in accelerated magnetic resonance imaging is the recovery of quality images from undersampled k-space data. Current state-of-the-art recovery algorithms exploit the spatial and temporal structures in underlying images to improve the reconstruction quality. In recent years, compressed sensing theory has helped formulate mathematical principles and conditions that ensure recovery of (structured) sparse signals from undersampled, incoherent measurements. In this article, a new recovery algorithm, motion-adaptive spatio-temporal regularization, is presented that uses spatial and temporal structured sparsity of MR images in the compressed sensing framework to recover dynamic MR images from highly undersampled k-space data. In contrast to existing algorithms, our proposed algorithm models temporal sparsity using motion-adaptive linear transformations between neighboring images. The efficiency of motion-adaptive spatio-temporal regularization is demonstrated with experiments on cardiac magnetic resonance imaging for a range of reduction factors. Results are also compared with k-t FOCUSS with motion estimation and compensation-another recently proposed recovery algorithm for dynamic magnetic resonance imaging. . Copyright © 2012 Wiley Periodicals, Inc.

Adaptive wavefront sensor based on the Talbot phenomenon.

PubMed

Podanchuk, Dmytro V; Goloborodko, Andrey A; Kotov, Myhailo M; Kovalenko, Andrey V; Kurashov, Vitalij N; Dan'ko, Volodymyr P

2016-04-20

A new adaptive method of wavefront sensing is proposed and demonstrated. The method is based on the Talbot self-imaging effect, which is observed in an illuminating light beam with strong second-order aberration. Compensation of defocus and astigmatism is achieved with an appropriate choice of size of the rectangular unit cell of the diffraction grating, which is performed iteratively. A liquid-crystal spatial light modulator is used for this purpose. Self-imaging of rectangular grating in the astigmatic light beam is demonstrated experimentally. High-order aberrations are detected with respect to the compensated second-order aberration. The comparative results of wavefront sensing with a Shack-Hartmann sensor and the proposed sensor are adduced.

A modified JPEG-LS lossless compression method for remote sensing images

NASA Astrophysics Data System (ADS)

Deng, Lihua; Huang, Zhenghua

2015-12-01

As many variable length source coders, JPEG-LS is highly vulnerable to channel errors which occur in the transmission of remote sensing images. The error diffusion is one of the important factors which infect its robustness. The common method of improving the error resilience of JPEG-LS is dividing the image into many strips or blocks, and then coding each of them independently, but this method reduces the coding efficiency. In this paper, a block based JPEP-LS lossless compression method with an adaptive parameter is proposed. In the modified scheme, the threshold parameter RESET is adapted to an image and the compression efficiency is close to that of the conventional JPEG-LS.

3D sensitivity encoded ellipsoidal MR spectroscopic imaging of gliomas at 3T☆

PubMed Central

Ozturk-Isik, Esin; Chen, Albert P.; Crane, Jason C.; Bian, Wei; Xu, Duan; Han, Eric T.; Chang, Susan M.; Vigneron, Daniel B.; Nelson, Sarah J.

2010-01-01

Purpose The goal of this study was to implement time efficient data acquisition and reconstruction methods for 3D magnetic resonance spectroscopic imaging (MRSI) of gliomas at a field strength of 3T using parallel imaging techniques. Methods The point spread functions, signal to noise ratio (SNR), spatial resolution, metabolite intensity distributions and Cho:NAA ratio of 3D ellipsoidal, 3D sensitivity encoding (SENSE) and 3D combined ellipsoidal and SENSE (e-SENSE) k-space sampling schemes were compared with conventional k-space data acquisition methods. Results The 3D SENSE and e-SENSE methods resulted in similar spectral patterns as the conventional MRSI methods. The Cho:NAA ratios were highly correlated (P<.05 for SENSE and P<.001 for e-SENSE) with the ellipsoidal method and all methods exhibited significantly different spectral patterns in tumor regions compared to normal appearing white matter. The geometry factors ranged between 1.2 and 1.3 for both the SENSE and e-SENSE spectra. When corrected for these factors and for differences in data acquisition times, the empirical SNRs were similar to values expected based upon theoretical grounds. The effective spatial resolution of the SENSE spectra was estimated to be same as the corresponding fully sampled k-space data, while the spectra acquired with ellipsoidal and e-SENSE k-space samplings were estimated to have a 2.36–2.47-fold loss in spatial resolution due to the differences in their point spread functions. Conclusion The 3D SENSE method retained the same spatial resolution as full k-space sampling but with a 4-fold reduction in scan time and an acquisition time of 9.28 min. The 3D e-SENSE method had a similar spatial resolution as the corresponding ellipsoidal sampling with a scan time of 4:36 min. Both parallel imaging methods provided clinically interpretable spectra with volumetric coverage and adequate SNR for evaluating Cho, Cr and NAA. PMID:19766422

Compressive sensing based wireless sensor for structural health monitoring

NASA Astrophysics Data System (ADS)

Bao, Yuequan; Zou, Zilong; Li, Hui

2014-03-01

Data loss is a common problem for monitoring systems based on wireless sensors. Reliable communication protocols, which enhance communication reliability by repetitively transmitting unreceived packets, is one approach to tackle the problem of data loss. An alternative approach allows data loss to some extent and seeks to recover the lost data from an algorithmic point of view. Compressive sensing (CS) provides such a data loss recovery technique. This technique can be embedded into smart wireless sensors and effectively increases wireless communication reliability without retransmitting the data. The basic idea of CS-based approach is that, instead of transmitting the raw signal acquired by the sensor, a transformed signal that is generated by projecting the raw signal onto a random matrix, is transmitted. Some data loss may occur during the transmission of this transformed signal. However, according to the theory of CS, the raw signal can be effectively reconstructed from the received incomplete transformed signal given that the raw signal is compressible in some basis and the data loss ratio is low. This CS-based technique is implemented into the Imote2 smart sensor platform using the foundation of Illinois Structural Health Monitoring Project (ISHMP) Service Tool-suite. To overcome the constraints of limited onboard resources of wireless sensor nodes, a method called random demodulator (RD) is employed to provide memory and power efficient construction of the random sampling matrix. Adaptation of RD sampling matrix is made to accommodate data loss in wireless transmission and meet the objectives of the data recovery. The embedded program is tested in a series of sensing and communication experiments. Examples and parametric study are presented to demonstrate the applicability of the embedded program as well as to show the efficacy of CS-based data loss recovery for real wireless SHM systems.

Prototype of a laser guide star wavefront sensor for the Extremely Large Telescope

NASA Astrophysics Data System (ADS)

Patti, M.; Lombini, M.; Schreiber, L.; Bregoli, G.; Arcidiacono, C.; Cosentino, G.; Diolaiti, E.; Foppiani, I.

2018-06-01

The new class of large telescopes, like the future Extremely Large Telescope (ELT), are designed to work with a laser guide star (LGS) tuned to a resonance of atmospheric sodium atoms. This wavefront sensing technique presents complex issues when applied to big telescopes for many reasons, mainly linked to the finite distance of the LGS, the launching angle, tip-tilt indetermination and focus anisoplanatism. The implementation of a laboratory prototype for the LGS wavefront sensor (WFS) at the beginning of the phase study of MAORY (Multi-conjugate Adaptive Optics Relay) for ELT first light has been indispensable in investigating specific mitigation strategies for the LGS WFS issues. This paper presents the test results of the LGS WFS prototype under different working conditions. The accuracy within which the LGS images are generated on the Shack-Hartmann WFS has been cross-checked with the MAORY simulation code. The experiments show the effect of noise on centroiding precision, the impact of LGS image truncation on wavefront sensing accuracy as well as the temporal evolution of the sodium density profile and LGS image under-sampling.

Nitrite sensing composite systems based on a core-shell emissive-superamagnetic structure: Construction, characterization and sensing behavior

NASA Astrophysics Data System (ADS)

Yang, Yan; Liu, Liang; Zha, Jianhua; Yuan, Ningyi

2017-04-01

Two recyclable nitrite sensing composite samples were designed and constructed through a core-shell structure, with Fe3O4 nanoparticles as core, silica molecular sieve MCM-41 as shell and two rhodamine derivatives as chemosensors, respectively. These samples and their structure were identified with their electron microscopy images, N2 adsorption/desorption isotherms, magnetic response, IR spectra and thermogravimetric analysis. Their nitrite sensing behavior was discussed based on emission intensity quenching, their limit of detection was found as low as 1.2 μM. Further analysis suggested a static sensing mechanism between nitrite and chemosensors through an additive reaction between NO+ and chemosensors. After finishing their nitrite sensing, these composite samples and their emission could be recycled and recovered by sulphamic acid.

Colorimetric assay for on-the-spot alcoholic strength sensing in spirit samples based on dual-responsive lanthanide coordination polymer particles with ratiometric fluorescence.

PubMed

Deng, Jingjing; Shi, Guoyue; Zhou, Tianshu

2016-10-26

This study demonstrates a new strategy for colorimetric detection of alcoholic strength (AS) in spirit samples based on dual-responsive lanthanide infinite coordination polymer (Ln-ICP) particles with ratiometric fluorescence. The ICP used in this study are composed of two components: one is the supramolecular Ln-ICP network formed by the coordination between the ligand 2,2'-thiodiacetic acid (TDA) and central metal ion Eu 3+ ; and the other is a fluorescent dye, i.e., coumarin 343 (C343), both as the cofactor ligand and as the sensitizer, doped into the Ln-ICP network through self-adaptive chemistry. Upon being excited at 300 nm, the red fluorescence of Ln-ICP network itself at 617 nm is highly enhanced due to the concomitant energy transfer from C343 to Eu 3+ , while the fluorescence of C343 at 495 nm is supressed. In pure ethanol solvent, the as-formed C343@Eu-TDA is well dispersed and quite stable. However, the addition of water into ethanolic dispersion of C343@Eu-TDA destructs Eu-TDA network structure, resulting in the release of C343 from ICP network into the solvent. Consequently, the fluorescence of Eu-TDA turns off and the fluorescence of C343 turns on, leading to the fluorescent color change of the dispersion from red to blue, which constitutes a new mechanism for colorimetric sensing of AS in commercial spirit samples. With the method developed here, we could clearly distinguish the AS of different spirit samples within a wide linear range from 10% vol to 100% vol directly by "naked eye" with the help of UV-lamp (365 nm). This study not only offers a new method for on-the-spot visible detection of AS, but also provides a strategy for dual-responsive sensing mode by rational designing the optical properties of the Ln-ICP network and the guest, respectively. Copyright © 2016 Elsevier B.V. All rights reserved.

ELECTRONIC BIVANE WIND DIRECTION INDICATOR

DOEpatents

Moses, H.

1961-05-01

An apparatus is described for determining and recording three dimensional wind vectors. The apparatus comprises a rotatably mounted azimuthal wind component sensing head and an elevational wind component sensing head mounted to the azimuthal head and adapted to rotate therewith in the azimuthal plane and independently in the elevational plane. A heat source and thermocouples disposed thereabout are mounted within each of the sensing heads, the thermocouples providing electrical signals responsive to the temperature differential created by the passage of air through the sensing tuhes. The thermocouple signals are applied to drive mechanisms which position the sensing heads to a null wind position. Recording means are provided responsive to positional data from the drive mechanisms which are a measurement of the three dimensional wind vectors.

The role of grief symptoms and a sense of injustice in the pathways to post-traumatic stress symptoms in post-conflict Timor-Leste.

PubMed

Tay, A K; Rees, S; Steel, Z; Liddell, B; Nickerson, A; Tam, N; Silove, D

2017-08-01

Grief symptoms and a sense of injustice may be interrelated responses amongst persons exposed to mass conflict and both reactions may contribute to post-traumatic stress disorder (PTSD) symptoms. As yet, however, there is a dearth of data examining these relationships. Our study examined the contributions of grief and a sense of injustice to a model of PTSD symptoms that included the established determinants of trauma events, ongoing adversity and severe psychological distress. The study involved a large population sample (n = 2964, response rate: 82.4%) surveyed in post-conflict Timor-Leste. The survey sites included an urban administrative area (suco) in Dili, the capital of Timor-Leste and a rural village located an hour's drive away. Culturally adapted measures were applied to assess conflict related traumatic events (TEs), ongoing adversity, persisting preoccupations with injustice, symptoms of grief, psychological distress (including depressive symptoms) and PTSD symptoms. We tested a series of structural equation models, the final comprehensive model, which included indices of grief symptoms and injustice, producing a good fit. Locating grief symptoms as the endpoint of the model produced a non-converging model. In the final model, strong associations were evident between grief and injustice (β = 0.34, s.e. = 0.02, p < 0.01) and grief and PTSD symptoms (β = 0.14, s.e. = 0.02, p < 0.01). The sense of injustice exerted a considerable effect on PTSD symptoms (β = 0.13, s.e. = 0.03, p < 0.01). In addition, multiple indirect paths were evident, most involving grief and a sense of injustice, attesting to the complex inter-relationship of these factors in contributing to PTSD symptoms. Our findings support an expanded model of PTSD symptoms relevant to post-conflict populations, in which grief symptoms and a sense of injustice play pivotal roles. The model supports the importance of a focus on loss, grief and a sense of injustice in conducting trauma-focused psychotherapies for PTSD amongst populations exposed to mass conflict and violence. Further research is needed to identify the precise mechanisms whereby grief symptoms and the sense of injustice impact on PTSD symptoms.

Methods for estimating the amount of vernal pool habitat in the northeastern United States

USGS Publications Warehouse

Van Meter, R.; Bailey, L.L.; Grant, E.H.C.

2008-01-01

The loss of small, seasonal wetlands is a major concern for a variety of state, local, and federal organizations in the northeastern U.S. Identifying and estimating the number of vernal pools within a given region is critical to developing long-term conservation and management strategies for these unique habitats and their faunal communities. We use three probabilistic sampling methods (simple random sampling, adaptive cluster sampling, and the dual frame method) to estimate the number of vernal pools on protected, forested lands. Overall, these methods yielded similar values of vernal pool abundance for each study area, and suggest that photographic interpretation alone may grossly underestimate the number of vernal pools in forested habitats. We compare the relative efficiency of each method and discuss ways of improving precision. Acknowledging that the objectives of a study or monitoring program ultimately determine which sampling designs are most appropriate, we recommend that some type of probabilistic sampling method be applied. We view the dual-frame method as an especially useful way of combining incomplete remote sensing methods, such as aerial photograph interpretation, with a probabilistic sample of the entire area of interest to provide more robust estimates of the number of vernal pools and a more representative sample of existing vernal pool habitats.

Staphylococcus aureus but not Listeria monocytogenes adapt to triclosan and adaptation correlates with increased fabI expression and agr deficiency

PubMed Central

2013-01-01

Background The ability of pathogens to adapt to the widely used biocide, triclosan, varies substantially. The purpose of the study was to examine bacterial adaptation over an extended period of time to low increments of triclosan concentrations. Focus was two human pathogens, S. aureus and L. monocytogenes that previously have displayed inherent high and low adaptability, respectively. Results Three strains of L. monocytogenes and two strains of S. aureus including the community-acquired USA300 were exposed to increasing, sub-lethal concentrations of triclosan in triclosan-containing agar gradients. Following 25 days of exposure on agar plates to sub-lethal concentrations of triclosan with a twofold concentration increase every second day, minimum inhibitory concentration (MIC) for S. aureus increased from 0.125 (8325–4) and 0.0625 (USA 300) mg/L to 4 mg/L. The MIC of all three L. monocytogenes strains was initially 4 mg/L and remained unaltered by the exposure. The adapted S. aureus isolates retained normal colony size but displayed increased expression of fabI encoding an essential enzyme in bacterial fatty acid synthesis. Also, they displayed decreased or no expression of the virulence associated agrC of the agr quorum sensing system. While most adapted strains of USA300 carried mutations in fabI, none of the adapted strains of 8325–4 did. Conclusions Adaptability to triclosan varies substantially between Gram positive human pathogens. S. aureus displayed an intrinsically lower MIC for triclosan compared to L. monocytogenes but was easily adapted leading to the same MIC as L. monocytogenes. Even though all adapted S. aureus strains over-expressed fabI and eliminated expression of the agr quorum sensing system, adaptation in USA300 involved fabI mutations whereas this was not the case for 8325–4. Thus, adaptation to triclosan by S. aureus appears to involve multiple genetic pathways. PMID:23898801

Reflective SOA-based fiber Bragg grating ultrasonic sensing system with two wave mixing interferometric demodulation

NASA Astrophysics Data System (ADS)

Wei, Heming; Krishnaswamy, Sridhar

2017-04-01

Damages such as cracking or impact loading in civil, aerospace, and mechanical structures generate transient ultrasonic waves, which can be used to reveal the structural health condition. Hence, it is necessary to find a practical tool based on ultrasonic detection for structural health monitoring. In this work, we describe an intelligent fiber-optic ultrasonic sensing system, which is designed based on a fiber Bragg grating (FBG) and a reflective semiconductor optical amplifier (RSOA) used as an adaptive source, and demodulated by an adaptive photorefractive two wave mixing (TWM) technique without any active compensation of quasi-static strains and temperature. As the wavelength of the FBG shifts due to the excited ultrasonic waves, the wavelength of the optical output from the fiber cavity laser shifts accordingly. With regard to the shift of the FBG reflective spectrum, the adaptivity of the RSOA-based laser is analyzed theoretically and verified by the TWM demodulator. Additionally, due to the response time of the photorefractive crystal, the TWM demodulator is insensitive to low frequency-FBG spectral shift. The results demonstrate that this proposed FBG ultrasonic sensing system has high sensitivity and can respond the ultrasonic waves into the megahertz frequency range, which shows a potential for acoustic emission detection in practical applications.

A closed-loop neurobotic system for fine touch sensing

NASA Astrophysics Data System (ADS)

Bologna, L. L.; Pinoteau, J.; Passot, J.-B.; Garrido, J. A.; Vogel, J.; Ros Vidal, E.; Arleo, A.

2013-08-01

Objective. Fine touch sensing relies on peripheral-to-central neurotransmission of somesthetic percepts, as well as on active motion policies shaping tactile exploration. This paper presents a novel neuroengineering framework for robotic applications based on the multistage processing of fine tactile information in the closed action-perception loop. Approach. The integrated system modules focus on (i) neural coding principles of spatiotemporal spiking patterns at the periphery of the somatosensory pathway, (ii) probabilistic decoding mechanisms mediating cortical-like tactile recognition and (iii) decision-making and low-level motor adaptation underlying active touch sensing. We probed the resulting neural architecture through a Braille reading task. Main results. Our results on the peripheral encoding of primary contact features are consistent with experimental data on human slow-adapting type I mechanoreceptors. They also suggest second-order processing by cuneate neurons may resolve perceptual ambiguities, contributing to a fast and highly performing online discrimination of Braille inputs by a downstream probabilistic decoder. The implemented multilevel adaptive control provides robustness to motion inaccuracy, while making the number of finger accelerations covariate with Braille character complexity. The resulting modulation of fingertip kinematics is coherent with that observed in human Braille readers. Significance. This work provides a basis for the design and implementation of modular neuromimetic systems for fine touch discrimination in robotics.

CSP - Hyperspectral Imaging and Sounding of the Environment Meeting Scholarship Fund

DTIC Science & Technology

2017-05-09

performance via adaptation to the environment. The meeting has also contributed to the focus area of Electromagnetic Maneuver Warfare through disseminating the...latest information about advanced sensing techniques and understanding the electromagnetic environment through sensing. Additional sessions on...across the electromagnetic spectrum. The attendees at this event from the Naval Research Enterprise were Dr. Michael Yetzbacher, as a Program Co

Fast parallel MR image reconstruction via B1-based, adaptive restart, iterative soft thresholding algorithms (BARISTA).

PubMed

Muckley, Matthew J; Noll, Douglas C; Fessler, Jeffrey A

2015-02-01

Sparsity-promoting regularization is useful for combining compressed sensing assumptions with parallel MRI for reducing scan time while preserving image quality. Variable splitting algorithms are the current state-of-the-art algorithms for SENSE-type MR image reconstruction with sparsity-promoting regularization. These methods are very general and have been observed to work with almost any regularizer; however, the tuning of associated convergence parameters is a commonly-cited hindrance in their adoption. Conversely, majorize-minimize algorithms based on a single Lipschitz constant have been observed to be slow in shift-variant applications such as SENSE-type MR image reconstruction since the associated Lipschitz constants are loose bounds for the shift-variant behavior. This paper bridges the gap between the Lipschitz constant and the shift-variant aspects of SENSE-type MR imaging by introducing majorizing matrices in the range of the regularizer matrix. The proposed majorize-minimize methods (called BARISTA) converge faster than state-of-the-art variable splitting algorithms when combined with momentum acceleration and adaptive momentum restarting. Furthermore, the tuning parameters associated with the proposed methods are unitless convergence tolerances that are easier to choose than the constraint penalty parameters required by variable splitting algorithms.

Fast Parallel MR Image Reconstruction via B1-based, Adaptive Restart, Iterative Soft Thresholding Algorithms (BARISTA)

PubMed Central

Noll, Douglas C.; Fessler, Jeffrey A.

2014-01-01

Sparsity-promoting regularization is useful for combining compressed sensing assumptions with parallel MRI for reducing scan time while preserving image quality. Variable splitting algorithms are the current state-of-the-art algorithms for SENSE-type MR image reconstruction with sparsity-promoting regularization. These methods are very general and have been observed to work with almost any regularizer; however, the tuning of associated convergence parameters is a commonly-cited hindrance in their adoption. Conversely, majorize-minimize algorithms based on a single Lipschitz constant have been observed to be slow in shift-variant applications such as SENSE-type MR image reconstruction since the associated Lipschitz constants are loose bounds for the shift-variant behavior. This paper bridges the gap between the Lipschitz constant and the shift-variant aspects of SENSE-type MR imaging by introducing majorizing matrices in the range of the regularizer matrix. The proposed majorize-minimize methods (called BARISTA) converge faster than state-of-the-art variable splitting algorithms when combined with momentum acceleration and adaptive momentum restarting. Furthermore, the tuning parameters associated with the proposed methods are unitless convergence tolerances that are easier to choose than the constraint penalty parameters required by variable splitting algorithms. PMID:25330484

Family Adaptation to Relocation: An Empirical Analysis of Family Stressors, Adaptive Resources, and Sense of Coherence

DTIC Science & Technology

1989-07-01

825. Lazarus , R. S., & Folkman , S. (1984). Stress, appraisal, and coping. New York: Springer. mcCuIbin, H. I., & Lavee, Y . (1986). Strengthenirg Army...Soirani, 1988; Lazarus & Folkman , 1984; Mckbbin & Patterson, 1983), family adaptation was defined broadly as a crmposite of the overall adjustment of...ongr- y of expectations that members and spouses had prior to arrival in West Germany with their actual experiences since arrival (Alpha: Members = .91

Adaptive Piezoelectric Circuitry Sensor Network with High-Frequency Harmonics Interrogation for Structural Damage Detection

DTIC Science & Technology

2014-09-17

AFRL-OSR-VA-TR-2014-0255 ADAPTIVE PIEZOELECTRIC CIRCUITRY SENSOR NETWORK KON -WELL WANG MICHIGAN UNIV ANN ARBOR Final Report 09/17/2014 DISTRIBUTION A...Harmonics Interrogation for Structural Damage Detection FA9550-11-1-0072 Kon -Well Wang and Jiong Tang The Regents of the University of Michigan, 3003...mechanism. These efforts have yielded a complete methodology of adaptive high-frequency piezoelectric self-sensing interrogation. None None None SAR Kon

Synthesis, characterization and nitrite ion sensing performance of reclaimable composite samples through a core-shell structure

NASA Astrophysics Data System (ADS)

Cui, Xiao; Yuqing, Zhao; Cui, Jiantao; Zheng, Qian; Bo, Wang

2018-02-01

The following paper reported and discussed a nitrite ion optical sensing platform based on a core-shell structure, using superamagnetic nanoparticles as the core, a silica molecular sieve MCM-41 as the shell and two rhodamine derivatives as probe, respectively. This superamagnetic core made this sensing platform reclaimable after finishing nitrite ion sensing procedure. This sensing platform was carefully characterized by means of electron microscopy images, porous structure analysis, magnetic response, IR spectra and thermal stability analysis. Detailed analysis suggested that the emission of these composite samples was quenchable by nitrite ion, showing emission turn off effect. A static sensing mechanism based on an additive reaction between chemosensors and nitrite ion was proposed. These composite samples followed Demas quenching equation against different nitrite ion concentrations. Limit of detection value was obtained as low as 0.4 μM. It was found that, after being quenched by nitrite ion, these composite samples could be reclaimed and recovered by sulphamic acid, confirming their recyclability.

Object Manifold Alignment for Multi-Temporal High Resolution Remote Sensing Images Classification

NASA Astrophysics Data System (ADS)

Gao, G.; Zhang, M.; Gu, Y.

2017-05-01

Multi-temporal remote sensing images classification is very useful for monitoring the land cover changes. Traditional approaches in this field mainly face to limited labelled samples and spectral drift of image information. With spatial resolution improvement, "pepper and salt" appears and classification results will be effected when the pixelwise classification algorithms are applied to high-resolution satellite images, in which the spatial relationship among the pixels is ignored. For classifying the multi-temporal high resolution images with limited labelled samples, spectral drift and "pepper and salt" problem, an object-based manifold alignment method is proposed. Firstly, multi-temporal multispectral images are cut to superpixels by simple linear iterative clustering (SLIC) respectively. Secondly, some features obtained from superpixels are formed as vector. Thirdly, a majority voting manifold alignment method aiming at solving high resolution problem is proposed and mapping the vector data to alignment space. At last, all the data in the alignment space are classified by using KNN method. Multi-temporal images from different areas or the same area are both considered in this paper. In the experiments, 2 groups of multi-temporal HR images collected by China GF1 and GF2 satellites are used for performance evaluation. Experimental results indicate that the proposed method not only has significantly outperforms than traditional domain adaptation methods in classification accuracy, but also effectively overcome the problem of "pepper and salt".

Application of adaptive cluster sampling to low-density populations of freshwater mussels

USGS Publications Warehouse

Smith, D.R.; Villella, R.F.; Lemarie, D.P.

2003-01-01

Freshwater mussels appear to be promising candidates for adaptive cluster sampling because they are benthic macroinvertebrates that cluster spatially and are frequently found at low densities. We applied adaptive cluster sampling to estimate density of freshwater mussels at 24 sites along the Cacapon River, WV, where a preliminary timed search indicated that mussels were present at low density. Adaptive cluster sampling increased yield of individual mussels and detection of uncommon species; however, it did not improve precision of density estimates. Because finding uncommon species, collecting individuals of those species, and estimating their densities are important conservation activities, additional research is warranted on application of adaptive cluster sampling to freshwater mussels. However, at this time we do not recommend routine application of adaptive cluster sampling to freshwater mussel populations. The ultimate, and currently unanswered, question is how to tell when adaptive cluster sampling should be used, i.e., when is a population sufficiently rare and clustered for adaptive cluster sampling to be efficient and practical? A cost-effective procedure needs to be developed to identify biological populations for which adaptive cluster sampling is appropriate.

Adaptive sampling in behavioral surveys.

PubMed

Thompson, S K

1997-01-01

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

Adaptive compressed sensing of multi-view videos based on the sparsity estimation

NASA Astrophysics Data System (ADS)

Yang, Senlin; Li, Xilong; Chong, Xin

2017-11-01

The conventional compressive sensing for videos based on the non-adaptive linear projections, and the measurement times is usually set empirically. As a result, the quality of videos reconstruction is always affected. Firstly, the block-based compressed sensing (BCS) with conventional selection for compressive measurements was described. Then an estimation method for the sparsity of multi-view videos was proposed based on the two dimensional discrete wavelet transform (2D DWT). With an energy threshold given beforehand, the DWT coefficients were processed with both energy normalization and sorting by descending order, and the sparsity of the multi-view video can be achieved by the proportion of dominant coefficients. And finally, the simulation result shows that, the method can estimate the sparsity of video frame effectively, and provides an active basis for the selection of compressive observation times. The result also shows that, since the selection of observation times is based on the sparsity estimated with the energy threshold provided, the proposed method can ensure the reconstruction quality of multi-view videos.

Automatic Domain Adaptation of Word Sense Disambiguation Based on Sublanguage Semantic Schemata Applied to Clinical Narrative

ERIC Educational Resources Information Center

Patterson, Olga

2012-01-01

Domain adaptation of natural language processing systems is challenging because it requires human expertise. While manual effort is effective in creating a high quality knowledge base, it is expensive and time consuming. Clinical text adds another layer of complexity to the task due to privacy and confidentiality restrictions that hinder the…

Olfactory Detection Thresholds and Adaptation in Adults with Autism Spectrum Condition

ERIC Educational Resources Information Center

Tavassoli, T.; Baron-Cohen, S.

2012-01-01

Sensory issues have been widely reported in Autism Spectrum Conditions (ASC). Since olfaction is one of the least investigated senses in ASC, the current studies explore olfactory detection thresholds and adaptation to olfactory stimuli in adults with ASC. 80 participants took part, 38 (18 females, 20 males) with ASC and 42 control participants…

State estimation for distributed systems with sensing delay

NASA Astrophysics Data System (ADS)

Alexander, Harold L.

1991-08-01

Control of complex systems such as remote robotic vehicles requires combining data from many sensors where the data may often be delayed by sensory processing requirements. The number and variety of sensors make it desirable to distribute the computational burden of sensing and estimation among multiple processors. Classic Kalman filters do not lend themselves to distributed implementations or delayed measurement data. The alternative Kalman filter designs presented in this paper are adapted for delays in sensor data generation and for distribution of computation for sensing and estimation over a set of networked processors.

Three examples of applied remote sensing of vegetation

NASA Technical Reports Server (NTRS)

Rouse, J. W., Jr.; Benton, A. R., Jr.; Toler, R. W.; Haas, R. H.

1975-01-01

Cause studies in which remote sensing techniques were adapted to assist in the solution of particular problem situations in Texas involving vegetation are described. In each case, the final sensing technique developed for operational use by the concerned organizations employed photographic sensors which were optimized through studies of the spectral reflectance characteristics of the vegetation species and background conditions unique to the problem being considered. The three examples described are: (1) Assisting Aquatic Plant Monitoring and Control; (2) Improving Vegetation Utilization in Urban Planning; and (3) Enforcing the Quarantine of Diseased Crops.

Remote Sensing in Archeology: Classifying Bajos of the Paten, Guatemala

NASA Technical Reports Server (NTRS)

Lowry, James D., Jr.

1998-01-01

This project focuses on the adaptation of human populations to their environments from prehistoric times to the present. It emphasizes interdisciplinary research to develop ecological baselines through the use of remotely sensed imagery, in situ field work, and the modeling of human population dynamics. It utilizes cultural and biological data from dated archaeological sites to assess the subsistence and settlement patterns of human societies in response to changing climatic and environmental conditions. The utilization of remote sensing techniques in archaeology is relatively new, exciting, and opens many doors.

Dynamic experiment design regularization approach to adaptive imaging with array radar/SAR sensor systems.

PubMed

Shkvarko, Yuriy; Tuxpan, José; Santos, Stewart

2011-01-01

We consider a problem of high-resolution array radar/SAR imaging formalized in terms of a nonlinear ill-posed inverse problem of nonparametric estimation of the power spatial spectrum pattern (SSP) of the random wavefield scattered from a remotely sensed scene observed through a kernel signal formation operator and contaminated with random Gaussian noise. First, the Sobolev-type solution space is constructed to specify the class of consistent kernel SSP estimators with the reproducing kernel structures adapted to the metrics in such the solution space. Next, the "model-free" variational analysis (VA)-based image enhancement approach and the "model-based" descriptive experiment design (DEED) regularization paradigm are unified into a new dynamic experiment design (DYED) regularization framework. Application of the proposed DYED framework to the adaptive array radar/SAR imaging problem leads to a class of two-level (DEED-VA) regularized SSP reconstruction techniques that aggregate the kernel adaptive anisotropic windowing with the projections onto convex sets to enforce the consistency and robustness of the overall iterative SSP estimators. We also show how the proposed DYED regularization method may be considered as a generalization of the MVDR, APES and other high-resolution nonparametric adaptive radar sensing techniques. A family of the DYED-related algorithms is constructed and their effectiveness is finally illustrated via numerical simulations.

Investigating NO2 gas sensing behavior of flower-like MoS2 and rGO based nano-composite

NASA Astrophysics Data System (ADS)

Kanaujiya, Neha; Anupam, Golimar, Kapil; Pandey, Prateek Chandra; Jyoti, Varma, G. D.

2018-05-01

In the present work, MoS2 nano-sheets with flower-like morphology have been synthesized by facile hydrothermal method. The nano-composite of MoS2 and reduced graphene oxide (rGO) nano-sheets has been synthesized to study the gas sensing behavior. The structural and morphological characteristics of the as prepared samples are investigated by X-ray diffraction (XRD) and Field emission scanning electron microscopy (FESEM) respectively. The gas sensing behavior of the as synthesized MoS2 and composite samples have been studied for different concentrations of NO2 at different temperatures. Improvement in sensing response of composite sample as compared to bare MoS2 sample has been observed. Percentage response of ˜ 23% has been observed at room temperature for 40ppm NO2. The detail correlation between gas sensing behavior and structural characteristics of the composite sample will be described and discussed in this paper.

Random Access Memories: A New Paradigm for Target Detection in High Resolution Aerial Remote Sensing Images.

PubMed

Zou, Zhengxia; Shi, Zhenwei

2018-03-01

We propose a new paradigm for target detection in high resolution aerial remote sensing images under small target priors. Previous remote sensing target detection methods frame the detection as learning of detection model + inference of class-label and bounding-box coordinates. Instead, we formulate it from a Bayesian view that at inference stage, the detection model is adaptively updated to maximize its posterior that is determined by both training and observation. We call this paradigm "random access memories (RAM)." In this paradigm, "Memories" can be interpreted as any model distribution learned from training data and "random access" means accessing memories and randomly adjusting the model at detection phase to obtain better adaptivity to any unseen distribution of test data. By leveraging some latest detection techniques e.g., deep Convolutional Neural Networks and multi-scale anchors, experimental results on a public remote sensing target detection data set show our method outperforms several other state of the art methods. We also introduce a new data set "LEarning, VIsion and Remote sensing laboratory (LEVIR)", which is one order of magnitude larger than other data sets of this field. LEVIR consists of a large set of Google Earth images, with over 22 k images and 10 k independently labeled targets. RAM gives noticeable upgrade of accuracy (an mean average precision improvement of 1% ~ 4%) of our baseline detectors with acceptable computational overhead.

Method, system and apparatus for monitoring and adjusting the quality of indoor air

DOEpatents

Hartenstein, Steven D.; Tremblay, Paul L.; Fryer, Michael O.; Hohorst, Frederick A.

2004-03-23

A system, method and apparatus is provided for monitoring and adjusting the quality of indoor air. A sensor array senses an air sample from the indoor air and analyzes the air sample to obtain signatures representative of contaminants in the air sample. When the level or type of contaminant poses a threat or hazard to the occupants, the present invention takes corrective actions which may include introducing additional fresh air. The corrective actions taken are intended to promote overall health of personnel, prevent personnel from being overexposed to hazardous contaminants and minimize the cost of operating the HVAC system. The identification of the contaminants is performed by comparing the signatures provided by the sensor array with a database of known signatures. Upon identification, the system takes corrective actions based on the level of contaminant present. The present invention is capable of learning the identity of previously unknown contaminants, which increases its ability to identify contaminants in the future. Indoor air quality is assured by monitoring the contaminants not only in the indoor air, but also in the outdoor air and the air which is to be recirculated. The present invention is easily adaptable to new and existing HVAC systems. In sum, the present invention is able to monitor and adjust the quality of indoor air in real time by sensing the level and type of contaminants present in indoor air, outdoor and recirculated air, providing an intelligent decision about the quality of the air, and minimizing the cost of operating an HVAC system.

The Impact of Correcting Cognitive Distortions in Reducing Depression and the Sense of Insecurity among a Sample of Female Refugee Adolescents

ERIC Educational Resources Information Center

Mhaidat, Fatin; ALharbi, Bassam H. M.

2016-01-01

This study aimed at identifying the level of depression and sense of insecurity among a sample of female refugee adolescents, and the impact of an indicative program for reducing cognitive distortions in reducing depression and their sense of insecurity. The study sample consisted of 220 female refugee adolescents, 7th to 1st secondary stage, at…

Bone strain magnitude is correlated with bone strain rate in tetrapods: implications for models of mechanotransduction

PubMed Central

Aiello, B. R.; Iriarte-Diaz, J.; Blob, R. W.; Butcher, M. T.; Carrano, M. T.; Espinoza, N. R.; Main, R. P.; Ross, C. F.

2015-01-01

Hypotheses suggest that structural integrity of vertebrate bones is maintained by controlling bone strain magnitude via adaptive modelling in response to mechanical stimuli. Increased tissue-level strain magnitude and rate have both been identified as potent stimuli leading to increased bone formation. Mechanotransduction models hypothesize that osteocytes sense bone deformation by detecting fluid flow-induced drag in the bone's lacunar–canalicular porosity. This model suggests that the osteocyte's intracellular response depends on fluid-flow rate, a product of bone strain rate and gradient, but does not provide a mechanism for detection of strain magnitude. Such a mechanism is necessary for bone modelling to adapt to loads, because strain magnitude is an important determinant of skeletal fracture. Using strain gauge data from the limb bones of amphibians, reptiles, birds and mammals, we identified strong correlations between strain rate and magnitude across clades employing diverse locomotor styles and degrees of rhythmicity. The breadth of our sample suggests that this pattern is likely to be a common feature of tetrapod bone loading. Moreover, finding that bone strain magnitude is encoded in strain rate at the tissue level is consistent with the hypothesis that it might be encoded in fluid-flow rate at the cellular level, facilitating bone adaptation via mechanotransduction. PMID:26063842

Towards a Standard Mixed-Signal Parallel Processing Architecture for Miniature and Microrobotics.

PubMed

Sadler, Brian M; Hoyos, Sebastian

2014-01-01

The conventional analog-to-digital conversion (ADC) and digital signal processing (DSP) architecture has led to major advances in miniature and micro-systems technology over the past several decades. The outlook for these systems is significantly enhanced by advances in sensing, signal processing, communications and control, and the combination of these technologies enables autonomous robotics on the miniature to micro scales. In this article we look at trends in the combination of analog and digital (mixed-signal) processing, and consider a generalized sampling architecture. Employing a parallel analog basis expansion of the input signal, this scalable approach is adaptable and reconfigurable, and is suitable for a large variety of current and future applications in networking, perception, cognition, and control.

Towards a Standard Mixed-Signal Parallel Processing Architecture for Miniature and Microrobotics

PubMed Central

Sadler, Brian M; Hoyos, Sebastian

2014-01-01

The conventional analog-to-digital conversion (ADC) and digital signal processing (DSP) architecture has led to major advances in miniature and micro-systems technology over the past several decades. The outlook for these systems is significantly enhanced by advances in sensing, signal processing, communications and control, and the combination of these technologies enables autonomous robotics on the miniature to micro scales. In this article we look at trends in the combination of analog and digital (mixed-signal) processing, and consider a generalized sampling architecture. Employing a parallel analog basis expansion of the input signal, this scalable approach is adaptable and reconfigurable, and is suitable for a large variety of current and future applications in networking, perception, cognition, and control. PMID:26601042

Detection of Single Molecules Illuminated by a Light-Emitting Diode

PubMed Central

Gerhardt, Ilja; Mai, Lijian; Lamas-Linares, Antía; Kurtsiefer, Christian

2011-01-01

Optical detection and spectroscopy of single molecules has become an indispensable tool in biological imaging and sensing. Its success is based on fluorescence of organic dye molecules under carefully engineered laser illumination. In this paper we demonstrate optical detection of single molecules on a wide-field microscope with an illumination based on a commercially available, green light-emitting diode. The results are directly compared with laser illumination in the same experimental configuration. The setup and the limiting factors, such as light transfer to the sample, spectral filtering and the resulting signal-to-noise ratio are discussed. A theoretical and an experimental approach to estimate these parameters are presented. The results can be adapted to other single emitter and illumination schemes. PMID:22346610

Stress and depression in mothers of failure-to-thrive children.

PubMed

Singer, L T; Song, L Y; Hill, B P; Jaffe, A C

1990-12-01

Compared 30 mothers whose children were hospitalized for failure-to-thrive (FTT) to a normative group on standardized measures of perceived stress and depression. Child and maternal medical and demographic data were also taken. Standardized development and feeding assessments were done. Descriptive statistics, correlational analyses, and t tests were used to describe and examine group differences. FTT children were perceived overall as more stressful, less adaptable, more inconsolable, and more unhappy than were healthy children. Child characteristics associated with higher maternal stress levels were higher birth weight, absence of organic disease or behavioral feeding problems, and higher IQ. Maternal self-report of depression, attachment to her child, sense of competence in parenting, social isolation, and relationship to spouse were not different from the normative sample.

Determination of Movement Sense in Mylonites.

ERIC Educational Resources Information Center

Simpson, Carol

1986-01-01

Describes how mylonite samples can be used to determine the sense of shear. Several sample collection techniques are presented. Criteria for shear sense determination are outlined and discussed so that they can be recognized and interpreted by students familiar with the use of a compass and a petrographic microscope. (TW)

A Ground Systems Template for Remote Sensing Systems

NASA Astrophysics Data System (ADS)

McClanahan, Timothy P.; Trombka, Jacob I.; Floyd, Samuel R.; Truskowski, Walter; Starr, Richard D.; Clark, Pamela E.; Evans, Larry G.

2002-10-01

Spaceborne remote sensing using gamma and X-ray spectrometers requires particular attention to the design and development of reliable systems. These systems must ensure the scientific requirements of the mission within the challenging technical constraints of operating instrumentation in space. The Near Earth Asteroid Rendezvous (NEAR) spacecraft included X-ray and gamma-ray spectrometers (XGRS), whose mission was to map the elemental chemistry of the 433 Eros asteroid. A remote sensing system template, similar to a blackboard systems approach used in artificial intelligence, was identified in which the spacecraft, instrument, and ground system was designed and developed to monitor and adapt to evolving mission requirements in a complicated operational setting. Systems were developed for ground tracking of instrument calibration, instrument health, data quality, orbital geometry, solar flux as well as models of the asteroid's surface characteristics, requiring an intensive human effort. In the future, missions such as the Autonomous Nano-Technology Swarm (ANTS) program will have to rely heavily on automation to collectively encounter and sample asteroids in the outer asteroid belt. Using similar instrumentation, ANTS will require information similar to data collected by the NEAR X-ray/Gamma-Ray Spectrometer (XGRS) ground system for science and operations management. The NEAR XGRS systems will be studied to identify the equivalent subsystems that may be automated for ANTS. The effort will also investigate the possibility of applying blackboard style approaches to automated decision making required for ANTS.

Principles underlying the design of "The Number Race", an adaptive computer game for remediation of dyscalculia

PubMed Central

Wilson, Anna J; Dehaene, Stanislas; Pinel, Philippe; Revkin, Susannah K; Cohen, Laurent; Cohen, David

2006-01-01

Background Adaptive game software has been successful in remediation of dyslexia. Here we describe the cognitive and algorithmic principles underlying the development of similar software for dyscalculia. Our software is based on current understanding of the cerebral representation of number and the hypotheses that dyscalculia is due to a "core deficit" in number sense or in the link between number sense and symbolic number representations. Methods "The Number Race" software trains children on an entertaining numerical comparison task, by presenting problems adapted to the performance level of the individual child. We report full mathematical specifications of the algorithm used, which relies on an internal model of the child's knowledge in a multidimensional "learning space" consisting of three difficulty dimensions: numerical distance, response deadline, and conceptual complexity (from non-symbolic numerosity processing to increasingly complex symbolic operations). Results The performance of the software was evaluated both by mathematical simulations and by five weeks of use by nine children with mathematical learning difficulties. The results indicate that the software adapts well to varying levels of initial knowledge and learning speeds. Feedback from children, parents and teachers was positive. A companion article [1] describes the evolution of number sense and arithmetic scores before and after training. Conclusion The software, open-source and freely available online, is designed for learning disabled children aged 5–8, and may also be useful for general instruction of normal preschool children. The learning algorithm reported is highly general, and may be applied in other domains. PMID:16734905

Decentralized digital adaptive control of robot motion

NASA Technical Reports Server (NTRS)

Tarokh, M.

1990-01-01

A decentralized model reference adaptive scheme is developed for digital control of robot manipulators. The adaptation laws are derived using hyperstability theory, which guarantees asymptotic trajectory tracking despite gross robot parameter variations. The control scheme has a decentralized structure in the sense that each local controller receives only its joint angle measurement to produce its joint torque. The independent joint controllers have simple structures and can be programmed using a very simple and computationally fast algorithm. As a result, the scheme is suitable for real-time motion control.

Sliding Mode Control of Dynamic Voltage Restorer by Using a New Adaptive Reaching Law

NASA Astrophysics Data System (ADS)

Pandey, Achala; Agrawal, Rekha; Mandloi, Ravindra S.; Sarkar, Biswaroop

2017-12-01

This paper presents a new kind of adaptive reaching law for sliding mode control of Dynamic Voltage Restorer (DVR). Such an adaptive reaching law follows under-damped sinusoidal nature that causes the initial state to reach the sliding regime in extremely less time with negligible chattering. Moreover, it is robust in the sense the trajectory does not deviate from the sliding surface. This new approach is developed and successfully applied to DVR. The simulation results are presented that show its robustness.

The Durham Adaptive Optics Simulation Platform (DASP): Current status

NASA Astrophysics Data System (ADS)

Basden, A. G.; Bharmal, N. A.; Jenkins, D.; Morris, T. J.; Osborn, J.; Peng, J.; Staykov, L.

2018-01-01

The Durham Adaptive Optics Simulation Platform (DASP) is a Monte-Carlo modelling tool used for the simulation of astronomical and solar adaptive optics systems. In recent years, this tool has been used to predict the expected performance of the forthcoming extremely large telescope adaptive optics systems, and has seen the addition of several modules with new features, including Fresnel optics propagation and extended object wavefront sensing. Here, we provide an overview of the features of DASP and the situations in which it can be used. Additionally, the user tools for configuration and control are described.

Analysis of Cell Biomechanics Response to Gravity:A Fluids for Biology Study Utilizing NASA Glenns Zero Gravity Research Facility

NASA Technical Reports Server (NTRS)

Bomani, Bilal M. M.; Kassemi, Mohammad; Neumann, Eric S.

2016-01-01

It remains unclear how biological cells sense and respond to gravitational forces. Leading scientists state that a large gap exists in the understanding of physiological and molecular adaptation that occurs as biology enters the spaceflight realm. We are seeking a method to fully understand how cells sense microgravity/gravity and what triggers their response.

Contribution of blood oxygen and carbon dioxide sensing to the energetic optimization of human walking.

PubMed

Wong, Jeremy D; O'Connor, Shawn M; Selinger, Jessica C; Donelan, J Maxwell

2017-08-01

People can adapt their gait to minimize energetic cost, indicating that walking's neural control has access to ongoing measurements of the body's energy use. In this study we tested the hypothesis that an important source of energetic cost measurements arises from blood gas receptors that are sensitive to O 2 and CO 2 concentrations. These receptors are known to play a role in regulating other physiological processes related to energy consumption, such as ventilation rate. Given the role of O 2 and CO 2 in oxidative metabolism, sensing their levels can provide an accurate estimate of the body's total energy use. To test our hypothesis, we simulated an added energetic cost for blood gas receptors that depended on a subject's step frequency and determined if subjects changed their behavior in response to this simulated cost. These energetic costs were simulated by controlling inspired gas concentrations to decrease the circulating levels of O 2 and increase CO 2 We found this blood gas control to be effective at shifting the step frequency that minimized the ventilation rate and perceived exertion away from the normally preferred frequency, indicating that these receptors provide the nervous system with strong physiological and psychological signals. However, rather than adapt their preferred step frequency toward these lower simulated costs, subjects persevered at their normally preferred frequency even after extensive experience with the new simulated costs. These results suggest that blood gas receptors play a negligible role in sensing energetic cost for the purpose of optimizing gait. NEW & NOTEWORTHY Human gait adaptation implies that the nervous system senses energetic cost, yet this signal is unknown. We tested the hypothesis that the blood gas receptors sense cost for gait optimization by controlling blood O 2 and CO 2 with step frequency as people walked. At the simulated energetic minimum, ventilation and perceived exertion were lowest, yet subjects preferred walking at their original frequency. This suggests that blood gas receptors are not critical for sensing cost during gait. Copyright © 2017 the American Physiological Society.

Adaptive foveated single-pixel imaging with dynamic supersampling

PubMed Central

Phillips, David B.; Sun, Ming-Jie; Taylor, Jonathan M.; Edgar, Matthew P.; Barnett, Stephen M.; Gibson, Graham M.; Padgett, Miles J.

2017-01-01

In contrast to conventional multipixel cameras, single-pixel cameras capture images using a single detector that measures the correlations between the scene and a set of patterns. However, these systems typically exhibit low frame rates, because to fully sample a scene in this way requires at least the same number of correlation measurements as the number of pixels in the reconstructed image. To mitigate this, a range of compressive sensing techniques have been developed which use a priori knowledge to reconstruct images from an undersampled measurement set. Here, we take a different approach and adopt a strategy inspired by the foveated vision found in the animal kingdom—a framework that exploits the spatiotemporal redundancy of many dynamic scenes. In our system, a high-resolution foveal region tracks motion within the scene, yet unlike a simple zoom, every frame delivers new spatial information from across the entire field of view. This strategy rapidly records the detail of quickly changing features in the scene while simultaneously accumulating detail of more slowly evolving regions over several consecutive frames. This architecture provides video streams in which both the resolution and exposure time spatially vary and adapt dynamically in response to the evolution of the scene. The degree of local frame rate enhancement is scene-dependent, but here, we demonstrate a factor of 4, thereby helping to mitigate one of the main drawbacks of single-pixel imaging techniques. The methods described here complement existing compressive sensing approaches and may be applied to enhance computational imagers that rely on sequential correlation measurements. PMID:28439538

A Small System—High-Resolution Study of Metabolic Adaptation in the Central Metabolic Pathway to Temperate Climates in Drosophila melanogaster

PubMed Central

Lavington, Erik; Cogni, Rodrigo; Kuczynski, Caitlin; Koury, Spencer; Behrman, Emily L.; O’Brien, Katherine R.; Schmidt, Paul S.; Eanes, Walter F.

2014-01-01

In this article, we couple the geographic variation in 127 single-nucleotide polymorphism (SNP) frequencies in genes of 46 enzymes of central metabolism with their associated cis-expression variation to predict latitudinal or climatic-driven gene expression changes in the metabolic architecture of Drosophila melanogaster. Forty-two percent of the SNPs in 65% of the genes show statistically significant clines in frequency with latitude across the 20 local population samples collected from southern Florida to Ontario. A number of SNPs in the screened genes are also associated with significant expression variation within the Raleigh population from North Carolina. A principal component analysis of the full variance–covariance matrix of latitudinal changes in SNP-associated standardized gene expression allows us to identify those major genes in the pathway and its associated branches that are likely targets of natural selection. When embedded in a central metabolic context, we show that these apparent targets are concentrated in the genes of the upper glycolytic pathway and pentose shunt, those controlling glycerol shuttle activity, and finally those enzymes associated with the utilization of glutamate and pyruvate. These metabolites possess high connectivity and thus may be the points where flux balance can be best shifted. We also propose that these points are conserved points associated with coupling energy homeostasis and energy sensing in mammals. We speculate that the modulation of gene expression at specific points in central metabolism that are associated with shifting flux balance or possibly energy-state sensing plays a role in adaptation to climatic variation. PMID:24770333

Plenoptic camera wavefront sensing with extended sources

NASA Astrophysics Data System (ADS)

Jiang, Pengzhi; Xu, Jieping; Liang, Yonghui; Mao, Hongjun

2016-09-01

The wavefront sensor is used in adaptive optics to detect the atmospheric distortion, which feeds back to the deformable mirror to compensate for this distortion. Different from the Shack-Hartmann sensor that has been widely used with point sources, the plenoptic camera wavefront sensor has been proposed as an alternative wavefront sensor adequate for extended objects in recent years. In this paper, the plenoptic camera wavefront sensing with extended sources is discussed systematically. Simulations are performed to investigate the wavefront measurement error and the closed-loop performance of the plenoptic sensor. The results show that there are an optimal lenslet size and an optimal number of pixels to make the best performance. The RMS of the resulting corrected wavefront in closed-loop adaptive optics system is less than 108 nm (0.2λ) when D/r0 ≤ 10 and the magnitude M ≤ 5. Our investigation indicates that the plenoptic sensor is efficient to operate on extended sources in the closed-loop adaptive optics system.

Phase retrieval based wavefront sensing experimental implementation and wavefront sensing accuracy calibration

NASA Astrophysics Data System (ADS)

Mao, Heng; Wang, Xiao; Zhao, Dazun

2009-05-01

As a wavefront sensing (WFS) tool, Baseline algorithm, which is classified as the iterative-transform algorithm of phase retrieval, estimates the phase distribution at pupil from some known PSFs at defocus planes. By using multiple phase diversities and appropriate phase unwrapping methods, this algorithm can accomplish reliable unique solution and high dynamic phase measurement. In the paper, a Baseline algorithm based wavefront sensing experiment with modification of phase unwrapping has been implemented, and corresponding Graphical User Interfaces (GUI) software has also been given. The adaptability and repeatability of Baseline algorithm have been validated in experiments. Moreover, referring to the ZYGO interferometric results, the WFS accuracy of this algorithm has been exactly calibrated.

Nanopore Device for Reversible Ion and Molecule Sensing or Migration

NASA Technical Reports Server (NTRS)

Seger, R. Adam (Inventor); Pourmand, Nader (Inventor); Actis, Paolo (Inventor); Singaram, Bakthan (Inventor); Vilozny, Boaz (Inventor)

2015-01-01

Disclosed are methods and devices for detection of ion migration and binding, utilizing a nanopipette adapted for use in an electrochemical sensing circuit. The nanopipette may be functionalized on its interior bore with metal chelators for binding and sensing metal ions or other specific binding molecules such as boronic acid for binding and sensing glucose. Such a functionalized nanopipette is comprised in an electrical sensor that detects when the nanopipette selectively and reversibly binds ions or small molecules. Also disclosed is a nanoreactor, comprising a nanopipette, for controlling precipitation in aqueous solutions by voltage-directed ion migration, wherein ions may be directed out of the interior bore by a repulsing charge in the bore.

Geometry correction Algorithm for UAV Remote Sensing Image Based on Improved Neural Network

NASA Astrophysics Data System (ADS)

Liu, Ruian; Liu, Nan; Zeng, Beibei; Chen, Tingting; Yin, Ninghao

2018-03-01

Aiming at the disadvantage of current geometry correction algorithm for UAV remote sensing image, a new algorithm is proposed. Adaptive genetic algorithm (AGA) and RBF neural network are introduced into this algorithm. And combined with the geometry correction principle for UAV remote sensing image, the algorithm and solving steps of AGA-RBF are presented in order to realize geometry correction for UAV remote sensing. The correction accuracy and operational efficiency is improved through optimizing the structure and connection weight of RBF neural network separately with AGA and LMS algorithm. Finally, experiments show that AGA-RBF algorithm has the advantages of high correction accuracy, high running rate and strong generalization ability.

pH measurements of FET-based (bio)chemical sensors using portable measurement system.

PubMed

Voitsekhivska, T; Zorgiebel, F; Suthau, E; Wolter, K-J; Bock, K; Cuniberti, G

2015-01-01

In this study we demonstrate the sensing capabilities of a portable multiplex measurement system for FET-based (bio)chemical sensors with an integrated microfluidic interface. We therefore conducted pH measurements with Silicon Nanoribbon FET-based Sensors using different measurement procedures that are suitable for various applications. We have shown multiplexed measurements in aqueous medium for three different modes that are mutually specialized in fast data acquisition (constant drain current), calibration-less sensing (constant gate voltage) and in providing full information content (sweeping mode). Our system therefore allows surface charge sensing for a wide range of applications and is easily adaptable for multiplexed sensing with novel FET-based (bio)chemical sensors.

In-vivo digital wavefront sensing using swept source OCT

PubMed Central

Kumar, Abhishek; Wurster, Lara M.; Salas, Matthias; Ginner, Laurin; Drexler, Wolfgang; Leitgeb, Rainer A.

2017-01-01

Sub-aperture based digital adaptive optics is demonstrated in a fiber based point scanning optical coherence tomography system using a 1060 nm swept source laser. To detect optical aberrations in-vivo, a small lateral field of view of ~150×150 μm2 is scanned on the sample at a high volume rate of 17 Hz (~1.3 kHz B-scan rate) to avoid any significant lateral and axial motion of the sample, and is used as a “guide star” for the sub-aperture based DAO. The proof of principle is demonstrated using a micro-beads phantom sample, wherein a significant root mean square wavefront error (RMS WFE) of 1.48 waves (> 1μm) is detected. In-vivo aberration measurement with a RMS WFE of 0.33 waves, which is ~5 times higher than the Marechal’s criterion of 1/14 waves for the diffraction limited performance, is shown for a human retinal OCT. Attempt has been made to validate the experimental results with the conventional Shack-Hartmann wavefront sensor within reasonable limitations. PMID:28717573

Surface sampling techniques for 3D object inspection

NASA Astrophysics Data System (ADS)

Shih, Chihhsiong S.; Gerhardt, Lester A.

1995-03-01

While the uniform sampling method is quite popular for pointwise measurement of manufactured parts, this paper proposes three novel sampling strategies which emphasize 3D non-uniform inspection capability. They are: (a) the adaptive sampling, (b) the local adjustment sampling, and (c) the finite element centroid sampling techniques. The adaptive sampling strategy is based on a recursive surface subdivision process. Two different approaches are described for this adaptive sampling strategy. One uses triangle patches while the other uses rectangle patches. Several real world objects were tested using these two algorithms. Preliminary results show that sample points are distributed more closely around edges, corners, and vertices as desired for many classes of objects. Adaptive sampling using triangle patches is shown to generally perform better than both uniform and adaptive sampling using rectangle patches. The local adjustment sampling strategy uses a set of predefined starting points and then finds the local optimum position of each nodal point. This method approximates the object by moving the points toward object edges and corners. In a hybrid approach, uniform points sets and non-uniform points sets, first preprocessed by the adaptive sampling algorithm on a real world object were then tested using the local adjustment sampling method. The results show that the initial point sets when preprocessed by adaptive sampling using triangle patches, are moved the least amount of distance by the subsequently applied local adjustment method, again showing the superiority of this method. The finite element sampling technique samples the centroids of the surface triangle meshes produced from the finite element method. The performance of this algorithm was compared to that of the adaptive sampling using triangular patches. The adaptive sampling with triangular patches was once again shown to be better on different classes of objects.

Mechano-adaptation of the stem cell nucleus.

PubMed

Heo, Su-Jin; Cosgrove, Brian D; Dai, Eric N; Mauck, Robert L

2018-01-01

Exogenous mechanical forces are transmitted through the cell and to the nucleus, initiating mechanotransductive signaling cascades with profound effects on cellular function and stem cell fate. A growing body of evidence has shown that the force sensing and force-responsive elements of the nucleus adapt to these mechanotransductive events, tuning their response to future mechanical input. The mechanisms underlying this "mechano-adaptation" are only just beginning to be elucidated, and it remains poorly understood how these components act and adapt in tandem to drive stem cell differentiation. Here, we review the evidence on how the stem cell nucleus responds and adapts to physical forces, and provide a perspective on how this mechano-adaptation may function to drive and enforce stem cell differentiation.

A preliminary study of the statistical analyses and sampling strategies associated with the integration of remote sensing capabilities into the current agricultural crop forecasting system

NASA Technical Reports Server (NTRS)

Sand, F.; Christie, R.

1975-01-01

Extending the crop survey application of remote sensing from small experimental regions to state and national levels requires that a sample of agricultural fields be chosen for remote sensing of crop acreage, and that a statistical estimate be formulated with measurable characteristics. The critical requirements for the success of the application are reviewed in this report. The problem of sampling in the presence of cloud cover is discussed. Integration of remotely sensed information about crops into current agricultural crop forecasting systems is treated on the basis of the USDA multiple frame survey concepts, with an assumed addition of a new frame derived from remote sensing. Evolution of a crop forecasting system which utilizes LANDSAT and future remote sensing systems is projected for the 1975-1990 time frame.

Sparse-view photoacoustic tomography using virtual parallel-projections and spatially adaptive filtering

NASA Astrophysics Data System (ADS)

Wang, Yihan; Lu, Tong; Wan, Wenbo; Liu, Lingling; Zhang, Songhe; Li, Jiao; Zhao, Huijuan; Gao, Feng

2018-02-01

To fully realize the potential of photoacoustic tomography (PAT) in preclinical and clinical applications, rapid measurements and robust reconstructions are needed. Sparse-view measurements have been adopted effectively to accelerate the data acquisition. However, since the reconstruction from the sparse-view sampling data is challenging, both of the effective measurement and the appropriate reconstruction should be taken into account. In this study, we present an iterative sparse-view PAT reconstruction scheme where a virtual parallel-projection concept matching for the proposed measurement condition is introduced to help to achieve the "compressive sensing" procedure of the reconstruction, and meanwhile the spatially adaptive filtering fully considering the a priori information of the mutually similar blocks existing in natural images is introduced to effectively recover the partial unknown coefficients in the transformed domain. Therefore, the sparse-view PAT images can be reconstructed with higher quality compared with the results obtained by the universal back-projection (UBP) algorithm in the same sparse-view cases. The proposed approach has been validated by simulation experiments, which exhibits desirable performances in image fidelity even from a small number of measuring positions.

The AVIRIS Low Altitude Option-An Approach to Increase Geometric Resolution and Improve Operational Flexibility Simultaneously

NASA Technical Reports Server (NTRS)

Sarture, Charles M.; Chovit, Christopher J.; Chrien, Thomas G.; Eastwood, Michael L.; Green, Robert O.; Kurzwell, Charles G.

1998-01-01

From 1987 through 1997 the Airborne Visible-InfraRed Imaging Spectrometer has matured into a remote sensing instrument capable of producing prodigious amounts of high quality data. Using the NASA/Ames ER-2 high altitude aircraft platform, flight operations have become very reliable as well. Being exclusively dependent on the ER-2, however, has limitations: the ER-2 has a narrow cruise envelope which fixes the AVIRIS ground pixel at 20 meters; it requires a significant support infrastructure; and it has a very limited number of bases it can operate from. In the coming years, the ER-2 will also become less available for AVIRIS flights as NASA Earth Observing System satellite underflights increase. Adapting AVIRIS to lower altitude, less specialized aircraft will create a much broader envelope for data acquisition, i.e., higher ground geometric resolution while maintaining nearly the ideal spatial sampling. This approach will also greatly enhance flexibility while decreasing the overall cost of flight operations and field support. Successful adaptation is expected to culminate with a one-month period of demonstration flights.

Characterising a holographic modal phase mask for the detection of ocular aberrations

NASA Astrophysics Data System (ADS)

Corbett, A. D.; Leyva, D. Gil; Diaz-Santana, L.; Wilkinson, T. D.; Zhong, J. J.

2005-12-01

The accurate measurement of the double-pass ocular wave front has been shown to have a broad range of applications from LASIK surgery to adaptively corrected retinal imaging. The ocular wave front can be accurately described by a small number of Zernike circle polynomials. The modal wave front sensor was first proposed by Neil et al. and allows the coefficients of the individual Zernike modes to be measured directly. Typically the aberrations measured with the modal sensor are smaller than those seen in the ocular wave front. In this work, we investigated a technique for adapting a modal phase mask for the sensing of the ocular wave front. This involved extending the dynamic range of the sensor by increasing the pinhole size to 2.4mm and optimising the mask bias to 0.75λ. This was found to decrease the RMS error by up to a factor of three for eye-like aberrations with amplitudes up to 0.2μm. For aberrations taken from a sample of real-eye measurements a 20% decrease in the RMS error was observed.

Network Topologies and Dynamics Leading to Endotoxin Tolerance and Priming in Innate Immune Cells

NASA Astrophysics Data System (ADS)

Fu, Yan; Glaros, Trevor; Zhu, Meng; Wang, Ping; Wu, Zhanghan; Tyson, John; Li, Liwu; Xing, Jianhua

2012-01-01

The innate immune system, acting as the first line of host defense, senses and adapts to foreign challenges through complex intracellular and intercellular signaling networks. Endotoxin tolerance and priming elicited by macrophages are classic examples of the complex adaptation of innate immune cells. Upon repetitive exposures to different doses of bacterial endotoxin (lipopolysaccharide) or other stimulants, macrophages show either suppressed or augmented inflammatory responses compared to a single exposure to the stimulant. Endotoxin tolerance and priming are critically involved in both immune homeostasis and the pathogenesis of diverse inflammatory diseases. However, the underlying molecular mechanisms are not well understood. By means of a computational search through the parameter space of a coarse-grained three-node network with a two-stage Metropolis sampling approach, we enumerated all the network topologies that can generate priming or tolerance. We discovered three major mechanisms for priming (pathway synergy, suppressor deactivation, activator induction) and one for tolerance (inhibitor persistence). These results not only explain existing experimental observations, but also reveal intriguing test scenarios for future experimental studies to clarify mechanisms of endotoxin priming and tolerance.

Dynamic sensing model for accurate delectability of environmental phenomena using event wireless sensor network

NASA Astrophysics Data System (ADS)

Missif, Lial Raja; Kadhum, Mohammad M.

2017-09-01

Wireless Sensor Network (WSN) has been widely used for monitoring where sensors are deployed to operate independently to sense abnormal phenomena. Most of the proposed environmental monitoring systems are designed based on a predetermined sensing range which does not reflect the sensor reliability, event characteristics, and the environment conditions. Measuring of the capability of a sensor node to accurately detect an event within a sensing field is of great important for monitoring applications. This paper presents an efficient mechanism for even detection based on probabilistic sensing model. Different models have been presented theoretically in this paper to examine their adaptability and applicability to the real environment applications. The numerical results of the experimental evaluation have showed that the probabilistic sensing model provides accurate observation and delectability of an event, and it can be utilized for different environment scenarios.

Radar network communication through sensing of frequency hopping

DOEpatents

Dowla, Farid; Nekoogar, Faranak

2013-05-28

In one embodiment, a radar communication system includes a plurality of radars having a communication range and being capable of operating at a sensing frequency and a reporting frequency, wherein the reporting frequency is different than the sensing frequency, each radar is adapted for operating at the sensing frequency until an event is detected, each radar in the plurality of radars has an identification/location frequency for reporting information different from the sensing frequency, a first radar of the radars which senses the event sends a reporting frequency corresponding to its identification/location frequency when the event is detected, and all other radars in the plurality of radars switch their reporting frequencies to match the reporting frequency of the first radar upon detecting the reporting frequency switch of a radar within the communication range. In another embodiment, a method is presented for communicating information in a radar system.

The Cultural Adaptation of the Youth Quality of Life Instrument-Research Version for Latino Children and Adolescents

ERIC Educational Resources Information Center

Chavez, Ligia M.; Matias-Carrelo, Leida; Barrio, Concepcion; Canino, Glorisa

2007-01-01

We reviewed the Spanish translation of the Youth Quality of Life Instrument-Research Version (YQOL-R) and culturally adapted the measure with Puerto Rican and Mexican American children and adolescents. The YQOL-R is a self-reported measure that includes four domains: Sense of Self, Social Relationships, Environment, and General Quality of Life. A…

Dissecting the regulon of the two-component system CvsSR: Identifying new virulence genes in Pseudomonas syringae pv. tomato DC3000

USDA-ARS?s Scientific Manuscript database

Recognition of environmental changes and regulation of genes that allow for adaption to those changes is essential for survival of bacteria. Two-component systems (TCSs) allow bacteria to sense and adapt to their environment. We previously identified the TCS CvsSR in the bacterial plant pathogen Pse...

Multi-Modalities Sensor Science

DTIC Science & Technology

2015-02-28

enhanced multi-mode sensor science. bio -sensing, cross-discipling, multi-physics, nano-technology sailing He +46-8790 8465 1 Final Report for SOARD Project...spectroscopy, nano-technology, biophotonics and multi-physics modeling to produce adaptable bio -nanostructure enhanced multi-mode sensor science. 1...adaptable bio -nanostructure enhanced multi-mode sensor science. The accomplishments includes 1) A General Method for Designing a Radome to Enhance

Confronting illusions of knowledge: how should we learn?

Treesearch

Sally Duncan

1999-01-01

Adaptive management. What is it and how can it help us learn? Bernard Bormann, a PNW Research Station scientist, is leading a study on the subject. He defines the term this way: the management of complex natural systems by building on common sense and learning from experience. Experience can often mean change. The challenge of implementing adaptive management is how to...

Mitochondrial protein acetylation mediates nutrient sensing of mitochondrial protein synthesis and mitonuclear protein balance.

PubMed

Di Domenico, Antonella; Hofer, Annette; Tundo, Federica; Wenz, Tina

2014-11-01

Changes in nutrient supply require global metabolic reprogramming to optimize the utilization of the nutrients. Mitochondria as a central component of the cellular metabolism play a key role in this adaptive process. Since mitochondria harbor their own genome, which encodes essential enzymes, mitochondrial protein synthesis is a determinant of metabolic adaptation. While regulation of cytoplasmic protein synthesis in response to metabolic challenges has been studied in great detail, mechanisms which adapt mitochondrial translation in response to metabolic challenges remain elusive. Our results suggest that the mitochondrial acetylation status controlled by Sirt3 and its proposed opponent GCN5L1 is an important regulator of the metabolic adaptation of mitochondrial translation. Moreover, both proteins modulate regulators of cytoplasmic protein synthesis as well as the mitonuclear protein balance making Sirt3 and GCN5L1 key players in synchronizing mitochondrial and cytoplasmic translation. Our results thereby highlight regulation of mitochondrial translation as a novel component in the cellular nutrient sensing scheme and identify mitochondrial acetylation as a new regulatory principle for the metabolic competence of mitochondrial protein synthesis. © 2014 International Union of Biochemistry and Molecular Biology.

Exfiltrometer apparatus and method for measuring unsaturated hydrologic properties in soil

DOEpatents

Hubbell, Joel M.; Sisson, James B.; Schafer, Annette L.

2006-01-17

Exfiltrometer apparatus includes a container for holding soil. A sample container for holding sample soil is positionable with respect to the container so that the sample soil contained in the sample container is in communication with soil contained in the container. A first tensiometer operatively associated with the sample container senses a surface water potential at about a surface of the sample soil contained in the sample container. A second tensiometer operatively associated with the sample container senses a first subsurface water potential below the surface of the sample soil. A water content sensor operatively associated with the sample container senses a water content in the sample soil. A water supply supplies water to the sample soil. A data logger operatively connected to the first and second tensiometers, and to the water content sensor receives and processes data provided by the first and second tensiometers and by the water content sensor.

Deploying a Proximal Sensing Cart to Identify Drought-Adaptive Traits in Upland Cotton for High-Throughput Phenotyping

PubMed Central

Thompson, Alison L.; Thorp, Kelly R.; Conley, Matthew; Andrade-Sanchez, Pedro; Heun, John T.; Dyer, John M.; White, Jeffery W.

2018-01-01

Field-based high-throughput phenotyping is an emerging approach to quantify difficult, time-sensitive plant traits in relevant growing conditions. Proximal sensing carts represent an alternative platform to more costly high-clearance tractors for phenotyping dynamic traits in the field. A proximal sensing cart and specifically a deployment protocol, were developed to phenotype traits related to drought tolerance in the field. The cart-sensor package included an infrared thermometer, ultrasonic transducer, multi-spectral reflectance sensor, weather station, and RGB cameras. The cart deployment protocol was evaluated on 35 upland cotton (Gossypium hirsutum L.) entries grown in 2017 at Maricopa, AZ, United States. Experimental plots were grown under well-watered and water-limited conditions using a (0,1) alpha lattice design and evaluated in June and July. Total collection time of the 0.87 hectare field averaged 2 h and 27 min and produced 50.7 MB and 45.7 GB of data from the sensors and RGB cameras, respectively. Canopy temperature, crop water stress index (CWSI), canopy height, normalized difference vegetative index (NDVI), and leaf area index (LAI) differed among entries and showed an interaction with the water regime (p < 0.05). Broad-sense heritability (H2) estimates ranged from 0.097 to 0.574 across all phenotypes and collections. Canopy cover estimated from RGB images increased with counts of established plants (r = 0.747, p = 0.033). Based on the cart-derived phenotypes, three entries were found to have improved drought-adaptive traits compared to a local adapted cultivar. These results indicate that the deployment protocol developed for the cart and sensor package can measure multiple traits rapidly and accurately to characterize complex plant traits under drought conditions. PMID:29868041

Paranoia as an Antecedent and Consequence of Getting Ahead in Organizations: Time-Lagged Effects Between Paranoid Cognitions, Self-Monitoring, and Changes in Span of Control

PubMed Central

Van Quaquebeke, Niels

2016-01-01

A 6-month, time-lagged online survey among 441 employees in diverse industries was conducted to investigate the role paranoia plays as an antecedent and as a consequence of advancement in organizations. The background of the study is the argument that it requires active social sense-making and behavioral adaptability to advance in organizations. The present paper thus explores the extent to which employees’ paranoid cognitions—representative of a heightened albeit suspicious sense-making and behavioral adaptability—link with their advancement in organizations (operationalized as changes in afforded span of control), both as an antecedent and an outcome. Following the strategy to illuminate the process by interaction analysis, both conditions (antecedent and outcome) are examined in interaction with employees’ self-monitoring, which is considered representative of a heightened but healthy sense-making and behavioral adaptability. Results support the expected interference interaction between paranoid cognitions and self-monitoring in that each can to some degree compensate for the other in explaining employees’ organizational advancement. Reversely, changes in span of control also affected paranoid cognitions. In particular, low self-monitors, i.e., those low in adaptive sense-making, reacted with heightened paranoid cognitions when demoted. In effect, the present study is thus the first to empirically support that paranoid cognitions can be a consequence but also a prerequisite for getting ahead in organizations. Practical advice should, however, be suspended until it is better understood whether and under what circumstances paranoia may relate not only to personally getting ahead but also to an increased effectiveness for the benefit of the organization. PMID:27713724

A Fabric Revolution. AFFOA Is Weaving the Next Fiber and Textile Revolution

DTIC Science & Technology

2016-10-01

adapt to both hot and cold environments • Home insulation and road construction materials that can monitor the performance of insulation and water...hear, sense, communicate, store and convert energy, regulate temperature, monitor health and change color—heralding the dawn of a “fabric...environ- mental conditions or wearer needs, monitoring health factors to both sense and treat injury, generating and/or storing energy from the

Safe Operations of Unmanned Systems for Reconnaissance in Complex Environments Army Technology Objective (SOURCE ATO)

DTIC Science & Technology

2011-04-25

must adapt its planning to vehicle size, shape, wheelbase, wheel and axle configuration, the specific obstacle-crossing capabilities of the vehicle...scalability of the ANS is a consequence of making each sensing modality capable of performing reasonable perception tasks while allowing a wider...autonomous system design achieves flexibility by exploiting redundant sensing modalities where possible, and by a decision-making process that

Ocean Remote Sensing Using Ambient Noise

DTIC Science & Technology

2015-09-30

and other adaptive array processing methods. OBJECTIVES Work on this project has focused on noise interferometry – the process by which an...measured at xA and xB. In that context, our objective is to investigate and identify the limitations of noise interferometry for remote sensing...and 6 is ongoing. 1. Demonstration of noise interferometry at 10 km range in a shallow water environment Recently conducted experiments in the

Atmospheric and ocean sensing with GNSS

NASA Technical Reports Server (NTRS)

Yunck, Thomas P.; Hajj, George A.

2003-01-01

The 1980s and 1990s saw the Global Positioning System (GPS) transform space geodesy from an elite national enterprise to one open to the individual researcher. By adapting the tools from that endeavor we are learning to probe the atmosphere and the ocean surface in novel ways, including ground-based sensing of atmospheric moisture; space-based profiling of atmospheric refractivity by active limb sounding; and global ocean altimetry with reflected signals.

Remote sensing of vegetation pattern and condition to monitor changes in Everglades biogeochemistry

USGS Publications Warehouse

Jones, John W.

2011-01-01

Ground-based studies of biogeochemistry and vegetation patterning yield process understanding, but the amount of information gained by ground-based studies can be greatly enhanced by efficient, synoptic, and temporally resolute monitoring afforded by remote sensing. The variety of presently available Everglades vegetation maps reflects both the wide range of application requirements and the need to balance cost and capability. More effort needs to be applied to documenting and understanding vegetation distribution and condition as indicators of biogeochemistry and contamination. Ground-based and remote sensing studies should be modified to maximize their synergy and utility for adaptive management.

Fiber optic medical pressure-sensing system employing intelligent self-calibration

NASA Astrophysics Data System (ADS)

He, Gang

1996-01-01

In this article, we describe a fiber-optic catheter-type pressure-sensing system that has been successfully introduced for medical diagnostic applications. We present overall sensors and optoelectronics designs, and highlight product development efforts that lead to a reliable and accurate disposable pressure-sensing system. In particular, the incorporation of an intelligent on-site self-calibration approach allows limited sensor reuses for reducing end-user costs and for system adaptation to wide sensor variabilities associated with low-cost manufacturing processes. We demonstrate that fiber-optic sensors can be cost-effectively produced to satisfy needs of certain medical market segments.

School Principals' Leadership Behaviours and Its Relation with Teachers' Sense of Self-Efficacy

ERIC Educational Resources Information Center

Mehdinezhad, Vali; Mansouri, Masoumeh

2016-01-01

The aim of this study was to investigate the relationship between school principals' leadership behaviours and teachers' sense of self-efficacy. The research method was descriptive and correlational. A sample size of 254 teachers was simply selected randomly by proportional sampling. For data collection, the Teachers' Sense of Efficacy Scale of…

Mapping urban climate zones and quantifying climate behaviors--an application on Toulouse urban area (France).

PubMed

Houet, Thomas; Pigeon, Grégoire

2011-01-01

Facing the concern of the population to its environment and to climatic change, city planners are now considering the urban climate in their choices of planning. The use of climatic maps, such Urban Climate Zone‑UCZ, is adapted for this kind of application. The objective of this paper is to demonstrate that the UCZ classification, integrated in the World Meteorological Organization guidelines, first can be automatically determined for sample areas and second is meaningful according to climatic variables. The analysis presented is applied on Toulouse urban area (France). Results show first that UCZ differentiate according to air and surface temperature. It has been possible to determine the membership of sample areas to an UCZ using landscape descriptors automatically computed with GIS and remote sensed data. It also emphasizes that climate behavior and magnitude of UCZ may vary from winter to summer. Finally we discuss the influence of climate data and scale of observation on UCZ mapping and climate characterization. Copyright © 2011 Elsevier Ltd. All rights reserved.

Methodologies and Perspectives of Proteomics Applied to Filamentous Fungi: From Sample Preparation to Secretome Analysis

PubMed Central

Bianco, Linda; Perrotta, Gaetano

2015-01-01

Filamentous fungi possess the extraordinary ability to digest complex biomasses and mineralize numerous xenobiotics, as consequence of their aptitude to sensing the environment and regulating their intra and extra cellular proteins, producing drastic changes in proteome and secretome composition. Recent advancement in proteomic technologies offers an exciting opportunity to reveal the fluctuations of fungal proteins and enzymes, responsible for their metabolic adaptation to a large variety of environmental conditions. Here, an overview of the most commonly used proteomic strategies will be provided; this paper will range from sample preparation to gel-free and gel-based proteomics, discussing pros and cons of each mentioned state-of-the-art technique. The main focus will be kept on filamentous fungi. Due to the biotechnological relevance of lignocellulose degrading fungi, special attention will be finally given to their extracellular proteome, or secretome. Secreted proteins and enzymes will be discussed in relation to their involvement in bio-based processes, such as biomass deconstruction and mycoremediation. PMID:25775160

Methodologies and perspectives of proteomics applied to filamentous fungi: from sample preparation to secretome analysis.

PubMed

Bianco, Linda; Perrotta, Gaetano

2015-03-12

Filamentous fungi possess the extraordinary ability to digest complex biomasses and mineralize numerous xenobiotics, as consequence of their aptitude to sensing the environment and regulating their intra and extra cellular proteins, producing drastic changes in proteome and secretome composition. Recent advancement in proteomic technologies offers an exciting opportunity to reveal the fluctuations of fungal proteins and enzymes, responsible for their metabolic adaptation to a large variety of environmental conditions. Here, an overview of the most commonly used proteomic strategies will be provided; this paper will range from sample preparation to gel-free and gel-based proteomics, discussing pros and cons of each mentioned state-of-the-art technique. The main focus will be kept on filamentous fungi. Due to the biotechnological relevance of lignocellulose degrading fungi, special attention will be finally given to their extracellular proteome, or secretome. Secreted proteins and enzymes will be discussed in relation to their involvement in bio-based processes, such as biomass deconstruction and mycoremediation.

Design of a Single Channel Modulated Wideband Converter for Wideband Spectrum Sensing: Theory, Architecture and Hardware Implementation

PubMed Central

Liu, Weisong; Huang, Zhitao; Wang, Xiang; Sun, Weichao

2017-01-01

In a cognitive radio sensor network (CRSN), wideband spectrum sensing devices which aims to effectively exploit temporarily vacant spectrum intervals as soon as possible are of great importance. However, the challenge of increasingly high signal frequency and wide bandwidth requires an extremely high sampling rate which may exceed today’s best analog-to-digital converters (ADCs) front-end bandwidth. Recently, the newly proposed architecture called modulated wideband converter (MWC), is an attractive analog compressed sensing technique that can highly reduce the sampling rate. However, the MWC has high hardware complexity owing to its parallel channel structure especially when the number of signals increases. In this paper, we propose a single channel modulated wideband converter (SCMWC) scheme for spectrum sensing of band-limited wide-sense stationary (WSS) signals. With one antenna or sensor, this scheme can save not only sampling rate but also hardware complexity. We then present a new, SCMWC based, single node CR prototype System, on which the spectrum sensing algorithm was tested. Experiments on our hardware prototype show that the proposed architecture leads to successful spectrum sensing. And the total sampling rate as well as hardware size is only one channel’s consumption of MWC. PMID:28471410

Neuroethology and life history adaptations of the elasmobranch electric sense.

PubMed

Sisneros, Joseph A; Tricas, Timothy C

2002-01-01

The electric sense of elasmobranch fishes (sharks and rays) is an important sensory modality known to mediate the detection of bioelectric stimuli. Although the best known function for the use of the elasmobranch electric sense is prey detection, relatively few studies have investigated other possible biological functions. Here, we review recent studies that demonstrate the elasmobranch electrosensory system functions in a wide number of behavioral contexts including social, reproductive and anti-predator behaviors. Recent work on non-electrogenic stingrays demonstrates that the electric sense is used during reproduction and courtship for conspecific detection and localization. Electrogenic skates may use their electrosensory encoding capabilities and electric organ discharges for communication during social and reproductive interactions. The electric sense may also be used to detect and avoid predators during early life history stages in many elasmobranch species. Embryonic clearnose skates demonstrate a ventilatory freeze response when a weak low-frequency electric field is imposed upon the egg capsule. Peak frequency sensitivity of the peripheral electrosensory system in embryonic skates matches the low frequencies of phasic electric stimuli produced by natural fish egg-predators. Neurophysiology experiments reveal that electrosensory tuning changes across the life history of a species and also seasonally due to steroid hormone changes during the reproductive season. We argue that the ontogenetic and seasonal variation in electrosensory tuning represent an adaptive electrosensory plasticity that may be common to many elasmobranchs to enhance an individual's fitness throughout its life history.

Changes in frontal-parietal activation and math skills performance following adaptive number sense training: Preliminary results from a pilot study

PubMed Central

Kesler, Shelli R.; Sheau, Kristen; Koovakkattu, Della; Reiss, Allan L.

2011-01-01

Number sense is believed to be critical for math development. It is putatively an implicitly learned skill and may therefore have limitations in terms of being explicitly trained, particularly in individuals with altered neurodevelopment. A case series study was conducted using an adaptive, computerized program that focused on number sense and general problem solving skills was designed to investigate training effects on performance as well as brain function in a group of children with Turner syndrome who are at risk for math difficulties and altered development of math-related brain networks. Standardized measurements of math and math-related cognitive skills as well as functional magnetic resonance imaging (fMRI) were used to assess behavioral and neurobiologic outcomes following training. Participants demonstrated significantly increased basic math skills, including number sense, and calculation as well as processing speed, cognitive flexibility and visual-spatial processing skills. With the exception of calculation, increased scores also were clinically significant (i.e. recovered) based on reliable change analysis. Participants additionally demonstrated significantly increased bilateral parietal lobe activation and decreased frontal-striatal and mesial temporal activation following the training program. These findings show proof of concept for an accessible training approach that may be potentially associated with improved number sense, math and related skills, as well as functional changes in math-related neural systems, even among individuals at risk for altered brain development. PMID:21714745

A mobile sensing system for structural health monitoring: design and validation

NASA Astrophysics Data System (ADS)

Zhu, Dapeng; Yi, Xiaohua; Wang, Yang; Lee, Kok-Meng; Guo, Jiajie

2010-05-01

This paper describes a new approach using mobile sensor networks for structural health monitoring. Compared with static sensors, mobile sensor networks offer flexible system architectures with adaptive spatial resolutions. The paper first describes the design of a mobile sensing node that is capable of maneuvering on structures built with ferromagnetic materials. The mobile sensing node can also attach/detach an accelerometer onto/from the structural surface. The performance of the prototype mobile sensor network has been validated through laboratory experiments. Two mobile sensing nodes are adopted for navigating on a steel portal frame and providing dense acceleration measurements. Transmissibility function analysis is conducted to identify structural damage using data collected by the mobile sensing nodes. This preliminary work is expected to spawn transformative changes in the use of mobile sensors for future structural health monitoring.

Thermodynamic Costs of Information Processing in Sensory Adaptation

PubMed Central

Sartori, Pablo; Granger, Léo; Lee, Chiu Fan; Horowitz, Jordan M.

2014-01-01

Biological sensory systems react to changes in their surroundings. They are characterized by fast response and slow adaptation to varying environmental cues. Insofar as sensory adaptive systems map environmental changes to changes of their internal degrees of freedom, they can be regarded as computational devices manipulating information. Landauer established that information is ultimately physical, and its manipulation subject to the entropic and energetic bounds of thermodynamics. Thus the fundamental costs of biological sensory adaptation can be elucidated by tracking how the information the system has about its environment is altered. These bounds are particularly relevant for small organisms, which unlike everyday computers, operate at very low energies. In this paper, we establish a general framework for the thermodynamics of information processing in sensing. With it, we quantify how during sensory adaptation information about the past is erased, while information about the present is gathered. This process produces entropy larger than the amount of old information erased and has an energetic cost bounded by the amount of new information written to memory. We apply these principles to the E. coli's chemotaxis pathway during binary ligand concentration changes. In this regime, we quantify the amount of information stored by each methyl group and show that receptors consume energy in the range of the information-theoretic minimum. Our work provides a basis for further inquiries into more complex phenomena, such as gradient sensing and frequency response. PMID:25503948

Dynamic Experiment Design Regularization Approach to Adaptive Imaging with Array Radar/SAR Sensor Systems

PubMed Central

Shkvarko, Yuriy; Tuxpan, José; Santos, Stewart

2011-01-01

We consider a problem of high-resolution array radar/SAR imaging formalized in terms of a nonlinear ill-posed inverse problem of nonparametric estimation of the power spatial spectrum pattern (SSP) of the random wavefield scattered from a remotely sensed scene observed through a kernel signal formation operator and contaminated with random Gaussian noise. First, the Sobolev-type solution space is constructed to specify the class of consistent kernel SSP estimators with the reproducing kernel structures adapted to the metrics in such the solution space. Next, the “model-free” variational analysis (VA)-based image enhancement approach and the “model-based” descriptive experiment design (DEED) regularization paradigm are unified into a new dynamic experiment design (DYED) regularization framework. Application of the proposed DYED framework to the adaptive array radar/SAR imaging problem leads to a class of two-level (DEED-VA) regularized SSP reconstruction techniques that aggregate the kernel adaptive anisotropic windowing with the projections onto convex sets to enforce the consistency and robustness of the overall iterative SSP estimators. We also show how the proposed DYED regularization method may be considered as a generalization of the MVDR, APES and other high-resolution nonparametric adaptive radar sensing techniques. A family of the DYED-related algorithms is constructed and their effectiveness is finally illustrated via numerical simulations. PMID:22163859

A slow-adapting microfluidic-based tactile sensor

NASA Astrophysics Data System (ADS)

Tseng, W.-Y.; Fisher, J. S.; Prieto, J. L.; Rinaldi, K.; Alapati, G.; Lee, A. P.

2009-08-01

We present a microfluidic-based tactile sensor mimicking the human slow-adapting mechanoreceptor such as Merkel's disc. The sensor is composed of a polyimide (PI)/polydimethylsiloxane (PDMS) multilayer structure. The device uses a hemispherical reservoir filled with electrolyte solution in the PDMS layer, a microchannel in the PI layer and a pair of sensing electrodes below the microchannel as the force transducer. The tactile signal is detected as the impedance change resulting predominantly from the resistance variance due to the electrodes coverage by the 1M NaCl solution and is measured across the electrode pair. The sensor response is linear and the working range is shown to be in the range of 0-1.8 N. The characterization results also demonstrate the sensing of various levels of forces and its long-term signal stability.

Wavefront sensing and control aspects in a high energy laser optical train

NASA Astrophysics Data System (ADS)

Bartosewcz, M.; Bareket, N.

1981-01-01

In this paper we review the major elements of a HEL (high energy laser) wavefront sensing and control system with particular emphasis on experimental demonstrations and hardware components developed at Lockheed Missiles & Space Company, Inc. The review concentrates on three important elements of wavefront control: wavefront sampling, wavefront sensing and active mirrors. Methods of wavefront sampling by diffraction gratings are described. Some new developments in wavefront sensing are explored. Hardware development efforts of fast steering mirrors and edge controlled deformable mirrors are described.

Simulation Experiments with Goal-Seeking Adaptive Elements.

DTIC Science & Technology

1984-02-01

when it comes to cognition and particularly bad when it comes to remote sensing, goal seeking, adaptation and decision making, where brains excel. In...Erlbaum 1981, 161-187 Hinton, G. E., & Sejnowski, T. J. Analyzing Cooperative Computation. Proceedings of the Fifth Annual Conference of the Cognitive ...Algorithms and Applications. Springer-Verlag, 1981. Lenat, D. B., Hayes-Roth, F., Klahr, P. Cognitive economy. Stanford Heuristic Program- ming Project HPP

Biology-Inspired Autonomous Control

DTIC Science & Technology

2011-08-31

from load sensing in a turbulent flow field with high levels of plant uncertainty and optical feedback latency. The results of this paper suggest... Mimicry of biological systems, in the form of precise mathematical or physical dynamical modeling, is yielding impressive insight into the underlying...processing and plants , the aerospace industry has been slow to accept adaptive control. In the past decade however, newer methods for design of adaptive

What Factors Promote Student Resilience on a Level 1 Distance Learning Module?

ERIC Educational Resources Information Center

Simons, Joan; Beaumont, Kythe; Holland, Lesley

2018-01-01

Resilience is understood to be the ability to adapt positively in the face of adversity. In relation to new students on a distance learning module, this can mean how they adapt and make sense of the demands of their chosen study to enable them to persist in their studies. This article reports a small-scale study involving semi-structured telephone…

Task directed sensing

NASA Technical Reports Server (NTRS)

Firby, R. James

1990-01-01

High-level robot control research must confront the limitations imposed by real sensors if robots are to be controlled effectively in the real world. In particular, sensor limitations make it impossible to maintain a complete, detailed world model of the situation surrounding the robot. To address the problems involved in planning with the resulting incomplete and uncertain world models, traditional robot control architectures must be altered significantly. Task-directed sensing and control is suggested as a way of coping with world model limitations by focusing sensing and analysis resources on only those parts of the world relevant to the robot's active goals. The RAP adaptive execution system is used as an example of a control architecture designed to deploy sensing resources in this way to accomplish both action and knowledge goals.

Piezoelectric film load cell robot collision detector

DOEpatents

Lembke, J.R.

1988-03-15

A piezoelectric load cell which can be utilized for detecting collisions and obstruction of a robot arm end effector includes a force sensing element of metallized polyvinylidene fluoride (PVDF) film. The piezoelectric film sensing element and a resilient support pad are clamped in compression between upper and lower plates. The lower plate has a central recess in its upper face for supporting the support pad and sensing element, while the upper plate has a corresponding central projection formed on its lower face for bearing on the sensing element and support pad. The upper and lower plates are dowelled together for concentric alignment and screwed together. The upper and lower plates are also adapted for mounting between the robot arm wrist and end effector. 3 figs.

Piezoelectric film load cell robot collision detector

DOEpatents

Lembke, John R.

1989-04-18

A piezoelectric load cell which can be utilized for detecting collisions and obstruction of a robot arm end effector includes a force sensing element of metallized polyvinylidene fluoride (PVDF) film. The piezoelectric film sensing element and a resilient support pad are clamped in compression between upper and lower plates. The lower plate has a central recess in its upper face for supporting the support pad and sensing element, while the upper plate has a corresponding central projection formed on its lower face for bearing on the sensing element and support pad. The upper and lower plates are dowelled together for concentric alignment and screwed together. The upper and lower plates are also adapted for mounting between the robot arm wrist and end effector.

Piezoelectric film load cell robot collision detector

DOEpatents

Lembke, J.R.

1989-04-18

A piezoelectric load cell which can be utilized for detecting collisions and obstruction of a robot arm end effector includes a force sensing element of metallized polyvinylidene fluoride (PVDF) film. The piezoelectric film sensing element and a resilient support pad are clamped in compression between upper and lower plates. The lower plate has a central recess in its upper face for supporting the support pad and sensing element, while the upper plate has a corresponding central projection formed on its lower face for bearing on the sensing element and support pad. The upper and lower plates are doweled together for concentric alignment and screwed together. The upper and lower plates are also adapted for mounting between the robot arm wrist and end effector. 3 figs.

To what extent can theory account for the findings of road safety evaluation studies?

PubMed

Elvik, Rune

2004-09-01

This paper proposes a conceptual framework that can be used to assess to what extent the findings of road safety evaluation research make sense from a theoretical point of view. The effects of road safety measures are modelled as passing through two causal chains. One of these, termed the engineering effect, refers to the intended effects of a road safety measure on a set of risk factors related to accident occurrence or injury severity. The engineering effect of road safety measures is modelled in terms of nine basic risk factors, one or more of which any road safety measure needs to influence in order to have the intended effect on accidents or injuries. The other causal chain producing the effects of road safety measures is termed the behavioural effect, and refers to road user behavioural adaptations to road safety measures. The behavioural effect is related to the engineering effect, in the sense that certain properties of the engineering effect of a road safety measure influence the likelihood that behavioural adaptation will occur. The behavioural effect of a road safety measure is modelled in terms of six factors that influence the likelihood that behavioural adaptation will occur. The nine basic risk factors representing the engineering effect of a road safety measure, and the six factors influencing the likelihood of behavioural adaptation can be used as checklists in assessing whether or not the findings of road safety evaluation studies make sense from a theoretical point of view. At the current state of knowledge, a more stringent evaluation of the extent to which theory can explain the findings of road safety evaluation studies is, in most cases, not possible. Copyright 2003 Elsevier Ltd.

Differentially Private Distributed Sensing

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

Fink, Glenn A.

The growth of the Internet of Things (IoT) creates the possibility of decentralized systems of sensing and actuation, potentially on a global scale. IoT devices connected to cloud networks can offer Sensing and Actuation as a Service (SAaaS) enabling networks of sensors to grow to a global scale. But extremely large sensor networks can violate privacy, especially in the case where IoT devices are mobile and connected directly to the behaviors of people. The thesis of this paper is that by adapting differential privacy (adding statistically appropriate noise to query results) to groups of geographically distributed sensors privacy could bemore » maintained without ever sending all values up to a central curator and without compromising the overall accuracy of the data collected. This paper outlines such a scheme and performs an analysis of differential privacy techniques adapted to edge computing in a simulated sensor network where ground truth is known. The positive and negative outcomes of employing differential privacy in distributed networks of devices are discussed and a brief research agenda is presented.« less

STING-Dependent Cytosolic DNA Sensing Promotes Radiation-Induced Type I Interferon-Dependent Antitumor Immunity in Immunogenic Tumors.

PubMed

Deng, Liufu; Liang, Hua; Xu, Meng; Yang, Xuanming; Burnette, Byron; Arina, Ainhoa; Li, Xiao-Dong; Mauceri, Helena; Beckett, Michael; Darga, Thomas; Huang, Xiaona; Gajewski, Thomas F; Chen, Zhijian J; Fu, Yang-Xin; Weichselbaum, Ralph R

2014-11-20

Ionizing radiation-mediated tumor regression depends on type I interferon (IFN) and the adaptive immune response, but several pathways control I IFN induction. Here, we demonstrate that adaptor protein STING, but not MyD88, is required for type I IFN-dependent antitumor effects of radiation. In dendritic cells (DCs), STING was required for IFN-? induction in response to irradiated-tumor cells. The cytosolic DNA sensor cyclic GMP-AMP (cGAMP) synthase (cGAS) mediated sensing of irradiated-tumor cells in DCs. Moreover, STING was essential for radiation-induced adaptive immune responses, which relied on type I IFN signaling on DCs. Exogenous IFN-? treatment rescued the cross-priming by cGAS or STING-deficient DCs. Accordingly, activation of STING by a second messenger cGAMP administration enhanced antitumor immunity induced by radiation. Thus radiation-mediated antitumor immunity in immunogenic tumors requires a functional cytosolic DNA-sensing pathway and suggests that cGAMP treatment might provide a new strategy to improve radiotherapy. Copyright © 2014 Elsevier Inc. All rights reserved.

Rotation and scale invariant shape context registration for remote sensing images with background variations

NASA Astrophysics Data System (ADS)

Jiang, Jie; Zhang, Shumei; Cao, Shixiang

2015-01-01

Multitemporal remote sensing images generally suffer from background variations, which significantly disrupt traditional region feature and descriptor abstracts, especially between pre and postdisasters, making registration by local features unreliable. Because shapes hold relatively stable information, a rotation and scale invariant shape context based on multiscale edge features is proposed. A multiscale morphological operator is adapted to detect edges of shapes, and an equivalent difference of Gaussian scale space is built to detect local scale invariant feature points along the detected edges. Then, a rotation invariant shape context with improved distance discrimination serves as a feature descriptor. For a distance shape context, a self-adaptive threshold (SAT) distance division coordinate system is proposed, which improves the discriminative property of the feature descriptor in mid-long pixel distances from the central point while maintaining it in shorter ones. To achieve rotation invariance, the magnitude of Fourier transform in one-dimension is applied to calculate angle shape context. Finally, the residual error is evaluated after obtaining thin-plate spline transformation between reference and sensed images. Experimental results demonstrate the robustness, efficiency, and accuracy of this automatic algorithm.

Wearable sensors: modalities, challenges, and prospects.

PubMed

Heikenfeld, J; Jajack, A; Rogers, J; Gutruf, P; Tian, L; Pan, T; Li, R; Khine, M; Kim, J; Wang, J; Kim, J

2018-01-16

Wearable sensors have recently seen a large increase in both research and commercialization. However, success in wearable sensors has been a mix of both progress and setbacks. Most of commercial progress has been in smart adaptation of existing mechanical, electrical and optical methods of measuring the body. This adaptation has involved innovations in how to miniaturize sensing technologies, how to make them conformal and flexible, and in the development of companion software that increases the value of the measured data. However, chemical sensing modalities have experienced greater challenges in commercial adoption, especially for non-invasive chemical sensors. There have also been significant challenges in making significant fundamental improvements to existing mechanical, electrical, and optical sensing modalities, especially in improving their specificity of detection. Many of these challenges can be understood by appreciating the body's surface (skin) as more of an information barrier than as an information source. With a deeper understanding of the fundamental challenges faced for wearable sensors and of the state-of-the-art for wearable sensor technology, the roadmap becomes clearer for creating the next generation of innovations and breakthroughs.

Cultural dimensions of climate change impacts and adaptation

NASA Astrophysics Data System (ADS)

Adger, W. Neil; Barnett, Jon; Brown, Katrina; Marshall, Nadine; O'Brien, Karen

2013-02-01

Society's response to every dimension of global climate change is mediated by culture. We analyse new research across the social sciences to show that climate change threatens cultural dimensions of lives and livelihoods that include the material and lived aspects of culture, identity, community cohesion and sense of place. We find, furthermore, that there are important cultural dimensions to how societies respond and adapt to climate-related risks. We demonstrate how culture mediates changes in the environment and changes in societies, and we elucidate shortcomings in contemporary adaptation policy.

Clinical efficacy and safety of an implantable cardioverter-defibrillator lead with a floating atrial sensing dipole.

PubMed

Safak, Erdal; Schmitz, Dietmar; Konorza, Thomas; Wende, Christian; De Ros, Jose Olague; Schirdewan, Alexander

2013-08-01

The concept of a single-lead implantable cardioverter-defibrillator (ICD), with a floating dipole, has been proven safe and functional. The studied active-fixation, steroid-eluting lead (Linox(smart) S DX, BIOTRONIK SE & Co KG, Berlin, Germany) is one French thinner than its predecessor and coated with lubricious SilGlide to improve lead handling. A dedicated ICD device has a self-adaptive atrial input stage including a fourfold amplifier. The amplification, filtering, and adapted atrial input stage are located in the Lumax 540 VR-T DX (BIOTRONIK). The Linox(smart) S DX ICD lead delivers only the signal. The lead was evaluated during implantation; at predischarge; and 1-, 3-, and 6-month follow-up examinations. The primary endpoint (efficacy) was the rate of appropriate atrial sensing tests. The secondary endpoint (safety) was freedom from lead-related invasive reinterventions. Both safety and efficacy were expected to be significantly higher than 90%. The study enrolled 116 patients at 25 clinical sites. Skin-to-skin operation time was 52.4 ± 26.2 minutes. The investigators graded lead insertion as "easy" in 87% of patients. Mean P-wave amplitudes (preamplified) varied from 5.0 to 6.1 mV in different body positions. Both primary and secondary endpoints were met, as 93.8% (364/388; P = 0.005) of specific sensing tests indicated appropriate atrial sensing, and 94.8% (110/116; P = 0.048) of patients were free from reinterventions (lead dislodgement). Analysis of arrhythmia episodes stored in ICDs and elective 24-hour Holter electrocardiogram tests raised no concerns about lead functionality. The studied ICD lead with a floating atrial sensing dipole met the predefined safety expectation and demonstrated appropriate atrial sensing performance. ©2013, The Authors. Journal compilation ©2013 Wiley Periodicals, Inc.

Dictionary-learning-based reconstruction method for electron tomography.

PubMed

Liu, Baodong; Yu, Hengyong; Verbridge, Scott S; Sun, Lizhi; Wang, Ge

2014-01-01

Electron tomography usually suffers from so-called “missing wedge” artifacts caused by limited tilt angle range. An equally sloped tomography (EST) acquisition scheme (which should be called the linogram sampling scheme) was recently applied to achieve 2.4-angstrom resolution. On the other hand, a compressive sensing inspired reconstruction algorithm, known as adaptive dictionary based statistical iterative reconstruction (ADSIR), has been reported for X-ray computed tomography. In this paper, we evaluate the EST, ADSIR, and an ordered-subset simultaneous algebraic reconstruction technique (OS-SART), and compare the ES and equally angled (EA) data acquisition modes. Our results show that OS-SART is comparable to EST, and the ADSIR outperforms EST and OS-SART. Furthermore, the equally sloped projection data acquisition mode has no advantage over the conventional equally angled mode in this context.

Adaptation to Variance of Stimuli in Drosophila Larva Navigation

NASA Astrophysics Data System (ADS)

Wolk, Jason; Gepner, Ruben; Gershow, Marc

In order to respond to stimuli that vary over orders of magnitude while also being capable of sensing very small changes, neural systems must be capable of rapidly adapting to the variance of stimuli. We study this adaptation in Drosophila larvae responding to varying visual signals and optogenetically induced fictitious odors using an infrared illuminated arena and custom computer vision software. Larval navigational decisions (when to turn) are modeled as the output a linear-nonlinear Poisson process. The development of the nonlinear turn rate in response to changes in variance is tracked using an adaptive point process filter determining the rate of adaptation to different stimulus profiles. Supported by NIH Grant 1DP2EB022359 and NSF Grant PHY-1455015.

Mechano-adaptation of the stem cell nucleus

PubMed Central

Heo, Su-Jin; Cosgrove, Brian D.; Dai, Eric N.; Mauck, Robert L.

2018-01-01

ABSTRACT Exogenous mechanical forces are transmitted through the cell and to the nucleus, initiating mechanotransductive signaling cascades with profound effects on cellular function and stem cell fate. A growing body of evidence has shown that the force sensing and force-responsive elements of the nucleus adapt to these mechanotransductive events, tuning their response to future mechanical input. The mechanisms underlying this “mechano-adaptation” are only just beginning to be elucidated, and it remains poorly understood how these components act and adapt in tandem to drive stem cell differentiation. Here, we review the evidence on how the stem cell nucleus responds and adapts to physical forces, and provide a perspective on how this mechano-adaptation may function to drive and enforce stem cell differentiation. PMID:29099288

How virtual reality works: illusions of vision in "real" and virtual environments

NASA Astrophysics Data System (ADS)

Stark, Lawrence W.

1995-04-01

Visual illusions abound in normal vision--illusions of clarity and completeness, of continuity in time and space, of presence and vivacity--and are part and parcel of the visual world inwhich we live. These illusions are discussed in terms of the human visual system, with its high- resolution fovea, moved from point to point in the visual scene by rapid saccadic eye movements (EMs). This sampling of visual information is supplemented by a low-resolution, wide peripheral field of view, especially sensitive to motion. Cognitive-spatial models controlling perception, imagery, and 'seeing,' also control the EMs that shift the fovea in the Scanpath mode. These illusions provide for presence, the sense off being within an environment. They equally well lead to 'Telepresence,' the sense of being within a virtual display, especially if the operator is intensely interacting within an eye-hand and head-eye human-machine interface that provides for congruent visual and motor frames of reference. Interaction, immersion, and interest compel telepresence; intuitive functioning and engineered information flows can optimize human adaptation to the artificial new world of virtual reality, as virtual reality expands into entertainment, simulation, telerobotics, and scientific visualization and other professional work.

Adapting a Natura 2000 field guideline for a remote sensing-based assessment of heathland conservation status

NASA Astrophysics Data System (ADS)

Schmidt, Johannes; Fassnacht, Fabian Ewald; Neff, Christophe; Lausch, Angela; Kleinschmit, Birgit; Förster, Michael; Schmidtlein, Sebastian

2017-08-01

Remote sensing can be a valuable tool for supporting nature conservation monitoring systems. However, for many areas of conservation interest, there is still a considerable gap between field-based operational monitoring guidelines and the current remote sensing-based approaches. This hampers application in practice of the latter. Here, we propose a remote sensing approach for mapping the conservation status of Calluna-dominated Natura 2000 dwarf shrub habitats that is closely related to field mapping schemes. We transferred the evaluation criteria of the field guidelines to three related variables that can be captured by remote sensing: (1) coverage of the key species, (2) stand structural diversity, and (3) co-occurring species. Continuous information on these variables was obtained by regressing ground reference data from field surveys and UAV flights against airborne hyperspectral imagery. Merging the three resulting quality layers in an RGB representation allowed for illustrating the habitat quality in a continuous way. User-defined thresholds can be applied to this stack of quality layers to derive an overall assessment of habitat quality in terms of nature conservation, i.e. the conservation status. In our study, we found good accordance of the remotely sensed data with field-based information for the three variables key species, stand structural diversity and co-occurring vegetation (R2 of 0.79, 0.69, and 0.71, respectively) and it was possible to derive meaningful habitat quality maps. The conservation status could be derived with an accuracy of 65%. In interpreting these results it should be considered that the remote sensing based layers are independent estimates of habitat quality in their own right and not a mere replacement of the criteria used in the field guidelines. The approach is thought to be transferable to similar regions with minor adaptions. Our results refer to Calluna heathland which we consider a comparably easy target for remote sensing. Hence, the transfer of field guidelines to remote sensing indicators was rather successful in this case but needs further evaluation for other habitats.

Low-dose CT reconstruction via L1 dictionary learning regularization using iteratively reweighted least-squares.

PubMed

Zhang, Cheng; Zhang, Tao; Li, Ming; Peng, Chengtao; Liu, Zhaobang; Zheng, Jian

2016-06-18

In order to reduce the radiation dose of CT (computed tomography), compressed sensing theory has been a hot topic since it provides the possibility of a high quality recovery from the sparse sampling data. Recently, the algorithm based on DL (dictionary learning) was developed to deal with the sparse CT reconstruction problem. However, the existing DL algorithm focuses on the minimization problem with the L2-norm regularization term, which leads to reconstruction quality deteriorating while the sampling rate declines further. Therefore, it is essential to improve the DL method to meet the demand of more dose reduction. In this paper, we replaced the L2-norm regularization term with the L1-norm one. It is expected that the proposed L1-DL method could alleviate the over-smoothing effect of the L2-minimization and reserve more image details. The proposed algorithm solves the L1-minimization problem by a weighting strategy, solving the new weighted L2-minimization problem based on IRLS (iteratively reweighted least squares). Through the numerical simulation, the proposed algorithm is compared with the existing DL method (adaptive dictionary based statistical iterative reconstruction, ADSIR) and other two typical compressed sensing algorithms. It is revealed that the proposed algorithm is more accurate than the other algorithms especially when further reducing the sampling rate or increasing the noise. The proposed L1-DL algorithm can utilize more prior information of image sparsity than ADSIR. By transforming the L2-norm regularization term of ADSIR with the L1-norm one and solving the L1-minimization problem by IRLS strategy, L1-DL could reconstruct the image more exactly.

Implications of sampling design and sample size for national carbon accounting systems.

PubMed

Köhl, Michael; Lister, Andrew; Scott, Charles T; Baldauf, Thomas; Plugge, Daniel

2011-11-08

Countries willing to adopt a REDD regime need to establish a national Measurement, Reporting and Verification (MRV) system that provides information on forest carbon stocks and carbon stock changes. Due to the extensive areas covered by forests the information is generally obtained by sample based surveys. Most operational sampling approaches utilize a combination of earth-observation data and in-situ field assessments as data sources. We compared the cost-efficiency of four different sampling design alternatives (simple random sampling, regression estimators, stratified sampling, 2-phase sampling with regression estimators) that have been proposed in the scope of REDD. Three of the design alternatives provide for a combination of in-situ and earth-observation data. Under different settings of remote sensing coverage, cost per field plot, cost of remote sensing imagery, correlation between attributes quantified in remote sensing and field data, as well as population variability and the percent standard error over total survey cost was calculated. The cost-efficiency of forest carbon stock assessments is driven by the sampling design chosen. Our results indicate that the cost of remote sensing imagery is decisive for the cost-efficiency of a sampling design. The variability of the sample population impairs cost-efficiency, but does not reverse the pattern of cost-efficiency of the individual design alternatives. Our results clearly indicate that it is important to consider cost-efficiency in the development of forest carbon stock assessments and the selection of remote sensing techniques. The development of MRV-systems for REDD need to be based on a sound optimization process that compares different data sources and sampling designs with respect to their cost-efficiency. This helps to reduce the uncertainties related with the quantification of carbon stocks and to increase the financial benefits from adopting a REDD regime.

Quorum-sensing in yeast and its potential in wine making.

PubMed

Avbelj, Martina; Zupan, Jure; Raspor, Peter

2016-09-01

This mini-review synthesises the present knowledge of microbial quorum-sensing, with a specific focus on quorum-sensing in yeast, and especially in wine yeast. In vine and wine ecosystems, yeast co-interact with a large variety of microorganisms, thereby affecting the fermentation process and, consequently, the flavour of the wine. The precise connections between microbial interactions and quorum-sensing remain unclear, but we describe here how and when some species start to produce quorum-sensing molecules to synchronously adapt their collective behaviour to new conditions. In Saccharomyces cerevisiae, the quorum-sensing molecules were identified as 2-phenylethanol and tryptophol. However, it was recently shown that also a quorum-sensing molecule formerly identified only in Candida albicans, tyrosol, appears to be regulated in S. cerevisiae according to cell density. This review describes the methods for detection and quantification of those quorum-sensing molecules, their underlying mechanisms of action, and their genetic background. It also examines the external stimuli that evoke the quorum-sensing mechanism in the wine-processing environment. The review closes with insight into the biotechnological applications that are already making use of the advantages of quorum-sensing systems and indicates the important questions that still need to be addressed in future research into quorum-sensing.

Complementary high performance sensing of gases and liquids using silver nanotube

NASA Astrophysics Data System (ADS)

Isro, Suhandoko D.; Iskandar, Alexander A.; Tjia, May-On

2017-11-01

A study on refractive index sensing using a silver nanotube is carried out to investigate the relative advantages of sensing gaseous and liquid samples outside the tube (outer sensing) and inside the core (inner sensing). The geometrical and material parameters of the nanotube are varied to explore the favorable sensing performances covering the range of refractive indices between 1.1 and 1.5. It is shown that the performances at the three sensing points considered are consistently improved with decreased shell thickness and core radius in both sensing modes. While the performance is also monotonously and drastically enhanced with decreased counter permittivity in inner sensing, the similarly large variations in the outer sensing mode are less than strictly consistent. The study further shows that the most favorable FOM values are attained by both sensing modes with 2.5 nm Ag shell thickness and 27.5 nm core radius of the nanotube, whereas the most favorable counter permittivities are different for the two modes. Remarkably, the trend of increasing FOM for samples of lower refractive indices in outer sensing is entirely reversed in inner sensing with roughly the same level of performances. Thus, the core/shell structure of the silver nanotube offers the complementary high performance sensing of gases and liquids using the two sensing modes with appropriately chosen system parameters.

The micron- to kilometer-scale Moon: linking samples to orbital observations, Apollo to LRO

NASA Astrophysics Data System (ADS)

Crites, S.; Lucey, P. G.; Taylor, J.; Martel, L.; Sun, L.; Honniball, C.; Lemelin, M.

2017-12-01

The Apollo missions have shaped the field of lunar science and our understanding of the Moon, from global-scale revelations like the magma ocean hypothesis, to providing ground truth for compositional remote sensing and absolute ages to anchor cratering chronologies. While lunar meteorite samples can provide a global- to regional-level view of the Moon, samples returned from known locations are needed to directly link orbital-scale observations with laboratory measurements-a link that can be brought to full fruition with today's extremely high spatial resolution observations from Lunar Reconnaissance Orbiter and other recent missions. Korotev et al. (2005) described a scenario of the Moon without Apollo to speculate about our understanding of the Moon if our data were confined to lunar meteorites and remote sensing. I will review some of the major points discussed by Korotev et al. (2005), and focus on some of the ways in which spectroscopic remote sensing in particular has benefited from the Apollo samples. For example, could the causes and effects of lunar-style space weathering have been unraveled without the Apollo samples? What would be the limitations on remote sensing compositional measurements that rely on Apollo samples for calibration and validation? And what new opportunities to bring together orbital and sample analyses now exist, in light of today's high spatial and spectral resolution remote sensing datasets?

A Surrogate-based Adaptive Sampling Approach for History Matching and Uncertainty Quantification

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

Li, Weixuan; Zhang, Dongxiao; Lin, Guang

A critical procedure in reservoir simulations is history matching (or data assimilation in a broader sense), which calibrates model parameters such that the simulation results are consistent with field measurements, and hence improves the credibility of the predictions given by the simulations. Often there exist non-unique combinations of parameter values that all yield the simulation results matching the measurements. For such ill-posed history matching problems, Bayesian theorem provides a theoretical foundation to represent different solutions and to quantify the uncertainty with the posterior PDF. Lacking an analytical solution in most situations, the posterior PDF may be characterized with a samplemore » of realizations, each representing a possible scenario. A novel sampling algorithm is presented here for the Bayesian solutions to history matching problems. We aim to deal with two commonly encountered issues: 1) as a result of the nonlinear input-output relationship in a reservoir model, the posterior distribution could be in a complex form, such as multimodal, which violates the Gaussian assumption required by most of the commonly used data assimilation approaches; 2) a typical sampling method requires intensive model evaluations and hence may cause unaffordable computational cost. In the developed algorithm, we use a Gaussian mixture model as the proposal distribution in the sampling process, which is simple but also flexible to approximate non-Gaussian distributions and is particularly efficient when the posterior is multimodal. Also, a Gaussian process is utilized as a surrogate model to speed up the sampling process. Furthermore, an iterative scheme of adaptive surrogate refinement and re-sampling ensures sampling accuracy while keeping the computational cost at a minimum level. The developed approach is demonstrated with an illustrative example and shows its capability in handling the above-mentioned issues. Multimodal posterior of the history matching problem is captured and are used to give a reliable production prediction with uncertainty quantification. The new algorithm reveals a great improvement in terms of computational efficiency comparing previously studied approaches for the sample problem.« less

Downhole steam quality measurement

DOEpatents

Lee, David O.; Montoya, Paul C.; Muir, James F.; Wayland, Jr., J. Robert

1987-01-01

An empirical method for the remote sensing of steam quality that can be easily adapted to downhole steam quality measurements by measuring the electrical properties of two-phase flow across electrode grids at low frequencies.

UAV Cooperation Architectures for Persistent Sensing

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

Roberts, R S; Kent, C A; Jones, E D

2003-03-20

With the number of small, inexpensive Unmanned Air Vehicles (UAVs) increasing, it is feasible to build multi-UAV sensing networks. In particular, by using UAVs in conjunction with unattended ground sensors, a degree of persistent sensing can be achieved. With proper UAV cooperation algorithms, sensing is maintained even though exceptional events, e.g., the loss of a UAV, have occurred. In this paper a cooperation technique that allows multiple UAVs to perform coordinated, persistent sensing with unattended ground sensors over a wide area is described. The technique automatically adapts the UAV paths so that on the average, the amount of time thatmore » any sensor has to wait for a UAV revisit is minimized. We also describe the Simulation, Tactical Operations and Mission Planning (STOMP) software architecture. This architecture is designed to help simulate and operate distributed sensor networks where multiple UAVs are used to collect data.« less

Normalized burn ratios link fire severity with patterns of avian occurrence

USGS Publications Warehouse

Rose, Eli T.; Simons, Theodore R.; Klein, Rob; McKerrow, Alexa

2016-01-01

ContextRemotely sensed differenced normalized burn ratios (DNBR) provide an index of fire severity across the footprint of a fire. We asked whether this index was useful for explaining patterns of bird occurrence within fire adapted xeric pine-oak forests of the southern Appalachian Mountains.ObjectivesWe evaluated the use of DNBR indices for linking ecosystem process with patterns of bird occurrence. We compared field-based and remotely sensed fire severity indices and used each to develop occupancy models for six bird species to identify patterns of bird occurrence following fire.MethodsWe identified and sampled 228 points within fires that recently burned within Great Smoky Mountains National Park. We performed avian point counts and field-assessed fire severity at each bird census point. We also used Landsat™ imagery acquired before and after each fire to quantify fire severity using DNBR. We used non-parametric methods to quantify agreement between fire severity indices, and evaluated single season occupancy models incorporating fire severity summarized at different spatial scales.ResultsAgreement between field-derived and remotely sensed measures of fire severity was influenced by vegetation type. Although occurrence models using field-derived indices of fire severity outperformed those using DNBR, summarizing DNBR at multiple spatial scales provided additional insights into patterns of occurrence associated with different sized patches of high severity fire.ConclusionsDNBR is useful for linking the effects of fire severity to patterns of bird occurrence, and informing how high severity fire shapes patterns of bird species occurrence on the landscape.

GOATS 2008: Autonomous, Adaptive Multistatic Acoustic Sensing

DTIC Science & Technology

2010-09-30

carried out jointly with the NATO Undersea Research Centre in the Tuscan archipelago July 26 – August 16, 2010. MIT operated the Unicorn AUV and...4 trail behavior with the physical Unicorn AUV, and is accidentally passing close the R/V Leonardo, fully autonomously changing its depth from...vehicles. The AUV Unicorn is performing an adaptive thermocline mapping mission, with the vehicle trail shown in green. Note the autonomous collision

Sensing marine biomolecules: smell, taste, and the evolutionary transition from aquatic to terrestrial life

PubMed Central

Mollo, Ernesto; Fontana, Angelo; Roussis, Vassilios; Polese, Gianluca; Amodeo, Pietro; Ghiselin, Michael T.

2014-01-01

The usual definition of smell and taste as distance and contact forms of chemoreception, respectively, has resulted in the belief that, during the shift from aquatic to terrestrial life, odorant receptors (ORs) were selected mainly to recognize airborne hydrophobic ligands, instead of the hydrophilic molecules involved in marine remote-sensing. This post-adaptive evolutionary scenario, however, neglects the fact that marine organisms 1) produce and detect a wide range of small hydrophobic and volatile molecules, especially terpenoids, and 2) contain genes coding for ORs that are able to bind those compounds. These apparent anomalies can be resolved by adopting an alternative, pre-adaptive scenario. Before becoming airborne on land, small molecules, almost insoluble in water, already played a key role in aquatic communication, but acting in “contact” forms of olfaction that did not require major molecular innovations to become effective at a distance in air. Rather, when air was “invaded” by volatile marine terpenoids, an expansion of the spatial range of olfaction was an incidental consequence rather than an adaptation. PMID:25360437

Leishmania Uses Mincle to Target an Inhibitory ITAM Signaling Pathway in Dendritic Cells that Dampens Adaptive Immunity to Infection.

PubMed

Iborra, Salvador; Martínez-López, María; Cueto, Francisco J; Conde-Garrosa, Ruth; Del Fresno, Carlos; Izquierdo, Helena M; Abram, Clare L; Mori, Daiki; Campos-Martín, Yolanda; Reguera, Rosa María; Kemp, Benjamin; Yamasaki, Sho; Robinson, Matthew J; Soto, Manuel; Lowell, Clifford A; Sancho, David

2016-10-18

C-type lectin receptors sense a diversity of endogenous and exogenous ligands that may trigger differential responses. Here, we have found that human and mouse Mincle bind to a ligand released by Leishmania, a eukaryote parasite that evades an effective immune response. Mincle-deficient mice had milder dermal pathology and a tenth of the parasite burden compared to wild-type mice after Leishmania major intradermal ear infection. Mincle deficiency enhanced adaptive immunity against the parasite, correlating with increased activation, migration, and priming by Mincle-deficient dendritic cells (DCs). Leishmania triggered a Mincle-dependent inhibitory axis characterized by SHP1 coupling to the FcRγ chain. Selective loss of SHP1 in CD11c + cells phenocopies enhanced adaptive immunity to Leishmania. In conclusion, Leishmania shifts Mincle to an inhibitory ITAM (ITAMi) configuration that impairs DC activation. Thus, ITAMi can be exploited for immune evasion by a pathogen and may represent a paradigm for ITAM-coupled receptors sensing self and non-self. Copyright © 2016 Elsevier Inc. All rights reserved.

Splicing-related genes are alternatively spliced upon changes in ambient temperatures in plants

PubMed Central

Bucher, Johan; Lammers, Michiel; Busscher-Lange, Jacqueline; Bonnema, Guusje; Rodenburg, Nicole; Proveniers, Marcel C. G.; Angenent, Gerco C.

2017-01-01

Plants adjust their development and architecture to small variations in ambient temperature. In a time in which temperatures are rising world-wide, the mechanism by which plants are able to sense temperature fluctuations and adapt to it, is becoming of special interest. By performing RNA-sequencing on two Arabidopsis accession and one Brassica species exposed to temperature alterations, we showed that alternative splicing is an important mechanism in ambient temperature sensing and adaptation. We found that amongst the differentially alternatively spliced genes, splicing related genes are enriched, suggesting that the splicing machinery itself is targeted for alternative splicing when temperature changes. Moreover, we showed that many different components of the splicing machinery are targeted for ambient temperature regulated alternative splicing. Mutant analysis of a splicing related gene that was differentially spliced in two of the genotypes showed an altered flowering time response to different temperatures. We propose a two-step mechanism where temperature directly influences alternative splicing of the splicing machinery genes, followed by a second step where the altered splicing machinery affects splicing of downstream genes involved in the adaptation to altered temperatures. PMID:28257507

A Comparison of Alternative Distributed Dynamic Cluster Formation Techniques for Industrial Wireless Sensor Networks.

PubMed

Gholami, Mohammad; Brennan, Robert W

2016-01-06

In this paper, we investigate alternative distributed clustering techniques for wireless sensor node tracking in an industrial environment. The research builds on extant work on wireless sensor node clustering by reporting on: (1) the development of a novel distributed management approach for tracking mobile nodes in an industrial wireless sensor network; and (2) an objective comparison of alternative cluster management approaches for wireless sensor networks. To perform this comparison, we focus on two main clustering approaches proposed in the literature: pre-defined clusters and ad hoc clusters. These approaches are compared in the context of their reconfigurability: more specifically, we investigate the trade-off between the cost and the effectiveness of competing strategies aimed at adapting to changes in the sensing environment. To support this work, we introduce three new metrics: a cost/efficiency measure, a performance measure, and a resource consumption measure. The results of our experiments show that ad hoc clusters adapt more readily to changes in the sensing environment, but this higher level of adaptability is at the cost of overall efficiency.

A Comparison of Alternative Distributed Dynamic Cluster Formation Techniques for Industrial Wireless Sensor Networks

PubMed Central

Gholami, Mohammad; Brennan, Robert W.

2016-01-01

In this paper, we investigate alternative distributed clustering techniques for wireless sensor node tracking in an industrial environment. The research builds on extant work on wireless sensor node clustering by reporting on: (1) the development of a novel distributed management approach for tracking mobile nodes in an industrial wireless sensor network; and (2) an objective comparison of alternative cluster management approaches for wireless sensor networks. To perform this comparison, we focus on two main clustering approaches proposed in the literature: pre-defined clusters and ad hoc clusters. These approaches are compared in the context of their reconfigurability: more specifically, we investigate the trade-off between the cost and the effectiveness of competing strategies aimed at adapting to changes in the sensing environment. To support this work, we introduce three new metrics: a cost/efficiency measure, a performance measure, and a resource consumption measure. The results of our experiments show that ad hoc clusters adapt more readily to changes in the sensing environment, but this higher level of adaptability is at the cost of overall efficiency. PMID:26751447

Performance assessment of MEMS adaptive optics in tactical airborne systems

NASA Astrophysics Data System (ADS)

Tyson, Robert K.

1999-09-01

Tactical airborne electro-optical systems are severely constrained by weight, volume, power, and cost. Micro- electrical-mechanical adaptive optics provide a solution that addresses the engineering realities without compromising spatial and temporal compensation requirements. Through modeling and analysis, we determined that substantial benefits could be gained for laser designators, ladar, countermeasures, and missile seekers. The developments potential exists for improving seeker imagery resolution 20 percent, extending countermeasures keep-out range by a factor of 5, doubling the range for ladar detection and identification, and compensating for supersonic and hypersonic aircraft boundary layers. Innovative concepts are required for atmospheric pat hand boundary layer compensation. We have developed design that perform these tasks using high speed scene-based wavefront sensing, IR aerosol laser guide stars, and extended-object wavefront beacons. We have developed a number of adaptive optics system configurations that met the spatial resolution requirements and we have determined that sensing and signal processing requirements can be met. With the help of micromachined deformable mirrors and sensor, we will be able to integrate the systems into existing airborne pods and missiles as well as next generation electro-optical systems.

Preliminary result of the solar multi-conjugate adaptive optics for 1m new vacuum solar telescope

NASA Astrophysics Data System (ADS)

Zhang, Lanqiang; Kong, Lin; Bao, Hua; Zhu, Lei; Rao, Xuejun; Rao, Changhui

2016-07-01

Solar observation with high resolution in large field of view (FoV) is required for some solar active regions with the typical sizes of 1' to 3'. Conventional adaptive optics (AO) could not satisfy this demand because of the atmospheric anisoplanatism. Through compensating the turbulence in different heights, multi-conjugate adaptive optics (MCAO) has been proved to obtain a larger corrected FoV. A MCAO experimental system including a conventional 151-element AO system and a 37-element MCAO part is being developed. The MCAO part contains a 37-element deformable mirror conjugated into the 2km to 5km height and a multi-direction Shack-Hartmann wavefront sensor (MD-SHWFS) with 7×7 subaperture array and 60 arcsec FoV, the frame rate of the MD-SHWFS is up to 840Hz. Three-dimensional (3-D) wavefront sensing utilizing atmospheric tomography had been validated by solar observation. Based on these results, a ground layer adaptive optics (GLAO) experimental system including a 151-element deformable mirror and the MD-SHWFS has been built at the 1m New Vacuum Solar Telescope (NVST). In this paper, the MCAO experimental system will be introduced. The preliminary experimental results of three-dimensional wavefront sensing and GLAO on the NVST of Full-shine Lake Solar Observatory are presented.

Framework for measuring adaptive knowledge-rich systems performance.

PubMed

Bushko, Renata G

2005-01-01

The universe is non repeatable in nature--most of events cannot be prestated and do not repeat themselves. The only way to create systems that are truly useful is to make them adaptive (able to reason by analogy and learn) and rich in knowledge (including common sense knowledge). Adaptive and knowledge-rich health management could get us closer to errorless health care where small incremental adjustments happen all the time preventing occurrence of an error. In the era of adaptive systems we need to have a way to evaluate their performance. Are they truly adaptive? How adaptive are they? Are they accurate enough? Are they fast enough? Are they cost effective? This chapter presents general framework for measuring adaptive knowledge-rich systems' performance and includes among others definitions of adaptiveness factor, britt (a unit of brittleness) and uso-quant (unit of usefulness of a piece of knowledge). Measuring adaptive knowledge-rich systems performance is one of the most important research areas that can have a big pay-off in healthcare now and in the future.

Remote sensing and the optical properties of the narrow cylindrical leaves of Juncus roemerianus

USGS Publications Warehouse

Ramsey, Elijah W.; Rangoonwala, A.

2004-01-01

To develop a more complete foundation for remote sensing of the marsh grass Juncus roemerianus, we measured the optical properties of its cylindrical leaves at sites of different canopy height, biomass composition and amount, and connectivity to ocean flushing. To measure the leaf optical properties, we adapted a technique used for conifer needles. After establishing the reliability and limits of the adapted technique to the wider J.roemerianus leaves, mean transmittance and reflectance spectra were compared to associated leaf diameters from two dates in 1999 and 2002 and at each site. Transmittance was inversely related to leaf diameter. Mean transmittance and reflectance generated from reoccupation of many field sites in 2002 indicated little or no difference in transmittance between years, a slight reflectance difference in the visible (<2%) and a slightly higher reflectance difference in the near infrared (NIR) (<4%). Site comparison indicated limited ability to separate leaf transmittance but not reflectance by marsh type (e.g., low, medium, high) or biomass. Excluding one outlier, we found leaf transmittances could be adequately represented as 1% ?? 0.2% in the visible and 9% ?? 1% in the NIR and leaf reflectances represented from 14% to 16% in the visible and 71% to 75% in the NIR (the reflectance ranges represent 1999 and 2002 means). Reflectance and transmittance spectra associated with the dead J. roemerianus leaves displayed a spectrally flat increase from the visible to the NIR wavelengths. In total, we documented the atypical optical properties of the cylindrical J. roemerianus leaves and showed that to a first approximation, single means could represent leaf transmittance and visible leaf reflectance across all marsh zones and, after accounting for sample standardization, possibly the NIR reflectance as well.

Planetary Evolution, Habitability and Life

NASA Astrophysics Data System (ADS)

Tilman, Spohn; Breuer, Doris; de Vera, Jean-Pierre; Jaumann, Ralf; Kuehrt, Ekkehard; Möhlmann, Diedrich; Rauer, Heike; Richter, Lutz

A Helmholtz Alliance has been established to study the interactions between life and the evo-lution of planets. The approach goes beyond current studies in Earth-System Sciences by including the entire planet from the atmosphere to the deep interior, going beyond Earth to include other Earth-like planets such as Mars and Venus and satellites in the solar system where ecosystems may exist underneath thick ice shells,considering other solar systems. The approach includes studies of the importance of plate tectonics and other tectonic regimes such as single plate tectonics for the development and for sustaining life and asks the question: If life can adapt to a planet, can a planet adapt to life? Can life be seen as a geological process and if so, can life shape the conditions on a planet such that life can flourish? The vision goes beyond the solar system by including the challenges that life would face in other solar systems. The Alliance uses theoretical modelling of feedback cycles and coupled planetary atmosphere and interior processes. These models are based on the results of remote sensing of planetary surfaces and atmospheres, laboratory studies on (meteorite) samples from other planets and on studies of life under extreme conditions. The Alliance uses its unique capabilities in remote sensing and in-situ exploration to prepare for empirical studies of the parameters affecting habitability. The Alliance aims to establish a network infrastructure in Germany to enable the most ad-vanced research in planetary evolution studies by including life as a planetary process. Finding extraterrestrial life is a task of fundamental importance to mankind, and its fulfilment will be philosophically profound. Evaluating the interactions between planetary evolution and life will help to put the evolution of our home planet (even anthropogenic effects) into perspective.

A small system--high-resolution study of metabolic adaptation in the central metabolic pathway to temperate climates in Drosophila melanogaster.

PubMed

Lavington, Erik; Cogni, Rodrigo; Kuczynski, Caitlin; Koury, Spencer; Behrman, Emily L; O'Brien, Katherine R; Schmidt, Paul S; Eanes, Walter F

2014-08-01

In this article, we couple the geographic variation in 127 single-nucleotide polymorphism (SNP) frequencies in genes of 46 enzymes of central metabolism with their associated cis-expression variation to predict latitudinal or climatic-driven gene expression changes in the metabolic architecture of Drosophila melanogaster. Forty-two percent of the SNPs in 65% of the genes show statistically significant clines in frequency with latitude across the 20 local population samples collected from southern Florida to Ontario. A number of SNPs in the screened genes are also associated with significant expression variation within the Raleigh population from North Carolina. A principal component analysis of the full variance-covariance matrix of latitudinal changes in SNP-associated standardized gene expression allows us to identify those major genes in the pathway and its associated branches that are likely targets of natural selection. When embedded in a central metabolic context, we show that these apparent targets are concentrated in the genes of the upper glycolytic pathway and pentose shunt, those controlling glycerol shuttle activity, and finally those enzymes associated with the utilization of glutamate and pyruvate. These metabolites possess high connectivity and thus may be the points where flux balance can be best shifted. We also propose that these points are conserved points associated with coupling energy homeostasis and energy sensing in mammals. We speculate that the modulation of gene expression at specific points in central metabolism that are associated with shifting flux balance or possibly energy-state sensing plays a role in adaptation to climatic variation. © The Author 2014. Published by Oxford University Press on behalf of the Society for Molecular Biology and Evolution. All rights reserved. For permissions, please e-mail: journals.permissions@oup.com.

Thirty years of use and improvement of remote sensing, applied to epidemiology: from early promises to lasting frustration.

PubMed

Herbreteau, Vincent; Salem, Gérard; Souris, Marc; Hugot, Jean-Pierre; Gonzalez, Jean-Paul

2007-06-01

Remote sensing, referring to the remote study of objects, was originally developed for Earth observation, through the use of sensors on board planes or satellites. Improvements in the use and accessibility of multi-temporal satellite-derived environmental data have, for 30 years, contributed to a growing use in epidemiology. Despite the potential of remote-sensed images and processing techniques for a better knowledge of disease dynamics, an exhaustive analysis of the bibliography shows a generalized use of pre-processed spatial data and low-cost images, resulting in a limited adaptability when addressing biological questions.

Flexible Framework for Capacitive Sensing

NASA Technical Reports Server (NTRS)

Woodard, Stanley E. (Inventor); Taylor, Bryant D. (Inventor)

2006-01-01

A flexible framework supports electrically-conductive elements in a capacitive sensing arrangement. Identical frames are arranged end-to-end with adjacent frames being capable of rotational movement there between. Each frame has first and second passages extending therethrough and parallel to one another. Each of the first and second passages is adapted to receive an electrically-conductive element therethrough. Each frame further has a hollowed-out portion for the passage of a fluent material therethrough. The hollowed-out portion is sized and shaped to provide for capacitive sensing along a defined region between the electrically-conductive element in the first passage and the electrically-conductive element in the second passage.

Remote sensing of vegetation pattern and condition to monitor changes in everglades biogeochemistry

USGS Publications Warehouse

Jones, J.W.

2011-01-01

Ground-based studies of biogeochemistry and vegetation patterning yield process understanding, but the amount of information gained by ground-based studies can be greatly enhanced by efficient, synoptic, and temporally resolute monitoring afforded by remote sensing. The variety of presently available Everglades vegetation maps reflects both the wide range of application requirements and the need to balance cost and capability. More effort needs to be applied to documenting and understanding vegetation distribution and condition as indicators of biogeochemistry and contamination. Ground-based and remote sensing studies should be modified to maximize their synergy and utility for adaptive management. Copyright ?? 2011 Taylor & Francis Group, LLC.

An adaptive two-stage sequential design for sampling rare and clustered populations

USGS Publications Warehouse

Brown, J.A.; Salehi, M.M.; Moradi, M.; Bell, G.; Smith, D.R.

2008-01-01

How to design an efficient large-area survey continues to be an interesting question for ecologists. In sampling large areas, as is common in environmental studies, adaptive sampling can be efficient because it ensures survey effort is targeted to subareas of high interest. In two-stage sampling, higher density primary sample units are usually of more interest than lower density primary units when populations are rare and clustered. Two-stage sequential sampling has been suggested as a method for allocating second stage sample effort among primary units. Here, we suggest a modification: adaptive two-stage sequential sampling. In this method, the adaptive part of the allocation process means the design is more flexible in how much extra effort can be directed to higher-abundance primary units. We discuss how best to design an adaptive two-stage sequential sample. ?? 2008 The Society of Population Ecology and Springer.

Speckle-metric-optimization-based adaptive optics for laser beam projection and coherent beam combining.

PubMed

Vorontsov, Mikhail; Weyrauch, Thomas; Lachinova, Svetlana; Gatz, Micah; Carhart, Gary

2012-07-15

Maximization of a projected laser beam's power density at a remotely located extended object (speckle target) can be achieved by using an adaptive optics (AO) technique based on sensing and optimization of the target-return speckle field's statistical characteristics, referred to here as speckle metrics (SM). SM AO was demonstrated in a target-in-the-loop coherent beam combining experiment using a bistatic laser beam projection system composed of a coherent fiber-array transmitter and a power-in-the-bucket receiver. SM sensing utilized a 50 MHz rate dithering of the projected beam that provided a stair-mode approximation of the outgoing combined beam's wavefront tip and tilt with subaperture piston phases. Fiber-integrated phase shifters were used for both the dithering and SM optimization with stochastic parallel gradient descent control.

Adaptive multisensor fusion for planetary exploration rovers

NASA Technical Reports Server (NTRS)

Collin, Marie-France; Kumar, Krishen; Pampagnin, Luc-Henri

1992-01-01

The purpose of the adaptive multisensor fusion system currently being designed at NASA/Johnson Space Center is to provide a robotic rover with assured vision and safe navigation capabilities during robotic missions on planetary surfaces. Our approach consists of using multispectral sensing devices ranging from visible to microwave wavelengths to fulfill the needs of perception for space robotics. Based on the illumination conditions and the sensors capabilities knowledge, the designed perception system should automatically select the best subset of sensors and their sensing modalities that will allow the perception and interpretation of the environment. Then, based on reflectance and emittance theoretical models, the sensor data are fused to extract the physical and geometrical surface properties of the environment surface slope, dielectric constant, temperature and roughness. The theoretical concepts, the design and first results of the multisensor perception system are presented.

Non-visual crypsis: a review of the empirical evidence for camouflage to senses other than vision.

PubMed

Ruxton, Graeme D

2009-02-27

I review the evidence that organisms have adaptations that confer difficulty of detection by predators and parasites that seek their targets primarily using sensory systems other than vision. In other words, I will answer the question of whether crypsis is a concept that can usefully be applied to non-visual sensory perception. Probably because vision is such an important sensory system in humans, research in this field is sparse. Thus, at present we have very few examples of chemical camouflage, and even these contain some ambiguity in deciding whether they are best seen as examples of background matching or mimicry. There are many examples of organisms that are adaptively silent at times or in locations when or where predation risk is higher or in response to detection of a predator. By contrast, evidence that the form (rather than use) of vocalizations and other sound-based signals has been influenced by issues of reducing detectability to unintended receivers is suggestive rather than conclusive. There is again suggestive but not completely conclusive evidence for crypsis against electro-sensing predators. Lastly, mechanoreception is highly understudied in this regard, but there are scattered reports that strongly suggest that some species can be thought of as being adapted to be cryptic in this modality. Hence, I conclude that crypsis is a concept that can usefully be applied to senses other than vision, and that this is a field very much worthy of more investigation.

Bacterial Adaptation of Respiration from Oxic to Microoxic and Anoxic Conditions: Redox Control

PubMed Central

Bueno, Emilio; Mesa, Socorro; Bedmar, Eulogio J.; Richardson, David J.

2012-01-01

Abstract Under a shortage of oxygen, bacterial growth can be faced mainly by two ATP-generating mechanisms: (i) by synthesis of specific high-affinity terminal oxidases that allow bacteria to use traces of oxygen or (ii) by utilizing other substrates as final electron acceptors such as nitrate, which can be reduced to dinitrogen gas through denitrification or to ammonium. This bacterial respiratory shift from oxic to microoxic and anoxic conditions requires a regulatory strategy which ensures that cells can sense and respond to changes in oxygen tension and to the availability of other electron acceptors. Bacteria can sense oxygen by direct interaction of this molecule with a membrane protein receptor (e.g., FixL) or by interaction with a cytoplasmic transcriptional factor (e.g., Fnr). A third type of oxygen perception is based on sensing changes in redox state of molecules within the cell. Redox-responsive regulatory systems (e.g., ArcBA, RegBA/PrrBA, RoxSR, RegSR, ActSR, ResDE, and Rex) integrate the response to multiple signals (e.g., ubiquinone, menaquinone, redox active cysteine, electron transport to terminal oxidases, and NAD/NADH) and activate or repress target genes to coordinate the adaptation of bacterial respiration from oxic to anoxic conditions. Here, we provide a compilation of the current knowledge about proteins and regulatory networks involved in the redox control of the respiratory adaptation of different bacterial species to microxic and anoxic environments. Antioxid. Redox Signal. 16, 819–852. PMID:22098259

An improved robust blind motion de-blurring algorithm for remote sensing images

NASA Astrophysics Data System (ADS)

He, Yulong; Liu, Jin; Liang, Yonghui

2016-10-01

Shift-invariant motion blur can be modeled as a convolution of the true latent image and the blur kernel with additive noise. Blind motion de-blurring estimates a sharp image from a motion blurred image without the knowledge of the blur kernel. This paper proposes an improved edge-specific motion de-blurring algorithm which proved to be fit for processing remote sensing images. We find that an inaccurate blur kernel is the main factor to the low-quality restored images. To improve image quality, we do the following contributions. For the robust kernel estimation, first, we adapt the multi-scale scheme to make sure that the edge map could be constructed accurately; second, an effective salient edge selection method based on RTV (Relative Total Variation) is used to extract salient structure from texture; third, an alternative iterative method is introduced to perform kernel optimization, in this step, we adopt l1 and l0 norm as the priors to remove noise and ensure the continuity of blur kernel. For the final latent image reconstruction, an improved adaptive deconvolution algorithm based on TV-l2 model is used to recover the latent image; we control the regularization weight adaptively in different region according to the image local characteristics in order to preserve tiny details and eliminate noise and ringing artifacts. Some synthetic remote sensing images are used to test the proposed algorithm, and results demonstrate that the proposed algorithm obtains accurate blur kernel and achieves better de-blurring results.

Complex adaptive systems (CAS): an overview of key elements, characteristics and application to management theory.

PubMed

Ellis, Beverley; Herbert, Stuart Ian

2011-01-01

To identify key elements and characteristics of complex adaptive systems (CAS) relevant to implementing clinical governance, drawing on lessons from quality improvement programmes and the use of informatics in primary care. The research strategy includes a literature review to develop theoretical models of clinical governance of quality improvement in primary care organisations (PCOs) and a survey of PCOs. Complex adaptive system theories are a valuable tool to help make sense of natural phenomena, which include human responses to problem solving within the sampled PCOs. The research commenced with a survey; 76% (n16) of respondents preferred to support the implementation of clinical governance initiatives guided by outputs from general practice electronic health records. There was considerable variation in the way in which consultation data was captured, recorded and organised. Incentivised information sharing led to consensus on coding policies and models of data recording ahead of national contractual requirements. Informatics was acknowledged as a mechanism to link electronic health record outputs, quality improvement and resources. Investment in informatics was identified as a development priority in order to embed clinical governance principles in practice. Complex adaptive system theory usefully describes evolutionary change processes, providing insight into how the origins of quality assurance were predicated on rational reductionism and linearity. New forms of governance do not neutralise previous models, but add further dimensions to them. Clinical governance models have moved from deterministic and 'objective' factors to incorporate cultural aspects with feedback about quality enabled by informatics. The socio-technical lessons highlighted should inform healthcare management.

Nutrient sensing modulates malaria parasite virulence.

PubMed

Mancio-Silva, Liliana; Slavic, Ksenija; Grilo Ruivo, Margarida T; Grosso, Ana Rita; Modrzynska, Katarzyna K; Vera, Iset Medina; Sales-Dias, Joana; Gomes, Ana Rita; MacPherson, Cameron Ross; Crozet, Pierre; Adamo, Mattia; Baena-Gonzalez, Elena; Tewari, Rita; Llinás, Manuel; Billker, Oliver; Mota, Maria M

2017-07-13

The lifestyle of intracellular pathogens, such as malaria parasites, is intimately connected to that of their host, primarily for nutrient supply. Nutrients act not only as primary sources of energy but also as regulators of gene expression, metabolism and growth, through various signalling networks that enable cells to sense and adapt to varying environmental conditions. Canonical nutrient-sensing pathways are presumed to be absent from the causative agent of malaria, Plasmodium, thus raising the question of whether these parasites can sense and cope with fluctuations in host nutrient levels. Here we show that Plasmodium blood-stage parasites actively respond to host dietary calorie alterations through rearrangement of their transcriptome accompanied by substantial adjustment of their multiplication rate. A kinome analysis combined with chemical and genetic approaches identified KIN as a critical regulator that mediates sensing of nutrients and controls a transcriptional response to the host nutritional status. KIN shares homology with SNF1/AMPKα, and yeast complementation studies suggest that it is part of a functionally conserved cellular energy-sensing pathway. Overall, these findings reveal a key parasite nutrient-sensing mechanism that is critical for modulating parasite replication and virulence.

A Functional Model of Sensemaking in a Neurocognitive Architecture (Open Access, Publisher’s Version)

DTIC Science & Technology

2013-07-08

bias. Moreover, it is to be expected that a rational agent learns and adapts its strategies and knowledge, its metacognitive control (e.g., more...Pirolli and S. K. Card, “The sensemaking process and leverage points for analyst technology ,” inProceedings of the International Conference on...user: the sense- making of qualitative-quantitative methodology,” in Sense- Making Methodology Reader: Selected Writings of Brenda Dervin, B. Dervin, L

Airborne Remote Sensing of the Plata Plume Using STARRS

DTIC Science & Technology

2006-09-01

marine constructions . www.sea-technoJlav.com .byT. RT O ’A" n. -, Airborne Remote Sensing of the Plata Plume Using STARRS A New Generation Microwave...using possibilities of adapting a Seville, MATLAB®-from The Spain-based Construcciones Aero- Mathworks Inc. (Natick, Mas- nduticas SA (CASA) Aviocar C...34 Simula-STARRS was constructed and flight of smaller coastal areas with a preci- tion, vol. 78, pp. 36-55, 2002.tested in July 2003. Since aircraft

Adaptive threshold determination for efficient channel sensing in cognitive radio network using mobile sensors

NASA Astrophysics Data System (ADS)

Morshed, M. N.; Khatun, S.; Kamarudin, L. M.; Aljunid, S. A.; Ahmad, R. B.; Zakaria, A.; Fakir, M. M.

2017-03-01

Spectrum saturation problem is a major issue in wireless communication systems all over the world. Huge number of users is joining each day to the existing fixed band frequency but the bandwidth is not increasing. These requirements demand for efficient and intelligent use of spectrum. To solve this issue, the Cognitive Radio (CR) is the best choice. Spectrum sensing of a wireless heterogeneous network is a fundamental issue to detect the presence of primary users' signals in CR networks. In order to protect primary users (PUs) from harmful interference, the spectrum sensing scheme is required to perform well even in low signal-to-noise ratio (SNR) environments. Meanwhile, the sensing period is usually required to be short enough so that secondary (unlicensed) users (SUs) can fully utilize the available spectrum. CR networks can be designed to manage the radio spectrum more efficiently by utilizing the spectrum holes in primary user's licensed frequency bands. In this paper, we have proposed an adaptive threshold detection method to detect presence of PU signal using free space path loss (FSPL) model in 2.4 GHz WLAN network. The model is designed for mobile sensors embedded in smartphones. The mobile sensors acts as SU while the existing WLAN network (channels) works as PU. The theoretical results show that the desired threshold range detection of mobile sensors mainly depends on the noise floor level of the location in consideration.

Evolutionary Effect on the Embodied Beauty of Landscape Architectures.

PubMed

Zhang, Wei; Tang, Xiaoxiang; He, Xianyou; Chen, Guangyao

2018-01-01

According to the framework of evolutionary aesthetics, a sense of beauty is related to environmental adaptation and plasticity of human beings, which has adaptive value and biological foundations. Prior studies have demonstrated that organisms derive benefits from the landscape. In this study, we investigated whether the benefits of landscape might elicit a stronger sense of beauty and what the nature of this sense of beauty is. In two experiments, when viewing classical landscape and nonlandscape architectures photographs, participants rated the aesthetic scores (Experiment 1) and had a two-alternative forced choice aesthetic judgment by pressing the reaction button located near to (15 cm) or far from (45 cm) the presenting stimuli (Experiment 2). The results showed that reaction of aesthetic ratings for classical landscape architectures was faster than those of classical nonlandscape architectures. Furthermore, only the reaction of beautiful judgment of classical landscape architecture photograph was significantly faster when the reaction button was in the near position to the presenting photograph than those in the position of far away from the presenting photograph. This finding suggests a facilitated effect for the aesthetic perception of classical landscape architectures due to their corresponding components including water and green plants with strong evolutionary implications. Furthermore, this sense of beauty for classical landscape architectures might be the embodied approach to beauty based on the viewpoint of evolutionary aesthetics and embodied cognition.

Simplicity and Specificity in Language: Domain-General Biases Have Domain-Specific Effects

PubMed Central

Culbertson, Jennifer; Kirby, Simon

2016-01-01

The extent to which the linguistic system—its architecture, the representations it operates on, the constraints it is subject to—is specific to language has broad implications for cognitive science and its relation to evolutionary biology. Importantly, a given property of the linguistic system can be “specific” to the domain of language in several ways. For example, if the property evolved by natural selection under the pressure of the linguistic function it serves then the property is domain-specific in the sense that its design is tailored for language. Equally though, if that property evolved to serve a different function or if that property is domain-general, it may nevertheless interact with the linguistic system in a way that is unique. This gives a second sense in which a property can be thought of as specific to language. An evolutionary approach to the language faculty might at first blush appear to favor domain-specificity in the first sense, with individual properties of the language faculty being specifically linguistic adaptations. However, we argue that interactions between learning, culture, and biological evolution mean any domain-specific adaptations that evolve will take the form of weak biases rather than hard constraints. Turning to the latter sense of domain-specificity, we highlight a very general bias, simplicity, which operates widely in cognition and yet interacts with linguistic representations in domain-specific ways. PMID:26793132

Spatial analysis of vector-borne infectious diseases and ecological indicators using GIS and remote sensing

NASA Astrophysics Data System (ADS)

Anh, N. K.; Liou, Y. A.

2017-12-01

Ecological and climate indicators play a vital role in defining patterns of human activities and behaviors, such as seasonal features, migration, winter-summer lifestyles, which in turn might be associated with vector-borne disease habitats and transmission risks. Remote sensing has been instrumental in deriving environmental variables and indicators. GIS is shown to be a powerful tool in spatiotemporal visualization and distribution of vector-borne diseases and for analysis of associations between environmental conditions and characteristics of vector-borne habitats. Vietnam is in the sub-tropical climate zone with high humidity and abundant precipitation, while the distribution of precipitation is uneven leading to frequently annual occurrence of drought and flood disasters. Moreover, urban heat island effect is significantly enhanced in urbanized areas in recent years. The increase in the frequency and magnitude of severity of weather extremes that are potentially linked to climate change and anthropogenic processes have highlighted the demand of research into health risk assessment and adaptive capacity. This research focuses on the analysis of physical features of environmental indicators and its association with vector-borne diseases as well as adaptive capacity. The study illustrates how remotely sensed data has been utilized in geohealth applications, surveillance, and health risk mapping. In addition, promising possibilities of allowing disease early-warning systems with citizen participation platform will be proposed. Keywords: Vector-borne diseases; environmental indicators; remote sensing; GIS; Vietnam.

Research on assessment and improvement method of remote sensing image reconstruction

NASA Astrophysics Data System (ADS)

Sun, Li; Hua, Nian; Yu, Yanbo; Zhao, Zhanping

2018-01-01

Remote sensing image quality assessment and improvement is an important part of image processing. Generally, the use of compressive sampling theory in remote sensing imaging system can compress images while sampling which can improve efficiency. A method of two-dimensional principal component analysis (2DPCA) is proposed to reconstruct the remote sensing image to improve the quality of the compressed image in this paper, which contain the useful information of image and can restrain the noise. Then, remote sensing image quality influence factors are analyzed, and the evaluation parameters for quantitative evaluation are introduced. On this basis, the quality of the reconstructed images is evaluated and the different factors influence on the reconstruction is analyzed, providing meaningful referential data for enhancing the quality of remote sensing images. The experiment results show that evaluation results fit human visual feature, and the method proposed have good application value in the field of remote sensing image processing.

Ocean Sense: Student-Led, Real-Time Research at the Bottom of the Ocean - Without Leaving the Classroom

NASA Astrophysics Data System (ADS)

Pelz, M.; Hoeberechts, M.; McLean, M. A.; Riddell, D. J.; Ewing, N.; Brown, J. C.

2016-12-01

This presentation outlines the authentic research experiences created by Ocean Networks Canada's Ocean Sense program, a transformative education program that connects students and teachers with place-based, real-time data via the Internet. This program, developed in collaboration with community educators, features student-centric activities, clearly outlined learning outcomes, assessment tools and curriculum aligned content. Ocean Networks Canada (ONC), an initiative of the University of Victoria, develops, operates, and maintains cabled ocean observatory systems. Technologies developed on the world-leading NEPTUNE and VENUS observatories have been adapted for small coastal installations called "community observatories," which enable community members to directly monitor conditions in the local ocean environment. Data from these observatories are fundamental to lessons and activities in the Ocean Sense program. Marketed as Ocean Sense: Local observations, global connections, the program introduces middle and high school students to research methods in biology, oceanography and ocean engineering. It includes a variety of resources and opportunities to excite students and spark curiosity about the ocean environment. The program encourages students to connect their local observations to global ocean processes and the observations of students in other geographic regions. Connection to place and local relevance of the program is enhanced through an emphasis on Indigenous and place-based knowledge. The program promotes of cross-cultural learning with the inclusion of Indigenous knowledge of the ocean. Ocean Sense provides students with an authentic research experience by connecting them to real-time data, often within their own communities. Using the freely accessible data portal, students can curate the data they need from a range of instruments and time periods. Further, students are not restricted to their local community; if their question requires a greater range of data, they also have access to the other observatories in the network. Our presentation will explore the design, implementation and lessons learned from the ongoing development of the Ocean Sense program, from its inception to its current form today. Sample activities will be made available.

Molecular characterization and mRNA expression of two key enzymes of hypoxia-sensing pathways in eastern oysters Crassostrea virginica (Gmelin): Hypoxia-inducible factor α (HIF-α) and HIF-prolyl hydroxylase (PHD)

PubMed Central

Piontkivska, Helen; Chung, J. Sook; Ivanina, Anna V.; Sokolov, Eugene P.; Techa, Sirinart; Sokolova, Inna M.

2010-01-01

Oxygen homeostasis is crucial for development, survival and normal function of all metazoans. A family of transcription factors called hypoxia-inducible factors (HIF) is critical in mediating the adaptive responses to reduced oxygen availability. The HIF transcription factor consists of a constitutively expressed β subunit and an oxygen-dependent α subunit; the abundance of the latter determines the activity of HIF and is regulated by a family of O2- and Fe2+-dependent enzymes prolyl hydroxylases (PHDs). Currently very little is known about the function of this important pathway and the molecular structure of its key players in hypoxia-tolerant intertidal mollusks including oysters, which are among the animal champions of anoxic and hypoxic tolerance and thus can serve as excellent models to study the role of HIF cascade in adaptations to oxygen deficiency. We have isolated transcripts of two key components of the oxygen sensing pathway - the oxygen-regulated HIF-α subunit and PHD - from an intertidal mollusk, the eastern oyster Crassostrea virginica, and determined the transcriptional responses of these two genes to anoxia, hypoxia and cadmium (Cd) stress. HIF-α and PHD homologs from eastern oysters C. virginica show significant sequence similarity and share key functional domains with the earlier described isoforms from vertebrates and invertebrates. Phylogenetic analysis shows that genetic diversification of HIF and PHD isoforms occurred within the vertebrate lineage indicating functional diversification and specialization of the oxygen-sensing pathways in this group, which parallels situation observed for many other important genes. HIF-α and PHD homologs are broadly expressed at the mRNA level in different oyster tissues and show transcriptional responses to prolonged hypoxia in the gills consistent with their putative role in oxygen sensing and the adaptive response to hypoxia. Similarity in amino acid sequence, domain structure and transcriptional responses between HIF-α and PHD homologs from oysters and other invertebrate and vertebrate species implies the highly conserved functions of these genes throughout the evolutionary history of animals, in accordance with their critical role in oxygen sensing and homeostasis. PMID:21106446

Adaptive Optics for Industry and Medicine

NASA Astrophysics Data System (ADS)

Dainty, Christopher

2008-01-01

pt. 1. Wavefront correctors and control. Liquid crystal lenses for correction of presbyopia (Invited Paper) / Guoqiang Li and Nasser Peyghambarian. Converging and diverging liquid crystal lenses (oral paper) / Andrew X. Kirby, Philip J. W. Hands, and Gordon D. Love. Liquid lens technology for miniature imaging systems: status of the technology, performance of existing products and future trends (invited paper) / Bruno Berge. Carbon fiber reinforced polymer deformable mirrors for high energy laser applications (oral paper) / S. R. Restaino ... [et al.]. Tiny multilayer deformable mirrors (oral paper) / Tatiana Cherezova ... [et al.]. Performance analysis of piezoelectric deformable mirrors (oral paper) / Oleg Soloviev, Mikhail Loktev and Gleb Vdovin. Deformable membrane mirror with high actuator density and distributed control (oral paper) / Roger Hamelinck ... [et al.]. Characterization and closed-loop demonstration of a novel electrostatic membrane mirror using COTS membranes (oral paper) / David Dayton ... [et al.]. Electrostatic micro-deformable mirror based on polymer materials (oral paper) / Frederic Zamkotsian ... [et al.]. Recent progress in CMOS integrated MEMS A0 mirror development (oral paper) / A. Gehner ... [et al.]. Compact large-stroke piston-tip-tilt actuator and mirror (oral paper) / W. Noell ... [et al.]. MEMS deformable mirrors for high performance AO applications (oral paper) / Paul Bierden, Thomas Bifano and Steven Cornelissen. A versatile interferometric test-rig for the investigation and evaluation of ophthalmic AO systems (poster paper) / Steve Gruppetta, Jiang Jian Zhong and Luis Diaz-Santana. Woofer-tweeter adaptive optics (poster paper) / Thomas Farrell and Chris Dainty. Deformable mirrors based on transversal piezoeffect (poster paper) / Gleb Vdovin, Mikhail Loktev and Oleg Soloviev. Low-cost spatial light modulators for ophthalmic applications (poster paper) / Vincente Durán ... [et al.]. Latest MEMS DM developments and the path ahead at Iris AO (poster paper) / Michael A. Helmbrecht ... [et al.]. Electrostatic push pull mirror improvernents in visual optics (poster paper) / S. Bonora and L. Poletto. 25cm bimorph mirror for petawatt laser / S. Bonora ... [et al.]. Hysteresis compensation for piezo deformable mirror (poster paper) / H. Song ... [et al.]. Static and dynamic responses of an adaptive optics ferrofluidic mirror (poster paper) / A. Seaman ... [et al.]. New HDTV (1920 x 1080) phase-only SLM (poster paper) / Stefan Osten and Sven Krueger. Monomorph large aperture deformable mirror for laser applications (poster paper) / J-C Sinquin, J-M Lurcon, C. Guillemard. Low cost, high speed for adaptive optics control (oral paper) / Christopher D. Saunter and Gordon D. Love. Open loop woofer-tweeter adaptive control on the LAO multi-conjugate adaptive optics testbed (oral paper) / Edward Laag, Don Gavel and Mark Ammons -- pt. 2. Wavefront sensors. Wave front sensorless adaptive optics for imaging and microscopy (invited paper) / Martin J. Booth, Delphine Débarre and Tony Wilson. A fundamental limit for wavefront sensing (oral paper) / Carl Paterson. Coherent fibre-bundle wavefront sensor (oral paper) / Brian Vohnsen, I. Iglesias and Pablo Artal. Maximum-likelihood methods in wave-front sensing: nuisance parameters (oral paper) / David Lara, Harrison H. Barrett, and Chris Dainty. Real-time wavefront sensing for ultrafast high-power laser beams (oral paper) / Juan M. Bueno ... [et al.]. Wavefront sensing using a random phase screen (oral paper) / M. Loktev, G. Vdovin and O. Soloviev. Quadri-Wave Lateral Shearing Interferometry: a new mature technique for wave front sensing in adaptive optics (oral paper) / Benoit Wattellier ... [et al.]. In vivo measurement of ocular aberrations with a distorted grating wavefront sensor (oral paper) / P. Harrison ... [et al.]. Position-sensitive detector designed with unusual CMOS layout strategies for a Hartman-Shack wavefront sensor (oral Paper) / Davies W. de Lima Monteiro ... [et al.]. Adaptive optics system to compensate complex-shaped wavefronts (oral paper) / Miguel Ares, and Santiago Royo. A kind of novel linear phase retrieval wavefront sensor and its application in close-loop adaptive optics system (oral paper) / Xinyang Li ... [et al.]. Ophthalmic Shack-Hatmann wavefront sensor applications (oral paper) / Daniel R. Neal. Wave front sensing of an optical vortex and its correction with the help of bimorph mirror (poster paper) / F. A. Starikov ... [et al.]. Recent advances in laser metrology and correction of high numerical aperture laser beams using quadri-wave lateral shearing-interferometry (poster paper) / Benoit Wattellier, Ivan Doudet and William Boucher. Thin film optical metrology using principles of wavefront sensing and interference (poster paper) / D. M. Faichnie, A. H. Greenaway and I. Bain. Direct diffractive image simulation (poster paper) / A. P. Maryasov, N. P. Maryasov, A. P. Layko. High speed smart CMOS sensor for adaptive optics (poster paper) / T. D. Raymond ... [et al.]. Traceable astigmatism measurements for wavefront sensors (poster paper) / S. R. G. Hall, S. D. Knox, R. F. Stevens -- pt. 3. Adaptive optics in vision science. Dual-conjugate adaptive optics instrument for wide-field retinal imaging (oral paper) / Jörgen Thaung, Mette-Owner Petersen and Zoran Popovic. Visual simulation using electromagnetic adaptive-optics (oral paper) / Laurent Vabre ... [et al.]. High-resolution field-of-view widening in human eye retina imaging (oral paper) / Alexander V. Dubinin, Tatyana Yu. Cherezova, Alexis V. Kudryashov. Psychophysical experiments on visual performance with an ocular adaptive optics system (oral paper) / E. Dalimier, J. C. Dainty and J. Barbur. Does the accommodative mechanism of the eye calibrate itself using aberration dynamics? (oral paper) / K. M. Hampson, S. S. Chin and E. A. H. Mallen. A study of field aberrations in the human eye (oral paper) / Alexander V. Goncharov ... [et al.]. Dual wavefront corrector ophthalmic adaptive optics: design and alignment (oral paper) / Alfredo Dubra and David Williams. High speed simultaneous SLO/OCT imaging of the human retina with adaptive optics (oral paper) / M. Pircher ... [et al.]. Characterization of an AO-OCT system (oral paper) / Julia W. Evans ... [et al.]. Adaptive optics optical coherence tomography for retina imaging (oral paper) / Guohua Shi ... [et al.]. Development, calibration and performance of an electromagnetic-mirror-based adaptive optics system for visual optics (oral paper) / Enrique Gambra ... [et al.]. Adaptive eye model (poster paper) / Sergey O. Galetskzy and Alexty V. Kudryashov. Adaptive optics system for retinal imaging based on a pyramid wavefront sensor (poster paper) / Sabine Chiesa ... [et al.]. Modeling of non-stationary dynamic ocular aberrations (poster paper) / Conor Leahy and Chris Dainty. High-order aberrations and accommodation of human eye (poster paper) / Lixia Xue ... [et al.]. Electromagnetic deformable mirror: experimental assessment and first ophthalmic applications (poster paper) / L. Vabre ... [et al.]. Correcting ocular aberrations in optical coherence tomography (poster paper) / Simon Tuohy ... [et al.] -- pt. 4. Adaptive optics in optical storage and microscopy. The application of liquid crystal aberration compensator for the optical disc systems (invited paper) / Masakazu Ogasawara. Commercialization of the adaptive scanning optical microscope (ASOM) (oral paper) / Benjamin Potsaid ... [et al.]. A practical implementation of adaptive optics for aberration compensation in optical microscopy (oral paper) / A. J. Wright ... [et al.]. Active focus locking in an optically sectioning microscope using adaptive optics (poster paper) / S. Poland, A. J. Wright, J. M. Girkin. Towards four dimensional particle tracking for biological applications / Heather I. Campbell ... [et al.]. Adaptive optics for microscopy (poster paper) / Xavier Levecq -- pt. 5. Adaptive optics in lasers. Improved beam quality of a high power Yb: YAG laser (oral paper) / Dennis G. Harris ... [et al.]. Intracavity adaptive optics optimization of an end-pumped Nd:YVO4 laser (oral paper) / Petra Welp, Ulrich Wittrock. New results in high power lasers beam correction (oral paper) / Alexis Kudryashov ... [et al.]. Adaptive optical systems for the Shenguang-III prototype facility (oral paper) / Zeping Yang ... [et al.]. Adaptive optics control of solid-state lasers (poster paper) / Walter Lubeigt ... [et al.]. Gerchberg-Saxton algorithm for multimode beam reshaping (poster paper) / Inna V. Ilyina, Tatyana Yu. Cherezova. New algorithm of combining for spatial coherent beams (poster paper) / Ruofu Yang ... [et al.]. Intracavity mode control of a solid-state laser using a 19-element deformable mirror (poster paper) / Ping Yang ... [et al.] -- pt. 6. Adaptive optics in communication and atmospheric compensation. Fourier image sharpness sensor for laser communications (oral paper) / Kristin N. Walker and Robert K. Tyson. Fast closed-loop adaptive optics system for imaging through strong turbulence layers (oral paper) / Ivo Buske and Wolfgang Riede. Correction of wavefront aberrations and optical communication using aperture synthesis (oral paper) / R. J. Eastwood ... [et al.]. Adaptive optics system for a small telescope (oral paper) / G. Vdovin, M. Loktev and O. Soloviev. Fast correction of atmospheric turbulence using a membrane deformable mirror (poster paper) / Ivan Capraro, Stefano Bonora, Paolo Villoresi. Atmospheric turbulence measurements over a 3km horizontal path with a Shack-Hartmann wavefront sensor (poster paper) / Ruth Mackey, K. Murphy and Chris Dainty. Field-oriented wavefront sensor for laser guide stars (poster paper) / Lidija Bolbasova, Alexander Goncharov and Vladimir Lukin.

Room-temperature quantum noise limited spectrometry and methods of the same

DOEpatents

Stevens, Charles G.; Tringe, Joseph W.; Cunningham, Christopher Thomas

2014-08-26

In one embodiment, a heterodyne detection system for detecting light includes a first input aperture adapted for receiving first light from a scene input, a second input aperture adapted for receiving second light from a local oscillator input, a broadband local oscillator adapted for providing the second light to the second input aperture, a dispersive element adapted for dispersing the first light and the second light, and a final condensing lens coupled to an infrared detector. The final condensing lens is adapted for concentrating incident light from a primary condensing lens onto the infrared detector, and the infrared detector is a square-law detector capable of sensing the frequency difference between the first light and the second light. More systems and methods for detecting light are described according to other embodiments.

Room-temperature quantum noise limited spectrometry and methods of the same

DOEpatents

Stevens, Charles G; Tringe, Joseph W

2014-12-02

In one embodiment, a heterodyne detection system for detecting light includes a first input aperture adapted for receiving a first light from a scene input, a second input aperture adapted for receiving a second light from a local oscillator input, a broadband local oscillator adapted for providing the second light to the second input aperture, a dispersive element adapted for dispersing the first light and the second light, and a final condensing lens coupled to an infrared detector. The final condensing lens is adapted for concentrating incident light from a primary condensing lens onto the detector, and the detector is a square-law detector capable of sensing the frequency difference between the first light and the second light. More systems and methods for detecting light are disclosed according to more embodiments.

Gradient-free MCMC methods for dynamic causal modelling

DOE PAGES

Sengupta, Biswa; Friston, Karl J.; Penny, Will D.

2015-03-14

Here, we compare the performance of four gradient-free MCMC samplers (random walk Metropolis sampling, slice-sampling, adaptive MCMC sampling and population-based MCMC sampling with tempering) in terms of the number of independent samples they can produce per unit computational time. For the Bayesian inversion of a single-node neural mass model, both adaptive and population-based samplers are more efficient compared with random walk Metropolis sampler or slice-sampling; yet adaptive MCMC sampling is more promising in terms of compute time. Slice-sampling yields the highest number of independent samples from the target density -- albeit at almost 1000% increase in computational time, in comparisonmore » to the most efficient algorithm (i.e., the adaptive MCMC sampler).« less

A Decentralized Adaptive Approach to Fault Tolerant Flight Control

NASA Technical Reports Server (NTRS)

Wu, N. Eva; Nikulin, Vladimir; Heimes, Felix; Shormin, Victor

2000-01-01

This paper briefly reports some results of our study on the application of a decentralized adaptive control approach to a 6 DOF nonlinear aircraft model. The simulation results showed the potential of using this approach to achieve fault tolerant control. Based on this observation and some analysis, the paper proposes a multiple channel adaptive control scheme that makes use of the functionally redundant actuating and sensing capabilities in the model, and explains how to implement the scheme to tolerate actuator and sensor failures. The conditions, under which the scheme is applicable, are stated in the paper.

Frequency position modulation using multi-spectral projections

NASA Astrophysics Data System (ADS)

Goodman, Joel; Bertoncini, Crystal; Moore, Michael; Nousain, Bryan; Cowart, Gregory

2012-10-01

In this paper we present an approach to harness multi-spectral projections (MSPs) to carefully shape and locate tones in the spectrum, enabling a new and robust modulation in which a signal's discrete frequency support is used to represent symbols. This method, called Frequency Position Modulation (FPM), is an innovative extension to MT-FSK and OFDM and can be non-uniformly spread over many GHz of instantaneous bandwidth (IBW), resulting in a communications system that is difficult to intercept and jam. The FPM symbols are recovered using adaptive projections that in part employ an analog polynomial nonlinearity paired with an analog-to-digital converter (ADC) sampling at a rate at that is only a fraction of the IBW of the signal. MSPs also facilitate using commercial of-the-shelf (COTS) ADCs with uniform-sampling, standing in sharp contrast to random linear projections by random sampling, which requires a full Nyquist rate sample-and-hold. Our novel communication system concept provides an order of magnitude improvement in processing gain over conventional LPI/LPD communications (e.g., FH- or DS-CDMA) and facilitates the ability to operate in interference laden environments where conventional compressed sensing receivers would fail. We quantitatively analyze the bit error rate (BER) and processing gain (PG) for a maximum likelihood based FPM demodulator and demonstrate its performance in interference laden conditions.

A Paper-Based Electrochromic Array for Visualized Electrochemical Sensing.

PubMed

Zhang, Fengling; Cai, Tianyi; Ma, Liang; Zhan, Liyuan; Liu, Hong

2017-01-31

We report a battery-powered, paper-based electrochromic array for visualized electrochemical sensing. The paper-based sensing system consists of six parallel electrochemical cells, which are powered by an aluminum-air battery. Each single electrochemical cell uses a Prussian Blue spot electrodeposited on an indium-doped tin oxide thin film as the electrochromic indicator. Each electrochemical cell is preloaded with increasing amounts of analyte. The sample activates the battery for the sensing. Both the preloaded analyte and the analyte in the sample initiate the color change of Prussian Blue to Prussian White. With a reaction time of 60 s, the number of electrochemical cells with complete color changes is correlated to the concentration of analyte in the sample. As a proof-of-concept analyte, lactic acid was detected semi-quantitatively using the naked eye.

Capacitive chemical sensor

DOEpatents

Manginell, Ronald P; Moorman, Matthew W; Wheeler, David R

2014-05-27

A microfabricated capacitive chemical sensor can be used as an autonomous chemical sensor or as an analyte-sensitive chemical preconcentrator in a larger microanalytical system. The capacitive chemical sensor detects changes in sensing film dielectric properties, such as the dielectric constant, conductivity, or dimensionality. These changes result from the interaction of a target analyte with the sensing film. This capability provides a low-power, self-heating chemical sensor suitable for remote and unattended sensing applications. The capacitive chemical sensor also enables a smart, analyte-sensitive chemical preconcentrator. After sorption of the sample by the sensing film, the film can be rapidly heated to release the sample for further analysis. Therefore, the capacitive chemical sensor can optimize the sample collection time prior to release to enable the rapid and accurate analysis of analytes by a microanalytical system.

Sense of coherence, self-regulated learning and academic performance in first year nursing students: A cluster analysis approach.

PubMed

Salamonson, Yenna; Ramjan, Lucie M; van den Nieuwenhuizen, Simon; Metcalfe, Lauren; Chang, Sungwon; Everett, Bronwyn

2016-03-01

This paper examines the relationship between nursing students' sense of coherence, self-regulated learning and academic performance in bioscience. While there is increasing recognition of a need to foster students' self-regulated learning, little is known about the relationship of psychological strengths, particularly sense of coherence and academic performance. Using a prospective, correlational design, 563 first year nursing students completed the three dimensions of sense of coherence scale - comprehensibility, manageability and meaningfulness, and five components of self-regulated learning strategy - elaboration, organisation, rehearsal, self-efficacy and task value. Cluster analysis was used to group respondents into three clusters, based on their sense of coherence subscale scores. Although there were no sociodemographic differences in sense of coherence subscale scores, those with higher sense of coherence were more likely to adopt self-regulated learning strategies. Furthermore, academic grades collected at the end of semester revealed that higher sense of coherence was consistently related to achieving higher academic grades across all four units of study. Students with higher sense of coherence were more self-regulated in their learning approach. More importantly, the study suggests that sense of coherence may be an explanatory factor for students' successful adaptation and transition in higher education, as indicated by the positive relationship of sense of coherence to academic performance. Copyright © 2016 Elsevier Ltd. All rights reserved.

Being Sherlock Holmes: Can we sense empathy from a brief sample of behaviour?

PubMed

Wu, Wenjie; Sheppard, Elizabeth; Mitchell, Peter

2016-02-01

Mentalizing (otherwise known as 'theory of mind') involves a special process that is adapted for predicting and explaining the behaviour of others (targets) based on inferences about targets' beliefs and character. This research investigated how well participants made inferences about an especially apposite aspect of character, empathy. Participants were invited to make inferences of self-rated empathy after watching or listening to an unfamiliar target for a few seconds telling a scripted joke (or answering questions about him/herself or reading aloud a paragraph of promotional material). Across three studies, participants were good at identifying targets with low and high self-rated empathy but not good at identifying those who are average. Such inferences, especially of high self-rated empathy, seemed to be based mainly on clues in the target's behaviour, presented either in a video, a still photograph or in an audio track. However, participants were not as effective in guessing which targets had low or average self-rated empathy from a still photograph showing a neutral pose or from an audio track. We conclude with discussion of the scope and the adaptive value of this inferential ability. © 2016 The British Psychological Society.

Future orientation and health quality of life in primary care: vitality as a mediator.

PubMed

Hirsch, Jameson K; Molnar, Danielle; Chang, Edward C; Sirois, Fuschia M

2015-07-01

Temporal perspective, including views about future goals, may influence motivational processes related to health. An adaptive sense of future orientation is linked to better health, but little research has examined potential underlying factors, such as vitality. In a sample of 101 primary care patients, we examined whether belief in the changeability of the future was related to mental and physical energization and, in turn, to health-related quality of life. Participants were working, uninsured primary care patients, who completed self-report measures of future orientation, vitality, and health-related quality of life. Mediation models, covarying age, sex, and race/ethnicity indicated that vitality significantly mediated the association between future orientation and the outcomes of general health, mental health, social functioning, bodily pain, and role limitations due to emotional and physical reasons. Vitality exerted an indirect-only effect on the relation between future orientation and physical functioning. Our findings suggest that adaptive beliefs about the future may promote, or allow access to, physical and mental energy and, in turn, may result in better mental and physical health functioning. Individual-level and public health interventions designed to promote future orientation and vitality may beneficially influence quality of life and well-being.

Unsupervised classification of multivariate geostatistical data: Two algorithms

NASA Astrophysics Data System (ADS)

Romary, Thomas; Ors, Fabien; Rivoirard, Jacques; Deraisme, Jacques

2015-12-01

With the increasing development of remote sensing platforms and the evolution of sampling facilities in mining and oil industry, spatial datasets are becoming increasingly large, inform a growing number of variables and cover wider and wider areas. Therefore, it is often necessary to split the domain of study to account for radically different behaviors of the natural phenomenon over the domain and to simplify the subsequent modeling step. The definition of these areas can be seen as a problem of unsupervised classification, or clustering, where we try to divide the domain into homogeneous domains with respect to the values taken by the variables in hand. The application of classical clustering methods, designed for independent observations, does not ensure the spatial coherence of the resulting classes. Image segmentation methods, based on e.g. Markov random fields, are not adapted to irregularly sampled data. Other existing approaches, based on mixtures of Gaussian random functions estimated via the expectation-maximization algorithm, are limited to reasonable sample sizes and a small number of variables. In this work, we propose two algorithms based on adaptations of classical algorithms to multivariate geostatistical data. Both algorithms are model free and can handle large volumes of multivariate, irregularly spaced data. The first one proceeds by agglomerative hierarchical clustering. The spatial coherence is ensured by a proximity condition imposed for two clusters to merge. This proximity condition relies on a graph organizing the data in the coordinates space. The hierarchical algorithm can then be seen as a graph-partitioning algorithm. Following this interpretation, a spatial version of the spectral clustering algorithm is also proposed. The performances of both algorithms are assessed on toy examples and a mining dataset.

Accelerated 1 H MRSI using randomly undersampled spiral-based k-space trajectories.

PubMed

Chatnuntawech, Itthi; Gagoski, Borjan; Bilgic, Berkin; Cauley, Stephen F; Setsompop, Kawin; Adalsteinsson, Elfar

2014-07-30

To develop and evaluate the performance of an acquisition and reconstruction method for accelerated MR spectroscopic imaging (MRSI) through undersampling of spiral trajectories. A randomly undersampled spiral acquisition and sensitivity encoding (SENSE) with total variation (TV) regularization, random SENSE+TV, is developed and evaluated on single-slice numerical phantom, in vivo single-slice MRSI, and in vivo three-dimensional (3D)-MRSI at 3 Tesla. Random SENSE+TV was compared with five alternative methods for accelerated MRSI. For the in vivo single-slice MRSI, random SENSE+TV yields up to 2.7 and 2 times reduction in root-mean-square error (RMSE) of reconstructed N-acetyl aspartate (NAA), creatine, and choline maps, compared with the denoised fully sampled and uniformly undersampled SENSE+TV methods with the same acquisition time, respectively. For the in vivo 3D-MRSI, random SENSE+TV yields up to 1.6 times reduction in RMSE, compared with uniform SENSE+TV. Furthermore, by using random SENSE+TV, we have demonstrated on the in vivo single-slice and 3D-MRSI that acceleration factors of 4.5 and 4 are achievable with the same quality as the fully sampled data, as measured by RMSE of reconstructed NAA map, respectively. With the same scan time, random SENSE+TV yields lower RMSEs of metabolite maps than other methods evaluated. Random SENSE+TV achieves up to 4.5-fold acceleration with comparable data quality as the fully sampled acquisition. Magn Reson Med, 2014. © 2014 Wiley Periodicals, Inc. © 2014 Wiley Periodicals, Inc.

Feasibility of 4D flow MR imaging of the brain with either Cartesian y-z radial sampling or k-t SENSE: comparison with 4D Flow MR imaging using SENSE.

PubMed

Sekine, Tetsuro; Amano, Yasuo; Takagi, Ryo; Matsumura, Yoshio; Murai, Yasuo; Kumita, Shinichiro

2014-01-01

A drawback of time-resolved 3-dimensional phase contrast magnetic resonance (4D Flow MR) imaging is its lengthy scan time for clinical application in the brain. We assessed the feasibility for flow measurement and visualization of 4D Flow MR imaging using Cartesian y-z radial sampling and that using k-t sensitivity encoding (k-t SENSE) by comparison with the standard scan using SENSE. Sixteen volunteers underwent 3 types of 4D Flow MR imaging of the brain using a 3.0-tesla scanner. As the standard scan, 4D Flow MR imaging with SENSE was performed first and then followed by 2 types of acceleration scan-with Cartesian y-z radial sampling and with k-t SENSE. We measured peak systolic velocity (PSV) and blood flow volume (BFV) in 9 arteries, and the percentage of particles arriving from the emitter plane at the target plane in 3 arteries, visually graded image quality in 9 arteries, and compared these quantitative and visual data between the standard scan and each acceleration scan. 4D Flow MR imaging examinations were completed in all but one volunteer, who did not undergo the last examination because of headache. Each acceleration scan reduced scan time by 50% compared with the standard scan. The k-t SENSE imaging underestimated PSV and BFV (P < 0.05). There were significant correlations for PSV and BFV between the standard scan and each acceleration scan (P < 0.01). The percentage of particles reaching the target plane did not differ between the standard scan and each acceleration scan. For visual assessment, y-z radial sampling deteriorated the image quality of the 3 arteries. Cartesian y-z radial sampling is feasible for measuring flow, and k-t SENSE offers sufficient flow visualization; both allow acquisition of 4D Flow MR imaging with shorter scan time.

OTDR fiber-optical chemical sensor system for detection and location of hydrocarbon leakage.

PubMed

Buerck, J; Roth, S; Kraemer, K; Mathieu, H

2003-08-15

A distributed sensing system for apolar hydrocarbons is presented which is built from a polymer-clad silica fiber adapted to an optical time domain reflectometer (OTDR) set-up. OTDR measurements allow locating and detecting chemicals by measuring the time delay between short light pulses entering the fiber and discrete changes in the backscatter signals that are caused by local extraction of hydrocarbons into the fiber cladding. The light guiding properties of the fiber are affected by interaction of the extracted chemicals with the evanescent wave light field extending into the fiber cladding. Distributed sensing of pure liquid hydrocarbons (HC) and aqueous HC solutions with a commercially available mini-OTDR adapted to sensing fibers of up to 1km length could be demonstrated. A pulsed laser diode emitting at the 850 nm telecommunication wavelength was applied in the mini-OTDR to locate the HCs by analyzing the step drop (light loss) in the backscatter signal, which is induced by local refractive index (RI) increase in the silicone cladding due to the extracted HC. The prototype instrument can be applied for monitoring hydrocarbon leakage in large technical installations, such as tanks, chemical pipelines or chemical waste disposal containments.

Relevance of Red Book Information to the Directorate of Engineering and Housing Decisionmaking Process

DTIC Science & Technology

1990-09-01

decisionmaking. (Adapted from: R. J. Boland, Jr., "Sense-Making of Accounting Data as a Technique of Organizational Diagnosis ," Management Science, Vol 30, No...Making of Accounting Data as a Technique of Organizational Diagnosis ," Managenent Science, Vol 30, No. 7 (July 1984), pp 868-882. 49 Decisionmaking...Third Edition (Irwin, 1984). Boland, R.J., Jr., "Sense-Making of Accounting Data as a Technique of Organizational Diagnosis ," Management Science, Vol 30

A temperature control design for a tapered element oscillating microbalance sensing surface

NASA Technical Reports Server (NTRS)

1982-01-01

A design study is presented which shows that a tapered element oscillating microbalance can be adapted for temperature control under space application by mating with multistage thermoelectric coolers in such a way that an integral structure evolves. The control of the temperature of the sensing surface can be achieved in a number of ways. An indirect method which uses a measurement of the absorbed power is recommended. The design goals can be met if a relaxation of the power requirement can be considered.

Gradient-free MCMC methods for dynamic causal modelling.

PubMed

Sengupta, Biswa; Friston, Karl J; Penny, Will D

2015-05-15

In this technical note we compare the performance of four gradient-free MCMC samplers (random walk Metropolis sampling, slice-sampling, adaptive MCMC sampling and population-based MCMC sampling with tempering) in terms of the number of independent samples they can produce per unit computational time. For the Bayesian inversion of a single-node neural mass model, both adaptive and population-based samplers are more efficient compared with random walk Metropolis sampler or slice-sampling; yet adaptive MCMC sampling is more promising in terms of compute time. Slice-sampling yields the highest number of independent samples from the target density - albeit at almost 1000% increase in computational time, in comparison to the most efficient algorithm (i.e., the adaptive MCMC sampler). Copyright © 2015 The Authors. Published by Elsevier Inc. All rights reserved.

Career Adapt-Abilities Scale in a French-Speaking Swiss Sample: Psychometric Properties and Relationships to Personality and Work Engagement

ERIC Educational Resources Information Center

Rossier, Jerome; Zecca, Gregory; Stauffer, Sarah D.; Maggiori, Christian; Dauwalder, Jean-Pierre

2012-01-01

The aim of this study was to analyze the psychometric properties of the Career Adapt-Abilities Scale (CAAS) in a French-speaking Swiss sample and its relationship with personality dimensions and work engagement. The heterogeneous sample of 391 participants (M[subscript age] = 39.59, SD = 12.30) completed the CAAS-International and a short version…

A Software Architecture for Adaptive Modular Sensing Systems

PubMed Central

Lyle, Andrew C.; Naish, Michael D.

2010-01-01

By combining a number of simple transducer modules, an arbitrarily complex sensing system may be produced to accommodate a wide range of applications. This work outlines a novel software architecture and knowledge representation scheme that has been developed to support this type of flexible and reconfigurable modular sensing system. Template algorithms are used to embed intelligence within each module. As modules are added or removed, the composite sensor is able to automatically determine its overall geometry and assume an appropriate collective identity. A virtual machine-based middleware layer runs on top of a real-time operating system with a pre-emptive kernel, enabling platform-independent template algorithms to be written once and run on any module, irrespective of its underlying hardware architecture. Applications that may benefit from easily reconfigurable modular sensing systems include flexible inspection, mobile robotics, surveillance, and space exploration. PMID:22163614

A software architecture for adaptive modular sensing systems.

PubMed

Lyle, Andrew C; Naish, Michael D

2010-01-01

By combining a number of simple transducer modules, an arbitrarily complex sensing system may be produced to accommodate a wide range of applications. This work outlines a novel software architecture and knowledge representation scheme that has been developed to support this type of flexible and reconfigurable modular sensing system. Template algorithms are used to embed intelligence within each module. As modules are added or removed, the composite sensor is able to automatically determine its overall geometry and assume an appropriate collective identity. A virtual machine-based middleware layer runs on top of a real-time operating system with a pre-emptive kernel, enabling platform-independent template algorithms to be written once and run on any module, irrespective of its underlying hardware architecture. Applications that may benefit from easily reconfigurable modular sensing systems include flexible inspection, mobile robotics, surveillance, and space exploration.

Modeling of high-precision wavefront sensing with new generation of CMT avalanche photodiode infrared detectors.

PubMed

Gousset, Silvère; Petit, Cyril; Michau, Vincent; Fusco, Thierry; Robert, Clelia

2015-12-01

Near-infrared wavefront sensing allows for the enhancement of sky coverage with adaptive optics. The recently developed HgCdTe avalanche photodiode arrays are promising due to their very low detector noise, but still present an imperfect cosmetic that may directly impact real-time wavefront measurements for adaptive optics and thus degrade performance in astronomical applications. We propose here a model of a Shack-Hartmann wavefront measurement in the presence of residual fixed pattern noise and defective pixels. To adjust our models, a fine characterization of such an HgCdTe array, the RAPID sensor, is proposed. The impact of the cosmetic defects on the Shack-Hartmann measurement is assessed through numerical simulations. This study provides both a new insight on the applicability of cadmium mercury telluride (CMT) avalanche photodiodes detectors for astronomical applications and criteria to specify the cosmetic qualities of future arrays.

Change Detection of High-Resolution Remote Sensing Images Based on Adaptive Fusion of Multiple Features

NASA Astrophysics Data System (ADS)

Wang, G. H.; Wang, H. B.; Fan, W. F.; Liu, Y.; Chen, C.

2018-04-01

In view of the traditional change detection algorithm mainly depends on the spectral information image spot, failed to effectively mining and fusion of multi-image feature detection advantage, the article borrows the ideas of object oriented analysis proposed a multi feature fusion of remote sensing image change detection algorithm. First by the multi-scale segmentation of image objects based; then calculate the various objects of color histogram and linear gradient histogram; utilizes the color distance and edge line feature distance between EMD statistical operator in different periods of the object, using the adaptive weighted method, the color feature distance and edge in a straight line distance of combination is constructed object heterogeneity. Finally, the curvature histogram analysis image spot change detection results. The experimental results show that the method can fully fuse the color and edge line features, thus improving the accuracy of the change detection.

Flexible Piezoelectric Sensor-Based Gait Recognition.

PubMed

Cha, Youngsu; Kim, Hojoon; Kim, Doik

2018-02-05

Most motion recognition research has required tight-fitting suits for precise sensing. However, tight-suit systems have difficulty adapting to real applications, because people normally wear loose clothes. In this paper, we propose a gait recognition system with flexible piezoelectric sensors in loose clothing. The gait recognition system does not directly sense lower-body angles. It does, however, detect the transition between standing and walking. Specifically, we use the signals from the flexible sensors attached to the knee and hip parts on loose pants. We detect the periodic motion component using the discrete time Fourier series from the signal during walking. We adapt the gait detection method to a real-time patient motion and posture monitoring system. In the monitoring system, the gait recognition operates well. Finally, we test the gait recognition system with 10 subjects, for which the proposed system successfully detects walking with a success rate over 93 %.

An adaptive image sparse reconstruction method combined with nonlocal similarity and cosparsity for mixed Gaussian-Poisson noise removal

NASA Astrophysics Data System (ADS)

Chen, Yong-fei; Gao, Hong-xia; Wu, Zi-ling; Kang, Hui

2018-01-01

Compressed sensing (CS) has achieved great success in single noise removal. However, it cannot restore the images contaminated with mixed noise efficiently. This paper introduces nonlocal similarity and cosparsity inspired by compressed sensing to overcome the difficulties in mixed noise removal, in which nonlocal similarity explores the signal sparsity from similar patches, and cosparsity assumes that the signal is sparse after a possibly redundant transform. Meanwhile, an adaptive scheme is designed to keep the balance between mixed noise removal and detail preservation based on local variance. Finally, IRLSM and RACoSaMP are adopted to solve the objective function. Experimental results demonstrate that the proposed method is superior to conventional CS methods, like K-SVD and state-of-art method nonlocally centralized sparse representation (NCSR), in terms of both visual results and quantitative measures.

LORAKS Makes Better SENSE: Phase-Constrained Partial Fourier SENSE Reconstruction without Phase Calibration

PubMed Central

Kim, Tae Hyung; Setsompop, Kawin; Haldar, Justin P.

2016-01-01

Purpose Parallel imaging and partial Fourier acquisition are two classical approaches for accelerated MRI. Methods that combine these approaches often rely on prior knowledge of the image phase, but the need to obtain this prior information can place practical restrictions on the data acquisition strategy. In this work, we propose and evaluate SENSE-LORAKS, which enables combined parallel imaging and partial Fourier reconstruction without requiring prior phase information. Theory and Methods The proposed formulation is based on combining the classical SENSE model for parallel imaging data with the more recent LORAKS framework for MR image reconstruction using low-rank matrix modeling. Previous LORAKS-based methods have successfully enabled calibrationless partial Fourier parallel MRI reconstruction, but have been most successful with nonuniform sampling strategies that may be hard to implement for certain applications. By combining LORAKS with SENSE, we enable highly-accelerated partial Fourier MRI reconstruction for a broader range of sampling trajectories, including widely-used calibrationless uniformly-undersampled trajectories. Results Our empirical results with retrospectively undersampled datasets indicate that when SENSE-LORAKS reconstruction is combined with an appropriate k-space sampling trajectory, it can provide substantially better image quality at high-acceleration rates relative to existing state-of-the-art reconstruction approaches. Conclusion The SENSE-LORAKS framework provides promising new opportunities for highly-accelerated MRI. PMID:27037836

Ratiometric, visual, dual-signal fluorescent sensing and imaging of pH/copper ions in real samples based on carbon dots-fluorescein isothiocyanate composites.

PubMed

Zhu, Xinxin; Jin, Hui; Gao, Cuili; Gui, Rijun; Wang, Zonghua

2017-01-01

In this article, a facile aqueous synthesis of carbon dots (CDs) was developed by using natural kelp as a new carbon source. Through hydrothermal carbonization of kelp juice, fluorescent CDs were prepared and the CDs' surface was modified with polyethylenimine (PEI). The PEI-modified CDs were conjugated with fluorescein isothiocyanate (FITC) to fabricate CDs-FITC composites. To exploit broad applications, the CDs-FITC composites were developed as fluorescent sensing or imaging platforms of pH and Cu 2+ . Analytical performances of the composites-based fluorescence (FL) sensors were evaluated, including visual FL imaging of pH in glass bottle, ratiometric FL sensing of pH in yogurt samples, visual FL latent fingerprint and leaf imaging detection of [Cu 2+ ], dual-signal FL sensing of [Cu 2+ ] in yogurt and human serum samples. Experimental results from ratiometric, visual, dual-signal FL sensing and imaging applications confirmed the high feasibility, accuracy, stabilization and simplicity of CDs-FITC composites-based FL sensors for the detection of pH and Cu 2+ ions in real samples. Copyright © 2016 Elsevier B.V. All rights reserved.

Field matric potential sensor

DOEpatents

Hubbell, Joel M.; Sisson, James B.

2001-01-01

A method of determining matric potential of a sample, the method comprising placing the sample in a container, the container having an opening; and contacting the sample with a tensiometer via the opening. An apparatus for determining matric potential of a sample, the apparatus comprising a housing configured to receive a sample; a portable matric potential sensing device extending into the housing and having a porous member; and a wall closing the housing to insulate the sample and at least a portion of the matric potential sensing device including the porous member.

Breaking through the bandwidth barrier in distributed fiber vibration sensing by sub-Nyquist randomized sampling

NASA Astrophysics Data System (ADS)

Zhang, Jingdong; Zhu, Tao; Zheng, Hua; Kuang, Yang; Liu, Min; Huang, Wei

2017-04-01

The round trip time of the light pulse limits the maximum detectable frequency response range of vibration in phase-sensitive optical time domain reflectometry (φ-OTDR). We propose a method to break the frequency response range restriction of φ-OTDR system by modulating the light pulse interval randomly which enables a random sampling for every vibration point in a long sensing fiber. This sub-Nyquist randomized sampling method is suits for detecting sparse-wideband- frequency vibration signals. Up to MHz resonance vibration signal with over dozens of frequency components and 1.153MHz single frequency vibration signal are clearly identified for a sensing range of 9.6km with 10kHz maximum sampling rate.

Direct phase measurement in zonal wavefront reconstruction using multidither coherent optical adaptive technique.

PubMed

Liu, Rui; Milkie, Daniel E; Kerlin, Aaron; MacLennan, Bryan; Ji, Na

2014-01-27

In traditional zonal wavefront sensing for adaptive optics, after local wavefront gradients are obtained, the entire wavefront can be calculated by assuming that the wavefront is a continuous surface. Such an approach will lead to sub-optimal performance in reconstructing wavefronts which are either discontinuous or undersampled by the zonal wavefront sensor. Here, we report a new method to reconstruct the wavefront by directly measuring local wavefront phases in parallel using multidither coherent optical adaptive technique. This method determines the relative phases of each pupil segment independently, and thus produces an accurate wavefront for even discontinuous wavefronts. We implemented this method in an adaptive optical two-photon fluorescence microscopy and demonstrated its superior performance in correcting large or discontinuous aberrations.

Robust adaptive fuzzy tracking control for pure-feedback stochastic nonlinear systems with input constraints.

PubMed

Wang, Huanqing; Chen, Bing; Liu, Xiaoping; Liu, Kefu; Lin, Chong

2013-12-01

This paper is concerned with the problem of adaptive fuzzy tracking control for a class of pure-feedback stochastic nonlinear systems with input saturation. To overcome the design difficulty from nondifferential saturation nonlinearity, a smooth nonlinear function of the control input signal is first introduced to approximate the saturation function; then, an adaptive fuzzy tracking controller based on the mean-value theorem is constructed by using backstepping technique. The proposed adaptive fuzzy controller guarantees that all signals in the closed-loop system are bounded in probability and the system output eventually converges to a small neighborhood of the desired reference signal in the sense of mean quartic value. Simulation results further illustrate the effectiveness of the proposed control scheme.

Load attenuating passively adaptive wind turbine blade

DOEpatents

Veers, Paul S.; Lobitz, Donald W.

2003-01-07

A method and apparatus for improving wind turbine performance by alleviating loads and controlling the rotor. The invention employs the use of a passively adaptive blade that senses the wind velocity or rotational speed, and accordingly modifies its aerodynamic configuration. The invention exploits the load mitigation prospects of a blade that twists toward feather as it bends. The invention includes passively adaptive wind turbine rotors or blades with currently preferred power control features. The apparatus is a composite fiber horizontal axis wind-turbine blade, in which a substantial majority of fibers in the blade skin are inclined at angles of between 15 and 30 degrees to the axis of the blade, to produces passive adaptive aeroelastic tailoring (bend-twist coupling) to alleviate loading without unduly jeopardizing performance.

Load attenuating passively adaptive wind turbine blade

DOEpatents

Veers, Paul S.; Lobitz, Donald W.

2003-01-01

A method and apparatus for improving wind turbine performance by alleviating loads and controlling the rotor. The invention employs the use of a passively adaptive blade that senses the wind velocity or rotational speed, and accordingly modifies its aerodynamic configuration. The invention exploits the load mitigation prospects of a blade that twists toward feather as it bends. The invention includes passively adaptive wind turbine rotors or blades with currently preferred power control features. The apparatus is a composite fiber horizontal axis wind-turbine blade, in which a substantial majority of fibers in the blade skin are inclined at angles of between 15 and 30 degrees to the axis of the blade, to produces passive adaptive aeroelastic tailoring (bend-twist coupling) to alleviate loading without unduly jeopardizing performance.

A novel 3D Cartesian random sampling strategy for Compressive Sensing Magnetic Resonance Imaging.

PubMed

Valvano, Giuseppe; Martini, Nicola; Santarelli, Maria Filomena; Chiappino, Dante; Landini, Luigi

2015-01-01

In this work we propose a novel acquisition strategy for accelerated 3D Compressive Sensing Magnetic Resonance Imaging (CS-MRI). This strategy is based on a 3D cartesian sampling with random switching of the frequency encoding direction with other K-space directions. Two 3D sampling strategies are presented. In the first strategy, the frequency encoding direction is randomly switched with one of the two phase encoding directions. In the second strategy, the frequency encoding direction is randomly chosen between all the directions of the K-Space. These strategies can lower the coherence of the acquisition, in order to produce reduced aliasing artifacts and to achieve a better image quality after Compressive Sensing (CS) reconstruction. Furthermore, the proposed strategies can reduce the typical smoothing of CS due to the limited sampling of high frequency locations. We demonstrated by means of simulations that the proposed acquisition strategies outperformed the standard Compressive Sensing acquisition. This results in a better quality of the reconstructed images and in a greater achievable acceleration.

Laser diodes for sensing applications: adaptive cruise control and more

NASA Astrophysics Data System (ADS)

Heerlein, Joerg; Morgott, Stefan; Ferstl, Christian

2005-02-01

Adaptive Cruise Controls (ACC) and pre-crash sensors require an intelligent eye which can recognize traffic situations and deliver a 3-dimensional view. Both microwave RADAR and "Light RADAR" (LIDAR) systems are well suited as sensors. In order to utilize the advantages of LIDARs -- such as lower cost, simpler assembly and high reliability -- the key component, the laser diode, is of primary importance. Here, we present laser diodes which meet the requirements of the automotive industry.

Evolution of static allometries: adaptive change in allometric slopes of eye span in stalk-eyed flies.

PubMed

Voje, Kjetil L; Hansen, Thomas F

2013-02-01

Julian Huxley showed that within-species (static) allometric (power-law) relations can arise from proportional growth regulation with the exponent in the power law equaling the factor of proportionality. Allometric exponents may therefore be hard to change and act as constraints on the independent evolution of traits. In apparent contradiction to this, many empirical studies have concluded that static allometries are evolvable. Many of these studies have been based, however, on a broad definition of allometry that includes any monotonic shape change with size, and do not falsify the hypothesis of constrained narrow-sense allometry. Here, we present the first phylogenetic comparative study of narrow-sense allometric exponents based on a reanalysis of data on eye span and body size in stalk-eyed flies (Diopsidae). Consistent with a role in sexual selection, we found strong evidence that male slopes were tracking "optima" based on sexual dimorphism and relative male trait size. This tracking was slow, however, with estimated times of 2-3 million years for adaptation to exceed ancestral influence on the trait. Our results are therefore consistent with adaptive evolution on million-year time scales, but cannot rule out that static allometry may act as a constraint on eye-span adaptation at shorter time scales. © 2012 The Author(s). Evolution© 2012 The Society for the Study of Evolution.

Image super-resolution via adaptive filtering and regularization

NASA Astrophysics Data System (ADS)

Ren, Jingbo; Wu, Hao; Dong, Weisheng; Shi, Guangming

2014-11-01

Image super-resolution (SR) is widely used in the fields of civil and military, especially for the low-resolution remote sensing images limited by the sensor. Single-image SR refers to the task of restoring a high-resolution (HR) image from the low-resolution image coupled with some prior knowledge as a regularization term. One classic method regularizes image by total variation (TV) and/or wavelet or some other transform which introduce some artifacts. To compress these shortages, a new framework for single image SR is proposed by utilizing an adaptive filter before regularization. The key of our model is that the adaptive filter is used to remove the spatial relevance among pixels first and then only the high frequency (HF) part, which is sparser in TV and transform domain, is considered as the regularization term. Concretely, through transforming the original model, the SR question can be solved by two alternate iteration sub-problems. Before each iteration, the adaptive filter should be updated to estimate the initial HF. A high quality HF part and HR image can be obtained by solving the first and second sub-problem, respectively. In experimental part, a set of remote sensing images captured by Landsat satellites are tested to demonstrate the effectiveness of the proposed framework. Experimental results show the outstanding performance of the proposed method in quantitative evaluation and visual fidelity compared with the state-of-the-art methods.

Adaptive web sampling.

PubMed

Thompson, Steven K

2006-12-01

A flexible class of adaptive sampling designs is introduced for sampling in network and spatial settings. In the designs, selections are made sequentially with a mixture distribution based on an active set that changes as the sampling progresses, using network or spatial relationships as well as sample values. The new designs have certain advantages compared with previously existing adaptive and link-tracing designs, including control over sample sizes and of the proportion of effort allocated to adaptive selections. Efficient inference involves averaging over sample paths consistent with the minimal sufficient statistic. A Markov chain resampling method makes the inference computationally feasible. The designs are evaluated in network and spatial settings using two empirical populations: a hidden human population at high risk for HIV/AIDS and an unevenly distributed bird population.

Adaptive optics for the ESO-VLT

NASA Astrophysics Data System (ADS)

Merkle, Fritz

1989-04-01

This paper discusses adaptive optics, its performance, and its requirements for applications in astronomy to overcome limitations due to atmospheric turbulence. Guidelines for the implementation of these devices in telescopes are given, in particular for the Very Large Telescope (VLT) at ESO. It is intended to equip each one of the four 8-m telescopes of the VLT, which are arranged in a linear array with an independent adaptive optical system. These systems will serve the individual and the combined coude foci. A small-scale prototype adaptive system is under development. It is equipped with a 19-piezoelectric-actuator deformable mirror, a Shack-Hartmann-type wavefront sensor, and a dedicated wavefront computer for closing the feedback loop. This system is based on a polychromatic approach; i.e., it senses the wavefront in the visible, but the adaptive correction loop works at 3-5 microns.

Refractive index and temperature sensing in anisotropic silver nanostructures with stable photo-physical properties

NASA Astrophysics Data System (ADS)

Biswas, Subrata; Kumbhakar, Pathik

2018-01-01

In this report, we have demonstrated the refractive index and temperature-sensing abilities of polyvinylpyrrolidone (PVP)-protected silver nanostructures of triangular, connected and plate-like shapes. Interestingly, these nanostructures even after 2 and ½ years of syntheses showed plasmonic-sensing ability of temperature in the temperature range of 283-333 K. Also, refractive index (R.I.) sensing has been demonstrated in the aged samples and obtained the highest R.I. sensitivity of 306 nm/RIU in one of the sample. The synthesized samples have been kept in dark (inside desiccators) intentionally for the extended period of 2 and ½ years after synthesis and monitored intermittently their UV-Vis absorption and photoluminescence (PL) emission characteristics to check the functionally of the aged silver nanostructures. It has been found the samples remain well dispersed in different solvents and can forbid agglomeration even in 0.25 M NaCl solution. We have also demonstrated here fabrication of a flexible and transparent thin film of the synthesized samples in polyvinyl alcohol (PVA) matrix and investigated its low power continuous-wave (CW) nonlinear optical properties using spatial self-phase modulation (SSPM) technique. The nonlinear refractive index ( n 2) value of the film has been determined to be 5.6 × 10- 6 cm2/W at the He-Ne laser wavelength of 632.8 nm. In this report we have demonstrated temperature and R.I. sensing and also it has been demonstrated that the synthesized samples remain functional even after 2 and ½ years of synthesis. Also, samples may find potential applications in nonlinear optical phase modulation devices.

Concepts, laboratory, and telescope test results of the plenoptic camera as a wavefront sensor

NASA Astrophysics Data System (ADS)

Rodríguez-Ramos, L. F.; Montilla, I.; Fernández-Valdivia, J. J.; Trujillo-Sevilla, J. L.; Rodríguez-Ramos, J. M.

2012-07-01

The plenoptic camera has been proposed as an alternative wavefront sensor adequate for extended objects within the context of the design of the European Solar Telescope (EST), but it can also be used with point sources. Originated in the field of the Electronic Photography, the plenoptic camera directly samples the Light Field function, which is the four - dimensional representation of all the light entering a camera. Image formation can then be seen as the result of the photography operator applied to this function, and many other features of the light field can be exploited to extract information of the scene, like depths computation to extract 3D imaging or, as it will be specifically addressed in this paper, wavefront sensing. The underlying concept of the plenoptic camera can be adapted to the case of a telescope by using a lenslet array of the same f-number placed at the focal plane, thus obtaining at the detector a set of pupil images corresponding to every sampled point of view. This approach will generate a generalization of Shack-Hartmann, Curvature and Pyramid wavefront sensors in the sense that all those could be considered particular cases of the plenoptic wavefront sensor, because the information needed as the starting point for those sensors can be derived from the plenoptic image. Laboratory results obtained with extended objects, phase plates and commercial interferometers, and even telescope observations using stars and the Moon as an extended object are presented in the paper, clearly showing the capability of the plenoptic camera to behave as a wavefront sensor.

Adaptive Oceanographic Sampling in a Coastal Environment Using Autonomous Gliding Vehicles

DTIC Science & Technology

2003-08-01

cost autonomous vehicles with near-global range and modular sensor payload. Particular emphasis is placed on the development of adaptive sampling...environment. Secondary objectives include continued development of adaptive sampling strategies suitable for large fleets of slow-moving autonomous ... vehicles , and development and implementation of new oceanographic sensors and sampling methodologies. The main task completed was a complete redesign of

Common-Path Wavefront Sensing for Advanced Coronagraphs

NASA Technical Reports Server (NTRS)

Wallace, J. Kent; Serabyn, Eugene; Mawet, Dimitri

2012-01-01

Imaging of faint companions around nearby stars is not limited by either intrinsic resolution of a coronagraph/telescope system, nor is it strictly photon limited. Typically, it is both the magnitude and temporal variation of small phase and amplitude errors imparted to the electric field by elements in the optical system which will limit ultimate performance. Adaptive optics systems, particularly those with multiple deformable mirrors, can remove these errors, but they need to be sensed in the final image plane. If the sensing system is before the final image plane, which is typical for most systems, then the non-common path optics between the wavefront sensor and science image plane will lead to un-sensed errors. However, a new generation of high-performance coronagraphs naturally lend themselves to wavefront sensing in the final image plane. These coronagraphs and the wavefront sensing will be discussed, as well as plans for demonstrating this with a high-contrast system on the ground. Such a system will be a key system-level proof for a future space-based coronagraph mission, which will also be discussed.

Time-jittered marine seismic data acquisition via compressed sensing and sparsity-promoting wavefield reconstruction

NASA Astrophysics Data System (ADS)

Wason, H.; Herrmann, F. J.; Kumar, R.

2016-12-01

Current efforts towards dense shot (or receiver) sampling and full azimuthal coverage to produce high resolution images have led to the deployment of multiple source vessels (or streamers) across marine survey areas. Densely sampled marine seismic data acquisition, however, is expensive, and hence necessitates the adoption of sampling schemes that save acquisition costs and time. Compressed sensing is a sampling paradigm that aims to reconstruct a signal--that is sparse or compressible in some transform domain--from relatively fewer measurements than required by the Nyquist sampling criteria. Leveraging ideas from the field of compressed sensing, we show how marine seismic acquisition can be setup as a compressed sensing problem. A step ahead from multi-source seismic acquisition is simultaneous source acquisition--an emerging technology that is stimulating both geophysical research and commercial efforts--where multiple source arrays/vessels fire shots simultaneously resulting in better coverage in marine surveys. Following the design principles of compressed sensing, we propose a pragmatic simultaneous time-jittered time-compressed marine acquisition scheme where single or multiple source vessels sail across an ocean-bottom array firing airguns at jittered times and source locations, resulting in better spatial sampling and speedup acquisition. Our acquisition is low cost since our measurements are subsampled. Simultaneous source acquisition generates data with overlapping shot records, which need to be separated for further processing. We can significantly impact the reconstruction quality of conventional seismic data from jittered data and demonstrate successful recovery by sparsity promotion. In contrast to random (sub)sampling, acquisition via jittered (sub)sampling helps in controlling the maximum gap size, which is a practical requirement of wavefield reconstruction with localized sparsifying transforms. We illustrate our results with simulations of simultaneous time-jittered marine acquisition for 2D and 3D ocean-bottom cable survey.

Occupational conditions and workers' sense of community: variations by gender and race.

PubMed

Lambert, S J; Hopkins, K

1995-04-01

The literature is reviewed to define a sense of community in the workplace and to identify factors that may foster it. A model is developed and estimated with survey data from a culturally diverse sample of men and women performing lower-level jobs at a medium-sized manufacturing firm. Results of regression analyses are reported that correct for sample selection bias resulting from the lower response rates of minority workers. Findings suggest that well-designed jobs and supportive workplace relationships and policies are important in explaining workers' sense of community, defined as workers' perceptions of mutual commitment between employee and employer. Informal sources of support play a larger role in explaining men's sense of community, while formal sources of support are more important in explaining women's sense of community. Findings further suggest that African American workers, especially women, have a difficult time experiencing a sense of community at work.

Remote Sensing, Modeling, and In-Situ Measurements to Study the Spring and Summer Thermal Regime of the Kuparuk River, Northern Alaska

NASA Astrophysics Data System (ADS)

Floyd, A.; Liljedahl, A. K.; Gens, R.; Prakash, A.; Mann, D. H.

2011-12-01

A combined use of remote sensing techniques, modeling and in-situ measurements is a pragmatic approach to study arctic hydrology, given the vastness, complexity, and logistical challenges posed by most arctic watersheds. Remote sensing techniques can provide tools to assess the geospatial variations that form the integrated response of a river system and therefore provide important details to study climate change effects on the remote arctic environment. The proposed study tests the applicability of remote sensing and modeling techniques to map, monitor and compare river temperatures and river break-up in the coastal and foothill sections of the Kuparak River, which is an intensely studied watershed. We co-registered about hundred synthetic aperture radar (SAR) images from RADARSAT-1, ERS-1 and ERS-2 satellites, acquired during the months of May through July for a period between 1999 and 2010. Co-registration involved a Fast Fourier Transform (FFT) match of amplitude images. The offsets were then applied to the radiometrically corrected SAR images, converted to dB values, to generate an image stack. We applied a mask to extract pixels representing only the river, and used an adaptive threshold to delineate open water from frozen areas. The variation in river break-up can be bracketed by defining open vs. frozen river conditions. Summer river surface water temperatures will be simulated through the well-established HEC-RAS hydrologic software package and validated with field measurements. The three-pronged approach of using remote sensing, modeling and field measurements demonstrated in this study can be adapted to work for other watersheds across the Arctic.

Enhancement of gold recovery using bioleaching from gold concentrate

NASA Astrophysics Data System (ADS)

Choi, S. H.; Cho, K. H.; Kim, B. J.; Choi, N. C.; Park, C. Y.

2012-04-01

The gold in refractory ores is encapsulated as fine particles (sometimes at a molecular level) in the crystal structure of the sulfide (typically pyrite with or without arsenopyrite) matrix. This makes it impossible to extract a significant amount of refractory gold by cyanidation since the cyanide solution cannot penetrate the pyrite/arsenopyrite crystals and dissolve gold particles, even after fine grinding. To effectively extract gold from these ores, an oxidative pretreatment is necessary to break down the sulfide matrix. The most popular methods of pretreatment include nitric acid oxidation, roasting, pressure oxidation and biological oxidation by microorganisms. This study investigated the bioleaching efficiency of Au concentrate under batch experimental conditions (adaptation cycles and chemical composition adaptation) using the indigenous acidophilic bacteria collected from gold mine leachate in Sunsin gold mine, Korea. We conducted the batch experiments at two different chemical composition (CuSO4 and ZnSO4), two different adaptation cycles 1'st (3 weeks) and 2'nd (6 weeks). The results showed that the pH in the bacteria inoculating sample decreased than initial condition and Eh increased. In the chemical composition adaptation case, the leached accumulation content of Fe and Pb was exhibited in CuSO4 adaptation bacteria sample more than in ZnSO4 adaptation bacteria samples, possibly due to pre-adaptation effect on chalcopyrite (CuFeS2) in gold concentrate. And after 21 days on the CuSO4 adaptation cycles case, content of Fe and Pb was appeared at 1'st adaptation bacteria sample(Fe - 1.82 and Pb - 25.81 times per control sample) lower than at 2'nd adaptation bacteria sample(Fe - 2.87 and Pb - 62.05 times per control sample). This study indicates that adaptation chemical composition and adaptation cycles can play an important role in bioleaching of gold concentrate in eco-/economic metallurgy process.

A Conjoint Analysis Framework for Evaluating User Preferences in Machine Translation

PubMed Central

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

2013-01-01

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

Adaptive Learning and Risk Taking

ERIC Educational Resources Information Center

Denrell, Jerker

2007-01-01

Humans and animals learn from experience by reducing the probability of sampling alternatives with poor past outcomes. Using simulations, J. G. March (1996) illustrated how such adaptive sampling could lead to risk-averse as well as risk-seeking behavior. In this article, the author develops a formal theory of how adaptive sampling influences risk…

Intramolecular co-action of two independent photosensory modules in the fern phytochrome 3.

PubMed

Kanegae, Takeshi

2015-01-01

Fern phytochrome3/neochrome1 (phy3/neo1) is a chimeric photoreceptor composed of a phytochrome-chromophore binding domain and an almost full-length phototropin. phy3 thus contains two different light-sensing modules; a red/far-red light receptor phytochrome and a blue light receptor phototropin. phy3 induces both red light- and blue light-dependent phototropism in phototropin-deficient Arabidopsis thaliana (phot1 phot2) seedlings. The red-light response is dependent on the phytochrome module of phy3, and the blue-light response is dependent on the phototropin module. We recently showed that both the phototropin-sensing module and the phytochrome-sensing module mediate the blue light-dependent phototropic response. Particularly under low-light conditions, these two light-sensing modules cooperate to induce the blue light-dependent phototropic response. This intramolecular co-action of two independent light-sensing modules in phy3 enhances light sensitivity, and perhaps allowed ferns to adapt to the low-light canopy conditions present in angiosperm forests.

Fiber optic shape sensing for monitoring of flexible structures

NASA Astrophysics Data System (ADS)

Lally, Evan M.; Reaves, Matt; Horrell, Emily; Klute, Sandra; Froggatt, Mark E.

2012-04-01

Recent advances in materials science have resulted in a proliferation of flexible structures for high-performance civil, mechanical, and aerospace applications. Large aspect-ratio aircraft wings, composite wind turbine blades, and suspension bridges are all designed to meet critical performance targets while adapting to dynamic loading conditions. By monitoring the distributed shape of a flexible component, fiber optic shape sensing technology has the potential to provide valuable data during design, testing, and operation of these smart structures. This work presents a demonstration of such an extended-range fiber optic shape sensing technology. Three-dimensional distributed shape and position sensing is demonstrated over a 30m length using a monolithic silica fiber with multiple optical cores. A novel, helicallywound geometry endows the fiber with the capability to convert distributed strain measurements, made using Optical Frequency-Domain Reflectometry (OFDR), to a measurement of curvature, twist, and 3D shape along its entire length. Laboratory testing of the extended-range shape sensing technology shows

Distributed multifunctional sensor network for composite structural state sensing

NASA Astrophysics Data System (ADS)

Qing, Xinlin P.; Wang, Yishou; Gao, Limin; Kumar, Amrita

2012-04-01

Advanced fiber reinforced composite materials are becoming the main structural materials of next generation of aircraft because of their high strength and stiffness to weight ratios, and strong designability. In order to take full advantages of composite materials, there is a need to develop an embeddable multifunctional sensing system to allow a structure to "feel" and "think" its structural state. In this paper, the concept of multifunctional sensor network integrated with a structure, similar to the human nervous system, has been developed. Different types of network sensors are permanently integrated within a composite structure to sense structural strain, temperature, moisture, aerodynamic pressure; monitor external impact on the structure; and detect structural damages. Utilizing this revolutionary concept, future composite structures can be designed and manufactured to provide multiple modes of information, so that the structures have the capabilities for intelligent sensing, environmental adaptation and multi-functionality. The challenges for building such a structural state sensing system and some solutions to address the challenges are also discussed in the paper.

Personal Factors Underlying Resilience in Adolescence: Cross-Cultural Validity of the Prince-Embury Model.

PubMed

Villasana, Mercedes; Alonso-Tapia, Jesús; Ruiz, Miguel A

2017-09-25

Resiliency personality factors are supposed to underlie resilience. To get evidence on this supposition, the Prince-Embury scales (PES) for adolescents were adapted to the Spanish population. Then, the relationship between the resiliency variables sense of mastery, sense of relatedness and emotional reactivity -assessed with the PES- with resilience -assessed with the Subjective Resilience Questionnaire (SRQ)- were analyzed, as well as the role of social integration within this relationship. Data from 1083 adolescents were analyzed using confirmatory techniques (CFA, PALV). CFA of PES displayed a good fit to the model (CFI: .95). Path-analysis showed that sense of mastery and emotional reactivity predict resilience as expected, but also that, contrary to expectations based on Prince-Embury's theory, sense of relatedness and resilience are not related, either directly, or through social integration. Being related and socially integrated probably favors well-being, but it may not favor resilience unless associated to Sense of Mastery, at least in adolescence.

Integrated sensing and actuation of dielectric elastomer actuator

NASA Astrophysics Data System (ADS)

Ye, Zhihang; Chen, Zheng

2017-04-01

Dielectric elastomer (DE) is a type of soft actuating material, the shape of which can be changed under electrical voltage stimuli. DE materials have great potential in applications involving energy harvesters, micro-manipulators, and adaptive optics. In this paper, a stripe DE actuator with integrated sensing and actuation is designed and fabricated, and characterized through several experiments. Considering the actuator's capacitor-like structure and its deform mechanism, detecting the actuator's displacement through the actuator's circuit feature is a potential approach. A self-sensing scheme that adds a high frequency probing signal into actuation signal is developed. A fast Fourier transform (FFT) algorithm is used to extract the magnitude change of the probing signal, and a non-linear fitting method and artificial neural network (ANN) approach are utilized to reflect the relationship between the probing signal and the actuator's displacement. Experimental results showed this structure has capability of performing self-sensing and actuation, simultaneously. With an enhanced ANN, the self-sensing scheme can achieve 2.5% accuracy.

2005 AG20/20 Annual Review

NASA Technical Reports Server (NTRS)

Ross, Kenton W.; McKellip, Rodney D.

2005-01-01

Topics covered include: Implementation and Validation of Sensor-Based Site-Specific Crop Management; Enhanced Management of Agricultural Perennial Systems (EMAPS) Using GIS and Remote Sensing; Validation and Application of Geospatial Information for Early Identification of Stress in Wheat; Adapting and Validating Precision Technologies for Cotton Production in the Mid-Southern United States - 2004 Progress Report; Development of a System to Automatically Geo-Rectify Images; Economics of Precision Agriculture Technologies in Cotton Production-AG 2020 Prescription Farming Automation Algorithms; Field Testing a Sensor-Based Applicator for Nitrogen and Phosphorus Application; Early Detection of Citrus Diseases Using Machine Vision and DGPS; Remote Sensing of Citrus Tree Stress Levels and Factors; Spectral-based Nitrogen Sensing for Citrus; Characterization of Tree Canopies; In-field Sensing of Shallow Water Tables and Hydromorphic Soils with an Electromagnetic Induction Profiler; Maintaining the Competitiveness of Tree Fruit Production Through Precision Agriculture; Modeling and Visualizing Terrain and Remote Sensing Data for Research and Education in Precision Agriculture; Thematic Soil Mapping and Crop-Based Strategies for Site-Specific Management; and Crop-Based Strategies for Site-Specific Management.

Nutrient sensing modulates malaria parasite virulence

PubMed Central

Mancio-Silva, Liliana; Slavic, Ksenija; Grilo Ruivo, Margarida T.; Grosso, Ana Rita; Modrzynska, Katarzyna K.; Vera, Iset Medina; Sales-Dias, Joana; Gomes, Ana Rita; MacPherson, Cameron Ross; Crozet, Pierre; Adamo, Mattia; Baena-Gonzalez, Elena; Tewari, Rita; Llinás, Manuel; Billker, Oliver; Mota, Maria M.

2017-01-01

The lifestyle of intracellular pathogens, such as malaria parasites, is intimately connected to that of their host(s), primarily for nutrient supply. Nutrients act not only as primary sources of energy but also as regulators of gene expression, metabolism and growth, through various signaling networks that confer to cells the ability to sense and adapt to varying environmental conditions1,2. Canonical nutrient-sensing pathways are presumably absent in the causing agent of malaria Plasmodium3–5, thus raising the question of whether these parasites possess the capacity to sense and cope with host nutrient fluctuations. Here, we show that Plasmodium blood-stage parasites actively respond to host dietary calorie alterations through a rearrangement of their transcriptome accompanied by a significant adjustment of their multiplication rate. A kinome analysis combined with chemical and genetic approaches identified KIN as a critical regulator that mediates sensing of nutrients and controls a transcriptional response to the host nutritional status. KIN shares homology to SNF1/AMPKα and yeast complementation studies suggest functional conservation of an ancient cellular energy sensing pathway. Overall, these findings reveal a key parasite nutrient-sensing mechanism that is critical to modulate parasite replication and virulence. PMID:28678779

Wavefront detection method of a single-sensor based adaptive optics system.

PubMed

Wang, Chongchong; Hu, Lifa; Xu, Huanyu; Wang, Yukun; Li, Dayu; Wang, Shaoxin; Mu, Quanquan; Yang, Chengliang; Cao, Zhaoliang; Lu, Xinghai; Xuan, Li

2015-08-10

In adaptive optics system (AOS) for optical telescopes, the reported wavefront sensing strategy consists of two parts: a specific sensor for tip-tilt (TT) detection and another wavefront sensor for other distortions detection. Thus, a part of incident light has to be used for TT detection, which decreases the light energy used by wavefront sensor and eventually reduces the precision of wavefront correction. In this paper, a single Shack-Hartmann wavefront sensor based wavefront measurement method is presented for both large amplitude TT and other distortions' measurement. Experiments were performed for testing the presented wavefront method and validating the wavefront detection and correction ability of the single-sensor based AOS. With adaptive correction, the root-mean-square of residual TT was less than 0.2 λ, and a clear image was obtained in the lab. Equipped on a 1.23-meter optical telescope, the binary stars with angle distance of 0.6″ were clearly resolved using the AOS. This wavefront measurement method removes the separate TT sensor, which not only simplifies the AOS but also saves light energy for subsequent wavefront sensing and imaging, and eventually improves the detection and imaging capability of the AOS.

Hierarchical adaptation scheme for multiagent data fusion and resource management in situation analysis

NASA Astrophysics Data System (ADS)

Benaskeur, Abder R.; Roy, Jean

2001-08-01

Sensor Management (SM) has to do with how to best manage, coordinate and organize the use of sensing resources in a manner that synergistically improves the process of data fusion. Based on the contextual information, SM develops options for collecting further information, allocates and directs the sensors towards the achievement of the mission goals and/or tunes the parameters for the realtime improvement of the effectiveness of the sensing process. Conscious of the important role that SM has to play in modern data fusion systems, we are currently studying advanced SM Concepts that would help increase the survivability of the current Halifax and Iroquois Class ships, as well as their possible future upgrades. For this purpose, a hierarchical scheme has been proposed for data fusion and resource management adaptation, based on the control theory and within the process refinement paradigm of the JDL data fusion model, and taking into account the multi-agent model put forward by the SASS Group for the situation analysis process. The novelty of this work lies in the unified framework that has been defined for tackling the adaptation of both the fusion process and the sensor/weapon management.

Adaptation to vestibular disorientation. XII, Habituation of vestibular responses : an overview.

DOT National Transportation Integrated Search

1974-03-01

Vestibular and visual mechanisms are critical sensing systems in spatial orientation and in spatial disorientation. In aviation or space environments in particular, the role of the vestibular system is central to the problems of spatial disorientatio...

Adaptive Combinatorial Multimodal Sensing Physics & Methods

DTIC Science & Technology

2012-03-07

group on doped Q-dot studies • NRL: support in-house polarimetry filter research effort • DARPA: coordinate w/Nibir Dhar in sensors -- their...International: • National Cheng Kung University, Taiwan: CNTs • Taras Shevchenko University, Kiev, Ukraine: polarimetry Coordination/Conferences

Development of gold nanoparticle-aptamer-based LSPR sensing chips for the rapid detection of Salmonella typhimurium in pork meat.

PubMed

Oh, Seo Yeong; Heo, Nam Su; Shukla, Shruti; Cho, Hye-Jin; Vilian, A T Ezhil; Kim, Jinwoon; Lee, Sang Yup; Han, Young-Kyu; Yoo, Seung Min; Huh, Yun Suk

2017-08-31

A non-labeled, portable plasmonic biosensor-based device was developed to enable the ultra-sensitive and selective detection of Salmonella typhimurium in pork meat samples. Specifically, a plasmonic sensor, using the self-assembly of gold nanoparticles (AuNPs) to achieve a regulated diameter of 20 nm for the AuNP monolayers, was used to conduct high-density deposition on a transparent substrate, which produced longitudinal wavelength extinction shifts via a localized surface plasmon resonance (LSPR) signal. The developed aptamers conjugated to the LSPR sensing chips revealed an ultra-sensitive upper limit of detection (LOD) of approximately 10 4 cfu/mL for S. typhimurium in pure culture under the optimal assay conditions, with a total analysis time of 30-35 min. When the LSPR sensing chips were applied on artificially contaminated pork meat samples, S. typhimurium in the spiked pork meat samples was also detected at an LOD of 1.0 × 10 4 cfu/mL. The developed method could detect S. typhimurium in spiked pork meat samples without a pre-enrichment step. Additionally, the LSPR sensing chips developed against S. typhimurium were not susceptible to any effect of the food matrix or background contaminant microflora. These findings confirmed that the developed gold nanoparticle-aptamer-based LSPR sensing chips could facilitate sensitive detection of S. typhimurium in food samples.

Photoperiodic growth control in perennial trees.

PubMed

Azeez, Abdul; Sane, Aniruddha P

2015-01-01

Plants have to cope with changing seasons and adverse environmental conditions. Being sessile, plants have developed elaborate mechanisms for their survival that allow them to sense and adapt to the environment and reproduce successfully. A major adaptive trait for the survival of trees of temperate and boreal forests is the induction of growth cessation in anticipation of winters. In the last few years enormous progress has been made to elucidate the molecular mechanisms underlying SDs induced growth cessation in model perennial tree hybrid aspen (Populus tremula × P. tremuloides). In this review we discuss the molecular mechanism underlying photoperiodic control of growth cessation and adaptive responses.

To Exist as a Case Manager Is to Constantly Change; to Be Successful, You Must Constantly Adapt.

PubMed

Tahan, Hussein M

Change is inevitable whether in personal or professional lives. Case management practice is always evolving on the basis of the dynamic nature of the U.S. health care environment. Effective case managers are those who possess an adaptive mind-set, recognize the importance to change to maintain success, and remain relevant. They also demonstrate a sense of accountability and responsibility for own learning, professional development, and acquisition of new skills and knowledge. This editorial discusses the nature of change and adaptation and presents key strategies for case managers to remain relevant and effective in dynamic practice environments.

A Structure-Adaptive Hybrid RBF-BP Classifier with an Optimized Learning Strategy

PubMed Central

Wen, Hui; Xie, Weixin; Pei, Jihong

2016-01-01

This paper presents a structure-adaptive hybrid RBF-BP (SAHRBF-BP) classifier with an optimized learning strategy. SAHRBF-BP is composed of a structure-adaptive RBF network and a BP network of cascade, where the number of RBF hidden nodes is adjusted adaptively according to the distribution of sample space, the adaptive RBF network is used for nonlinear kernel mapping and the BP network is used for nonlinear classification. The optimized learning strategy is as follows: firstly, a potential function is introduced into training sample space to adaptively determine the number of initial RBF hidden nodes and node parameters, and a form of heterogeneous samples repulsive force is designed to further optimize each generated RBF hidden node parameters, the optimized structure-adaptive RBF network is used for adaptively nonlinear mapping the sample space; then, according to the number of adaptively generated RBF hidden nodes, the number of subsequent BP input nodes can be determined, and the overall SAHRBF-BP classifier is built up; finally, different training sample sets are used to train the BP network parameters in SAHRBF-BP. Compared with other algorithms applied to different data sets, experiments show the superiority of SAHRBF-BP. Especially on most low dimensional and large number of data sets, the classification performance of SAHRBF-BP outperforms other training SLFNs algorithms. PMID:27792737

Evaluating sampling designs by computer simulation: A case study with the Missouri bladderpod

USGS Publications Warehouse

Morrison, L.W.; Smith, D.R.; Young, C.; Nichols, D.W.

2008-01-01

To effectively manage rare populations, accurate monitoring data are critical. Yet many monitoring programs are initiated without careful consideration of whether chosen sampling designs will provide accurate estimates of population parameters. Obtaining accurate estimates is especially difficult when natural variability is high, or limited budgets determine that only a small fraction of the population can be sampled. The Missouri bladderpod, Lesquerella filiformis Rollins, is a federally threatened winter annual that has an aggregated distribution pattern and exhibits dramatic interannual population fluctuations. Using the simulation program SAMPLE, we evaluated five candidate sampling designs appropriate for rare populations, based on 4 years of field data: (1) simple random sampling, (2) adaptive simple random sampling, (3) grid-based systematic sampling, (4) adaptive grid-based systematic sampling, and (5) GIS-based adaptive sampling. We compared the designs based on the precision of density estimates for fixed sample size, cost, and distance traveled. Sampling fraction and cost were the most important factors determining precision of density estimates, and relative design performance changed across the range of sampling fractions. Adaptive designs did not provide uniformly more precise estimates than conventional designs, in part because the spatial distribution of L. filiformis was relatively widespread within the study site. Adaptive designs tended to perform better as sampling fraction increased and when sampling costs, particularly distance traveled, were taken into account. The rate that units occupied by L. filiformis were encountered was higher for adaptive than for conventional designs. Overall, grid-based systematic designs were more efficient and practically implemented than the others. ?? 2008 The Society of Population Ecology and Springer.

Lateral Coherence and Mixing in the Coastal Ocean: Adaptive Sampling using Gliders

DTIC Science & Technology

2012-09-30

Adaptive Sampling using Gliders R. Kipp Shearman Jonathan D. Nash James N. Moum John A. Barth College of Oceanic & Atmospheric Sciences Oregon State...persistent on O (3 day) timescales, so are ideally suited to be adaptively sampled by autonomous gliders that actively report both turbulent and...plan to deploy 4 AUV gliders to perform intensive, adaptive surveys. Newly-enhanced to measure turbulent mixing, water-column currents and dye

Lateral Coherence and Mixing in the Coastal Ocean: Adaptive Sampling using Gliders

DTIC Science & Technology

2011-09-30

Coherence and Mixing in the Coastal Ocean: Adaptive Sampling using Gliders R. Kipp Shearman Jonathan D. Nash James N. Moum John A. Barth College of...These structures evolve yet are often persistent on O (3 day) timescales, so are ideally suited to be adaptively sampled by autonomous gliders that...processes driving lateral dispersion, we plan to deploy 4 AUV gliders to perform intensive, adaptive surveys. Newly-enhanced to measure turbulent mixing

Are You Ready to Have Fun? The Spanish State Form of the State-Trait-Cheerfulness Inventory.

PubMed

López-Benítez, Raúl; Acosta, Alberto; Lupiáñez, Juan; Carretero-Dios, Hugo

2017-09-21

Although cheerfulness, seriousness, and bad mood as traits have been widely studied as the basis of sense of humor, data are scarce regarding the same dimensions as states. In this study, we adapted the state form of the State-Trait-Cheerfulness Inventory (STCI-S) into Spanish. At the same time, we empirically tested new predictions. We assessed 5 independent samples accounting for 1,029 participants (647 women) with ages ranging from 18 to 78 years. We confirmed the 3-dimensional structure as well as a strong measurement invariance between men and women. The internal consistency of the scale was satisfactory, the expected intercorrelations emerged, and the convergence between states and traits was corroborated. We also confirmed that the STCI-S's items were sensitive to affective changes in the environment. A longitudinal stability study of the state-trait dimensions using latent state-trait (LST) models revealed that all three trait measures capture mostly stable interindividual differences, with occasion-specific effects mainly in the state dimensions. Finally, we found that the STCI-S dimensions were related to state well-being. The results suggest that the STCI-S is a valid option for measuring the state basis of sense of humor in the Spanish population.

Analysis of variograms with various sample sizes from a multispectral image

USDA-ARS?s Scientific Manuscript database

Variogram plays a crucial role in remote sensing application and geostatistics. It is very important to estimate variogram reliably from sufficient data. In this study, the analysis of variograms with various sample sizes of remotely sensed data was conducted. A 100x100-pixel subset was chosen from ...

Analysis of variograms with various sample sizes from a multispectral image

USDA-ARS?s Scientific Manuscript database

Variograms play a crucial role in remote sensing application and geostatistics. In this study, the analysis of variograms with various sample sizes of remotely sensed data was conducted. A 100 X 100 pixel subset was chosen from an aerial multispectral image which contained three wavebands, green, ...

Self-Supervised Learning of Terrain Traversability from Proprioceptive Sensors

NASA Technical Reports Server (NTRS)

Bajracharya, Max; Howard, Andrew B.; Matthies, Larry H.

2009-01-01

Robust and reliable autonomous navigation in unstructured, off-road terrain is a critical element in making unmanned ground vehicles a reality. Existing approaches tend to rely on evaluating the traversability of terrain based on fixed parameters obtained via testing in specific environments. This results in a system that handles the terrain well that it trained in, but is unable to process terrain outside its test parameters. An adaptive system does not take the place of training, but supplements it. Whereas training imprints certain environments, an adaptive system would imprint terrain elements and the interactions amongst them, and allow the vehicle to build a map of local elements using proprioceptive sensors. Such sensors can include velocity, wheel slippage, bumper hits, and accelerometers. Data obtained by the sensors can be compared to observations from ranging sensors such as cameras and LADAR (laser detection and ranging) in order to adapt to any kind of terrain. In this way, it could sample its surroundings not only to create a map of clear space, but also of what kind of space it is and its composition. By having a set of building blocks consisting of terrain features, a vehicle can adapt to terrain that it has never seen before, and thus be robust to a changing environment. New observations could be added to its library, enabling it to infer terrain types that it wasn't trained on. This would be very useful in alien environments, where many of the physical features are known, but some are not. For example, a seemingly flat, hard plain could actually be soft sand, and the vehicle would sense the sand and avoid it automatically.

Identifying signatures of natural selection in Tibetan and Andean populations using dense genome scan data.

PubMed

Bigham, Abigail; Bauchet, Marc; Pinto, Dalila; Mao, Xianyun; Akey, Joshua M; Mei, Rui; Scherer, Stephen W; Julian, Colleen G; Wilson, Megan J; López Herráez, David; Brutsaert, Tom; Parra, Esteban J; Moore, Lorna G; Shriver, Mark D

2010-09-09

High-altitude hypoxia (reduced inspired oxygen tension due to decreased barometric pressure) exerts severe physiological stress on the human body. Two high-altitude regions where humans have lived for millennia are the Andean Altiplano and the Tibetan Plateau. Populations living in these regions exhibit unique circulatory, respiratory, and hematological adaptations to life at high altitude. Although these responses have been well characterized physiologically, their underlying genetic basis remains unknown. We performed a genome scan to identify genes showing evidence of adaptation to hypoxia. We looked across each chromosome to identify genomic regions with previously unknown function with respect to altitude phenotypes. In addition, groups of genes functioning in oxygen metabolism and sensing were examined to test the hypothesis that particular pathways have been involved in genetic adaptation to altitude. Applying four population genetic statistics commonly used for detecting signatures of natural selection, we identified selection-nominated candidate genes and gene regions in these two populations (Andeans and Tibetans) separately. The Tibetan and Andean patterns of genetic adaptation are largely distinct from one another, with both populations showing evidence of positive natural selection in different genes or gene regions. Interestingly, one gene previously known to be important in cellular oxygen sensing, EGLN1 (also known as PHD2), shows evidence of positive selection in both Tibetans and Andeans. However, the pattern of variation for this gene differs between the two populations. Our results indicate that several key HIF-regulatory and targeted genes are responsible for adaptation to high altitude in Andeans and Tibetans, and several different chromosomal regions are implicated in the putative response to selection. These data suggest a genetic role in high-altitude adaption and provide a basis for future genotype/phenotype association studies necessary to confirm the role of selection-nominated candidate genes and gene regions in adaptation to altitude.

Identifying Signatures of Natural Selection in Tibetan and Andean Populations Using Dense Genome Scan Data

PubMed Central

Bigham, Abigail; Bauchet, Marc; Pinto, Dalila; Mao, Xianyun; Akey, Joshua M.; Mei, Rui; Scherer, Stephen W.; Julian, Colleen G.; Wilson, Megan J.; López Herráez, David; Brutsaert, Tom; Parra, Esteban J.; Moore, Lorna G.; Shriver, Mark D.

2010-01-01

High-altitude hypoxia (reduced inspired oxygen tension due to decreased barometric pressure) exerts severe physiological stress on the human body. Two high-altitude regions where humans have lived for millennia are the Andean Altiplano and the Tibetan Plateau. Populations living in these regions exhibit unique circulatory, respiratory, and hematological adaptations to life at high altitude. Although these responses have been well characterized physiologically, their underlying genetic basis remains unknown. We performed a genome scan to identify genes showing evidence of adaptation to hypoxia. We looked across each chromosome to identify genomic regions with previously unknown function with respect to altitude phenotypes. In addition, groups of genes functioning in oxygen metabolism and sensing were examined to test the hypothesis that particular pathways have been involved in genetic adaptation to altitude. Applying four population genetic statistics commonly used for detecting signatures of natural selection, we identified selection-nominated candidate genes and gene regions in these two populations (Andeans and Tibetans) separately. The Tibetan and Andean patterns of genetic adaptation are largely distinct from one another, with both populations showing evidence of positive natural selection in different genes or gene regions. Interestingly, one gene previously known to be important in cellular oxygen sensing, EGLN1 (also known as PHD2), shows evidence of positive selection in both Tibetans and Andeans. However, the pattern of variation for this gene differs between the two populations. Our results indicate that several key HIF-regulatory and targeted genes are responsible for adaptation to high altitude in Andeans and Tibetans, and several different chromosomal regions are implicated in the putative response to selection. These data suggest a genetic role in high-altitude adaption and provide a basis for future genotype/phenotype association studies necessary to confirm the role of selection-nominated candidate genes and gene regions in adaptation to altitude. PMID:20838600

Self-Referenced Smartphone-Based Nanoplasmonic Imaging Platform for Colorimetric Biochemical Sensing.

PubMed

Wang, Xinhao; Chang, Te-Wei; Lin, Guohong; Gartia, Manas Ranjan; Liu, Gang Logan

2017-01-03

Colorimetric sensors usually suffer due to errors from variation in light source intensity, the type of light source, the Bayer filter algorithm, and the sensitivity of the camera to incoming light. Here, we demonstrate a self-referenced portable smartphone-based plasmonic sensing platform integrated with an internal reference sample along with an image processing method to perform colorimetric sensing. Two sensing principles based on unique nanoplasmonics enabled phenomena from a nanostructured plasmonic sensor, named as nanoLCA (nano Lycurgus cup array), were demonstrated here for colorimetric biochemical sensing: liquid refractive index sensing and optical absorbance enhancement sensing. Refractive indices of colorless liquids were measured by simple smartphone imaging and color analysis. Optical absorbance enhancement in the colorimetric biochemical assay was achieved by matching the plasmon resonance wavelength with the chromophore's absorbance peak wavelength. Such a sensing mechanism improved the limit of detection (LoD) by 100 times in a microplate reader format. Compared with a traditional colorimetric assay such as urine testing strips, a smartphone plasmon enhanced colorimetric sensing system provided 30 times improvement in the LoD. The platform was applied for simulated urine testing to precisely identify the samples with higher protein concentration, which showed potential point-of-care and early detection of kidney disease with the smartphone plasmonic resonance sensing system.

Carbon dioxide-sensing in organisms and its implications for human disease

PubMed Central

Cummins, Eoin P.; Selfridge, Andrew C.; Sporn, Peter H.; Sznajder, Jacob I.; Taylor, Cormac T.

2013-01-01

The capacity of organisms to sense changes in the levels of internal and external gases and to respond accordingly is central to a range of physiologic and pathophysiologic processes. Carbon dioxide, a primary product of oxidative metabolism is one such gas that can be sensed by both prokaryotic and eukaryotic cells and in response to altered levels, elicit the activation of multiple adaptive pathways. The outcomes of activating CO2-sensitive pathways in various species include increased virulence of fungal and bacterial pathogens, prey-seeking behavior in insects as well as taste perception, lung function, and the control of immunity in mammals. In this review, we discuss what is known about the mechanisms underpinning CO2 sensing across a range of species and consider the implications of this for physiology, disease progression, and the possibility of developing new therapeutics for inflammatory and infectious disease. PMID:24045706

Phase I Marine Archeological Remote Sensing Survey of the Proposed Mississippi River Sand Borrow Sites for the Louisiana Coastal Area Barrier Shoreline Restoration Project, Plaquemines Parish, Louisiana

DTIC Science & Technology

2008-09-01

massive, organically-rich, clayey silts and silty clays that contain ostracods, the remains of fiddler crabs and crayfish, and gastropods such as...that big game hunting was a dominant adaptive strategy in the southeast is less certain because of the regional environmental...evidence suggests that a degree of continuity existed between the adaptations of prehistoric peoples living in northern forests and those who lived in

Media Access Time-Rearrangement of Wireless LAN for a Multi-Radio Collocated Platform

NASA Astrophysics Data System (ADS)

Shin, Sang-Heon; Kim, Chul; Park, Sang Kyu

With the advent of new Radio Access Technologies (RATs), it is inevitable that several RATs will co-exist, especially in the license-exempt band. In this letter, we present an in-depth adaptation of the proactive time-rearrangement (PATRA) scheme for IEEE 802.11 WLAN. The PATRA is a time division approach for reducing interference from a multi-radio device. Because IEEE 802.11 is based on carrier sensing and contention mechanism, it is the most suitable candidate to adapt the PATRA.

FUEL HANDLING MECHANISM

DOEpatents

Koch, L.J.; Hutter, E.

1960-02-01

A remotely operable handling device specifically adapted for the handling of vertically disposed fuel rods in a nuclear reactor was developed. The device consists essentially of an elongated tubular member having a gripping device at the lower end of the pivoted jaw type adapted to grip an enlarged head on the upper end of the workpiece. The device includes a sensing element which engages the enlarged head and is displaced to remotely indicate when the workpiece is in the proper position to be engaged by the jaws.

Adaptive temporal compressive sensing for video with motion estimation

NASA Astrophysics Data System (ADS)

Wang, Yeru; Tang, Chaoying; Chen, Yueting; Feng, Huajun; Xu, Zhihai; Li, Qi

2018-04-01

In this paper, we present an adaptive reconstruction method for temporal compressive imaging with pixel-wise exposure. The motion of objects is first estimated from interpolated images with a designed coding mask. With the help of motion estimation, image blocks are classified according to the degree of motion and reconstructed with the corresponding dictionary, which was trained beforehand. Both the simulation and experiment results show that the proposed method can obtain accurate motion information before reconstruction and efficiently reconstruct compressive video.

LORAKS makes better SENSE: Phase-constrained partial fourier SENSE reconstruction without phase calibration.

PubMed

Kim, Tae Hyung; Setsompop, Kawin; Haldar, Justin P

2017-03-01

Parallel imaging and partial Fourier acquisition are two classical approaches for accelerated MRI. Methods that combine these approaches often rely on prior knowledge of the image phase, but the need to obtain this prior information can place practical restrictions on the data acquisition strategy. In this work, we propose and evaluate SENSE-LORAKS, which enables combined parallel imaging and partial Fourier reconstruction without requiring prior phase information. The proposed formulation is based on combining the classical SENSE model for parallel imaging data with the more recent LORAKS framework for MR image reconstruction using low-rank matrix modeling. Previous LORAKS-based methods have successfully enabled calibrationless partial Fourier parallel MRI reconstruction, but have been most successful with nonuniform sampling strategies that may be hard to implement for certain applications. By combining LORAKS with SENSE, we enable highly accelerated partial Fourier MRI reconstruction for a broader range of sampling trajectories, including widely used calibrationless uniformly undersampled trajectories. Our empirical results with retrospectively undersampled datasets indicate that when SENSE-LORAKS reconstruction is combined with an appropriate k-space sampling trajectory, it can provide substantially better image quality at high-acceleration rates relative to existing state-of-the-art reconstruction approaches. The SENSE-LORAKS framework provides promising new opportunities for highly accelerated MRI. Magn Reson Med 77:1021-1035, 2017. © 2016 International Society for Magnetic Resonance in Medicine. © 2016 International Society for Magnetic Resonance in Medicine.

Small RNA Library Preparation Method for Next-Generation Sequencing Using Chemical Modifications to Prevent Adapter Dimer Formation.

PubMed

Shore, Sabrina; Henderson, Jordana M; Lebedev, Alexandre; Salcedo, Michelle P; Zon, Gerald; McCaffrey, Anton P; Paul, Natasha; Hogrefe, Richard I

2016-01-01

For most sample types, the automation of RNA and DNA sample preparation workflows enables high throughput next-generation sequencing (NGS) library preparation. Greater adoption of small RNA (sRNA) sequencing has been hindered by high sample input requirements and inherent ligation side products formed during library preparation. These side products, known as adapter dimer, are very similar in size to the tagged library. Most sRNA library preparation strategies thus employ a gel purification step to isolate tagged library from adapter dimer contaminants. At very low sample inputs, adapter dimer side products dominate the reaction and limit the sensitivity of this technique. Here we address the need for improved specificity of sRNA library preparation workflows with a novel library preparation approach that uses modified adapters to suppress adapter dimer formation. This workflow allows for lower sample inputs and elimination of the gel purification step, which in turn allows for an automatable sRNA library preparation protocol.

Preparation and characterization of Pt loaded WO3 films suitable for gas sensing applications

NASA Astrophysics Data System (ADS)

Jolly Bose, R.; Illyasukutty, Navas; Tan, K. S.; Rawat, R. S.; Vadakke Matham, Murukesan; Kohler, Heinz; Mahadevan Pillai, V. P.

2018-05-01

This paper presents the preparation of nanostructured platinum (Pt) loaded tungsten oxide (WO3) thin films by radio frequency (RF) magnetron sputtering technique. Even though, Pt loading does not produce any phase change in WO3 lattice, it deteriorates the crystalline quality and induces defects on WO3 films. The Pt loading in WO3 has profound impact on structural and optical properties of the films by which the particle size, lattice strain and optical band gap energy are reduced. Nanoporous film with reduced particle size is obtained for 5 wt% Pt loaded WO3 sample which is crucial for gas sensors. Hence the sensing response of 5 wt% Pt loaded sample is tested towards carbon monoxide (CO) gas along with pure WO3 sample. The sensing response of Pt loaded sample is nearly 15 times higher than pure WO3 sample in non-humid ambience at an operating temperature 200 °C. This indicates the suitability of the prepared films for gas sensors. The sensing response of pure WO3 film depends on the humidity while the Pt loaded WO3 film shows stable response in both humid and non-humid ambiences.

Electrochemical sensing of heavy metal ions with inorganic, organic and bio-materials.

PubMed

Cui, Lin; Wu, Jie; Ju, Huangxian

2015-01-15

As heavy metal ions severely harm human health, it is important to develop simple, sensitive and accurate methods for their detection in environment and food. Electrochemical detection featured with short analytical time, low power cost, high sensitivity and easy adaptability for in-situ measurement is one of the most developed methods. This review introduces briefly the recent achievements in electrochemical sensing of heavy metal ions with inorganic, organic and bio-materials modified electrodes. In particular, the unique properties of inorganic nanomaterials, organic small molecules or their polymers, enzymes and nucleic acids for detection of heavy metal ions are highlighted. By employing some representative examples, the design and sensing mechanisms of these electrodes are discussed. Copyright © 2014 Elsevier B.V. All rights reserved.

Flight Testing of Terrain-Relative Navigation and Large-Divert Guidance on a VTVL Rocket

NASA Technical Reports Server (NTRS)

Trawny, Nikolas; Benito, Joel; Tweddle, Brent; Bergh, Charles F.; Khanoyan, Garen; Vaughan, Geoffrey M.; Zheng, Jason X.; Villalpando, Carlos Y.; Cheng, Yang; Scharf, Daniel P.;

Mechanisms of β-cell functional adaptation to changes in workload

PubMed Central

Wortham, Matthew; Sander, Maike

2016-01-01

Insulin secretion must be tightly coupled to nutritional state to maintain blood glucose homeostasis. To this end, pancreatic β-cells sense and respond to changes in metabolic conditions, thereby anticipating insulin demands for a given physiological context. This is achieved in part through adjustments of nutrient metabolism, which is controlled at several levels including allosteric regulation, posttranslational modifications, and altered expression of metabolic enzymes. In this review, we discuss mechanisms of β-cell metabolic and functional adaptation in the context of two physiological states that alter glucose-stimulated insulin secretion: fasting and insulin resistance. We review current knowledge of metabolic changes that occur in the β-cell during adaptation and specifically discuss transcriptional mechanisms that underlie β-cell adaptation. A more comprehensive understanding of how β-cells adapt to changes in nutrient state could identify mechanisms to be co-opted for therapeutically modulating insulin secretion in metabolic disease. PMID:27615135

Incoherent feedforward control governs adaptation of activated ras in a eukaryotic chemotaxis pathway.

PubMed

Takeda, Kosuke; Shao, Danying; Adler, Micha; Charest, Pascale G; Loomis, William F; Levine, Herbert; Groisman, Alex; Rappel, Wouter-Jan; Firtel, Richard A

2012-01-03

Adaptation in signaling systems, during which the output returns to a fixed baseline after a change in the input, often involves negative feedback loops and plays a crucial role in eukaryotic chemotaxis. We determined the dynamical response to a uniform change in chemoattractant concentration of a eukaryotic chemotaxis pathway immediately downstream from G protein-coupled receptors. The response of an activated Ras showed near-perfect adaptation, leading us to attempt to fit the results using mathematical models for the two possible simple network topologies that can provide perfect adaptation. Only the incoherent feedforward network accurately described the experimental results. This analysis revealed that adaptation in this Ras pathway is achieved through the proportional activation of upstream components and not through negative feedback loops. Furthermore, these results are consistent with a local excitation, global inhibition mechanism for gradient sensing, possibly with a Ras guanosine triphosphatase-activating protein acting as a global inhibitor.

Methodology of remote sensing data interpretation and geological applications. [Brazil

NASA Technical Reports Server (NTRS)

Parada, N. D. J. (Principal Investigator); Veneziani, P.; Dosanjos, C. E.

1982-01-01

Elements of photointerpretation discussed include the analysis of photographic texture and structure as well as film tonality. The method used is based on conventional techniques developed for interpreting aerial black and white photographs. By defining the properties which characterize the form and individuality of dual images, homologous zones can be identified. Guy's logic method (1966) was adapted and used on functions of resolution, scale, and spectral characteristics of remotely sensed products. Applications of LANDSAT imagery are discussed for regional geological mapping, mineral exploration, hydrogeology, and geotechnical engineering in Brazil.

Sustainable Cooperative Robotic Technologies for Human and Robotic Outpost Infrastructure Construction and Maintenance

NASA Technical Reports Server (NTRS)

Stroupe, Ashley W.; Okon, Avi; Robinson, Matthew; Huntsberger, Terry; Aghazarian, Hrand; Baumgartner, Eric

2004-01-01

Robotic Construction Crew (RCC) is a heterogeneous multi-robot system for autonomous acquisition, transport, and precision mating of components in construction tasks. RCC minimizes resources constrained in a space environment such as computation, power, communication and, sensing. A behavior-based architecture provides adaptability and robustness despite low computational requirements. RCC successfully performs several construction related tasks in an emulated outdoor environment despite high levels of uncertainty in motions and sensing. Quantitative results are provided for formation keeping in component transport, precision instrument placement, and construction tasks.

Constitutional dynamic self-sensing in a zinc(II)/polyiminofluorenes system.

PubMed

Giuseppone, Nicolas; Lehn, Jean-Marie

2004-09-22

The interaction of an external effector, ZnII ions, with a constitutional dynamic library of fluorescent polyiminofluorenes leads to component exchange, which generates an entity responding by a change in emission to the effector that has induced its formation. The overall coupled system displays a tuning of optical signal, resulting from two synergistic processes: adaptative constitutional reorganization and self-sensing. In broader terms, this work highlights the perspectives opened by constitutional dynamic chemistry toward the design of smart materials, capable of expressing different latent properties in response to environmental conditions.

Use of self-actuating and self-sensing cantilevers for imaging biological samples in fluid

PubMed Central

Barbero, R J; Deutschinger, A; Todorov, V; Gray, D S; Belcher, A M; Rangelow, I W; Youcef-Toumi, K

2014-01-01

In this paper, we present a detailed investigation into the suitability of atomic force microscopy (AFM) cantilevers with integrated deflection sensor and micro-actuator for imaging of soft biological samples in fluid. The Si cantilevers are actuated using a micro-heater at the bottom end of the cantilever. Sensing is achieved through p-doped resistors connected in a Wheatstone bridge. We investigated the influence of the water on the cantilever dynamics, the actuation and the sensing mechanisms, as well as the crosstalk between sensing and actuation. Successful imaging of yeast cells in water using the integrated sensor and actuator shows the potential of the combination of this actuation and sensing method. This constitutes a major step towards the automation and miniaturization required to establish AFM in routine biomedical diagnostics and in vivo applications. PMID:19801750

Systems and methods for self-synchronized digital sampling

NASA Technical Reports Server (NTRS)

Samson, Jr., John R. (Inventor)

2008-01-01

Systems and methods for self-synchronized data sampling are provided. In one embodiment, a system for capturing synchronous data samples is provided. The system includes an analog to digital converter adapted to capture signals from one or more sensors and convert the signals into a stream of digital data samples at a sampling frequency determined by a sampling control signal; and a synchronizer coupled to the analog to digital converter and adapted to receive a rotational frequency signal from a rotating machine, wherein the synchronizer is further adapted to generate the sampling control signal, and wherein the sampling control signal is based on the rotational frequency signal.

Multipurpose floating platform for hyperspectral imaging, sampling and sensing of surface water sources used in irrigation and recreation

USDA-ARS?s Scientific Manuscript database

The objective of this work was to design, construct, and test the self-propelled aquatic platform for imaging, multi-tier water sampling, water quality sensing, and depth profiling to document microbial content and environmental covariates in the interior of irrigation ponds and reservoirs. The plat...

Annealing Temperature Dependence of ZnO Nanostructures Grown by Facile Chemical Bath Deposition for EGFET pH Sensors

NASA Astrophysics Data System (ADS)

Bazilah Rosli, Aimi; Awang, Zaiki; Sobihana Shariffudin, Shafinaz; Herman, Sukreen Hana

2018-03-01

Zinc Oxide (ZnO) nanostructures were deposited using chemical bath deposition (CBD) technique in water bath at 95 °C for 4 h. Post-deposition heat treatment in air ambient at various temperature ranging from 200-600 °C for 30 min was applied in order to enhance the electrical properties of ZnO nanostructures as the sensing membrane of extended-gate field effect transistor (EGFET) pH sensor. The as-deposited sample was prepared for comparison. The samples were characterized in terms of physical and sensing properties. FESEM images showed that scattered ZnO nanorods were formed for the as-deposited sample, and the morphology of the ZnO nanorods changed to ZnO nanoflowers when the heat treatment was applied from 200-600 °C. For sensing properties, the samples heated at 300 °C showed the higher sensitivity which was 39.9 mV/pH with the linearity of 0.9792. The sensing properties was increased with the increasing annealing treatment temperature up to 300 °C before decreased drastically.

Multidirectional Image Sensing for Microscopy Based on a Rotatable Robot.

PubMed

Shen, Yajing; Wan, Wenfeng; Zhang, Lijun; Yong, Li; Lu, Haojian; Ding, Weili

2015-12-15

Image sensing at a small scale is essentially important in many fields, including microsample observation, defect inspection, material characterization and so on. However, nowadays, multi-directional micro object imaging is still very challenging due to the limited field of view (FOV) of microscopes. This paper reports a novel approach for multi-directional image sensing in microscopes by developing a rotatable robot. First, a robot with endless rotation ability is designed and integrated with the microscope. Then, the micro object is aligned to the rotation axis of the robot automatically based on the proposed forward-backward alignment strategy. After that, multi-directional images of the sample can be obtained by rotating the robot within one revolution under the microscope. To demonstrate the versatility of this approach, we view various types of micro samples from multiple directions in both optical microscopy and scanning electron microscopy, and panoramic images of the samples are processed as well. The proposed method paves a new way for the microscopy image sensing, and we believe it could have significant impact in many fields, especially for sample detection, manipulation and characterization at a small scale.

Multi-species attributes as the condition for adaptive sampling of rare species using two-stage sequential sampling with an auxiliary variable

USGS Publications Warehouse

Panahbehagh, B.; Smith, D.R.; Salehi, M.M.; Hornbach, D.J.; Brown, D.J.; Chan, F.; Marinova, D.; Anderssen, R.S.

2011-01-01

Assessing populations of rare species is challenging because of the large effort required to locate patches of occupied habitat and achieve precise estimates of density and abundance. The presence of a rare species has been shown to be correlated with presence or abundance of more common species. Thus, ecological community richness or abundance can be used to inform sampling of rare species. Adaptive sampling designs have been developed specifically for rare and clustered populations and have been applied to a wide range of rare species. However, adaptive sampling can be logistically challenging, in part, because variation in final sample size introduces uncertainty in survey planning. Two-stage sequential sampling (TSS), a recently developed design, allows for adaptive sampling, but avoids edge units and has an upper bound on final sample size. In this paper we present an extension of two-stage sequential sampling that incorporates an auxiliary variable (TSSAV), such as community attributes, as the condition for adaptive sampling. We develop a set of simulations to approximate sampling of endangered freshwater mussels to evaluate the performance of the TSSAV design. The performance measures that we are interested in are efficiency and probability of sampling a unit occupied by the rare species. Efficiency measures the precision of population estimate from the TSSAV design relative to a standard design, such as simple random sampling (SRS). The simulations indicate that the density and distribution of the auxiliary population is the most important determinant of the performance of the TSSAV design. Of the design factors, such as sample size, the fraction of the primary units sampled was most important. For the best scenarios, the odds of sampling the rare species was approximately 1.5 times higher for TSSAV compared to SRS and efficiency was as high as 2 (i.e., variance from TSSAV was half that of SRS). We have found that design performance, especially for adaptive designs, is often case-specific. Efficiency of adaptive designs is especially sensitive to spatial distribution. We recommend that simulations tailored to the application of interest are highly useful for evaluating designs in preparation for sampling rare and clustered populations.

Phosphate binding protein as the biorecognition element in a biosensor for phosphate

NASA Technical Reports Server (NTRS)

Salins, Lyndon L E.; Deo, Sapna K.; Daunert, Sylvia

2004-01-01

This work explores the potential use of a member of the periplasmic family of binding proteins, the phosphate binding protein (PBP), as the biorecognition element in a sensing scheme for the detection of inorganic phosphate (Pi). The selectivity of this protein originates from its natural role which, in Escherichia coli, is to serve as the initial receptor for the highly specific translocation of Pi to the cytoplasm. The single polypeptide chain of PBP is folded into two similar domains connected by three short peptide linkages that serve as a hinge. The Pi binding site is located deep within the cleft between the two domains. In the presence of the ligand, the two globular domains engulf the former in a hinge-like manner. The resultant conformational change constitutes the basis of the sensor development. A mutant of PBP (MPBP), where an alanine was replaced by a cysteine residue, was prepared by site-directed mutagenesis using the polymerase chain reaction (PCR). The mutant was expressed, from plasmid pSD501, in the periplasmic space of E. coli and purified in a single chromatographic step on a perfusion anion-exchange column. Site-specific labeling was achieved by attaching the fluorophore, N-[2-(1-maleimidyl)ethyl]-7-(diethylamino)coumarin-3-carboxamide (MDCC), to the protein through the sulfhydryl group of the cysteine moiety. Steady-state fluorescence studies of the MPBP-MDCC conjugate showed a change in the intensity of the signal upon addition of Pi. Calibration curves for Pi were constructed by relating the intensity of the fluorescence signal with the amount of analyte present in the sample. The sensing system was first developed and optimized on a spectrofluorometer using ml volumes of sample. It was then adapted to be used on a microtiter plate arrangement with microliter sample volumes. The system's versatility was finally proven by developing a fiber optic fluorescence-based sensor for monitoring Pi. In all three cases the detection limits for the analyte were in the sub-microMolar range. It was also demonstrated that the sensing system was selective for phosphate over other structurally-similar anions, paving the way for the design and development of a new family of biosensors utilizing the specific binding properties of periplasmic proteins. c2003 Elsevier B.V. All rights reserved.

Research Opportunities from Emerging Atmospheric Observing and Modeling Capabilities.

NASA Astrophysics Data System (ADS)

Dabberdt, Walter F.; Schlatter, Thomas W.

1996-02-01

The Second Prospectus Development Team (PDT-2) of the U.S. Weather Research Program was charged with identifying research opportunities that are best matched to emerging operational and experimental measurement and modeling methods. The overarching recommendation of PDT-2 is that inputs for weather forecast models can best be obtained through the use of composite observing systems together with adaptive (or targeted) observing strategies employing both in situ and remote sensing. Optimal observing systems and strategies are best determined through a three-part process: observing system simulation experiments, pilot field measurement programs, and model-assisted data sensitivity experiments. Furthermore, the mesoscale research community needs easy and timely access to the new operational and research datasets in a form that can readily be reformatted into existing software packages for analysis and display. The value of these data is diminished to the extent that they remain inaccessible.The composite observing system of the future must combine synoptic observations, routine mobile observations, and targeted observations, as the current or forecast situation dictates. High costs demand fuller exploitation of commercial aircraft, meteorological and navigation [Global Positioning System (GPS)] satellites, and Doppler radar. Single observing systems must be assessed in the context of a composite system that provides complementary information. Maintenance of the current North American rawinsonde network is critical for progress in both research-oriented and operational weather forecasting.Adaptive sampling strategies are designed to improve large-scale and regional weather prediction but they will also improve diagnosis and prediction of flash flooding, air pollution, forest fire management, and other environmental emergencies. Adaptive measurements can be made by piloted or unpiloted aircraft. Rawinsondes can be launched and satellites can be programmed to make adaptive observations at special times or in specific regions. PDT-2 specifically recommends the following forms of data gathering: a pilot field and modeling study should be designed and executed to assess the benefit of adaptive observations over the eastern Pacific for mesoscale forecasts over the contiguous United

Development and validation of the Relaxation-Mindfulness Scale for Adolescents (EREMIND-A).

PubMed

López-González, Luis; Amutio, Alberto; Oriol, Xavier; Gázquez, José J; Pérez-Fuentes, Mª C; Molero, Mª M

2018-05-01

The aim of this investigation was to validate the Relaxation-Mindfulness Scale for Adolescents (EREMIND-A), consisting of 18 items and three factors (Attention-Concentration in the present moment; Relaxation (abilities and attitudes); and Sensory awareness/Contemplation/Interiority). The validation was done with a sample of Secondary Education and Baccalaureate students from four different centres in Spain (n = 1.120). EFA and CFA of the EREMIND-A were performed and construct and incremental validities calculated. Initial results confirm the validity and reliability of the scale. There is a need for a broader conceptualization of mindfulness, as well as the inclusion and analysis of other related and cross-cutting concepts. The research in this sense will propitiate the adaptation of the Mindfulness-Based Interventions to the reality of the adolescents in the educational centers, where relaxation and the interiority are aspects to be taken into consideration.

Climate Observing Systems: Where are we and where do we need to be in the future

NASA Astrophysics Data System (ADS)

Baker, B.; Diamond, H. J.

2017-12-01

Climate research and monitoring requires an observational strategy that blends long-term, carefully calibrated measurements as well as short-term, focused process studies. The operation and implementation of operational climate observing networks and the provision of related climate services, both have a significant role to play in assisting the development of national climate adaptation policies and in facilitating national economic development. Climate observing systems will require a strong research element for a long time to come. This requires improved observations of the state variables and the ability to set them in a coherent physical (as well as a chemical and biological) framework with models. Climate research and monitoring requires an integrated strategy of land/ocean/atmosphere observations, including both in situ and remote sensing platforms, and modeling and analysis. It is clear that we still need more research and analysis on climate processes, sampling strategies, and processing algorithms.

Interdisciplinary education approach to the human science

NASA Astrophysics Data System (ADS)

Szu, Harold; Zheng, Yufeng; Zhang, Nian

2012-06-01

We introduced human sciences as components, and integrated them together as an interdisciplinary endeavor over decades. This year, we built a website to maintain systematically the educational research service. We captured the human sciences in various components in the SPIE proceedings over the last decades, which included: (i) ears & eyes like adaptive wavelets, (ii) brain-like unsupervised learning independent component analysis (ICA); (iii) compressive sampling spatiotemporal sparse information processing, (iv) nanoengineering approach to sensing components, (v) systems biology measurements, and (vi) biomedical wellness applications. In order to serve the interdisciplinary community better, our system approach is based on that the former recipients invited the next recipients to deliver their review talks and panel discussions. Since only the former recipients of each component can lead the nomination committees and make the final selections, we also create a leadership award which may be nominated by any conference attendance, to be approved by the conference organization committee.

Development of a luminous textile for reflective pulse oximetry measurements

PubMed Central

Krehel, Marek; Wolf, Martin; Boesel, Luciano F.; Rossi, René M.; Bona, Gian-Luca; Scherer, Lukas J.

2014-01-01

In this paper, a textile-based sensing principle for long term photopletysmography (PPG) monitoring is presented. Optical fibers were embroidered into textiles such that out-coupling and in-coupling of light was possible. The “light-in light-out” properties of the textile enabled the spectroscopic characterization of human tissue. For the optimization of the textile sensor, three different carrier fabrics and different fiber modifications were compared. The sample with best light coupling efficiency was successfully used to measure heart rate and SpO2 values of a subject. The latter was determined by using a modified Beer-Lambert law and measuring the light attenuation at two different wavelengths (632 nm and 894 nm). Moreover, the system was adapted to work in reflection mode which makes the sensor more versatile. The measurements were additionally compared with commercially available system and showed good correlation. PMID:25136484

Broadband Phase Spectroscopy over Turbulent Air Paths

NASA Astrophysics Data System (ADS)

Giorgetta, Fabrizio R.; Rieker, Gregory B.; Baumann, Esther; Swann, William C.; Sinclair, Laura C.; Kofler, Jon; Coddington, Ian; Newbury, Nathan R.

2015-09-01

Broadband atmospheric phase spectra are acquired with a phase-sensitive dual-frequency-comb spectrometer by implementing adaptive compensation for the strong decoherence from atmospheric turbulence. The compensation is possible due to the pistonlike behavior of turbulence across a single spatial-mode path combined with the intrinsic frequency stability and high sampling speed associated with dual-comb spectroscopy. The atmospheric phase spectrum is measured across 2 km of air at each of the 70 000 comb teeth spanning 233 cm-1 across hundreds of near-infrared rovibrational resonances of CO2 , CH4 , and H2O with submilliradian uncertainty, corresponding to a 10-13 refractive index sensitivity. Trace gas concentrations extracted directly from the phase spectrum reach 0.7 ppm uncertainty, demonstrated here for CO2 . While conventional broadband spectroscopy only measures intensity absorption, this approach enables measurement of the full complex susceptibility even in practical open path sensing.

Development of a luminous textile for reflective pulse oximetry measurements.

PubMed

Krehel, Marek; Wolf, Martin; Boesel, Luciano F; Rossi, René M; Bona, Gian-Luca; Scherer, Lukas J

2014-08-01

In this paper, a textile-based sensing principle for long term photopletysmography (PPG) monitoring is presented. Optical fibers were embroidered into textiles such that out-coupling and in-coupling of light was possible. The "light-in light-out" properties of the textile enabled the spectroscopic characterization of human tissue. For the optimization of the textile sensor, three different carrier fabrics and different fiber modifications were compared. The sample with best light coupling efficiency was successfully used to measure heart rate and SpO2 values of a subject. The latter was determined by using a modified Beer-Lambert law and measuring the light attenuation at two different wavelengths (632 nm and 894 nm). Moreover, the system was adapted to work in reflection mode which makes the sensor more versatile. The measurements were additionally compared with commercially available system and showed good correlation.

Taste receptors of the gut: emerging roles in health and disease.

PubMed

Depoortere, Inge

2014-01-01

Recent progress in unravelling the nutrient-sensing mechanisms in the taste buds of the tongue has triggered studies on the existence and role of chemosensory cells in the gut. Indeed, the gastrointestinal tract is the key interface between food and the human body and can sense basic tastes in much the same way as the tongue, through the use of similar G-protein-coupled taste receptors. These receptors 'taste' the luminal content and transmit signals that regulate nutrient transporter expression and nutrient uptake, and also the release of gut hormones and neurotransmitters involved in the regulation of energy and glucose homeostasis. Hence, they play a prominent role in the communication between the lumen, epithelium, smooth muscle cells, afferent nerve fibres and the brain to trigger adaptive responses that affect gastrointestinal function, food intake and glucose metabolism. This review summarises how sensing of nutrients by taste receptors along the gut plays a key role in the process of digestion, and how disturbances or adaptations of these chemosensory signalling pathways may contribute to the induction or resolution of a number of pathological conditions related to diabetes, obesity, or diet-induced symptom generation in irritable bowel syndrome. Targeting these receptors may represent a promising novel route for the treatment of a number of these diseases.

Nutrient sensing signaling integrates nutrient metabolism and intestinal immunity in grass carp, Ctenopharyngodon idellus after prolonged starvation.

PubMed

Li, Shan; Li, Jiabo; Zhao, Yongliang; Zhang, Qin; Wang, Qingchao

2017-12-01

Starvation has been shown to affect growth and nutrient metabolism in fish; however, little information about the nutrient sensing signaling and mucosal adaptive immunity in fish was known. In the present study, grass carp was starved for 8weeks to simulate the natural aquaculture practice in Hubei during winter. The histology of liver was significantly affected with decreased expression of tight junction proteins including claudin-3, claudin-b and ZO-1. Muscle gene expression was also affected, with decreased expression of muscle growth promoting factors such as Myogenin, MyoD, Myf5, and increased expression of muscle degradation factors, such as CathepsinD. In addition, mucosal adaptive immunity was also significantly affected, with decreased expression of antibodies including IgZ and IgM in gut. Along with these changes was the inhibition of several nutrient sensing signaling including MAPK and TOR signaling, which leads to the inhibition of the synthesis of protein including immunoglobulin. The increased phosphorylation of eIF2α not only inhibited the translation, but also resulted in the decreased expression of IkB and increased expression of NF-B, with the activation of pro-inflammatory genes including IL8 and TNF. Copyright © 2017 Elsevier Ltd. All rights reserved.

A wireless batteryless in vivo EKG and core body temperature sensing microsystem with 60 Hz suppression technique for untethered genetically engineered mice real-time monitoring.

PubMed

Chaimanonart, Nattapon; Young, Darrin J

2009-01-01

A wireless, batteryless, and implantable EKG and core body temperature sensing microsystem with adaptive RF powering for untethered genetically engineered mice real-time monitoring is designed, implemented, and in vivo characterized. A packaged microsystem, exhibiting a total size of 9 mm x 7 mm x 3 mm with a weight of 400 mg including a pair of stainless-steel EKG electrodes, is implanted in a mouse abdomen for real-time monitoring. A low power 2 mm x 2 mm ASIC, consisting of an EKG amplifier, a proportional-to-absolute-temperature (PTAT)-based temperature sensor, an RF power sensing circuit, an RF-DC power converter, an 8-bit ADC, digital control circuitry, and a 433 MHz FSK transmitter, is powered by an adaptively controlled external RF energy source at 4 MHz to ensure a stable 2V supply with 156microA current driving capability for the overall microsystem. An electrical model for analyzing 60 Hz interference based on 2-electrode and 3-electrode configurations is proposed and compared with in vivo evaluation results. Due to the small laboratory animal chest area, a 60 Hz suppression technique by employing input termination resistors is chosen for two-EKG-electrode implant configuration.

Evolution of vertebrate mechanosensory hair cells and inner ears: toward identifying stimuli that select mutation driven altered morphologies

PubMed Central

Fritzsch, Bernd; Straka, Hans

2014-01-01

Among the major distance senses of vertebrates, the ear is unique in its complex morphological changes during evolution. Conceivably, these changes enable the ear to adapt toward sensing various physically well-characterized stimuli. This review develops a scenario that integrates sensory cell with organ evolution. We propose that molecular and cellular evolution of the vertebrate hair cells occurred prior to the formation of the vertebrate ear. We previously proposed that the genes driving hair cell differentiation, were aggregated in the otic region through developmental re-patterning that generated a unique vertebrate embryonic structure, the otic placode. In agreement with the presence of graviceptive receptors in many vertebrate outgroups, it is likely that the vertebrate ear originally functioned as a simple gravity-sensing organ. Based on the rare occurrence of angular acceleration receptors in vertebrate outgroups, we further propose that the canal system evolved with a more sophisticated ear morphogenesis. This evolving morphogenesis obviously turned the initial otocyst into a complex set of canals and recesses, harboring multiple sensory epithelia each adapted to the acquisition of a specific aspect of a given physical stimulus. As support for this evolutionary progression, we provide several details of the molecular basis of ear development. PMID:24281353

Molecular mechanisms underlying phosphate sensing, signaling, and adaptation in plants.

PubMed

Zhang, Zhaoliang; Liao, Hong; Lucas, William J

2014-03-01

As an essential plant macronutrient, the low availability of phosphorus (P) in most soils imposes serious limitation on crop production. Plants have evolved complex responsive and adaptive mechanisms for acquisition, remobilization and recycling of phosphate (Pi) to maintain P homeostasis. Spatio-temporal molecular, physiological, and biochemical Pi deficiency responses developed by plants are the consequence of local and systemic sensing and signaling pathways. Pi deficiency is sensed locally by the root system where hormones serve as important signaling components in terms of developmental reprogramming, leading to changes in root system architecture. Root-to-shoot and shoot-to-root signals, delivered through the xylem and phloem, respectively, involving Pi itself, hormones, miRNAs, mRNAs, and sucrose, serve to coordinate Pi deficiency responses at the whole-plant level. A combination of chromatin remodeling, transcriptional and posttranslational events contribute to globally regulating a wide range of Pi deficiency responses. In this review, recent advances are evaluated in terms of progress toward developing a comprehensive understanding of the molecular events underlying control over P homeostasis. Application of this knowledge, in terms of developing crop plants having enhanced attributes for P use efficiency, is discussed from the perspective of agricultural sustainability in the face of diminishing global P supplies. © 2014 Institute of Botany, Chinese Academy of Sciences.

Employment, Sense of Coherence, and Identity Formation: Contextual and Psychological Processes on the Pathway to Sense of Adulthood

ERIC Educational Resources Information Center

Luyckx, Koen; Schwartz, Seth J.; Goossens, Luc; Pollock, Sophie

2008-01-01

The present study investigated the influence of contextual (i.e., being in college vs. being employed) and psychological (i.e., sense of coherence) processes on achieving a sense of adulthood in a sample of 317 emerging adults. Identity formation, conceptualized as multiple dimensions of exploration and of commitment, was conceived of as a…

Solar tomography adaptive optics.

PubMed

Ren, Deqing; Zhu, Yongtian; Zhang, Xi; Dou, Jiangpei; Zhao, Gang

2014-03-10

Conventional solar adaptive optics uses one deformable mirror (DM) and one guide star for wave-front sensing, which seriously limits high-resolution imaging over a large field of view (FOV). Recent progress toward multiconjugate adaptive optics indicates that atmosphere turbulence induced wave-front distortion at different altitudes can be reconstructed by using multiple guide stars. To maximize the performance over a large FOV, we propose a solar tomography adaptive optics (TAO) system that uses tomographic wave-front information and uses one DM. We show that by fully taking advantage of the knowledge of three-dimensional wave-front distribution, a classical solar adaptive optics with one DM can provide an extra performance gain for high-resolution imaging over a large FOV in the near infrared. The TAO will allow existing one-deformable-mirror solar adaptive optics to deliver better performance over a large FOV for high-resolution magnetic field investigation, where solar activities occur in a two-dimensional field up to 60'', and where the near infrared is superior to the visible in terms of magnetic field sensitivity.

BIOMOLECULAR SENSING FOR BIOLOGICAL PROCESSES AND ENVIRONMENTAL MONITORING APPLICATIONS

EPA Science Inventory

Biomolecular recognition is being increasingly employed as the basis for a variety of analytical methods such as biosensors. he sensitivity, selectivity, and format versatility inherent in these methods may allow them to be adapted to solving a number of analytical problems. ltho...

Data processing 1: Advancements in machine analysis of multispectral data

NASA Technical Reports Server (NTRS)

Swain, P. H.

1972-01-01

Multispectral data processing procedures are outlined beginning with the data display process used to accomplish data editing and proceeding through clustering, feature selection criterion for error probability estimation, and sample clustering and sample classification. The effective utilization of large quantities of remote sensing data by formulating a three stage sampling model for evaluation of crop acreage estimates represents an improvement in determining the cost benefit relationship associated with remote sensing technology.

Serenity in political uncertainty.

PubMed

Doumit, Rita; Afifi, Rema A; Devon, Holli A

2015-01-01

College students are often faced with academic and personal stressors that threaten their well-being. Added to that may be political and environmental stressors such as acts of violence on the streets, interruptions in schooling, car bombings, targeted religious intimidations, financial hardship, and uncertainty of obtaining a job after graduation. Research on how college students adapt to the latter stressors is limited. The aims of this study were (1) to investigate the associations between stress, uncertainty, resilience, social support, withdrawal coping, and well-being for Lebanese youth during their first year of college and (2) to determine whether these variables predicted well-being. A sample of 293 first-year students enrolled in a private university in Lebanon completed a self-reported questionnaire in the classroom setting. The mean age of sample participants was 18.1 years, with nearly an equal percentage of males and females (53.2% vs 46.8%), who lived with their family (92.5%), and whose family reported high income levels (68.4%). Multiple regression analyses revealed that best determinants of well-being are resilience, uncertainty, social support, and gender that accounted for 54.1% of the variance. Despite living in an environment of frequent violence and political uncertainty, Lebanese youth in this study have a strong sense of well-being and are able to go on with their lives. This research adds to our understanding on how adolescents can adapt to stressors of frequent violence and political uncertainty. Further research is recommended to understand the mechanisms through which young people cope with political uncertainty and violence.

Multiplatform sampling (ship, aircraft, and satellite) of a Gulf Stream warm core ring

NASA Technical Reports Server (NTRS)

Smith, Raymond C.; Brown, Otis B.; Hoge, Frank E.; Baker, Karen S.; Evans, Robert H.

1987-01-01

The purpose of this paper is to demonstrate the ability to meet the need to measure distributions of physical and biological properties of the ocean over large areas synoptically and over long time periods by means of remote sensing utilizing contemporaneous buoy, ship, aircraft, and satellite (i.e., multiplatform) sampling strategies. A mapping of sea surface temperature and chlorophyll fields in a Gulf Stream warm core ring using the multiplatform approach is described. Sampling capabilities of each sensing system are discussed as background for the data collected by means of these three dissimilar methods. Commensurate space/time sample sets from each sensing system are compared, and their relative accuracies in space and time are determined. The three-dimensional composite maps derived from the data set provide a synoptic perspective unobtainable from single platforms alone.

Scaling up functional traits for ecosystem services with remote sensing: concepts and methods.

PubMed

Abelleira Martínez, Oscar J; Fremier, Alexander K; Günter, Sven; Ramos Bendaña, Zayra; Vierling, Lee; Galbraith, Sara M; Bosque-Pérez, Nilsa A; Ordoñez, Jenny C

2016-07-01

Ecosystem service-based management requires an accurate understanding of how human modification influences ecosystem processes and these relationships are most accurate when based on functional traits. Although trait variation is typically sampled at local scales, remote sensing methods can facilitate scaling up trait variation to regional scales needed for ecosystem service management. We review concepts and methods for scaling up plant and animal functional traits from local to regional spatial scales with the goal of assessing impacts of human modification on ecosystem processes and services. We focus our objectives on considerations and approaches for (1) conducting local plot-level sampling of trait variation and (2) scaling up trait variation to regional spatial scales using remotely sensed data. We show that sampling methods for scaling up traits need to account for the modification of trait variation due to land cover change and species introductions. Sampling intraspecific variation, stratification by land cover type or landscape context, or inference of traits from published sources may be necessary depending on the traits of interest. Passive and active remote sensing are useful for mapping plant phenological, chemical, and structural traits. Combining these methods can significantly improve their capacity for mapping plant trait variation. These methods can also be used to map landscape and vegetation structure in order to infer animal trait variation. Due to high context dependency, relationships between trait variation and remotely sensed data are not directly transferable across regions. We end our review with a brief synthesis of issues to consider and outlook for the development of these approaches. Research that relates typical functional trait metrics, such as the community-weighted mean, with remote sensing data and that relates variation in traits that cannot be remotely sensed to other proxies is needed. Our review narrows the gap between functional trait and remote sensing methods for ecosystem service management.

Asynchronous signal-dependent non-uniform sampler

NASA Astrophysics Data System (ADS)

Can-Cimino, Azime; Chaparro, Luis F.; Sejdić, Ervin

2014-05-01

Analog sparse signals resulting from biomedical and sensing network applications are typically non-stationary with frequency-varying spectra. By ignoring that the maximum frequency of their spectra is changing, uniform sampling of sparse signals collects unnecessary samples in quiescent segments of the signal. A more appropriate sampling approach would be signal-dependent. Moreover, in many of these applications power consumption and analog processing are issues of great importance that need to be considered. In this paper we present a signal dependent non-uniform sampler that uses a Modified Asynchronous Sigma Delta Modulator which consumes low-power and can be processed using analog procedures. Using Prolate Spheroidal Wave Functions (PSWF) interpolation of the original signal is performed, thus giving an asynchronous analog to digital and digital to analog conversion. Stable solutions are obtained by using modulated PSWFs functions. The advantage of the adapted asynchronous sampler is that range of frequencies of the sparse signal is taken into account avoiding aliasing. Moreover, it requires saving only the zero-crossing times of the non-uniform samples, or their differences, and the reconstruction can be done using their quantized values and a PSWF-based interpolation. The range of frequencies analyzed can be changed and the sampler can be implemented as a bank of filters for unknown range of frequencies. The performance of the proposed algorithm is illustrated with an electroencephalogram (EEG) signal.

Effect of adaptation and pulp density on bioleaching of mine waste using indigenous acidophilic bacteria

NASA Astrophysics Data System (ADS)

Cho, K.; Kim, B.; Lee, D.; Choi, N.; Park, C.

2011-12-01

Adaptation to environment is a natural phenomena that takes place in many animals, plants and microorganisms. These adapted organisms achieve stronger applicability than unadapted organisms after habitation in a specific environment for a long time. In the biohydrometallurgical industry, adaptation to special environment conditions by selective culturing is the most popular method for improving bioleaching activity of strains-although that is time consuming. This study investigated the influence of the bioleaching efficiency of mine waste under batch experimental conditions (adaptation and pulp density) using the indigenous acidophilic bacteria collected from acid mine drainage in Go-seong and Yeon-hwa, Korea. We conducted the batch experiments at the influences of parameters, such as the adaptation of bacteria and pulp density of the mine waste. In the adaptation case, the value of pH in 1'st adaptation bacteria sample exhibited lower than in 2'nd adaptation bacteria sample. And the content of both Cu and Zn at 1'st adaptation bacteria sample appeared lower than at 2'nd adaptation bacteria sample. In the SEM analysis, the rod-shaped bacteria with 1μm in length were observed on the filter paper (pore size - 0.45μm). The results of pulp density experiments revealed that the content of both Cu and Zn increased with increasing pulp density, since the increment of pulp density resulted in the enhancement of bioleaching capacity.

How Big Is Big Enough? Sample Size Requirements for CAST Item Parameter Estimation

ERIC Educational Resources Information Center

Chuah, Siang Chee; Drasgow, Fritz; Luecht, Richard

2006-01-01

Adaptive tests offer the advantages of reduced test length and increased accuracy in ability estimation. However, adaptive tests require large pools of precalibrated items. This study looks at the development of an item pool for 1 type of adaptive administration: the computer-adaptive sequential test. An important issue is the sample size required…

Prediction-based manufacturing center self-adaptive demand side energy optimization in cyber physical systems

NASA Astrophysics Data System (ADS)

Sun, Xinyao; Wang, Xue; Wu, Jiangwei; Liu, Youda

2014-05-01

Cyber physical systems(CPS) recently emerge as a new technology which can provide promising approaches to demand side management(DSM), an important capability in industrial power systems. Meanwhile, the manufacturing center is a typical industrial power subsystem with dozens of high energy consumption devices which have complex physical dynamics. DSM, integrated with CPS, is an effective methodology for solving energy optimization problems in manufacturing center. This paper presents a prediction-based manufacturing center self-adaptive energy optimization method for demand side management in cyber physical systems. To gain prior knowledge of DSM operating results, a sparse Bayesian learning based componential forecasting method is introduced to predict 24-hour electric load levels for specific industrial areas in China. From this data, a pricing strategy is designed based on short-term load forecasting results. To minimize total energy costs while guaranteeing manufacturing center service quality, an adaptive demand side energy optimization algorithm is presented. The proposed scheme is tested in a machining center energy optimization experiment. An AMI sensing system is then used to measure the demand side energy consumption of the manufacturing center. Based on the data collected from the sensing system, the load prediction-based energy optimization scheme is implemented. By employing both the PSO and the CPSO method, the problem of DSM in the manufacturing center is solved. The results of the experiment show the self-adaptive CPSO energy optimization method enhances optimization by 5% compared with the traditional PSO optimization method.

An adaptive band selection method for dimension reduction of hyper-spectral remote sensing image

NASA Astrophysics Data System (ADS)

Yu, Zhijie; Yu, Hui; Wang, Chen-sheng

2014-11-01

Hyper-spectral remote sensing data can be acquired by imaging the same area with multiple wavelengths, and it normally consists of hundreds of band-images. Hyper-spectral images can not only provide spatial information but also high resolution spectral information, and it has been widely used in environment monitoring, mineral investigation and military reconnaissance. However, because of the corresponding large data volume, it is very difficult to transmit and store Hyper-spectral images. Hyper-spectral image dimensional reduction technique is desired to resolve this problem. Because of the High relation and high redundancy of the hyper-spectral bands, it is very feasible that applying the dimensional reduction method to compress the data volume. This paper proposed a novel band selection-based dimension reduction method which can adaptively select the bands which contain more information and details. The proposed method is based on the principal component analysis (PCA), and then computes the index corresponding to every band. The indexes obtained are then ranked in order of magnitude from large to small. Based on the threshold, system can adaptively and reasonably select the bands. The proposed method can overcome the shortcomings induced by transform-based dimension reduction method and prevent the original spectral information from being lost. The performance of the proposed method has been validated by implementing several experiments. The experimental results show that the proposed algorithm can reduce the dimensions of hyper-spectral image with little information loss by adaptively selecting the band images.

SEQ-POINTER: Next generation, planetary spacecraft remote sensing science observation design tool

NASA Technical Reports Server (NTRS)

Boyer, Jeffrey S.

1994-01-01

Since Mariner, NASA-JPL planetary missions have been supported by ground software to plan and design remote sensing science observations. The software used by the science and sequence designers to plan and design observations has evolved with mission and technological advances. The original program, PEGASIS (Mariners 4, 6, and 7), was re-engineered as POGASIS (Mariner 9, Viking, and Mariner 10), and again later as POINTER (Voyager and Galileo). Each of these programs were developed under technological, political, and fiscal constraints which limited their adaptability to other missions and spacecraft designs. Implementation of a multi-mission tool, SEQ POINTER, under the auspices of the JPL Multimission Operations Systems Office (MOSO) is in progress. This version has been designed to address the limitations experienced on previous versions as they were being adapted to a new mission and spacecraft. The tool has been modularly designed with subroutine interface structures to support interchangeable celestial body and spacecraft definition models. The computational and graphics modules have also been designed to interface with data collected from previous spacecraft, or on-going observations, which describe the surface of each target body. These enhancements make SEQ POINTER a candidate for low-cost mission usage, when a remote sensing science observation design capability is required. The current and planned capabilities of the tool will be discussed. The presentation will also include a 5-10 minute video presentation demonstrating the capabilities of a proto-Cassini Project version that was adapted to test the tool. The work described in this abstract was performed by the Jet Propulsion Laboratory, California Institute of Technology, under contract to the National Aeronautics and Space Administration.

SEQ-POINTER: Next generation, planetary spacecraft remote sensing science observation design tool

NASA Astrophysics Data System (ADS)

Boyer, Jeffrey S.

1994-11-01

Since Mariner, NASA-JPL planetary missions have been supported by ground software to plan and design remote sensing science observations. The software used by the science and sequence designers to plan and design observations has evolved with mission and technological advances. The original program, PEGASIS (Mariners 4, 6, and 7), was re-engineered as POGASIS (Mariner 9, Viking, and Mariner 10), and again later as POINTER (Voyager and Galileo). Each of these programs were developed under technological, political, and fiscal constraints which limited their adaptability to other missions and spacecraft designs. Implementation of a multi-mission tool, SEQ POINTER, under the auspices of the JPL Multimission Operations Systems Office (MOSO) is in progress. This version has been designed to address the limitations experienced on previous versions as they were being adapted to a new mission and spacecraft. The tool has been modularly designed with subroutine interface structures to support interchangeable celestial body and spacecraft definition models. The computational and graphics modules have also been designed to interface with data collected from previous spacecraft, or on-going observations, which describe the surface of each target body. These enhancements make SEQ POINTER a candidate for low-cost mission usage, when a remote sensing science observation design capability is required. The current and planned capabilities of the tool will be discussed. The presentation will also include a 5-10 minute video presentation demonstrating the capabilities of a proto-Cassini Project version that was adapted to test the tool. The work described in this abstract was performed by the Jet Propulsion Laboratory, California Institute of Technology, under contract to the National Aeronautics and Space Administration.